In [1]:
# Data handling libraries
import pandas as pd
pd.options.display.max_rows = 10000
pd.options.display.max_columns = 10000
import numpy as np
import boto3
import io
import requests as req
# File manipulation libraries
import os
import pickle
# Data visualization libraries
import matplotlib.pyplot as plt
%matplotlib inline
# Initialize S3 client, location of files for this project
s3_client = boto3.client('s3')
s3_resource = boto3.resource('s3')
s3_bucket = "wri-public-data"
s3_folder = "resourcewatch/blog_data/GHG-GDP_Divergence_D3/"
RAW_DATA = s3_folder + "Raw_Data/"
PROCESSED_DATA = s3_folder + "Processed_Data/"
FINAL_DATA = s3_folder + "Final_Data/"
CONVERSIONS = s3_folder + "Conversions/"
# Functions for reading and uploading data to/from S3
def read_from_S3(bucket, key, index_col=0):
obj = s3_client.get_object(Bucket=bucket, Key=key)
df = pd.read_csv(io.BytesIO(obj['Body'].read()), index_col=[index_col], encoding="utf8")
return(df)
def write_to_S3(df, bucket, key):
csv_buffer = io.StringIO()
df.to_csv(csv_buffer)
s3_resource.Object(bucket, key).put(Body=csv_buffer.getvalue())
Load Raw Data from S3
In [2]:
# These four files are derived from the original CDIAC data sheet
# They were initially cleaned (using code outlined at the bottom of this notebook)
# And then uploaded to Amazon S3
file_names = ['Territorial Emissions GCB',
'Consumption Emissions GCB',
'Emissions Transfers GCB',
'Territorial Emissions CDIAC']
# Initialize a dictionary to store the raw data
cdiac_raw_data = {}
# Load each of the raw datasets from S3
# Reference: https://stackoverflow.com/questions/37703634/how-to-import-a-text-file-on-aws-s3-into-pandas-without-writing-to-disk
for file in file_names:
cdiac_raw_data[file] = read_from_S3(s3_bucket, RAW_DATA+file+".csv")
In [144]:
#cdiac_raw_data["Territorial Emissions GCB"].head()
#cdiac_raw_data["Consumption Emissions GCB"].head()
#cdiac_raw_data["Emissions Transfers GCB"].head()
#cdiac_raw_data["Territorial Emissions CDIAC"].head()
Convert raw data to pct_change data for territorial and consumption emissions, load to S3
In [14]:
def add_summary_range(country,row,summ_type,default_start,default_end):
if summ_type == 'absolute':
if country in adjustments:
val = row[adjustments[country]['end']]-row[adjustments[country]['start']]
time = '{}-{}'.format(adjustments[country]['start'],adjustments[country]['end'])
else:
val = row[default_end]-row[default_start]
time = '{}-{}'.format(default_start, default_end)
else:
if country in adjustments:
val = row[adjustments[country]['end']]/row[adjustments[country]['start']] - 1
time = '{}-{}'.format(adjustments[country]['start'],adjustments[country]['end'])
else:
val = row[default_end]/row[default_start] - 1
time = '{}-{}'.format(default_start, default_end)
return(val, time)
adjustments = {
'Eritrea':{
'start':2000,
'end':2011
},
'Maldives':{
'start':2001,
'end':2015
},
'Venezuela, RB':{
'start':2000,
'end':2014
},
'Bermuda':{
'start':2000,
'end':2013
},
'Libya':{
'start':2000,
'end':2011
}
}
# Territory data
territorial_emissions_abs_raw = cdiac_raw_data["Territorial Emissions GCB"]
territory_gcb_abs_val = territorial_emissions_abs_raw.loc[2000:2015].transpose()
territory_gcb_abs_val['Summary Range'], territory_gcb_abs_val["Summary Range Years"] = \
zip(*territory_gcb_abs_val.apply(lambda row: add_summary_range(row.name,row,'absolute',2000,2015),axis=1))
territory_gcb_pct_change = territorial_emissions_abs_raw.loc[1999:2015].transpose().pct_change(axis=1).loc[:,2000:]
territory_gcb_pct_change['Summary Range'], territory_gcb_pct_change["Summary Range Years"] = \
zip(*territory_gcb_abs_val.apply(lambda row: add_summary_range(row.name,row,'percent',2000,2015),axis=1))
territory_gcb_abs_change = territorial_emissions_abs_raw.loc[1999:2015].transpose().diff(periods=1, axis=1).loc[:,2000:]
territory_gcb_abs_change['Summary Range'], territory_gcb_abs_change["Summary Range Years"] = \
zip(*territory_gcb_abs_val.apply(lambda row: add_summary_range(row.name,row,'absolute',2000,2015),axis=1))
adjustments = {
'Eritrea':{
'start':2000,
'end':2011
},
'Maldives':{
'start':2001,
'end':2014
},
'Venezuela, RB':{
'start':2000,
'end':2014
},
'Bermuda':{
'start':2000,
'end':2013
},
'Libya':{
'start':2000,
'end':2011
}
}
# Consumption data
consumption_emissions_abs_raw = cdiac_raw_data["Consumption Emissions GCB"]
consumption_gcb_abs_val = consumption_emissions_abs_raw.loc[2000:2014].transpose()
consumption_gcb_abs_val['Summary Range'], consumption_gcb_abs_val['Summary Range Years'] = \
zip(*consumption_gcb_abs_val.apply(lambda row: add_summary_range(row.name,row,'absolute',2000,2014),axis=1))
consumption_gcb_pct_change = consumption_emissions_abs_raw.loc[1999:2014].transpose().pct_change(axis=1).loc[:,2000:]
consumption_gcb_pct_change['Summary Range'], consumption_gcb_pct_change['Summary Range Years'] = \
zip(*consumption_gcb_abs_val.apply(lambda row: add_summary_range(row.name,row,'percent',2000,2014),axis=1))
consumption_gcb_abs_change = consumption_emissions_abs_raw.loc[1999:2014].transpose().diff(periods=1,axis=1).loc[:,2000:]
consumption_gcb_abs_change['Summary Range'], consumption_gcb_abs_change['Summary Range Years'] = \
zip(*consumption_gcb_abs_val.apply(lambda row: add_summary_range(row.name,row,'absolute',2000,2014),axis=1))
# Upload these percent change figures to S3
write_to_S3(territory_gcb_abs_val, s3_bucket, PROCESSED_DATA + \
"Territorial Emissions GCB absolute values 2000-2015.csv")
write_to_S3(territory_gcb_pct_change, s3_bucket, PROCESSED_DATA + \
"Territorial Emissions GCB percent changes 2000-2015.csv")
write_to_S3(territory_gcb_abs_change, s3_bucket, PROCESSED_DATA + \
"Territorial Emissions GCB absolute changes 2000-2015.csv")
write_to_S3(consumption_gcb_abs_val, s3_bucket, PROCESSED_DATA + \
"Consumption Emissions GCB absolute values 2000-2014.csv")
write_to_S3(consumption_gcb_pct_change, s3_bucket, PROCESSED_DATA + \
"Consumption Emissions GCB percent changes 2000-2014.csv")
write_to_S3(consumption_gcb_abs_change, s3_bucket, PROCESSED_DATA + \
"Consumption Emissions GCB absolute changes 2000-2014.csv")
Download Conversions used to align CDIAC, World Bank, and ISO3 country designations
In [15]:
# CDIAC names to World Bank names
cdiac_to_wb_name_conversion = read_from_S3(s3_bucket, CONVERSIONS+"CDIAC to World Bank name conversion.csv")
# World Bank names to ISO3 codes
wb_name_to_iso3_conversion = read_from_S3(s3_bucket, CONVERSIONS+"World Bank to ISO3 name conversion.csv")
Create final data for the D3 application by adding ISO3 codes to the CDIAC pct change data
In [16]:
# Download pct_change data from S3
territory_gcb_abs_val = read_from_S3(s3_bucket, PROCESSED_DATA+"Territorial Emissions GCB absolute values 2000-2015.csv")
consumption_gcb_abs_val = read_from_S3(s3_bucket, PROCESSED_DATA+"Consumption Emissions GCB absolute values 2000-2015.csv")
territory_gcb_pct_change = read_from_S3(s3_bucket, PROCESSED_DATA+"Territorial Emissions GCB percent changes 2000-2015.csv")
consumption_gcb_pct_change = read_from_S3(s3_bucket, PROCESSED_DATA+"Consumption Emissions GCB percent changes 2000-2015.csv")
territory_gcb_abs_change = read_from_S3(s3_bucket, PROCESSED_DATA+"Territorial Emissions GCB percent changes 2000-2015.csv")
consumption_gcb_abs_change = read_from_S3(s3_bucket, PROCESSED_DATA+"Consumption Emissions GCB percent changes 2000-2015.csv")
dfs = {
"Production CO2 Emissions Absolute Value":territory_gcb_abs_val,
"Consumption CO2 Emissions Absolute Value":consumption_gcb_abs_val,
"Production CO2 Emissions Percent Change":territory_gcb_pct_change,
"Consumption CO2 Emissions Percent Change":consumption_gcb_pct_change,
"Production CO2 Emissions Absolute Change":territory_gcb_abs_change,
"Consumption CO2 Emissions Absolute Change":consumption_gcb_abs_change
}
# Name for Congo didn't match in the CDIAC data and crosswalk file
def replace_congo(name):
if name == "Congo":
return("Congo (Rep)")
else:
return(name)
# Add the wb_name to each dataframe
def fetch_name(name):
try:
return(cdiac_to_wb_name_conversion.loc[name][0])
except:
return(np.nan)
def add_iso(name):
try:
return(wb_name_to_iso3_conversion.loc[name,"ISO"])
except:
return(np.nan)
for df_name, df in dfs.items():
print(df_name)
df.index = list(map(replace_congo, df.index))
df["Country Name"] = list(map(fetch_name, df.index))
df = df.loc[pd.notnull(df["Country Name"])]
df = df.set_index("Country Name")
df["ISO"] = list(map(add_iso, df.index))
df = df.loc[pd.notnull(df["ISO"])]
df["Indicator"] = df_name
dfs[df_name] = df
Production CO2 Emissions Absolute Value
Consumption CO2 Emissions Absolute Value
Production CO2 Emissions Percent Change
Consumption CO2 Emissions Percent Change
Production CO2 Emissions Absolute Change
Consumption CO2 Emissions Absolute Change
In [17]:
# Export final files
write_to_S3(dfs["Production CO2 Emissions Absolute Value"], s3_bucket, FINAL_DATA + "Territory Emissions GCB absolute values with ISO3 2000-2015.csv")
write_to_S3(dfs["Consumption CO2 Emissions Absolute Value"], s3_bucket, FINAL_DATA + "Consumption Emissions GCB absolute values with ISO3 2000-2015.csv")
write_to_S3(dfs["Production CO2 Emissions Percent Change"], s3_bucket, FINAL_DATA + "Territory Emissions GCB percent changes with ISO3 2000-2015 plus summary data.csv")
write_to_S3(dfs["Consumption CO2 Emissions Percent Change"], s3_bucket, FINAL_DATA + "Consumption Emissions GCB percent changes with ISO3 2000-2014 plus summary data.csv")
write_to_S3(dfs["Production CO2 Emissions Absolute Change"], s3_bucket, FINAL_DATA + "Territory Emissions GCB absolute changes with ISO3 2000-2015 plus summary data.csv")
write_to_S3(dfs["Consumption CO2 Emissions Absolute Change"], s3_bucket, FINAL_DATA + "Consumption Emissions GCB absolute changes with ISO3 2000-2014 plus summary data.csv")
In [200]:
# Territory or Consumption?
emissions_type = "Territory"
# absolute values or percent changes?
metric = "absolute values"
df = read_from_S3(s3_bucket, FINAL_DATA + \
"{} Emissions GCB {} with ISO3 2000-2015 plus summary data.csv".format(emissions_type,metric) \
, index_col="ISO")
df
Out[200]:
Country Name
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Summary Range
Summary Range Years
Indicator
ISO
ALB
Albania
0.824000
0.879000
1.023000
1.171000
1.136000
1.160000
1.063000
1.071000
1.193000
1.194000
1.254000
1.429000
1.285000
1.313000
1.308100
1.323801
0.499801
2000-2015
Production CO2 Emissions Absolute Value
DZA
Algeria
23.979000
22.987000
24.776000
25.234000
24.405000
29.214000
27.588000
29.860000
30.079000
33.115000
32.500000
33.048000
35.448000
36.601000
39.257647
40.921606
16.942606
2000-2015
Production CO2 Emissions Absolute Value
AND
Andorra
0.143000
0.143000
0.145000
0.146000
0.154000
0.157000
0.149000
0.147000
0.147000
0.141000
0.141000
0.134000
0.134000
0.134000
0.134952
0.135947
-0.007053
2000-2015
Production CO2 Emissions Absolute Value
AGO
Angola
2.602000
2.654000
3.454000
2.472000
5.125000
5.224000
6.072000
6.859000
7.011000
7.579000
7.924000
8.274000
9.108000
8.853000
8.848174
8.990173
6.388173
2000-2015
Production CO2 Emissions Absolute Value
ATG
Antigua and Barbuda
0.094000
0.094000
0.099000
0.106000
0.111000
0.112000
0.116000
0.128000
0.131000
0.139000
0.143000
0.140000
0.143000
0.143000
0.146480
0.149771
0.055771
2000-2015
Production CO2 Emissions Absolute Value
ARG
Argentina
38.761000
36.466000
34.010000
36.832000
42.975000
44.208000
47.842000
47.771000
51.570000
49.076000
51.246000
52.259000
52.457000
51.764000
52.080937
52.799821
14.038821
2000-2015
Production CO2 Emissions Absolute Value
ARM
Armenia
0.945000
0.966000
0.830000
0.935000
0.994000
1.187000
1.195000
1.381000
1.516000
1.189000
1.150000
1.341000
1.553000
1.499000
1.490023
1.525120
0.580120
2000-2015
Production CO2 Emissions Absolute Value
AUS
Australia
95.492749
97.612808
98.761296
100.531107
104.126436
105.235025
106.750573
108.847285
110.326918
111.476113
110.862716
110.181640
110.934183
108.328039
107.294472
109.099849
13.607100
2000-2015
Production CO2 Emissions Absolute Value
AUT
Austria
18.088085
19.186537
19.685205
21.294747
21.394377
21.721753
20.997530
20.269681
20.214589
18.472359
19.795804
19.194096
18.476708
18.547249
17.538909
18.161297
0.073212
2000-2015
Production CO2 Emissions Absolute Value
AZE
Azerbaijan
8.047000
7.846000
8.076000
8.349000
8.751000
9.364000
10.681000
8.320000
9.682000
8.700000
8.366000
9.121000
9.696000
9.720000
10.174873
10.462132
2.415132
2000-2015
Production CO2 Emissions Absolute Value
BHS
Bahamas, The
0.455000
0.428000
0.430000
0.414000
0.470000
0.475000
0.454000
0.461000
0.408000
0.448000
0.672000
0.520000
0.523000
0.848000
0.867732
0.887198
0.432198
2000-2015
Production CO2 Emissions Absolute Value
BHR
Bahrain
5.084000
3.798000
4.281000
4.491000
4.775000
5.238000
5.135000
7.279000
8.075000
7.446000
7.946000
8.008000
7.932000
8.715000
8.502706
9.044415
3.960415
2000-2015
Production CO2 Emissions Absolute Value
BGD
Bangladesh
7.600000
8.851000
9.192000
9.728000
10.282000
10.766000
11.874000
12.110000
13.515000
14.678000
16.360000
17.336000
18.402000
18.803000
19.572385
20.866106
13.266106
2000-2015
Production CO2 Emissions Absolute Value
BRB
Barbados
0.324000
0.333000
0.335000
0.346000
0.353000
0.369000
0.374000
0.372000
0.442000
0.441000
0.403000
0.417000
0.401000
0.395000
0.404409
0.412691
0.088691
2000-2015
Production CO2 Emissions Absolute Value
BLR
Belarus
14.668000
14.388000
14.291000
14.598000
15.860000
16.135000
16.927000
16.505000
17.209000
16.543000
17.087000
17.359000
17.241000
17.390000
17.573425
16.594135
1.926135
2000-2015
Production CO2 Emissions Absolute Value
BEL
Belgium
34.474675
34.292950
34.392793
34.804582
35.109302
34.147930
33.384169
32.212721
32.850057
29.280170
31.155946
28.642389
27.546833
27.768760
26.289687
27.278434
-7.196241
2000-2015
Production CO2 Emissions Absolute Value
BLZ
Belize
0.113000
0.112000
0.100000
0.105000
0.108000
0.113000
0.118000
0.125000
0.105000
0.118000
0.147000
0.163000
0.131000
0.141000
0.144490
0.147689
0.034689
2000-2015
Production CO2 Emissions Absolute Value
BEN
Benin
0.436000
0.495000
0.567000
0.642000
0.684000
0.653000
1.056000
1.226000
1.203000
1.271000
1.388000
1.447000
1.503000
1.581000
1.571840
1.603080
1.167080
2000-2015
Production CO2 Emissions Absolute Value
BMU
Bermuda
0.127000
0.127000
0.135000
0.128000
0.124000
0.108000
0.142000
0.199000
0.177000
0.124000
0.156000
0.108000
0.121000
0.099000
0.101409
0.103688
-0.023312
2000-2015
Production CO2 Emissions Absolute Value
BTN
Bhutan
0.108000
0.105000
0.114000
0.103000
0.084000
0.108000
0.107000
0.107000
0.115000
0.106000
0.133000
0.200000
0.223000
0.241000
0.252330
0.255200
0.147200
2000-2015
Production CO2 Emissions Absolute Value
BIH
Bosnia and Herzegovina
3.760000
3.644000
3.900000
3.951000
4.257000
4.419000
4.790000
4.814000
5.496000
5.646000
5.802000
6.514000
6.070000
5.974000
5.630224
5.911606
2.151606
2000-2015
Production CO2 Emissions Absolute Value
BWA
Botswana
1.031000
1.050000
1.085000
1.044000
1.063000
1.117000
1.128000
1.154000
1.229000
1.071000
1.308000
1.200000
1.213000
1.479000
1.696881
1.682385
0.651385
2000-2015
Production CO2 Emissions Absolute Value
BRA
Brazil
89.442000
92.019000
90.610000
87.707000
92.126000
94.712000
94.810000
99.049000
105.708000
100.122000
114.468000
119.829000
128.178000
137.354000
143.826163
140.519909
51.077909
2000-2015
Production CO2 Emissions Absolute Value
BRN
Brunei Darussalam
1.285000
1.229000
1.194000
1.252000
1.363000
1.365000
1.326000
2.295000
2.487000
2.144000
2.237000
2.644000
2.632000
2.123000
2.342513
2.490797
1.205797
2000-2015
Production CO2 Emissions Absolute Value
BGR
Bulgaria
12.292803
13.307175
12.547142
13.699928
13.394386
13.674991
14.018200
15.040820
14.625176
12.392713
12.987859
14.444829
13.112765
11.593870
12.304292
13.012168
0.719365
2000-2015
Production CO2 Emissions Absolute Value
BFA
Burkina Faso
0.284000
0.272000
0.274000
0.294000
0.301000
0.307000
0.371000
0.449000
0.523000
0.527000
0.535000
0.603000
0.717000
0.834000
0.829018
0.846011
0.562011
2000-2015
Production CO2 Emissions Absolute Value
BDI
Burundi
0.079000
0.056000
0.058000
0.044000
0.054000
0.042000
0.051000
0.051000
0.052000
0.052000
0.058000
0.066000
0.077000
0.080000
0.082103
0.083064
0.004064
2000-2015
Production CO2 Emissions Absolute Value
KHM
Cambodia
0.539000
0.614000
0.602000
0.649000
0.667000
0.757000
0.818000
0.945000
1.063000
1.269000
1.367000
1.420000
1.488000
1.520000
1.612996
1.629560
1.090560
2000-2015
Production CO2 Emissions Absolute Value
CAN
Canada
156.192791
154.098532
155.530062
160.291124
159.774798
158.085517
156.517268
162.675033
157.599599
148.152145
151.474825
152.334258
153.772820
156.412129
156.686620
152.026836
-4.165955
2000-2015
Production CO2 Emissions Absolute Value
CPV
Cabo Verde
0.051000
0.057000
0.066000
0.084000
0.090000
0.094000
0.102000
0.108000
0.084000
0.090000
0.131000
0.145000
0.135000
0.121000
0.120201
0.122925
0.071925
2000-2015
Production CO2 Emissions Absolute Value
CAF
Central African Republic
0.073000
0.067000
0.067000
0.064000
0.064000
0.064000
0.068000
0.069000
0.069000
0.069000
0.072000
0.076000
0.080000
0.081000
0.080465
0.082289
0.009289
2000-2015
Production CO2 Emissions Absolute Value
TCD
Chad
0.048000
0.047000
0.046000
0.104000
0.103000
0.109000
0.111000
0.126000
0.139000
0.134000
0.141000
0.147000
0.148000
0.166000
0.164905
0.168641
0.120641
2000-2015
Production CO2 Emissions Absolute Value
CHL
Chile
16.039000
14.546000
15.043000
15.163000
16.301000
16.858000
17.675000
19.536000
19.594000
18.218000
19.703000
21.610000
22.082000
22.681000
22.192967
22.091812
6.052812
2000-2015
Production CO2 Emissions Absolute Value
CHN
China
986.700389
1039.178973
1135.073206
1340.506409
1561.958408
1787.329793
1968.347949
2139.695032
2182.653538
2308.501434
2461.433441
2687.342853
2748.313691
2840.614919
2847.688346
2826.710621
1840.010232
2000-2015
Production CO2 Emissions Absolute Value
COL
Colombia
15.796000
15.346000
15.179000
15.659000
15.018000
16.620000
17.164000
17.025000
18.568000
19.815000
20.770000
20.870000
21.782000
24.441000
25.783773
26.934614
11.138614
2000-2015
Production CO2 Emissions Absolute Value
COM
Comoros
0.023000
0.023000
0.024000
0.026000
0.027000
0.028000
0.031000
0.031000
0.032000
0.032000
0.035000
0.041000
0.040000
0.044000
0.043710
0.044700
0.021700
2000-2015
Production CO2 Emissions Absolute Value
COG
Congo, Rep.
0.286000
0.209000
0.157000
0.250000
0.259000
0.268000
0.305000
0.331000
0.357000
0.465000
0.525000
0.609000
0.650000
0.677000
0.688615
0.720296
0.434296
2000-2015
Production CO2 Emissions Absolute Value
CRI
Costa Rica
1.493000
1.571000
1.725000
1.807000
1.890000
1.873000
1.936000
2.215000
2.217000
2.155000
2.064000
2.111000
2.118000
2.077000
2.129269
2.170394
0.677394
2000-2015
Production CO2 Emissions Absolute Value
CIV
Cote d'Ivoire
1.852000
2.107000
1.987000
1.489000
2.090000
2.134000
1.908000
1.848000
1.848000
1.543000
1.681000
1.745000
2.288000
2.451000
2.573308
2.775501
0.923501
2000-2015
Production CO2 Emissions Absolute Value
HRV
Croatia
5.400961
5.715914
6.012862
6.374242
6.278721
6.400613
6.464229
6.810965
6.472539
5.994988
5.781580
5.626212
5.124558
5.010781
4.805492
4.900968
-0.499994
2000-2015
Production CO2 Emissions Absolute Value
CUB
Cuba
7.113000
6.941000
7.115000
6.950000
6.819000
7.092000
7.474000
7.307000
8.302000
8.153000
10.465000
9.814000
9.860000
10.728000
11.000645
11.229179
4.116179
2000-2015
Production CO2 Emissions Absolute Value
CYP
Cyprus
1.948561
1.911001
1.963130
2.069570
2.131813
2.172954
2.224887
2.308444
2.352551
2.284864
2.184658
2.100526
1.954339
1.760213
1.877274
1.889565
-0.058996
2000-2015
Production CO2 Emissions Absolute Value
CZE
Czech Republic
33.774000
33.739000
32.656000
33.286000
31.845000
32.754000
33.299000
33.625000
31.824000
29.358000
30.428000
29.154000
27.553000
26.905000
26.222670
26.255132
-7.518868
2000-2015
Production CO2 Emissions Absolute Value
ZAR
Congo, Dem. Rep.
0.222000
0.228000
0.253000
0.269000
0.327000
0.409000
0.435000
0.472000
0.499000
0.469000
0.543000
0.673000
0.698000
0.758000
0.752961
0.769216
0.547216
2000-2015
Production CO2 Emissions Absolute Value
DNK
Denmark
14.996180
15.412461
15.311976
16.718973
15.208639
14.233851
16.396125
15.089760
14.159137
13.484032
13.604108
12.252355
10.978607
11.515257
10.378265
9.550526
-5.445654
2000-2015
Production CO2 Emissions Absolute Value
DJI
Djibouti
0.093000
0.100000
0.109000
0.115000
0.111000
0.113000
0.112000
0.126000
0.136000
0.126000
0.141000
0.129000
0.141000
0.166000
0.165037
0.168323
0.075323
2000-2015
Production CO2 Emissions Absolute Value
DMA
Dominica
0.028000
0.030000
0.028000
0.032000
0.031000
0.032000
0.031000
0.042000
0.036000
0.036000
0.038000
0.035000
0.037000
0.036000
0.036876
0.037705
0.009705
2000-2015
Production CO2 Emissions Absolute Value
DOM
Dominican Republic
5.397000
5.404000
5.817000
5.867000
4.993000
5.083000
5.395000
5.774000
5.845000
5.607000
5.904000
6.022000
6.203000
6.019000
6.242362
6.335794
0.938794
2000-2015
Production CO2 Emissions Absolute Value
ECU
Ecuador
5.650000
6.304000
6.804000
7.354000
7.921000
8.253000
7.870000
8.696000
9.236000
9.809000
10.383000
10.810000
11.037000
11.870000
12.262382
12.006210
6.356210
2000-2015
Production CO2 Emissions Absolute Value
EGY
Egypt, Arab Rep.
38.540000
34.211000
34.686000
40.350000
41.154000
45.598000
48.701000
51.566000
54.155000
56.377000
55.281000
59.221000
59.195000
58.089000
58.425611
59.657438
21.117438
2000-2015
Production CO2 Emissions Absolute Value
SLV
El Salvador
1.566000
1.622000
1.647000
1.787000
1.736000
1.760000
1.867000
1.903000
1.785000
1.757000
1.732000
1.813000
1.963000
1.734000
1.771569
1.807112
0.241112
2000-2015
Production CO2 Emissions Absolute Value
GNQ
Equatorial Guinea
0.124000
0.844000
1.358000
1.641000
1.423000
1.285000
1.297000
1.308000
1.228000
1.260000
1.276000
1.846000
1.590000
1.476000
1.592322
1.747356
1.623356
2000-2015
Production CO2 Emissions Absolute Value
ERI
Eritrea
0.166000
0.172000
0.165000
0.198000
0.210000
0.209000
0.153000
0.158000
0.113000
0.140000
0.140000
0.162000
0.180000
0.182000
0.181030
0.184338
0.018338
2000-2015
Production CO2 Emissions Absolute Value
EST
Estonia
4.132475
4.228674
4.099423
4.594218
4.654769
4.457078
4.290264
5.118900
4.711932
3.862720
4.867298
5.035461
4.722881
5.340166
5.163405
5.418496
1.286021
2000-2015
Production CO2 Emissions Absolute Value
ETH
Ethiopia
0.968000
1.187000
1.233000
1.360000
1.444000
1.396000
1.501000
1.640000
1.794000
1.808000
1.796000
2.107000
2.335000
2.900000
2.961878
2.996029
2.028029
2000-2015
Production CO2 Emissions Absolute Value
FSM
Micronesia, Fed. Sts.
0.037000
0.048000
0.040000
0.040000
0.040000
0.033000
0.034000
0.039000
0.033000
0.046000
0.033000
0.035000
0.039000
0.040000
0.042697
0.043151
0.006151
2000-2015
Production CO2 Emissions Absolute Value
FJI
Fiji
0.236000
0.304000
0.228000
0.235000
0.309000
0.372000
0.371000
0.328000
0.137000
0.291000
0.436000
0.434000
0.435000
0.466000
0.496196
0.501304
0.265304
2000-2015
Production CO2 Emissions Absolute Value
FIN
Finland
15.549495
17.042205
17.725564
19.793283
18.783246
15.532837
18.614057
18.158221
15.955686
15.184384
17.420311
15.414505
13.914649
14.147024
12.990648
11.987580
-3.561915
2000-2015
Production CO2 Emissions Absolute Value
FRA
France
112.940920
113.100582
111.849425
114.231943
114.473064
115.869257
112.893375
110.363248
108.575190
103.651589
106.283207
99.116276
99.767568
99.597048
91.522767
92.765113
-20.175807
2000-2015
Production CO2 Emissions Absolute Value
GAB
Gabon
1.280000
1.309000
1.247000
1.266000
1.278000
1.333000
1.138000
1.123000
1.136000
1.181000
1.237000
1.219000
1.249000
1.297000
1.322564
1.370837
0.090837
2000-2015
Production CO2 Emissions Absolute Value
GMB
Gambia, The
0.075000
0.077000
0.086000
0.086000
0.088000
0.088000
0.092000
0.108000
0.112000
0.119000
0.129000
0.119000
0.129000
0.134000
0.133254
0.136418
0.061418
2000-2015
Production CO2 Emissions Absolute Value
GEO
Georgia
1.237000
1.028000
0.924000
1.029000
1.179000
1.382000
1.677000
1.751000
1.409000
1.613000
1.515000
1.877000
2.006000
2.048000
2.020984
2.069268
0.832268
2000-2015
Production CO2 Emissions Absolute Value
DEU
Germany
245.416012
249.878408
245.380116
245.715858
241.891129
236.329700
239.459024
232.191510
232.858592
215.168449
227.134174
221.735674
222.977601
228.096506
216.391534
217.881997
-27.534015
2000-2015
Production CO2 Emissions Absolute Value
GHA
Ghana
1.715000
1.887000
2.024000
2.081000
2.004000
1.907000
2.552000
2.680000
2.492000
2.102000
2.715000
2.681000
3.239000
3.987000
3.986100
4.090842
2.375842
2000-2015
Production CO2 Emissions Absolute Value
GRC
Greece
28.116721
28.768370
28.671252
29.783452
29.904766
30.900607
30.507026
31.148350
30.091639
28.376033
26.483374
25.683118
24.757253
22.628446
21.732608
20.701510
-7.415210
2000-2015
Production CO2 Emissions Absolute Value
GRL
Greenland
0.145000
0.147000
0.147000
0.145000
0.159000
0.166000
0.171000
0.174000
0.180000
0.157000
0.181000
0.193000
0.155000
0.155000
0.158771
0.162340
0.017340
2000-2015
Production CO2 Emissions Absolute Value
GRD
Grenada
0.052000
0.053000
0.056000
0.059000
0.056000
0.059000
0.063000
0.065000
0.069000
0.069000
0.071000
0.069000
0.074000
0.083000
0.085020
0.086930
0.034930
2000-2015
Production CO2 Emissions Absolute Value
GTM
Guatemala
2.704000
2.898000
3.026000
2.953000
3.169000
3.428000
3.449000
3.443000
3.117000
3.232000
3.181000
3.228000
3.265000
3.708000
3.833895
3.898924
1.194924
2000-2015
Production CO2 Emissions Absolute Value
GIN
Guinea
0.349000
0.354000
0.361000
0.366000
0.366000
0.322000
0.322000
0.330000
0.597000
0.616000
0.710000
0.758000
0.704000
0.627000
0.623199
0.636163
0.287163
2000-2015
Production CO2 Emissions Absolute Value
GNB
Guinea-Bissau
0.040000
0.041000
0.042000
0.053000
0.055000
0.058000
0.059000
0.063000
0.062000
0.064000
0.065000
0.067000
0.069000
0.070000
0.069538
0.071114
0.031114
2000-2015
Production CO2 Emissions Absolute Value
GUY
Guyana
0.439000
0.435000
0.431000
0.427000
0.444000
0.392000
0.352000
0.426000
0.425000
0.427000
0.469000
0.486000
0.544000
0.528000
0.540847
0.553002
0.114002
2000-2015
Production CO2 Emissions Absolute Value
HTI
Haiti
0.373000
0.428000
0.498000
0.473000
0.542000
0.566000
0.576000
0.652000
0.654000
0.619000
0.580000
0.605000
0.632000
0.656000
0.670964
0.685122
0.312122
2000-2015
Production CO2 Emissions Absolute Value
HND
Honduras
1.372000
1.558000
1.661000
1.846000
2.009000
2.060000
1.911000
2.394000
2.365000
2.147000
2.175000
2.442000
2.450000
2.472000
2.549319
2.595094
1.223094
2000-2015
Production CO2 Emissions Absolute Value
HKG
Hong Kong SAR, China
11.028000
10.351000
10.809000
11.824000
11.374000
11.964000
11.469000
11.923000
11.993000
11.495000
11.115000
11.943000
11.848000
12.270000
12.138279
12.967427
1.939427
2000-2015
Production CO2 Emissions Absolute Value
HUN
Hungary
15.921618
16.374382
16.093949
16.857762
16.438772
16.465476
16.307787
15.944061
15.645514
14.091346
14.221859
13.720760
12.766088
11.989868
11.892306
12.457695
-3.463923
2000-2015
Production CO2 Emissions Absolute Value
ISL
Iceland
0.744797
0.739709
0.763075
0.762206
0.774298
0.763459
0.802204
0.883432
0.973583
0.961215
0.923459
0.900264
0.898083
0.901145
0.893070
0.924175
0.179377
2000-2015
Production CO2 Emissions Absolute Value
IND
India
281.389000
283.925000
287.499000
299.863000
314.786000
333.396000
355.527000
383.858000
427.701000
474.133000
468.964000
503.617000
550.451000
554.882000
589.953591
620.723220
339.334220
2000-2015
Production CO2 Emissions Absolute Value
IDN
Indonesia
71.835000
80.422000
83.648000
86.390000
92.074000
93.262000
94.115000
102.412000
113.597000
121.737000
116.924000
156.362000
163.496000
130.724000
141.694058
146.616740
74.781740
2000-2015
Production CO2 Emissions Absolute Value
IRQ
Iraq
19.756000
23.273000
23.796000
24.848000
31.111000
30.958000
26.935000
16.950000
25.402000
28.510000
30.596000
36.523000
41.727000
45.763000
46.571128
46.880320
27.124320
2000-2015
Production CO2 Emissions Absolute Value
IRL
Ireland
12.315321
12.959258
12.541684
12.432948
12.566158
13.087392
12.938310
12.962098
12.875420
11.461879
11.342324
10.342575
10.379809
10.111742
9.977912
10.166216
-2.149104
2000-2015
Production CO2 Emissions Absolute Value
IRN
Iran, Islamic Rep.
101.576000
108.715000
109.624000
114.164000
121.965000
127.895000
138.959000
152.959000
158.698000
161.285000
165.044000
168.848000
175.583000
168.251000
174.113901
176.715588
75.139588
2000-2015
Production CO2 Emissions Absolute Value
ISR
Israel
16.433000
17.343000
16.311000
17.150000
16.095000
15.531000
17.036000
17.200000
18.616000
17.581000
18.784000
18.852000
20.597000
19.382000
18.784113
19.579393
3.146393
2000-2015
Production CO2 Emissions Absolute Value
ITA
Italy
126.958262
128.581953
129.231457
133.623228
134.483148
133.983150
132.804057
130.523393
127.711134
114.323438
117.052315
113.673454
106.261125
98.816498
93.566233
98.640130
-28.318132
2000-2015
Production CO2 Emissions Absolute Value
JAM
Jamaica
2.811000
2.895000
2.793000
2.909000
2.910000
2.863000
3.135000
2.632000
2.784000
2.111000
1.979000
2.106000
1.998000
2.107000
2.163385
2.207309
-0.603691
2000-2015
Production CO2 Emissions Absolute Value
JPN
Japan
347.788752
343.172642
353.274890
354.664467
354.376061
356.424351
350.758143
360.207203
337.187721
317.305183
331.050826
344.394907
353.762652
357.944637
345.384992
337.698995
-10.089757
2000-2015
Production CO2 Emissions Absolute Value
JOR
Jordan
4.229000
4.364000
4.605000
4.764000
5.247000
5.743000
5.760000
6.009000
5.822000
5.970000
5.776000
5.909000
6.779000
6.765000
6.959052
6.991164
2.762164
2000-2015
Production CO2 Emissions Absolute Value
KAZ
Kazakhstan
37.720475
35.743455
40.568084
44.979633
47.152969
50.575149
56.459506
58.104320
57.892713
56.670922
63.511742
61.071098
61.888628
63.873215
66.551439
64.223050
26.502575
2000-2015
Production CO2 Emissions Absolute Value
KEN
Kenya
2.841000
2.555000
2.173000
1.842000
2.079000
2.335000
2.611000
2.681000
2.793000
3.368000
3.320000
3.670000
3.413000
3.627000
3.706983
3.752594
0.911594
2000-2015
Production CO2 Emissions Absolute Value
KIR
Kiribati
0.009000
0.007000
0.011000
0.011000
0.012000
0.017000
0.019000
0.014000
0.015000
0.011000
0.017000
0.017000
0.017000
0.017000
0.018146
0.018339
0.009339
2000-2015
Production CO2 Emissions Absolute Value
KWT
Kuwait
14.606000
15.719000
15.879000
16.341000
17.326000
19.511000
20.117000
20.517000
22.561000
23.808000
24.441000
24.824000
27.583000
26.714000
26.720925
27.729798
13.123798
2000-2015
Production CO2 Emissions Absolute Value
KGZ
Kyrgyz Republic
1.264000
1.062000
1.352000
1.483000
1.602000
1.470000
1.448000
1.547000
2.089000
1.852000
1.741000
2.088000
2.760000
2.684000
2.618417
2.689473
1.425473
2000-2015
Production CO2 Emissions Absolute Value
LAO
Lao PDR
0.256000
0.238000
0.314000
0.300000
0.380000
0.383000
0.423000
0.248000
0.258000
0.343000
0.447000
0.443000
0.589000
0.593000
0.617539
0.626533
0.370533
2000-2015
Production CO2 Emissions Absolute Value
LVA
Latvia
1.929511
2.042798
2.050671
2.104393
2.107259
2.127856
2.263531
2.351552
2.234947
2.031523
2.327548
2.124854
2.047128
2.001090
1.948420
1.979287
0.049777
2000-2015
Production CO2 Emissions Absolute Value
LBN
Lebanon
4.158000
4.410000
4.364000
4.958000
4.581000
4.420000
3.943000
3.677000
4.699000
5.694000
5.469000
5.577000
6.174000
6.158000
6.330575
6.330937
2.172937
2000-2015
Production CO2 Emissions Absolute Value
LBR
Liberia
0.116000
0.135000
0.134000
0.143000
0.168000
0.199000
0.204000
0.183000
0.154000
0.141000
0.217000
0.244000
0.281000
0.261000
0.259443
0.264754
0.148754
2000-2015
Production CO2 Emissions Absolute Value
LBY
Libya
12.848000
13.117000
13.044000
13.408000
13.733000
14.210000
14.527000
13.624000
15.124000
15.997000
16.730000
10.742000
14.289000
13.919000
14.172383
14.794847
1.946847
2000-2015
Production CO2 Emissions Absolute Value
LTU
Lithuania
3.221060
3.413746
3.442802
3.440294
3.598661
3.806464
3.903666
4.264213
4.083858
3.473559
3.716952
3.798858
3.814280
3.544710
3.475109
3.489385
0.268325
2000-2015
Production CO2 Emissions Absolute Value
LUX
Luxembourg
2.406964
2.546813
2.753485
2.856108
3.245612
3.316097
3.278395
3.115435
3.072716
2.931269
3.082511
3.051279
2.970066
2.812577
2.682841
2.718884
0.311920
2000-2015
Production CO2 Emissions Absolute Value
MAC
Macao SAR, China
0.446000
0.460000
0.416000
0.419000
0.471000
0.501000
0.445000
0.421000
0.625000
0.722000
0.541000
0.643000
0.620000
0.591000
0.631902
0.640174
0.194174
2000-2015
Production CO2 Emissions Absolute Value
MKD
Macedonia, FYR
3.290000
3.272000
2.982000
3.084000
3.052000
3.076000
2.983000
2.589000
2.564000
2.372000
2.346000
2.560000
2.444000
2.262000
2.164947
2.250890
-1.039110
2000-2015
Production CO2 Emissions Absolute Value
MDG
Madagascar
0.511000
0.475000
0.337000
0.464000
0.493000
0.475000
0.459000
0.495000
0.515000
0.483000
0.534000
0.631000
0.727000
0.839000
0.945305
0.940653
0.429653
2000-2015
Production CO2 Emissions Absolute Value
MWI
Malawi
0.244000
0.243000
0.241000
0.261000
0.266000
0.250000
0.260000
0.256000
0.299000
0.274000
0.325000
0.324000
0.308000
0.347000
0.365579
0.368374
0.124374
2000-2015
Production CO2 Emissions Absolute Value
MYS
Malaysia
34.288000
36.984000
36.472000
43.157000
44.676000
47.583000
45.733000
50.400000
55.640000
54.214000
59.579000
60.105000
59.642000
64.497000
65.205853
67.886433
33.598433
2000-2015
Production CO2 Emissions Absolute Value
MDV
Maldives
0.123000
0.126000
0.162000
0.138000
0.182000
0.164000
0.207000
0.213000
0.230000
0.241000
0.245000
0.260000
0.294000
0.286000
0.305281
0.308531
0.185531
2000-2015
Production CO2 Emissions Absolute Value
MLI
Mali
0.224000
0.226000
0.231000
0.230000
0.239000
0.245000
0.257000
0.275000
0.292000
0.220000
0.263000
0.285000
0.271000
0.280000
0.278152
0.284454
0.060454
2000-2015
Production CO2 Emissions Absolute Value
MLT
Malta
0.658920
0.696126
0.672547
0.727657
0.710902
0.746810
0.757728
0.772828
0.770307
0.732675
0.734312
0.760343
0.782925
0.675785
0.677821
0.682836
0.023916
2000-2015
Production CO2 Emissions Absolute Value
MHL
Marshall Islands
0.021000
0.022000
0.023000
0.023000
0.024000
0.023000
0.025000
0.027000
0.027000
0.028000
0.028000
0.028000
0.028000
0.028000
0.029888
0.030206
0.009206
2000-2015
Production CO2 Emissions Absolute Value
MRT
Mauritania
0.320000
0.347000
0.368000
0.379000
0.419000
0.433000
0.439000
0.503000
0.528000
0.579000
0.610000
0.653000
0.724000
0.722000
0.717816
0.732086
0.412086
2000-2015
Production CO2 Emissions Absolute Value
MUS
Mauritius
0.734000
0.781000
0.787000
0.835000
0.843000
0.899000
0.990000
1.006000
1.028000
1.008000
1.068000
1.069000
1.110000
1.016000
1.174684
1.163372
0.429372
2000-2015
Production CO2 Emissions Absolute Value
MEX
Mexico
104.311000
107.891000
106.861000
110.695000
112.290000
118.745000
121.432000
125.134000
129.395000
122.875000
121.397000
127.292000
131.138000
133.243000
131.168560
128.822497
24.511497
2000-2015
Production CO2 Emissions Absolute Value
MNG
Mongolia
2.047000
2.150000
2.260000
2.191000
2.332000
2.335000
2.562000
3.290000
3.283000
3.573000
6.725000
7.522000
8.925000
11.342000
12.039260
12.343542
10.296542
2000-2015
Production CO2 Emissions Absolute Value
MNE
Montenegro
0.474291
0.509627
0.544837
0.582582
0.636559
0.693578
0.650000
0.614000
0.750000
0.498000
0.704000
0.701000
0.637000
0.613000
0.585690
0.610330
0.136039
2000-2015
Production CO2 Emissions Absolute Value
MAR
Morocco
9.246000
10.285000
10.432000
10.243000
11.811000
12.482000
12.933000
13.708000
14.426000
14.312000
15.260000
15.731000
17.105000
15.969000
17.091290
17.267704
8.021704
2000-2015
Production CO2 Emissions Absolute Value
MOZ
Mozambique
0.368000
0.431000
0.433000
0.523000
0.524000
0.497000
0.540000
0.617000
0.618000
0.690000
0.746000
0.879000
0.851000
1.096000
1.106006
1.140225
0.772225
2000-2015
Production CO2 Emissions Absolute Value
MMR
Myanmar
2.751000
2.379000
2.511000
2.685000
3.391000
3.163000
3.504000
3.511000
2.673000
2.790000
3.413000
3.899000
3.527000
3.437000
3.724696
3.862725
1.111725
2000-2015
Production CO2 Emissions Absolute Value
NAM
Namibia
0.448000
0.550000
0.480000
0.511000
0.535000
0.630000
0.635000
0.644000
0.908000
0.837000
0.845000
0.770000
0.920000
0.804000
0.809806
0.823703
0.375703
2000-2015
Production CO2 Emissions Absolute Value
NPL
Nepal
0.837000
0.891000
0.716000
0.775000
0.728000
0.841000
0.699000
0.713000
0.933000
1.182000
1.379000
1.509000
1.594000
1.773000
1.864304
1.884674
1.047674
2000-2015
Production CO2 Emissions Absolute Value
NLD
Netherlands
46.959556
48.318068
48.161136
49.090581
49.548651
48.455369
47.154174
47.264853
48.082538
46.614672
49.817082
46.340649
45.214253
45.162632
43.064842
44.310334
-2.649222
2000-2015
Production CO2 Emissions Absolute Value
NZL
New Zealand
8.830774
9.438243
9.489159
9.961018
9.842703
10.274409
10.239930
10.003104
10.282219
9.499564
9.557107
9.379526
9.721896
9.578135
9.720793
9.708202
0.877428
2000-2015
Production CO2 Emissions Absolute Value
NIC
Nicaragua
1.026000
1.081000
1.101000
1.203000
1.207000
1.178000
1.218000
1.256000
1.206000
1.226000
1.237000
1.331000
1.275000
1.246000
1.274006
1.300502
0.274502
2000-2015
Production CO2 Emissions Absolute Value
NER
Niger
0.190000
0.179000
0.191000
0.207000
0.222000
0.195000
0.189000
0.197000
0.221000
0.264000
0.320000
0.362000
0.509000
0.535000
0.565266
0.570112
0.380112
2000-2015
Production CO2 Emissions Absolute Value
NGA
Nigeria
21.590000
22.727000
26.756000
25.397000
26.463000
28.549000
26.968000
25.922000
26.220000
20.926000
25.093000
26.205000
27.171000
26.084000
27.002547
28.476011
6.886011
2000-2015
Production CO2 Emissions Absolute Value
NOR
Norway
11.515724
11.880279
11.641613
11.982998
12.095797
11.885159
11.984918
12.511409
12.251934
11.793146
12.508702
12.266611
12.159378
12.092611
11.972556
12.001086
0.485362
2000-2015
Production CO2 Emissions Absolute Value
OMN
Oman
5.971000
5.532000
6.946000
8.833000
7.632000
8.152000
10.800000
11.916000
11.646000
12.024000
13.737000
15.330000
16.145000
16.685000
16.342672
17.267459
11.296459
2000-2015
Production CO2 Emissions Absolute Value
PAK
Pakistan
29.029000
29.529000
31.111000
32.423000
35.888000
37.261000
39.835000
43.331000
43.379000
43.315000
44.013000
44.180000
44.467000
41.824000
44.298749
46.752676
17.723676
2000-2015
Production CO2 Emissions Absolute Value
PLW
Palau
0.031000
0.049000
0.049000
0.051000
0.051000
0.052000
0.055000
0.057000
0.057000
0.057000
0.059000
0.061000
0.061000
0.061000
0.065112
0.065806
0.034806
2000-2015
Production CO2 Emissions Absolute Value
PAN
Panama
1.579000
1.911000
1.601000
1.678000
1.583000
1.865000
2.010000
1.963000
2.011000
2.345000
2.499000
2.754000
2.750000
2.826000
2.931153
2.978976
1.399976
2000-2015
Production CO2 Emissions Absolute Value
PNG
Papua New Guinea
0.727000
0.875000
0.951000
1.076000
1.224000
1.196000
1.175000
1.669000
1.308000
1.389000
1.272000
1.426000
1.358000
1.656000
1.771599
1.796232
1.069232
2000-2015
Production CO2 Emissions Absolute Value
PRY
Paraguay
1.006000
1.042000
1.063000
1.110000
1.115000
1.045000
1.087000
1.128000
1.214000
1.232000
1.390000
1.451000
1.420000
1.356000
1.386853
1.416042
0.410042
2000-2015
Production CO2 Emissions Absolute Value
PER
Peru
8.262000
7.408000
7.414000
7.194000
8.698000
10.127000
9.511000
11.714000
11.185000
14.100000
15.706000
13.535000
14.868000
15.586000
15.889004
16.472963
8.210963
2000-2015
Production CO2 Emissions Absolute Value
PHL
Philippines
19.991000
19.376000
19.454000
19.507000
20.198000
20.407000
18.460000
19.681000
21.505000
21.153000
23.158000
23.339000
24.903000
26.790000
28.437831
30.918010
10.927010
2000-2015
Production CO2 Emissions Absolute Value
BOL
Bolivia
2.788000
2.679000
2.609000
3.853000
3.568000
3.323000
4.106000
3.363000
3.610000
3.815000
4.146000
4.403000
5.125000
5.373000
5.551822
5.621119
2.833119
2000-2015
Production CO2 Emissions Absolute Value
POL
Poland
87.096180
86.046423
83.934400
87.399064
88.504217
88.256708
91.839678
91.776231
89.884872
86.227611
91.164344
91.079053
89.136952
88.002316
84.690856
86.196701
-0.899480
2000-2015
Production CO2 Emissions Absolute Value
PRT
Portugal
17.948733
17.879288
18.899734
17.481627
18.211898
18.896185
17.635886
16.907763
16.335000
15.567261
14.309373
13.933189
13.479439
12.959145
12.886167
13.841428
-4.107305
2000-2015
Production CO2 Emissions Absolute Value
QAT
Qatar
9.471000
11.289000
11.155000
11.323000
11.711000
13.896000
17.310000
17.256000
17.683000
18.877000
19.803000
21.935000
25.668000
23.186000
22.071376
24.784421
15.313421
2000-2015
Production CO2 Emissions Absolute Value
CMR
Cameroon
0.936000
0.933000
0.932000
1.035000
1.079000
1.008000
1.053000
1.591000
1.512000
1.834000
1.849000
1.573000
1.671000
1.858000
1.880101
1.952893
1.016893
2000-2015
Production CO2 Emissions Absolute Value
KOR
Korea, Rep.
122.051000
122.769000
126.979000
127.138000
131.518000
126.240000
128.349000
135.172000
138.421000
138.768000
154.545000
160.731000
159.280000
161.576000
161.364540
161.615942
39.564942
2000-2015
Production CO2 Emissions Absolute Value
SDN
Sudan
1.383394
1.592416
2.029712
2.268070
2.865799
2.745703
3.003313
3.531368
3.728472
3.890739
3.985165
3.914575
3.998000
4.212000
4.187345
4.271432
2.888038
2000-2015
Production CO2 Emissions Absolute Value
ROM
Romania
25.680647
27.157752
27.226178
28.556319
28.252800
27.626675
28.655521
28.196880
27.283603
23.041044
21.788759
23.144829
22.689601
20.026970
20.023152
20.488454
-5.192193
2000-2015
Production CO2 Emissions Absolute Value
RUS
Russian Federation
410.628518
421.085694
418.003643
428.189901
430.012223
435.131473
451.333707
451.291528
459.988549
430.417157
453.865016
468.783032
471.581820
454.977025
456.315998
441.407001
30.778484
2000-2015
Production CO2 Emissions Absolute Value
RWA
Rwanda
0.144000
0.145000
0.145000
0.142000
0.144000
0.144000
0.144000
0.152000
0.148000
0.157000
0.161000
0.181000
0.201000
0.218000
0.215660
0.220229
0.076229
2000-2015
Production CO2 Emissions Absolute Value
STP
Sao Tome and Principe
0.013000
0.014000
0.016000
0.018000
0.020000
0.021000
0.023000
0.023000
0.023000
0.025000
0.027000
0.028000
0.031000
0.031000
0.030795
0.031493
0.018493
2000-2015
Production CO2 Emissions Absolute Value
SAU
Saudi Arabia
80.975000
81.051000
89.012000
89.248000
107.945000
108.438000
118.009000
105.748000
117.310000
127.834000
141.956000
136.550000
154.349000
147.649000
156.923615
163.900631
82.925631
2000-2015
Production CO2 Emissions Absolute Value
SEN
Senegal
1.074000
1.181000
1.230000
1.357000
1.427000
1.585000
1.290000
1.413000
1.389000
1.250000
2.112000
2.282000
2.158000
2.297000
2.369522
2.391468
1.317468
2000-2015
Production CO2 Emissions Absolute Value
SRB
Serbia
10.746709
11.547373
12.345163
13.200418
14.423441
15.715422
14.728000
14.305000
14.208000
12.594000
12.524000
13.415000
12.016000
12.236000
11.599671
12.143812
1.397103
2000-2015
Production CO2 Emissions Absolute Value
SYC
Seychelles
0.156000
0.173000
0.147000
0.150000
0.201000
0.188000
0.200000
0.175000
0.189000
0.202000
0.188000
0.163000
0.192000
0.176000
0.174839
0.178800
0.022800
2000-2015
Production CO2 Emissions Absolute Value
SLE
Sierra Leone
0.116000
0.155000
0.166000
0.178000
0.175000
0.149000
0.200000
0.175000
0.181000
0.178000
0.198000
0.245000
0.281000
0.325000
0.323139
0.329486
0.213486
2000-2015
Production CO2 Emissions Absolute Value
SGP
Singapore
13.364000
13.510000
12.880000
8.490000
7.765000
8.279000
8.399000
5.434000
9.854000
10.095000
11.984000
10.452000
14.897000
13.787000
14.377520
15.026088
1.662088
2000-2015
Production CO2 Emissions Absolute Value
SVK
Slovak Republic
11.232263
11.863563
11.351947
11.479408
11.620349
11.621458
11.550351
11.114984
11.254455
10.216548
10.476513
10.338661
9.789273
9.660250
9.112289
9.319817
-1.912446
2000-2015
Production CO2 Emissions Absolute Value
SVN
Slovenia
4.219474
4.471822
4.510457
4.445793
4.541258
4.622905
4.675164
4.714077
4.972634
4.456389
4.466002
4.461856
4.312278
4.134477
3.681763
3.786500
-0.432974
2000-2015
Production CO2 Emissions Absolute Value
SLB
Solomon Islands
0.040000
0.042000
0.042000
0.044000
0.044000
0.044000
0.044000
0.048000
0.050000
0.052000
0.053000
0.054000
0.054000
0.054000
0.057640
0.058254
0.018254
2000-2015
Production CO2 Emissions Absolute Value
ZAF
South Africa
103.263000
101.457000
97.256000
110.297000
122.767000
113.694000
122.142000
127.471000
135.695000
137.241000
129.288000
129.544000
128.735000
128.508000
131.120033
126.141427
22.878427
2000-2015
Production CO2 Emissions Absolute Value
ESP
Spain
85.043593
85.260754
90.666169
91.886578
96.471783
100.640030
98.270561
100.243527
91.701639
80.954692
77.396670
77.488722
76.372901
68.848169
69.177652
74.383415
-10.660178
2000-2015
Production CO2 Emissions Absolute Value
LKA
Sri Lanka
2.792000
2.848000
3.015000
3.021000
3.354000
3.300000
3.266000
3.369000
3.329000
3.593000
3.733000
4.154000
4.425000
4.370000
4.633638
4.688064
1.896064
2000-2015
Production CO2 Emissions Absolute Value
KNA
St. Kitts and Nevis
0.050000
0.050000
0.054000
0.060000
0.062000
0.064000
0.064000
0.068000
0.068000
0.071000
0.071000
0.073000
0.076000
0.076000
0.077849
0.079599
0.029599
2000-2015
Production CO2 Emissions Absolute Value
VCT
St. Vincent and the Grenadines
0.040000
0.049000
0.051000
0.054000
0.060000
0.060000
0.060000
0.062000
0.062000
0.085000
0.060000
0.054000
0.069000
0.057000
0.058387
0.059699
0.019699
2000-2015
Production CO2 Emissions Absolute Value
SUR
Suriname
0.627000
0.674000
0.461000
0.461000
0.455000
0.460000
0.497000
0.515000
0.541000
0.562000
0.716000
0.592000
0.684000
0.573000
0.586759
0.599672
-0.027328
2000-2015
Production CO2 Emissions Absolute Value
SWZ
Swaziland
0.324000
0.312000
0.307000
0.284000
0.281000
0.278000
0.277000
0.290000
0.299000
0.285000
0.283000
0.286000
0.329000
0.297000
0.333486
0.332225
0.008225
2000-2015
Production CO2 Emissions Absolute Value
SWE
Sweden
14.937343
15.198348
15.456304
15.612336
15.400874
14.699565
14.655474
14.440973
13.873247
12.900504
14.480823
13.409822
12.707325
12.254135
11.846316
11.609315
-3.328028
2000-2015
Production CO2 Emissions Absolute Value
CHE
Switzerland
11.884814
12.282281
11.837878
12.169209
12.322507
12.494020
12.377503
11.834166
12.193489
11.874751
12.289046
11.182628
11.528808
11.785387
10.716444
11.002684
-0.882130
2000-2015
Production CO2 Emissions Absolute Value
TJK
Tajikistan
0.610000
0.625000
0.513000
0.566000
0.699000
0.666000
0.725000
0.882000
0.792000
0.669000
0.694000
0.641000
0.833000
0.978000
0.963394
0.984940
0.374940
2000-2015
Production CO2 Emissions Absolute Value
THA
Thailand
49.433000
53.068000
56.810000
61.242000
66.318000
67.485000
69.545000
69.622000
69.637000
73.744000
78.699000
79.177000
83.235000
82.661000
84.431519
85.233024
35.800024
2000-2015
Production CO2 Emissions Absolute Value
TGO
Togo
0.371000
0.317000
0.336000
0.399000
0.381000
0.365000
0.333000
0.384000
0.459000
0.759000
0.712000
0.657000
0.590000
0.608000
0.605096
0.615000
0.244000
2000-2015
Production CO2 Emissions Absolute Value
TON
Tonga
0.026000
0.024000
0.028000
0.032000
0.030000
0.031000
0.035000
0.031000
0.033000
0.036000
0.032000
0.028000
0.049000
0.057000
0.060843
0.061490
0.035490
2000-2015
Production CO2 Emissions Absolute Value
TTO
Trinidad and Tobago
6.516000
6.857000
7.424000
7.609000
8.403000
8.048000
12.662000
13.145000
12.718000
12.237000
13.065000
12.790000
12.373000
12.692000
12.523152
12.346807
5.830807
2000-2015
Production CO2 Emissions Absolute Value
TUN
Tunisia
5.433000
5.677000
5.689000
5.794000
6.081000
6.180000
6.270000
6.575000
6.770000
6.760000
7.543000
7.096000
7.364000
7.545000
7.961044
8.593519
3.160519
2000-2015
Production CO2 Emissions Absolute Value
TUR
Turkey
63.468665
59.353030
61.780953
65.748489
69.097183
76.181971
82.477062
90.929699
88.301459
84.765475
87.433586
92.274675
99.106443
96.878014
104.315885
105.434953
41.966288
2000-2015
Production CO2 Emissions Absolute Value
TKM
Turkmenistan
10.237000
10.383000
10.899000
12.163000
12.692000
13.182000
13.502000
15.283000
15.498000
13.728000
15.623000
17.069000
17.724000
18.242000
21.016225
24.764827
14.527827
2000-2015
Production CO2 Emissions Absolute Value
UGA
Uganda
0.390000
0.412000
0.425000
0.436000
0.474000
0.592000
0.692000
0.788000
0.870000
0.922000
1.069000
1.163000
1.114000
1.335000
1.373342
1.387830
0.997830
2000-2015
Production CO2 Emissions Absolute Value
UKR
Ukraine
74.080178
79.359910
76.948512
77.980480
80.991739
83.881409
88.860978
90.089315
86.534892
73.580355
78.360700
82.225301
80.705804
78.448800
67.565835
54.996826
-19.083352
2000-2015
Production CO2 Emissions Absolute Value
ARE
United Arab Emirates
30.696000
27.656000
23.099000
29.136000
30.881000
31.674000
33.781000
36.986000
42.911000
45.803000
43.854000
43.519000
47.002000
46.120000
46.284954
48.169493
17.473493
2000-2015
Production CO2 Emissions Absolute Value
GBR
United Kingdom
153.188009
155.757923
151.263001
154.332839
154.639237
153.871053
153.406958
151.124438
147.357031
133.464110
138.535948
126.879298
132.201990
129.866826
118.666637
113.755112
-39.432898
2000-2015
Production CO2 Emissions Absolute Value
TZA
Tanzania
0.723000
0.853000
0.979000
1.038000
1.190000
1.501000
1.644000
1.608000
1.675000
1.614000
1.938000
2.207000
2.603000
2.932000
3.009124
3.137720
2.414720
2000-2015
Production CO2 Emissions Absolute Value
USA
United States
1635.490721
1608.750819
1620.016103
1632.720797
1664.022380
1671.055404
1649.125000
1670.757096
1616.594159
1497.903930
1552.608079
1517.332969
1459.940229
1501.787937
1516.377456
1477.501915
-157.988805
2000-2015
Production CO2 Emissions Absolute Value
URY
Uruguay
1.447000
1.388000
1.260000
1.254000
1.530000
1.575000
1.813000
1.637000
2.259000
2.202000
1.740000
2.117000
2.371000
2.074000
2.122665
2.166809
0.719809
2000-2015
Production CO2 Emissions Absolute Value
UZB
Uzbekistan
33.013000
33.597000
34.927000
33.700000
32.813000
30.782000
31.489000
31.506000
32.481000
29.215000
28.407000
31.002000
31.583000
28.150000
29.222975
29.834931
-3.178069
2000-2015
Production CO2 Emissions Absolute Value
VUT
Vanuatu
0.023000
0.024000
0.023000
0.023000
0.016000
0.016000
0.013000
0.027000
0.026000
0.033000
0.033000
0.036000
0.031000
0.029000
0.030955
0.031285
0.008285
2000-2015
Production CO2 Emissions Absolute Value
VEN
Venezuela, RB
41.566000
47.065000
52.718000
52.387000
41.378000
45.022000
46.227000
43.847000
48.845000
49.029000
51.560000
48.761000
54.170000
50.595000
49.576528
47.688261
6.122261
2000-2015
Production CO2 Emissions Absolute Value
VNM
Vietnam
14.629000
16.673000
19.309000
21.480000
24.693000
26.764000
28.019000
28.599000
32.177000
36.792000
40.180000
44.147000
43.150000
41.621000
45.960524
50.275780
35.646780
2000-2015
Production CO2 Emissions Absolute Value
YEM
Yemen, Rep.
3.992000
4.432000
4.299000
4.719000
5.149000
5.466000
5.671000
5.719000
6.092000
6.698000
6.390000
5.363000
4.988000
6.912000
7.081961
7.124621
3.132621
2000-2015
Production CO2 Emissions Absolute Value
ZMB
Zambia
0.497000
0.520000
0.541000
0.576000
0.585000
0.624000
0.572000
0.485000
0.595000
0.689000
0.739000
0.800000
0.949000
1.043000
1.099214
1.106203
0.609203
2000-2015
Production CO2 Emissions Absolute Value
ZWE
Zimbabwe
3.797000
3.435000
3.263000
2.906000
2.587000
2.937000
2.849000
2.696000
2.119000
2.273000
2.527000
3.171000
3.527000
3.758000
4.634124
4.529074
0.732074
2000-2015
Production CO2 Emissions Absolute Value
WLD
World
6785.099389
6974.110973
7073.644206
7473.479409
7854.862408
8233.377793
8526.107949
8775.553032
8963.833538
8871.867434
9207.411441
9543.422853
9686.631691
9821.560919
9890.947818
9896.706046
3111.606657
2000-2015
Production CO2 Emissions Absolute Value
Process GDP and other WB indicator Data
In [18]:
adjustments = {
'Eritrea':{
'start':'2000',
'end':'2011'
},
'Maldives':{
'start':'2001',
'end':'2015'
},
'Venezuela, RB':{
'start':'2000',
'end':'2014'
},
'Bermuda':{
'start':'2000',
'end':'2013'
},
'Libya':{
'start':'2000',
'end':'2011'
}
}
res = req.get("http://api.worldbank.org/countries/all/indicators/NY.GDP.MKTP.KD?date=1999:2016&format=json&per_page=10000")
data = pd.io.json.json_normalize(res.json()[1])
data = data[["country.value", "date", "value"]]
value_name = 'GDP Absolute Value'
data.columns = ["Country Name", "Year", value_name]
data = data.pivot(index="Country Name", columns="Year", values=value_name).astype(float)
data["ISO"] = list(map(add_iso, data.index))
data = data.loc[pd.notnull(data["ISO"])]
data["Indicator"] = value_name
# Absolute values
data['Summary Range'], data['Summary Range Years'] = zip(*data.apply(lambda row: add_summary_range(row.name,row,'absolute','2000','2015'),axis=1))
# Setting up to calculate changes & their summary ranges
wbg_gdp_data = data.copy()
year_cols = [str(yr) for yr in range(1999,2016)]
# Percent changes
data2 = data.loc[:,year_cols].pct_change(axis=1).loc[:,year_cols[1:]]
data2["Indicator"] = "GDP Percent Change"
data2["ISO"] = list(map(add_iso, data2.index))
data2['Summary Range'], data2['Summary Range Years'] = zip(*data.apply(lambda row: add_summary_range(row.name,row,'percent','2000','2015'),axis=1))
wbg_gdp_data = wbg_gdp_data.append(data2)
# Absolute changes
data3 = data.loc[:,year_cols].diff(periods=1,axis=1).loc[:,year_cols[1:]]
data3["Indicator"] = "GDP Absolute Change"
data3["ISO"] = list(map(add_iso, data3.index))
data3['Summary Range'], data3['Summary Range Years'] = zip(*data.apply(lambda row: add_summary_range(row.name,row,'absolute','2000','2015'),axis=1))
wbg_gdp_data = wbg_gdp_data.append(data3)
# Clean up
wbg_gdp_data.index.name = "Country Name"
wbg_gdp_data = wbg_gdp_data.drop(["1999", "2016"], axis=1)
In [19]:
wbg_gdp_data.loc['Libya']
Out[19]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
ISO
Indicator
Summary Range
Summary Range Years
Country Name
Libya
4.802634e+10
4.717970e+10
4.672732e+10
5.280934e+10
5.516550e+10
6.171405e+10
6.572580e+10
6.990091e+10
7.176542e+10
7.119837e+10
7.477344e+10
2.835714e+10
NaN
NaN
NaN
NaN
LBY
GDP Absolute Value
-1.966920e+10
2000-2011
Libya
3.679213e-02
-1.762878e-02
-9.588494e-03
1.301600e-01
4.461630e-02
1.187073e-01
6.500547e-02
6.352317e-02
2.667356e-02
-7.901418e-03
5.021290e-02
-6.207592e-01
NaN
NaN
NaN
NaN
LBY
GDP Percent Change
-4.095503e-01
2000-2011
Libya
1.704287e+09
-8.466459e+08
-4.523822e+08
6.082028e+09
2.356158e+09
6.548547e+09
4.011751e+09
4.175111e+09
1.864506e+09
-5.670486e+08
3.575076e+09
-4.641630e+10
NaN
NaN
NaN
NaN
LBY
GDP Absolute Change
-1.966920e+10
2000-2011
In [20]:
write_to_S3(wbg_gdp_data, s3_bucket, FINAL_DATA + "World Bank GDP Data with ISO3, 2000-2015 with Summary Values.csv")
In [21]:
production_co2_emissions_absolute_value = read_from_S3(s3_bucket, FINAL_DATA+"Territory Emissions GCB absolute values with ISO3 2000-2015.csv")
consumption_co2_emissions_absolute_value = read_from_S3(s3_bucket, FINAL_DATA+"Consumption Emissions GCB absolute values with ISO3 2000-2015.csv")
production_co2_emissions_pct_change = read_from_S3(s3_bucket, FINAL_DATA+"Territory Emissions GCB percent changes with ISO3 2000-2015 plus summary data.csv")
consumption_co2_emissions_pct_change = read_from_S3(s3_bucket, FINAL_DATA+"Consumption Emissions GCB percent changes with ISO3 2000-2014 plus summary data.csv")
production_co2_emissions_abs_change = read_from_S3(s3_bucket, FINAL_DATA+"Territory Emissions GCB absolute changes with ISO3 2000-2015 plus summary data.csv")
consumption_co2_emissions_abs_change = read_from_S3(s3_bucket, FINAL_DATA+"Consumption Emissions GCB absolute changes with ISO3 2000-2014 plus summary data.csv")
gdp_data = read_from_S3(s3_bucket, FINAL_DATA + "World Bank GDP Data with ISO3, 2000-2015 with Summary Values.csv")
dsets = [production_co2_emissions_absolute_value, consumption_co2_emissions_absolute_value,
production_co2_emissions_pct_change, consumption_co2_emissions_pct_change,
production_co2_emissions_abs_change, consumption_co2_emissions_abs_change,
gdp_data]
In [22]:
keep_these_countries = production_co2_emissions_pct_change.reset_index().set_index("ISO").index
def make_one_file(dsets):
df = dsets[0].reset_index().set_index("ISO").loc[keep_these_countries].reset_index()
print(df.shape)
for i in range(1, len(dsets)):
df = df.append(dsets[i].reset_index().set_index("ISO").loc[keep_these_countries].reset_index())
print(df.shape)
return(df)
final_data = make_one_file(dsets)
(183, 21)
(366, 21)
(549, 21)
(732, 21)
(915, 21)
(1098, 21)
(1647, 21)
In [23]:
# Write to S3
write_to_S3(final_data, s3_bucket, FINAL_DATA + \
"All Data Together.csv")
final_data.to_csv("/Users/nathansuberi/Documents/GitHub/nsuberi.github.io/wri-ghg/final-data/All Data Together Concise.csv")
In [6]:
# Read final data
final_data = read_from_S3(s3_bucket, FINAL_DATA + \
"All Data Together.csv")
final_data.head()
Out[6]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Country Name
ISO
Indicator
Summary Range
Summary Range Years
0
0.824
0.879
1.023
1.171
1.136
1.160
1.063
1.071
1.193
1.194
1.254
1.429
1.285
1.313
1.308100
1.323801
Albania
ALB
Production CO2 Emissions Absolute Value
0.499801
2000-2015
1
23.979
22.987
24.776
25.234
24.405
29.214
27.588
29.860
30.079
33.115
32.500
33.048
35.448
36.601
39.257647
40.921606
Algeria
DZA
Production CO2 Emissions Absolute Value
16.942606
2000-2015
2
0.143
0.143
0.145
0.146
0.154
0.157
0.149
0.147
0.147
0.141
0.141
0.134
0.134
0.134
0.134952
0.135947
Andorra
AND
Production CO2 Emissions Absolute Value
-0.007053
2000-2015
3
2.602
2.654
3.454
2.472
5.125
5.224
6.072
6.859
7.011
7.579
7.924
8.274
9.108
8.853
8.848174
8.990173
Angola
AGO
Production CO2 Emissions Absolute Value
6.388173
2000-2015
4
0.094
0.094
0.099
0.106
0.111
0.112
0.116
0.128
0.131
0.139
0.143
0.140
0.143
0.143
0.146480
0.149771
Antigua and Barbuda
ATG
Production CO2 Emissions Absolute Value
0.055771
2000-2015
In [7]:
final_data['Indicator'].unique()
Out[7]:
array(['Production CO2 Emissions Absolute Value',
'Consumption CO2 Emissions Absolute Value', nan,
'Production CO2 Emissions Percent Change',
'Consumption CO2 Emissions Percent Change',
'Production CO2 Emissions Absolute Change',
'Consumption CO2 Emissions Absolute Change', 'GDP Absolute Value',
'GDP Percent Change', 'GDP Absolute Change'], dtype=object)
In [18]:
import math
countries = final_data['ISO'].unique()
cntry_data = final_data.set_index('ISO')
for cntry in countries:
data = cntry_data.loc[cntry]
x = data.loc[data['Indicator']=='Production CO2 Emissions Percent Change', 'Summary Range'].values
y = data.loc[data['Indicator']=='GDP Percent Change', 'Summary Range'].values
print(x,y)
deg = math.atan(y/x)*180/math.pi
if(x>0):
if(deg>=-45):
deg = deg - 45
else:
deg = -135 - deg
else:
deg = -1*deg
if(deg<=45):
deg = deg + 45
else:
deg = 135 - deg
print(cntry, deg)
[ 0.60655503] [ 0.80493138]
ALB 8.000194039993765
[ 0.70656017] [ 0.71858514]
DZA 0.48343404923929256
[-0.04931959] [ 0.22125593]
AND 57.566213048230594
[ 2.45510098] [ 2.00908822]
AGO -5.7054318693906865
[ 0.59331214] [ 0.27428638]
ATG -20.189044409357702
[ 0.36218934] [ 0.50200817]
ARG 9.190268843467216
[ 0.61388324] [ 1.66292521]
ARM 24.737938524422304
[ 0.14249354] [ 0.54310439]
AUS 30.29873917211559
[ 0.00404754] [ 0.22370868]
AUT 43.963466585089904
[ 0.30012825] [ 3.48979911]
AZE 40.08456696879668
[ 0.94988671] [ 0.05913363]
BHS -41.437742563474345
[ 0.77899581] [ 1.01747939]
BHR 7.561849151106628
[ 1.74554027] [ 1.33728481]
BGD -7.543728253334571
[ 0.2737368] [ 0.11947036]
BRB -21.421501049337483
[ 0.13131543] [ 1.16631544]
BLR 38.57612217047033
[-0.20873992] [ 0.23388059]
BEL 86.74911531779301
[ 0.30698464] [ 0.68280292]
BLZ 20.791564125564392
[ 2.67678957] [ 0.83677657]
BEN -27.640518721281175
[-0.22047244] [ 0.04155454]
BMU 55.67386189398175
[ 1.36296361] [ 2.00464604]
BTN 10.78812274416891
[ 0.57223553] [ 0.62252704]
BIH 2.4103460161300987
[ 0.63179874] [ 0.88545541]
BWA 9.491014523823516
[ 0.57107297] [ 0.51551437]
BRA -2.9270577387714383
[ 0.93836375] [ 0.13921358]
BRN -36.56127696161784
[ 0.05851921] [ 0.66728128]
BGR 39.98809941801997
[ 1.97891025] [ 1.31597542]
BFA -11.376091764215097
[ 0.05144443] [ 0.58145577]
BDI 39.943908136895445
[ 2.02330174] [ 2.05406363]
KHM 0.43226271558206975
[-0.02667188] [ 0.33784169]
CAN 49.514016468445845
[ 1.41029144] [ 0.89022693]
CPV -12.738398281105965
[ 0.12724034] [-0.07443302]
CAF -75.32676839970487
[ 2.51334837] [ 2.46213811]
TCD -0.5896966708078466
[ 0.37738085] [ 0.83214597]
CHL 20.605556234714115
[ 1.8648115] [ 2.98210997]
CHN 12.980902550763446
[ 0.7051541] [ 0.86564171]
COL 5.833645938687965
[ 0.9434761] [ 0.36773562]
COM -23.7058166746485
[ 1.51851752] [ 0.91605682]
COG -13.899211773167835
[ 0.45371304] [ 0.84918712]
CRI 16.88481091634894
[ 0.49865056] [ 0.522986]
CIV 1.3645307420088315
[-0.09257491] [ 0.25217872]
HRV 65.1582073632035
[ 0.57868401] [ 0.90731182]
CUB 12.470245274724583
[-0.03027673] [ 0.24018684]
CYP 52.18451950938544
[-0.22262297] [ 0.48504392]
CZE 69.6539331677933
[ 2.46493702] [ 1.29539169]
ZAR -17.276848355990108
[-0.36313607] [ 0.14286285]
DNK 66.47537593029872
[ 0.80992003] [ 0.90367623]
DJI 3.1317086045951825
[ 0.34659547] [ 0.27691104]
DMA -6.377036009882396
[ 0.17394733] [ 1.06452952]
DOM 35.71971319910017
[ 1.12499294] [ 0.86009422]
ECU -7.600894600752248
[ 0.54793561] [ 0.83304075]
EGY 11.664934211269347
[ 0.1539665] [ 0.32624087]
SLV 19.73544580049972
[ 13.09157948] [ 3.88799706]
GNQ -28.459393064276895
[-0.02409639] [ 0.1863825]
ERI 52.366599832822104
[ 0.31119886] [ 0.65196187]
EST 19.483607579950316
[ 2.09507124] [ 2.72217553]
ETH 7.416996513655057
[ 0.16624873] [ 0.01950331]
FSM -38.30898458087732
[ 1.12417055] [ 0.39699895]
FJI -25.54941180001485
[-0.2290695] [ 0.17993434]
FIN 83.14967288458294
[-0.17864037] [ 0.18370199]
FRA 89.19967723159559
[ 0.07096652] [ 0.48442091]
GAB 36.66558942571389
[ 0.81890248] [ 0.62450471]
GMB -7.670428212533523
[ 0.67281179] [ 1.32632955]
GEO 18.102528721045907
[-0.11219323] [ 0.18748633]
DEU 75.89661907850808
[ 1.38533046] [ 1.53347795]
GHA 2.905620128964138
[-0.26372956] [-0.02556675]
GRC 39.46287415712891
[ 0.11958321] [ 0.28513078]
GRL 22.246932940848055
[ 0.67173498] [ 0.389559]
GRD -14.889285098980451
[ 0.44190961] [ 0.67576816]
GTM 11.817853480790589
[ 0.82281658] [ 0.69393798]
GIN -4.85675507707564
[ 0.77783893] [ 0.51097015]
GNB -11.698689073688612
[ 0.25968536] [ 0.59602533]
GUY 21.457475304849012
[ 0.83678687] [ 0.18936891]
HTI -32.248477850527834
[ 0.89146774] [ 0.77893979]
HND -3.8539399374124343
[ 0.17586393] [ 0.72361067]
HKG 31.339867536689027
[-0.217561] [ 0.34429104]
HUN 77.28920717514727
[ 0.24084042] [ 0.472346]
ISL 17.983813598840236
[ 1.20592568] [ 1.86684526]
IND 12.138760518748136
[ 1.04102096] [ 1.17930808]
IDN 3.5639074559566097
[ 1.37296619] [ 0.87894508]
IRQ -12.373453276543337
[-0.17450657] [ 0.93440387]
IRL 55.57853129291554
[ 0.73973761] [ 0.54133125]
IRN -8.803774834793721
[ 0.19146798] [ 0.59079058]
ISR 27.04312691821606
[-0.22305072] [ 0.00177828]
ITA 45.4567821452616
[-0.21476018] [ 0.10330076]
JAM 70.6877962562623
[-0.02901117] [ 0.11912831]
JPN 58.6867491386557
[ 0.65314819] [ 1.10644799]
JOR 14.446187844929177
[ 0.70260451] [ 1.78619342]
KAZ 23.527656831917284
[ 0.32087098] [ 0.99753902]
KEN 27.168959614096536
[ 1.0376957] [ 0.30531508]
KIR -28.604846101333685
[ 0.89852104] [ 0.87957422]
KWT -0.6105025462691955
[ 1.1277477] [ 0.89790776]
KGZ -6.473350645352866
[ 1.44739594] [ 1.89588542]
LAO 7.640415446887687
[ 0.02579759] [ 0.7216674]
LVA 42.95270820996198
[ 0.52259195] [ 0.92707019]
LBN 15.589927560773639
[ 1.28236447] [ 0.46050218]
LBR -25.246585075387024
[-0.16391656] [-0.40955029]
LBY -23.18695950872774
[ 0.08330333] [ 0.83671476]
LTU 39.31436760324168
[ 0.12959046] [ 0.503685]
LUX 30.571603011648165
[ 0.43536769] [ 2.34255982]
MAC 34.47162968595583
[-0.31583893] [ 0.51250737]
MKD 76.64395923880994
[ 0.84080773] [ 0.46586475]
MDG -16.010561130134853
[ 0.50972958] [ 0.94212477]
MWI 16.584726386082565
[ 0.97988897] [ 1.03124466]
MYS 1.4627695020937281
[ 1.44865954] [ 4.25596718]
MDV 26.202290681836317
[ 0.26988495] [ 1.08944918]
MLI 31.08644528058184
[ 0.03629556] [ 0.54284309]
MLT 41.17478432375323
[ 0.43837344] [ 0.28689138]
MHL -11.797452470597136
[ 1.28776765] [ 1.02085404]
MRT -6.595027556842474
[ 0.5849758] [ 0.81163846]
MUS 9.218408221880416
[ 0.23498477] [ 0.37418505]
MEX 12.871556298637401
[ 5.03006457] [ 2.04404896]
MNG -22.884830015558503
[ 0.28682583] [ 0.5124537]
MNE 15.763792640516087
[ 0.86758644] [ 0.97146082]
MAR 3.2327861166092333
[ 2.09843688] [ 2.08682052]
MOZ -0.15902655113816877
[ 0.40411669] [ 3.40041692]
MMR 38.22256996172324
[ 0.83862224] [ 1.08404653]
NAM 7.274336662683275
[ 1.25170121] [ 0.81424539]
NPL -11.955555579740938
[-0.05641496] [ 0.18537668]
NLD 61.92637331185435
[ 0.09936025] [ 0.47302353]
NZL 33.13728432227478
[ 0.267546] [ 0.73674162]
NIC 25.04162790317332
[ 2.00058717] [ 1.10485442]
NER -16.08966304733096
[ 0.31894445] [ 1.94830513]
NGA 35.7029427348085
[ 0.04214772] [ 0.27443702]
NOR 36.26880006995239
[ 1.89188725] [ 0.69060356]
OMN -24.9461882771388
[ 0.61055069] [ 0.83686246]
PAK 8.886589165347615
[ 1.1227608] [ 0.21819331]
PLW -34.00242340201824
[ 0.88662186] [ 1.56157625]
PAN 15.413231088527503
[ 1.47074485] [ 1.00203045]
PNG -10.733076750983535
[ 0.4075968] [ 0.77764736]
PRY 17.339127274792418
[ 0.99382265] [ 1.1708137]
PER 4.674379388982132
[ 0.54659645] [ 1.12253052]
PHL 19.037049788421513
[ 1.0161833] [ 0.90369896]
BOL -3.3530800636092195
[-0.01032743] [ 0.70507322]
POL 45.83916918451247
[-0.22883539] [ 0.030179]
PRT 52.51285809748423
[ 1.61687475] [ 3.63183112]
QAT 21.00158839305452
[ 1.08642421] [ 0.88843481]
CMR -5.725055881372427
[ 0.32416729] [ 0.78692743]
KOR 22.611252386073318
[ 2.08764647] [ 1.13581398]
SDN -16.450965080997737
[-0.20218311] [ 0.72374909]
ROM 60.607985006215515
[ 0.07495457] [ 0.74257636]
RUS 39.23617017001615
[ 0.52937025] [ 2.16542553]
RWA 31.26263288191801
[ 1.42254975] [ 1.08108805]
STP -7.76643654444662
[ 1.0240893] [ 0.7897884]
SAU -7.360214180920153
[ 1.22669269] [ 0.81928321]
SEN -11.26184084546226
[ 0.13000288] [ 0.5697453]
SRB 32.14646673913687
[ 0.14615257] [ 0.59273603]
SYC 31.14871933159847
[ 1.84039694] [ 1.28604635]
SLE -10.054631910242733
[ 0.12437052] [ 1.15012951]
SGP 38.82823965342372
[-0.17026367] [ 0.82587727]
SVK 56.64894866768081
[-0.10261324] [ 0.32581677]
SVN 62.481381213475714
[ 0.4563531] [ 0.69062568]
SLB 11.5439849022992
[ 0.22155494] [ 0.56703603]
ZAF 23.65818878336428
[-0.12534957] [ 0.23365483]
ESP 73.2123679963187
[ 0.67910606] [ 1.22814425]
LKA 16.059468061365543
[ 0.59197509] [ 0.43348959]
KNA -8.785549220155865
[ 0.49247665] [ 0.40288562]
VCT -5.714064907864731
[-0.04358561] [ 0.77710888]
SUR 48.210177972499025
[ 0.02538635] [ 0.65105177]
SWZ 42.76700692773696
[-0.22279921] [ 0.36894971]
SWE 76.1266944371485
[-0.0742233] [ 0.30016702]
CHE 58.88911314468831
[ 0.61465645] [ 2.07779341]
TJK 28.520637783620103
[ 0.72421307] [ 0.80824606]
THA 3.138692903620928
[ 0.6576806] [ 0.57678388]
TGO -3.74933666104765
[ 1.36501786] [ 0.22303142]
TON -35.72039213742487
[ 0.89484452] [ 0.83125984]
TTO -2.109656376075023
[ 0.58172626] [ 0.64972184]
TUN 3.1604318023917983
[ 0.66121271] [ 1.08826379]
TUR 13.717763901361316
[ 1.4191489] [ 2.46426323]
TKM 15.06271415769848
[ 2.55853852] [ 1.65016504]
UGA -12.179443737039414
[-0.25760403] [ 0.35571825]
UKR 80.91130258854939
[ 0.56924333] [ 0.85453737]
ARE 11.330744414552335
[-0.25741504] [ 0.29116336]
GBR 86.47962402345787
[ 3.33986226] [ 1.64837951]
TZA -18.731488372372453
[-0.09660025] [ 0.30892087]
USA 62.36458002760587
[ 0.49744952] [ 0.59149305]
URY 4.93594524339148
[-0.09626721] [ 1.89083332]
UZB 47.91455967200953
[ 0.36020097] [ 0.42163108]
VUT 4.49261452274996
[ 0.14729011] [ 0.45831394]
VEN 27.183953831427203
[ 2.43672022] [ 1.52686777]
VNM -12.928423156405643
[ 0.78472463] [ 0.02134919]
YEM -43.44159754010972
[ 1.22575988] [ 1.63693202]
ZMB 8.173565953365234
[ 0.1928032] [-0.04450101]
ZWE -57.99686418078739
[ 0.45859412] [ 0.51268373]
WLD 3.1874593202116586
In [267]:
indicators = final_data["Indicator"].unique()
year_cols = [str(yr) for yr in range(2000,2016)]
extents = {}
long_extents = {}
for indicator in indicators:
data = final_data.loc[final_data["Indicator"]==indicator, year_cols]
extents[indicator] = [data.min().min(), data.max().max()]
summary_data = final_data.loc[final_data["Indicator"]==indicator, "Summary Range"]
long_extents[indicator] = [summary_data.min(), summary_data.max()]
In [268]:
final_data[pd.isnull(final_data["Summary Range"])]
Out[268]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Country Name
ISO
Indicator
Summary Range
Summary Range Years
1
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Algeria
DZA
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
2
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Andorra
AND
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
3
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Angola
AGO
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
4
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Antigua and Barbuda
ATG
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
10
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bahamas, The
BHS
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
13
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Barbados
BRB
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
16
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Belize
BLZ
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
18
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bermuda
BMU
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
19
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bhutan
BTN
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
20
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bosnia and Herzegovina
BIH
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
26
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Burundi
BDI
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
29
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Cabo Verde
CPV
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
30
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Central African Republic
CAF
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
31
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Chad
TCD
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
35
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Comoros
COM
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
36
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Congo, Rep.
COG
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
40
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Cuba
CUB
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
43
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Congo, Dem. Rep.
ZAR
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
45
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Djibouti
DJI
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
46
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Dominica
DMA
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
51
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Equatorial Guinea
GNQ
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
52
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Eritrea
ERI
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
55
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Micronesia, Fed. Sts.
FSM
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
56
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Fiji
FJI
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
59
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Gabon
GAB
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
60
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Gambia, The
GMB
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
65
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Greenland
GRL
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
66
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Grenada
GRD
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
69
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Guinea-Bissau
GNB
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
70
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Guyana
GUY
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
71
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Haiti
HTI
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
75
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Iceland
ISL
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
78
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Iraq
IRQ
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
88
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Kiribati
KIR
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
93
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Lebanon
LBN
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
94
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Liberia
LBR
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
95
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Libya
LBY
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
98
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Macao SAR, China
MAC
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
99
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Macedonia, FYR
MKD
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
103
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Maldives
MDV
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
104
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Mali
MLI
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
106
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Marshall Islands
MHL
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
107
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Mauritania
MRT
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
111
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Montenegro
MNE
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
114
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Myanmar
MMR
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
120
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Niger
NER
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
125
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Palau
PLW
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
127
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Papua New Guinea
PNG
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
137
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sudan
SDN
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
141
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sao Tome and Principe
STP
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
144
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Serbia
SRB
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
145
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Seychelles
SYC
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
146
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sierra Leone
SLE
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
150
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Solomon Islands
SLB
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
154
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
St. Kitts and Nevis
KNA
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
155
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
St. Vincent and the Grenadines
VCT
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
156
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Suriname
SUR
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
157
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Swaziland
SWZ
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
160
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Tajikistan
TJK
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
163
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Tonga
TON
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
167
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Turkmenistan
TKM
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
175
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Uzbekistan
UZB
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
176
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Vanuatu
VUT
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
179
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Yemen, Rep.
YEM
Consumption CO2 Emissions Absolute Value
NaN
2000-2014
182
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
WLD
NaN
NaN
NaN
1
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Algeria
DZA
Consumption CO2 Emissions Percent Change
NaN
2000-2014
2
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Andorra
AND
Consumption CO2 Emissions Percent Change
NaN
2000-2014
3
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Angola
AGO
Consumption CO2 Emissions Percent Change
NaN
2000-2014
4
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Antigua and Barbuda
ATG
Consumption CO2 Emissions Percent Change
NaN
2000-2014
10
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bahamas, The
BHS
Consumption CO2 Emissions Percent Change
NaN
2000-2014
13
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Barbados
BRB
Consumption CO2 Emissions Percent Change
NaN
2000-2014
16
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Belize
BLZ
Consumption CO2 Emissions Percent Change
NaN
2000-2014
18
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bermuda
BMU
Consumption CO2 Emissions Percent Change
NaN
2000-2014
19
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bhutan
BTN
Consumption CO2 Emissions Percent Change
NaN
2000-2014
20
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bosnia and Herzegovina
BIH
Consumption CO2 Emissions Percent Change
NaN
2000-2014
26
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Burundi
BDI
Consumption CO2 Emissions Percent Change
NaN
2000-2014
29
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Cabo Verde
CPV
Consumption CO2 Emissions Percent Change
NaN
2000-2014
30
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Central African Republic
CAF
Consumption CO2 Emissions Percent Change
NaN
2000-2014
31
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Chad
TCD
Consumption CO2 Emissions Percent Change
NaN
2000-2014
35
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Comoros
COM
Consumption CO2 Emissions Percent Change
NaN
2000-2014
36
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Congo, Rep.
COG
Consumption CO2 Emissions Percent Change
NaN
2000-2014
40
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Cuba
CUB
Consumption CO2 Emissions Percent Change
NaN
2000-2014
43
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Congo, Dem. Rep.
ZAR
Consumption CO2 Emissions Percent Change
NaN
2000-2014
45
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Djibouti
DJI
Consumption CO2 Emissions Percent Change
NaN
2000-2014
46
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Dominica
DMA
Consumption CO2 Emissions Percent Change
NaN
2000-2014
51
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Equatorial Guinea
GNQ
Consumption CO2 Emissions Percent Change
NaN
2000-2014
52
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Eritrea
ERI
Consumption CO2 Emissions Percent Change
NaN
2000-2014
55
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Micronesia, Fed. Sts.
FSM
Consumption CO2 Emissions Percent Change
NaN
2000-2014
56
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Fiji
FJI
Consumption CO2 Emissions Percent Change
NaN
2000-2014
59
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Gabon
GAB
Consumption CO2 Emissions Percent Change
NaN
2000-2014
60
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Gambia, The
GMB
Consumption CO2 Emissions Percent Change
NaN
2000-2014
65
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Greenland
GRL
Consumption CO2 Emissions Percent Change
NaN
2000-2014
66
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Grenada
GRD
Consumption CO2 Emissions Percent Change
NaN
2000-2014
69
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Guinea-Bissau
GNB
Consumption CO2 Emissions Percent Change
NaN
2000-2014
70
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Guyana
GUY
Consumption CO2 Emissions Percent Change
NaN
2000-2014
71
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Haiti
HTI
Consumption CO2 Emissions Percent Change
NaN
2000-2014
75
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Iceland
ISL
Consumption CO2 Emissions Percent Change
NaN
2000-2014
78
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Iraq
IRQ
Consumption CO2 Emissions Percent Change
NaN
2000-2014
88
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Kiribati
KIR
Consumption CO2 Emissions Percent Change
NaN
2000-2014
93
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Lebanon
LBN
Consumption CO2 Emissions Percent Change
NaN
2000-2014
94
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Liberia
LBR
Consumption CO2 Emissions Percent Change
NaN
2000-2014
95
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Libya
LBY
Consumption CO2 Emissions Percent Change
NaN
2000-2014
98
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Macao SAR, China
MAC
Consumption CO2 Emissions Percent Change
NaN
2000-2014
99
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Macedonia, FYR
MKD
Consumption CO2 Emissions Percent Change
NaN
2000-2014
103
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Maldives
MDV
Consumption CO2 Emissions Percent Change
NaN
2000-2014
104
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Mali
MLI
Consumption CO2 Emissions Percent Change
NaN
2000-2014
106
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Marshall Islands
MHL
Consumption CO2 Emissions Percent Change
NaN
2000-2014
107
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Mauritania
MRT
Consumption CO2 Emissions Percent Change
NaN
2000-2014
111
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Montenegro
MNE
Consumption CO2 Emissions Percent Change
NaN
2000-2014
114
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Myanmar
MMR
Consumption CO2 Emissions Percent Change
NaN
2000-2014
120
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Niger
NER
Consumption CO2 Emissions Percent Change
NaN
2000-2014
125
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Palau
PLW
Consumption CO2 Emissions Percent Change
NaN
2000-2014
127
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Papua New Guinea
PNG
Consumption CO2 Emissions Percent Change
NaN
2000-2014
137
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sudan
SDN
Consumption CO2 Emissions Percent Change
NaN
2000-2014
141
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sao Tome and Principe
STP
Consumption CO2 Emissions Percent Change
NaN
2000-2014
144
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Serbia
SRB
Consumption CO2 Emissions Percent Change
NaN
2000-2014
145
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Seychelles
SYC
Consumption CO2 Emissions Percent Change
NaN
2000-2014
146
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sierra Leone
SLE
Consumption CO2 Emissions Percent Change
NaN
2000-2014
150
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Solomon Islands
SLB
Consumption CO2 Emissions Percent Change
NaN
2000-2014
154
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
St. Kitts and Nevis
KNA
Consumption CO2 Emissions Percent Change
NaN
2000-2014
155
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
St. Vincent and the Grenadines
VCT
Consumption CO2 Emissions Percent Change
NaN
2000-2014
156
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Suriname
SUR
Consumption CO2 Emissions Percent Change
NaN
2000-2014
157
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Swaziland
SWZ
Consumption CO2 Emissions Percent Change
NaN
2000-2014
160
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Tajikistan
TJK
Consumption CO2 Emissions Percent Change
NaN
2000-2014
163
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Tonga
TON
Consumption CO2 Emissions Percent Change
NaN
2000-2014
167
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Turkmenistan
TKM
Consumption CO2 Emissions Percent Change
NaN
2000-2014
175
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Uzbekistan
UZB
Consumption CO2 Emissions Percent Change
NaN
2000-2014
176
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Vanuatu
VUT
Consumption CO2 Emissions Percent Change
NaN
2000-2014
179
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Yemen, Rep.
YEM
Consumption CO2 Emissions Percent Change
NaN
2000-2014
182
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
WLD
NaN
NaN
NaN
1
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Algeria
DZA
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
2
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Andorra
AND
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
3
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Angola
AGO
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
4
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Antigua and Barbuda
ATG
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
10
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bahamas, The
BHS
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
13
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Barbados
BRB
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
16
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Belize
BLZ
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
18
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bermuda
BMU
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
19
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bhutan
BTN
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
20
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Bosnia and Herzegovina
BIH
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
26
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Burundi
BDI
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
29
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Cabo Verde
CPV
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
30
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Central African Republic
CAF
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
31
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Chad
TCD
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
35
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Comoros
COM
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
36
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Congo, Rep.
COG
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
40
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Cuba
CUB
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
43
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Congo, Dem. Rep.
ZAR
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
45
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Djibouti
DJI
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
46
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Dominica
DMA
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
51
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Equatorial Guinea
GNQ
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
52
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Eritrea
ERI
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
55
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Micronesia, Fed. Sts.
FSM
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
56
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Fiji
FJI
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
59
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Gabon
GAB
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
60
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Gambia, The
GMB
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
65
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Greenland
GRL
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
66
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Grenada
GRD
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
69
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Guinea-Bissau
GNB
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
70
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Guyana
GUY
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
71
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Haiti
HTI
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
75
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Iceland
ISL
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
78
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Iraq
IRQ
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
88
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Kiribati
KIR
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
93
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Lebanon
LBN
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
94
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Liberia
LBR
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
95
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Libya
LBY
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
98
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Macao SAR, China
MAC
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
99
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Macedonia, FYR
MKD
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
103
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Maldives
MDV
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
104
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Mali
MLI
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
106
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Marshall Islands
MHL
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
107
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Mauritania
MRT
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
111
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Montenegro
MNE
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
114
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Myanmar
MMR
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
120
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Niger
NER
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
125
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Palau
PLW
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
127
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Papua New Guinea
PNG
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
137
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sudan
SDN
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
141
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sao Tome and Principe
STP
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
144
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Serbia
SRB
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
145
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Seychelles
SYC
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
146
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Sierra Leone
SLE
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
150
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Solomon Islands
SLB
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
154
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
St. Kitts and Nevis
KNA
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
155
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
St. Vincent and the Grenadines
VCT
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
156
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Suriname
SUR
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
157
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Swaziland
SWZ
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
160
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Tajikistan
TJK
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
163
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Tonga
TON
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
167
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Turkmenistan
TKM
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
175
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Uzbekistan
UZB
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
176
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Vanuatu
VUT
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
179
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Yemen, Rep.
YEM
Consumption CO2 Emissions Absolute Change
NaN
2000-2014
182
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
WLD
NaN
NaN
NaN
In [ ]:
final_data
In [269]:
extents
Out[269]:
{'Production CO2 Emissions Absolute Value': [0.0069999999999999993,
9896.7060457050302],
'Consumption CO2 Emissions Absolute Value': [-0.31450916878671931,
2470.0722301013307],
nan: [nan, nan],
'Production CO2 Emissions Percent Change': [-0.58231707317073167,
5.8064516129032278],
'Consumption CO2 Emissions Percent Change': [-2.2820333549161385,
4.0330301875807812],
'Production CO2 Emissions Absolute Change': [-0.58231707317073167,
5.8064516129032278],
'Consumption CO2 Emissions Absolute Change': [-2.2820333549161385,
4.0330301875807812],
'GDP Absolute Value': [118428316.402523, 75636751196801.094],
'GDP Percent Change': [-0.62075919584900086, 1.7918065792259044],
'GDP Absolute Change': [-1118392942734.1953, 2727043480126.0]}
In [270]:
long_extents
Out[270]:
{'Production CO2 Emissions Absolute Value': [-157.98880529674875,
3111.6066568448969],
'Consumption CO2 Emissions Absolute Value': [-97.065613082643722,
1600.804809484755],
nan: [nan, nan],
'Production CO2 Emissions Percent Change': [-0.36313606588722158,
13.091579476991498],
'Consumption CO2 Emissions Percent Change': [-0.39043823222336332,
5.0366677469343344],
'Production CO2 Emissions Absolute Change': [-0.36313606588722158,
13.091579476991498],
'Consumption CO2 Emissions Absolute Change': [-0.39043823222336332,
5.0366677469343344],
'GDP Absolute Value': [-19669203139.392899, 25635055621226.297],
'GDP Percent Change': [-0.40955028618152017, 4.2559671805372483],
'GDP Absolute Change': [-19669203139.392899, 25635055621226.297]}
In [271]:
final_data[(final_data['Country Name']=='Eritrea') & ['GDP' in ind if type(ind)==str else False for ind in final_data['Indicator']]]
Out[271]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Country Name
ISO
Indicator
Summary Range
Summary Range Years
156
1.939336e+09
2.109133e+09
2.172522e+09
2.114830e+09
2.145532e+09
2.200768e+09
2.179437e+09
2.210534e+09
1.994277e+09
2.071585e+09
2.117040e+09
2.300794e+09
NaN
NaN
NaN
NaN
Eritrea
ERI
GDP Absolute Value
3.614583e+08
2000-2011
157
-3.141986e-02
8.755435e-02
3.005429e-02
-2.655516e-02
1.451736e-02
2.574450e-02
-9.692169e-03
1.426822e-02
-9.783030e-02
3.876502e-02
2.194191e-02
8.679800e-02
NaN
NaN
NaN
NaN
Eritrea
ERI
GDP Percent Change
1.863825e-01
2000-2011
158
-6.291029e+07
1.697973e+08
6.338851e+07
-5.769166e+07
3.070174e+07
5.523564e+07
-2.133021e+07
3.109669e+07
-2.162572e+08
7.730817e+07
4.545452e+07
1.837548e+08
NaN
NaN
NaN
NaN
Eritrea
ERI
GDP Absolute Change
3.614583e+08
2000-2011
In [ ]:
In [215]:
production_co2_emissions_absolute_value['ISO'].unique()
Out[215]:
array(['ALB', 'DZA', 'AND', 'AGO', 'ATG', 'ARG', 'ARM', 'AUS', 'AUT',
'AZE', 'BHS', 'BHR', 'BGD', 'BRB', 'BLR', 'BEL', 'BLZ', 'BEN',
'BMU', 'BTN', 'BIH', 'BWA', 'BRA', 'BRN', 'BGR', 'BFA', 'BDI',
'KHM', 'CAN', 'CPV', 'CAF', 'TCD', 'CHL', 'CHN', 'COL', 'COM',
'COG', 'CRI', 'CIV', 'HRV', 'CUB', 'CYP', 'CZE', 'ZAR', 'DNK',
'DJI', 'DMA', 'DOM', 'ECU', 'EGY', 'SLV', 'GNQ', 'ERI', 'EST',
'ETH', 'FSM', 'FJI', 'FIN', 'FRA', 'GAB', 'GMB', 'GEO', 'DEU',
'GHA', 'GRC', 'GRL', 'GRD', 'GTM', 'GIN', 'GNB', 'GUY', 'HTI',
'HND', 'HKG', 'HUN', 'ISL', 'IND', 'IDN', 'IRQ', 'IRL', 'IRN',
'ISR', 'ITA', 'JAM', 'JPN', 'JOR', 'KAZ', 'KEN', 'KIR', 'KWT',
'KGZ', 'LAO', 'LVA', 'LBN', 'LBR', 'LBY', 'LTU', 'LUX', 'MAC',
'MKD', 'MDG', 'MWI', 'MYS', 'MDV', 'MLI', 'MLT', 'MHL', 'MRT',
'MUS', 'MEX', 'MNG', 'MNE', 'MAR', 'MOZ', 'MMR', 'NAM', 'NPL',
'NLD', 'NZL', 'NIC', 'NER', 'NGA', 'NOR', 'OMN', 'PAK', 'PLW',
'PAN', 'PNG', 'PRY', 'PER', 'PHL', 'BOL', 'POL', 'PRT', 'QAT',
'CMR', 'KOR', 'SDN', 'ROM', 'RUS', 'RWA', 'STP', 'SAU', 'SEN',
'SRB', 'SYC', 'SLE', 'SGP', 'SVK', 'SVN', 'SLB', 'ZAF', 'ESP',
'LKA', 'KNA', 'VCT', 'SUR', 'SWZ', 'SWE', 'CHE', 'TJK', 'THA',
'TGO', 'TON', 'TTO', 'TUN', 'TUR', 'TKM', 'UGA', 'UKR', 'ARE',
'GBR', 'TZA', 'USA', 'URY', 'UZB', 'VUT', 'VEN', 'VNM', 'YEM',
'ZMB', 'ZWE', 'WLD'], dtype=object)
Experimentation Below
In [58]:
data_names_and_codes = {'NY.GDP.MKTP.KD': 'GDP (current US$)'}
# {'EG.ELC.ACCS.ZS': 'Access to electricity (% of population)',
# 'EG.FEC.RNEW.ZS': 'Renewable energy consumption (% of total final energy consumption)',
# 'IT.NET.USER.ZS': 'Individuals using the Internet (% of population)',
# 'NE.CON.PRVT.PC.KD': 'Household final consumption expenditure per capita (constant 2010 US$)',
# 'NV.IND.TOTL.KD': 'Industry, value added (constant 2010 US$)',
# 'NY.GDP.TOTL.RT.ZS': 'Total natural resources rents (% of GDP)',
# 'SG.GEN.PARL.ZS': 'Proportion of seats held by women in national parliaments (%)',
# 'SL.EMP.TOTL.SP.ZS': 'Employment to population ratio, 15+, total (%) (modeled ILO estimate)',
# 'SM.POP.NETM': 'Net migration',
# 'SP.DYN.LE00.IN': 'Life expectancy at birth, total (years)',
# 'SP.URB.TOTL.IN.ZS': 'Urban population (% of total)',
# 'TM.VAL.MRCH.CD.WT': 'Merchandise imports (current US$)'}
column_long_name_to_short_name = {'GDP (current US$)': 'GDP'}
# {'Renewable energy consumption (% of total final energy consumption)': 'renewable_energy_consumption_of_total_final_energy_consumpti',
# 'Household final consumption expenditure per capita (constant 2010 US$)': 'household_final_consumption_expenditure_per_capita_constant_20',
# 'Merchandise imports (current US$)': 'merchandise_imports_current_us_tm_val_mrch_cd_wt',
# 'Industry, value added (constant 2010 US$)': 'industry_value_added_constant_2010_us_nv_ind_totl_kd',
# 'Access to electricity (% of population)': 'access_to_electricity_of_population_eg_elc_accs_zs',
# 'Urban population (% of total)': 'urban_population_of_total_sp_urb_totl_in_zs',
# 'Employment to population ratio, 15+, total (%) (modeled ILO estimate)': 'employment_to_population_ratio_15_total_modeled_ilo_est',
# 'Total natural resources rents (% of GDP)': 'total_natural_resources_rents_of_gdp_ny_gdp_totl_rt_zs',
# 'Life expectancy at birth, total (years)': 'life_expectancy_at_birth_total_years_sp_dyn_le00_in',
# 'Net migration': 'net_migration_sm_pop_netm',
# 'Proportion of seats held by women in national parliaments (%)': 'proportion_of_seats_held_by_women_in_national_parliaments',
# 'Individuals using the Internet (% of population)': 'individuals_using_the_internet_of_population_it_net_user_z'}
series_code_to_data_viz_name = {}
for key, value in data_names_and_codes.items():
series_code_to_data_viz_name[key] = column_long_name_to_short_name[value]
series_code_to_data_viz_name
Out[58]:
{'NY.GDP.MKTP.CD': 'GDP'}
In [ ]:
indicators = series_code_to_data_viz_name
for indicator in indicators:
# Results are paginated
print(indicator)
res = req.get("http://api.worldbank.org/countries/all/indicators/{}?date=1999:2016&format=json&per_page=10000".format(indicator))
data = pd.io.json.json_normalize(res.json()[1])
data = data[["country.value", "date", "value"]]
value_name = series_code_to_data_viz_name[indicator]
data.columns = ["Country Name", "Year", value_name]
data = data.pivot(index="Country Name", columns="Year", values=value_name).astype(float)
data["ISO"] = list(map(add_iso, data.index))
data = data.loc[pd.notnull(data["ISO"])]
data["Indicator"] = value_name
all_world_bank_data = all_world_bank_data.append(data)
if indicator == "NY.GDP.MKTP.CD":
year_cols = [str(yr) for yr in range(1999,2016)]
data = data.loc[:,year_cols].pct_change(axis=1).loc[:,year_cols[1:]]
data["Indicator"] = "GDP percent change"
data["ISO"] = list(map(add_iso, data.index))
all_world_bank_data = all_world_bank_data.append(data)
all_world_bank_data.index.name = "Country Name"
all_world_bank_data = all_world_bank_data.drop(["1999", "2016"], axis=1)
In [26]:
all_world_bank_data.head()
Out[26]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
ISO
Indicator
Country Name
Afghanistan
NaN
2.461666e+09
4.128821e+09
4.583644e+09
5.285466e+09
6.275074e+09
7.057598e+09
9.843842e+09
1.019053e+10
1.248694e+10
1.593680e+10
1.793024e+10
2.053654e+10
2.004633e+10
2.005019e+10
1.921556e+10
AFG
GDP
Albania
3.632044e+09
4.060759e+09
4.435079e+09
5.746946e+09
7.314865e+09
8.158549e+09
8.992642e+09
1.070101e+10
1.288135e+10
1.204421e+10
1.192695e+10
1.289087e+10
1.231978e+10
1.277628e+10
1.322824e+10
1.133526e+10
ALB
GDP
Algeria
5.479025e+10
5.474471e+10
5.676029e+10
6.786383e+10
8.532500e+10
1.031982e+11
1.170273e+11
1.349771e+11
1.710007e+11
1.372110e+11
1.612073e+11
2.000191e+11
2.090590e+11
2.097550e+11
2.138100e+11
1.658743e+11
DZA
GDP
American Samoa
NaN
NaN
5.140000e+08
5.270000e+08
5.120000e+08
5.030000e+08
4.960000e+08
5.200000e+08
5.630000e+08
6.780000e+08
5.760000e+08
5.740000e+08
6.440000e+08
6.410000e+08
6.430000e+08
6.590000e+08
ASM
GDP
Andorra
1.434430e+09
1.496913e+09
1.733117e+09
2.398646e+09
2.935659e+09
3.255789e+09
3.543257e+09
4.016972e+09
4.007353e+09
3.660531e+09
3.355695e+09
3.442063e+09
3.164615e+09
3.281585e+09
3.350736e+09
2.811489e+09
AND
GDP
In [29]:
reverse_map = {v: k for k, v in column_long_name_to_short_name.items()}
def create_summary_values_World_Bank(row):
#print(row)
if row["Indicator"] == "GDP percent change":
val = row["2015"] - row["2000"]
return(val, "2000-2015")
else:
indicator = reverse_map[row["Indicator"]]
if indicator == 'Renewable energy consumption (% of total final energy consumption)':
val = row["2014"] - row["2000"]
return(val, "2000-2014")
elif indicator == 'GDP (current US$)':
val = row["2015"] - row["2000"]
return(val, "2000-2015")
elif indicator == 'Household final consumption expenditure per capita (constant 2010 US$)':
val = row["2015"]
return(val, "2015")
elif indicator == 'Merchandise imports (current US$)':
val = row["2015"] - row["2000"]
return(val, "2000-2015")
elif indicator == 'Industry, value added (constant 2010 US$)':
val = row["2015"] - row["2000"]
return(val, "2000-2015")
elif indicator == 'Access to electricity (% of population)':
val = row["2014"]
return(val, "2014")
elif indicator == 'Urban population (% of total)':
val = row["2015"]
return(val, "2015")
elif indicator == 'Employment to population ratio, 15+, total (%) (modeled ILO estimate)':
val = row["2015"] - row["2000"]
return(val, "2000-2015")
elif indicator == 'Total natural resources rents (% of GDP)':
val = row["2015"]
return(val, "2015")
elif indicator == 'Life expectancy at birth, total (years)':
val = row["2015"]
return(val, "2015")
elif indicator == 'Net migration':
val = row["2012"]
return(val, "2012")
elif indicator == 'Proportion of seats held by women in national parliaments (%)':
val = row["2015"]
return(val, "2015")
elif indicator == 'Individuals using the Internet (% of population)':
val = row["2015"]
return(val, "2015")
summary_data = all_world_bank_data.apply(create_summary_values_World_Bank, axis=1)
all_world_bank_data["Summary Range"], all_world_bank_data["Summary Range Years"] = list(zip(*summary_data))
In [30]:
all_world_bank_data.head()
Out[30]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
ISO
Indicator
Summary Range
Summary Range Years
Country Name
Afghanistan
0.163713
1.006099
3.467205
7.209179
13.969172
23.000000
27.506411
34.290512
42.4
47.888466
42.700000
61.514420
69.100000
75.154373
89.5
NaN
AFG
access_to_electricity_of_population_eg_elc_acc...
89.5
2014
Albania
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.0
100.000000
100.000000
100.000000
100.000000
100.000000
100.0
NaN
ALB
access_to_electricity_of_population_eg_elc_acc...
100.0
2014
Algeria
96.702133
97.004044
97.298698
97.590019
97.881889
98.184265
98.490738
98.806519
99.3
99.443893
99.711174
99.889542
99.973083
99.996918
100.0
NaN
DZA
access_to_electricity_of_population_eg_elc_acc...
100.0
2014
American Samoa
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
ASM
access_to_electricity_of_population_eg_elc_acc...
NaN
2014
Andorra
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.0
100.000000
100.000000
100.000000
100.000000
100.000000
100.0
NaN
AND
access_to_electricity_of_population_eg_elc_acc...
100.0
2014
In [31]:
write_to_S3(all_world_bank_data, s3_bucket, FINAL_DATA + "World Bank Data with ISO3, 2000-2015 with Summary Values.csv")
Calculate Index Values
In [32]:
world_bank_data = read_from_S3(s3_bucket, FINAL_DATA + "World Bank Data with ISO3, 2000-2015 with Summary Values.csv")
world_bank_data.head()
Out[32]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
ISO
Indicator
Summary Range
Summary Range Years
Country Name
Afghanistan
0.163713
1.006099
3.467205
7.209179
13.969172
23.000000
27.506411
34.290512
42.4
47.888466
42.700000
61.514420
69.100000
75.154373
89.5
NaN
AFG
access_to_electricity_of_population_eg_elc_acc...
89.5
2014
Albania
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.0
100.000000
100.000000
100.000000
100.000000
100.000000
100.0
NaN
ALB
access_to_electricity_of_population_eg_elc_acc...
100.0
2014
Algeria
96.702133
97.004044
97.298698
97.590019
97.881889
98.184265
98.490738
98.806519
99.3
99.443893
99.711174
99.889542
99.973083
99.996918
100.0
NaN
DZA
access_to_electricity_of_population_eg_elc_acc...
100.0
2014
American Samoa
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
ASM
access_to_electricity_of_population_eg_elc_acc...
NaN
2014
Andorra
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.000000
100.0
100.000000
100.000000
100.000000
100.000000
100.000000
100.0
NaN
AND
access_to_electricity_of_population_eg_elc_acc...
100.0
2014
In [38]:
# Calculating index values
# formula = (1 – ΔCO2)*(1 + ΔGDP) - ΔCO2 + ΔGDP
world_bank_data = read_from_S3(s3_bucket, FINAL_DATA + "World Bank Data with ISO3, 2000-2015 with Summary Values.csv")
gdp_percent_change_data = world_bank_data.set_index("Indicator").loc["GDP percent change"]
gdp_percent_change_data.set_index(["ISO"], inplace=True)
gdp_percent_change_data = gdp_percent_change_data.drop(["Summary Range", "Summary Range Years"], axis=1)
def calc_index(co2, gdp):
return((1-co2)*(1+gdp) - co2 + gdp)
# import CO2 change
## Territorial
territory_emissions = read_from_S3(s3_bucket, FINAL_DATA + \
"Territory Emissions GCB percent changes with ISO3 2000-2015 plus summary data.csv", index_col = "ISO")
## Consumption
consumption_emissions = read_from_S3(s3_bucket, FINAL_DATA + \
"Consumption Emissions GCB percent changes with ISO3 2000-2015 plus summary data.csv", index_col = "ISO")
# https://stackoverflow.com/questions/22149584/what-does-axis-in-pandas-mean
country_names_territory = territory_emissions["Country Name"]
country_names_consumption = consumption_emissions["Country Name"]
territory_emissions_gdp_index = calc_index(territory_emissions.drop(["Country Name", "Summary Range", "Summary Range Years", "Indicator"], axis=1), gdp_percent_change_data)
consumption_emissions_gdp_index = calc_index(consumption_emissions.drop(["Country Name", "Summary Range", "Summary Range Years","Indicator"], axis=1), gdp_percent_change_data)
def create_summary_values_ICGGD(row):
val = row["2015"] - row["2000"]
return(val, "2000-2015")
summary_data = territory_emissions_gdp_index.apply(create_summary_values_ICGGD, axis=1)
territory_emissions_gdp_index["Summary Range"], territory_emissions_gdp_index["Summary Range Years"] = list(zip(*summary_data))
summary_data = consumption_emissions_gdp_index.apply(create_summary_values_ICGGD, axis=1)
consumption_emissions_gdp_index["Summary Range"], consumption_emissions_gdp_index["Summary Range Years"] = list(zip(*summary_data))
territory_emissions_gdp_index["Indicator"] = "ICGGD with Production Emissions"
consumption_emissions_gdp_index["Indicator"] = "ICGGD with Consumption Emissions"
territory_emissions_gdp_index["Country Name"] = country_names_territory
consumption_emissions_gdp_index["Country Name"] = country_names_consumption
In [39]:
# Write to S3
write_to_S3(territory_emissions_gdp_index, s3_bucket, FINAL_DATA + \
"ICGGD calculated with Territory Emissions.csv")
write_to_S3(consumption_emissions_gdp_index, s3_bucket, FINAL_DATA + \
"ICGGD calculated with Consumption Emissions.csv")
In [76]:
# Create single file that has all the data for the application
#gdp_annual_pct_change = read_from_S3(s3_bucket, FINAL_DATA+".csv")
#gdp_annual_absolute_value = read_from_S3(s3_bucket, FINAL_DATA+".csv")
production_co2_emissions_annual_change = read_from_S3(s3_bucket, FINAL_DATA+"Territory Emissions GCB percent changes with ISO3 2000-2015 plus summary data.csv")
production_co2_emissions_absolute_value = read_from_S3(s3_bucket, FINAL_DATA+"Territory Emissions GCB absolute values with ISO3 2000-2015 plus summary data.csv")
consumption_co2_emissions_annual_change = read_from_S3(s3_bucket, FINAL_DATA+"Consumption Emissions GCB percent changes with ISO3 2000-2015 plus summary data.csv")
consumption_co2_emissions_absolute_value = read_from_S3(s3_bucket, FINAL_DATA+"Consumption Emissions GCB absolute values with ISO3 2000-2015 plus summary data.csv")
index_with_production_emissions_and_gdp = read_from_S3(s3_bucket, FINAL_DATA+"ICGGD calculated with Territory Emissions.csv")
index_with_consumption_emissions_and_gdp = read_from_S3(s3_bucket, FINAL_DATA+"ICGGD calculated with Consumption Emissions.csv")
world_bank_data = read_from_S3(s3_bucket, FINAL_DATA+"World Bank Data with ISO3, 2000-2015 with Summary Values.csv")
dsets = [production_co2_emissions_annual_change, production_co2_emissions_absolute_value,
consumption_co2_emissions_annual_change, consumption_co2_emissions_absolute_value,
index_with_production_emissions_and_gdp, index_with_consumption_emissions_and_gdp,
world_bank_data]
def print_columns(list_of_dfs):
for df in list_of_dfs:
print(df.reset_index().columns)
print_columns(dsets)
2000 2001 2002 2003 2004 \
Country Name
Albania 0.012285 0.066748 0.163823 0.144673 -0.029889
Algeria -0.045460 -0.041370 0.077827 0.018486 -0.032853
Andorra 0.021429 0.000000 0.013986 0.006897 0.054795
Angola 0.042050 0.019985 0.301432 -0.284308 1.073220
Antigua and Barbuda -0.010526 0.000000 0.053191 0.070707 0.047170
2005 2006 2007 2008 2009 \
Country Name
Albania 0.021127 -0.083621 0.007526 0.113912 0.000838
Algeria 0.197050 -0.055658 0.082355 0.007334 0.100934
Andorra 0.019481 -0.050955 -0.013423 0.000000 -0.040816
Angola 0.019317 0.162328 0.129611 0.022161 0.081016
Antigua and Barbuda 0.009009 0.035714 0.103448 0.023438 0.061069
2010 2011 2012 2013 2014 \
Country Name
Albania 0.050251 0.139553 -0.100770 0.021790 -0.003732
Algeria -0.018572 0.016862 0.072622 0.032527 0.072584
Andorra 0.000000 -0.049645 0.000000 0.000000 0.007104
Angola 0.045521 0.044170 0.100798 -0.027997 -0.000545
Antigua and Barbuda 0.028777 -0.020979 0.021429 0.000000 0.024332
2015 ISO Summary Range Summary Range Years \
Country Name
Albania 0.012003 ALB -0.000282 2000-2015
Algeria 0.042386 DZA 0.087846 2000-2015
Andorra 0.007376 AND -0.014053 2000-2015
Angola 0.016048 AGO -0.026002 2000-2015
Antigua and Barbuda 0.022473 ATG 0.032999 2000-2015
Indicator
Country Name
Albania Production CO2 Emissions Annual Change
Algeria Production CO2 Emissions Annual Change
Andorra Production CO2 Emissions Annual Change
Angola Production CO2 Emissions Annual Change
Antigua and Barbuda Production CO2 Emissions Annual Change
2000 2001 2002 2003 2004 2005 2006 \
Country Name
Albania 0.824 0.879 1.023 1.171 1.136 1.160 1.063
Algeria 23.979 22.987 24.776 25.234 24.405 29.214 27.588
Andorra 0.143 0.143 0.145 0.146 0.154 0.157 0.149
Angola 2.602 2.654 3.454 2.472 5.125 5.224 6.072
Antigua and Barbuda 0.094 0.094 0.099 0.106 0.111 0.112 0.116
2007 2008 2009 2010 2011 2012 2013 \
Country Name
Albania 1.071 1.193 1.194 1.254 1.429 1.285 1.313
Algeria 29.860 30.079 33.115 32.500 33.048 35.448 36.601
Andorra 0.147 0.147 0.141 0.141 0.134 0.134 0.134
Angola 6.859 7.011 7.579 7.924 8.274 9.108 8.853
Antigua and Barbuda 0.128 0.131 0.139 0.143 0.140 0.143 0.143
2014 2015 ISO Summary Range \
Country Name
Albania 1.308100 1.323801 ALB 0.499801
Algeria 39.257647 40.921606 DZA 16.942606
Andorra 0.134952 0.135947 AND -0.007053
Angola 8.848174 8.990173 AGO 6.388173
Antigua and Barbuda 0.146480 0.149771 ATG 0.055771
Summary Range Years \
Country Name
Albania 2000-2015
Algeria 2000-2015
Andorra 2000-2015
Angola 2000-2015
Antigua and Barbuda 2000-2015
Indicator
Country Name
Albania Production CO2 Emissions Absolute Value
Algeria Production CO2 Emissions Absolute Value
Andorra Production CO2 Emissions Absolute Value
Angola Production CO2 Emissions Absolute Value
Antigua and Barbuda Production CO2 Emissions Absolute Value
2000 2001 2002 2003 2004 \
Country Name
Albania 0.041009 0.071166 0.229345 0.111479 -0.035056
Algeria NaN NaN NaN NaN NaN
Andorra NaN NaN NaN NaN NaN
Angola NaN NaN NaN NaN NaN
Antigua and Barbuda NaN NaN NaN NaN NaN
2005 2006 2007 2008 2009 \
Country Name
Albania 0.104597 -0.055692 0.000868 0.090902 0.024621
Algeria NaN NaN NaN NaN NaN
Andorra NaN NaN NaN NaN NaN
Angola NaN NaN NaN NaN NaN
Antigua and Barbuda NaN NaN NaN NaN NaN
2010 2011 2012 2013 2014 2015 \
Country Name
Albania -0.026749 0.036497 -0.065904 -0.03428 -0.006087 NaN
Algeria NaN NaN NaN NaN NaN NaN
Andorra NaN NaN NaN NaN NaN NaN
Angola NaN NaN NaN NaN NaN NaN
Antigua and Barbuda NaN NaN NaN NaN NaN NaN
ISO Summary Range Summary Range Years \
Country Name
Albania ALB -0.047096 2000-2014
Algeria DZA NaN 2000-2014
Andorra AND NaN 2000-2014
Angola AGO NaN 2000-2014
Antigua and Barbuda ATG NaN 2000-2014
Indicator
Country Name
Albania Consumption CO2 Emissions Annual Change
Algeria Consumption CO2 Emissions Annual Change
Andorra Consumption CO2 Emissions Annual Change
Angola Consumption CO2 Emissions Annual Change
Antigua and Barbuda Consumption CO2 Emissions Annual Change
2000 2001 2002 2003 2004 \
Country Name
Albania 1.029235 1.102482 1.355331 1.506422 1.453613
Algeria NaN NaN NaN NaN NaN
Andorra NaN NaN NaN NaN NaN
Angola NaN NaN NaN NaN NaN
Antigua and Barbuda NaN NaN NaN NaN NaN
2005 2006 2007 2008 2009 \
Country Name
Albania 1.605657 1.516234 1.51755 1.655498 1.696258
Algeria NaN NaN NaN NaN NaN
Andorra NaN NaN NaN NaN NaN
Angola NaN NaN NaN NaN NaN
Antigua and Barbuda NaN NaN NaN NaN NaN
2010 2011 2012 2013 2014 2015 \
Country Name
Albania 1.650886 1.711138 1.598367 1.543575 1.534179 NaN
Algeria NaN NaN NaN NaN NaN NaN
Andorra NaN NaN NaN NaN NaN NaN
Angola NaN NaN NaN NaN NaN NaN
Antigua and Barbuda NaN NaN NaN NaN NaN NaN
ISO Summary Range Summary Range Years \
Country Name
Albania ALB 0.504944 2000-2014
Algeria DZA NaN 2000-2014
Andorra AND NaN 2000-2014
Angola AGO NaN 2000-2014
Antigua and Barbuda ATG NaN 2000-2014
Indicator
Country Name
Albania Consumption CO2 Emissions Absolute Value
Algeria Consumption CO2 Emissions Absolute Value
Andorra Consumption CO2 Emissions Absolute Value
Angola Consumption CO2 Emissions Absolute Value
Antigua and Barbuda Consumption CO2 Emissions Absolute Value
2000 2001 2002 2003 2004 2005 2006 \
ISO
ABW NaN NaN NaN NaN NaN NaN NaN
AFG NaN NaN NaN NaN NaN NaN NaN
AGO 1.863119 0.918058 1.074066 1.877813 -0.790338 1.827914 1.557661
ALB 1.101909 1.094700 0.841613 1.259449 1.613586 1.185986 1.380261
AND 1.215370 1.117462 1.284470 1.747994 1.335232 1.186081 1.284020
2007 2008 2009 2010 2011 2012 2013 \
ISO
ABW NaN NaN NaN NaN NaN NaN NaN
AFG NaN NaN NaN NaN NaN NaN NaN
AGO 1.575926 1.732076 0.639964 1.089631 1.424981 1.004210 1.223187
ALB 1.363467 1.156468 0.868401 0.880515 0.871251 1.108473 1.030483
AND 1.296900 0.995118 0.902545 0.833666 1.148598 0.836085 1.065332
2014 2015 Summary Range Summary Range Years \
ISO
ABW NaN NaN NaN 2000-2015
AFG NaN NaN NaN 2000-2015
AGO 1.030956 0.595224 -1.267895 2000-2015
ALB 1.076261 0.700875 -0.401034 2000-2015
AND NaN NaN NaN 2000-2015
Indicator Country Name
ISO
ABW ICGGD with Production Emissions NaN
AFG ICGGD with Production Emissions NaN
AGO ICGGD with Production Emissions Angola
ALB ICGGD with Production Emissions Albania
AND ICGGD with Production Emissions Andorra
2000 2001 2002 2003 2004 2005 2006 \
ISO
ABW NaN NaN NaN NaN NaN NaN NaN
AFG NaN NaN NaN NaN NaN NaN NaN
AGO NaN NaN NaN NaN NaN NaN NaN
ALB 1.042633 1.085342 0.704528 1.335654 1.625329 1.009418 1.321549
AND NaN NaN NaN NaN NaN NaN NaN
2007 2008 2009 2010 2011 2012 2013 \
ISO
ABW NaN NaN NaN NaN NaN NaN NaN
AFG NaN NaN NaN NaN NaN NaN NaN
AGO NaN NaN NaN NaN NaN NaN NaN
ALB 1.378048 1.207177 0.82238 1.033766 1.085692 1.040286 1.144722
AND NaN NaN NaN NaN NaN NaN NaN
2014 2015 Summary Range Summary Range Years \
ISO
ABW NaN NaN NaN 2000-2015
AFG NaN NaN NaN 2000-2015
AGO NaN NaN NaN 2000-2015
ALB 1.081052 NaN NaN 2000-2015
AND NaN NaN NaN 2000-2015
Indicator Country Name
ISO
ABW ICGGD with Consumption Emissions NaN
AFG ICGGD with Consumption Emissions NaN
AGO ICGGD with Consumption Emissions Angola
ALB ICGGD with Consumption Emissions Albania
AND ICGGD with Consumption Emissions Andorra
2000 2001 2002 2003 2004 \
Country Name
Afghanistan 0.163713 1.006099 3.467205 7.209179 13.969172
Albania 100.000000 100.000000 100.000000 100.000000 100.000000
Algeria 96.702133 97.004044 97.298698 97.590019 97.881889
American Samoa NaN NaN NaN NaN NaN
Andorra 100.000000 100.000000 100.000000 100.000000 100.000000
2005 2006 2007 2008 2009 \
Country Name
Afghanistan 23.000000 27.506411 34.290512 42.4 47.888466
Albania 100.000000 100.000000 100.000000 100.0 100.000000
Algeria 98.184265 98.490738 98.806519 99.3 99.443893
American Samoa NaN NaN NaN NaN NaN
Andorra 100.000000 100.000000 100.000000 100.0 100.000000
2010 2011 2012 2013 2014 2015 \
Country Name
Afghanistan 42.700000 61.514420 69.100000 75.154373 89.5 NaN
Albania 100.000000 100.000000 100.000000 100.000000 100.0 NaN
Algeria 99.711174 99.889542 99.973083 99.996918 100.0 NaN
American Samoa NaN NaN NaN NaN NaN NaN
Andorra 100.000000 100.000000 100.000000 100.000000 100.0 NaN
ISO Indicator \
Country Name
Afghanistan AFG access_to_electricity_of_population_eg_elc_acc...
Albania ALB access_to_electricity_of_population_eg_elc_acc...
Algeria DZA access_to_electricity_of_population_eg_elc_acc...
American Samoa ASM access_to_electricity_of_population_eg_elc_acc...
Andorra AND access_to_electricity_of_population_eg_elc_acc...
Summary Range Summary Range Years
Country Name
Afghanistan 89.5 2014
Albania 100.0 2014
Algeria 100.0 2014
American Samoa NaN 2014
Andorra 100.0 2014
In [53]:
world_bank_data[world_bank_data["Indicator"]=="GDP"]
Out[53]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
ISO
Indicator
Summary Range
Summary Range Years
Country Name
Afghanistan
NaN
2.461666e+09
4.128821e+09
4.583644e+09
5.285466e+09
6.275074e+09
7.057598e+09
9.843842e+09
1.019053e+10
1.248694e+10
1.593680e+10
1.793024e+10
2.053654e+10
2.004633e+10
2.005019e+10
1.970299e+10
AFG
GDP
NaN
2000-2015
Albania
3.632044e+09
4.060759e+09
4.435079e+09
5.746946e+09
7.314865e+09
8.158549e+09
8.992642e+09
1.070101e+10
1.288135e+10
1.204421e+10
1.192695e+10
1.289087e+10
1.231978e+10
1.278103e+10
1.321986e+10
1.139037e+10
ALB
GDP
7.758321e+09
2000-2015
Algeria
5.479025e+10
5.474471e+10
5.676029e+10
6.786383e+10
8.532500e+10
1.031982e+11
1.170273e+11
1.349771e+11
1.710007e+11
1.372110e+11
1.612073e+11
2.000131e+11
2.090474e+11
2.097835e+11
2.139831e+11
1.647795e+11
DZA
GDP
1.099892e+11
2000-2015
American Samoa
NaN
NaN
5.140000e+08
5.270000e+08
5.120000e+08
5.030000e+08
4.960000e+08
5.200000e+08
5.630000e+08
6.780000e+08
5.760000e+08
5.740000e+08
6.440000e+08
6.390000e+08
6.380000e+08
6.410000e+08
ASM
GDP
NaN
2000-2015
Andorra
1.401695e+09
1.484018e+09
1.717485e+09
2.373928e+09
2.916787e+09
3.248215e+09
3.536633e+09
4.010991e+09
4.001201e+09
3.650083e+09
3.346517e+09
3.427023e+09
3.146152e+09
3.248925e+09
NaN
NaN
AND
GDP
NaN
2000-2015
Angola
9.129595e+09
8.936064e+09
1.249735e+10
1.418895e+10
1.964085e+10
2.823371e+10
4.178948e+10
6.044892e+10
8.417803e+10
7.549238e+10
8.247091e+10
1.041159e+11
1.153984e+11
1.249121e+11
1.267769e+11
1.029622e+11
AGO
GDP
9.383265e+10
2000-2015
Antigua and Barbuda
8.254055e+08
7.959765e+08
8.097545e+08
8.502186e+08
9.137104e+08
1.014980e+09
1.149025e+09
1.302389e+09
1.359734e+09
1.217720e+09
1.147942e+09
1.141865e+09
1.216046e+09
1.195885e+09
1.274330e+09
1.355646e+09
ATG
GDP
5.302404e+08
2000-2015
Argentina
2.842038e+11
2.686968e+11
9.772400e+10
1.275870e+11
1.646579e+11
1.987371e+11
2.325573e+11
2.875305e+11
3.615580e+11
3.329765e+11
4.236274e+11
5.301633e+11
5.459824e+11
5.520251e+11
5.263197e+11
5.847115e+11
ARG
GDP
3.005077e+11
2000-2015
Armenia
1.911564e+09
2.118468e+09
2.376335e+09
2.807061e+09
3.576615e+09
4.900470e+09
6.384452e+09
9.206302e+09
1.166204e+10
8.647937e+09
9.260285e+09
1.014211e+10
1.061932e+10
1.112147e+10
1.160951e+10
1.052918e+10
ARM
GDP
8.617619e+09
2000-2015
Aruba
1.873453e+09
1.920263e+09
1.941095e+09
2.021302e+09
2.228279e+09
2.331006e+09
2.421475e+09
2.623726e+09
2.791961e+09
2.498933e+09
2.467704e+09
2.584464e+09
NaN
NaN
NaN
NaN
ABW
GDP
NaN
2000-2015
Australia
4.154462e+11
3.788999e+11
3.946358e+11
4.668532e+11
6.133298e+11
6.937641e+11
7.475726e+11
8.537646e+11
1.055335e+12
9.271683e+11
1.142877e+12
1.390557e+12
1.538194e+12
1.567179e+12
1.459598e+12
1.345383e+12
AUS
GDP
9.299369e+11
2000-2015
Austria
1.964217e+11
1.969536e+11
2.129707e+11
2.607215e+11
2.998572e+11
3.146490e+11
3.343094e+11
3.864590e+11
4.276115e+11
3.975943e+11
3.902119e+11
4.290374e+11
4.074516e+11
4.282484e+11
4.383762e+11
3.769674e+11
AUT
GDP
1.805457e+11
2000-2015
Azerbaijan
5.272617e+09
5.707720e+09
6.235795e+09
7.276013e+09
8.680472e+09
1.324572e+10
2.098302e+10
3.305034e+10
4.885248e+10
4.429149e+10
5.290270e+10
6.595163e+10
6.968432e+10
7.416444e+10
7.524417e+10
5.307437e+10
AZE
GDP
4.780175e+10
2000-2015
Bahamas, The
6.327552e+09
6.516651e+09
6.957996e+09
6.949317e+09
7.094413e+09
7.706222e+09
7.965588e+09
8.318996e+09
8.247000e+09
7.820000e+09
7.910000e+09
7.890000e+09
8.399000e+09
8.522000e+09
8.618000e+09
8.854000e+09
BHS
GDP
2.526448e+09
2000-2015
Bahrain
9.062907e+09
8.976208e+09
9.632155e+09
1.107482e+10
1.315017e+10
1.596873e+10
1.850505e+10
2.173000e+10
2.571088e+10
2.293822e+10
2.571327e+10
2.915745e+10
3.074931e+10
3.289867e+10
3.338771e+10
3.112585e+10
BHR
GDP
2.206294e+10
2000-2015
Bangladesh
5.336979e+10
5.399129e+10
5.472408e+10
6.015893e+10
6.510854e+10
6.944294e+10
7.181908e+10
7.961189e+10
9.163128e+10
1.024778e+11
1.152791e+11
1.286379e+11
1.333557e+11
1.499905e+11
1.728855e+11
1.950786e+11
BGD
GDP
1.417088e+11
2000-2015
Barbados
3.121620e+09
3.116632e+09
3.169613e+09
3.274857e+09
3.514371e+09
3.897467e+09
4.303276e+09
4.546115e+09
4.595265e+09
4.601250e+09
4.446800e+09
4.358900e+09
4.332150e+09
4.371200e+09
4.352700e+09
4.421800e+09
BRB
GDP
1.300180e+09
2000-2015
Belarus
1.273686e+10
1.235482e+10
1.459493e+10
1.782544e+10
2.314159e+10
3.021009e+10
3.696182e+10
4.527575e+10
6.075218e+10
4.920866e+10
5.723190e+10
6.176234e+10
6.568590e+10
7.552754e+10
7.881305e+10
5.645478e+10
BLR
GDP
4.371792e+10
2000-2015
Belgium
2.379049e+11
2.378416e+11
2.588603e+11
3.190034e+11
3.708853e+11
3.873660e+11
4.098131e+11
4.718218e+11
5.186260e+11
4.845527e+11
4.835487e+11
5.270080e+11
4.978841e+11
5.201171e+11
5.317509e+11
4.549913e+11
BEL
GDP
2.170864e+11
2000-2015
Belize
8.320724e+08
8.718606e+08
9.325518e+08
9.903740e+08
1.057846e+09
1.114223e+09
1.217468e+09
1.290573e+09
1.368625e+09
1.336957e+09
1.397113e+09
1.486712e+09
1.573619e+09
1.613706e+09
1.706498e+09
1.742546e+09
BLZ
GDP
9.104734e+08
2000-2015
Benin
2.569187e+09
2.680214e+09
3.054571e+09
3.905366e+09
4.521425e+09
4.803703e+09
5.142381e+09
5.969535e+09
7.132787e+09
7.097199e+09
6.970241e+09
7.814081e+09
8.152554e+09
9.156748e+09
9.707432e+09
8.290987e+09
BEN
GDP
5.721800e+09
2000-2015
Bermuda
3.480219e+09
3.680483e+09
3.937228e+09
4.186525e+09
4.484703e+09
4.868136e+09
5.414299e+09
5.895048e+09
6.109928e+09
5.806378e+09
5.744414e+09
5.550771e+09
5.537537e+09
5.573710e+09
NaN
NaN
BMU
GDP
NaN
2000-2015
Bhutan
4.391582e+08
4.763607e+08
5.370501e+08
6.220261e+08
7.026820e+08
8.188691e+08
8.977315e+08
1.196092e+09
1.258332e+09
1.264758e+09
1.585473e+09
1.820208e+09
1.823692e+09
1.798334e+09
1.958820e+09
2.057948e+09
BTN
GDP
1.618789e+09
2000-2015
Bolivia
8.397913e+09
8.141538e+09
7.905485e+09
8.082365e+09
8.773452e+09
9.549078e+09
1.145187e+10
1.312016e+10
1.667432e+10
1.733999e+10
1.964963e+10
2.396303e+10
2.708450e+10
3.065934e+10
3.299619e+10
3.300020e+10
BOL
GDP
2.460229e+10
2000-2015
Bosnia and Herzegovina
5.505984e+09
5.748991e+09
6.651226e+09
8.370020e+09
1.002284e+10
1.122514e+10
1.286652e+10
1.577642e+10
1.910145e+10
1.760063e+10
1.716428e+10
1.862935e+10
1.720737e+10
1.815429e+10
1.852148e+10
1.617381e+10
BIH
GDP
1.066782e+10
2000-2015
Botswana
5.788330e+09
5.489608e+09
5.438857e+09
7.511582e+09
8.957468e+09
9.931135e+09
1.012694e+10
1.093905e+10
1.094507e+10
1.026713e+10
1.278665e+10
1.568293e+10
1.468628e+10
1.491578e+10
1.625945e+10
1.443061e+10
BWA
GDP
8.642279e+09
2000-2015
Brazil
6.554212e+11
5.593725e+11
5.079627e+11
5.583201e+11
6.693162e+11
8.916300e+11
1.107640e+12
1.397084e+12
1.695825e+12
1.667020e+12
2.208872e+12
2.616202e+12
2.465189e+12
2.472807e+12
2.455993e+12
1.803653e+12
BRA
GDP
1.148231e+12
2000-2015
British Virgin Islands
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
VGB
GDP
NaN
2000-2015
Brunei Darussalam
6.001153e+09
5.601091e+09
5.843329e+09
6.557333e+09
7.872333e+09
9.531403e+09
1.147070e+10
1.224769e+10
1.439310e+10
1.073237e+10
1.370737e+10
1.852532e+10
1.904850e+10
1.809383e+10
1.712313e+10
1.293039e+10
BRN
GDP
6.929242e+09
2000-2015
Bulgaria
1.314810e+10
1.413539e+10
1.636035e+10
2.107478e+10
2.609462e+10
2.982166e+10
3.430445e+10
4.476573e+10
5.466664e+10
5.178345e+10
5.061003e+10
5.741839e+10
5.390303e+10
5.575874e+10
5.673201e+10
5.019912e+10
BGR
GDP
3.705102e+10
2000-2015
Burkina Faso
2.628920e+09
2.812846e+09
3.205592e+09
4.205691e+09
4.838551e+09
5.462709e+09
5.844670e+09
6.771278e+09
8.369637e+09
8.369175e+09
8.979967e+09
1.072406e+10
1.116606e+10
1.193461e+10
1.240069e+10
1.114876e+10
BFA
GDP
8.519839e+09
2000-2015
Burundi
8.704861e+08
8.767947e+08
8.253945e+08
7.846544e+08
9.152573e+08
1.117257e+09
1.273181e+09
1.356078e+09
1.611634e+09
1.739781e+09
2.026864e+09
2.355652e+09
2.472385e+09
2.714506e+09
3.093647e+09
3.097325e+09
BDI
GDP
2.226839e+09
2000-2015
Cabo Verde
5.392273e+08
5.630244e+08
6.209747e+08
8.139638e+08
9.243185e+08
9.719771e+08
1.107891e+09
1.513934e+09
1.789334e+09
1.711817e+09
1.664311e+09
1.864824e+09
1.751889e+09
1.850951e+09
1.858122e+09
1.574289e+09
CPV
GDP
1.035061e+09
2000-2015
Cambodia
3.654032e+09
3.984001e+09
4.284028e+09
4.658247e+09
5.337833e+09
6.293046e+09
7.274596e+09
8.639236e+09
1.035191e+10
1.040185e+10
1.124228e+10
1.282954e+10
1.403838e+10
1.544963e+10
1.677782e+10
1.804995e+10
KHM
GDP
1.439592e+10
2000-2015
Cameroon
9.287367e+09
9.633109e+09
1.087978e+10
1.362174e+10
1.577536e+10
1.658786e+10
1.795307e+10
2.043178e+10
2.332225e+10
2.338114e+10
2.362248e+10
2.658731e+10
2.647206e+10
2.956750e+10
3.205082e+10
2.841595e+10
CMR
GDP
1.912858e+10
2000-2015
Canada
7.422934e+11
7.363798e+11
7.579507e+11
8.923810e+11
1.023196e+12
1.169358e+12
1.315415e+12
1.464977e+12
1.549131e+12
1.371153e+12
1.613464e+12
1.788648e+12
1.824289e+12
1.842628e+12
1.792883e+12
1.552808e+12
CAN
GDP
8.105142e+11
2000-2015
Cayman Islands
NaN
NaN
NaN
NaN
NaN
NaN
3.207033e+09
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
CYM
GDP
NaN
2000-2015
Central African Republic
9.145003e+08
9.318333e+08
9.913879e+08
1.139755e+09
1.270080e+09
1.350301e+09
1.460562e+09
1.698126e+09
1.985239e+09
1.981728e+09
1.986015e+09
2.212700e+09
2.184184e+09
1.518565e+09
1.702899e+09
1.583777e+09
CAF
GDP
6.692765e+08
2000-2015
Chad
1.385058e+09
1.709348e+09
1.987622e+09
2.736667e+09
4.414929e+09
6.646664e+09
7.422103e+09
8.638711e+09
1.035193e+10
9.253484e+09
1.065771e+10
1.215638e+10
1.236807e+10
1.294985e+10
1.392222e+10
1.088880e+10
TCD
GDP
9.503740e+09
2000-2015
Chile
7.786093e+10
7.097992e+10
6.973681e+10
7.564346e+10
9.921039e+10
1.229648e+11
1.547880e+11
1.736060e+11
1.796385e+11
1.723895e+11
2.185376e+11
2.522520e+11
2.671223e+11
2.783843e+11
2.609903e+11
2.425179e+11
CHL
GDP
1.646570e+11
2000-2015
China
1.211346e+12
1.339395e+12
1.470550e+12
1.660288e+12
1.955347e+12
2.285966e+12
2.752132e+12
3.552183e+12
4.598205e+12
5.109954e+12
6.100620e+12
7.572554e+12
8.560547e+12
9.607224e+12
1.048237e+13
1.106466e+13
CHN
GDP
9.853318e+12
2000-2015
Colombia
9.988658e+10
9.820355e+10
9.793339e+10
9.468458e+10
1.170749e+11
1.465663e+11
1.625901e+11
2.074165e+11
2.439824e+11
2.338217e+11
2.870182e+11
3.354152e+11
3.696597e+11
3.801919e+11
3.781957e+11
2.915196e+11
COL
GDP
1.916330e+11
2000-2015
Comoros
2.038464e+08
2.200938e+08
2.467377e+08
3.175623e+08
3.681431e+08
3.803729e+08
4.061119e+08
4.624536e+08
5.231349e+08
5.241573e+08
5.304934e+08
5.862818e+08
5.708659e+08
6.186639e+08
6.477207e+08
5.656898e+08
COM
GDP
3.618433e+08
2000-2015
Congo, Dem. Rep.
1.908805e+10
7.438189e+09
8.728039e+09
8.937567e+09
1.029748e+10
1.196448e+10
1.429651e+10
1.636403e+10
1.920606e+10
1.826277e+10
2.052329e+10
2.384901e+10
2.746322e+10
3.001481e+10
3.402812e+10
3.618852e+10
ZAR
GDP
1.710047e+10
2000-2015
Congo, Rep.
3.219911e+09
2.794260e+09
3.019994e+09
3.495869e+09
4.648629e+09
6.087003e+09
7.731261e+09
8.394688e+09
1.185901e+10
9.593537e+09
1.200788e+10
1.442561e+10
1.367793e+10
1.408585e+10
1.417744e+10
8.553155e+09
COG
GDP
5.333244e+09
2000-2015
Costa Rica
1.494951e+10
1.591336e+10
1.650480e+10
1.719587e+10
1.852977e+10
1.995216e+10
2.260043e+10
2.674387e+10
3.061293e+10
3.056236e+10
3.726864e+10
4.226270e+10
4.647313e+10
4.974509e+10
5.065600e+10
5.484010e+10
CRI
GDP
3.989059e+10
2000-2015
Cote d'Ivoire
1.071702e+10
1.119256e+10
1.234692e+10
1.530660e+10
1.655444e+10
1.708493e+10
1.780089e+10
2.034364e+10
2.422490e+10
2.427749e+10
2.488451e+10
2.538162e+10
2.704056e+10
3.127305e+10
3.537260e+10
3.282852e+10
CIV
GDP
2.211149e+10
2000-2015
Croatia
2.177427e+10
2.328967e+10
2.687850e+10
3.465811e+10
4.157453e+10
4.541608e+10
5.045358e+10
6.009316e+10
7.048145e+10
6.270310e+10
5.966543e+10
6.223675e+10
5.648530e+10
5.776987e+10
5.708037e+10
4.867633e+10
HRV
GDP
2.690206e+10
2000-2015
Cuba
3.056540e+10
3.168240e+10
3.359050e+10
3.590120e+10
3.820300e+10
4.264384e+10
5.274280e+10
5.860390e+10
6.080630e+10
6.208000e+10
6.432800e+10
6.899000e+10
7.314100e+10
7.714800e+10
8.065610e+10
8.713280e+10
CUB
GDP
5.656740e+10
2000-2015
Cyprus
1.018332e+10
1.056730e+10
1.161827e+10
1.457690e+10
1.742238e+10
1.870315e+10
2.040371e+10
2.407747e+10
2.783946e+10
2.594262e+10
2.556225e+10
2.742716e+10
2.501221e+10
2.405497e+10
2.330821e+10
1.955994e+10
CYP
GDP
9.376625e+09
2000-2015
Czech Republic
6.147427e+10
6.737562e+10
8.169665e+10
9.930033e+10
1.189760e+11
1.359902e+11
1.552130e+11
1.888182e+11
2.352048e+11
2.057298e+11
2.070164e+11
2.279483e+11
2.073764e+11
2.094024e+11
2.078183e+11
1.851564e+11
CZE
GDP
1.236821e+11
2000-2015
Denmark
1.641588e+11
1.647914e+11
1.786352e+11
2.180960e+11
2.513730e+11
2.644673e+11
2.828849e+11
3.194234e+11
3.533611e+11
3.212414e+11
3.219954e+11
3.440032e+11
3.271489e+11
3.435844e+11
3.522970e+11
3.013078e+11
DNK
GDP
1.371490e+11
2000-2015
Djibouti
5.512309e+08
5.724174e+08
5.911220e+08
6.220447e+08
6.660721e+08
7.086332e+08
7.688737e+08
8.479189e+08
9.991053e+08
1.049111e+09
1.128612e+09
1.239145e+09
1.353633e+09
1.455000e+09
1.588000e+09
1.727000e+09
DJI
GDP
1.175769e+09
2000-2015
Dominica
3.358458e+08
3.431194e+08
3.376957e+08
3.500912e+08
3.747715e+08
3.703704e+08
3.903704e+08
4.213759e+08
4.581902e+08
4.890743e+08
4.938244e+08
5.009884e+08
4.859056e+08
5.084471e+08
5.281787e+08
5.172190e+08
DMA
GDP
1.813731e+08
2000-2015
Dominican Republic
2.399606e+10
2.489252e+10
2.657162e+10
2.127717e+10
2.203923e+10
3.400403e+10
3.595285e+10
4.416968e+10
4.828897e+10
4.837656e+10
5.395458e+10
5.774668e+10
6.061365e+10
6.196594e+10
6.523103e+10
6.810262e+10
DOM
GDP
4.410655e+10
2000-2015
Ecuador
1.832776e+10
2.446832e+10
2.854894e+10
3.243286e+10
3.659166e+10
4.150708e+10
4.680204e+10
5.100778e+10
6.176264e+10
6.251969e+10
6.955537e+10
7.927666e+10
8.792454e+10
9.512966e+10
1.022923e+11
1.001768e+11
ECU
GDP
8.184904e+10
2000-2015
Egypt, Arab Rep.
9.983854e+10
9.763201e+10
8.785068e+10
8.292450e+10
7.884519e+10
8.968573e+10
1.074840e+11
1.304790e+11
1.628182e+11
1.889824e+11
2.188883e+11
2.360019e+11
2.793728e+11
2.885862e+11
3.055297e+11
3.326980e+11
EGY
GDP
2.328595e+11
2000-2015
El Salvador
1.313410e+10
1.381270e+10
1.430670e+10
1.504670e+10
1.579830e+10
1.709380e+10
1.855070e+10
2.010490e+10
2.143095e+10
2.066103e+10
2.141833e+10
2.313904e+10
2.381360e+10
2.435093e+10
2.505423e+10
2.605234e+10
SLV
GDP
1.291824e+10
2000-2015
Equatorial Guinea
1.045998e+09
1.461139e+09
1.806743e+09
2.484746e+09
4.410764e+09
8.217369e+09
1.008653e+10
1.307172e+10
1.974989e+10
1.502780e+10
1.629854e+10
2.132940e+10
2.238963e+10
2.194260e+10
2.146199e+10
1.216212e+10
GNQ
GDP
1.111612e+10
2000-2015
Eritrea
7.063708e+08
7.523685e+08
7.293214e+08
8.702477e+08
1.109054e+09
1.098426e+09
1.211162e+09
1.317974e+09
1.380189e+09
1.856696e+09
2.117040e+09
2.607740e+09
NaN
NaN
NaN
NaN
ERI
GDP
NaN
2000-2015
Estonia
5.685775e+09
6.245070e+09
7.322070e+09
9.833871e+09
1.205920e+10
1.400609e+10
1.696363e+10
2.223706e+10
2.419404e+10
1.965249e+10
1.949094e+10
2.317024e+10
2.304386e+10
2.508119e+10
2.621394e+10
2.246047e+10
EST
GDP
1.677470e+10
2000-2015
Ethiopia
8.242392e+09
8.231326e+09
7.850809e+09
8.623691e+09
1.013119e+10
1.240114e+10
1.528086e+10
1.970762e+10
2.706691e+10
3.243739e+10
2.993379e+10
3.195276e+10
4.331072e+10
4.764821e+10
5.561223e+10
6.446442e+10
ETH
GDP
5.622203e+10
2000-2015
European Union
8.899281e+12
9.000713e+12
9.811089e+12
1.194576e+13
1.379555e+13
1.442659e+13
1.538873e+13
1.778130e+13
1.911780e+13
1.708088e+13
1.697786e+13
1.834054e+13
1.727172e+13
1.800271e+13
1.858824e+13
1.633484e+13
EUN
GDP
7.435563e+12
2000-2015
Fiji
1.684110e+09
1.660102e+09
1.842691e+09
2.315936e+09
2.727507e+09
3.006725e+09
3.102741e+09
3.405051e+09
3.523186e+09
2.870625e+09
3.140509e+09
3.774531e+09
3.972013e+09
4.190143e+09
4.469810e+09
4.391065e+09
FJI
GDP
2.706955e+09
2000-2015
Finland
1.255399e+11
1.292501e+11
1.395530e+11
1.710711e+11
1.967681e+11
2.044360e+11
2.165525e+11
2.553846e+11
2.837425e+11
2.514990e+11
2.477998e+11
2.736742e+11
2.567065e+11
2.699801e+11
2.726093e+11
2.323617e+11
FIN
GDP
1.068218e+11
2000-2015
France
1.368438e+12
1.382218e+12
1.500338e+12
1.848124e+12
2.124112e+12
2.203679e+12
2.325012e+12
2.663113e+12
2.923466e+12
2.693827e+12
2.646837e+12
2.862680e+12
2.681416e+12
2.808511e+12
2.849305e+12
2.433562e+12
FRA
GDP
1.065124e+12
2000-2015
French Polynesia
3.447543e+09
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
PYF
GDP
NaN
2000-2015
Gabon
5.067865e+09
5.018874e+09
5.310381e+09
6.497306e+09
7.756294e+09
9.458885e+09
1.015404e+10
1.243896e+10
1.550857e+10
1.206514e+10
1.435858e+10
1.818648e+10
1.717145e+10
1.759072e+10
1.817972e+10
1.426203e+10
GAB
GDP
9.194167e+09
2000-2015
Gambia, The
7.829154e+08
6.874088e+08
5.782360e+08
4.870388e+08
5.787853e+08
6.241747e+08
6.550687e+08
7.988709e+08
9.657691e+08
9.006397e+08
9.524290e+08
9.042566e+08
9.125697e+08
9.037793e+08
8.491226e+08
9.387947e+08
GMB
GDP
1.558793e+08
2000-2015
Georgia
3.057453e+09
3.219488e+09
3.395779e+09
3.991375e+09
5.125274e+09
6.410941e+09
7.745406e+09
1.017287e+10
1.279504e+10
1.076681e+10
1.163854e+10
1.443462e+10
1.584647e+10
1.614005e+10
1.650931e+10
1.399355e+10
GEO
GDP
1.093609e+10
2000-2015
Germany
1.949954e+12
1.950649e+12
2.079136e+12
2.505734e+12
2.819245e+12
2.861410e+12
3.002446e+12
3.439953e+12
3.752366e+12
3.418005e+12
3.417095e+12
3.757698e+12
3.543984e+12
3.752514e+12
3.879277e+12
3.363600e+12
DEU
GDP
1.413646e+12
2000-2015
Ghana
4.983024e+09
5.314910e+09
6.166330e+09
7.632407e+09
8.881369e+09
1.073163e+10
2.040926e+10
2.475882e+10
2.852689e+10
2.597785e+10
3.217477e+10
3.956629e+10
4.193973e+10
4.780507e+10
3.861654e+10
3.754336e+10
GHA
GDP
3.256034e+10
2000-2015
Gibraltar
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
GIB
GDP
NaN
2000-2015
Greece
1.301338e+11
1.361914e+11
1.538309e+11
2.019243e+11
2.405213e+11
2.477830e+11
2.733177e+11
3.184979e+11
3.544608e+11
3.300003e+11
2.993616e+11
2.877978e+11
2.456707e+11
2.398620e+11
2.360798e+11
1.948602e+11
GRC
GDP
6.472634e+10
2000-2015
Greenland
1.068031e+09
1.086173e+09
1.169139e+09
1.407866e+09
1.621822e+09
1.656172e+09
1.818760e+09
2.049139e+09
2.310743e+09
2.324871e+09
2.306502e+09
2.515246e+09
2.408666e+09
2.483397e+09
2.551127e+09
2.220381e+09
GRL
GDP
1.152350e+09
2000-2015
Grenada
5.200444e+08
5.204442e+08
5.403369e+08
5.910184e+08
5.991186e+08
6.953703e+08
6.985185e+08
7.585185e+08
8.259259e+08
7.712781e+08
7.710159e+08
7.786487e+08
7.998821e+08
8.425713e+08
9.114815e+08
9.840741e+08
GRD
GDP
4.640297e+08
2000-2015
Guam
NaN
NaN
3.385000e+09
3.560000e+09
3.857000e+09
4.197000e+09
4.213000e+09
4.375000e+09
4.621000e+09
4.781000e+09
4.895000e+09
4.928000e+09
5.199000e+09
5.364000e+09
5.566000e+09
5.734000e+09
GUM
GDP
NaN
2000-2015
Guatemala
1.928893e+10
1.870280e+10
2.077667e+10
2.191771e+10
2.396528e+10
2.721138e+10
3.023125e+10
3.411311e+10
3.913689e+10
3.773399e+10
4.133860e+10
4.765484e+10
5.038845e+10
5.385106e+10
5.872232e+10
6.376760e+10
GTM
GDP
4.447867e+10
2000-2015
Guinea
2.995361e+09
2.833443e+09
2.949637e+09
3.446442e+09
3.666349e+09
2.937072e+09
2.931625e+09
4.134173e+09
4.515825e+09
4.609924e+09
4.735956e+09
5.067360e+09
5.667230e+09
6.231725e+09
6.624068e+09
6.699204e+09
GIN
GDP
3.703843e+09
2000-2015
Guinea-Bissau
3.701739e+08
3.922782e+08
4.158435e+08
4.763883e+08
5.311094e+08
5.867919e+08
5.918299e+08
6.956063e+08
8.641367e+08
8.258287e+08
8.463325e+08
1.105498e+09
9.955821e+08
1.026664e+09
1.109007e+09
1.056777e+09
GNB
GDP
6.866030e+08
2000-2015
Guyana
7.126679e+08
6.962815e+08
7.224609e+08
7.419293e+08
7.859188e+08
8.248806e+08
1.458447e+09
1.740335e+09
1.922598e+09
2.025565e+09
2.259288e+09
2.576602e+09
2.851154e+09
2.990007e+09
3.077086e+09
3.179104e+09
GUY
GDP
2.466436e+09
2000-2015
Haiti
3.953840e+09
3.596448e+09
3.472194e+09
2.960306e+09
3.537721e+09
4.310356e+09
4.756204e+09
5.885322e+09
6.548531e+09
6.584649e+09
6.622542e+09
7.516834e+09
7.890217e+09
8.452509e+09
8.776361e+09
8.724656e+09
HTI
GDP
4.770817e+09
2000-2015
Honduras
7.103529e+09
7.565870e+09
7.775078e+09
8.140271e+09
8.772194e+09
9.672036e+09
1.084174e+10
1.227550e+10
1.378972e+10
1.458750e+10
1.583934e+10
1.771028e+10
1.852855e+10
1.849973e+10
1.975653e+10
2.084431e+10
HND
GDP
1.374078e+10
2000-2015
Hong Kong SAR, China
1.716682e+11
1.694032e+11
1.663492e+11
1.613845e+11
1.690998e+11
1.815701e+11
1.935363e+11
2.115974e+11
2.192797e+11
2.140464e+11
2.286377e+11
2.485136e+11
2.626294e+11
2.756969e+11
2.914594e+11
3.094039e+11
HKG
GDP
1.377357e+11
2000-2015
Hungary
4.720947e+10
5.369673e+10
6.756129e+10
8.505028e+10
1.036945e+11
1.125890e+11
1.148012e+11
1.391982e+11
1.572910e+11
1.299654e+11
1.302556e+11
1.400916e+11
1.273211e+11
1.346805e+11
1.392946e+11
1.217152e+11
HUN
GDP
7.450573e+10
2000-2015
Iceland
8.946080e+09
8.146074e+09
9.199644e+09
1.130408e+10
1.370332e+10
1.669121e+10
1.704325e+10
2.129501e+10
1.764038e+10
1.288707e+10
1.325482e+10
1.467465e+10
1.421858e+10
1.547926e+10
1.717896e+10
1.678371e+10
ISL
GDP
7.837635e+09
2000-2015
India
4.621468e+11
4.789655e+11
5.080690e+11
5.995929e+11
6.996889e+11
8.089011e+11
9.203165e+11
1.201112e+12
1.186953e+12
1.323940e+12
1.656617e+12
1.823050e+12
1.827638e+12
1.856722e+12
2.035393e+12
2.111751e+12
IND
GDP
1.649604e+12
2000-2015
Indonesia
1.650210e+11
1.604469e+11
1.956606e+11
2.347725e+11
2.568369e+11
2.858686e+11
3.645705e+11
4.322167e+11
5.102286e+11
5.395801e+11
7.550942e+11
8.929691e+11
9.178699e+11
9.125241e+11
8.908148e+11
8.612564e+11
IDN
GDP
6.962353e+11
2000-2015
Iran, Islamic Rep.
1.095917e+11
1.268788e+11
1.286269e+11
1.535448e+11
1.836972e+11
2.198460e+11
2.586457e+11
3.374745e+11
3.971896e+11
3.989781e+11
4.677902e+11
5.920378e+11
5.872094e+11
5.116209e+11
4.253261e+11
3.934361e+11
IRN
GDP
2.838444e+11
2000-2015
Iraq
NaN
NaN
NaN
NaN
3.662790e+10
4.995489e+10
6.514029e+10
8.884005e+10
1.316137e+11
1.116609e+11
1.385167e+11
1.857497e+11
2.180010e+11
2.346484e+11
2.346484e+11
1.796402e+11
IRQ
GDP
NaN
2000-2015
Ireland
9.985507e+10
1.091191e+11
1.279417e+11
1.642856e+11
1.938709e+11
2.116848e+11
2.321675e+11
2.700430e+11
2.749190e+11
2.357660e+11
2.213435e+11
2.405907e+11
2.258192e+11
2.392712e+11
2.562713e+11
2.837160e+11
IRL
GDP
1.838609e+11
2000-2015
Israel
1.323967e+11
1.307516e+11
1.210927e+11
1.267497e+11
1.354186e+11
1.428375e+11
1.545114e+11
1.795643e+11
2.167603e+11
2.080688e+11
2.337547e+11
2.613748e+11
2.576418e+11
2.933148e+11
3.087694e+11
2.994157e+11
ISR
GDP
1.670190e+11
2000-2015
Italy
1.141760e+12
1.162318e+12
1.266511e+12
1.569650e+12
1.798315e+12
1.852662e+12
1.942634e+12
2.203053e+12
2.390729e+12
2.185160e+12
2.125058e+12
2.276292e+12
2.072823e+12
2.130491e+12
2.151733e+12
1.824902e+12
ITA
GDP
6.831422e+11
2000-2015
Jamaica
8.929376e+09
9.087919e+09
9.694162e+09
9.399453e+09
1.015098e+10
1.120442e+10
1.190553e+10
1.282409e+10
1.367855e+10
1.203900e+10
1.319223e+10
1.444046e+10
1.480243e+10
1.427656e+10
1.389756e+10
1.426200e+10
JAM
GDP
5.332620e+09
2000-2015
Japan
4.887520e+12
4.303544e+12
4.115116e+12
4.445658e+12
4.815149e+12
4.755411e+12
4.530377e+12
4.515265e+12
5.037908e+12
5.231383e+12
5.700098e+12
6.157460e+12
6.203213e+12
5.155717e+12
4.848733e+12
4.383076e+12
JPN
GDP
-5.044434e+11
2000-2015
Jordan
8.460424e+09
8.975690e+09
9.582453e+09
1.019566e+10
1.141139e+10
1.258867e+10
1.505693e+10
1.711059e+10
2.197200e+10
2.382023e+10
2.642538e+10
2.884026e+10
3.093728e+10
3.359384e+10
3.582693e+10
3.751741e+10
JOR
GDP
2.905699e+10
2000-2015
Kazakhstan
1.829199e+10
2.215269e+10
2.463660e+10
3.083369e+10
4.315165e+10
5.712367e+10
8.100388e+10
1.048499e+11
1.334416e+11
1.153087e+11
1.480473e+11
1.926265e+11
2.079986e+11
2.366346e+11
2.214156e+11
1.843884e+11
KAZ
GDP
1.660964e+11
2000-2015
Kenya
1.270536e+10
1.298601e+10
1.314774e+10
1.490452e+10
1.609534e+10
1.873790e+10
2.582552e+10
3.195820e+10
3.589515e+10
3.702151e+10
3.999966e+10
4.195343e+10
5.041275e+10
5.509734e+10
6.144535e+10
6.376754e+10
KEN
GDP
5.106218e+10
2000-2015
Kiribati
6.725417e+07
6.310127e+07
7.219646e+07
9.023186e+07
1.023670e+08
1.121339e+08
1.085456e+08
1.307549e+08
1.391255e+08
1.304654e+08
1.532759e+08
1.771421e+08
1.880457e+08
1.871536e+08
1.860670e+08
1.601219e+08
KIR
GDP
9.286775e+07
2000-2015
Korea, Rep.
5.616331e+11
5.330521e+11
6.090201e+11
6.805207e+11
7.648806e+11
8.981372e+11
1.011797e+12
1.122679e+12
1.002219e+12
9.019350e+11
1.094499e+12
1.202464e+12
1.222807e+12
1.305605e+12
1.411334e+12
1.382764e+12
KOR
GDP
8.211309e+11
2000-2015
Kuwait
3.771186e+10
3.489077e+10
3.813755e+10
4.787584e+10
5.944011e+10
8.079795e+10
1.015507e+11
1.146411e+11
1.473958e+11
1.058999e+11
1.154191e+11
1.540275e+11
1.740700e+11
1.741615e+11
1.626318e+11
1.140412e+11
KWT
GDP
7.632935e+10
2000-2015
Kyrgyz Republic
1.369693e+09
1.525112e+09
1.605641e+09
1.919013e+09
2.211535e+09
2.460248e+09
2.834169e+09
3.802566e+09
5.139958e+09
4.690062e+09
4.794358e+09
6.197766e+09
6.605140e+09
7.335028e+09
7.468097e+09
6.678178e+09
KGZ
GDP
5.308485e+09
2000-2015
Lao PDR
1.731198e+09
1.768619e+09
1.758177e+09
2.023324e+09
2.366398e+09
2.735559e+09
3.452883e+09
4.222963e+09
5.443915e+09
5.832915e+09
7.127793e+09
8.261299e+09
1.019137e+10
1.194216e+10
1.326830e+10
1.439032e+10
LAO
GDP
1.265913e+10
2000-2015
Latvia
7.937759e+09
8.350253e+09
9.546442e+09
1.174843e+10
1.437327e+10
1.692250e+10
2.144702e+10
3.090140e+10
3.559602e+10
2.616985e+10
2.375737e+10
2.822355e+10
2.812000e+10
3.025457e+10
3.135225e+10
2.702604e+10
LVA
GDP
1.908828e+10
2000-2015
Lebanon
1.726036e+10
1.764975e+10
1.915224e+10
2.008292e+10
2.095522e+10
2.128756e+10
2.179635e+10
2.457711e+10
2.882985e+10
3.513964e+10
3.800995e+10
4.007894e+10
4.320510e+10
4.435242e+10
4.573095e+10
4.708470e+10
LBN
GDP
2.982434e+10
2000-2015
Lesotho
8.872953e+08
8.257070e+08
7.757807e+08
1.157833e+09
1.511237e+09
1.682351e+09
1.800106e+09
1.820597e+09
1.868776e+09
1.864005e+09
2.394097e+09
2.791546e+09
2.678243e+09
2.532392e+09
2.520952e+09
2.335195e+09
LSO
GDP
1.447900e+09
2000-2015
Liberia
5.290646e+08
5.210000e+08
5.430000e+08
4.160000e+08
4.747000e+08
5.500000e+08
6.040289e+08
7.390272e+08
8.500405e+08
1.155147e+09
1.292697e+09
1.545400e+09
1.735500e+09
1.946500e+09
2.013000e+09
2.034000e+09
LBR
GDP
1.504935e+09
2000-2015
Libya
3.827021e+10
3.411006e+10
2.048189e+10
2.626562e+10
3.312231e+10
4.733415e+10
5.496194e+10
6.751624e+10
8.714041e+10
6.302832e+10
7.477344e+10
3.469940e+10
NaN
NaN
NaN
NaN
LBY
GDP
NaN
2000-2015
Liechtenstein
2.483953e+09
2.491823e+09
2.688631e+09
3.070691e+09
3.454363e+09
3.659252e+09
4.000239e+09
4.601300e+09
5.081433e+09
4.504549e+09
5.082366e+09
5.739977e+09
5.456009e+09
6.391736e+09
6.663501e+09
NaN
LIE
GDP
NaN
2000-2015
Lithuania
1.153921e+10
1.225250e+10
1.427836e+10
1.880258e+10
2.264993e+10
2.612558e+10
3.021606e+10
3.973818e+10
4.785055e+10
3.744067e+10
3.712052e+10
4.347688e+10
4.284790e+10
4.647365e+10
4.854525e+10
4.140202e+10
LTU
GDP
2.986281e+10
2000-2015
Luxembourg
2.126351e+10
2.127242e+10
2.361633e+10
2.955733e+10
3.468528e+10
3.734739e+10
4.241431e+10
5.088813e+10
5.584969e+10
5.137054e+10
5.321248e+10
6.000463e+10
5.667796e+10
6.180818e+10
6.629806e+10
5.804824e+10
LUX
GDP
3.678473e+10
2000-2015
Macao SAR, China
6.720492e+09
6.811228e+09
7.322678e+09
8.195033e+09
1.058562e+10
1.209222e+10
1.478966e+10
1.834045e+10
2.091744e+10
2.147552e+10
2.812364e+10
3.670986e+10
4.303158e+10
5.155208e+10
5.534800e+10
4.541528e+10
MAC
GDP
3.869479e+10
2000-2015
Macedonia, FYR
3.772851e+09
3.709638e+09
4.018365e+09
4.946293e+09
5.682719e+09
6.258601e+09
6.861222e+09
8.336478e+09
9.909548e+09
9.401731e+09
9.407169e+09
1.049463e+10
9.745251e+09
1.081771e+10
1.136227e+10
1.005166e+10
MKD
GDP
6.278808e+09
2000-2015
Madagascar
3.877674e+09
4.529575e+09
4.397255e+09
5.474030e+09
4.363934e+09
5.039293e+09
5.515884e+09
7.342923e+09
9.413003e+09
8.550364e+09
8.729936e+09
9.892702e+09
9.919780e+09
1.060169e+10
1.067352e+10
9.738652e+09
MDG
GDP
5.860979e+09
2000-2015
Malawi
1.743506e+09
1.716503e+09
3.495748e+09
3.208837e+09
3.476094e+09
3.655910e+09
3.997853e+09
4.432193e+09
5.320925e+09
6.190992e+09
6.959697e+09
8.003300e+09
6.028471e+09
5.518902e+09
6.054750e+09
6.373201e+09
MWI
GDP
4.629695e+09
2000-2015
Malaysia
9.378974e+10
9.278395e+10
1.008453e+11
1.102024e+11
1.247497e+11
1.435341e+11
1.626910e+11
1.935478e+11
2.308136e+11
2.022576e+11
2.550166e+11
2.979520e+11
3.144428e+11
3.232768e+11
3.380690e+11
2.962832e+11
MYS
GDP
2.024935e+11
2000-2015
Maldives
6.243371e+08
8.701797e+08
8.970312e+08
1.043403e+09
1.202240e+09
1.119806e+09
1.474698e+09
1.745999e+09
2.109961e+09
2.149258e+09
2.323402e+09
2.449577e+09
2.518312e+09
2.795148e+09
3.094198e+09
3.435245e+09
MDV
GDP
2.810908e+09
2000-2015
Mali
2.954130e+09
3.465306e+09
3.889758e+09
4.703504e+09
5.444474e+09
6.245032e+09
6.899800e+09
8.145695e+09
9.750823e+09
1.018102e+10
1.067875e+10
1.297811e+10
1.244275e+10
1.281325e+10
1.400407e+10
1.274669e+10
MLI
GDP
9.792559e+09
2000-2015
Malta
4.306192e+09
4.331871e+09
4.689833e+09
5.456584e+09
6.062780e+09
6.394851e+09
6.757120e+09
7.880509e+09
8.977150e+09
8.528202e+09
8.741060e+09
9.500002e+09
9.198987e+09
1.013142e+10
1.118879e+10
1.028701e+10
MLT
GDP
5.980815e+09
2000-2015
Marshall Islands
1.109377e+08
1.151521e+08
1.247351e+08
1.268876e+08
1.311064e+08
1.377445e+08
1.436566e+08
1.508516e+08
1.529011e+08
1.526312e+08
1.647513e+08
1.726749e+08
1.850558e+08
1.909920e+08
1.831141e+08
1.794326e+08
MHL
GDP
6.849490e+07
2000-2015
Mauritania
1.293654e+09
1.295539e+09
1.324427e+09
1.563075e+09
1.833445e+09
2.184445e+09
3.040717e+09
3.356757e+09
3.978426e+09
3.670516e+09
4.343665e+09
5.179690e+09
5.225533e+09
5.724228e+09
5.391476e+09
4.844224e+09
MRT
GDP
3.550569e+09
2000-2015
Mauritius
4.582555e+09
4.536538e+09
4.767303e+09
5.609831e+09
6.385695e+09
6.283803e+09
7.028803e+09
8.150139e+09
9.990370e+09
9.128843e+09
1.000367e+10
1.151839e+10
1.166869e+10
1.212964e+10
1.280345e+10
1.168176e+10
MUS
GDP
7.099206e+09
2000-2015
Mexico
6.836480e+11
7.247036e+11
7.415595e+11
7.132842e+11
7.702676e+11
8.663458e+11
9.652812e+11
1.043471e+12
1.101275e+12
8.949487e+11
1.051129e+12
1.171188e+12
1.186598e+12
1.261982e+12
1.298399e+12
1.151037e+12
MEX
GDP
4.673892e+11
2000-2015
Micronesia, Fed. Sts.
2.332263e+08
2.400519e+08
2.415434e+08
2.449910e+08
2.395633e+08
2.498456e+08
2.529912e+08
2.558908e+08
2.613396e+08
2.775109e+08
2.941172e+08
3.102875e+08
3.258352e+08
3.157256e+08
3.180720e+08
3.149711e+08
FSM
GDP
8.174480e+07
2000-2015
Moldova
1.288429e+09
1.480657e+09
1.661818e+09
1.980902e+09
2.598231e+09
2.988338e+09
3.408272e+09
4.401154e+09
6.054806e+09
5.439422e+09
5.811604e+09
7.015206e+09
7.284687e+09
7.985350e+09
7.983271e+09
6.512900e+09
MDA
GDP
5.224470e+09
2000-2015
Monaco
2.647884e+09
2.671401e+09
2.905973e+09
3.588989e+09
4.110348e+09
4.280073e+09
4.663488e+09
5.974372e+09
6.919241e+09
5.557245e+09
5.350675e+09
6.074884e+09
NaN
NaN
NaN
NaN
MCO
GDP
NaN
2000-2015
Mongolia
1.136896e+09
1.267998e+09
1.396556e+09
1.595297e+09
1.992067e+09
2.523472e+09
3.414056e+09
4.235000e+09
5.623216e+09
4.583850e+09
7.189482e+09
1.040980e+10
1.229277e+10
1.258212e+10
1.222651e+10
1.174134e+10
MNG
GDP
1.060444e+10
2000-2015
Montenegro
9.842796e+08
1.159860e+09
1.284446e+09
1.707678e+09
2.073256e+09
2.257174e+09
2.696021e+09
3.668857e+09
4.519732e+09
4.141382e+09
4.139192e+09
4.538198e+09
4.087725e+09
4.464260e+09
4.587929e+09
4.019889e+09
MNE
GDP
3.035610e+09
2000-2015
Morocco
3.885725e+10
3.945958e+10
4.223684e+10
5.206406e+10
5.962602e+10
6.234302e+10
6.864083e+10
7.904129e+10
9.250726e+10
9.289732e+10
9.321675e+10
1.013705e+11
9.826631e+10
1.068256e+11
1.098814e+11
1.005933e+11
MAR
GDP
6.173603e+10
2000-2015
Mozambique
5.016469e+09
4.766929e+09
5.031511e+09
5.597368e+09
6.831809e+09
7.723846e+09
8.312079e+09
9.366742e+09
1.149484e+10
1.091170e+10
1.015424e+10
1.313117e+10
1.453428e+10
1.601885e+10
1.696113e+10
1.479840e+10
MOZ
GDP
9.781931e+09
2000-2015
Myanmar
8.905066e+09
6.477791e+09
6.777633e+09
1.046711e+10
1.056735e+10
1.198697e+10
1.450255e+10
2.018248e+10
3.186255e+10
3.690618e+10
4.954081e+10
5.997733e+10
5.973112e+10
6.013285e+10
6.557473e+10
6.260091e+10
MMR
GDP
5.369584e+10
2000-2015
Namibia
3.908662e+09
3.546784e+09
3.361251e+09
4.931312e+09
6.606859e+09
7.261334e+09
7.978734e+09
8.740866e+09
8.486722e+09
8.876191e+09
1.128219e+10
1.240963e+10
1.301627e+10
1.271337e+10
1.285396e+10
1.149151e+10
NAM
GDP
7.582846e+09
2000-2015
Nauru
NaN
NaN
NaN
NaN
NaN
NaN
NaN
2.043274e+07
3.933357e+07
4.429095e+07
4.924881e+07
7.275180e+07
1.038120e+08
1.086015e+08
1.170204e+08
1.004598e+08
NRU
GDP
NaN
2000-2015
Nepal
5.494252e+09
6.007061e+09
6.050876e+09
6.330473e+09
7.273938e+09
8.130258e+09
9.043715e+09
1.032562e+10
1.254544e+10
1.285499e+10
1.600266e+10
1.891357e+10
1.885151e+10
1.927117e+10
2.000297e+10
2.131355e+10
NPL
GDP
1.581930e+10
2000-2015
Netherlands
4.128073e+11
4.265736e+11
4.653689e+11
5.718634e+11
6.505327e+11
6.785338e+11
7.266491e+11
8.394197e+11
9.362282e+11
8.579328e+11
8.363899e+11
8.937573e+11
8.289468e+11
8.666800e+11
8.796351e+11
7.503181e+11
NLD
GDP
3.375108e+11
2000-2015
New Caledonia
2.682347e+09
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NCL
GDP
NaN
2000-2015
New Zealand
5.262328e+10
5.387243e+10
6.662822e+10
8.825089e+10
1.039059e+11
1.147194e+11
1.116069e+11
1.373146e+11
1.332797e+11
1.213374e+11
1.465809e+11
1.684620e+11
1.761929e+11
1.905211e+11
2.006963e+11
1.755644e+11
NZL
GDP
1.229411e+11
2000-2015
Nicaragua
5.107329e+09
5.323147e+09
5.224213e+09
5.322455e+09
5.795568e+09
6.321336e+09
6.763672e+09
7.423377e+09
8.496966e+09
8.298695e+09
8.758622e+09
9.774317e+09
1.053200e+10
1.098297e+10
1.188044e+10
1.274774e+10
NIC
GDP
7.640413e+09
2000-2015
Niger
1.798374e+09
1.945328e+09
2.170482e+09
2.731416e+09
3.052899e+09
3.405135e+09
3.646728e+09
4.291363e+09
5.403364e+09
5.397122e+09
5.718590e+09
6.409170e+09
6.942210e+09
7.667952e+09
8.245312e+09
7.142951e+09
NER
GDP
5.344577e+09
2000-2015
Nigeria
4.638601e+10
4.413799e+10
5.911685e+10
6.765581e+10
8.784542e+10
1.122484e+11
1.454298e+11
1.664512e+11
2.080648e+11
1.694813e+11
3.690625e+11
4.117438e+11
4.609538e+11
5.149663e+11
5.684989e+11
4.810662e+11
NGA
GDP
4.346801e+11
2000-2015
Northern Mariana Islands
NaN
NaN
1.284000e+09
1.239000e+09
1.210000e+09
1.061000e+09
9.900000e+08
9.380000e+08
9.390000e+08
7.950000e+08
7.990000e+08
7.330000e+08
7.510000e+08
7.800000e+08
8.360000e+08
9.220000e+08
MNP
GDP
NaN
2000-2015
Norway
1.713156e+11
1.740032e+11
1.954183e+11
2.287524e+11
2.643575e+11
3.087221e+11
3.454247e+11
4.008839e+11
4.619468e+11
3.863839e+11
4.285271e+11
4.981568e+11
5.097049e+11
5.227462e+11
4.983398e+11
3.865784e+11
NOR
GDP
2.152628e+11
2000-2015
Oman
1.950741e+10
1.945202e+10
2.014278e+10
2.163381e+10
2.476359e+10
3.108192e+10
3.721586e+10
4.208531e+10
6.090533e+10
4.838830e+10
5.864162e+10
6.793731e+10
7.668958e+10
7.893859e+10
8.103440e+10
6.983177e+10
OMN
GDP
5.032436e+10
2000-2015
Pakistan
7.395237e+10
7.230974e+10
7.230682e+10
8.324480e+10
9.797777e+10
1.095021e+11
1.372641e+11
1.523857e+11
1.700778e+11
1.681528e+11
1.774069e+11
2.135874e+11
2.243836e+11
2.312186e+11
2.443609e+11
2.710499e+11
PAK
GDP
1.970975e+11
2000-2015
Palau
1.493000e+08
1.600000e+08
1.635000e+08
1.599000e+08
1.753000e+08
1.933000e+08
1.947000e+08
1.960000e+08
1.981000e+08
1.864000e+08
1.838000e+08
1.999000e+08
2.142000e+08
2.287000e+08
2.509000e+08
2.874000e+08
PLW
GDP
1.381000e+08
2000-2015
Panama
1.230412e+10
1.250201e+10
1.299431e+10
1.369398e+10
1.501338e+10
1.637439e+10
1.814167e+10
2.095800e+10
2.452220e+10
2.659350e+10
2.891720e+10
3.437382e+10
3.995476e+10
4.485619e+10
4.916577e+10
5.213229e+10
PAN
GDP
3.982817e+10
2000-2015
Papua New Guinea
3.521348e+09
3.081030e+09
2.999542e+09
3.536459e+09
3.927114e+09
4.865972e+09
5.527857e+09
6.340674e+09
8.000074e+09
8.105332e+09
9.716103e+09
1.287305e+10
1.539163e+10
1.541316e+10
1.692868e+10
NaN
PNG
GDP
NaN
2000-2015
Paraguay
8.195993e+09
7.662595e+09
6.325152e+09
6.588104e+09
8.033877e+09
8.734654e+09
1.064616e+10
1.379491e+10
1.850413e+10
1.592990e+10
2.003053e+10
2.509968e+10
2.459532e+10
2.896591e+10
3.088117e+10
2.728258e+10
PRY
GDP
1.908659e+10
2000-2015
Peru
5.174475e+10
5.203016e+10
5.477755e+10
5.873103e+10
6.676870e+10
7.606061e+10
8.864319e+10
1.021710e+11
1.205506e+11
1.208230e+11
1.475289e+11
1.717617e+11
1.926490e+11
2.012177e+11
2.010497e+11
1.892121e+11
PER
GDP
1.374673e+11
2000-2015
Philippines
8.102630e+10
7.626207e+10
8.135760e+10
8.390821e+10
9.137124e+10
1.030716e+11
1.222107e+11
1.493599e+11
1.741951e+11
1.683346e+11
1.995908e+11
2.241431e+11
2.500921e+11
2.718361e+11
2.845845e+11
2.927741e+11
PHL
GDP
2.117478e+11
2000-2015
Poland
1.718856e+11
1.905213e+11
1.986806e+11
2.175186e+11
2.551023e+11
3.061346e+11
3.448264e+11
4.292496e+11
5.338158e+11
4.397962e+11
4.793211e+11
5.288199e+11
5.003443e+11
5.242148e+11
5.451518e+11
4.773368e+11
POL
GDP
3.054512e+11
2000-2015
Portugal
1.183585e+11
1.215459e+11
1.342287e+11
1.649642e+11
1.891874e+11
1.973045e+11
2.085669e+11
2.401693e+11
2.620076e+11
2.437457e+11
2.383034e+11
2.448951e+11
2.163682e+11
2.260735e+11
2.296298e+11
1.990823e+11
PRT
GDP
8.072380e+10
2000-2015
Puerto Rico
6.170181e+10
6.966864e+10
7.254619e+10
7.583400e+10
8.032231e+10
8.391452e+10
8.727616e+10
8.952413e+10
9.363932e+10
9.638564e+10
9.838127e+10
1.003517e+11
1.010807e+11
1.031348e+11
NaN
NaN
PRI
GDP
NaN
2000-2015
Qatar
1.775989e+10
1.753846e+10
1.936374e+10
2.353379e+10
3.173407e+10
4.453049e+10
6.088214e+10
7.971209e+10
1.152701e+11
9.779835e+10
1.251223e+11
1.677753e+11
1.868335e+11
1.987277e+11
2.062247e+11
1.646415e+11
QAT
GDP
1.468816e+11
2000-2015
Romania
3.743853e+10
4.071684e+10
4.617456e+10
5.986780e+10
7.621644e+10
9.969757e+10
1.235330e+11
1.715367e+11
2.081816e+11
1.674229e+11
1.679981e+11
1.853629e+11
1.716646e+11
1.915490e+11
1.994935e+11
1.775227e+11
ROM
GDP
1.400842e+11
2000-2015
Russian Federation
2.597085e+11
3.066027e+11
3.451104e+11
4.303478e+11
5.910167e+11
7.640171e+11
9.899305e+11
1.299705e+12
1.660844e+12
1.222644e+12
1.524916e+12
2.031769e+12
2.170144e+12
2.230625e+12
2.063662e+12
1.365865e+12
RUS
GDP
1.106157e+12
2000-2015
Rwanda
1.734938e+09
1.674685e+09
1.677447e+09
1.845979e+09
2.089189e+09
2.581466e+09
3.152017e+09
3.824812e+09
4.860577e+09
5.379378e+09
5.774004e+09
6.491684e+09
7.315702e+09
7.622526e+09
8.016288e+09
8.261034e+09
RWA
GDP
6.526096e+09
2000-2015
Samoa
2.690197e+08
2.730884e+08
2.880789e+08
3.388386e+08
4.203202e+08
4.626447e+08
5.085054e+08
5.509673e+08
6.441433e+08
5.609678e+08
6.430566e+08
7.397773e+08
8.011523e+08
8.048162e+08
8.035748e+08
8.039765e+08
WSM
GDP
5.349568e+08
2000-2015
San Marino
7.739076e+08
8.152052e+08
8.799572e+08
1.122982e+09
1.317358e+09
1.375417e+09
1.469000e+09
1.687567e+09
1.899880e+09
NaN
NaN
NaN
NaN
NaN
NaN
NaN
SMR
GDP
NaN
2000-2015
Sao Tome and Principe
NaN
7.223028e+07
8.053199e+07
9.634391e+07
1.053608e+08
1.261942e+08
1.344411e+08
1.458274e+08
1.880212e+08
1.878210e+08
1.974541e+08
2.332135e+08
2.525606e+08
3.029255e+08
3.484635e+08
3.176962e+08
STP
GDP
NaN
2000-2015
Saudi Arabia
1.895149e+11
1.841375e+11
1.896059e+11
2.158077e+11
2.587421e+11
3.284596e+11
3.769001e+11
4.159645e+11
5.197968e+11
4.290979e+11
5.282072e+11
6.712388e+11
7.359748e+11
7.466471e+11
7.563503e+11
6.542699e+11
SAU
GDP
4.647550e+11
2000-2015
Senegal
4.679605e+09
4.877602e+09
5.333862e+09
6.858953e+09
8.031344e+09
8.707016e+09
9.358711e+09
1.128460e+10
1.342846e+10
1.280904e+10
1.293730e+10
1.436835e+10
1.420239e+10
1.481098e+10
1.530897e+10
1.360998e+10
SEN
GDP
8.930373e+09
2000-2015
Serbia
6.540247e+09
1.226718e+10
1.611684e+10
2.118870e+10
2.486148e+10
2.625201e+10
3.060799e+10
4.028956e+10
4.925953e+10
4.261665e+10
3.946036e+10
4.646673e+10
4.074231e+10
4.551965e+10
4.421081e+10
3.716033e+10
SRB
GDP
3.062009e+10
2000-2015
Seychelles
6.148798e+08
6.222621e+08
6.975182e+08
7.057048e+08
8.393199e+08
9.191033e+08
1.016418e+09
1.033562e+09
9.671996e+08
8.473979e+08
9.699365e+08
1.065827e+09
1.134267e+09
1.411061e+09
1.422531e+09
1.437722e+09
SYC
GDP
8.228424e+08
2000-2015
Sierra Leone
6.358740e+08
1.079478e+09
1.239004e+09
1.371443e+09
1.431209e+09
1.627854e+09
1.885112e+09
2.158497e+09
2.505459e+09
2.489986e+09
2.616611e+09
2.942547e+09
3.801863e+09
4.920343e+09
5.015158e+09
4.251780e+09
SLE
GDP
3.615906e+09
2000-2015
Singapore
9.583393e+10
8.928621e+10
9.194119e+10
9.700138e+10
1.141886e+11
1.274177e+11
1.477972e+11
1.799813e+11
1.922259e+11
1.924084e+11
2.364218e+11
2.755995e+11
2.891621e+11
3.025107e+11
3.081428e+11
2.968407e+11
SGP
GDP
2.010068e+11
2000-2015
Slovak Republic
2.911488e+10
3.070302e+10
3.508361e+10
4.673177e+10
5.724054e+10
6.269754e+10
7.059673e+10
8.630425e+10
1.003246e+11
8.894563e+10
8.950101e+10
9.818126e+10
9.341399e+10
9.847835e+10
1.007606e+11
8.726759e+10
SVK
GDP
5.815272e+10
2000-2015
Slovenia
2.034220e+10
2.087539e+10
2.356358e+10
2.969745e+10
3.447023e+10
3.634697e+10
3.958773e+10
4.811469e+10
5.558985e+10
5.024479e+10
4.801361e+10
5.129079e+10
4.625825e+10
4.768857e+10
4.953015e+10
4.277672e+10
SVN
GDP
2.243452e+10
2000-2015
Solomon Islands
4.351039e+08
4.004635e+08
3.416616e+08
3.327382e+08
3.751119e+08
4.139099e+08
4.567054e+08
5.160742e+08
6.082939e+08
5.977654e+08
6.715853e+08
8.864984e+08
1.025125e+09
1.059695e+09
1.156563e+09
1.129165e+09
SLB
GDP
6.940609e+08
2000-2015
Somalia
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
5.352000e+09
5.647000e+09
5.925000e+09
SOM
GDP
NaN
2000-2015
South Africa
1.363619e+11
1.215161e+11
1.154824e+11
1.752569e+11
2.285936e+11
2.577727e+11
2.716385e+11
2.994155e+11
2.867698e+11
2.959365e+11
3.753494e+11
4.164189e+11
3.963278e+11
3.666239e+11
3.508506e+11
3.174066e+11
ZAF
GDP
1.810447e+11
2000-2015
Spain
5.954026e+11
6.259758e+11
7.051459e+11
9.068533e+11
1.069556e+12
1.157276e+12
1.264551e+12
1.479342e+12
1.634989e+12
1.499075e+12
1.431588e+12
1.488017e+12
1.335946e+12
1.361776e+12
1.375856e+12
1.192955e+12
ESP
GDP
5.975529e+11
2000-2015
Sri Lanka
1.633081e+10
1.574623e+10
1.653654e+10
1.888177e+10
2.066253e+10
2.440625e+10
2.827981e+10
3.235025e+10
4.071381e+10
4.206622e+10
5.672575e+10
6.529274e+10
6.843440e+10
7.431781e+10
7.935646e+10
8.061199e+10
LKA
GDP
6.428118e+10
2000-2015
St. Kitts and Nevis
4.205151e+08
4.610781e+08
4.831202e+08
4.658507e+08
5.025616e+08
5.431677e+08
6.362180e+08
6.740085e+08
7.389426e+08
7.232091e+08
7.050154e+08
7.532260e+08
7.344627e+08
7.881639e+08
8.477782e+08
8.764786e+08
KNA
GDP
4.559634e+08
2000-2015
St. Lucia
7.841592e+08
7.438081e+08
7.483466e+08
8.238371e+08
8.931072e+08
9.512074e+08
1.062617e+09
1.150526e+09
1.187076e+09
1.180950e+09
1.241893e+09
1.280624e+09
1.298815e+09
1.318052e+09
1.386189e+09
1.431136e+09
LCA
GDP
6.469765e+08
2000-2015
St. Vincent and the Grenadines
3.962700e+08
4.300404e+08
4.618834e+08
4.818063e+08
5.219751e+08
5.507287e+08
6.109300e+08
6.518333e+08
6.954289e+08
6.749225e+08
6.812260e+08
6.761294e+08
6.929337e+08
7.212071e+08
7.279128e+08
7.376836e+08
VCT
GDP
3.414136e+08
2000-2015
Sudan
1.225742e+10
1.318298e+10
1.480319e+10
1.764650e+10
2.145747e+10
2.652454e+10
3.582241e+10
4.589895e+10
5.452658e+10
5.315021e+10
6.563411e+10
6.732729e+10
6.812563e+10
7.206594e+10
8.215159e+10
9.715612e+10
SDN
GDP
8.489870e+10
2000-2015
Suriname
8.921644e+08
7.634656e+08
1.078402e+09
1.271196e+09
1.484093e+09
1.793755e+09
2.626380e+09
2.936612e+09
3.532969e+09
3.875410e+09
4.368398e+09
4.422277e+09
4.980000e+09
5.145758e+09
5.240606e+09
4.878732e+09
SUR
GDP
3.986567e+09
2000-2015
Swaziland
1.738101e+09
1.542477e+09
1.432228e+09
2.197613e+09
2.770083e+09
3.178127e+09
3.291354e+09
3.469364e+09
3.294093e+09
3.580417e+09
4.438779e+09
4.820499e+09
4.807282e+09
4.575596e+09
4.486262e+09
4.137639e+09
SWZ
GDP
2.399538e+09
2000-2015
Sweden
2.598020e+11
2.399173e+11
2.639262e+11
3.311089e+11
3.817054e+11
3.890423e+11
4.200321e+11
4.878163e+11
5.139657e+11
4.296570e+11
4.883777e+11
5.631097e+11
5.438806e+11
5.787420e+11
5.738177e+11
4.956944e+11
SWE
GDP
2.358923e+11
2000-2015
Switzerland
2.716597e+11
2.786288e+11
3.011278e+11
3.519826e+11
3.935417e+11
4.075357e+11
4.291956e+11
4.774078e+11
5.515470e+11
5.395282e+11
5.812086e+11
6.962787e+11
6.650541e+11
6.848350e+11
7.027055e+11
6.707899e+11
CHE
GDP
3.991302e+11
2000-2015
Syrian Arab Republic
1.932589e+10
2.109983e+10
2.158225e+10
2.182814e+10
2.508693e+10
2.885897e+10
3.333284e+10
4.040501e+10
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
SYR
GDP
NaN
2000-2015
Tajikistan
8.605503e+08
1.080774e+09
1.221114e+09
1.554126e+09
2.076149e+09
2.312320e+09
2.830236e+09
3.719497e+09
5.161336e+09
4.979482e+09
5.642179e+09
6.522732e+09
7.633050e+09
8.506675e+09
9.236309e+09
7.853450e+09
TJK
GDP
6.992900e+09
2000-2015
Tanzania
1.018579e+10
1.038356e+10
1.080560e+10
1.165913e+10
1.282580e+10
1.692998e+10
1.861046e+10
2.150174e+10
2.736839e+10
2.857378e+10
3.140791e+10
3.387863e+10
3.908775e+10
4.433346e+10
4.819722e+10
4.562825e+10
TZA
GDP
3.544246e+10
2000-2015
Thailand
1.263923e+11
1.202967e+11
1.343009e+11
1.522807e+11
1.728955e+11
1.893185e+11
2.217585e+11
2.629427e+11
2.913831e+11
2.817101e+11
3.411050e+11
3.708187e+11
3.975600e+11
4.205287e+11
4.065216e+11
3.992345e+11
THA
GDP
2.728422e+11
2000-2015
Togo
1.294250e+09
1.332329e+09
1.474630e+09
1.673690e+09
1.937075e+09
2.115154e+09
2.202809e+09
2.523463e+09
3.163416e+09
3.163001e+09
3.172946e+09
3.756023e+09
3.866617e+09
4.080929e+09
4.482880e+09
4.087628e+09
TGO
GDP
2.793378e+09
2000-2015
Tonga
2.023635e+08
1.812448e+08
1.827370e+08
2.025432e+08
2.293582e+08
2.621761e+08
2.941377e+08
3.001431e+08
3.494596e+08
3.181520e+08
3.694355e+08
4.230159e+08
4.724414e+08
4.493879e+08
4.434751e+08
4.354303e+08
TON
GDP
2.330668e+08
2000-2015
Trinidad and Tobago
8.154338e+09
8.824873e+09
9.008274e+09
1.130546e+10
1.328028e+10
1.598228e+10
1.836907e+10
2.164230e+10
2.787026e+10
1.917520e+10
2.215795e+10
2.543301e+10
2.569416e+10
2.643622e+10
2.617591e+10
2.355929e+10
TTO
GDP
1.540495e+10
2000-2015
Tunisia
2.147319e+10
2.206610e+10
2.314229e+10
2.745308e+10
3.118314e+10
3.227301e+10
3.437844e+10
3.890807e+10
4.485659e+10
4.345494e+10
4.405093e+10
4.581063e+10
4.504418e+10
4.625531e+10
4.760323e+10
4.315661e+10
TUN
GDP
2.168342e+10
2000-2015
Turkey
2.729794e+11
2.002541e+11
2.384239e+11
3.118259e+11
4.047763e+11
5.014228e+11
5.525050e+11
6.757541e+11
7.643229e+11
6.446565e+11
7.718769e+11
8.325465e+11
8.739818e+11
9.505956e+11
9.341678e+11
8.593836e+11
TUR
GDP
5.864042e+11
2000-2015
Turkmenistan
2.904663e+09
3.534772e+09
4.462029e+09
5.977441e+09
6.838351e+09
8.104356e+09
1.027760e+10
1.266417e+10
1.927152e+10
2.021439e+10
2.258316e+10
2.923333e+10
3.516421e+10
3.919754e+10
4.352421e+10
3.579963e+10
TKM
GDP
3.289497e+10
2000-2015
Tuvalu
1.374206e+07
1.319654e+07
1.545099e+07
1.823108e+07
2.153493e+07
2.183910e+07
2.290286e+07
2.703037e+07
3.029022e+07
2.710108e+07
3.182352e+07
3.931202e+07
3.987575e+07
3.832236e+07
3.725969e+07
3.267328e+07
TUV
GDP
1.893122e+07
2000-2015
Uganda
6.193247e+09
5.840504e+09
6.178564e+09
6.336696e+09
7.940363e+09
9.013834e+09
9.942598e+09
1.229281e+10
1.423903e+10
2.120377e+10
2.017941e+10
2.050860e+10
2.351608e+10
2.487905e+10
2.792788e+10
2.785638e+10
UGA
GDP
2.166313e+10
2000-2015
Ukraine
3.126153e+10
3.800934e+10
4.239290e+10
5.013295e+10
6.488306e+10
8.614202e+10
1.077531e+11
1.427190e+11
1.799924e+11
1.172278e+11
1.360132e+11
1.631597e+11
1.757814e+11
1.833101e+11
1.335034e+11
9.103096e+10
UKR
GDP
5.976943e+10
2000-2015
United Arab Emirates
1.043374e+11
1.033116e+11
1.098162e+11
1.243464e+11
1.478244e+11
1.806170e+11
2.221165e+11
2.579161e+11
3.154746e+11
2.535474e+11
2.898804e+11
3.509084e+11
3.748180e+11
3.904273e+11
4.031977e+11
3.579492e+11
ARE
GDP
2.536118e+11
2000-2015
United Kingdom
1.635441e+12
1.613034e+12
1.757572e+12
2.028488e+12
2.389004e+12
2.508104e+12
2.678278e+12
3.063005e+12
2.875463e+12
2.367127e+12
2.429680e+12
2.608825e+12
2.646003e+12
2.719509e+12
2.998834e+12
2.861091e+12
GBR
GDP
1.225650e+12
2000-2015
United States
1.028478e+13
1.062182e+13
1.097751e+13
1.151067e+13
1.227493e+13
1.309373e+13
1.385589e+13
1.447764e+13
1.471858e+13
1.441874e+13
1.496437e+13
1.551793e+13
1.615526e+13
1.669152e+13
1.739310e+13
1.803665e+13
USA
GDP
7.751869e+12
2000-2015
Uruguay
2.282326e+10
2.089879e+10
1.360649e+10
1.204563e+10
1.368633e+10
1.736286e+10
1.957946e+10
2.341057e+10
3.036621e+10
3.166091e+10
4.028448e+10
4.796244e+10
5.126439e+10
5.753123e+10
5.723601e+10
5.327430e+10
URY
GDP
3.045105e+10
2000-2015
Uzbekistan
1.376037e+10
1.140135e+10
9.687951e+09
1.012811e+10
1.203002e+10
1.430751e+10
1.733083e+10
2.231139e+10
2.954944e+10
3.368922e+10
3.933277e+10
4.591519e+10
5.182157e+10
5.769045e+10
6.306708e+10
6.690380e+10
UZB
GDP
5.314343e+10
2000-2015
Vanuatu
2.720147e+08
2.579269e+08
2.626038e+08
3.144631e+08
3.649969e+08
3.949626e+08
4.393768e+08
5.264283e+08
6.079586e+08
6.100666e+08
7.008043e+08
7.921497e+08
7.817029e+08
8.017876e+08
8.149543e+08
7.424321e+08
VUT
GDP
4.704174e+08
2000-2015
Venezuela, RB
1.171407e+11
1.229040e+11
9.289359e+10
8.362063e+10
1.124534e+11
1.455100e+11
1.834775e+11
2.303640e+11
3.159534e+11
3.297876e+11
3.931907e+11
3.164822e+11
3.812862e+11
3.710063e+11
NaN
NaN
VEN
GDP
NaN
2000-2015
Vietnam
3.364009e+10
3.529135e+10
3.794790e+10
4.271707e+10
4.942411e+10
5.763326e+10
6.637166e+10
7.741443e+10
9.913030e+10
1.060146e+11
1.159317e+11
1.355395e+11
1.558200e+11
1.712220e+11
1.862047e+11
1.932411e+11
VNM
GDP
1.596010e+11
2000-2015
Virgin Islands (U.S.)
NaN
NaN
3.269000e+09
3.453000e+09
3.799000e+09
4.439000e+09
4.504000e+09
4.803000e+09
4.250000e+09
4.203000e+09
4.339000e+09
4.239000e+09
4.095000e+09
3.764000e+09
3.624000e+09
3.765000e+09
VIR
GDP
NaN
2000-2015
World
3.354317e+13
3.333598e+13
3.461241e+13
3.886746e+13
4.377074e+13
4.738562e+13
5.130676e+13
5.779333e+13
6.338636e+13
6.008699e+13
6.590615e+13
7.324172e+13
7.480229e+13
7.692465e+13
7.887012e+13
7.450972e+13
WLD
GDP
4.096655e+13
2000-2015
Yemen, Rep.
9.636342e+09
9.854042e+09
1.069328e+10
1.177777e+10
1.387350e+10
1.675377e+10
1.908172e+10
2.165652e+10
2.691085e+10
2.513027e+10
3.090675e+10
3.272642e+10
3.540134e+10
4.041523e+10
4.322858e+10
3.773392e+10
YEM
GDP
2.809758e+10
2000-2015
Zambia
3.600683e+09
4.094481e+09
4.193846e+09
4.901840e+09
6.221078e+09
8.331870e+09
1.275686e+10
1.405696e+10
1.791086e+10
1.532834e+10
2.026556e+10
2.346010e+10
2.550337e+10
2.804546e+10
2.715063e+10
2.115439e+10
ZMB
GDP
1.755371e+10
2000-2015
Zimbabwe
6.689958e+09
6.777385e+09
6.342116e+09
5.727592e+09
5.805598e+09
5.755215e+09
5.443896e+09
5.291950e+09
4.415703e+09
8.366794e+09
1.005205e+10
1.207173e+10
1.405838e+10
1.522353e+10
1.583407e+10
1.607238e+10
ZWE
GDP
9.382423e+09
2000-2015
In [62]:
consumption_co2_emissions_absolute_value.head()
Out[62]:
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
ISO
Summary Range
Summary Range Years
Indicator
Country Name
Albania
1.029235
1.102482
1.355331
1.506422
1.453613
1.605657
1.516234
1.51755
1.655498
1.696258
1.650886
1.711138
1.598367
1.543575
1.534179
NaN
ALB
0.504944
2000-2014
Consumption CO2 Emissions Absolute Value
Algeria
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
DZA
NaN
2000-2014
Consumption CO2 Emissions Absolute Value
Andorra
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
AND
NaN
2000-2014
Consumption CO2 Emissions Absolute Value
Angola
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
AGO
NaN
2000-2014
Consumption CO2 Emissions Absolute Value
Antigua and Barbuda
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
ATG
NaN
2000-2014
Consumption CO2 Emissions Absolute Value
In [80]:
keep_these_countries = production_co2_emissions_annual_change.reset_index().set_index("ISO").index
def make_one_file(dsets):
df = dsets[0].reset_index().set_index("ISO").loc[keep_these_countries].reset_index()
print(df.shape)
for i in range(1, len(dsets)):
df = df.append(dsets[i].reset_index().set_index("ISO").loc[keep_these_countries].reset_index())
print(df.shape)
return(df)
final_data = make_one_file(dsets)
(183, 21)
(366, 21)
(549, 21)
(732, 21)
(915, 21)
(1098, 21)
(3660, 21)
In [81]:
# Write to S3
write_to_S3(final_data, s3_bucket, FINAL_DATA + \
"All Data Together.csv")
final_data.to_csv("/Users/nathansuberi/Desktop/Code Portfolio/nsuberi.github.io/wri-ghg/final-data/All Data Together.csv")
In [ ]:
In [ ]:
## Calculate extents in Python... re-did this in javascript
In [73]:
indicators = final_data["Indicator"].unique()
year_cols = [str(yr) for yr in range(2000,2016)]
extents = {}
long_extents = {}
for indicator in indicators:
data = final_data.loc[final_data["Indicator"]==indicator, year_cols]
extents[indicator] = [data.min().min(), data.max().max()]
summary_data = final_data.loc[final_data["Indicator"]==indicator, "Summary Range"]
long_extents[indicator] = [summary_data.min(), summary_data.max()]
In [75]:
print("extents")
print(extents)
print("long extents")
print(long_extents)
extents
{'Production CO2 Emissions Annual Change': [-0.58231707317073167, 5.8064516129032278], 'Production CO2 Emissions Absolute Value': [0.0069999999999999993, 9896.7060457050302], 'Consumption CO2 Emissions Annual Change': [-2.2820333549161385, 4.0330301875807812], 'Consumption CO2 Emissions Absolute Value': [-0.31450916878671931, 2470.0722301013307], 'ICGGD with Production Emissions': [-12.123624635633307, 9.1800704884216824], 'ICGGD with Consumption Emissions': [-7.4118054937117783, 5.9522470514303185], 'access_to_electricity_of_population_eg_elc_accs_zs': [0.0154853165149689, 100.0], 'renewable_energy_consumption_of_total_final_energy_consumpti': [0.0, 98.342609009734005], 'individuals_using_the_internet_of_population_it_net_user_z': [0.000289277, 98.323609649999995], 'household_final_consumption_expenditure_per_capita_constant_20': [152.47162086105499, 48546.572692095098], 'industry_value_added_constant_2010_us_nv_ind_totl_kd': [1322136.39560658, 21258209566653.301], 'total_natural_resources_rents_of_gdp_ny_gdp_totl_rt_zs': [0.0, 89.166111851230795], 'proportion_of_seats_held_by_women_in_national_parliaments': [0.0, 63.799999999999997], 'employment_to_population_ratio_15_total_modeled_ilo_est': [29.510000228881804, 87.013999938964801], 'net_migration_sm_pop_netm': [-4157896.0, 7257129.0], 'life_expectancy_at_birth_total_years_sp_dyn_le00_in': [38.690146341463397, 84.278048780487794], 'urban_population_of_total_sp_urb_totl_in_zs': [8.2460000000000004, 100.0], 'merchandise_imports_current_us_tm_val_mrch_cd_wt': [3500000.0, 19080333043346.699], 'GDP': [13196544.946726, 78870119013702.906], 'GDP percent change': [-0.64473258619264096, 3.0515803895874303]}
long extents
{'Production CO2 Emissions Annual Change': [-0.713655185305198, 0.43272870175187], 'Production CO2 Emissions Absolute Value': [-157.98880529674875, 3111.6066568448969], 'Consumption CO2 Emissions Annual Change': [-2.0643888043379244, 0.39177854934118], 'Consumption CO2 Emissions Absolute Value': [-97.065613082643722, 1600.804809484755], 'ICGGD with Production Emissions': [-8.0976398848380811, 1.0343011545141971], 'ICGGD with Consumption Emissions': [nan, nan], 'access_to_electricity_of_population_eg_elc_accs_zs': [7.0, 100.0], 'renewable_energy_consumption_of_total_final_energy_consumpti': [-46.199260618760185, 22.392458422154203], 'individuals_using_the_internet_of_population_it_net_user_z': [1.0837331159999999, 98.323609649999995], 'household_final_consumption_expenditure_per_capita_constant_20': [162.473602866269, 41385.197522464499], 'industry_value_added_constant_2010_us_nv_ind_totl_kd': [-52054713029.230034, 7210893651537.6025], 'total_natural_resources_rents_of_gdp_ny_gdp_totl_rt_zs': [0.0, 46.440583662763004], 'proportion_of_seats_held_by_women_in_national_parliaments': [0.0, 63.799999999999997], 'employment_to_population_ratio_15_total_modeled_ilo_est': [-14.747001647949205, 13.649002075195297], 'net_migration_sm_pop_netm': [-4157896.0, 4500000.0], 'life_expectancy_at_birth_total_years_sp_dyn_le00_in': [51.377853658536608, 84.278048780487794], 'urban_population_of_total_sp_urb_totl_in_zs': [8.4450000000000003, 100.0], 'merchandise_imports_current_us_tm_val_mrch_cd_wt': [-1311564245.81006, 10044415244462.127], 'GDP': [-504443362663.00049, 40966546818461.008], 'GDP percent change': [-2.9880916685916032, 0.48525859148192518]}
In [ ]:
Content source: nsuberi/nsuberi.github.io
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