In [1]:

    

import geopandas as gpd
import pandas as pd
import pickle

from sklearn.linear_model import LinearRegression
import statsmodels.api as sm
import statsmodels.formula.api as smf

from library.analyze import countries_regressions


    

In [13]:

    

# import cleaned dataframe
df = pd.read_pickle('data/geo/pickles/zonal_stats_c_norm.pickle')

# calculate regression stats for each country
df_regression = countries_regressions(df).sort_values(by='r', ascending=False)

# save outputs to csv
df_regression.to_csv('data/country_stats.csv')


    

    




AFG
ALB
DZA
ASM
ADO
AGO
ATG
ARG
ARM
ABW
AUS
AUT
AZE
BHS
BHR
BGD
BRB
BLR
BEL
BLZ
BEN
BMU
BTN
BOL
BIH
BWA
BRA
BRN
BGR
BFA
BDI
CPV
KHM
CMR
CAN
CYM
CAF
TCD
CHI
CHL
CHN
COL
COM
ZAR
COG
CRI
CIV
HRV
CUB
CUW
CYP
CZE
DNK
DJI
DMA
DOM
ECU
EGY
SLV
GNQ
ERI
EST
ETH
FRO
FJI
FIN
FRA
PYF
GAB
GMB
GEO
DEU
GHA
GRC
GRL
GRD
GUM
GTM
GIN
GNB
GUY
HTI
HND
HKG
HUN
ISL
IND
IDN
IRN
IRQ
IRL
IMY
ISR
ITA
JAM
JPN
JOR
KAZ
KEN
KIR
PRK
KOR
KSV
KWT
KGZ
LAO
LVA
LBN
LSO
LBR
LBY
LIE
LTU
LUX
MAC
MKD
MDG
MWI
MYS
MDV
MLI
MLT
MHL
MRT
MUS
MEX
FSM
MDA
MCO
MNG
MNE
MAR
MOZ
MMR
NAM
NPL
NLD
NCL
NZL
NIC
NER
NGA
MNP
OMN
PAK
PLW
PAN
PNG
PRY
PER
PHL
POL
PRT
PRI
QAT
ROM
RUS
RWA
WSM
SMR
STP
SAU
SEN
SRB
SYC
SLE
SGP
SXM
SVK
SVN
SLB
SOM
ZAF
SSD
ESP
LKA
KNA
LCA
MAF
VCT
SDN
SUR
SWZ
SWE
CHE
SYR
TJK
TZA
THA
TMP
TGO
TON
TTO
TUN
TUR
TKM
TCA
TUV
UGA
UKR
ARE
GBR
USA
URY
UZB
VUT
VEN
VNM
VIR
WBG
YEM
ZMB
ZWE

In [14]:

    

# syria case

# import cleaned dataframe
df_syria = pd.read_pickle('data/geo/pickles/zonal_stats_c_norm_syr.pickle')

# calculate regression stats for each country
df_syria_regression = countries_regressions(df_syria).sort_values(by='r', ascending=False)

# save outputs to csv
df_syria_regression.to_csv('data/country_stats_syria.csv')


    

    




SYR

In [16]:

    

# angola and south sudan cases

# import cleaned dataframe
df_agossd = pd.read_pickle('data/geo/pickles/zonal_stats_c_norm_agossd.pickle')

# calculate regression stats for each country
df_agossd_regression = countries_regressions(df_agossd).sort_values(by='r', ascending=False)

# save outputs to csv
df_agossd_regression.to_csv('data/country_stats_agossd.csv')


    

    




SSD
AGO

In [17]:

    

df_agossd_regression


    

    
Out[17]:






  

    

      

      
beta
      
intercept
      
r
      
r_adj
      
p_beta
      
p_int
      
c_beta_low
      
c_beta_high
      
c_int_low
      
c_int_high
    
    

      
country
      

      

      

      

      

      

      

      

      

      

    
  
  

    

      
AGO
      
1.017198
      
-0.066976
      
0.862810
      
0.858523
      
2.361394e-15
      
0.024607
      
0.871145
      
1.163251
      
-0.124813
      
-0.009138
    
    

      
SSD
      
0.240826
      
0.853164
      
0.105244
      
-0.118445
      
5.304519e-01
      
0.058750
      
-0.733977
      
1.215629
      
-0.050667
      
1.756995