This example uses historical data since 1880 on average global surface temperature changes from NASA's GISS Surface Temperature Analysis (GISTEMP) (original file) That site has lots of other data sets in csv format, too.
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# import the software packages needed
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib as mpl
import matplotlib.pyplot as plt
inline_rc = dict(mpl.rcParams)
import datetime as dt
import matplotlib.dates as mdates
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# Combined land and ocean temperature averages (LOTI: Land Ocean Temperature Index)
data1 = pd.read_csv('http://github.com/adamlamee/CODINGinK12-data/raw/master/LOTI.csv', header=1).replace(to_replace="***", value=np.NaN)
data_LOTI = data1.apply(lambda x: pd.to_numeric(x, errors='ignore'))
# Only land temperature averages
data2 = pd.read_csv('http://github.com/adamlamee/CODINGinK12-data/raw/master/LAND.csv', header=1).replace(to_replace="***", value=np.NaN)
data_LAND = data2.apply(lambda x: pd.to_numeric(x, errors='ignore'))
data3 = pd.read_csv('./Orlando Temps.csv')
#data3 = pd.read_csv(https://gist.githubusercontent.com/GoodmanSciences/9953c23049f7814c0d26b5a49a5375f3/raw/72423fbdf5c54e14083d30bbbfccea79553f8025/Orlando%2520Temps.csv)
dates = ['1/1/1975','1/2/1975','01/3/1975']
x = [dt.datetime.strptime(d,'%m/%d/%Y').date() for d in dates]
y = "range(len(x))"
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# The .head(n) command displays the first n rows of the local temperature data file.
data3.head(4)
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data3.columns
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ax = data3.plot('date', 'avg', title="Average Temperature at Orlando International Airport (1975 - Present)", legend=False)
ax.set(xlabel="Date", ylabel="Average Temperature (Fahrenheit)")
# Get current size
fig_size = plt.rcParams["figure.figsize"]
# Prints: [8.0, 6.0]
print( "Current size:", fig_size)
# Set figure width to 20 and height to 6.5
fig_size[0] = 20
fig_size[1] = 6.5
plt.rcParams["figure.figsize"] = fig_size
plt.show()
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# The .head(n) command displays the first n rows of the file.
data_LAND.head(5)
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x1 = data_LOTI.Year
y1 = data_LOTI.JanDec
# plt.plot() makes a line graph, by default
fig = plt.figure(figsize=(10, 5))
plt.plot(x1, y1)
plt.title('Average land an docean temperature readings')
plt.xlabel('Year')
plt.ylabel('Percent temp change')
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x2 = data_LAND.Year
y2 = data_LAND.JanDec
# plt.plot() makes a line graph, by default
fig = plt.figure(figsize=(10, 5))
plt.plot(x2, y2)
plt.title('Land temperature readings')
plt.xlabel('Year')
plt.ylabel('Percent temp change')
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# Wow, this needs a title and axis labels!
fig = plt.figure(figsize=(10, 5))
plt.plot(x1, y1, label="Land and Ocean")
plt.plot(x2, y2, label="Land only")
plt.legend()
plt.show()
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