Two subplots in Python (matplotlib)

Question

I want to create two subplots in Python (using Anaconda 2.7) but code which I wrote generates two graphs, both not showing too much. Here's the code:

import pandas as pd
import pandas.io.data as web

import matplotlib.pyplot as plt
from matplotlib import style
style.use('ggplot')

import datetime

start = datetime.datetime(2000, 10, 23)
end = datetime.datetime(2016, 10, 23)

df = web.DataReader("BAC", "yahoo", start, end)

df['100MA'] = pd.rolling_mean(df['Adj Close'], 100, min_periods=1)
df['STD'] = pd.rolling_std(df['Close'], 25, min_periods=1)

print(df.tail())

ax1 = plt.subplot(2, 1, 1)
df[['Adj Close', '100MA']].plot()
ax2 = plt.subplot(2, 1, 2, sharex=ax1)
df['STD'].plot()
plt.show()

Thanks in advance!

Kennet Celeste · Accepted Answer · 2016-10-25 18:25:07Z

8

import pandas as pd
import pandas.io.data as web

import matplotlib.pyplot as plt
from matplotlib import style
style.use('ggplot')

import datetime

start = datetime.datetime(2000, 10, 23)
end = datetime.datetime(2016, 10, 23)

df = web.DataReader("BAC", "yahoo", start, end)

df['100MA'] = pd.rolling_mean(df['Adj Close'], 100, min_periods=1)
df['STD'] = pd.rolling_std(df['Close'], 25, min_periods=1)

print(df.tail())
f,axarr = plt.subplots(2,1)
df[['Adj Close', '100MA']].plot(ax=axarr[0])
df['STD'].plot(ax=axarr[1])
plt.show()

result:

answered Oct 25, 2016 at 18:25

Kennet Celeste

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4 Comments

user5021612 Over a year ago

Thanks a lot for the answer!

Kennet Celeste Over a year ago

@StanislavJirák no problem, If the answer addresses your question accept it by clicking on the checkmark of that answer (like here) so that others notice it will work in the first look.

user5021612 Over a year ago

I was waiting until I can accept the aswer due to the time limit (5m).

MaxU - stand with Ukraine Over a year ago

I think it's better to switch to pandas_datareader module as pandas.io.data is deprecated and doesn't work with Pandas 0.19.0. So use import pandas_datareader.data as web instead of import pandas.io.data as web. PS +1 for the great answer

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