Multiple plots on subplots in pandas

Question

Let's say I've got a dataframe that looks like this (indexed on dates):

Value1 Value2 Value3 Value4 Value5
1      1      3      4      -1    
2      2      3      4      1
3      3      3      2      -1

The values don't really matter, but I wanted to show an example.

I've got what seems like a fairly basic issue. I am trying to plot a MACD chart like the one found here. I want a plot that has the stock price with a plot immediately below it with the MACD lines. I've got subplots working, but I can't figure out how to get a linegraph and a barchart on the same chart. I've tried the following:

fig, axes = plt.subplots(nrows=2, ncols=1, sharex=True, squeeze=False)
ind3.iloc[:,0].plot(title="Stock Price", ax=axes[0,0], fontsize=12, color=colors)
ind3.iloc[:,1:-1].plot(title="MACD", ax=axes[1,0], fontsize=12, color=colors)
ind3.iloc[:,-1].plot(title="MACD", ax=axes[1,0], kind='bar',fontsize=12, color=colors)

Which results in gibberish that looks like this:

Can anyone help? Thanks!

Answer 1

That is probably related to the way you're indexing using iloc but its hard to tell without seeing the rest of your code.

Multiple plots in a subplot just requires you to call plot/bar on a specific subplot, and pass it the data you want to plot. In general, the structure looks something like this...

Generate some test data:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame(np.random.randint(0,100,size=(10,2)), columns=list('AB'))
df['time'] = pd.date_range('2019-03-01', periods=10, freq='1D')
df = df.set_index('time')
print(df)

             A   B
time              
2019-03-01  12  73
2019-03-02  46  12
2019-03-03  41  10
2019-03-04  18  89
2019-03-05  60  98
2019-03-06  57  23
2019-03-07  59  73
2019-03-08  76  41
2019-03-09  71  34
2019-03-10  38  16

Create the plot:

fig, ax = plt.subplots(nrows=2, ncols=1, figsize=(8,10))
ax[0].set_title('Stock Price')
ax[1].set_title('MACD')

ax[1].plot(df.index, df['A'], color='b', label='Signal')
ax[1].bar(df.index, df['B'], color='g', label='MACD')

ax[1].set_xticklabels(df.index, rotation=90)

plt.legend(loc=1)
plt.tight_layout()
plt.show()