How to Make Two Plots Side-By-Side Using Python

How to graph two plots side by side using matplotlib (no pandas)

Every time you call subplots(), a new figure is created, which is not what you want. To get the side-by-side plots, do fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2) and then use ax1 for plotting whatever you want on the left plot, ax2 for the right plot.

creating two plots side by side in matplotlib

You can get the desired display if you remove tight_layout(), adjust the bounding box for the table and the figure size, and then change the column spanning, i.e.

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
df = \
pd.DataFrame({'data': {'Performance': "[None, ' bps']Performance cannot be calculated",
            'Basket Switch Cost': '400000 bps / 4000',
            '10\\% VWAP Switch Cost': '0 bps / 0',
            'Portfolio Expense Ratio': 'Savings of None bps  /  None',
            'Common Items': '523 Items  \\&  53% by Weight',
            'Starting \\& Ending Security Count': '611 / 611',
            'Largest Sector Exposure Difference': '0%  Increase  in Information Technology',
            'Common Inception Date': '2011-03-24'}})

fig = plt.figure(figsize=(16,6))
ax = plt.subplot2grid((1,2), (0,0))

circle = plt.Circle((0.0,0.0),radius=0.75, fc='r')
ax.add_patch(circle)
ax.axis('scaled')
ax2 = plt.subplot2grid((1,2), (0,1))
font_size=10
bbox=[0.3, 0, 0.95, 1]
ax2.axis('off')
mpl_table = ax2.table(cellText = df.values, rowLabels = df.index, 
                      bbox=bbox, colLabels=df.columns)
mpl_table.auto_set_font_size(False)
mpl_table.set_fontsize(font_size)

Which would give you

Matplotlib pyplot putting two plots side by side

It looks like DataFrame.plot takes an ax argument for a pyplot axis https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.plot.html.
Try:

ax = plt.subplot(1, 2, 1)
myDataFrame.plot(kind='scatter' x='xcol', y='ycol', ax=ax) 

Combine two matplotlib Figures, side by side, high quality

You can render your figures to arrays using the agg backend.
Then concat the arrays side by side and switch back to your normal backend to show the result:

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

backend = mpl.get_backend()
mpl.use('agg')

dpi = 100
fig1,_ = plt.subplots(2,2, figsize=(1000/dpi, 1000/dpi), dpi=dpi)
fig1.suptitle('Figure 1')
fig2,_ = plt.subplots(2,2, figsize=(1000/dpi, 1000/dpi), dpi=dpi)
fig2.suptitle('Figure 2')

c1 = fig1.canvas
c2 = fig2.canvas

c1.draw()
c2.draw()

a1 = np.array(c1.buffer_rgba())
a2 = np.array(c2.buffer_rgba())
a = np.hstack((a1,a2))

mpl.use(backend)
fig,ax = plt.subplots(figsize=(2000/dpi, 1000/dpi), dpi=dpi)
fig.subplots_adjust(0, 0, 1, 1)
ax.set_axis_off()
ax.matshow(a)

How do I plot two countplot graphs side by side in seaborn?

Something like this:

import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt

batData = ['a','b','c','a','c']
bowlData = ['b','a','d','d','a']

df=pd.DataFrame()
df['batting']=batData
df['bowling']=bowlData

fig, ax =plt.subplots(1,2)
sns.countplot(df['batting'], ax=ax[0])
sns.countplot(df['bowling'], ax=ax[1])
fig.show()

The idea is to specify the subplots in the figure - there are numerous ways to do this but the above will work fine.

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