Subplots

Often times we might want to plot multiple plots within the same figure. For example, we might want to perform a side by side comparison of the box plot with the line plot of China and India's immigration.

To visualize multiple plots together, we can create a figure (overall canvas) and divide it into subplots, each containing a plot. With subplots, we usually work with the artist layer instead of the scripting layer.

Typical syntax is : 

fig = plt.figure()
    ax = fig.add_subplot(nrows, ncols, plot_number)

Where

  • nrows and ncols are used to notionally split the figure into (nrows * ncols) sub-axes,
  • plot_number is used to identify the particular subplot that this function is to create within the notional grid. plot_number starts at 1, increments across rows first and has a maximum of nrows * ncols as shown below.

%%capture
!pip3 install xlrd

import matplotlib.pyplot as plt
import pandas as pd

df_can = pd.read_excel(
    './data/ibm/canada.xlsx',
    sheet_name='Canada by Citizenship',
    skiprows=range(20),
    skipfooter=2
)

df_can.columns = list(map(lambda x: str(x), df_can.columns))

drops = [
    'AREA', 
    'REG', 
    'DEV', 
    'Type', 
    'Coverage'
]
df_can.drop(columns=drops, inplace=True)

columns = {
    'OdName': 'Country',
    'AreaName': 'Continent',
    'RegName': 'Region'
}

df_can.rename(columns=columns, inplace=True)

df_can.set_index('Country', inplace=True)

df_can['Total'] = df_can.sum(axis=1)

/var/folders/s5/lzcc_1614bq9rypw8vg_pf7r0000gn/T/ipykernel_27997/552165185.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.
  df_can['Total'] = df_can.sum(axis=1)

years = list(map(str, range(1980, 2014)))

df_ci = df_can.loc[['China', 'India'], years].transpose()

fig = plt.figure()

ax0 = fig.add_subplot(1, 2, 1) 
ax1 = fig.add_subplot(1, 2, 2)

df_ci.plot(kind='box', color='blue', vert=False, figsize=(20, 6), ax=ax0)
ax0.set_title('Box Plots of Immigrants from China and India (1980 - 2013)')
ax0.set_xlabel('Number of Immigrants')
ax0.set_ylabel('Countries')

df_ci.plot(kind='line', figsize=(20, 6), ax=ax1)
ax1.set_title ('Line Plots of Immigrants from China and India (1980 - 2013)')
ax1.set_ylabel('Number of Immigrants')
ax1.set_xlabel('Years')

plt.show()

Tip regarding subplot convention

In the case when nrows, ncols, and plot_number are all less than 10, a convenience exists such that the a 3 digit number can be given instead, where the hundreds represent nrows, the tens represent ncols and the units represent plot_number. For instance,

subplot(211) == subplot(2, 1, 1)

produces a subaxes in a figure which represents the top plot (i.e. the first) in a 2 rows by 1 column notional grid (no grid actually exists, but conceptually this is how the returned subplot has been positioned).