Subplotting subplots

Question

I am creating two plots using matplotlib, each of them is a subplot showing two metrics on the same axis.

I'm trying to run them so they show as two charts but in one graphic, so that when I save the graphic I see both plots. At the moment, running the second plot overwrites the first in memory so I can only ever save the second.

How can I plot them together?

My code is below.

plot1 = plt.figure()
fig,ax1 = plt.subplots()
ax1.plot(dfSat['time'],dfSat['wind_at_altitude'], 'b-', label = "speed", linewidth = 5.0)
plt.title('Wind Speeds - Saturday - {}'.format(windloc))
plt.xlabel('Time of day')
plt.ylabel('Wind speed (mph)')
ax1.plot(dfSat['time'],dfSat['gust_at_altitude'], 'r-', label = "gust", linewidth = 5.0)
plt.legend(loc="upper right")
ax1.text(0.05, 0.95, calcmeassat, transform=ax1.transAxes, fontsize=30,
        verticalalignment='top')
plt.ylim((0,100))

plot2 = plt.figure()
fig,ax2 = plt.subplots()
ax2.plot(dfSun['time'],dfSun['wind_at_altitude'], 'b-', label = "speed", linewidth = 5.0)
plt.title('Wind Speeds - Sunday - {}'.format(windloc))
plt.xlabel('Time of day')
plt.ylabel('Wind speed (mph)')
ax2.plot(dfSun['time'],dfSun['gust_at_altitude'], 'r-', label = "gust", linewidth = 5.0)
plt.legend(loc="upper right")
ax2.text(0.05, 0.95, calcmeassun, transform=ax2.transAxes, fontsize=30,
        verticalalignment='top')
plt.ylim((0,100))

`fig, (ax1, ax2) = plt.subplots(1, 2)` or similar. Please read the [matplotlib tutorial on generating subplots.](https://matplotlib.org/stable/gallery/subplots_axes_and_figures/subplots_demo.html) — Mr. T, Mar 05 '22 at 14:21

score 2 · Accepted Answer · answered Mar 05 '22 at 19:10

As mentioned, in your case you only need one level of subplots, e.g., nrows=1, ncols=2.
However, in matplotlib 3.4+ there is such a thing as "subplotting subplots" called subfigures, which makes it easier to implement nested layouts, e.g.:

Subplots

For your simpler use case, create 1x2 subplots with ax1 on the left and ax2 on the right:

# create 1x2 subplots
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(16, 4))

# plot saturdays on the left
dfSat.plot(ax=ax1, x='date', y='temp_min')
dfSat.plot(ax=ax1, x='date', y='temp_max')
ax1.set_ylim(-20, 50)
ax1.set_title('Saturdays')

# plot sundays on the right
dfSun.plot(ax=ax2, x='date', y='temp_min')
dfSun.plot(ax=ax2, x='date', y='temp_max')
ax2.set_ylim(-20, 50)
ax2.set_title('Sundays')

Subfigures

Say you want something more complicated like having the left side show 2012 with its own suptitle and right side to show 2015 with its own suptitle.

Create 1x2 subfigures (left subfig_l and right subfig_r) with 2x1 subplots on the left (top ax_lt and bottom ax_lb) and 2x1 subplots on the right (top ax_rt and bottom ax_rb):

# create 1x2 subfigures
fig = plt.figure(constrained_layout=True, figsize=(12, 5))
(subfig_l, subfig_r) = fig.subfigures(nrows=1, ncols=2, wspace=0.07)

# create top/box axes in left subfig
(ax_lt, ax_lb) = subfig_l.subplots(nrows=2, ncols=1)

# plot 2012 saturdays on left-top axes
dfSat12 = dfSat.loc[dfSat['date'].dt.year.eq(2012)]
dfSat12.plot(ax=ax_lt, x='date', y='temp_min')
dfSat12.plot(ax=ax_lt, x='date', y='temp_max')
ax_lt.set_ylim(-20, 50)
ax_lt.set_ylabel('Saturdays')

# plot 2012 sundays on left-top axes
dfSun12 = dfSun.loc[dfSun['date'].dt.year.eq(2012)]
dfSun12.plot(ax=ax_lb, x='date', y='temp_min')
dfSun12.plot(ax=ax_lb, x='date', y='temp_max')
ax_lb.set_ylim(-20, 50)
ax_lb.set_ylabel('Sundays')

# set suptitle for left subfig
subfig_l.suptitle('2012', size='x-large', weight='bold')

# create top/box axes in right subfig
(ax_rt, ax_rb) = subfig_r.subplots(nrows=2, ncols=1)

# plot 2015 saturdays on left-top axes
dfSat15 = dfSat.loc[dfSat['date'].dt.year.eq(2015)]
dfSat15.plot(ax=ax_rt, x='date', y='temp_min')
dfSat15.plot(ax=ax_rt, x='date', y='temp_max')
ax_rt.set_ylim(-20, 50)
ax_rt.set_ylabel('Saturdays')

# plot 2015 sundays on left-top axes
dfSun15 = dfSun.loc[dfSun['date'].dt.year.eq(2015)]
dfSun15.plot(ax=ax_rb, x='date', y='temp_min')
dfSun15.plot(ax=ax_rb, x='date', y='temp_max')
ax_rb.set_ylim(-20, 50)
ax_rb.set_ylabel('Sundays')

# set suptitle for right subfig
subfig_r.suptitle('2015', size='x-large', weight='bold')

Sample data for reference:

import pandas as pd
from vega_datasets import data

df = data.seattle_weather()
df['date'] = pd.to_datetime(df['date'])
dfSat = df.loc[df['date'].dt.weekday.eq(5)]
dfSun = df.loc[df['date'].dt.weekday.eq(6)]

score 1 · Answer 2 · answered Mar 05 '22 at 14:27

It doesn't work like that. Subplots are what they are called; plots inside a main plot.

That means if you need two subplots; then you need one plot containing two subplots in it.

# figure object NOT plot object
# useful when you want only one plot NO subplots
fig = plt.figure() 

# 2 subplots inside 1 plot
# 1 row, 2 columns
fig, [ax1, ax2] = plt.subplots(1, 2)

# then call plotting method on each axis object to
# create plot on that subplot
sns.histplot(...., ax=ax1)
sns.violinplot(..., ax=ax2)

# or using matplotlib like this
ax1.plot()
ax2.plot()

Learn more about subplots

Subplotting subplots

2 Answers2

Subplots

Subfigures