How to create subplots of all column combinations from two dataframes

Question

I have a made a function which plots input variables against predicted variables.

dummy_data = pd.DataFrame(np.random.uniform(low=65.5,high=140.5,size=(50,4)), columns=list('ABCD'))
dummy_predicted = pd.DataFrame(np.random.uniform(low=15.5,high=17.5,size=(50,4)), columns=list('WXYZ'))

##Plot test input distriubtions
fig = plt.figure(figsize=(15,6))
n_rows = 1 
n_cols = 4
counter = 1
for i in dummy_data.keys():
    plt.subplot(n_rows, n_cols, counter)
    plt.scatter(dummy_data[i], dummy_predicted['Z'])

    plt.title(f'{i} vs Z')
    plt.xlabel(i)
    counter += 1

plt.tight_layout() 
plt.show()

How do I create a 4 x 4 subplot of all combinations of 'ABCD' and 'WXYZ'? I can have any number of dummy_data and dummy_predicted columns so some dynamism would be useful.

Trenton McKinney · Answer 1 · 2022-06-13T20:53:54.910

Use itertools.product from the standard library, to create all combinations of column names, combos.
Use the len of each set of columns to determine nrows and ncols for plt.subplots
Flatten the array of axes to easily iterate through a 1D array instead of a 2D array.
zip combos and axes to iterate through, and plot each group with a single loop.
See this answer in How to plot in multiple subplots.

from itertools import product
import matplotlib.pyplot as plt
import numpy as np

# sample data
np.random.seed(2022)
dd = pd.DataFrame(np.random.uniform(low=65.5, high=140.5, size=(50, 4)), columns=list('ABCD'))
dp = pd.DataFrame(np.random.uniform(low=15.5, high=17.5, size=(50, 4)), columns=list('WXYZ'))

# create combinations of columns
combos = product(dd.columns, dp.columns)

# create subplots
fig, axes = plt.subplots(nrows=len(dd.columns), ncols=len(dp.columns), figsize=(15, 6))

# flatten axes into a 1d array
axes = axes.flat

# iterate and plot
for (x, y), ax in zip(combos, axes):
    ax.scatter(dd[x], dp[y])
    ax.set(title=f'{x} vs. {y}', xlabel=x, ylabel=y)
plt.tight_layout()
plt.show()

score 2 · Accepted Answer · answered Jun 13 '22 at 18:42

just do a double for loop

n_rows = len(dummy_data.columns)
n_cols = len(dummy_predicted.columns)

fig, axes = plt.subplots(n_rows, n_cols, figsize=(15,6))

for row, data_col in enumerate(dummy_data):
    for col, pred_col in enumerate(dummy_predicted):
        ax = axes[row][col]

        ax.scatter(dummy_data[data_col], dummy_predicted[pred_col])
        
        ax.set_title(f'{data_col} vs {pred_col}')

        ax.set_xlabel(data_col)

plt.tight_layout() 
plt.show()

Output:

How to create subplots of all column combinations from two dataframes

2 Answers2