How do I plot multiple graphs using matplotlib?

Question

I'm doing some EDA on a dataset I have using seaborn primarily. However, I'd like to plot these graphs in a single kernel. I think I'm meant to use matplotlib to achieve this. I've done 3 separate sns.countplot graphs, but I'm trying to show them in one single kernel/output.

I've tried using the following code but I'm still not entirely sure how it works:

fig, axes = plt.subplots(1, 3, figsize=(16,8))

ax = sns.countplot(y = 'loan_status', data = df, order = df['loan_status'].value_counts().iloc[:6].index)

ax = sns.countplot(y = 'loan_status', data = df, order = df['loan_status'].value_counts().iloc[2:9].index)

ax = sns.distplot(df['loan_amnt'], bins=50)

Answer 1

Do you mean something like this?

Here is a simple example:

import numpy as np
import matplotlib.pyplot as plt

# Some random data to plot
M = np.random.rand(3,100,100)

fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(16,8))

for i, ax in enumerate(axes.flatten()):
    ax.imshow(M[i])

# OR
# axes[0].imshow(M[0])
# axes[1].imshow(M[1])
# axes[2].imshow(M[2])

plt.show()

Answer 2

Try this.

fig, [ax1, ax2, ax3] = plt.subplots(1, 3, figsize=(16,8))

     ax1 = sns.countplot(y = 'loan_status', data = df, order = df['loan_status'].value_counts().iloc[:6].index)

     ax2 = sns.countplot(y = 'loan_status', data = df, order = df['loan_status'].value_counts().iloc[2:9].index)

     ax3 = sns.distplot(df['loan_amnt'], bins=50)

fig.tight_layout()

plt.show()