How Can I Efficiently Display Multiple Pandas DataFrames in Matplotlib Subplots?

Displaying Multiple DataFrames in Subplots

Plotting separate Pandas DataFrames as individual plots can be cumbersome when you want to visualize them together. Manually creating subplots in matplotlib offers a solution to combine these dataframes into a single coherent plot.

Solution:

1. Create Subplots:

   • Import Matplotlib (import matplotlib.pyplot as plt).
   • Create a figure and subplots ("fig", "axes") using plt.subplots().

2. Assign DataFrames to Subplots:

   • Iterate through the dataframes and plot each one onto a specific subplot using the ax=axes[row,column] keyword.

Example (2x2 Subplots):

import matplotlib.pyplot as plt

fig, axes = plt.subplots(nrows=2, ncols=2)

df1.plot(ax=axes[0,0])
df2.plot(ax=axes[0,1])
df3.plot(ax=axes[1,0])
df4.plot(ax=axes[1,1])

This code will generate a 2x2 grid of subplots, with each dataframe assigned to its own subplot.

Additional Note:

To ensure all subplots share the same x-axis, provide sharex=True to plt.subplots during creation.

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