#lang en

<<TableOfContents()>>

= Description =

[[https://matplotlib.org/|Matplotlib]] is a comprehensive library for creating static, animated, and interactive visualizations in Python. 

= Snippets =

=== Standard import ===
{{{#!highlight python
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
}}}

=== Bar graph with 3 y-axi ===
{{{#!highlight python
x = np.arange(len(df['Index Column']))  # the label locations
width = 0.20  # the width of the bars

fig, ax1 = plt.subplots(figsize=(16,7))

ax1.bar(x - 1 * width, df['Column A'], width, label='Column A', color='C0')
ax1.set_ylabel('Column A', color='C0')
ax1.yaxis.label.set_size(18)
ax1.set_xticks(x)
ax1.set_xticklabels(df['Index Column'], rotation='vertical', size=15)
ax1.legend(bbox_to_anchor=(1, 1), prop={'size': 15})

ax2 = ax1.twinx()          # instantiate a second axes that shares the same x-axis
ax2.bar(x * width, df['Column B'], width, label='Column B', color='C1')
ax2.set_ylabel('Column B', color='C1')
ax2.yaxis.label.set_size(18)
ax2.legend(bbox_to_anchor=(1, .9), prop={'size': 15})
ax2.spines["right"].set_position(("axes", 1.0))

ax3 = ax1.twinx()
ax3.bar(x + 1 * width, df['Column C'], width, label='Column C', color='C2')
#ax3.set_yscale('log')
ax3.set_ylabel('Column C', color='C2')
ax3.yaxis.label.set_size(18)
ax3.legend(bbox_to_anchor=(1, .8), prop={'size': 15})
ax3.spines["right"].set_position(("axes", 1.06))

plt.show()
}}}