Matplotlib.ticker.IndexFormatter class in Python (original) (raw)

Last Updated : 27 Apr, 2020

Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

matplotlib.ticker.IndexFormatter

The matplotlib.ticker.IndexFormatter class is a subclass of matplotlib.ticker class and is used to format the position x that is the nearest i-th label where i = int(x + 0.5). The positions with i len(list) have 0 tick labels.

Syntax: class matplotlib.ticker.IndexFormatter(labels)Parameter :

• labels: It is a list of labels.

Example 1:

Python3 `

import numpy as np import matplotlib.pyplot as plt import matplotlib as mpl

create dummy data

x = ['str{}'.format(k) for k in range(20)] y = np.random.rand(len(x))

create an IndexFormatter

with labels x

x_fmt = mpl.ticker.IndexFormatter(x)

fig,ax = plt.subplots()

ax.plot(y)

set our IndexFormatter to be

responsible for major ticks

ax.xaxis.set_major_formatter(x_fmt)

`

Output: Example 2:

Python3 `

from matplotlib.ticker import IndexFormatter, IndexLocator import pandas as pd import matplotlib.pyplot as plt

years = range(2015, 2018) fields = range(4) days = range(4) bands = ['R', 'G', 'B']

index = pd.MultiIndex.from_product( [years, fields], names =['year', 'field'])

columns = pd.MultiIndex.from_product( [days, bands], names =['day', 'band'])

df = pd.DataFrame(0, index = index, columns = columns)

df.loc[(2015, ), (0, )] = 1 df.loc[(2016, ), (1, )] = 1 df.loc[(2017, ), (2, )] = 1 ax = plt.gca() plt.spy(df)

xbase = len(bands) xoffset = xbase / 2 xlabels = df.columns.get_level_values('day')

ax.xaxis.set_major_locator(IndexLocator(base = xbase, offset = xoffset))

ax.xaxis.set_major_formatter(IndexFormatter(xlabels))

plt.xlabel('Day') ax.xaxis.tick_bottom()

ybase = len(fields) yoffset = ybase / 2 ylabels = df.index.get_level_values('year')

ax.yaxis.set_major_locator(IndexLocator(base = ybase, offset = yoffset))

ax.yaxis.set_major_formatter(IndexFormatter(ylabels))

plt.ylabel('Year')

plt.show()

`

Output: