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:
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:
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, )] = 1df.loc[(2016, ), (1, )] = 1df.loc[(2017, ), (2, )] = 1ax = plt.gca() plt.spy(df)   xbase = len(bands) xoffset = xbase / 2xlabels = 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 / 2ylabels = 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:
