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.PercentFormatter
The matplotlib.ticker.PercentFormatter class is used to format numbers as a percentage.
Syntax: class matplotlib.ticker.PercentFormatter(xmax=100, decimals=None, symbol=’%’, is_latex=False)
Parameters:
- xmax: It is a float value that determines how the number is converted into a percentage.
- decimals: It is either an integer value or None. It determines the number of decimal places to place after the point. If None (the default), the number will be computed automatically.
- symbol : It is either a string or none that gets appended to the label.
- is_latex: It is a boolean value. If False, reserved LaTeX characters in symbol are eliminated.
Example 1:
import pandas as pd import numpy as np import matplotlib.ticker as mtick from matplotlib.ticker import PercentFormatter df = pd.DataFrame(np.random.randn(100, 5)) ax = df.plot() ax.yaxis.set_major_formatter(mtick.PercentFormatter(5.0)) |
Output:
Example 2:
import matplotlib.pyplot as plt import numpy as np import matplotlib.ticker as mtick from matplotlib.ticker import PercentFormatter data = [8, 12, 15, 17, 18, 18.5] perc = np.linspace(0, 100, len(data)) fig = plt.figure(1, (7, 4)) ax = fig.add_subplot(1, 1, 1) ax.plot(perc, data) xticks = mtick.PercentFormatter(0.5) ax.xaxis.set_major_formatter(xticks) plt.show() |
Output:
