Matplotlib.axes.Axes.format_ydata() in Python
Last Updated :
19 Apr, 2020
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Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.
matplotlib.axes.Axes.format_ydata() Function
The Axes.format_ydata() function in axes module of matplotlib library is used to return y formatted as an y-value.
Syntax:
Axes.format_ydata(self, y)
Below examples illustrate the matplotlib.axes.Axes.format_ydata() function in matplotlib.axes:
Example 1:
# Implementation of matplotlib function import numpy as np import matplotlib.pyplot as plt import matplotlib.dates as mdates import matplotlib.cbook as cbook years = mdates.YearLocator() months = mdates.MonthLocator() years_fmt = mdates.DateFormatter('% Y') with cbook.get_sample_data('goog.npz') as datafile: data = np.load(datafile)['price_data'].view(np.recarray) fig, ax = plt.subplots() ax.plot('date', 'adj_close', data = data[:300], color ="green") ax.xaxis.set_major_locator(years) ax.format_ydata = lambda x: '$% 1.2f' % x ax.grid(True) fig.autofmt_xdate() fig.suptitle('matplotlib.axes.Axes.format_ydata() function\ Example', fontweight ="bold") plt.show() |
Output:
Example 2:
# Implementation of matplotlib function import numpy as np import matplotlib.pyplot as plt import matplotlib.dates as mdates import matplotlib.cbook as cbook years = mdates.YearLocator() months = mdates.MonthLocator() years_fmt = mdates.DateFormatter('% Y') with cbook.get_sample_data('goog.npz') as datafile: data = np.load(datafile)['price_data'] fig, ax = plt.subplots() ax.plot('date', 'adj_close', data = data, color ="k") ax.yaxis.set_major_locator(years) ax.yaxis.set_major_formatter(years_fmt) ax.yaxis.set_minor_locator(months) ax.format_ydata = mdates.DateFormatter('% Y') ax.grid(True) fig.suptitle('matplotlib.axes.Axes.format_ydata() function\ Example', fontweight ="bold") plt.show() |
Output:
