Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.
matplotlib.axis.Axis.axis_date() Function
The Axis.axis_date() function in axis module of matplotlib library is used to set up axis ticks and labels treating data along this axis as dates.
Syntax: Axis.axis_date(self, tz=None)
Parameters: This method accepts the following parameters.
- tz : This parameter is the timezone used to create date labels.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axis.Axis.axis_date() function in matplotlib.axis:
Example 1:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import datetime as dt import matplotlib.pyplot as plt from matplotlib.dates import DateFormatter, MinuteLocator x = [16.7,16.8,17.1,17.4] y = [15,17,14,16] plt.plot(x, y) plt.gca().yaxis.axis_date() plt.title("Matplotlib.axis.Axis.axis_date()\ Function Example", fontsize = 12, fontweight ='bold') plt.show() |
Output:
Example 2:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis from datetime import datetime import matplotlib.pyplot as plt from matplotlib.dates import ( DateFormatter, AutoDateLocator, AutoDateFormatter, datestr2num ) days = [ '30/01/2019', '31/01/2019', '01/02/2019', '02/02/2019', '03/02/2019', '04/02/2019'] data1 = [2, 5, 13, 6, 11, 7] data2 = [6, 3, 10, 3, 6, 5] z = datestr2num([ datetime.strptime(day, '%d/%m/%Y').strftime('%m/%d/%Y') for day in days ]) r = 0.25 figure = plt.figure(figsize =(8, 4)) axes = figure.add_subplot(111) axes.bar(z - r, data1, width = 2 * r, color ='g', align ='center', tick_label = days) axes.bar(z + r, data2, width = 2 * r, color ='y', align ='center', tick_label = days) axes.xaxis.axis_date() plt.title("Matplotlib.axis.Axis.axis_date()\ Function Example", fontsize = 12, fontweight ='bold') plt.show() |
Output:
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