Home >Backend Development >Python Tutorial >How to Format a Datetime Axis in Matplotlib for Better Readability?
Formatting a Datetime Axis
When plotting a Series with a datetime index, the x-axis may display hours, minutes, and seconds along with the year and month. To simplify the graph's readability, it is possible to remove this excessive time information.
Consider a sample Series:
2014-01-01 7 2014-02-01 8 2014-03-01 9 2014-04-01 8
Plotting this Series would initially display a graph with a crowded x-axis.
import matplotlib.pyplot as plt import pandas as pd series = pd.Series([7, 8, 9, 8], index=pd.date_range('2014-01', periods=4, freq='MS')) plt.plot(series.index, series.values) plt.show()
To resolve this issue, Matplotlib's formatters can be utilized to control the display format of the x-axis ticks.
import numpy as np import matplotlib.dates as mdates # generate data N = 30 drange = pd.date_range("2014-01", periods=N, freq="MS") np.random.seed(365) # for reproducible values values = {'values':np.random.randint(1,20,size=N)} df = pd.DataFrame(values, index=drange) # plot fig, ax = plt.subplots() ax.plot(df.index, df.values) # set tick formatters ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m")) ax.xaxis.set_minor_formatter(mdates.DateFormatter("%Y-%m")) plt.xticks(rotation=90) plt.show()
By specifying the "%Y-%m" format string, the x-axis labels now display the year and month in a simplified format.
The above is the detailed content of How to Format a Datetime Axis in Matplotlib for Better Readability?. For more information, please follow other related articles on the PHP Chinese website!