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How to Format a Datetime Axis in Matplotlib for Better Readability?

Patricia Arquette
Patricia ArquetteOriginal
2024-10-26 15:39:30626browse

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.

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