Plotting Dates and Times - ( Matplotlib Plots )

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Syntax

import matplotlib.pyplot as plt
import matplotlib.dates as mdates

plt.plot_date(x, y, fmt='.', tz=None, xdate=True, ydate=False, **kwargs)

Example

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas as pd

data = pd.read_csv('data.csv', parse_dates=['Date'], index_col='Date')

x = data.index
y = data['Value']

plt.plot_date(x, y, fmt='.')
plt.show()

Output

A line plot with dates on the x-axis and values on the y-axis.

Explanation

Matplotlib provides a function plot_date to plot time series data with dates on the x-axis. The x argument should be a sequence of date objects and the y argument should be the data values. The fmt argument specifies the marker style and color, similar to plot function.

In the above example, we first read in a CSV file with dates and data values using Pandas. We then extract the dates as the index and the data values as a column of the DataFrame. Finally, we plot the dates and values using the plot_date function.

Use

The plot_date function is useful for plotting time series data with dates on the x-axis, and is particularly well-suited for financial or economic data.

Important Points

• The plot_date function is used to plot time series data with dates on the x-axis
• The x argument should be a sequence of date objects and the y argument should be the data values
• The fmt argument specifies the marker style and color, and follows the same format as the plot function
• Matplotlib's dates module provides various date and time formatting options to customize the x-axis labels

Summary

In conclusion, plot_date is a convenient function provided by Matplotlib to plot time series data with dates on the x-axis. It takes in a sequence of date objects as the x argument and the data values as the y argument, and allows customization of the marker style and color using the fmt argument. Matplotlib's dates module provides various formatting options to customize the x-axis labels.