To plot a kernel density plot of dates in Pandas using Matplotlib, we can take the following steps −
- Set the figure size and adjust the padding between and around the subplots.
- Create a Pandas dataframe.
- Format the Pandas date column.
- Plot the Pandas date as kernel density estimate class by name.
- Set xtick labels using set_xticklabels() method.
- To display the figure, use show() method.
Example
import pandas as pd import numpy as np import datetime import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True dates = pd.date_range('2010-01-01', periods=31, freq='D') df = pd.DataFrame(np.random.choice(dates, 100), columns=['dates']) df['ordinal'] = [x.toordinal() for x in df.dates] ax = df['ordinal'].plot(kind='kde') x_ticks = ax.get_xticks() ax.set_xticks(x_ticks[::2]) xlabels = [datetime.datetime.fromordinal(int(x)) .strftime('%Y-%m-%d') for x in x_ticks[::2]] ax.set_xticklabels(xlabels) plt.show()