To make matplotlib date manipulation so that the year tick shows up every 12 months, we can take the following steps −
- Set the figure size and adjust the padding between and around the subplots.
- Create d, y, s, years, months, monthsFmt and yearsFmt using Pandas, Numpy and matplotlib dates.
- Use "%B" in DateFormatter to show full month names.
- Ue "%Y" in DateFormatter to show years.
- Create a new figure or activate an existing figure.
- Add an 'ax' to the figure as part of a subplot arrangement.
- Plot "dts" and "s" data points using plot() method.
- Set minor or major axes locator and formatter. Set minor_locator as months so that the year tick will be displayed every 12 months.
- To display the figure, use show() method.
Example
import numpy as np
from matplotlib import pyplot as plt, dates as mdates
import pandas as pd
plt.rcParams["figure.figsize"] = [7.00, 3.50]
plt.rcParams["figure.autolayout"] = True
d = pd.date_range("2020-01-01", "2021-06-01", freq="7D")
y = np.cumsum(np.random.normal(size=len(d)))
s = pd.Series(y, index=d)
years = mdates.YearLocator()
months = mdates.MonthLocator()
monthsFmt = mdates.DateFormatter('%B')
yearsFmt = mdates.DateFormatter('\n%Y')
dts = s.index.to_pydatetime()
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(dts, s)
ax.xaxis.set_minor_locator(months)
ax.xaxis.set_minor_formatter(monthsFmt)
plt.setp(ax.xaxis.get_minorticklabels(), rotation=90)
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
plt.show()Output
It will produce the following output
