formatting timeseries x-axis in pandas/matplotlib

Question

I would like to show each month abbreviation, as well as the year on the year.

I am quite close. The issue I am currently having is that the years are incorrect. I have

Answer 1

After some playing around it seems to work if you specify the axis and then plot onto that (rather than call the pandas plot function).

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

from matplotlib.dates import MonthLocator, WeekdayLocator, DateFormatter, YearLocator

indx = pd.date_range('2017-04-01', '2019-01-01')
s = pd.Series(np.random.randn(len(indx)), index=indx)

df = pd.DataFrame(s)

fig, ax = plt.subplots(1)
ax.plot(df)

months = MonthLocator(range(1, 13), bymonthday=1, interval=1)
monthsFmt = DateFormatter("%b")
years = YearLocator(1, month=4, day=1)
yrsFmt = DateFormatter("\n %Y")

ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yrsFmt)


ax.xaxis.set_minor_locator(months)
ax.xaxis.set_minor_formatter(monthsFmt)

fig.show()

Also note that I changed %y to %Y so it is formatted as 2017/2018 rather than 17/18.