Why does my date axis formatting break when building with Pandas' built-in plot calls and not through Matplotlib?

Question

I collect aggregated data in Python using Pandas and Matlplotlib. My axis setup commands do not work as a function from which of two similar functions I call to make line graphs. A working case is, for example:

import datetime import pandas as pd import numpy as np import matplotlib.pyplot as plt import matplotlib.dates as mdates def format_x_date_month_day(ax): days = mdates.DayLocator() months = mdates.MonthLocator() # every month dayFmt = mdates.DateFormatter('%D') monthFmt = mdates.DateFormatter('%Y-%m') ax.figure.autofmt_xdate() ax.xaxis.set_major_locator(months) ax.xaxis.set_major_formatter(monthFmt) ax.xaxis.set_minor_locator(days) span_days = 90 start = pd.to_datetime("1-1-2012") idx = pd.date_range(start, periods=span_days).tolist() df=pd.DataFrame(index=idx, data={'A':np.random.random(span_days), 'B':np.random.random(span_days)}) plt.close('all') fig, ax = plt.subplots(1) ax.bar(df.index, df.A) # loop over columns here to do stacked plot format_x_date_month_day(ax) plt.show() 

(see matplotlib.org , for example, a loop to create a line-by-line graph.) This gives us

Another approach, which should work and be much simpler, is to use df.plot.bar(ax=ax, stacked=True) , however it does not allow formatting the date axis with mdates :

 plt.close('all') fig, ax = plt.subplots(1) df.plot.bar(ax=ax, stacked=True) format_x_date_month_day(ax) plt.show() 

How can mdates and ax.figure.autofmt_xdate() be made to play well with df.plot.bar ?