matplotlib DateFormatter not showing correct dates with yyyy-mm-dd column

Question

I have a python dataframe with two columns, a numeric column (total_outbounds) on the y-axis and a date column (month, pardon the bad name) for x-axis:

and when when I run this code to create a graph using this dataframe:

fig,ax = plt.subplots()

my_df.plot(x='month', y='total_outbounds', ax=ax, label = 'Total Email Outbounds on LE Change')
ax.xaxis.set_major_formatter(mdates.DateFormatter('%m/%y'))
plt.xlabel('')
plt.title('Total LE Changes and Outbounds by Month', pad = 10)

I receive a graph where the X-axis is not what I was hoping for... Am I using mdates.DateFormatter wrong? Looking to receive mm/yy on the X-Axis, instead of the Apr, Jul, etc. that are currently appearing.

For reproducibility, here is the dataframe output with my_df.to_dict()

{'month': {0: Timestamp('2020-01-01 00:00:00'),
  1: Timestamp('2020-02-01 00:00:00'),
  2: Timestamp('2020-03-01 00:00:00'),
  3: Timestamp('2020-04-01 00:00:00'),
  4: Timestamp('2020-05-01 00:00:00'),
  5: Timestamp('2020-06-01 00:00:00'),
  6: Timestamp('2020-07-01 00:00:00'),
  7: Timestamp('2020-08-01 00:00:00'),
  8: Timestamp('2020-09-01 00:00:00'),
  9: Timestamp('2020-10-01 00:00:00'),
  10: Timestamp('2020-11-01 00:00:00'),
  11: Timestamp('2020-12-01 00:00:00'),
  12: Timestamp('2021-01-01 00:00:00'),
  13: Timestamp('2021-02-01 00:00:00'),
  14: Timestamp('2021-03-01 00:00:00')},
 'total_outbounds': {0: 26364,
  1: 33081,
  2: 35517,
  3: 34975,
  4: 40794,
  5: 51659,
  6: 50948,
  7: 65332,
  8: 82839,
  9: 96408,
  10: 86923,
  11: 99176,
  12: 122199,
  13: 116057,
  14: 108439}}

and I think you should be able to use pd.DataFrame.from_dict() to turn that back into a dataframe my_df from the dictionary. Please let me know if there's a more reproducible way to share the dataframe.

Edit: the solution in the comments works, however now I cannot rotate the minor ticks using plt.xaxis(rotation=50), this only rotates the two major ticks... also the X-axis values appearing are odd (showing 71 as the year?)

Answer 1

As discussed in the comments, the Apr/Jul/Oct are minor ticks.

However, rather than customizing both major/minor ticks, I suggest increasing the major tick frequency, disabling minor ticks, and using autofmt_xdate() to style the date ticks:

fig, ax = plt.subplots()
ax.plot(df.month, df.total_outbounds, label='Total Email Outbounds on LE Change')
ax.legend()

# increase the major tick frequency (8 ticks in this example)
start, end = ax.get_xlim()
xticks = np.linspace(start, end, 8)
ax.set_xticks(xticks)
ax.set_xticklabels(xticks)

# set date format
ax.xaxis.set_major_formatter(mdates.DateFormatter('%m/%y'))

# use matplotlib's auto date styling
fig.autofmt_xdate()

# disable minor ticks
plt.minorticks_off()