matplotlib DateFormatter 未显示带有 yyyy-mm-dd 列的正确日期 [英] matplotlib DateFormatter not showing correct dates with yyyy-mm-dd column

问题描述

我有一个带有两列的python数据框，y轴上的数字列(total_outbounds)，x轴上的日期列(月，请输入错误名称):

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:

以及当我运行以下代码以使用此数据框创建图形时:

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)

我收到一个X轴不是我想要的图形...我使用 mdates.DateFormatter 错误吗?希望在 X 轴上接收 mm/yy，而不是当前显示的 Apr、Jul 等.

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.

为了重现性，这里是带有 my_df.to_dict()

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}}

，我认为您应该能够使用pd.DataFrame.from_dict()将其从字典转换回数据框 my_df .如果有更可重现的方式来共享数据框，请告诉我.

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.

注释中的解决方案有效，但是现在我无法使用 plt.xaxis(rotation=50) 旋转次要刻度，这只旋转两个主要刻度滴答声...出现的 X 轴值也很奇怪(将 71 显示为年份?)

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?)

推荐答案

如评论中所述，Apr/Jul/Oct是次要刻度.

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

但是，建议不要增加主刻度线和副刻度线，而建议自定义主刻度线频率，禁用次刻度线，并使用 autofmt_xdate()设置日期刻度的样式:

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()

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