<p>@unutbu:多谢了:我到处找相关问题的答案!在</p>
<p>@eliu:我改编了unutbu的优秀答案来演示如何定义列表(创建不同的“dateutil”规则),让您完全控制显示哪些x记号。试着依次取消对下面每个示例的注释,并使用这些值来查看效果。希望这有帮助。在</p>
<pre><code>import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
idx = pd.date_range('2017-01-01 05:03', '2017-01-01 18:03', freq = 'min')
df = pd.Series(np.random.randn(len(idx)), index = idx)
fig, ax = plt.subplots()
# Choose which major hour ticks are displayed by creating a 'dateutil' rule e.g.:
# Only use the hours in an explicit list:
# hourlocator = mdates.HourLocator(byhour=[6,12,8])
# Use the hours in a range defined by: Start, Stop, Step:
# hourlocator = mdates.HourLocator(byhour=range(8,15,2))
# Use every 3rd hour:
# hourlocator = mdates.HourLocator(interval = 3)
# Set the format of the major x-ticks:
majorFmt = mdates.DateFormatter('%H:%M')
ax.xaxis.set_major_locator(hourlocator)
ax.xaxis.set_major_formatter(majorFmt)
#... and ditto to set minor_locators and minor_formatters for minor x-ticks if needed as well)
ax.plot(df.index, df.values, color = 'black', linewidth = 0.4)
fig.autofmt_xdate() # optional: makes 30 deg tilt on tick labels
plt.show()
</code></pre>