轻描淡写地访问tick标签并更改它们:
import pandas as pd
import numpy as np
date_range = pd.date_range('2014-01-01', '2015-01-01', freq='MS')
df = pd.DataFrame({'foo': np.random.randint(0, 10, len(date_range))}, index=date_range)
ax = df.plot(kind='bar')
xtl=[item.get_text()[:10] for item in ax.get_xticklabels()]
_=ax.set_xticklabels(xtl)
date_range
:
Timestamp
您只能通过您喜欢的strftime完全通过新标签:
Timestamp.strftime
这不是最漂亮的答案,但它可以始终如一地完成工作。
对我来说最简单的解决方案是:date_range = pd.date_range('2014-01-01', '2015-01-01', freq='MS')
date_range = date_range.map(lambda t: t.strftime('%Y-%m-%d'))
print date_range
array([2014-01-01, 2014-02-01, 2014-03-01, 2014-04-01, 2014-05-01,
2014-06-01, 2014-07-01, 2014-08-01, 2014-09-01, 2014-10-01,
2014-11-01, 2014-12-01, 2015-01-01], dtype=object)
ax.set_xticklabels([pandas_datetime.strftime("%Y-%m-%d") for pandas_datetime in df.index])