# 在熊猫时间序列图中从 Axes.get_xlim() 获取可用日期(Getting usable dates from Axes.get_xlim() in a pandas time series plot)

``````import pandas
from matplotlib import dates
import matplotlib.pyplot as plt
from datetime import datetime
from numpy.random import randn

ts = pandas.Series(randn(10000), index=pandas.date_range('1/1/2000',
periods=10000, freq='H'))
ts.plot()
ax = plt.gca()

ax.set_xlim(datetime(2000,1,1))
d1, d2 = ax.get_xlim()
print "%s(%s) to %s(%s)" % (d1, type(d1), d2, type(d2))

print "Using matplotlib: %s" % dates.num2date(d1)
print "Using datetime: %s" % datetime.fromtimestamp(d1)
``````

``````262968.0 (<type 'numpy.float64'>) to 272967.0 (<type 'numpy.float64'>)
Using matplotlib: 0720-12-25 00:00:00+00:00
Using datetime: 1970-01-03 19:02:48
``````

## 破解以获取可用值

``````In [66]: d1, d2 = ax.get_xlim()

In [67]: time.gmtime(d1*60*60)
Out[67]: time.struct_time(tm_year=2000, tm_mon=1, tm_mday=1, tm_hour=0, tm_min=0, tm_sec=0, tm_wday=5, tm_yday=1, tm_isdst=0)
``````

matplotlib.dates 的当前行为：

datetime 对象转换为浮点数，表示自 0001-01-01 UTC 以来的天数加上 1。例如，0001-01-01, 06:00 是 1.25，而不是 0.25。 辅助函数 date2num()、num2date() 和 drange() 用于促进与日期时间和数字范围的轻松转换。

pandas.tseries.converter.PandasAutoDateFormatter() 似乎建立在此之上，所以：

``````x = pandas.date_range(start='01/01/2000', end='01/02/2000')
plt.plot(x, x)
matplotlib.dates.num2date(plt.gca().get_xlim()[0])
``````

``````datetime.datetime(2000, 1, 1, 0, 0, tzinfo=<matplotlib.dates._UTC object at 0x7ff73a60f290>)
``````

``````# First convert to pandas Period
period = pandas.tseries.period.Period(ordinal=int(d1), freq=ax.freq)
# Then convert to pandas timestamp
ts = period.to_timestamp()
# Then convert to date object
dt = ts.to_datetime()
``````