擅长:python、mysql、java
<p>您可以尝试<code>pd.to_datetime(df['actualDateTime'], unit='ms')</code></p>
<p><a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html" rel="nofollow noreferrer">http://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html</a></p>
<p>说这将表示在纪元,与变化's','ms','ns'。。。</p>
<h2>更新</h2>
<p>如果你想要14567899表格的时间戳。。</p>
<pre><code>import pandas as pd
import time
t = pd.Timestamp('2015-10-19 07:22:00')
time.mktime(t.timetuple())
>> 1445219520.0
</code></pre>
<h2>最新更新</h2>
<pre><code>df = pd.DataFrame(s1)
df1 = pd.to_datetime(df['Date'])
pd.DatetimeIndex(df1)
>>>DatetimeIndex(['2015-10-20 07:21:00', '2015-10-19 07:18:00',
'2015-10-19 07:15:00'],
dtype='datetime64[ns]', freq=None)
df1.astype(np.int64)
>>>0 1445325660000000000
1 1445239080000000000
2 1445238900000000000
df1.astype(np.int64) // 10**9
>>>0 1445325660
1 1445239080
2 1445238900
Name: Date, dtype: int64
</code></pre>