to_datetime 接受格式字符串：
In [92]:
t = 20070530
pd.to_datetime(str(t), format='%Y%m%d')
Out[92]:
Timestamp('2007-05-30 00:00:00')
例：
In [94]:
t = 20070530
df = pd.DataFrame({'date':[t]*10})
df
Out[94]:
date
0 20070530
1 20070530
2 20070530
3 20070530
4 20070530
5 20070530
6 20070530
7 20070530
8 20070530
9 20070530
In [98]:
df['DateTime'] = df['date'].apply(lambda x: pd.to_datetime(str(x), format='%Y%m%d'))
df
Out[98]:
date DateTime
0 20070530 2007-05-30
1 20070530 2007-05-30
2 20070530 2007-05-30
3 20070530 2007-05-30
4 20070530 2007-05-30
5 20070530 2007-05-30
6 20070530 2007-05-30
7 20070530 2007-05-30
8 20070530 2007-05-30
9 20070530 2007-05-30
In [99]:
df.dtypes
Out[99]:
date int64
DateTime datetime64[ns]
dtype: object
实际上，将类型转换为字符串然后将整个系列转换为日期时间要快得多，而不是对每个值调用apply：
In [102]:
df['DateTime'] = pd.to_datetime(df['date'].astype(str), format='%Y%m%d')
df
Out[102]:
date DateTime
0 20070530 2007-05-30
1 20070530 2007-05-30
2 20070530 2007-05-30
3 20070530 2007-05-30
4 20070530 2007-05-30
5 20070530 2007-05-30
6 20070530 2007-05-30
7 20070530 2007-05-30
8 20070530 2007-05-30
9 20070530 2007-05-30
In [104]:
%timeit df['date'].apply(lambda x: pd.to_datetime(str(x), format='%Y%m%d'))
100 loops, best of 3: 2.55 ms per loop
In [105]:
%timeit pd.to_datetime(df['date'].astype(str), format='%Y%m%d')
1000 loops, best of 3: 396 µs per loop
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