Python 从给定日期提取日、月和年的最快方法是什么？
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Which is the fastest way to extract day, month and year from a given date?
提问by ram
I read a csv file containing 150,000 lines into a pandas dataframe. This dataframe has a field, Date, with the dates in yyyy-mm-ddformat. I want to extract the month, day and year from it and copy into the dataframes' columns, Month, Dayand Yearrespectively. For a few hundred records the below two methods work ok, but for 150,000 records both take a ridiculously long time to execute. Is there a faster way to do this for 100,000+ records?
我将一个包含 150,000 行的 csv 文件读入熊猫数据帧。这个数据框有一个字段，Date，日期yyyy-mm-dd格式。我想从中提取月、日和年Month，Day并Year分别复制到数据框的列中。对于几百条记录，以下两种方法可以正常工作，但是对于 150,000 条记录，它们都需要非常长的时间来执行。有没有更快的方法来处理 100,000 多条记录？
First method:
第一种方法：
df = pandas.read_csv(filename)
for i in xrange(len(df)):
df.loc[i,'Day'] = int(df.loc[i,'Date'].split('-')[2])
Second method:
第二种方法：
df = pandas.read_csv(filename)
for i in xrange(len(df)):
df.loc[i,'Day'] = datetime.strptime(df.loc[i,'Date'], '%Y-%m-%d').day
Thank you.
谢谢你。
采纳答案by Jeff
In 0.15.0 you will be able to use the new .dt accessor to do this nice syntactically.
在 0.15.0 中，您将能够使用新的 .dt 访问器在语法上做到这一点。
In [36]: df = DataFrame(date_range('20000101',periods=150000,freq='H'),columns=['Date'])
In [37]: df.head(5)
Out[37]:
Date
0 2000-01-01 00:00:00
1 2000-01-01 01:00:00
2 2000-01-01 02:00:00
3 2000-01-01 03:00:00
4 2000-01-01 04:00:00
[5 rows x 1 columns]
In [38]: %timeit f(df)
10 loops, best of 3: 22 ms per loop
In [39]: def f(df):
df = df.copy()
df['Year'] = DatetimeIndex(df['Date']).year
df['Month'] = DatetimeIndex(df['Date']).month
df['Day'] = DatetimeIndex(df['Date']).day
return df
....:
In [40]: f(df).head()
Out[40]:
Date Year Month Day
0 2000-01-01 00:00:00 2000 1 1
1 2000-01-01 01:00:00 2000 1 1
2 2000-01-01 02:00:00 2000 1 1
3 2000-01-01 03:00:00 2000 1 1
4 2000-01-01 04:00:00 2000 1 1
[5 rows x 4 columns]
From 0.15.0 on (release in end of Sept 2014), the following is now possible with the new .dt accessor:
从 0.15.0 开始（2014 年 9 月末发布），现在可以使用新的 .dt 访问器执行以下操作：
df['Year'] = df['Date'].dt.year
df['Month'] = df['Date'].dt.month
df['Day'] = df['Date'].dt.day
回答by Nim J
I use below code which works very well for me
我使用下面的代码，这对我来说效果很好
df['Year']=[d.split('-')[0] for d in df.Date]
df['Month']=[d.split('-')[1] for d in df.Date]
df['Day']=[d.split('-')[2] for d in df.Date]
df.head(5)
