pandas 将字符串转换为日期 [带年份和季度]
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Convert String to Date [With Year and Quarter]
提问by hoof_hearted
I have a pandas dataframe, where one column contains a string for the year and quarter in the following format:
我有一个Pandas数据框，其中一列包含以下格式的年份和季度的字符串：
2015Q1
My Question:?How do I convert this into two datetime columns, one for the year and one for the quarter.
我的问题：？如何将其转换为两个日期时间列，一个用于年份，一个用于季度。
回答by jezrael
You can use split, then cast column yearto intand if necessary add Qto column q:
您可以使用split，然后将 column 强制转换year为int并在必要时添加Q到 column q：
df = pd.DataFrame({'date':['2015Q1','2015Q2']})
print (df)
date
0 2015Q1
1 2015Q2
df[['year','q']] = df.date.str.split('Q', expand=True)
df.year = df.year.astype(int)
df.q = 'Q' + df.q
print (df)
date year q
0 2015Q1 2015 Q1
1 2015Q2 2015 Q2
Also you can use Period:
你也可以使用Period：
df['date'] = pd.to_datetime(df.date).dt.to_period('Q')
df['year'] = df['date'].dt.year
df['quarter'] = df['date'].dt.quarter
print (df)
date year quarter
0 2015Q1 2015 1
1 2015Q2 2015 2
回答by Julien Marrec
You could also construct a datetimeIndex and call year and quarter on it.
您还可以构造一个 datetimeIndex 并在其上调用 year 和季度。
df.index = pd.to_datetime(df.date)
df['year'] = df.index.year
df['quarter'] = df.index.quarter
date year quarter
date
2015-01-01 2015Q1 2015 1
2015-04-01 2015Q2 2015 2
Note that you don't even need a dedicated column for year and quarter if you have a datetimeIndex, you could do a groupby like this for example: df.groupby(df.index.quarter)
请注意，如果您有 datetimeIndex，您甚至不需要年和季度的专用列，您可以执行这样的 groupby，例如： df.groupby(df.index.quarter)
