将 2010 Q1 转换为日期时间为 2010-3-31

2022-01-11 00:00:00 python pandas time-series data-cleaning

问题描述

如何找到将 Year_Q 转换为日期时间的智能解决方案?我尝试使用

How to find a smart solution to turn Year_Q to datetime? I tried to use 

pd.to_datetime(working_visa_nationality['Year_Q'])

但得到错误说这无法识别.所以我尝试了一个愚蠢的方法:

but got error says that this cannot be recognized. So I tried a stupid way as:

working_visa_nationality['Year'] = working_visa_nationality.Year_Q.str.slice(0,4)
working_visa_nationality['Quarter'] = working_visa_nationality.Year_Q.str.slice(6,8)

现在我发现了一个问题:确实可以按年份对数据进行分组，但是很难将季度包含在我的折线图中.

And now I found a problem: it is true that I can groupby data by the year, but it is difficult to include the quarter to my line plot.

那么如何让 2010 Q1 像 2010-3-31 一样呢?

So how to make 2010 Q1 like 2010-3-31?

解决方案

我有点改变MaxU 回答:

I a bit changed MaxU answer:

df = pd.DataFrame({'Year_Q': ['2010 Q1', '2015 Q2']})

df['Dates']  = pd.PeriodIndex(df['Year_Q'].str.replace(' ', ''), freq='Q').to_timestamp()
print (df)
    Year_Q      Dates
0  2010 Q1 2010-01-01
1  2015 Q2 2015-04-01


df['Dates']  = pd.PeriodIndex(df['Year_Q'].str.replace(' ', ''), freq='Q').to_timestamp(how='e')
print (df)
    Year_Q      Dates
0  2010 Q1 2010-03-31
1  2015 Q2 2015-06-30

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