转换“年"和“一年中的一周"要“更新"的列在 pandas [英] Converting "year" and "week of year" columns to "date" in Pandas

问题描述

为了将年份和年份的两列转换为日期，我希望这样做:

In order to convert two columns with year and week of year into date I would expect to do something like:

df['formatted_date'] = df.year*100+df.weekofyear
df['date'] = pd.to_datetime(df['formatted_date'], format='%Y%w')

但是，它不起作用，给出 ValueError :

However, it does not work, giving ValueError:

ValueError: unconverted data remains: 01

解决方法

我发现解决方法是将一年中的某周转换为一年中的某天，并使用year-dayofyear ％Y％j 格式:

df['formatted_date'] = df.year*1000+df.weekofyear*7-6 
df['date'] = pd.to_datetime(df['formatted_date'], format='%Y%j')

第一行变得丑陋，但这可以正常工作.一年中的星期在(00,53)范围内.有什么想法，为什么优雅的方式行不通?

The first line becomes ugly, but this works fine. Week of year is in the range (00,53). Any ideas, why is the elegant way not working?

推荐答案

您需要在一周中的某天组合％w -

You need combine %w for day of week - explanation with %W for week:

http://strftime.org/:

一年中的一周号(星期一为一周的第一天)，以十进制数表示.在新的一年中，第一个星期一之前的所有天均视为在第0周.

Week number of the year (Monday as the first day of the week) as a decimal number. All days in a new year preceding the first Monday are considered to be in week 0.

对于％w :

工作日(十进制)，其中0是星期日，6是星期六.

Weekday as a decimal number, where 0 is Sunday and 6 is Saturday.

---

df = pd.DataFrame({'year':[2015, 2018],
                   'weekofyear':[10,12]})

dates = df.year*100+df.weekofyear
@adde
df['date'] = pd.to_datetime(dates.astype(str) + '0', format='%Y%W%w')
print (df)

   year  weekofyear  formatted_date       date
0  2015  10          201510         2015-03-15
1  2018  12          201812         2018-03-25

另一种解决方案:

#added 0 only for demontration, you can remove it
df['formatted_date'] = df.year * 1000 + df.weekofyear * 10 + 0
df['date'] = pd.to_datetime(df['formatted_date'], format='%Y%W%w')
print (df)

   year  weekofyear  formatted_date       date
0  2015  10          2015100        2015-03-15
1  2018  12          2018120        2018-03-25

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