Python Pandas convert month/year dataframe with one column to dataframe where each row is one year-CodePudding

Given a Pandas dataframe of the form

January-2021,0.294 
February-2021,0.252 
March-2021,0.199 
...
January-2022,0.384 
February-2022,0.333 
March-2022,0.271 
...

how do I transform it to a dataframe with 12 columns, one for each month, so it looks like

year,January,February,March,...
2021,0.294,0.252,0.199,...
2022,0.384,0.333,0.271,...

CodePudding user response：

You can do:

# `month-year` is name of date column
dates = df['month-year'].str.extract('(?P<month>\w )-(?P<year>\d )')

# `data` is name of data column
pd.crosstab(dates['year'], dates['month'], df['data'], aggfunc='first')

Output:

month  February  January  March
year                           
2021      0.252    0.294  0.199
2022      0.333    0.384  0.271

CodePudding user response：

You can use