CODEWITHSUNDEEP
pythonpandas
Bahador Saket
Bahador Saket

Reputation: 1035

Sort dataframe based on a specific column after GroupBy

I initially had a dataframe called df. I grouped my dataframe based on specific criteria that I had in mind using the following command.

df= df.groupby([df['Date'].dt.strftime('%B'), 'Project','Name'])['Hours'].sum()

As a result of this I got the following data frame.

**Date**   **Project**                     **Name**                          **Hours**
September  Project 1                          x                                1.00
                                              x                                3.00
           Project 2                          a                                16.00
                                              z                                4.00
           Project 3                          y                                1.00
June       Project 1                          x                                1.00
                                              x                                45.00
                                              y                                6.00
July       Project 2                          a                                16.00
                                              z                                4.00
           Project 3                          y                                1.00

Now, I am trying to sort this dataframe based on ``Date". In other words, I want to have June, July and September rather than having September, June, July. so here is what I am hoping to get:

**Date**   **Project**                     **Name**                          **Hours**
June       Project 1                          x                                1.00
                                              x                                45.00
                                              y                                6.00
July       Project 2                          a                                16.00
                                              z                                4.00
           Project 3                          y                                1.00
September  Project 1                          x                                1.00
                                              x                                3.00
           Project 2                          a                                16.00
                                              z                                4.00
           Project 3                          y                                1.00

Any idea how to do it?

Upvotes: 2

Views: 53

Answers (1)

jezrael
jezrael

Reputation: 862511

Aggregate by months and then use rename by dictionary:

MonthDict={ 1 : "January",
       2 : "February",
       3 : "March",
       4 : "April",
       5 : "May",
       6 : "June",
       7 : "July",
       8 : "August",
       9 : "September",
       10 : "October",
       11 : "November",
       12 : "December"
}

df= (df.groupby([df['Date'].dt.month, 'Project','Name'])['Hours'].sum()
       .rename(MonthDict, level=0))

If datetimes are sorted in original, is possible use sort=False in groupby for avoid sorting:

df= df.groupby([df['Date'].dt.strftime('%B'), 'Project','Name'], sort=False)['Hours'].sum()

Upvotes: 1

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