python - How do you iterate through groups in a pandas Dataframe, operate on each group, then assign values to the original dataframe? - 


    yearcount = df[['antibiotic', 'order_date', 'antiyearcount']]      yeargroups = yearcount.groupby('order_date')      year in yeargroups:         yearcount['antiyearcount'] =year.groupby('antibiotic'['antibiotic'].transform(pd.series.value_counts)

in case, yearcount dataframe containing 'order_date', 'antibiotic', 'antiyearcount'. have cleaned 'order_date' contain year of order. want group yearcount years in 'order_date', count number of times each 'antibiotic' appears in each "year group" assign value yearcount's 'antiyearcount' variable. help!

i think need add new column order_date groupby , possible usesize instead pd.series.value_counts same output:

df = pd.dataframe({'antibiotic':list('accbbb'),                    'antiyearcount':[4,5,4,5,5,4],                    'c':[7,8,9,4,2,3],                    'd':[1,3,5,7,1,0],                    'e':[5,3,6,9,2,4],                    'order_date': pd.to_datetime(['2012-01-01']*3+['2012-01-02']*3)})  print (df)    c  d  e  antiyearcount antibiotic order_date 0  7  1  5              4          2012-01-01 1  8  3  3              5          c 2012-01-01 2  9  5  6              4          c 2012-01-01 3  4  7  9              5          b 2012-01-02 4  2  1  2              5          b 2012-01-02 5  3  0  4              4          b 2012-01-02  #copy remove warning #https://stackoverflow.com/a/45035966/2901002 yearcount = df[['antibiotic', 'order_date', 'antiyearcount']].copy() yearcount['antiyearcount'] = yearcount.groupby(['order_date','antibiotic'])['antibiotic'] \                                       .transform('size') print (yearcount)   antibiotic order_date  antiyearcount 0          2012-01-01              1 1          c 2012-01-01              2 2          c 2012-01-01              2 3          b 2012-01-02              3 4          b 2012-01-02              3 5          b 2012-01-02              3 
yearcount['antiyearcount'] = yearcount.groupby(['order_date','antibiotic'])['antibiotic'] \                                       .transform(pd.series.value_counts) print (yearcount)   antibiotic order_date  antiyearcount 0          2012-01-01              1 1          c 2012-01-01              2 2          c 2012-01-01              2 3          b 2012-01-02              3 4          b 2012-01-02              3 5          b 2012-01-02              3

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