Pandas DataFrame Groupby two columns and get counts

Question

I have a pandas dataframe in the following format   df   pd DataFrame   1 1  1 1  1 1  2 6  2 5  3 4 2 6 2 6 3 4 3 4 2 6 1 1 1 1 3 3   list  AAABBBBABCBDDD     1 1  1 7  2 5  2 6  3 3  3 8 4 0 4 2 4 3 4 5 4 6 4 7 4 7 4 8     x y z   x y   x y z n   x u   x   x u v   x y z   x   x u v b   -   x y   x y z   x   x u v w     1   3   3   2   4   2   5   3   6   3   5   1   1   1     T df columns     col1   col2   col3   col4   col5     df      col1 col2 col3     col4 col5 0   1 1    A  1 1    x y z    1 1   1 1    A  1 7      x y    3 2   1 1    A  2 5  x y z n    3 3   2 6    B  2 6      x u    2 4   2 5    B  3 3        x    4 5   3 4    B  3 8    x u v    2 6   2 6    B    4    x y z    5 7   2 6    A  4 2        x    3 8   3 4    B  4 3  x u v b    6 9   3 4    C  4 5        -    3 10  2 6    B  4 6      x y    5 11  1 1    D  4 7    x y z    1 12  1 1    D  4 7        x    1 13  3 3    D  4 8  x u v w    1   Now I want to group this by two columns like following   df groupby   col5   col2    reset index     OutPut                index col1 col2 col3     col4 col5 col5 col2                                       1    A    0      0  1 1    A  1 1    x y z    1      D    0     11  1 1    D  4 7    x y z    1           1     12  1 1    D  4 7        x    1           2     13  3 3    D  4 8  x u v w    1 2    B    0      3  2 6    B  2 6      x u    2           1      5  3 4    B  3 8    x u v    2 3    A    0      1  1 1    A  1 7      x y    3           1      2  1 1    A  2 5  x y z n    3           2      7  2 6    A  4 2        x    3      C    0      9  3 4    C  4 5        -    3 4    B    0      4  2 5    B  3 3        x    4 5    B    0      6  2 6    B    4    x y z    5           1     10  2 6    B  4 6      x y    5 6    B    0      8  3 4    B  4 3  x u v b    6   I want to get the count by each row like following  Expected Output   col5 col2 count 1    A      1      D      3 2    B      2 etc      How to get my expected output  And I want to find largest count for each  col2  value

User · Answer

You can just use the built-in function count follow by the groupby function  df groupby   col5   col2    count

User · Answer

Inserting data into a pandas dataframe and providing column name      import pandas as pd df   pd DataFrame    A   C   A   B   C   A   B   B   A   A      ONE   TWO   ONE   ONE   ONE   TWO   ONE   TWO   ONE   THREE     T df columns      Alphabet   Words    print df     printing dataframe    This is our printed data     For making a group of dataframe in pandas and counter   You need to provide one more column which counts the grouping  let s call that column as   COUNTER  in  dataframe   Like this   df  COUNTER    1        initially  set that counter to 1  group data   df groupby   Alphabet   Words     COUNTER   sum    sum function print group data    OUTPUT

User · Answer

Should you want to add a new column  say  count column   containing the groups  counts into the dataframe   df count column df groupby   col5   col2    col5 transform  count      I picked  col5  as it contains no nan

User · Answer

You are looking for size   In  11   df groupby   col5    col2    size   Out 11   col5  col2 1     A       1       D       3 2     B       2 3     A       3       C       1 4     B       1 5     B       2 6     B       1 dtype  int64     To get the same answer as waitingkuo  the  second question    but slightly cleaner  is to groupby the level   In  12   df groupby   col5    col2    size   groupby level 1  max   Out 12   col2 A       3 B       2 C       1 D       3 dtype  int64

User · Answer

Followed by  Andy s answer  you can do following to solve your second question   In  56   df groupby   col5   col2    size   reset index   groupby  col2    0   max   Out 56          0 col2    A     3 B     2 C     1 D     3

User · Answer

Idiomatic solution that uses only a single groupby   df groupby   col5    col2    size        sort values ascending False       reset index name  count        drop duplicates subset  col2       col5 col2  count 0    3    A      3 1    1    D      3 2    5    B      2 6    3    C      1   Explanation  The result of the groupby size method is a Series with col5 and col2 in the index  From here  you can use another groupby method to find the maximum value of each value in  col2 but it is not necessary to do  You can simply sort all the values descendingly and then keep only the rows with the first occurrence of col2 with the drop duplicates method

[python] Pandas DataFrame Groupby two columns and get counts

Examples related to python

Examples related to pandas

Examples related to dataframe