Python: get a frequency count based on two columns (variables) in pandas dataframe some row appers

Hello I have the following dataframe.

    Group           Size

    Short          Small
    Short          Small
    Moderate       Medium
    Moderate       Small
    Tall           Large

I want to count the frequency of how many time the same row appears in the dataframe.

    Group           Size      Time

    Short          Small        2
    Moderate       Medium       1 
    Moderate       Small        1
    Tall           Large        1

Answers:

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Method 1

You can use groupby’s size:

In [11]: df.groupby(["Group", "Size"]).size()
Out[11]:
Group     Size
Moderate  Medium    1
          Small     1
Short     Small     2
Tall      Large     1
dtype: int64

In [12]: df.groupby(["Group", "Size"]).size().reset_index(name="Time")
Out[12]:
      Group    Size  Time
0  Moderate  Medium     1
1  Moderate   Small     1
2     Short   Small     2
3      Tall   Large     1

Method 2

Update after pandas 1.1 value_counts now accept multiple columns

df.value_counts(["Group", "Size"])

You can also try pd.crosstab()

Group           Size

Short          Small
Short          Small
Moderate       Medium
Moderate       Small
Tall           Large

pd.crosstab(df.Group,df.Size)


Size      Large  Medium  Small
Group                         
Moderate      0       1      1
Short         0       0      2
Tall          1       0      0

EDIT: In order to get your out put

pd.crosstab(df.Group,df.Size).replace(0,np.nan).
     stack().reset_index().rename(columns={0:'Time'})
Out[591]: 
      Group    Size  Time
0  Moderate  Medium   1.0
1  Moderate   Small   1.0
2     Short   Small   2.0
3      Tall   Large   1.0

Method 3

Other posibbility is using .pivot_table() and aggfunc='size'

df_solution = df.pivot_table(index=['Group','Size'], aggfunc='size')

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