I have a data frame:

Where 'Placed' column has a boolean value I want to print the count of rows that have the value '1' in placed grouped by the Dept_Name

CodePudding user response：

As you have a boolean 0/1 a simple sum will work:

out = df.groupby('Dept_Name', as_index=False).sum()

output:

  Dept_Name  Placed
0         A       5
1         B       0
2         C       2

For a named column:

out = df.groupby('Dept_Name', as_index=False).agg(**{'Count': ('Placed', 'sum')})

output:

  Dept_Name  Count
0         A      5
1         B      0
2         C      2

CodePudding user response：

If values are 0,1 or True/False you can aggregate sum, last for column Count use Series.reset_index:

df1 = df.groupby('Dept_Name')['Placed'].sum().reset_index(name='Count')

If test some non boolean values - e.g. count values 100:

df2 = df['Placed'].eq(100).groupby(df['Dept_Name']).sum().reset_index(name='Count')