Calculate percentage of rows with a column above a certain value Pandas-CodePudding

I have a sample of a large dataset as below

I would like to get the percentage of the count of number of rows with a value above 30 which would give me an output as below

How would I go about achieving this with pandas. I have gotten to this last point of processing my data and a bit stuck with this

CodePudding user response：

You can compare values for greater like 30 with aggregate mean:

df = (df.B > 30).groupby(df['A']).mean().mul(100).reset_index(name='C')
print (df)
   A     C
0  r  60.0

Or:

df = df.assign(C = df.B > 30).groupby('A')['C'].mean().mul(100).reset_index()