[FIXED] how to calculate percentile value of number in dataframe column grouped by index

Issue

I have a dataframe like this:

df:
        Score
group
  A      100
  A      34
  A      40
  A      30
  C      24
  C      60
  C      35

For every group in the data, I want to find out the percentile value of Score 35. (i.e the percentile where the 35 fits in the grouped data)

I tried different tricks but none of them worked.

scipy.stats.percentileofscore(df['Score], 35, kind='weak')
 --> This is working but this doesn't give me the percentile grouped by index

df.groupby('group')['Score].percentileofscore()
 --> 'SeriesGroupBy' object has no attribute 'percentileofscore'

scipy.stats.percentileofscore(df.groupby('group')[['Score]], 35, kind='strict')
 --> TypeError: '<' not supported between instances of 'str' and 'int'

My ideal output looks like this:

df:
        Score Percentile
group 
  A       50
  C       33

Can anyone suggest to me what works well here?

Solution

Inverse quantile function for a sequence at point X is the proportion of values less than X in the sequence, right? So:

In [158]: df["Score"].lt(35).groupby(df["group"]).mean().mul(100)
Out[158]:
group
A    50.000000
C    33.333333
Name: Score, dtype: float64

• get a True/False Series of whether < 35 or not on "Score"
• group this Series over "group"
• take the mean
  • since True == 1 and False == 0, it will effectively give the proportion!
• multiply by 100 to get percentages

Answered By - Mustafa Aydın

Answer Checked By - Robin (PHPFixing Admin)