add a new dataframe based on multiple condition in pandas

Question

Hi I have data like this:

for example

id        genre    total_play
1         pop      20
1         rock     30
1         jazz     60
2         pop      60
2         country  30
2         rock     25
3         latin    25
3         kpop     25
3         folk     10

I want to create a new column based on the following rules:

If a user listens to jazz music for more than 30% of the total play it will be labeled with category A
If a user listens to pop music for more than 40% of the total play it will be labeled with category B
Other than that then C

and will be like this:

id   tendency
1    A
2    B
3    C

Thanks before :)

Quang Hoang · Accepted Answer · 2020-10-08 14:35:33Z

3

Let's try pivot the table to calculate the total plays, then use np.select:

plays  = df.pivot_table('total_play','id','genre',fill_value=0)
totals = plays.sum(1)

pd.Series(np.select([plays['jazz']>totals*0.3, plays['pop'] > totals*0.4],['A','B'],'C'),
          index=plays.index)

Output:

id
1    A
2    B
3    C
dtype: object

answered Oct 8, 2020 at 14:35

Quang Hoang

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