Select values with condition count() Python

I want select all data of values have two type ‘E’ in data values. In this data, we can have many type 'S' but it’s only one value of type 'E'.

For example: ID: 1114 have two 'Type': 'E' in values so show all values of 1114.

dataframe 1:

id /date /origine /destination /horaire A /horaire B/ Type /Other data

1112 2021-03-11 Paris / Marseille/10:00/14:00/A / ..
1112 2021-03-11 Paris / Marseille/10:00/14:00/E /..
1112 2021-03-11 Paris / Marseille/10:00/14:00/S /..
1112 2021-03-11 Paris / Lyon/10:00/12:00/S/..
1112 2021-03-11 Paris / Marseille/10:00/14:00/S/..
1112 2021-03-11 Paris / Marseille/10:00/14:00/C/..
1114 2021-05-11 Paris / Bordeaux/09:00/13:00/A/..
1114 2021-05-11 Paris / Bordeaux/09:00/13:00/E/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/S/..
1114 2021-05-11 Paris / Bordeaux/10:20/14:00/E/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/S/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/S/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/S/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/C/..

data output:

id /date /origine /destination /horaire A /horaire B/ Type /Other data

1114 2021-05-11 Paris / Bordeaux/09:00/13:00/A/..
1114 2021-05-11 Paris / Bordeaux/09:00/13:00/E/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/S/..
1114 2021-05-11 Paris / Bordeaux/10:20/14:00/E/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/S/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/S/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/S/..
1114 2021-05-11 Paris / Bordeaux/10:00/14:00/C/..

I wrote this code:

mask = df.groupby(['date','Id']).apply(lambda x: x['Type'].value_counts())
data_set = df[((df['Type']=='E).isin(mask.index[mask > 1]))]
data_set 

But my output is empty

>Solution :

For count number of E values create helper column tmp and caout values by sum:

df = (df[df.assign(tmp = df['Type']=='E')
           .groupby(['date','Id'])['tmp'].transform('sum').gt(1)])