Reputation: 1543
I have a large pandas dataframe and I would like to select all user actions that happen between an entry (action1 == 0) and an exit point (action1 == 1). There are multiple such user sessions in the database. It looks something like this:
User_action Reference Other_data Row_index
action2 0 foo a
action1 0 bar b
action6 0 foo c
action4 0 foo d
action1 1 bar e
action7 0 foo f
action1 0 foo g
action3 0 bar h
action1 1 foo i
action1 1 foo j
action3 0 bar k
action1 0 foo l
action9 0 foo m
action1 1 foo n
The result should produce the rows with the indexes: c,d,h and m:
User_action Reference Other_data Row_index
action6 0 foo c
action4 0 foo d
action3 0 bar h
action9 0 foo m
Upvotes: 1
Views: 70
Reputation: 863451
Use:
#filter only category
df1 = df[df['User_action'] == 'action1'].copy()
#test only pairs 0, 1 and reindex for same length as original df
m1 = df1['Reference'].eq(1) & df1['Reference'].shift(1).eq(0)
m1 = m1.reindex(df.index, fill_value=False)
m2 = df1['Reference'].eq(0) & df1['Reference'].shift(-1).eq(1)
m2 = m2.reindex(df.index, fill_value=False).shift().fillna(False)
a = np.select([m1, m2], [-1,1], default=0)
m = a.cumsum() == 1
#filter by final condition
df = df[m]
print (df)
User_action Reference Other_data Row_index
4 action6 0 foo c
5 action4 0 foo d
9 action3 0 bar h
14 action9 0 foo m
Upvotes: 2