Please help me find a solution for this: I have a Pandas DataFrame containing website visitors and date of their visit. Now I want to know, how many people visit once, twice, etc.
I start with a table:
Visitor | Date
---------------------
A | Jan-1st
B | Jan-1st
C | Jan-2nd
D | Jan-2nd
A | Jan-2nd
I want to end up with a result in the form of:
Frequency | No. of
of visits | visitors
-----------------------
1 | 3
2 | 1
Usevalue_count on Visitor column twice.
In [182]: df.Visitor.value_counts().value_counts()
Out[182]:
1 3
2 1
Details
First get, visitor-wise visits, then you get group the similar counts.
In [183]: df.Visitor.value_counts()
Out[183]:
A 2
D 1
B 1
C 1
Name: Visitor, dtype: int64
In [188]: (df.Visitor.value_counts()
.value_counts()
.reset_index()
.rename(columns={'index': 'Freq of visits', 'Visitor': 'No. of visitors'}))
Out[188]:
Freq of visits No. of visitors
0 1 3
1 2 1
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