CODEWITHSUNDEEP
pythonpandas
qrs
qrs

Reputation: 131

pandas - groupby column with multiple values

I want to display the users that have used a value. 

import pandas as pd
user = ['alice', 'bob', 'tim', 'alice']
val = [['a','b','c'],['a'],['c','d'],['a','d']]
df = pd.DataFrame({'user': user, 'val': val})

user    val
'alice'      [a, b, c]
'bob'        [a]
'tim'        [c, d]
'alice'      [a, d]

Desired output:

val     users
a      [alice,bob]
b      [alice]
c      [alice,tim]
d      [alice,tim]

Any ideas?

Upvotes: 3

Views: 1435

Answers (4)

jezrael
jezrael

Reputation: 862641

I think need:

df2 = (pd.DataFrame(df['val'].values.tolist(), index=df['user'].values)
         .stack()
         .reset_index(name='val')
         .groupby('val')['level_0']
         .unique()
         .reset_index()
         .rename(columns={'level_0':'user'})
     )
print(df2)
  val          user
0   a  [alice, bob]
1   b       [alice]
2   c  [alice, tim]
3   d  [tim, alice]

Upvotes: 1

cs95
cs95

Reputation: 402483

Step 1
Reshape your data -

from itertools import chain

df = pd.DataFrame({
    'val' : list(chain.from_iterable(df.val.tolist())), 
    'user' : df.user.repeat(df.val.str.len())
})

Step 2
Use groupby + apply + unique:

df.groupby('val').user.apply(lambda x: x.unique().tolist())


val
a    [alice, bob]
b         [alice]
c    [alice, tim]
d    [tim, alice]
Name: user, dtype: object

Upvotes: 4

pe-perry
pe-perry

Reputation: 2621

This is my approach.

df2 = (df
       .set_index('user')
       .val
       .apply(pd.Series)
       .stack()
       .reset_index(name='val')  # Reshape the data
       .groupby(['val'])
       .user
       .apply(lambda x: sorted(set(x))))  # Show users that use the value

Output:

print(df2)
# val
# a    [alice, bob]
# b         [alice]
# c    [alice, tim]
# d    [alice, tim]
# Name: user, dtype: object

Upvotes: 1

David L
David L

Reputation: 441

Don't have enough reputation to write this as a comment, but this question has the answer: How to print dataframe without index

basically, change the last line to:

print(df2.to_string(index=False))

Upvotes: 0

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