How can I group different rows based on its value?

user_19582541 0
Viewed 60

I have a data frame in pandas like this:

Attributes1 Attributes value1 Attributes2 Attributes value2
a 1 b 4
b 2 a 5

Does anyone know how can I get a new data frame like below?

a b
1 2
5 4

Thank you!

pandas dataframe merge group-by
3 Answers

Try:

x = pd.DataFrame(
    df.apply(
        lambda x: dict(
            zip(x.filter(regex=r"Attributes\d+$"), x.filter(like="value"))
        ),
        axis=1,
    ).to_list()
)

print(x)

Prints:

   a  b
0  1  4
1  5  2
user_100359850

Use the transpose() function to transpose the rows to columns, then use the groupby() function to group the columns with the same name.

Also, in the future, please add what you've tried to do to solve the problem as well.

user_194960250

We can do wide_to_long then pivot

s = pd.wide_to_long(df.reset_index(),
                    ['Attributes','Attributes value'], 
                    i = 'index',
                    j = 'a').reset_index().drop(['a'],axis=1)
s = s.pivot(*s)
Out[22]: 
Attributes  a  b
index           
0           1  4
1           5  2
user_79645270
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