pandas sort alphabetically for every row based on column content-CodePudding

I have a dataframe that looks like this:

Col1	Col2
Bonnie	Anna
Connor	Ethan
Sophia	Daniel

And I want to sort its content alphabetically so that the final result is:

Col1	Col2
Anna	Bonnie
Connor	Ethan
Daniel	Sophia

I want each pair to be ordered alphabetically. As they are in different columns, I don't know how to sort them directly with sort_values method. Thanks!

CodePudding user response：

data = df.to_numpy()
data.sort(axis=1)
pd.DataFrame(data, columns=df.columns)

CodePudding user response：

You can sort each row with DataFrame.apply

out = (df.apply(lambda row: sorted(row), axis=1, result_type='expand')
       .set_axis(df.columns, axis=1))

print(out)

     Col1    Col2
0    Anna  Bonnie
1  Connor   Ethan
2  Daniel  Sophia

CodePudding user response：

You need to make a list for each row, then sort that list:

col_names = dta.columns # save the column names
dta = dta.apply(lambda x:list(x), axis=1) # convert each row to a list
dta = dta.apply(lambda x: sorted(x)) # sorting the row lists
dta = dta.to_list() # convert the Series to a list
dta = pd.DataFrame(dta) # recreate the data frame
dta.columns = col_names # replace the name of columns

Also you can do the whole thing in one line:

dta = pd.DataFrame(dta.apply(lambda x: sorted(list(x)), axis=1).to_list())
dta.columns = col_names

result:

	Col1	Col2
0	Anna	Bonnie
1	Connor	Ethan
2	Daniel	Sophia

CodePudding user response：

You can try this:

df[['col1', 'col2']] = pd.DataFrame(
    zip(*df[['col1', 'col2']].apply(sorted, axis=1).values)
).T