Combining rows in pandas DataFrame by iterating

Question

How can I achieve the expected result from the following DataFrame

 df
            col_1             col_2    col_3
     0  Non-Saved    www.google.com   20,567
     1             www.facebook.com      
     2             www.linkedin.com      
     3      Saved     www.Quora.com    6,337
     4                www.gmail.com

Expected result:

            col_1              col_2    col_3
     0  Non-Saved     www.google.com   20,567
                    www.facebook.com
                    www.linkedin.com
     1  Saved          www.Quora.com    6,337
                       www.gmail.com

From 5 rows to 2 rows by merging the empty strings in col_1 and col_3. Also, concatenating values in col_2 into one cell. Can anyone help me with an user-defined function to do this?

Scott Boston · Accepted Answer · 2017-10-11 18:25:20Z

2

Let's try:

df = df.apply(lambda x: x.str.strip()).replace('',np.nan)

df.groupby(df.col_1.ffill())\
  .agg({'col_2': lambda x: ' '.join(x) ,'col_3':'first'})\
  .reset_index()

Output:

       col_1                                             col_2   col_3
0  Non-Saved  www.google.com www.facebook.com www.linkedin.com  20,567
1      Saved                       www.Quora.com www.gmail.com   6,337

answered Oct 11, 2017 at 18:25

Scott Boston

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5 Comments

Preetesh Gaitonde Over a year ago

df = df.apply(lambda x: x.str.strip()).replace('',np.nan) Gives an error:

AttributeError: ('Can only use .str accessor with string values, which use np.object_ dtype in pandas', u'occurred at index NumberOfRequests')

Scott Boston Over a year ago

Yes, but see this SO Post

Scott Boston Over a year ago

You can try '\n'.join(x)

Preetesh Gaitonde Over a year ago

col_1 object col_2 object col_3 int64 dtype: object

Preetesh Gaitonde Over a year ago

I have a slight tricky condition here -> Combine_rows.... Would you mind taking a look once. Meanwhile I am trying as well.

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