Adding a blank row after a specific data in a dataframe column

Question

This question has been asked for excel. How to automatically insert a blank row after a group of data. I would like to know if there is a function for doing the same in pandas dataframe.

Answer 1

There are probably other (faster?) ways to do this. Here an attempt.

First create a sample dataframe to use for this example. We assume that the index defines the groups that need to be split:

users = {'user_id': ['A','A','A','A', 'B','B','B'],
     'status': ['S1', 'S2', 'S1', 'S3', 'S1', 'S2', 'S1'],
     'value': [100, 30, 100, 20, 50, 30, 60 ],
    }

df1 = pd.DataFrame(users, columns = ['user_id', 'status', 'value'])
df1.set_index('user_id', drop=True, inplace=True)

Here the output:

user_id	status	value
A	S1	100
A	S2	30
A	S1	100
A	S3	20
B	S1	50
B	S2	30
B	S1	60

We create a new dataframe with empty rows, one for each unique element of the index:

df2 = pd.DataFrame(index=df1.index.drop_duplicates(keep='first'))

Append the new rows and sort the index:

df_merged = df1.append(df2)
df_merged.sort_index(inplace=True)

The final output looks as follows:

user_id	status	value
A	S1	100
A	S2	30
A	S1	100
A	S3	20
A	NaN	NaN
B	S1	50
B	S2	30
B	S1	60
B	NaN	NaN