CODEWITHSUNDEEP
pythonpandasdataframecsv
Shubham Srivastava
Shubham Srivastava

Reputation: 1283

Add empty row after every data row while processing dataframe to csv

I am processing a large csv file. In that, for first 6 (n) rows needs to be modified. For now, I am reading the csv in dataframe then running our process and the result I am exporting again in csv using df.to_csv(). Wherein, df is a dataframe object.

So, after reading the csv I'm getting the row like

                                                   0
0                              COMPANY NAME XYZ LTD.
1                                          Region c.
2  Here some header just to make readbale for user..
0

After this, I am appending this dataframe on top of other one and then extracting into csv. But, the issue is now, that I want to add a BLANK ROW after every row in above dataframe.

Expected output for above given example

                                                   0
0                              COMPANY NAME XYZ LTD.
1
2                                          Region c.
3
4  Here some header just to make readbale for user..
5
0

Note: The number of rows in dataframe may very so let's say we need to add blank row after every row for all n rows and then append to other df and export it to csv.

Thank you all in advance for helping me.

Upvotes: 1

Views: 201

Answers (1)

Umar.H
Umar.H

Reputation: 23099

Most likely a multitude of ways to do this, you could simply concat both dataframes and use .loc to assign the odd numbered index with a zero length string.

df1 =  pd.concat([df,df],0).sort_index().reset_index(drop=True)

df1.loc[df1.index % 2 == 1, 0] = ''

print(df1)


               0
0                              COMPANY NAME XYZ LTD.
1                                                   
2                                          Region c.
3                                                   
4  Here some header just to make readbale for user..
5

A more simplier method would be to assign the value to your 2nd value of concat in the concat.. Note you'll need a string based column name.

#df.columns = ['A']
df1 =  pd.concat([df,df.assign(A='')],0).sort_index().reset_index(drop=True)

print(df1)
                                                   A
0                              COMPANY NAME XYZ LTD.
1                                                   
2                                          Region c.
3                                                   
4  Here some header just to make readbale for user..
5

Upvotes: 3

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