Python pandas insert empty rows after each row

Using append on a dataframe is quite inefficient I believe (has to reallocate memory for the entire data frame each time).

DataFrames were meant for analyzing data and easily adding columns—but not rows.

So I think a good approach would be to create a new dataframe of the correct size and then transfer the data over to it. Easiest way to do that is using an index.

# Demonstration data
data = 'name profession Bill cashier Sam stock Adam security'
data = np.array(data.split()).reshape((4,2))
df = pd.DataFrame(data[1:],columns=data[0])

# Add n blank rows
n = 3
new_index = pd.RangeIndex(len(df)*(n+1))
new_df = pd.DataFrame(np.nan, index=new_index, columns=df.columns)
ids = np.arange(len(df))*(n+1)
new_df.loc[ids] = df.values
print(new_df)

Output:

    name profession
0   Bill    cashier
1    NaN        NaN
2    NaN        NaN
3    NaN        NaN
4    Sam      stock
5    NaN        NaN
6    NaN        NaN
7    NaN        NaN
8   Adam   security
9    NaN        NaN
10   NaN        NaN
11   NaN        NaN

The code below includes a function to add empty rows between the existing rows of a dataframe.

Might not be the best approach for what you want to do, it might be better to add the blank rows when you are exporting the data.

import pandas as pd

def add_blank_rows(df, no_rows):
    df_new = pd.DataFrame(columns=df.columns)
    for idx in range(len(df)):
        df_new = df_new.append(df.iloc[idx])
        for _ in range(no_rows):
            df_new=df_new.append(pd.Series(), ignore_index=True)
    return df_new
    
df = pd.read_csv('test.csv')

df_with_blank_rows = add_blank_rows(df, 3)

print(df_with_blank_rows)

 # original_df is your original dataframe
 # new_df is the resulting dataframe with empty rows
 # empty_rows is the amount of rows you want to insert (change to number of rows you need):
 
 empty_rows = 3
 original_df.index = range(0, empty_rows*len(original_df), empty_rows)
 new_df = original_df.reindex(index=range(empty_rows*len(original_df)))

If you provided more information that would be helpful, but a thing that comes to mind is to use this command

df.append(pd.Series(), ignore_index=True)

This will add an empty row to your data frame, though as you can see you have to pass set ignore_index=True, otherwise the append won’t work.