Insert empty rows after each row

Question

I am trying to insert 3 empty rows after each row of the current data using pandas then export the data. For example a sample current data could be:

name     profession
Bill      cashier
Sam        stock
Adam      security

Ideally what I want to achieve:

name     profession
Bill      cashier
Nan         Nan
Nan         Nan
Nan         Nan
Sam        stock
Nan         Nan
Nan         Nan
Nan         Nan
Adam      security
Nan         Nan
Nan         Nan
Nan         Nan

I have experimented with itertools however i am not sure how i can precisely get three empty rows using after each row using this method. Any help, guidance, sample would definitely be appreciative!

Answer 1

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(index=new_index, columns=df.columns, dtype='object')
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

Answer 2

 insert_rows = 3   # how many rows to insert

 df.index = range(0, insert_rows * len(df), insert_rows)

 # create new_df with added rows
 new_df = df.reindex(index = range(insert_rows * len(df)))