Python Pandas replicate rows in dataframe

Question

If the data look like:

Store,Dept,Date,Weekly_Sales,IsHoliday
1,1,2010-02-05,24924.5,FALSE
1,1,2010-02-12,46039.49,TRUE
1,1,2010-02-19,41595.55,FALSE
1,1,201         


        

Answer 1

Appending and concatenating is usually slow in Pandas so I recommend just making a new list of the rows and turning that into a dataframe (unless appending a single row or concatenating a few dataframes).

import pandas as pd

df = pd.DataFrame([
[1,1,'2010-02-05',24924.5,False],
[1,1,'2010-02-12',46039.49,True],
[1,1,'2010-02-19',41595.55,False],
[1,1,'2010-02-26',19403.54,False],
[1,1,'2010-03-05',21827.9,False],
[1,1,'2010-03-12',21043.39,False],
[1,1,'2010-03-19',22136.64,False],
[1,1,'2010-03-26',26229.21,False],
[1,1,'2010-04-02',57258.43,False]
], columns=['Store','Dept','Date','Weekly_Sales','IsHoliday'])

temp_df = []
for row in df.itertuples(index=False):
    if row.IsHoliday:
        temp_df.extend([list(row)]*5)
    else:
        temp_df.append(list(row))

df = pd.DataFrame(temp_df, columns=df.columns)