Python Pandas replicate rows in dataframe
Other way is using concat() function:
import pandas as pd
In [603]: df = pd.DataFrame({'col1':list("abc"),'col2':range(3)},index = range(3))
In [604]: df
Out[604]:
col1 col2
0 a 0
1 b 1
2 c 2
In [605]: pd.concat([df]*3, ignore_index=True) # Ignores the index
Out[605]:
col1 col2
0 a 0
1 b 1
2 c 2
3 a 0
4 b 1
5 c 2
6 a 0
7 b 1
8 c 2
In [606]: pd.concat([df]*3)
Out[606]:
col1 col2
0 a 0
1 b 1
2 c 2
0 a 0
1 b 1
2 c 2
0 a 0
1 b 1
2 c 2
You can put df_try
inside a list and then do what you have in mind:
>>> df.append([df_try]*5,ignore_index=True)
Store Dept Date Weekly_Sales IsHoliday
0 1 1 2010-02-05 24924.50 False
1 1 1 2010-02-12 46039.49 True
2 1 1 2010-02-19 41595.55 False
3 1 1 2010-02-26 19403.54 False
4 1 1 2010-03-05 21827.90 False
5 1 1 2010-03-12 21043.39 False
6 1 1 2010-03-19 22136.64 False
7 1 1 2010-03-26 26229.21 False
8 1 1 2010-04-02 57258.43 False
9 1 1 2010-02-12 46039.49 True
10 1 1 2010-02-12 46039.49 True
11 1 1 2010-02-12 46039.49 True
12 1 1 2010-02-12 46039.49 True
13 1 1 2010-02-12 46039.49 True
This is an old question, but since it still comes up at the top of my results in Google, here's another way.
import pandas as pd
import numpy as np
df = pd.DataFrame({'col1':list("abc"),'col2':range(3)},index = range(3))
Say you want to replicate the rows where col1="b".
reps = [3 if val=="b" else 1 for val in df.col1]
df.loc[np.repeat(df.index.values, reps)]
You could replace the 3 if val=="b" else 1
in the list interpretation with another function that could return 3 if val=="b" or 4 if val=="c" and so on, so it's pretty flexible.