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Given the following data frame:
import pandas as pd
import numpy as np
df1=pd.DataFrame({'A':['a','b','c','d'],
'B':['d',np.nan,'c','f']})
df1
A B
0 a d
1 b NaN
2 c c
3 d f
I'd like to insert blank rows before each row. The desired result is:
A B
0 NaN NaN
1 a d
2 NaN NaN
3 b NaN
4 NaN NaN
5 c c
6 NaN NaN
7 d f
In reality, I have many rows.
Thanks in advance!
212
Select the cells where the empty rows need to appear and press Shift + Space. When you pick the correct number of rows, right-click within the selection and choose the Insert option from the menu list.
Empty rows can be appended by using the df. loc[df. shape[0]] and assigning None values for all the existing columns. For example, if your dataframe has three columns, you can create a series with 3 None values and assign it at the last position of the dataframe.
There are multiple ways to add a new empty/blank column (single or multiple columns) to a pandas DataFrame by using assign operator, assign() , insert() and apply() methods. By using these you can add one or multiple empty columns with either NaN , None , Blank or Empty string values to all cells.
I think you could change your index like @bananafish did and then use reindex:
df1.index = range(1, 2*len(df1)+1, 2)
df2 = df1.reindex(index=range(2*len(df1)))
In [29]: df2
Out[29]:
A B
0 NaN NaN
1 a d
2 NaN NaN
3 b NaN
4 NaN NaN
5 c c
6 NaN NaN
7 d f
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