Table of Contents
To add an empty column to a Pandas DataFrame, you can use the “df[‘new_column’] = np.nan” command. This will create a new column with the specified name and fill it with empty values represented by “np.nan”. This can be useful for adding a new column to a DataFrame before filling it with data, or for creating a placeholder column for future data.
Add an Empty Column to a Pandas DataFrame
Occasionally you may want to add an empty column to a pandas DataFrame.
Fortunately this is fairly easy to do and this tutorial shows several examples of how to do so using the following pandas DataFrame:
import numpy as np import pandas as pd #create DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19], 'assists': [5, 7, 7, 9, 12], 'rebounds': [11, 8, 10, 6, 6]}) #view DataFrame df points assists rebounds 0 25 5 11 1 12 7 8 2 15 7 10 3 14 9 6 4 19 12 6
Example 1: Add an Empty Column Using “”
The first way to add an empty column is to use quotations as follows:
#add new column titled 'steals' df['steals'] = "" #view DataFrame df points assists rebounds steals 0 25 5 11 1 12 7 8 2 15 7 10 3 14 9 6 4 19 12 6
Example 2: Add an Empty Column Using Numpy
Another way to add an empty column is to use np.nan as follows:
#add new column titled 'steals' df['steals'] = np.nan #view DataFrame df points assists rebounds steals 0 25 5 11 NaN 1 12 7 8 NaN 2 15 7 10 NaN 3 14 9 6 NaN 4 19 12 6 NaN
Example 3: Add an Empty Column Using Pandas Series
Another way to add an empty column is to use pd.Series() as follows:
#add new column titled 'steals' df['steals'] = pd.Series() #view DataFrame df points assists rebounds steals 0 25 5 11 NaN 1 12 7 8 NaN 2 15 7 10 NaN 3 14 9 6 NaN 4 19 12 6 NaN
Example 4: Add an Empty Column Using Pandas Insert
Another way to add an empty column is to use the insert() function as follows:
#create DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19], 'assists': [5, 7, 7, 9, 12], 'rebounds': [11, 8, 10, 6, 6]}) #insert empty column titled 'steals' into index position 2 df.insert(2, "steals", np.nan) #view DataFrame df points assists steals rebounds 0 25 5 NaN 11 1 12 7 NaN 8 2 15 7 NaN 10 3 14 9 NaN 6 4 19 12 NaN 6
The nice part about this approach is that you can insert the empty column into any position you’d like in the DataFrame.
Example 5: Add Multiple Empty Columns at Once
#create DataFrame
df = pd.DataFrame({'points': [25, 12, 15, 14, 19],
'assists': [5, 7, 7, 9, 12],
'rebounds': [11, 8, 10, 6, 6]})#add empty columns titled 'empty1' and 'empty2'df = df.reindex(columns = df.columns.tolist() + ['empty1', 'empty2'])#view DataFrame
df
points assists reboundsempty1 empty2
0 25 5 11 NaN NaN
1 12 7 8 NaN NaN
2 15 7 10 NaN NaN
3 14 9 6 NaN NaN
4 19 12 6 NaN NaN
You can find more Python tutorials .