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To add an empty column to a Pandas DataFrame, you can use the “assign” method and pass in a column label and value of None. This will create a new column in the DataFrame with the specified label and no data. You can then populate the column with data as needed. Additionally, you can use the “insert” method to add an empty column at a specified position in the 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 rebounds empty1 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
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