x
import pandas as pddata = { "age": [50, 40, 30, 40], "qualified": [True, False, False, False]}idx = ["Sally", "Mary", "John", "Monica"]df = pd.DataFrame(data, index=idx)print("--------BEFORE--------")print(df)newidx = ["Robert", "Cindy", "Chloe", "Pete"]newdf = df.reindex(newidx)print("--------AFTER--------")print(newdf)#Notice that the values are set to NaN, which is the default behaviour when the new index is not the same as the old. --------BEFORE--------
age qualified
Sally 50 True
Mary 40 False
John 30 False
Monica 40 False
--------AFTER--------
age qualified
Robert NaN NaN
Cindy NaN NaN
Chloe NaN NaN
Pete NaN NaN