How to append a list to a Pandas DataFrame using loc in Python?

The Dataframe.loc is used to access a group of rows and columns by label or a boolean array. We will append a list to a DataFrame using loc. Let us first create a DataFrame. The data is in the form of lists of team rankings for our example −

# data in the form of list of team rankings Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50],['Bangladesh', 6, 40]] # Creating a DataFrame and adding columns dataFrame = pd.DataFrame(Team, columns=['Country', 'Rank', 'Points'])

Following is the row to be appended −

myList = ["Sri Lanka", 7, 30] 

Append the above row in the form of list using loc() −

dataFrame.loc[len(dataFrame)] = myList

Example

Following is the code −

import pandas as pd # data in the form of list of team rankings Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50],['Bangladesh', 6, 40]] # Creating a DataFrame and adding columns dataFrame = pd.DataFrame(Team, columns=['Country', 'Rank', 'Points']) print"DataFrame...\n",dataFrame # row to be appended myList = ["Sri Lanka", 7, 30] # append the above row in the form of list using loc() dataFrame.loc[len(dataFrame)] = myList # display the update dataframe print"\nUpdated DataFrame after appending a row using loc...\n",dataFrame

Output

This will produce the following output

DataFrame...         Country   Rank   Points 0         India      1      100 1     Australia      2       85 2       England      3       75 3   New Zealand      4       65 4  South Africa      5       50 5    Bangladesh      6       40 Updated DataFrame after appending a row using loc...         Country   Rank Points 0         India      1 100 1     Australia      2 85 2       England      3 75 3   New Zealand      4 65 4  South Africa      5 50 5    Bangladesh      6 40 6     Sri Lanka      7 30