How to create an empty DataFrame and append rows & columns to it in Pandas?
Let’s discuss how to create an empty DataFrame and append rows & columns to it in Pandas. There are multiple ways in which we can do this task.
Method #1: Create a complete empty DataFrame without any column name or indices and then appending columns one by one to it.
# import pandas library as pd import pandas as pd # create an Empty DataFrame object df = pd.DataFrame() print (df) # append columns to an empty DataFrame df[ 'Name' ] = [ 'Ankit' , 'Ankita' , 'Yashvardhan' ] df[ 'Articles' ] = [ 97 , 600 , 200 ] df[ 'Improved' ] = [ 2200 , 75 , 100 ] df |
Output:
Method #2: Create an empty DataFrame with columns name only then appending rows one by one to it using append()
method.
# import pandas library as pd import pandas as pd # create an Empty DataFrame # object With column names only df = pd.DataFrame(columns = [ 'Name' , 'Articles' , 'Improved' ]) print (df) # append rows to an empty DataFrame df = df.append({ 'Name' : 'Ankit' , 'Articles' : 97 , 'Improved' : 2200 }, ignore_index = True ) df = df.append({ 'Name' : 'Aishwary' , 'Articles' : 30 , 'Improved' : 50 }, ignore_index = True ) df = df.append({ 'Name' : 'yash' , 'Articles' : 17 , 'Improved' : 220 }, ignore_index = True ) df |
Output:
Method #3: Create an empty DataFrame with a column name and indices and then appending rows one by one to it using loc[]
method.
# import pandas library as pd import pandas as pd # create an Empty DataFrame object With # column names and indices df = pd.DataFrame(columns = [ 'Name' , 'Articles' , 'Improved' ], index = [ 'a' , 'b' , 'c' ]) print ( "Empty DataFrame With NaN values : \n\n" , df) # adding rows to an empty # dataframe at existing index df.loc[ 'a' ] = [ 'Ankita' , 50 , 100 ] df.loc[ 'b' ] = [ 'Ankit' , 60 , 120 ] df.loc[ 'c' ] = [ 'Harsh' , 30 , 60 ] df |
Output:
Last Updated on October 24, 2021 by admin