Create a list from rows in Pandas dataframe - GeeksforGeeks

26 Jan, 2019
Python list is easy to work with and also list has a lot of in-built functions to do a whole lot of operations on lists. Pandas dataframe’s columns consist of series but unlike the columns, Pandas dataframe rows are not having any similar association. In this post, we are going to discuss several ways in which we can extract the whole row of the dataframe at a time.
Solution #1: In order to iterate over the rows of the Pandas dataframe we can use DataFrame.iterrows() function and then we can append the data of each row to the end of the list.
# importing pandas as pdimport pandas as pd  # Create the dataframedf = pd.DataFrame({'Date':['10/2/2011', '11/2/2011', '12/2/2011', '13/2/11'],                    'Event':['Music', 'Poetry', 'Theatre', 'Comedy'],                    'Cost':[10000, 5000, 15000, 2000]})  # Print the dataframeprint(df)
Output :
Now we will use the DataFrame.iterrows() function to iterate over each of the row of the given Dataframe and construct a list out of the data of each row.
# Create an empty listRow_list =[]  # Iterate over each rowfor index, rows in df.iterrows():    # Create list for the current row    my_list =[rows.Date, rows.Event, rows.Cost]          # append the list to the final list    Row_list.append(my_list)  # Print the listprint(Row_list)
Output :
As we can see in the output, we have successfully extracted each row of the given dataframe into a list. Just like any other Python’s list we can perform any list operation on the extracted list.
# Find the length of the newly # created listprint(len(Row_list))  # Print the first 3 elementsprint(Row_list[:3])
Output :
Solution #2: In order to iterate over the rows of the Pandas dataframe we can use DataFrame.itertuples() function and then we can append the data of each row to the end of the list.
# importing pandas as pdimport pandas as pd  # Create the dataframedf = pd.DataFrame({'Date':['10/2/2011', '11/2/2011', '12/2/2011', '13/2/11'],                    'Event':['Music', 'Poetry', 'Theatre', 'Comedy'],                    'Cost':[10000, 5000, 15000, 2000]})  # Print the dataframeprint(df)
Output :
Now we will use the DataFrame.itertuples() function to iterate over each of the row of the given Dataframe and construct a list out of the data of each row.
# Create an empty listRow_list =[]  # Iterate over each rowfor rows in df.itertuples():    # Create list for the current row    my_list =[rows.Date, rows.Event, rows.Cost]          # append the list to the final list    Row_list.append(my_list)  # Print the listprint(Row_list)
Output :
As we can see in the output, we have successfully extracted each row of the given dataframe into a list. Just like any other Python’s list we can perform any list operation on the extracted list.
# Find the length of the newly # created listprint(len(Row_list))  # Print the first 3 elementsprint(Row_list[:3])
Output :
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Python pandas-dataFrame
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