Let’s discuss how to convert Pandas dataframe to List.
First, let’s create a Basic DataFrame:
Python3
import pandas as pd # Creating a dictionary to store datadata = {'Name':['Tony', 'Steve', 'Bruce', 'Peter' ], 'Age': [35, 70, 45, 20] } # Creating DataFrame df = pd.DataFrame(data) # Print the dataframedf |
Output :
Convert Pandas DataFrame into a List
At times, you may need to convert your pandas dataframe to List. To accomplish this task, ‘ tolist() ‘ function can be used. Below is a basic example to use this function and convert the required DataFrame into a List.
Python3
df.values.tolist() |
Output :
[['Tony', 35], ['Steve', 70], ['Bruce', 45], ['Peter', 20]]
Here, Each inner list contains all the columns of a particular row.
Pandas DataFrame can be converted into lists in multiple ways. Let’s have a look at different ways of converting a DataFrame one by one.
Converting a DataFrame to List containing all the rows of a particular column:
Python3
import pandas as pd # Creating a dictionary to store datadata = {'Name':['Tony', 'Steve', 'Bruce', 'Peter' ] , 'Age': [35, 70, 45, 20] } # Creating DataFrame df = pd.DataFrame(data) # Converting DataFrame to a list containing# all the rows of column 'Name'names = df['Name'].tolist()# Printing the converted list.print(names) |
Output:
['Tony', 'Steve', 'Bruce', 'Peter']
Converting a DataFrame to Nested List containing all the rows of all the columns
Python3
import pandas as pd # Creating a dictionary to store datadata = {'Name':['Tony', 'Steve', 'Bruce', 'Peter' ] , 'Age': [35, 70, 45, 20] } # Creating DataFramedf = pd.DataFrame(data)# Creating an empty listres=[]# Iterating through the columns of# dataframefor column in df.columns: # Storing the rows of a column # into a temporary list li = df[column].tolist() # appending the temporary list res.append(li) # Printing the final listprint(res) |
Output:
[['Tony', 'Steve', 'Bruce', 'Peter'], [35, 70, 45, 20]]
Converting a DataFrame to a list that contains lists having all the columns of a row
Python3
import pandas as pd # Creating a dictionary to store datadata = {'Name':['Tony', 'Steve', 'Bruce', 'Peter' ] , 'Age': [35, 70, 45, 20] } # Creating DataFramedf = pd.DataFrame(data) # Converting dataframe to listli = df.values.tolist()# Printing listprint(li) |
Output :
[['Tony', 35], ['Steve', 70], ['Bruce', 45], ['Peter', 20]]
Converting a DataFrame to a list that contains lists having all the columns of a row along with column names
Python3
import pandas as pd # Creating a dictionary to store datadata = {'Name':['Tony', 'Steve', 'Bruce', 'Peter' ] , 'Age': [35, 70, 45, 20] } # Creating DataFramedf = pd.DataFrame(data) # Converting dataframe to listli = [df.columns.values.tolist()] + df.values.tolist()# Printing listprint(li) |
Output:
[['Name', 'Age'], ['Tony', 35], ['Steve', 70], ['Bruce', 45], ['Peter', 20]]
