In this article we will discuss how to convert a single or multiple lists to a DataFrame.

Python’s pandas library provide a constructor of DataFrame to create a Dataframe by passing objects i.e.

pandas.DataFrame(data=None, index=None, columns=None, dtype=None, copy=False)

Here data parameter can be a numpy ndarray , dict, or an other DataFrame. Also, columns and index are for column and index labels.
Let’s use this to convert lists to dataframe object from lists.

Create DataFrame from list of lists

Suppose we have a list of lists i.e.

# List of lists
students = [ ['jack', 34, 'Sydeny'] ,
             ['Riti', 30, 'Delhi' ] ,
             ['Aadi', 16, 'New York'] ]

Pass this list to DataFrame’s constructor to create a dataframe object i.e.
# Creating a dataframe object from listoftuples
dfObj = pd.DataFrame(students) 

Contents of the created DataFrames are as follows,
      0   1         2
0  jack  34    Sydeny
1  Riti  30     Delhi
2  Aadi  16  New York

Create DataFrame from lists of tuples

Just like list of lists we can pass list of tuples in dataframe contsructor to create a dataframe.

Suppose we have a list of tuples i.e.

# List of Tuples
students = [ ('jack', 34, 'Sydeny') ,
             ('Riti', 30, 'Delhi' ) ,
             ('Aadi', 16, 'New York') ]

Pass this list of tuples to DataFrame’s constructor to create a DataFrame object i.e.
# Creating a dataframe object from listoftuples
dfObj = pd.DataFrame(students) 

Contents of the created dataframe is as follows,
      0   1         2
0  jack  34    Sydeny
1  Riti  30     Delhi
2  Aadi  16  New York

Both Column & Index labels are default. But we can also provide them i.e.

Create a Dataframe from list and  set column names and indexes

#Convert list of tuples to dataframe and set column names and indexes
dfObj = pd.DataFrame(students, columns = ['Name' , 'Age', 'City'], index=['a', 'b', 'c']) 

Contents of the created dataframe is as follows,
   Name  Age      City
a  jack   34    Sydeny
b  Riti   30     Delhi
c  Aadi   16  New York

Create dataframe from list of tuples and skip certain columns

In out list of tuples we have 3 entries in each tuple. What if we want to use 1st and 3rd entry only?
Let’s create a dataframe by skipping 2nd entry in tuples i.e.

# Create datafrae from student list but skip column 'Age' i.e. only with 2 columns
dfObj = pd.DataFrame.from_records(students, exclude=['Age'], columns = ['Name' , 'Age', 'City'], index=['a', 'b', 'c']) 

Contents of the created dataframe is as follows,
   Name      City
a  jack    Sydeny
b  Riti     Delhi
c  Aadi  New York

Create dataframe from multiple lists

Suppose we have 3 different lists i.e.

listOfNames =  ['jack', 'Riti', 'Aadi']
listOfAge   =  [34, 30, 16]
listOfCity  =  ['Sydney', 'Delhi', 'New york']

Now we want to conver them to a dataframe with each lists as a column. Let’s see how to do that i.e.
Zip the lists to create a list of tuples i.e.
# Create a zipped list of tuples from above lists
zippedList =  list(zip(listOfNames, listOfAge, listOfCity))

Contents of ziipledLists is,
[('jack', 34, 'Sydney'), ('Riti', 30, 'Delhi'), ('Aadi', 16, 'New york')]

Let’s create a dataframe with this zipped lists i.e.
# Create a dataframe from zipped list
dfObj = pd.DataFrame(zippedList, columns = ['Name' , 'Age', 'City'], index=['a', 'b', 'c']) 

Contents of the created dataframe is as follows,
   Name  Age      City
a  jack   34    Sydney
b  Riti   30     Delhi
c  Aadi   16  New york

Complete example is as follows,
import pandas as pd

def main():
    
    # List of lists
    students = [ ['jack', 34, 'Sydeny'] ,
                 ['Riti', 30, 'Delhi' ] ,
                 ['Aadi', 16, 'New York'] ]
    
    print("****Create a Dataframe from list of lists *****")
    
    # Creating a dataframe object from listoftuples
    dfObj = pd.DataFrame(students) 
    
    print("Dataframe : " , dfObj, sep='\n')
    
    # List of Tuples
    students = [ ('jack', 34, 'Sydeny') ,
                 ('Riti', 30, 'Delhi' ) ,
                 ('Aadi', 16, 'New York') ]
    
    print("****Create a Dataframe from list of tuple *****")
    
    # Creating a dataframe object from listoftuples
    dfObj = pd.DataFrame(students) 
    
    print("Dataframe : " , dfObj, sep='\n')
    
    
    print("****Create a Dataframe from list of tuple, also set column names and indexes *****")
    
    #Convert list of tuples to dataframe and set column names and indexes
    dfObj = pd.DataFrame(students, columns = ['Name' , 'Age', 'City'], index=['a', 'b', 'c']) 
    
    print("Dataframe : " , dfObj, sep='\n')
    
    print("****Create dataframe from list of tuples and skip certain columns*********")
    
    # Create datafrae from student list but skip column 'Age' i.e. only with 2 columns
    dfObj = pd.DataFrame.from_records(students, exclude=['Age'], columns = ['Name' , 'Age', 'City'], index=['a', 'b', 'c']) 
    
    print("Dataframe : " , dfObj, sep='\n')
    
    print("***Create dataframe from multiple lists***")
    
    listOfNames =  ['jack', 'Riti', 'Aadi']
    listOfAge   =  [34, 30, 16]
    listOfCity  =  ['Sydney', 'Delhi', 'New york']
    
    # Create a zipped list of tuples from above lists
    zippedList =  list(zip(listOfNames, listOfAge, listOfCity))
    
    print("zippedList = " , zippedList)
    
    # Create a dataframe from zipped list
    dfObj = pd.DataFrame(zippedList, columns = ['Name' , 'Age', 'City'], index=['a', 'b', 'c']) 

    print("Dataframe : " , dfObj, sep='\n')
    
if __name__ == '__main__':
    main()

Output:
****Create a Dataframe from list of lists *****
Dataframe : 
      0   1         2
0  jack  34    Sydeny
1  Riti  30     Delhi
2  Aadi  16  New York
****Create a Dataframe from list of tuple *****
Dataframe : 
      0   1         2
0  jack  34    Sydeny
1  Riti  30     Delhi
2  Aadi  16  New York
****Create a Dataframe from list of tuple, also set column names and indexes *****
Dataframe : 
   Name  Age      City
a  jack   34    Sydeny
b  Riti   30     Delhi
c  Aadi   16  New York
****Create dataframe from list of tuples and skip certain columns*********
Dataframe : 
   Name      City
a  jack    Sydeny
b  Riti     Delhi
c  Aadi  New York
***Create dataframe from multiple lists***
zippedList =  [('jack', 34, 'Sydney'), ('Riti', 30, 'Delhi'), ('Aadi', 16, 'New york')]
Dataframe : 
   Name  Age      City
a  jack   34    Sydney
b  Riti   30     Delhi
c  Aadi   16  New york

 

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