Convert Python List To Pandas DataFrame

Write a Python program to convert the list to Pandas DataFrame with an example. In this example, first, we declared a fruit string list. Next, we used the pandas DataFrame function that converts the list to DataFrame.

import pandas as pd

fruitList = ['kiwi', 'orange', 'banana', 'berry', 'mango', 'cherry']
print("List Items = ", fruitList)

df = pd.DataFrame(fruitList)
print(df)

List Items =  ['kiwi', 'orange', 'banana', 'berry', 'mango', 'cherry']
        0
0    kiwi
1  orange
2  banana
3   berry
4   mango
5  cherry

The DataFrame has a column that helps to assign the column names and index to assign the index values. Here, we set the column name as Fruits and index values as a list of six integers.

import pandas as pd

fruitList = ['kiwi', 'orange', 'banana', 'berry', 'mango', 'cherry']

print("List Items = ", fruitList)

df = pd.DataFrame(fruitList, columns = ['Fruits'],
                  index = [1, 2, 3, 4, 5, 6])

print(df)

List Items =  ['kiwi', 'orange', 'banana', 'berry', 'mango', 'cherry']
   Fruits
1    kiwi
2  orange
3  banana
4   berry
5   mango
6  cherry

How to Convert Python List To Pandas DataFrame?

We declared two lists of fruits and orders. Next, we used the zip function to zip those two lists, and then the pandas DataFrame function will convert them.

import pandas as pd

fruitList = ['kiwi', 'orange', 'banana', 'berry', 'mango', 'cherry']

print("List Items = ", fruitList)

ordersList = [100, 2000, 5000, 400, 8000, 12000]

print("List Items = ", ordersList)

df = pd.DataFrame(list(zip(fruitList, ordersList)),
                  columns = ['Fruits', 'Orders'],
                  index = ['a', 'b', 'c', 'd', 'e', 'f'])

print(df)

List Items =  ['kiwi', 'orange', 'banana', 'berry', 'mango', 'cherry']
List Items =  [100, 2000, 5000, 400, 8000, 12000]
   Fruits  Orders
a    kiwi     100
b  orange    2000
c  banana    5000
d   berry     400
e   mango    8000
f  cherry   12000

The DataFrame function also converts the nested lists.

import pandas as pd

fruitList = [['kiwi', 100], ['orange', 3500], ['banana', 2000],
             ['berry', 1500], ['mango', 5000],['cherry', 9000]]

print("List Items = ", fruitList)

df = pd.DataFrame(fruitList, columns = ['Fruits', 'Orders'])

print(df)

This nested one is different from others, and if you convert this nested list to DataFrame, you get the below result.

import pandas as pd

emplist = [['Jhon', 'Xi', 'Ram', 'Dave', 'Nancy'],
           ['Miller', 'Jing', 'KK', 'Williams', 'Cook'],
           [40, 52, 25, 37, 29]]

df = pd.DataFrame(emplist)
print(df)

print('\n========')
df1 = pd.DataFrame(emplist, index = ['First_Name', 'Last_Name', 'Age'])
print(df1)

        0     1    2         3      4
0    Jhon    Xi  Ram      Dave  Nancy
1  Miller  Jing   KK  Williams   Cook
2      40    52   25        37     29

========
                 0     1    2         3      4
First_Name    Jhon    Xi  Ram      Dave  Nancy
Last_Name   Miller  Jing   KK  Williams   Cook
Age             40    52   25        37     29

However, there is a transpose function in pandas DataFrame that will convert the above nested Python list into a meaningful one.

import pandas as pd

emplist = [['Jhon', 'Xi', 'Ram', 'Dave', 'Nancy'],
           ['Miller', 'Jing', 'KK', 'Williams', 'Cook'],
           [40, 52, 25, 37, 29]]

print("List Items = ", emplist)

df = pd.DataFrame(emplist).transpose()

df.columns = ['First Name', 'Last Name', 'Age']

print(df)

df1 = pd.DataFrame(emplist)

print(df1)

List Items =  [['Jhon', 'Xi', 'Ram', 'Dave', 'Nancy'], ['Miller', 'Jing', 'KK', 'Williams', 'Cook'], [40, 52, 25, 37, 29]]
  First Name Last Name Age
0       Jhon    Miller  40
1         Xi      Jing  52
2        Ram        KK  25
3       Dave  Williams  37
4      Nancy      Cook  29
        0     1    2         3      4
0    Jhon    Xi  Ram      Dave  Nancy
1  Miller  Jing   KK  Williams   Cook
2      40    52   25        37     29