Creating a Pandas dataframe using list of tuples

Pandas is famous for data manipulation in Python. We can create a DataFrame from a list of simple tuples, and can even choose the specific elements of the tuples we want to use.

Using pd.DataFrame() function

Here we will create a Pandas Dataframe using a list of tuples with the pd.DataFrame() function.

Example 1: In this example, we will simply pass the tuple to the DataFrame constructor which will return a pandas dataframe.

Python3

# import pandas to use pandas DataFrame
import pandas as pd

# data in the form of list of tuples
data = [('Peter', 18, 7),
        ('Riff', 15, 6),
        ('John', 17, 8),
        ('Michel', 18, 7),
        ('Sheli', 17, 5) ]

# create DataFrame using data
df = pd.DataFrame(data, columns =['Name', 'Age', 'Score'])

print(df)

Output:

     Name  Age  Score
0   Peter   18      7
1    Riff   15      6
2    John   17      8
3  Michel   18      7
4   Sheli   17      5

Using from_records()

Here we will create a Pandas Dataframe using a list of tuples using the from_records() method.

Example 2: In this example, we will use the df.from_records() to create the dataframe from the list of tuples.

Python3

import pandas as pd

# data in the form of list of tuples
data = [('Peter', 18, 7),
        ('Riff', 15, 6),
        ('John', 17, 8),
        ('Michel', 18, 7),
        ('Sheli', 17, 5) ]


# create DataFrame using data
df = pd.DataFrame.from_records(data, columns =['Team', 'Age', 'Score'])

print(df)

Output:

     Team  Age  Score
0   Peter   18      7
1    Riff   15      6
2    John   17      8
3  Michel   18      7
4   Sheli   17      5

Using df.pivot() function

Here we will create a Pandas Dataframe using a list of tuples using the df.pivot() function method.

Example 3: Creating pivot table by using three columns

Python3

# import pandas to use pandas DataFrame
import pandas as pd

# data in the form of list of tuples
data = [('Peter', 18, 7),
        ('Riff', 15, 6),
    ('John', 17, 8),
    ('Michel', 18, 7),
    ('Sheli', 17, 5) ]


# create DataFrame using data
df = pd.DataFrame(data, columns =['Team', 'Age', 'Score'])

a = df.pivot('Team', 'Score','Age')
print(a)

Output:

Score      5     6     7     8
Team                          
John     NaN   NaN   NaN  17.0
Michel   NaN   NaN  18.0   NaN
Peter    NaN   NaN  18.0   NaN
Riff     NaN  15.0   NaN   NaN
Sheli   17.0   NaN   NaN   NaN