Python | Convert list of nested dictionary into Pandas dataframe

Given a list of the nested dictionary, write a Python program to create a Pandas dataframe using it. Let’s understand the stepwise procedure to create a Pandas Dataframe using the list of nested dictionary.

Step #1: Creating a list of nested dictionary.

Python3

# importing pandas
import pandas as pd

# List of nested dictionary initialization
list = [{
        "Student": [{"Exam": 90, "Grade": "a"},
                    {"Exam": 99, "Grade": "b"},
                    {"Exam": 97, "Grade": "c"},
                ],
        "Name": "Paras Jain"
        },
        {
        "Student": [{"Exam": 89, "Grade": "a"},
                    {"Exam": 80, "Grade": "b"}
                ],
        "Name": "Chunky Pandey"
        }
    ]

print(list)

Output:

[{'Student': [{'Exam': 90, 'Grade': 'a'}, {'Exam': 99, 'Grade': 'b'}, {'Exam': 97, 'Grade': 'c'}],
   'Name': 'Paras Jain'},
 {'Student': [{'Exam': 89, 'Grade': 'a'}, {'Exam': 80, 'Grade': 'b'}], 
   'Name': 'Chunky Pandey'}]

Step #2: Adding dict values to rows.

Python3

# rows list initialization
rows = []

# appending rows
for data in list:
    data_row = data['Student']
    time = data['Name']

    for row in data_row:
        row['Name']= time
        rows.append(row)

# using data frame
df = pd.DataFrame(rows)

print(df)

Output:

   Exam Grade           Name
0    90     a     Paras Jain
1    99     b     Paras Jain
2    97     c     Paras Jain
3    89     a  Chunky Pandey
4    80     b  Chunky Pandey

Step #3: Pivoting DataFrame and assigning column names.

Python3

# using pivot_table
df = df.pivot_table(index ='Name', columns =['Grade'],
                        values =['Exam']).reset_index()
# Defining columns
df.columns =['Name', 'Maths', 'Physics', 'Chemistry']

# print dataframe
print(df)

Output:

            Name  Maths  Physics  Chemistry
0  Chunky Pandey   89.0     80.0        NaN
1     Paras Jain   90.0     99.0       97.0

Below is the complete code:

Python3

# Python program to convert list of nested
# dictionary into Pandas dataframe

# importing pandas
import pandas as pd

# List of list of dictionary initialization
list = [
        {
        "Student": [{"Exam": 90, "Grade": "a"},
                    {"Exam": 99, "Grade": "b"},
                    {"Exam": 97, "Grade": "c"},
                ],
        "Name": "Paras Jain"
        },
        {
        "Student": [{"Exam": 89, "Grade": "a"},
                    {"Exam": 80, "Grade": "b"}
                ],
        "Name": "Chunky Pandey"
        }
    ]

# rows list initialization
rows = []

# appending rows
for data in list:
    data_row = data['Student']
    time = data['Name']

    for row in data_row:
        row['Name']= time
        rows.append(row)

# using data frame
df = pd.DataFrame(rows)

# using pivot_table
df = df.pivot_table(index ='Name', columns =['Grade'],
                        values =['Exam']).reset_index()

# Defining columns
df.columns =['Name', 'Maths', 'Physics', 'Chemistry']

# print dataframe
print(df)

Output:

            Name  Maths  Physics  Chemistry
0  Chunky Pandey     89       80        NaN
1     Paras Jain     90       99         97