Convert DataFrame to Dictionary using Pandas DataFrame to_dict() Method

to_dict() converts a Pandas DataFrame into a dictionary. The structure of the resulting dictionary depends on the specified orientation, allowing you to choose how rows and columns are represented. Example:

import pandas as pd
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': ['x', 'y', 'z']
})

res = df.to_dict()
print(res)

{'A': {0: 1, 1: 2, 2: 3}, 'B': {0: 'x', 1: 'y', 2: 'z'}}

Explanation: Each column is converted into a nested dictionary where the keys are the row indices and values are the column entries.

Syntax

DataFrame.to_dict(orient='dict', into=dict)

Parameters:

• orient (str, default='dict') specifies the format of the resulting dictionary. Common options include:

• into (class, default=dict) is the collection type used for the resulting dictionary. By default, it is the built-in Python dict, but can be set to collections.OrderedDict or others if desired.

Returns: A dictionary (or specified mapping type) representation of the DataFrame

Examples

Example 1: In this example, we convert the DataFrame into a dictionary where each column name maps to a list of its values.

import pandas as pd
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': ['x', 'y', 'z']
})

res = df.to_dict(orient='list')
print(res)

{'A': [1, 2, 3], 'B': ['x', 'y', 'z']}

Example 2: In this example, we convert the DataFrame into a list of dictionaries, where each dictionary represents a row with column names as keys.

import pandas as pd
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': ['x', 'y', 'z']
})

res = df.to_dict(orient='records')
print(res)

[{'A': 1, 'B': 'x'}, {'A': 2, 'B': 'y'}, {'A': 3, 'B': 'z'}]

Example 3: In this example, we convert the DataFrame into a dictionary keyed by the row index, where each value is another dictionary representing the row’s data.

import pandas as pd
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': ['x', 'y', 'z']
})

res = df.to_dict(orient='index')
print(res)

{0: {'A': 1, 'B': 'x'}, 1: {'A': 2, 'B': 'y'}, 2: {'A': 3, 'B': 'z'}}

Example 4: In this example, the DataFrame is converted into a dictionary with separate keys for the index, columns and data.

import pandas as pd
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': ['x', 'y', 'z']
})

res = df.to_dict(orient='split')
print(res)

{'index': [0, 1, 2], 'columns': ['A', 'B'], 'data': [[1, 'x'], [2, 'y'], [3, 'z']]}