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Convert pandas DataFrame to List of dictionaries python

A pandas DataFrame is a two-dimensional, tabular data structure with labeled rows and columns. It can be thought of as a dictionary of dictionaries, with the outer dictionary keys being the column names and the inner keys being the row labels. To convert a DataFrame to a list of dictionaries, we can use the to_dict() method. This will return a list of dictionaries, with each dictionary representing a row in the DataFrame. The keys in each dictionary will be the column names, and the values will be the row values.
import pandas as pd

# create dataframe and add column and rows to it
df_fruits = pd.DataFrame()
df_fruits["fruit_name"] = ["Orange", "Banana", "Apple", "Grapes"]
df_fruits["color"] = ["orange", "yellow", "red", "green"]
df_fruits["price"] = [50, 100, 150, 70]

# convert DataFrame to list of dictionaries
result = df_fruits.to_dict('records')

print(result)
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Output

[
   {'fruit_name': 'Orange', 'color': 'orange', 'price': 50}, 
   {'fruit_name': 'Banana', 'color': 'yellow', 'price': 100}, 
   {'fruit_name': 'Apple', 'color': 'red', 'price': 150}, 
   {'fruit_name': 'Grapes', 'color': 'green', 'price': 70}
]

Our DataFrame will look like this:

╒════╤══════════════╤═════════╤═════════╕
│    │ fruit_name   │ color   │   price │
╞════╪══════════════╪═════════╪═════════╡
│  0 │ Orange       │ orange  │      50 │
├────┼──────────────┼─────────┼─────────┤
│  1 │ Banana       │ yellow  │     100 │
├────┼──────────────┼─────────┼─────────┤
│  2 │ Apple        │ red     │     150 │
├────┼──────────────┼─────────┼─────────┤
│  3 │ Grapes       │ green   │      70 │
╘════╧══════════════╧═════════╧═════════╛

You can pass 'records' as a parameter to the to_dict() method of the pandas DataFrame to convert a DataFrame to the list of dictionaries.

Solution 1: Using DataFrame.to_dict('records') function

If you have a DataFrame and you want to convert it into a list of dictionaries, you can use the DataFrame.to_dict('records') function. This function will take your DataFrame and return a list of dictionaries, where each dictionary represents one row of the DataFrame.

Syntax

DataFrame.to_dict('records')

Code example

import pandas as pd

# create dataframe and add column and rows to it
df = pd.DataFrame({
    'product_id': [1000, 1001, 1002, 1003, 1004],
    'product_name': ['P01', 'P02', 'P03', 'P04', 'P05'],
    'price': [330.0, 510.0, 23.0, 590.0, 620.4]
})

print(df)

# convert DataFrame to list of dictionaries
result = df.to_dict('records')

print(result)

Output

DataFrame output

╒════╤══════════════╤════════════════╤═════════╕
│    │   product_id │ product_name   │   price │
╞════╪══════════════╪════════════════╪═════════╡
│  0 │         1000 │ P01            │   330   │
├────┼──────────────┼────────────────┼─────────┤
│  1 │         1001 │ P02            │   510   │
├────┼──────────────┼────────────────┼─────────┤
│  2 │         1002 │ P03            │    23   │
├────┼──────────────┼────────────────┼─────────┤
│  3 │         1003 │ P04            │   590   │
├────┼──────────────┼────────────────┼─────────┤
│  4 │         1004 │ P05            │   620.4 │
╘════╧══════════════╧════════════════╧═════════╛

After converting to a list of dictionaries:

[
   {'product_id': 1000, 'product_name': 'P01', 'price': 330.0},
   {'product_id': 1001, 'product_name': 'P02', 'price': 510.0},
   {'product_id': 1002, 'product_name': 'P03', 'price': 23.0},
   {'product_id': 1003, 'product_name': 'P04', 'price': 590.0},
   {'product_id': 1004, 'product_name': 'P05', 'price': 620.4}
]

The code example creates a DataFrame and then converts it to a list of dictionaries. The result variable contains the list of dictionaries.

Solution 2: Using DataFrame.T.to_dict().values() function

The function DataFrame.T.to_dict().values() will output the same result as to_dict('records') but you need to use the list() function of python to convert the output to a list of dictionaries. Check the below code example for reference.

Syntax

list(DataFrame.T.to_dict().values())

Code example

import pandas as pd

# create dataframe and add column and rows to it
df = pd.DataFrame({
    'product_id': [1000, 1001, 1002, 1003, 1004],
    'product_name': ['P01', 'P02', 'P03', 'P04', 'P05'],
    'price': [330.0, 510.0, 23.0, 590.0, 620.4]
})

# convert DataFrame to list of dictionaries
result = df.T.to_dict().values()
result = list(result)

print(result)

Output

[
   {'product_id': 1000, 'product_name': 'P01', 'price': 330.0},
   {'product_id': 1001, 'product_name': 'P02', 'price': 510.0},
   {'product_id': 1002, 'product_name': 'P03', 'price': 23.0},
   {'product_id': 1003, 'product_name': 'P04', 'price': 590.0},
   {'product_id': 1004, 'product_name': 'P05', 'price': 620.4}
]

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dataframe to array of objects pandas
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