How to Convert Pandas DataFrame to a Dictionary

The following syntax can be used to convert Pandas DataFrame to a dictionary:

my_dictionary = df.to_dict()

Next, you’ll see the complete steps to convert a DataFrame to a dictionary. You’ll also learn how to apply different orientations for your dictionary.

Steps to Convert Pandas DataFrame to a Dictionary

Step 1: Create a DataFrame

To begin with a simple example, let’s create a DataFrame with two columns:

import pandas as pd

data = {'Product': ['Laptop','Printer','Monitor','Tablet'],
        'Price': [1200,100,300,150]
        }
df = pd.DataFrame(data, columns = ['Product', 'Price'])

print (df)
print(type(df))

You’ll then get the following DataFrame:

   Product  Price
0   Laptop   1200
1  Printer    100
2  Monitor    300
3   Tablet    150
<class 'pandas.core.frame.DataFrame'>

Note that the syntax of print(type(df)) was added at the bottom of the code to demonstrate that we got a DataFrame (as highlighted in yellow).

Step 2: Convert the DataFrame to a Dictionary

You can use df.to_dict() in order to convert the DataFrame to a dictionary.

Here is the complete code to perform the conversion:

import pandas as pd

data = {'Product': ['Laptop','Printer','Monitor','Tablet'],
        'Price': [1200,100,300,150]
        }
df = pd.DataFrame(data, columns = ['Product', 'Price'])

my_dictionary = df.to_dict()

print (my_dictionary)
print(type(my_dictionary))

Run the code, and you’ll get this dictionary:

{'Product': {0: 'Laptop', 1: 'Printer', 2: 'Monitor', 3: 'Tablet'}, 'Price': {0: 1200, 1: 100, 2: 300, 3: 150}}
<class 'dict'>

The above dictionary has the following ‘dict‘ orientation (which is the default):

{'column name':{index value:'column value'}}

You may pick other orientations based on your needs. Let’s now review two additional orientations:

• The ‘list‘ orientation
• The ‘split‘ orientation

The List Orientation

The ‘list’ orientation has the following structure:

{'column name':['column values']}

In order to get the list orientation, you’ll need to set orient = ‘list’ as captured below:

import pandas as pd

data = {'Product': ['Laptop','Printer','Monitor','Tablet'],
        'Price': [1200,100,300,150]
        }
df = pd.DataFrame(data, columns = ['Product', 'Price'])

my_dictionary = df.to_dict(orient = 'list')

print (my_dictionary)
print(type(my_dictionary))

You’ll now get the following orientation:

{'Product': ['Laptop', 'Printer', 'Monitor', 'Tablet'], 'Price': [1200, 100, 300, 150]}
<class 'dict'>

The Split Orientation

The ‘split’ orientation looks like this:

{'index':[index values],'columns':['column names'], 'data': [[column values]]}

To get the split orientation, set orient = ‘split’ as follows:

import pandas as pd

data = {'Product': ['Laptop','Printer','Monitor','Tablet'],
        'Price': [1200,100,300,150]
        }
df = pd.DataFrame(data, columns = ['Product', 'Price'])

my_dictionary = df.to_dict(orient = 'split')

print (my_dictionary)
print(type(my_dictionary))

You’ll now see the following orientation:

{'index': [0, 1, 2, 3], 'columns': ['Product', 'Price'], 'data': [['Laptop', 1200], ['Printer', 100], ['Monitor', 300], ['Tablet', 150]]}
<class 'dict'>

There are additional orientations to choose from. You can check the Pandas Documentations for the complete list of orientations that you may apply.