Python dictionary is one of the most versatile data structures. It can store any type of data. Pandas dataframe is a row and column-oriented data structure that is ideal for data analysis and data visualization tasks. This blog is about how you can convert dictionary to pandas dataframe in python.

The way to convert dictionary to Pandas DataFrame in Python

Option 1: Utilize pandas.dataframe().from_dict()

You can utilize pandas.dataframe().from_dict() to convert a Python Dictionary to a Pandas DataFram. Let’s take a look at an example of this:

import pandas as pd 
print(pd.DataFrame.from_dict({  
 'heeya': 43,  
 'meet': 45,  
 'jaydeep': 47,  
 'romil': 41,   
 'vrunda': 48,  
 'nirali': 43}, orient='index').rename(columns={0:'marks'}))

Output

marks heeya       43

meet        45

jaydeep     47

romil       41

vrunda      48

nirali      43

Option 2: Utilize pd.dataframe()

Another way to convert dictionary to Pandas Dataframe in Python is using pd.dataframe(). 

import pandas as pd 
marks_dict = {  
 'heeya': 43,  
 'meet': 45,  
 'jaydeep': 47,  
 'romil': 41,  
 'vrunda': 48,  
 'nirali': 43} 
 print(pd.DataFrame(list(marks_dict.items()),                    
                    columns=['student', 'marks']))

Output

student  marks 0   

heeya     43 1    

meet     45 2 

jaydeep     47 3   

romil     41 4  

vrunda     48 5  

nirali     43

Option 3: Use list of items

Utilizing the list(my_dict.items()) to creat list of Dictionary items is a great solution to convert dictionary to Pandas Dataframe in Python. The columns parameter also allows you to pass the values for the column headers.

For example, the dictionary’s key values do not consist of a list of values. The dictionary keys will be produced as rows in the pandas dataframe by this method.

import pandas as pd

my_dict = {"S.No.": 1, "Item":"CPU", "Quantity": 3, "Price": 5000}

df = pd.DataFrame(list(my_dict.items()), columns = ['Name','Value'])

df

Output

Conclusion

We hope you found our blog post on how to convert dictionary to pandas dataframe in python helpful. If you have any further queries or concerns about this topic, please leave a comment. Thank you for reading; we are always glad when one of our articles provides useful knowledge on this subject!

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