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Python – Convert dict of list to Pandas dataframe

In this article, we will discuss how to convert a dictionary of lists to a pandas dataframe.

Method 1: Using DataFrame.from_dict()

We will use the from_dict method. This method will construct DataFrame from dict of array-like or dicts.



Syntax:

pandas.DataFrame.from_dict(dictionary)

where dictionary is the input dictionary



Example: Program to take student dictionary as input and display subjects data then store in pandas dataframe




# import pandas module
import pandas as pd
  
  
# create a dictionary for three subjects with list
# of three subjects for each student
data = {
    'manoj': ["java", "php", "python"],
    'tripura': ["bigdata", "c/cpp", "R"],
    'uma': ["js/css/html", "ruby", "IOT"]
}
  
# convert to dataframe using from_dict method
pd.DataFrame.from_dict(data)

Output:

Suppose if we want to get the dataframe with keys as row names then we have to use the orient parameter

Syntax:

pd.DataFrame.from_dict(data,orient='index')

Example:




# import pandas module
import pandas as pd
  
  
# create a dictionary for three subjects with list
# of three subjects for each student
data = {
    'manoj': ["java", "php", "python"],
    'tripura': ["bigdata", "c/cpp", "R"],
    'uma': ["js/css/html", "ruby", "IOT"]
}
  
# convert to dataframe using from_dict method
# with orient
pd.DataFrame.from_dict(data, orient='index')

Output:

Method 2: Using pd.Series() 

Here we are using Series data structure inside the dataframe method by using the items() method

Syntax:

pd.DataFrame({ key: pd.Series(val) for key, val in dictionary.items() })

where

Example:




# import pandas module
import pandas as pd
  
# create a dictionary for three subjects with list
# of three subjects for each student
data = {
    'manoj': ["java", "php", "python"],
    'tripura': ["bigdata", "c/cpp", "R"],
    'uma': ["js/css/html", "ruby", "IOT"]
}
  
# convert to dataframe using series with items() method
pd.DataFrame({key: pd.Series(val) for key, val in data.items()})

Output:


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