Python - Convert dict of list to Pandas dataframe
Last Updated :
28 Nov, 2021
Improve
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
- dictionary.items() is the method to get items from the dictionary
- pd.Series(val) will get series of values from the items() method
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:
