How to Convert Python Dictionary into Dataframe

Python features dictionary data structure that allows you to easily store data as key-value pairs in a compact manner. It also offers pandas library that allows you to analyze data in tabular manner. Often we need to convert Python dictionary into dataframe, especially if we use python for server programming and receive JSON data from client browsers that is converted into python dictionary before processing. In this article, we will learn how to convert python dictionary into dataframe.

How to Convert Python Dictionary into Dataframe

Let us say you have a python dictionary as shown below where each key is a date and value is a sale amount.

d = {u'2012-06-08': 388,
 u'2022-06-09': 388,
 u'2022-06-10': 388,
 u'2022-06-11': 389,
 u'2022-06-12': 389,
 u'2022-06-13': 389,
 u'2022-06-14': 389,
 u'2022-06-15': 389,
...
}

Let us say you want to convert this dictionary into dataframe as shown below.

     Date         DateValue
0    2022-06-08    388
1    2022-06-09    388
2    2022-06-10    388
.    2022-06-11    389
.    ...           ...

You can easily convert this into dataframe as shown below using DataFrame() constructor. Please note, you need to pass a list of key-value pairs as input to DataFrame() constructor.

In [11]: pd.DataFrame(d.items())  # or list(d.items()) in python 3
Out[11]:
             0    1
0   2022-06-08  388
1   2022-06-09  388
2   2022-06-10  388
3   2022-06-11  389
...

In [12]: pd.DataFrame(d.items(), columns=['Date', 'DateValue'])
Out[12]:
          Date  DateValue
0   2022-06-08        388
1   2022-06-09        388
2   2022-06-10        388

In this article, we have learnt how to convert python dictionary to dataframe. It is useful if you want to analyze python dictionary using pandas framework.

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