How can I convert a JSON File as such into a dataframe to do some transformations.
For Example if the JSON file reads:
{"FirstName":"John",
"LastName":"Mark",
"MiddleName":"Lewis",
"username":"johnlewis2",
"password":"2910"}
How can I convert it to a table like such
Column -> FirstName | LastName | MiddleName | username | password
Row ----->    John | Mark |Lewis | johnlewis2 |2910
                To read a JSON file via Pandas, we'll utilize the read_json() method and pass it the path to the file we'd like to read. The method returns a Pandas DataFrame that stores data in the form of columns and rows.
Parse JSON - Convert from JSON to Python If you have a JSON string, you can parse it by using the json.loads() method. The result will be a Python dictionary.
Creating dataframe from dictionary object.
import pandas as pd data = [{'name': 'vikash', 'age': 27}, {'name': 'Satyam', 'age': 14}] df = pd.DataFrame.from_dict(data, orient='columns')  df Out[4]:    age  name 0   27  vikash 1   14  Satyam  If you have nested columns then you first need to normalize the data:
data = [   {     'name': {       'first': 'vikash',       'last': 'singh'     },     'age': 27   },   {     'name': {       'first': 'satyam',       'last': 'singh'     },     'age': 14   } ]  df = pd.DataFrame.from_dict(pd.json_normalize(data), orient='columns')  df     Out[8]: age name.first  name.last 0   27  vikash  singh 1   14  satyam  singh  Source:
pandas.DataFrame.from_dictpandas.json_normalizeimport pandas as pd
print(pd.json_normalize(your_json))
This will Normalize semi-structured JSON data into a flat table
Output
  FirstName LastName MiddleName password    username
      John     Mark      Lewis     2910  johnlewis2
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