how to read nested json in python pandas

title: a guide to reading nested json in python pandas
introduction:
json (javascript object notation) is a widely used data interchange format. in many real-world scenarios, json data may be nested, i.e., containing other json objects or arrays within the main structure. when working with nested json data in python, the pandas library offers a convenient way to read and manipulate the data. this tutorial will guide you through the process of reading nested json in python using pandas, with practical examples.
step 1: install pandas
before you begin, make sure you have pandas installed. you can install it using the following command:
step 2: import pandas and load json data
step 3: explore the nested json structure
to understand the nested structure of your json data, print the dataframe's head and inspect the columns:
step 4: flatten nested json using json_normalize
the json_normalize function in pandas helps flatten nested json structures. this is particularly useful when dealing with nested dictionaries or lists within the json data. here's an example:
replace 'nested_column' with the actual name of the column containing nested json structures.
step 5: access nested data
once the json data is flattened, you can access nested information more easily. for example:
replace 'nested_key' with the specific key or column name in the flattened dataframe.
conclusion:
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