On the other hand, JSON files can have much more complex structures than CSV files, so a direct conversion is not always possible and will require us to rework our structure of the file concerned. SummaryĪs we have seen, it may be easy to convert a Json file to a CSV file. ![]() Of course it’s possible to get all the JSON file data. To retrieve the header we need to use the keys() function which allows us to get the keys of each “ Name” element of our JSON file. ![]() We were able to export the different names of the Pokémon in the CSV. Here is an example with the pokedex.json file :Ĭsvwriter.writerow(data.keys()) JSON in Python Python has a built-in package called json, which can be used to work with JSON data. JSON is text, written with JavaScript object notation. To read a JSON file we can use the read_json function. JSON is a syntax for storing and exchanging data. Indeed a lot of python API returns as a result of JSON and with pandas it is very easy to exploit this data directly. Pandas is a python library that allows to easily manipulate data to be analyzed.
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