![]() ![]() 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()) /rebates/2fcourse2fthe-pandas-bootcamp-data-analysis-with-pandas-python32f&. To read a JSON file we can use the read_json function. 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.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |