The simplest way to do that is using the Python request modules: import requests URL = ' ' data = json.loads(requests.get(URL).text) # Flattening JSON data pd.json_normalize(data) Conclusion Often, you need to work with API’s response in JSON format.
JSON is a standard format for transferring data in REST APIs. After that, json_normalize() is called on the data to flatten it into a DataFrame. To work around it, you need help from a 3rd module, for example, the Python json module: import json # load data using Python JSON module with open('data/simple.json','r') as f: data = json.loads(f.read()) # Flattening JSON data pd.json_normalize(data)ĭata = json.loads(f.read()) loads data using Python json module. However, Pandas json_normalize() function only accepts a dict or a list of dicts. Often, the JSON data you will be working on is stored locally as a. 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.(image by author) 7. 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()) 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. Use the json module to read the JSON file.Use the pandas library and its read_json function.The first step is to load the json file into a python object.
We will see at the end of this tutorial how to convert this type of file to csv and see how to do it in python. This file represents the pokemons as well as the characteristics associated with each one of them, if you wish to recover the complete list of the Pokedex, you will find it at this address :
0 kommentar(er)
