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Furthermore, we can convert almost any standard data type to any other data type using the Pandas library.
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In cases like this, the Pandas library can make for an efficient way to explore and analyze the data. Working with large JSON datasets can deteriorate, mainly when they are too large to fit into memory. In the final step, we need to use the Pandas to_csv() function to convert Pandas object to CSV data or export it into a file. In the second step, we have used the read_json() function to convert it into a Pandas object. In the first step, we have prepared the JSON file. The exported file’s name is the streaming.csv file, in the same directory as the export.json file. So that is why the returning value here is None. In this case, we don’t need to return any data because we are exporting the file. Convert JSON to CSV using pandas in python pandas is a library in python that can be used to convert JSON (String or file) to CSV file, all you need is. PdObj.to_csv('streaming.csv', index=False) We are exporting in the same directory as the export.json file. We need to provide the export path to create a CSV file to do that. We have disabled the index because we don’t need an index in CSV data. PdObj = pd.read_json('export.json', orient='index') Let’s convert Pandas object to CSV data and print it in the console. įrom the output, we can say that we have transformed the json string into Pandas object. You can copy the following content and create your json file. Let’s say we have a file called export.json.
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Read the data using the read_json() function and transform it into a Pandas object. Then with the dataframe in a table format, it's easy to convert to CSV with the 'df.tocsv ()' dataframe object method.Then we read that file get the data, and convert it into CSV format using the following steps. So we have to create a static json file with some data. Gender_unknown = meetupĬsv_writer.In our case, there are no servers. import jsonĭata_to_file = open(output_file, 'w', newline='')Ĭsv_writer = csv.writer(data_to_file, delimiter=" ")Ĭsv_writer.writerow() The JSON was too nestled and complex to parse, so now I just read the fields I need from the data. If anyone else has the same problem, I solved it, not very elegantly, but I needed the data. Therefore, the description of the value should be listed just once, as a header, and the values listed beneath (new lines and pipes indicating a new field of a csv sheet): RSVPs_per_event | Organizer | ID I get multiple Meetup groups in the reply, all having the same structure as shown above. Any help is really appreciated, and it would be great if it was Python3 compatible.Įdit: What I would like it to look like in the end: However, if I don't write it as a list, I only get the fields of the JSON object, without the data, so it would just be 'Organizers', 'Name' etc, without the actual name.Īs I said, I am a python beginner and haven't found any libraries to help me with it, but I'm sure they exist. So basically, the whole JSON object in a single CSV field, with weird 'u's, in lists and so on. This leads to a really ugly output, looking like this (again, the values in caps are anonymized): Now, as you can see, I write into the CSV as a list. My code, anonymized: import jsonĭata = requests.get(url_path, params=params) Getting the data is not a problem, but I can't seem to parse the JSON object into a proper CSV file. I've never worked with JSON or Python, so I've run into some issues. I need to get some data from the Meetup API, convert the JSON I get into a CSV, all of that in Python 3.