JIYIK CN >

JSON is JavaScript Object Notationan abbreviation of , which is based on the format of objects in JavaScript and is an encoding technology for representing structured data. It is based on the format of objects in JavaScript and is an encoding technology for representing structured data. It is now widely used, especially for data sharing between servers and network applications.

CSV files are used to store data in a tabular format such as an Excel spreadsheet.

In this tutorial, we will learn how to convert JSON data into a CSV file.

to_csv()Convert JSON to CSV in Python using Pandas DataFrames

In this method, we will first convert the JSON to a Pandas DataFrame and then to_csv()convert it to a CSV file using the parseInt method. We can use the parseInt function jsonprovided by the Python library json.loads()to read the JSON string and convert the JSON to a DataFrame. We will then pass this JSON object to json_normalize()the parseInt function, which will return a Pandas DataFrame containing the required data.

The following code snippet will explain how we do this.

import pandas as pd
import json

data = """
{
"Results":
         [
         { "id": "1", "Name": "Jay" },
         { "id": "2", "Name": "Mark" },
         { "id": "3", "Name": "Jack" }
         ],
"status": ["ok"]
}
"""

info = json.loads(data)

df = pd.json_normalize(info["Results"])

df.to_csv("samplecsv.csv")

The contents of the created CSV file are as follows.

,id,Name
0,1,Jay
1,2,Mark
2,3,Jack

Use csvthe module to convert JSON to CSV file

In this method, we will use csvthe CSV library in Python, which is used to read and write CSV files. First, we will read the JSON data like in the previous method. We open a file in write mode and use the JSON object csvfrom the module DictWriter()to create an object that allows us to map and write JSON data to the file. The keys are the keys that are recognized and matched to the data fieldnameswhen we write the lines using the CSV function.writerows()

The following code snippet shows how we can implement the above method.

import csv
import json

data = """
{
"Results":
         [
         { "id": "1", "Name": "Jay" },
         { "id": "2", "Name": "Mark" },
         { "id": "3", "Name": "Jack" }
         ],
"status": ["ok"]
}
"""

info = json.loads(data)["Results"]

print(info[0].keys())

with open("samplecsv.csv", "w") as f:
    wr = csv.DictWriter(f, fieldnames=info[0].keys())
    wr.writeheader()
    wr.writerows(info)