CSV (or Comma Separated Value) files represent data in a tabular format, with several rows and columns. An example of a CSV file can be an Excel Spreadsheet. These files have the extension of .csv, for instance, neveropen.csv. In this sample file, every row will represent a record of the dataset, and each column will indicate a unique feature variable.
On the other hand, JSON (or JavaScript Object Notation) is a dictionary-like notation that can be used by importing the JSON package in Python. Every record (or row) is saved as a separate dictionary, with the column names as Keys of the dictionary. All of these records as dictionaries are saved in a nested dictionary to compose the entire dataset. It is stored with the extension .json, for example, neveropen.json
Refer to the below articles to understand the basics of JSON and CSV.
Converting CSV to JSON
We will create a JSON file that will have several dictionaries, each representing a record (row) from the CSV file, with the Key as the column specified.
Sample CSV File used:
Python3
import csvimport json# Function to convert a CSV to JSON# Takes the file paths as argumentsdef make_json(csvFilePath, jsonFilePath): # create a dictionary data = {} # Open a csv reader called DictReader with open(csvFilePath, encoding='utf-8') as csvf: csvReader = csv.DictReader(csvf) # Convert each row into a dictionary # and add it to data for rows in csvReader: # Assuming a column named 'No' to # be the primary key key = rows['No'] data[key] = rows # Open a json writer, and use the json.dumps() # function to dump data with open(jsonFilePath, 'w', encoding='utf-8') as jsonf: jsonf.write(json.dumps(data, indent=4)) # Driver Code# Decide the two file paths according to your# computer systemcsvFilePath = r'Names.csv'jsonFilePath = r'Names.json'# Call the make_json functionmake_json(csvFilePath, jsonFilePath) |
Output:
