The data can also be parsed by using ordered dict but for a better understanding of data, I have converted the data to a dictionary in the code snippet #3.Loading data into R can be quite frustrating. #3 # Selecting headers for CSV HEADERS = rows = # Interating through each element to get row data for employee in employee_data_list: name = employee role= employee age = employee # Adding data of each employee to row list rows.append() #Writing to CSV with open('employee_data.csv', 'w',newline='') as f: write = csv.writer(f) write.writerow(HEADERS) write.writerows(rows) Conclusion: Making headers and rows of employee data and writing it to the CSV file. This is how employee_data_list looks, we can parse the data based on our required columns. #3 # creating a list of employee data employee_data_list = ] The converted dict is an ordered dictionary, so the following code converts all the ordered dict elements to dict. Step 2: Converting XML to DICT #2 # Reading xml file with open('sample.xml', 'r') as file: filedata = file.read() # C onverting xml to python dictionary (ordered dict) data_dict = xmltodict.parse(filedata)

Install the required packages if prompted: #1 import csv import xmltodict Sample XML: Carolina Data Engineer 24 Roosaka Data Scientist 27 Kumar Machine Learning Engineer 31 Vijay Devops Engineer 26 This process has two conversions: XML → DICT → CSV Based on these tags we can select the required columns to make a CSV. Unlike HTML, XML files have their own tags.

Convert xml to csv in r