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- import pandas as pd
- new_data = pd.read_excel(r"C:\Users\Test\Desktop\std_data.xlsx")
- new_data
- import xml.etree.ElementTree as ET
- import pandas as pd
- mytree = ET.parse(r"C:\Users\Test\Desktop\note.xml")
- myroot = mytree.getroot()
- print(myroot)
- print(myroot[0].text)
- import json
- #with open(r"C:\Users\Test\Desktop\data.json",'r') as f:
- # data1 = json.load(f)
- #print(data1)
- #print(data1['age'])
- data = '{"name":"abu","age":19,"place":"bengaluru"}'
- data_dict = json.loads(data)
- print(data_dict)
- #print(data_dict['name'])
- import pandas as pd
- import json
- employees = pd.read_excel(r"C:\Users\Test\Desktop\employees.xlsx")
- departments = pd.read_xml(r"C:\Users\Test\Desktop\department.xml")
- with open(r"C:\Users\Test\Desktop\salaries.json", 'r') as f:
- salariesdict = json.load(f)
- salaries = pd.DataFrame(salariesdict)
- print("Employees DataFrame:")
- print(employees)
- print("\nDepartments DataFrame:")
- print(departments)
- print("\nSalaries DataFrame:")
- print(salaries)
- merged_df = pd.merge(employees, departments, on="dept_id")
- merged_df = pd.merge(merged_df, salaries, on="dept_id")
- print("\nMerged DataFrame based on dept_id:")
- print(merged_df)
- merged_df.to_csv(r"C:\Users\Test\Desktop\Company.csv", index=False)
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