Python: Reads each row of a given csv file and skip the header of the file

Last update on December 21 2024 07:25:34 (UTC/GMT +8 hours)

Write a Python program that reads each row of a given csv file and skip the header of the file. Also print the number of rows and the field names.

Sample Solution:

Python Code :

import csv
fields = []
rows = []
with open('departments.csv', newline='') as csvfile:
 data = csv.reader(csvfile, delimiter=' ', quotechar=',')
 # Following command skips the first row of the CSV file.
 fields = next(data)
 for row in data:
   print(', '.join(row))
print("\nTotal no. of rows: %d"%(data.line_num))
print('Field names are:')
print(', '.join(field for field in fields))

departments.csv

department_id,department_name,manager_id,location_id
10,Administration,200,1700
20,Marketing,201,1800
30,Purchasing,114,1700
40,Human Resources,203,2400
50,Shipping,121,1500
60,IT,103,1400
70,Public Relations,204,2700
80,Sales,145,2500
90,Executive,100,1700
100,Finance,108,1700
110,Accounting,205,1700
120,Treasury,,1700
130,Corporate Tax,,1700
140,Control And Credit,,1700
150,Shareholder Services,,1700
160,Benefits,,1700
170,Manufacturing,,1700
180,Construction,,1700
190,Contracting,,1700
200,Operations,,1700
210,IT Support,,1700
220,NOC,,1700
230,IT Helpdesk,,1700
240,Government Sales,,1700
250,Retail Sales,,1700
260,Recruiting,,1700
270,Payroll,,1700

Sample Output:

10,Administration,200,1700
20,Marketing,201,1800
30,Purchasing,114,1700
40,Human, Resources,203,2400
50,Shipping,121,1500
60,IT,103,1400
70,Public, Relations,204,2700
80,Sales,145,2500
90,Executive,100,1700
100,Finance,108,1700
110,Accounting,205,1700
120,Treasury,,1700
130,Corporate, Tax,,1700
140,Control, And, Credit,,1700
150,Shareholder, Services,,1700
160,Benefits,,1700
170,Manufacturing,,1700
180,Construction,,1700
190,Contracting,,1700
200,Operations,,1700
210,IT, Support,,1700
220,NOC,,1700
230,IT, Helpdesk,,1700
240,Government, Sales,,1700
250,Retail, Sales,,1700
260,Recruiting,,1700
270,Payroll,,1700

Total no. of rows: 28
Field names are:
department_id,department_name,manager_id,location_id

Python Code Editor:

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