Python: Skip the headers of a given CSV file

Last update on April 24 2025 12:45:25 (UTC/GMT +8 hours)

5. CSV Header Skipper

Write a Python program to skip the headers of a given CSV file. Use csv.reader

Sample Solution:

Python Code:

import csv
f = open("employees.csv", "r")
reader = csv.reader(f)
next(reader)

for row in reader:
    print(row)

Sample Output:

['100', 'Steven', 'King', 'SKING', '515.123.4567', '1987-06-17', 'AD_PRES', '24000', '', '', '90']
['101', 'Neena', 'Kochhar', 'NKOCHHAR', '515.123.4568', '1987-06-18', 'AD_VP', '17000', '', '100', '90']
['102', 'Lex', 'De Haan', 'LDEHAAN', '515.123.4569', '1987-06-19', 'AD_VP', '17000', '', '100', '90']
['103', 'Alexander', 'Hunold', 'AHUNOLD', '590.423.4567', '1987-06-20', 'IT_PROG', '9000', '', '102', '60']
['104', 'Bruce', 'Ernst', 'BERNST', '590.423.4568', '1987-06-21', 'IT_PROG', '6000', '', '103', '60']
['105', 'David', 'Austin', 'DAUSTIN', '590.423.4569', '1987-06-22', 'IT_PROG', '4800', '', '103', '60']
['106', 'Valli', 'Pataballa', 'VPATABAL', '590.423.4560', '1987-06-23', 'IT_PROG', '4800', '', '103', '60']
['107', 'Diana', 'Lorentz', 'DLORENTZ', '590.423.5567', '1987-06-24', 'IT_PROG', '4200', '', '103', '60']
['108', 'Nancy', 'Greenberg', 'NGREENBE', '515.124.4569', '1987-06-25', 'FI_MGR', '12000', '', '101', '100']
['109', 'Daniel', 'Faviet', 'DFAVIET', '515.124.4169', '1987-06-26', 'FI_ACCOUNT', '9000', '', '108', '100']
['110', 'John', 'Chen', 'JCHEN', '515.124.4269', '1987-06-27', 'FI_ACCOUNT', '8200', '', '108', '100']
['111', 'Ismael', 'Sciarra', 'ISCIARRA', '515.124.4369', '1987-06-28', 'FI_ACCOUNT', '7700', '', '108', '100']
['112', 'Jose Manuel', 'Urman', 'JMURMAN', '515.124.4469', '1987-06-29', 'FI_ACCOUNT', '7800', '', '108', '100']
['113', 'Luis', 'Popp', 'LPOPP', '515.124.4567', '1987-06-30', 'FI_ACCOUNT', '6900', '', '108', '100']
['114', 'Den', 'Raphaely', 'DRAPHEAL', '515.127.4561', '1987-07-01', 'PU_MAN', '11000', '', '100', '30']
['115', 'Alexander', 'Khoo', 'AKHOO', '515.127.4562', '1987-07-02', 'PU_CLERK', '3100', '', '114', '30']
['116', 'Shelli', 'Baida', 'SBAIDA', '515.127.4563', '1987-07-03', 'PU_CLERK', '2900', '', '114', '30']
['117', 'Sigal', 'Tobias', 'STOBIAS', '515.127.4564', '1987-07-04', 'PU_CLERK', '2800', '', '114', '30']
['118', 'Guy', 'Himuro', 'GHIMURO', '515.127.4565', '1987-07-05', 'PU_CLERK', '2600', '', '114', '30']
['119', 'Karen', 'Colmenares', 'KCOLMENA', '515.127.4566', '1987-07-06', 'PU_CLERK', '2500', '', '114', '30']
['120', 'Matthew', 'Weiss', 'MWEISS', '650.123.1234', '1987-07-07', 'ST_MAN', '8000', '', '100', '50']
['121', 'Adam', 'Fripp', 'AFRIPP', '650.123.2234', '1987-07-08', 'ST_MAN', '8200', '', '100', '50']
['122', 'Payam', 'Kaufling', 'PKAUFLIN', '650.123.3234', '1987-07-09', 'ST_MAN', '7900', '', '100', '50']
['123', 'Shanta', 'Vollman', 'SVOLLMAN', '650.123.4234', '1987-07-10', 'ST_MAN', '6500', '', '100', '50']
['124', 'Kevin', 'Mourgos', 'KMOURGOS', '650.123.5234', '1987-07-11', 'ST_MAN', '5800', '', '100', '50']
['125', 'Julia', 'Nayer', 'JNAYER', '650.124.1214', '1987-07-12', 'ST_CLERK', '3200', '', '120', '50']
['126', 'Irene', 'Mikkilineni', 'IMIKKILI', '650.124.1224', '1987-07-13', 'ST_CLERK', '2700', '', '120', '50']
['127', 'James', 'Landry', 'JLANDRY', '650.124.1334', '1987-07-14', 'ST_CLERK', '2400', '', '120', '50']
['128', 'Steven', 'Markle', 'SMARKLE', '650.124.1434', '1987-07-15', 'ST_CLERK', '2200', '', '120', '50']
['129', 'Laura', 'Bissot', 'LBISSOT', '650.124.5234', '1987-07-16', 'ST_CLERK', '3300', '', '121', '50']
['130', 'Mozhe', 'Atkinson', 'MATKINSO', '650.124.6234', '1987-07-17', 'ST_CLERK', '2800', '', '121', '50']
['131', 'James', 'Marlow', 'JAMRLOW', '650.124.7234', '1987-07-18', 'ST_CLERK', '2500', '', '121', '50']
['132', 'TJ', 'Olson', 'TJOLSON', '650.124.8234', '1987-07-19', 'ST_CLERK', '2100', '', '121', '50']
['133', 'Jason', 'Mallin', 'JMALLIN', '650.127.1934', '1987-07-20', 'ST_CLERK', '3300', '', '122', '50']
['134', 'Michael', 'Rogers', 'MROGERS', '650.127.1834', '1987-07-21', 'ST_CLERK', '2900', '', '122', '50']
['135', 'Ki', 'Gee', 'KGEE', '650.127.1734', '1987-07-22', 'ST_CLERK', '2400', '', '122', '50']
['136', 'Hazel', 'Philtanker', 'HPHILTAN', '650.127.1634', '1987-07-23', 'ST_CLERK', '2200', '', '122', '50']
['137', 'Renske', 'Ladwig', 'RLADWIG', '650.121.1234', '1987-07-24', 'ST_CLERK', '3600', '', '123', '50']
['138', 'Stephen', 'Stiles', 'SSTILES', '650.121.2034', '1987-07-25', 'ST_CLERK', '3200', '', '123', '50']
['139', 'John', 'Seo', 'JSEO', '650.121.2019', '1987-07-26', 'ST_CLERK', '2700', '', '123', '50']
['140', 'Joshua', 'Patel', 'JPATEL', '650.121.1834', '1987-07-27', 'ST_CLERK', '2500', '', '123', '50']
['141', 'Trenna', 'Rajs', 'TRAJS', '650.121.8009', '1987-07-28', 'ST_CLERK', '3500', '', '124', '50']
['142', 'Curtis', 'Davies', 'CDAVIES', '650.121.2994', '1987-07-29', 'ST_CLERK', '3100', '', '124', '50']
['143', 'Randall', 'Matos', 'RMATOS', '650.121.2874', '1987-07-30', 'ST_CLERK', '2600', '', '124', '50']
['144', 'Peter', 'Vargas', 'PVARGAS', '650.121.2004', '1987-07-31', 'ST_CLERK', '2500', '', '124', '50']
['145', 'John', 'Russell', 'JRUSSEL', '011.44.1344.429268', '1987-08-01', 'SA_MAN', '14000', '0.4', '100', '80']
['146', 'Karen', 'Partners', 'KPARTNER', '011.44.1344.467268', '1987-08-02', 'SA_MAN', '13500', '0.3', '100', '80']
['147', 'Alberto', 'Errazuriz', 'AERRAZUR', '011.44.1344.429278', '1987-08-03', 'SA_MAN', '12000', '0.3', '100', '80']
['148', 'Gerald', 'Cambrault', 'GCAMBRAU', '011.44.1344.619268', '1987-08-04', 'SA_MAN', '11000', '0.3', '100', '80']
['149', 'Eleni', 'Zlotkey', 'EZLOTKEY', '011.44.1344.429018', '1987-08-05', 'SA_MAN', '10500', '0.2', '100', '80']
['150', 'Peter', 'Tucker', 'PTUCKER', '011.44.1344.129268', '1987-08-06', 'SA_REP', '10000', '0.3', '145', '80']

Flowchart:

For more Practice: Solve these Related Problems:

Write a Python program to open a CSV file using csv.reader, skip the header row, and then print the remaining rows.
Write a Python function that reads a CSV file, discards the first row (header), and returns a list of data rows.
Write a Python script to count the number of rows in a CSV file after skipping the header row using csv.reader.
Write a Python program to read a CSV file, skip the header, and compute the sum of a specific numeric column.

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Python Code Editor:

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