import csv python code example

Example 1: python read csv

# pip install pandas 
import pandas as pd

# Read the csv file
data = pd.read_csv('data.csv')

# Print it out if you want
print(data)

Example 2: create csv file python

# This action requires the 'csv' module
import csv

# The basic usage is to first define the rows of the csv file:
row_list = [["SN", "Name", "Contribution"],
             [1, "Linus Torvalds", "Linux Kernel"],
             [2, "Tim Berners-Lee", "World Wide Web"],
             [3, "Guido van Rossum", "Python Programming"]]

# And then use the following to create the csv file:
with open('protagonist.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerows(row_list)
# This will create a csv file in the current directory

Example 3: how to import csv in pandas

import pandas as pd

df = pd.read_csv (r'Path where the CSV file is stored\File name.csv')
print (df)

Example 4: csv python write

import csv

with open('names.csv', 'w') as csvfile:
    fieldnames = ['first_name', 'last_name']
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

    writer.writeheader()
    writer.writerow({'first_name': 'Baked', 'last_name': 'Beans'})
    writer.writerow({'first_name': 'Lovely', 'last_name': 'Spam'})
    writer.writerow({'first_name': 'Wonderful', 'last_name': 'Spam'})

Example 5: command to read file in python using pandas

import panda as pd 

file_csv = pd.read_csv("file path")  ## as csv format
file_excel = pd.read_excel("file path") ## as excel format
file_json = pd.read_json("file path") ## as json format
file_html = pd.read_html("file path") ## as html format
file_localClipboard = pd.read_clipboard("file path") ## as clipboard format
file_MSExcel = pd.read_excel("file path") ## as excel format
file_HDF5 = pd.read_hdf("file path") ## as hdf5 fomrmat
file_Feather = pd.read_feather("file path") ## as feather format
file_msgpack = pd.read_msgpack("file path") ## as msgpack format
file_stata = pd.read_stata("file path") ## as stata format
file_SAS = pd.read_sas("file path") ## as SAS format
file_paythonPickle = pd.read_pickle("file path") ## as paython_pickle format
file_SQL = pd.read_sql("file path") ## as sql format
file_google_big_query = pd.read_gbq("file path") ## as google big query

Example 6: python read csv file

import csv

with open('employee_birthday.txt') as csv_file:
    csv_reader = csv.reader(csv_file, delimiter=',')
    line_count = 0
    for row in csv_reader:
        if line_count == 0:
            print(f'Column names are {", ".join(row)}')
            line_count += 1
        else:
            print(f'\t{row[0]} works in the {row[1]} department, and was born in {row[2]}.')
            line_count += 1
    print(f'Processed {line_count} lines.')

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