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)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)how to import csv in pandas
import pandas as pd
df = pd.read_csv (r'Path where the CSV file is storedFile name.csv')
print (df)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 directorycsv 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'})how to open csv file in python
import csv
with open('example.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=',')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 queryCopyright © 2021 Codeinu
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