Python las 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)
Random boi
# 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)import csv
# open the file
with open('csvfile.csv' , 'r') as csvfile:
# create the object of csv.reader()
csv_file_reader = csv.reader(csvfile,delimiter=',')
for row in csv_file_reader:
print(row) import csv
with open('file_csv.csv', newline='') as file:
reader = csv.reader(file)
for row in reader:
print(row)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'})
import csv
with open('some.csv', newline='') as f:
reader = csv.reader(f)
for row in reader:
print(row)
# importing Pandas library
import pandas as pd
pd.read_csv(filepath_or_buffer = "pokemon.csv")
# makes the passed rows header
pd.read_csv("pokemon.csv", header =[1, 2])
# make the passed column as index instead of 0, 1, 2, 3....
pd.read_csv("pokemon.csv", index_col ='Type')
# uses passed cols only for data frame
pd.read_csv("pokemon.csv", usecols =["Type"])
# returns pandas series if there is only one column
pd.read_csv("pokemon.csv", usecols =["Type"],
squeeze = True)
# skips the passed rows in new series
pd.read_csv("pokemon.csv",
skiprows = [1, 2, 3, 4])