How to import a csv-file into a data array?

Question

I have a line of code in a script that imports data from a text file with lots of spaces between values into an array for use later.

textfile = open('file.txt')
data = []
for line in textfile:
    row_data = line.strip("\n").split()
    for i, item in enumerate(row_data):
        try:
            row_data[i] = float(item)
        except ValueError:
            pass
    data.append(row_data)

I need to change this from a text file to a csv file. I don't want to just change this text to split on commas (since some values can have commas if they're in quotes). Luckily I saw there is a csv library I can import that can handle this.

import csv
with open('file.csv', 'rb') as csvfile:
    ???

How can I load the csv file into the data array?

If it makes a difference, this is how the data will be used:

row = 0
for row_data in (data):
    worksheet.write_row(row, 0, row_data)
    row += 1

Answer 1

Assuming the CSV file is delimited with commas, the simplest way using the csv module in Python 3 would probably be:

import csv  with open('testfile.csv', newline='') as csvfile:     data = list(csv.reader(csvfile))  print(data) 

You can specify other delimiters, such as tab characters, by specifying them when creating the csv.reader:

    data = list(csv.reader(csvfile, delimiter='\t')) 

For Python 2, use open('testfile.csv', 'rb') to open the file.

Answer 2

You can use pandas library or numpy to read the CSV file. If your file is tab-separated then use '\t' in place of comma in both sep and delimiter arguments below.

import pandas as pd 
myFile = pd.read_csv('filepath', sep=',')

Or

 import numpy as np
 myFile = np.genfromtxt('filepath', delimiter=',')