ValueError: could not convert string to float: '.' Python

Question

So I am trying to make sure that all the values that I have in the csv file are converted into float. The values in each cell inside the csv file are just numbers like for example "0.089" "23". For some reason when I try to run the code it is giving the following error, " ValueError: could not convert string to float: '.' " I can not really understand why the program is not reading the numbers from the csv file properly.

def loadCsv(filename):
    with open('BreastCancerTumor.csv','r') as f:
        lines = f.readlines()[1:]
    dataset = list(lines)
    for i in range(len(dataset)):
        dataset[i] = [float(x) for x in dataset[i]]
    return dataset

The error message is pretty clear. One of the lines you're converting contains just a decimal point. It doesn't know how to convert . to a float. — Frank Yellin
– Frank Yellin, Commented Nov 11, 2021 at 0:14
By the way, did you mean to write dataset[I]? What is I here? — Frank Yellin
– Frank Yellin, Commented Nov 11, 2021 at 0:16
lines is already a list, there's no need to write list(lines) — Barmar
– Barmar, Commented Nov 11, 2021 at 0:17
I just misspell that, it is [i]. I will try to replace the value that contains just the decimal point for 0. So by doing that I can run the program with no errors. Should that work? — Jaime
– Jaime, Commented Nov 11, 2021 at 0:20

Barmar · Accepted Answer · 2021-11-11 00:22:45Z

1

You never split the line into comma-separated fields. So you're looping over the characters in the line, not the fields, and trying to parse each character as a float. You get an error when you get to the . character.

Use the csv library to read the file, it will split each line into lists of fields.

import csv

def loadCsv(filename):
    with open('BreastCancerTumor.csv','r') as f:
        f.readline() # skip header
        csvf = csv.reader(f):

        dataset = [[float(x) for x in row] for row in csvf]
        return dataset

answered Nov 11, 2021 at 0:22

Barmar

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Acccumulation Over a year ago

Panda's read_csv is also an option.

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