Python data error: ValueError: invalid literal for int() with base 10: '42152129.0'

Question

I am working on a simple data science project with Python. However, I am getting an error which is the following:

ValueError: could not convert string to float:

Here is what my code looks like:

import matplotlib.pyplot as plt 
import csv
from datetime import datetime

filename = 'USAID.csv'
with open(filename) as f:
reader = csv.reader(f)
header_row = next(reader)

monies = []
for row in reader:
   money = int(row[1])
   monies.append(money)
print(monies)

if I change the line:

money = int(row[1]) to money = float(row[1])

I get this error: ValueError: could not convert string to float: Here are my tracebacks: first error:

Traceback (most recent call last):
File "funding.py", line 60, in <module>
  money = int(row[1])
ValueError: invalid literal for int() with base 10: '42152129.0'

Second Error:

Traceback (most recent call last):
File "funding.py", line 60, in <module>
  money = float(row[1])
ValueError: could not convert string to float:

Any help would be great! Thank you!

Answer 1

The first failure is because you passed a string with . in it to int() ; you can't convert that to an integer because there is a decimal portion.

The second failure is due to a different row[1] string value; one that is empty.

You could test for that:

if row[1]:
   money = float(row[1])

Since you are working with a Data Science project you may want to consider using the pandas project to load your CSV instead with DataFrame.read_csv() .

Answer 2

Some of the entries in row[1] are empty so you probably want to check for those before trying to cast . Pass a default value of, say 0 , if the entry is blank.

Then you should consider using decimal for computations that relate to money.

Answer 3

I had the same issue while I was learning data visualization using Seaborn. Thanks EdChum 's help, I was able to solve the issue with his approach:

df['col'] = pd.to_numeric(df['col'], errors='coerce')