如何在不使用异常的情况下解决 ValueError dtype

Question

I am working on a program that is supposed to update employees salaries by %5 and %10 based on age:

import csv
infile = open('employee.csv')
csvreader = csv.reader(infile)

rows = []
for row in csvreader:
  rows.append(row)

for i in rows:
  if(int(i[2]) < 40):      #LINE CAUSING A PROBLEM
    i[3] = round((1.05 * float(i[3])) , 2)
  else:
    i[3] = round((1.10 * float(i[3])) , 2)

print('\n\nList after updation:')
#loop print the data on the compile
for row in rows:
  print(row)

#open file and write the updated data
with open('employeeUpdate.csv', 'w', encoding='UTF8', newline='') as f:
  writer = csv.writer(f)
  for row in rows:
    writer.writerow(row) 

When I run it I get the following error:

ValueError                                Traceback (most recent call last)
---> 23   if(int(i[2]) < 40):
ValueError: invalid literal for int() with base 10: 'age'

Data Sample:

ID   employee name   age   salary
1    Sara Wales      33    60994
2    John Smith      42    78399
3    Michael Ousley  22    58000
4    Rami Elliot     50    88382

I double-checked the data type and it was an integer--> ('age', dtype('int64'))

I tried with open ('employee.csv', r) as infile and changing the problem line to if int(float(i[2]) < 40): but they both did not work. It said cannot convert string to float. I don't know why it is reading the integer as a string.

But when I added an exception like this:

for i in rows:
  try:
    if (int(i[2]) < 40):
        i[3] = round((1.05 * int(i[3])) , 2)
    else:
        i[3] = round((1.10 * int(i[3])) , 2)
  except ValueError:
        print("")

It worked, so my question is why did it only work with the exception!, and is there a way I can have it done without the exception?

Answer 1

Since csv.reader() continuously reads a stream until EOF, it doesn't have a concept of a header row. For the first iteration of rows , i would always be the string header row. And you're trying to convert the text "age" into int which would Python to error.

Your try-except works because it simply masks the error raised from the first row and prints a blank line instead.

To fix it, simply skip a line from the file to not include the header row, or skip the first iteration when doing the int conversion.

with open('employee.csv') as infile:
    infile.readline()
    csvreader = csv.reader(infile)
    # do stuff with csvreader

When handling large datasets and doing complicated data manipulations, consider using the pandas library. The issue described here and dtype conversions would automatically be handled by pandas.