.dtypes shows the "Amount" column is by default an object
So I tried this,
df['Amount'] = df['Amount'].astype(int)
I got this error,
ValueError: invalid literal for int() with base 10: '3,448.91'
1 Answer
The issue is that your column contains a comma(,). First replace that with empty string, then convert the type to int.
df['Amount'] = df['Amount'].str.replace(',', '').astype(float)
If you want to round off the values and convert to int, do this:
df['Amount'] = df['Amount'].str.replace(',', '').astype(float).round().astype(int)
6 Comments
Karl Knechtel
This will not fix the problem, as
'3448.91' still cannot be converted to integer. There are two things OP could possibly want: to convert to float instead, or to round or truncate the value to an integer according to some rule. The question should not be answered until that is resolved.Karl Knechtel
I downvoted, because I knew you would still get that error.
Mayank Porwal
@Pythonaccount Try the answer now.
Mayank Porwal
@KarlKnechtel Please check my updated answer. I've handled both the cases you pointed out.
Python account
@Mayank Porwal I must be doing something really stupid. First first line above errors as "AttributeError: Can only use .str accessor with string values!". However if I instead create a new column instead of overwriting Amount, df['New_Amount'] = .... It works fine.
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'3,448.91'appears in the column, what do you think should be theintresult for that? Why? In your own words, what doesintmean?