How do I fix invalid literal for int() with base 10 error in pandas

I run this

int('260,327,021')

and get this

---------------------------------------------------------------------------ValueError                                Traceback (most recent call last)<ipython-input-448-a3ba7c4bd4fe> in <module>()----> 1 int('260,327,021')ValueError: invalid literal for int() with base 10: '260,327,021'

I assure you that not everything in your dataframe is a number. It may look like a number, but it is a string with commas in it.

You'll want to replace your commas and then turn to an int

pd.Series(['260,327,021']).str.replace(',', '').astype(int)0    260327021dtype: int64

Others might encounter the following issue, when the string is a float:

    >>> int("34.54545")Traceback (most recent call last):  File "<stdin>", line 1, in <module>ValueError: invalid literal for int() with base 10: '34.54545'

The workaround for this is to convert to a float first and then to an int:

>>> int(float("34.54545"))34

Or pandas specific:

df.astype(float).astype(int)

I solved the error using pandas.to_numeric

In your case,

data.Population1 = pd.to_numeric(data.Population1, errors="coerce")

'data' is the parent Object.

After that, you can convert float to int as well

data.Population1.astype(int)