In Python, we can convert data to numeric by using the astype()
method. This method is available for all pandas Series and DataFrame objects.
Let's say we have a DataFrame called df
with a column called column_name
that we want to convert to numeric type. We can use the following code:
main.py52 chars2 lines
This will change the data in the column_name
column to floating-point numbers. If we want to convert them to integers, we can use int
instead of float
.
If there are non-numeric values in the column, we can use the errors
parameter of the astype()
method to either raise an error or turn those values into NaN
.
main.py68 chars2 lines
This will raise a ValueError
if there are non-numeric values in the column.
main.py69 chars2 lines
This will turn non-numeric values into NaN
.
Note that if the astype()
method fails to convert a value, it will raise an exception. If you want to handle these exceptions, you can use a try
-except
block.
gistlibby LogSnag