In my case the .csv file had strings as date and time with the following format:
30/07/2017 21:01:17
I find this to be the simplest way to convert this column to float:
df['dateTime'] = df['dateTime'].str.replace('/', '') df['dateTime'] = df['dateTime'].str.replace(':', '') df['dateTime'] = df['dateTime'].str.replace(' ', '') df['dateTime'] = df['dateTime'].astype(float)
So we are removing any signs and spaces between digits and then converting the format to float so the final result would look like this:
30072017210117
Now we can use it in any numpy arrays and machine learning models. Got any better ideas? Please let us know in the comments! 🙂