Skip to content Skip to sidebar Skip to footer

Sort_values() Method In Pandas

I have the following subset of data and I need to sort the Education column in ascending order; from 0 to 17. I tried the following code without success. suicide_data.sort_index(a

Solution 1:

It looks like you must have mixed types within the Education column of your DataFrame. The error message is telling you that it cannot compare the strings to the floats in your column. Assuming you want to sort the values numerically, you could convert them to integer type and then sort. I'd advise you do this anyways, as mixed types won't be too useful for any operations in your DataFrame. Then use DataFrame.sort_values.

suicide_data['Education'] = suicide_data['Education'].astype('int')
suicide_data.sort_values(by='Education')

It is also worth pointing out that your first attempt,

suicide_data.sort_index(axis=0, kind='mergesort')

would sort your DataFrame by the index, which you don't want, and your second attempt

suicide_data.Education.sort_values()

would only return the sorted Series - they are completely invalid approaches.

Solution 2:

suicide_data['Education'].sort_values('Education', ascending = 'True')

Post a Comment for "Sort_values() Method In Pandas"