Sorting Data
We need sorting for ease of work.
We can sort our data in 2 ways: ascending sorting and descending sorting.
To perform the ascending sorting, use the following code:
DataFrame.sort_values(by = 'column_name', inplace = True)
If we want to perform descending, we have to turn off the ascending parameter.
DataFrame.sort_values(by = 'column_name', inplace = True, ascending = False)
If the parameter inplace is set to
True(inplace = True), it will perform the operation inplace. Modify the original DataFrame itself. The return type isNone.
Swipe to start coding
Now we are going to practice sorting. We will sort 2 different DataFrame columns using ascending and descending sorting.
- Import the
pandasusing thepdalias. - Perform an ascending sorting by the
'price'column. - Perform a descending sorting by the
'user_id'column.
Solution
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We need sorting for ease of work.
We can sort our data in 2 ways: ascending sorting and descending sorting.
To perform the ascending sorting, use the following code:
DataFrame.sort_values(by = 'column_name', inplace = True)
If we want to perform descending, we have to turn off the ascending parameter.
DataFrame.sort_values(by = 'column_name', inplace = True, ascending = False)
If the parameter inplace is set to
True(inplace = True), it will perform the operation inplace. Modify the original DataFrame itself. The return type isNone.
Swipe to start coding
Now we are going to practice sorting. We will sort 2 different DataFrame columns using ascending and descending sorting.
- Import the
pandasusing thepdalias. - Perform an ascending sorting by the
'price'column. - Perform a descending sorting by the
'user_id'column.
Solution
Passez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessousMerci pour vos commentaires !
Awesome!
Completion rate improved to 2.08single
