All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.
All our activities include solutions with explanations on how they work and why we chose them.
Make sure you run all the previous cells. Don't worry if you screw up with the DataFrame! just reload it with the first line of the notebook.
Look at the result of question 1 and find which column has the most of its values missing
You can check the column from the solution for question 1. No need to write any code.
You must modify the
df variable itself. Don't worry if you screw up with the DataFrame! just reload it with the first line of the notebook.
You have to drop this column perminently as we can not use it for any purpose.
Do not use
inpace=True as it will perminently remove the rows from our DataFrame.