After replacing zeros with NaN, which feature had the highest number of missing values before imputation?
After replacing zeros with NaN, which feature had the highest number of missing values before imputation?: a task in data agent rl environment train (Harbor dataset). You have access to the following files: - diabetes.csv All of the files are located only in the '/home/user/input' folder without…
The task
You have access to the following files: - diabetes.csv All of the files are located only in the '/home/user/input' folder without any folders inside 'input'. Do not use '/kaggle/input/' folder as it does not exist.