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.
Invalid values are defined as any value that is not an integer.
Perform the selection of valid values and store them in column Salary_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_salaries.
Invalid values are defined as any value that is not an integer.
Perform the selection of valid values and store them in column Zip_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_zip.
Invalid values are defined as any value that is not an integer or is an integer below 1.
Perform the selection of valid values and store them in column ManagerID_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_managerID.
Invalid values are defined as any value other than M or F.
Perform the selection of valid values and store them in column Sex_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_sex.
Invalid values are defined as any value other than [White, Black or African American, Asian, Two or more races, American Indian or Alaska Native, Hispanic].
Perform the selection of valid values and store them in column RaceDesc_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_race.
Invalid values are defined as any value other than Single, Married, Divorced, Separated, or Widowed.
Perform the selection of valid values and store them in column MaritalDesc_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_marital_status.
Invalid values are defined as any value that is not a datetime.
Perform the selection of valid values and store them in column DOB_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_DOB.
Invalid values are defined as any value that is not a datetime.
Perform the selection of valid values and store them in column DateofHire_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_HireDate.
Invalid values are defined as any value that does not contain @.
Perform the selection of valid values and store them in column Email_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_Email.
Invalid values are defined as any value that does not contain +.
Perform the selection of valid values and store them in column Phone_Fixed while invalid values should be NaN. Then select invalid values and store the results in the variable df_invalid_Phone.
