I get a type error with this. I did upload an image though guess it didn't work.
Find example of data here:
age workclass fnlwgt education education-num marital-status occupation relationship race sex capital-gain capital-loss hours-per-week native-country prediction
17 32.0 Private 186824.0 HS-grad 9.0 Never-married Machine-op-inspct Unmarried White Male 0.0 0.0 40.0 United-States <=50K
18 38.0 Private 28887.0 11th 7.0 Married-civ-spouse Sales Husband White Male 0.0 0.0 50.0 United-States <=50K
19 43.0 Self-emp-not-inc 292175.0 Masters 14.0 Divorced Exec-managerial Unmarried White Female 0.0 0.0 45.0 United-States >50K
20 40.0 Private 193524.0 Doctorate 16.0 Married-civ-spouse Prof-specialty Husband White Male 0.0 0.0 60.0 United-States >50K
21 54.0 Private 302146.0 HS-grad 9.0 Separated Other-service Unmarried Black Female 0.0 0.0 20.0 United-States <=50K
22 35.0 Federal-gov 76845.0 9th 5.0 Married-civ-spouse Farming-fishing Husband Black Male 0.0 0.0 40.0 United-States <=50K
23 43.0 Private 117037.0 11th 7.0 Married-civ-spouse Transport-moving Husband White Male 0.0 2042.0 40.0 United-States <=50K
24 59.0 Private 109015.0 HS-grad 9.0 Divorced Tech-support Unmarried White Female 0.0 0.0 40.0 United-States <=50K
25 56.0 Local-gov 216851.0 Bachelors 13.0 Married-civ-spouse Tech-support Husband White Male 0.0 0.0 40.0 United-States >50K
26 19.0 Private 168294.0 HS-grad 9.0 Never-married Craft-repair Own-child White Male 0.0 0.0 40.0 United-States <=50K
27 54.0 ? 180211.0 Some-college 10.0 Married-civ-spouse ? Husband Asian-Pac-Islander Male 0.0 0.0 60.0 South >50K
28 39.0 Private 367260.0 HS-grad 9.0 Divorced Exec-managerial Not-in-family White Male 0.0 0.0 80.0 United-States <=50K
29 49.0 Private 193366.0 HS-grad 9.0 Married-civ-spouse Craft-repair Husband White Male 0.0 0.0 40.0 United-States <=50K
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
Refer to index 27 to see '?'
I would to to search the entire df rather than search a single column. Or would it be necessary to iterate through each column? Though that seems kinda un-python.
