Page View Time Series Visualizer test error

Curriculum Help
1

Data Analysis with Python Projects

Page View Time Series Visualizer project

I have the code working and passing all but one test which fails with an error. The error happens in the assignment to ‘actual’ from the test:

class DataCleaningTestCase(unittest.TestCase):
    def test_data_cleaning(self):
        actual = int(time_series_visualizer.df.count())
        expected = 1238
        self.assertEqual(actual, expected, "Expected DataFrame count after cleaning to be 1238.")

And the error is:

TypeError: cannot convert the series to <class 'int'>

the return from df.count() is a Pandas Series and if I change the the line to :

 actual = int(time_series_visualizer.df.count()[0])

It passes. Am I missing something or is this an error in the test code?

3

Hello there,

Could you provide a link to your project, please?

4

I can’t really change the return type. Here is the code.

The df is set up as a global variable by the starter code and df.count() is a pandas method. It returns an array type (pandas series). I can change the test but these are FCC’s tests and should remain unchanged by me.

5

Thank you, for pointing this out. I believe the line should be:

actual = int(time_series_visualizer.df.count(numeric_only=True))
6

Thanks. I put that line in test_module instead.

7

On second thought, I think the reason you are told to:

Use Pandas to import the data from “fcc-forum-pageviews.csv”. Set the index to the “date” column.

Is so that your df is purely numeric…

So, maybe the tests are correct in expecting numeric values…

8

OK That works with the test as is, as long as you drop the date column. (Although I am not sure that should be required to test the count after data cleaning. It wouldn’t hurt to add the argument you suggested.)

Thanks

9

Hello Sky020, I feel your initial suggestion make more sense. Otherwise in draw_bar_plot() session we have to reset the index. Unless this is design intention.

actual = int(time_series_visualizer.df.count(numeric_only=True))

Thanks

10

Thank you so much for this post and mentioning dropping the date column! I didn’t feel right about changing the test code, either, even though it was frustrating that my code was creating the visualizations but kept from passing by that one error. I’m glad I kept looking for answers because this helped clarify the distinction between numerical and non-numerical data and the right tools to use (Numpy) with each type.