Error in location_data.unique()

Addendum: Actually, I got error messages every time I used 'unique', as shown below:

Hi Vania!

Thanks for reaching out.

The error DataFrame object has no attribute 'unique' occurs because the unique() function is not a direct attribute of a DataFrame object in pandas.

To get the unique values from a column or Series within a DataFrame, you can use the unique() function on that specific column or Series.

if location_data is a Series object instead of a DataFrame, the unique() function would work without producing the error.

Thus, I assume that earlier in your code you created a DataFrame with the same name. Please try to restart Kernel and re-execute the code cells after creating a Series object in a new document. 

Hope this helps.

Best,

Ivan

Hi Ivan,

Thanks for your quick reply. I re-started the kernel, but obtained the same mistake. I did not create a dataFrame before with the same name, I have been copying everything from the video class into jupyter.

 I also tried the same code in a different document but obtained the same error messages. 

However, as regards it being a Series object or a dataFrame, I did obtain the results below that I don't know how to interpret:

Thanks again. Best, Vânia

Hi Vania!

The reason you have a DataFrame instead of a Series, as shown in the lesson, is because you didn't utilize the squeeze parameter when creating the variable that holds the data from the resources.

When squeeze=True is used, the output is returned as a Series object instead of a DataFrame.

data = pd.read_csv('Location.csv', squeeze = True)

After fixing that, your code should work as intended.

Hope this helps.

Best,

Ivan

after the line:

     data = pd.read_csv('Location.csv')

add the line:
    data = data.squeeze("columns")

Then check you have a Series and not a DataFrame.

unique() only works on Series. If you do not 'squeee' the columns then pd will create a DataFrame instead of a Series.  The video is dated as the attribute 'squeeze = True' has now been deprecated. It would be nice if Data365 added a caption to tell us this. It took me a while to work out what was going on.