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I have just been a helper on this course and noticed a couple of issues that may need amending (detail below). Hope this is OK raised as an issue, very happy to put in as a PR if that is a better way of doing it.
Nigel
Episode 2, about 2/3 of the way down
Text says: "To support this functionality, most array functions allow us to specify the axis we want to work on. If we ask for the average across axis 0 (rows in our 2D example), we get:
print(numpy.mean(data, axis=0))" (table of output follows this)
but if you look at the diagram it shows down arrows for axis=0, and it is clearly showing an average for the days, which are the columns in our data.
Episode 2, Change In Inflammation exercise
This says: "The numpy.diff() function takes an array and returns the differences between two successive values. Let’s use it to examine the changes each day across the first week of patient 3 from our inflammation dataset.", but the first line in the following code is:
patient3_week1 = data[3, :7]
which will give the data for patient 4 (patient 3 is at index 2).
The text was updated successfully, but these errors were encountered:
Hi,
I have just been a helper on this course and noticed a couple of issues that may need amending (detail below). Hope this is OK raised as an issue, very happy to put in as a PR if that is a better way of doing it.
Nigel
Episode 2, about 2/3 of the way down
Text says: "To support this functionality, most array functions allow us to specify the axis we want to work on. If we ask for the average across axis 0 (rows in our 2D example), we get:
print(numpy.mean(data, axis=0))
" (table of output follows this)but if you look at the diagram it shows down arrows for axis=0, and it is clearly showing an average for the days, which are the columns in our data.
Episode 2, Change In Inflammation exercise
This says: "The numpy.diff() function takes an array and returns the differences between two successive values. Let’s use it to examine the changes each day across the first week of patient 3 from our inflammation dataset.", but the first line in the following code is:
patient3_week1 = data[3, :7]
which will give the data for patient 4 (patient 3 is at index 2).
The text was updated successfully, but these errors were encountered: