### Change In Inflammation: Added explanation of numpy.diff()

```Changes to the "Change In Inflammation" example:
Added explanation of numpy.diff(), including an example.
Corrected grammatical problem in the second sentence of the first paragraph.
Fixed spelling of "difference" in first Solution.```
parent a1c7b9af
 ... ... @@ -1139,18 +1139,42 @@ the graphs will actually be squeezed together more closely.) >## Change In Inflammation > >This patient data is _longitudinal_ in the sense that each row represents a >series of observations relating to one individual. This means that change >inflammation is a meaningful concept. >series of observations relating to one individual. This means that >the change in inflammation over time is a meaningful concept. > >The `numpy.diff()` function takes a NumPy array and returns the >difference along a specified axis. >differences between two successive values along a specified axis. For >example, a NumPy array that looks like this: > > ~~~ > npdiff = array([ 0, 2, 5, 9, 14]) > ~~~ > {: .language-python} > >Calling `numpy.diff(npdiff)` would do the following calculations and >put the answers in another array. > > ~~~ > [ 2 - 0, 5 - 2, 9 - 5, 14 - 9 ] > ~~~ > {: .language-python} > ~~~ > numpy.diff(npdiff) > ~~~ > {: .language-python} > > ~~~ > array([2, 3, 4, 5]) > ~~~ > {: .language-python} > >Which axis would it make sense to use this function along? > > > ## Solution > > Since the row axis (0) is patients, it does not make sense to get the > > difference between two arbitrary patients. The column axis (1) is in > > days, so the differnce is the change in inflammation -- a meaningful > > days, so the difference is the change in inflammation -- a meaningful > > concept. > > > > ~~~ ... ...
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