|
487 | 487 | "source": [ |
488 | 488 | "## Common Routines\n", |
489 | 489 | "* Common [mathematical](https://docs.scipy.org/doc/numpy-1.14.0/reference/routines.math.html) [routines](https://docs.scipy.org/doc/numpy-1.14.0/reference/routines.html) are exposed so the formula can be abstracted away.\n", |
490 | | -" * [`mean`](https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.mean.html#numpy.mean) is aroutine[statistics](https://docs.scipy.org/doc/numpy-1.14.0/reference/routines.statistics.html) used to calculate the average.\n", |
| 490 | +" * [`mean`](https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.mean.html#numpy.mean) is a [statistics](https://docs.scipy.org/doc/numpy-1.14.0/reference/routines.statistics.html) routine used to calculate the average.\n", |
491 | 491 | "* Reduction functions take a dimension and collapse it into a single value.\n", |
492 | 492 | " * These functions define an axis parameter, and you should remember that the function works across the dimension.\n", |
493 | 493 | "" |
|
500 | 500 | "outputs": [], |
501 | 501 | "source": [] |
502 | 502 | }, |
| 503 | + { |
| 504 | +"cell_type":"code", |
| 505 | +"execution_count":null, |
| 506 | +"metadata": {}, |
| 507 | +"outputs": [], |
| 508 | +"source": [] |
| 509 | + }, |
503 | 510 | { |
504 | 511 | "cell_type":"code", |
505 | 512 | "execution_count":86, |
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