Python: Numpy Part II

Beyond numpy’s usefulness in creating arrays and matrices, numpy also provides a great suite of math functions that – for anyone with any programming background – are fairly intuitive.

Here are some examples:

np.pi returns pi and np.sqrt() takes the square root of whatever value you feed it.

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Trig Functions

numpy handles most common trigonometry functions.

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Stats

Numpy handles many statistics functions.

Below we have mean and median. Unfortunately, just like in R, there is no mode command, but we can fake it using Set.

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using set to fake mode

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Numpy can also be used to find range, variance, and standard deviation.

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Rounding

Numpy has rounding features for dealing with decimals. It also has floor() and ceil() functions that bring the number down to the “floor” or up to the “ceiling”

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Use in creating graphs

use np.sin()

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use np.log()

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you can even put the two together

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linspace()

My final one today is a function called linspace(). It lets you create a start and finish point, and how many elements you want. It then will create a even list of number between start and finish.

linspace(start,finish, num=numbers you want)

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