Introduction to matplotlib – Part 2

When you finished reading part 1 of the introduction you might have wondered how to draw more than one line or curve into on plot. I will show you now. To make it a bit more interesting we generate two functions: sine and cosine. We generate our x-values with numpy’s linspace function import numpy as…

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numpy random choice

With numpy you can easily create test data with random_integers and randint. numpy.random.randint(low, high=None, size=None, dtype=’l’) numpy.random.random_integers(low, high=None, size=None) random_integers includes the high boundary while randint does not. >>> import numpy as np >>> np.random.random_integers(5) 4 >>> np.random.random_integers(5, size=(5)) array([5, 3, 4, 1, 4]) >>>np.random.random_integers(5, size=(5, 4)) array([[2, 3, 3, 5], [1, 3, 1, 3],…

Linear Algebra with numpy – Part 1

Numpy is a package for scientific computing in Python. It is blazing fast due to its implementation in C. It is often used together with pandas, matplotlib and Jupyter notebooks. Often these packages are referred to as the datascience stack. Installation You can install numpy via pip pip install numpy Basic Usage In the datascience…

Numpy linspace function

To create e.g. x-axis indices you can use the linspace function from numpy. You give it a range (e.g. 0 to 10) and the number of divisions and it will distribute the values evenly across that range. The stop values is included in the resulting value array by default. Example: >>import numpy as np >>np.linspace(0,…