Modules

Using Modules

To use modules in your scripts, simply use the import keyword. You can use it to import an entire module, or some specific method, data type or constant from it. You can also rename their namespace during the import.
Here's a couple of examples:

import numpy
array1 = numpy.array([1, 2])

import numpy as np
array2 = np.array([3, 4])

from numpy import array
array3 = array([5, 6])

from numpy import array as np_array
array3 = np_array([7, 8])

Standard Library Modules

For all standard library modules, check the standard library.
Here's some of the modules you'll see yourself using somewhat frequently:

• Math:
  Math functions such as sin(), cos(), log(), and constants such as e and π.
• Random:
  Pseudo-Random number generator, can generate numbers based on some statistical distributions.
• Time:
  Provides a Time datatype to you, amazing module since times are painful to program.
• DateTime:
  Provides a DateTime datatype to you, amazing module since dates and times are painful to program.
• Os:
  Handles operating system related operation.

External Modules

For all available modules, check the Python Package Index. To install these, you will probably have to use a pip install command on the terminal, or some similar method (Anaconda brings lots of external modules already).
Here's a highlight of some great modules:

• NumPy & ScyPy:
  Uses code written in C to boost computing speed and introduce computation with matrices and other mathematical data structures.
• MatPlotLib:
  Plot graphs, bar graphs, histograms and more.
• Seaborn:
  Statistical data visualization.
• Pandas:
  Process large data from files and apply statistics related methods.
• SciKit-Learn:
  Regressions, machine learning and more.
• TensorFlow:
  Machine learning, neural networks and deep learning.

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