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Packages

Updated Oct 28, 2019 ·

Overview​

A package is a collection of modules. These are sometimes called libraries. Many packages are publicly available and free to use. To use a package, we first need to download it from the Python Package Index (PyPI).

Some popular packages:

  • NumPy: For arrays.
  • Matplotlib: For visualization.
  • Scikit-learn: For machine learning.

Installing Pip​

Install packages using pip, Python's package management tool.

  1. Download get-pip.py from link below:

    https://pip.pypa.io/en/stable/installation

  2. Run python3 get-pip.py from the terminal.

  3. Install packages with pip3 install <package_name> (e.g., pip3 install numpy).

Installing a Package​

To install a package, run:

python3 -m pip install package_name

For example, to install pandas:

python3 -m pip install pandas

Import a Package​

When using a package, we import it just like a module. Some packages, like numpy, are commonly given an alias to shorten the code.

  • Import entire package:

    import numpy

  • Use alias:

    import numpy as np

  • Import specific function:

    from numpy import array

When importing entire package, to use a specific function from the package (e.g.array function), the function has to be appended like this:

import numpy
numpy.array([1,2,3])

When importing the specific package, can simply call the function directly:

from numpy import array 
array([1,2,3])

However, simply calling the function might confuse others; using import numpy is clearer as it shows the package in the function call (numpy.array()).

Sample Package: Math​

Calculate the area and circumference of a circle using the formula below:

C = 2 * π * r
A = π * r²

Using code below:

# circle-area-circumference.py
import math

C = 2 * 0.43 * math.pi

A = math.pi * 0.43 ** 2

print("Circumference: " + str(C))
print("Area: " + str(A))

Run the code:

python3  circle-area-circumference.py

Output:

Circumference: 2.701769682087222
Area: 0.5808804816487527

Sample Package: Pandas​

To import Pandas:

import pandas as pd  # 'pd' is a common alias for pandas

Creating a DataFrame​

We can use pandas to create a table-like structure called a DataFrame.

import pandas as pd

data = {"user_id": [1, 2, 3], "order_value": [100, 200, 150]}
sales_df = pd.DataFrame(data)

print(sales_df)

Output:

   user_id  order_value
0        1         100
1        2         200
2        3         150

Reading a CSV File​

To read data from a CSV file into a DataFrame:

sales_df = pd.read_csv("sales_data.csv")
print(type(sales_df))  # <class 'pandas.core.frame.DataFrame'>

Previewing Data​

If a dataset has many rows, we can preview the first five:

print(sales_df.head())  # Shows the first 5 rows