Python

Fundamental Packages

pip
Pip stands for Pip Installs Packages.
numpy
one of the common libraries used to set a data.
matplotlib
one of the most common libraries used to draw a graph.
pandas
Idk

Install Numpy

Numpy stands for Numerical Python. It is a fundamental package for scientific computing in Python.

pip install numpy

Install Matplotlib

Matplotlib is used to create a graph within Python.

pip install matplotlib

Install Pandas

idk

pip install pandas

Update the pip version

To update the pip version, type the following command. 
python.exe -m pip install --upgrade pip

Create a 2D Graph

Fundamental Script

The following script enables you to draw a simple graph, as shown below. The graph represents the function \( f(x) = x^2 - \frac{1}{4}x^3 \) , consisting of 400 points, with the x-values ranging from -2 to 4. 
import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-2, 4, 400)
y = x**2 - (1/4)*x**3

plt.plot(x, y)
plt.show()
the output graph

Load plot data from a file

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

data = pd.read_csv('data.csv')

x = data['my-x']
y = data['my-y']

plt.plot(x, y)
plt.show()
The data to be read is shown below: 
my-x,my-y
-10,10
-6,8
-2,10
2,6
6,10
10,4
The outcome looks like as following:

Points and lines

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-2, 4, 10)
y = x**2 - (1/4)*x**3

plt.plot(x, y, marker='o', linestyle='-')
plt.show()
Otherwise, you can designate its style using the following property inside a plot function:
  • maker

    'None', '^', 'x', 'o', 's', etc

  • makersize

    As default, the markersize is 6.

  • linestyle

    'None', '-' for solid, ':' for dotted, '--' for dashed

  • linewidth

    As default, linewidth is 1. it can be smaller than 1, such as 0.5.

  • color

    'r' for red, 'b' for blue, 'g' for green, 'm' for magenta, 'c' for cyan

plt.plot(x, y, marker='^', markersize=12, linestyle=':', linewidth=2, color='m')
the default size of markersize is 6, and the default size of linewidth is 1.

Grid

By adding plt.grid(), you can show grid as shown below. 
import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-2, 4, 400)
y = x**2 - (1/4)*x**3

plt.plot(x, y)
plt.grid()
plt.show()

By adding plt.xtics(np.arrange(start, end, step)), you can adjust grid's interval. 
import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-2, 4, 400)
y = x**2 - (1/4)*x**3

plt.plot(x, y)
plt.grid()
plt.xticks(np.arange(-2, 4.5, 0.5))
plt.show()

Adding labels and title

Using Japanese Characters

Plot a bar chart

Save the graph (png,svg,bmp,jpg)

Create animations