Learn Numpy Matplotlib Tutorial to learn basics of Matplotlib. Learn various types of matplotlib charts like histogram, bar chart, scatter plot, box plot etc

Python is a really useful tool for data science implementations. We prefer it because of the wide range of libraries and packages available in Python. NumPy along with Matplotlib is a fundamental feature of Python. It helps to ease data interpretation and visualization. We implement the plotting functions in NumPy with the use of Matplotlib.

NumPy Matplotlib Tutorial

Let us firstly see what is Matplotlib?

We use Matplotlib to ease the analysis of statistical data. Matplotlib is a visualization tool and hence provides a visual analysis of the data.

Matplotlib is an effective replacement for the MatLab tool. It contains all the requirements for replacements. It is also effective when put to use with other GUI toolkits. We can use it alongside Tkinter and pyqt packages.

We can access matplotlib by importing its subpackage pyplot.

from matplotlib import pyplot as plt

The pyplot() function is very useful for demonstrating 2-D array plots.

import numpy as np
from matplotlib import pyplot as plt

x = np.arange(10)
y = 2 * x + 4

plt.xlabel("x axis")
plt.ylabel("y axis")
plt.plot(x,y)
plt.show()

Output

#numpy #matplotlib #python