Matplotlib is highly customizable. Can be used to create any type of plot or chart. It is compatible, with Python scripts, Python and IPython shells Jupyter notebooks, web application servers, and various graphical user interface toolkits. To leverage its features effectively understanding the figure and axes objects is essential; the figure object represents the window or page where content is displayed while the axes object defines the area where data is visualized.
Example: Creating a complex figure with multiple subplots.
import matplotlib.pyplot as plt import numpy as np x = np.linspace(0, 10, 100) # Creating a figure and a grid of subplots fig, axs = plt.subplots(2, 2, figsize=(10, 10)) # Plotting different mathematical functions on each subplot axs[0, 0].plot(x, np.sin(x)) axs[0, 0].set_title('Sine Function') axs[0, 1].plot(x, np.cos(x), 'tab:orange') axs[0, 1].set_title('Cosine Function') axs[1, 0].plot(x, np.tan(x), 'tab:green') axs[1, 0].set_title('Tangent Function') axs[1, 0].set_ylim(-10, 10) # Limiting y-axis values due to asymptotes axs[1, 1].plot(x, np.exp(x), 'tab:red') axs[1, 1].set_title('Exponential Function') axs[1, 1].set_yscale('log') # Setting y-axis to logarithmic scale plt.tight_layout() plt.show() |
This example shows how to make a figure using a 2x2 grid of axis objects, or subplots. Each subplot displays a different mathematical function along with names and adjustments such as y-axis limitations, color changes, and logarithmic scaling.
Matplotlib is highly customizable. Can be used to create any type of plot or chart. It is compatible, with Python scripts, Python and IPython shells Jupyter notebooks, web application servers, and various graphical user interface toolkits. To leverage its features effectively understanding the figure and axes objects is essential; the figure object represents the window or page where content is displayed while the axes object defines the area where data is visualized.
Example: Creating a complex figure with multiple subplots.
import matplotlib.pyplot as plt import numpy as np x = np.linspace(0, 10, 100) # Creating a figure and a grid of subplots fig, axs = plt.subplots(2, 2, figsize=(10, 10)) # Plotting different mathematical functions on each subplot axs[0, 0].plot(x, np.sin(x)) axs[0, 0].set_title('Sine Function') axs[0, 1].plot(x, np.cos(x), 'tab:orange') axs[0, 1].set_title('Cosine Function') axs[1, 0].plot(x, np.tan(x), 'tab:green') axs[1, 0].set_title('Tangent Function') axs[1, 0].set_ylim(-10, 10) # Limiting y-axis values due to asymptotes axs[1, 1].plot(x, np.exp(x), 'tab:red') axs[1, 1].set_title('Exponential Function') axs[1, 1].set_yscale('log') # Setting y-axis to logarithmic scale plt.tight_layout() plt.show() |
This example shows how to make a figure using a 2x2 grid of axis objects, or subplots. Each subplot displays a different mathematical function along with names and adjustments such as y-axis limitations, color changes, and logarithmic scaling.
Python is commonly used for developing websites and software, task automation, data analysis, and data visualisation. Since it's relatively easy to learn, Python has been adopted by many non-programmers, such as accountants and scientists, for a variety of everyday tasks, like organising finances.
Learning Curve: Python is generally considered easier to learn for beginners due to its simplicity, while Java is more complex but provides a deeper understanding of how programming works.
The point is that Java is more complicated to learn than Python. It doesn't matter the order. You will have to do some things in Java that you don't in Python. The general programming skills you learn from using either language will transfer to another.
Read on for tips on how to maximize your learning. In general, it takes around two to six months to learn the fundamentals of Python. But you can learn enough to write your first short program in a matter of minutes. Developing mastery of Python's vast array of libraries can take months or years.
6 Top Tips for Learning Python
The following is a step-by-step guide for beginners interested in learning Python using Windows.
Best YouTube Channels to Learn Python
Write your first Python programStart by writing a simple Python program, such as a classic "Hello, World!" script. This process will help you understand the syntax and structure of Python code.
The average salary for Python Developer is ₹5,55,000 per year in the India. The average additional cash compensation for a Python Developer is within a range from ₹3,000 - ₹1,20,000.
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