Gain insights into Python for MATLAB users, covering syntax, data structures, file handling, and data visualization. Learn about NumPy, pandas, Matplotlib, Seaborn, and practice through hands-on challenges.

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Python is a versatile programming language with many open-source packages for different applications. Even scientists using MATLAB for complex tasks are shifting toward Python. This course focuses on MATLAB users learning Python.

First, you’ll be introduced to MATLAB and Python’s key differences and similarities. You’ll learn the fundamentals of Python syntax and data types and structures, particularly lists, dictionaries, sets, and tuples. You’ll learn the control flow of programs, functions, and file handling. You’ll learn about NumPy, pandas, Matplotlib, and Seaborn packages. You’ll learn different Python operators and how to store, manipulate, and visualize data. You’ll also get hands-on experience with three practice challenges at the end of the course. The course also discusses the Zen of Python.

After completing this course, you can program in Python and embark on any advanced Python, data science, or machine learning course.

Introduction to Python for MATLAB Users

Date,Product,Sales,Profit,Region
2023-01-01,Product_A,1500,300,North
2023-01-01,Product_B,2000,500,South
2023-01-02,Product_A,1600,350,East
2023-01-02,Product_C,1200,200,West
2023-01-03,Product_B,1800,450,North
2023-01-03,Product_C,1400,250,South
2023-01-04,Product_A,1700,370,East
2023-01-04,Product_B,1900,480,West
2023-01-05,Product_C,1300,220,North
2023-01-05,Product_A,1800,400,South

# Write import command

# read data using pandas

# print data


# Write import command
import pandas as pd

# read data using pandas
sales_data = pd.read_csv('Sales-Data.csv')

# print data
print(sales_data.shape)
print(sales_data.head())

# group by Product and calculate total sales

# import command
from matplotlib import pyplot as plt

# create figure


# create bar plot

# add title and labels

# show plot


# group by Product and calculate total sales
total_sales = sales_data.groupby('Product')['Sales'].sum()

# import command
from matplotlib import pyplot as plt

# create figure
fig = plt.figure(figsize=(10, 10), dpi=300)

# create bar plot
total_sales.plot(kind='bar')

# add title and labels
plt.title("Total Sales by Product")
plt.xlabel("Product")
plt.ylabel("Total Sales")

# show plot
plt.show()

Test your data manipulation skills with the sales dataset in pandas and Matplotlib.

Introduction to the Course

Universe of the Two Worlds

Basic Data Types and Operations

Control Flow

Functions

File Handling

Data Visualization

Practice Challenges

Conclusion

Appendix

Challenge 1: Sales Data Analysis

Task 1: Load the dataset

Task 2: Plot the data