This is the best way to get into data science or machine learning. You should learn Numpy and pandas and matplotlib, which are the best libraries for that.
What you’ll learn
Mastering Numpy, Pandas and MatplotLib-Data Manipulation Tool
- Download and set up Jupyter Notebook.
- Working with Numpy to do Numerical Computing, as shown
- In Numpy, you can work with arrays.
- Keeping track of data.
- Working with Pandas to change data.
- This word is more relevant: series and data frames.
- Using Pandas, I can read files.
- Use Matplotlib Library to Make Data Visualizations.
- Assembling a Histogram, Bargraph and many other types of graphs and charts. Boxplot and Pie Chart are also shown.
- No Programming Knowledge Is Needed
If you want to be a Data Scientist, Data Analyst, or Machine Learning Expert with Python, you need to learn Numpy, Pandas, and Matplotlib. In today’s world, these libraries are very important. In this course, you will learn about topics and functions that are important to the Numpy, pandas, and matplotlib library. If you finish this course, you will be able to manipulate and show off data, as well as other things. People who work with data can say that these tools are the steps on their way up the ladder.
This is a very important thing about this class:
- Every subject is covered in depth.
- Simple words were used to explain what was going on.
- Non-programming people can also learn quickly.
- Do this in a simple way so that you can do the same thing by watching videos.
In terms of Data Science, this is the best course. There are a lot of good ways to make decisions in businesses today, and one of them is Data Visualization. Here, you can use the matplotlib library to quickly show the data in a variety of ways, such as a histogram, bar chart, pie chart, scatter diagram, and many more.
In Numpy, these are the topics:
- Array of Numpy
- In Numpy, you can index things and slice things, too.
- Copy vs. View
- Shape and reshape Numpy arrays with these tools
- Repeating a Numpy Array
- Numpy Arrays can be joined and merged.
- splitting, looking for and sorting
Who this course is for:
- Students, teachers, and other people who want to work in Data Science, Machine Learning, Data Analysis, and Data Visualization should read this.