Free Udemy Coupon Data Analysis and Visualization using Python in Hindi

Data Analysis and Visualization using Python in Hindi

In this course, you'll get very well knowledge of Numpy, Pandas, and Matplotlib with a project. You will learn all the essential things which are needed in data science and data analysis.

By the end of this course you will learn:


  • What is Numpy and how to use it?

  • You'll learn how to download install Anaconda.

  • Learn about 1D, 2D, 3D arrays, how to create them, accessing them, changing them.

  • Learn how Numpy array is better than a simple List with code.

  • Learn axis in 2D array and 3D array which is too confusing to understand.

  • Learn various Mathematical operations that you can perform on Numpy arrays like Addition, Subtraction, Multiplication, Division, Power, sin, cos, tan, Natural log, log base2, log base 10, etc.

  • Learn Various Numpy functions like vertical stacking, horizontal stacking, mean, sum, variance, standard deviation.

  • Learn Indexing and Slicing.

  • We'll do an exercise in which we learn to solve different Numpy related questions.

2. Pandas

  • What is Pandas and how it is useful in data analysis?

  • Learn about the Series Data Structure, create them with a tuple, list, and dictionary.

  • Querying a Series

  • Learn Indexing and Slicing using loc and iloc in 1D, 2D, and 3D arrays.

  • Learn the DataFrame Data Structure, create them, analyze them, accessing them, etc

  • Learn Reading data from files.

  • Learn Indexing DataFrames.

  • Learn to handle Missing Values

3. Matplotlib

  • Learn what is Matplotlib, why, and how to use it.

  • Learn the Line plot and all operation on that plot like adding and changing the style of markers, legend, shape, face color, etc.

  • Setting x and y-axis and use your data on the x and y-axis.

  • Learn Subplots.

  • Learn Pie Plot.

  • Learn the Scatter Plot.

  • Learn Bar plot

4. Data Analysis Project

In this project, you'll be able to learn:

  • how to handle new data.

  • how to read datasets.

  • how to merge two datasets.

  • Removing unnecessary rows and columns.

  • Arrange dataset according to your need.

  • Plot the datasets.

  • Barplot with subplots.

  • Barplot with multiple plots in a single diagram.

  • ETC.

With Python code notebooks, you will be excellently prepared for a future in data science.

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