Data Analysis and Visualization using Python in Hindi

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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.

Instructors: Sachin Saini

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