• Post category:StudyBullet-5
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What you will learn

How to Download and Install Jupyter Notebook

Working with Numpy for Numerical Computing

Working with Array in Numpy

Management of data

Working with Pandas for data manipulations

Series and DataFrames

Reading files using Pandas

Data Visualization Using Matplotlib Library

Plotting Histogram, Bargraph, Scatter Plot, Boxplot, Pie Chart and many more

Description

If you are looking to make a career as a Data Scientist, Data Analyst, Machine Learning Expert using Python, then Numpy, Pandas and Matplotlib library is very important to learn in today’s scenario. In this course you will get a detailed explanation of topics and functions related to Numpy, pandas and matplotlib library.  After this course, you can able to do Data Manipulation and Data Visualization. You can say these tools are the ladder for the Data Scientist.

Important Feature of this course is as follows:

1. Every topic is covered practically.
2. Explained in very easy language.
3. Non-Programming background can also understand easily
4. Demonstrated in a simple way so that you can do the same by watching videos.

For Data Science aspirant, this is the best course. Nowadays Data Visualization is an important tool to take decisions in organizations. Here using matplotlib library you can easily visualize the data using histogram, bar chart, pie chart, scatter diagram and many more.

 

Topics Covered in Numpy:

1. Numpy Array

2. Numpy indexing and Slicing

3. Copy vs View

4. Numpy Array Shape, Reshape

5. Numpy Array Iterating

6. Numpy Array joining and Merging

7. Splitting , Searching and Sorting

8. Filtering

9. Random Module

Topics Covered in Pandas:

1. Series
2. DataFrame

3. Import Files/Dataset

4. Merging , Joining and Concatenating


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5. Analyzing Data

6. Cleaning Data

7. Data Manipulation

 

Topics Covered in Matplotlib:

1. Importance of Data Visualization

2. Type of Data Visualization

3. Concepts of matplotlib Library

4. Line Plotting

5. Histogram

6. Bar Plot

7. Scatter Plot

8. Pie Chart

9. Box Plot

10. Area Chart

 

English
language

Content

Introduction to Numpy , Pandas and Matplotlib

Introduction to Numpy Library
Introduction to Pandas
Introduction to Matplotlib

Anaconda for Jupyter Notebook and Google Colab

Download and Install Anaconda for Jupyter Notebook
Working with Google Colab

Numpy Part I – Basics

Creation and Initialization of Numpy Array
Exploring Numpy Array
Mathematical Operations using Numpy Array
Indexing and Slicing

Numpy Part 2-Advanced

Joining of Array
Array Splitting
Searching
Sorting
Random Module

Data Manipulation using Pandas Part I

Getting Started with Pandas
Importing Files/Dataset
Pandas Data Structure : Series
Pandas Data Structure : DataFrame

Data Manipulation using Pandas Part II

Merging , Joining and Concatenating
Analyzing Data
Cleaning Data
Data manipulation

Data Visualization Using Matplotlib Library

Importance of Data Visualization
Type of Data Visualization
Concepts of matplotlib Library
Line Plotting
Histogram Plotting
Bar Plotting
Scatter Plot
Pie Chart
Box Plot
Area Chart