Mastering Numpy,Pandas and MatplotLib-Data Manipulation Tool

Learn Numpy, pandas and matplotlib library which is the path for Data Science, Machine Learning, Data Analysis

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.

What you’ll 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.

Course Content

  • Introduction to Numpy , Pandas and Matplotlib –> 3 lectures • 12min.
  • Anaconda for Jupyter Notebook and Google Colab –> 2 lectures • 15min.
  • Numpy Part I – Basics –> 4 lectures • 45min.
  • Numpy Part 2-Advanced –> 5 lectures • 48min.
  • Data Manipulation using Pandas Part I –> 4 lectures • 1hr 1min.
  • Data Manipulation using Pandas Part II –> 4 lectures • 1hr 12min.
  • Data Visualization Using Matplotlib Library –> 10 lectures • 1hr 17min.

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Requirements

  • No Programming Experiance Required.

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

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

 

 

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