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Python Data Science Basics With Numpy, Pandas, and Matplotlib
Python Data Science Essentials: Learn the basics of Python data types, structures, and the NumPy & Pandas libraries.
Lectures -64
Resources -1
Duration -6 hours
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Course Description
This is a beginner-friendly and expert-led course that covers concepts of Python Data Science. This includes the basics of Python data types and structures, as well as the most important Data Science libraries: NumPy and Pandas. The course is self-paced, so you can learn conveniently at your own speed.
Python Data Science Basics With Numpy, Pandas & Matplotlib Overview
Python Data Science Basics With Numpy, Pandas, and Matplotlib is a project-based course that starts with an introduction to Python, its applications, and its libraries. It will guide you to install Python and Anaconda, a platform that makes it easy to install and manage Python libraries.
The curriculum also involves guidance on how to use Jupyter Notebook, an interactive environment for writing and running Python code. We will then learn about the basic Python data types: strings, numbers, lists, tuples, and dictionaries.
You will also learn about NumPy and Pandas libraries. NumPy is a library for working with arrays, while Pandas is a library for working with tabular data. You will learn to use these libraries in order to perform operations such as data cleaning, analysis, and visualization. This course is ideal for Data science enthusiasts who want to begin their careers.
Here is an outline of the course curriculum:
Introduction to Python
Python for data science
Installing Python and Anaconda
Using Jupyter Notebook
Basic Python data types
Strings
Numbers
Lists
Tuples
Dictionaries
NumPy
Creating and manipulating NumPy arrays
Performing operations on NumPy arrays
Pandas
Creating and manipulating Pandas DataFrames
Cleaning and analyzing data with Pandas
Goals
What will you learn in this course:
Essential Python data types and data structure basics with libraries like NumPy and Pandas for Data Science or Machine Learning beginners.
Basic Python data types and operations
Basic data structures in Python: lists, tuples, and sets
Python dictionaries
The NumPy library: creating, manipulating, and analyzing NumPy arrays.
The Pandas library: creating, manipulating, and analyzing Pandas DataFrames.
Importing and exporting data from CSV and JSON files.
Data wrangling with Pandas: handling missing data, grouping data, and aggregating data.
Data visualization with Matplotlib: creating graphs and plots.
Visualizing data with Pandas
Prerequisites
What are the prerequisites for this course?
A decent configuration computer and the willingness to lay the cornerstone for your big data journey.
Curriculum
Check out the detailed breakdown of what’s inside the course
Course Introduction and Table of Contents
1 Lectures
- Course Introduction and Table of Contents 09:29 09:29
Introduction to Python, Pandas and Numpy
1 Lectures
System and Environment Setup
1 Lectures
Python Strings
2 Lectures
Python Numbers and Operators
2 Lectures
Python Lists
5 Lectures
Tuples in Python
1 Lectures
Sets in Python
2 Lectures
Python Dictionary
2 Lectures
NumPy Library Introduction
3 Lectures
NumPy Array Operations and Indexing
2 Lectures
NumPy Multi-Dimensional Arrayss
3 Lectures
Introduction to Pandas Series
1 Lectures
Introduction to Pandas Dataframes
1 Lectures
Pandas Dataframe conversion and drop
3 Lectures
Pandas Dataframe summary and selection
3 Lectures
Pandas Missing Data Management and Sorting
2 Lectures
Pandas Hierarchical-Multi Indexing
1 Lectures
Pandas CSV File Read Write
2 Lectures
Pandas JSON File Read Write
1 Lectures
Pandas Concatenation Merging and Joining
3 Lectures
Pandas Stacking and Pivoting
2 Lectures
Pandas Duplicate Data Management
1 Lectures
Pandas Mapping
1 Lectures
Pandas Groupby
1 Lectures
Pandas Aggregation
1 Lectures
Pandas Binning or Bucketing
1 Lectures
Pandas Re-index and Rename
2 Lectures
Pandas Replace Values
1 Lectures
Pandas Dataframe Metrics
1 Lectures
Pandas Random Permutation
1 Lectures
Pandas Excel sheet Import
1 Lectures
Pandas Condition Selection and Lambda Function
2 Lectures
Pandas Ranks Min Max
1 Lectures
Pandas Cross Tabulation
1 Lectures
Graphs and plots using Matplotlib
2 Lectures
Matplotlib Histograms
1 Lectures
Source Code
1 Lectures
Instructor Details
Abhilash Nelson
I am a pioneering, talented and security-oriented Android/iOS Mobile and PHP/Python Web Developer Application Developer offering more than eight years’ overall IT experience which involves designing, implementing, integrating, testing and supporting impact-full web and mobile applications.
I am a Post Graduate Masters Degree holder in Computer Science and Engineering.
My experience with PHP/Python Programming is an added advantage for server based Android and iOS Client Applications.
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