Data Analysis using NumPy and Pandas
Analyze data quickly and easily with Python's powerful numpy and pandas libraries
Updated on Sep, 2023
Language - English
Course Description
If you've spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you!
Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language.
Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets -- analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more!
I call it "Excel on steroids"!
Over the course of more than 19 hours, I'll take you step-by-step through Pandas, from installation to visualization! We'll cover hundreds of different methods, attributes, features, and functionalities packed away inside this awesome library. We'll dive into tons of different datasets, short and long, broken and pristine, to demonstrate the incredible versatility and efficiency of this package.
Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas!
Who this course is for:
- Data analysts and business analysts
- Excel users looking to learn a more powerful software for data analysis
Goals
What will you learn in this course:
- NumPy Introduction
- Python Numpy Array
- Indexing & Slicing
- Statistical Functions, Operators & Random Numbers
- Introduction Series & DataFrame
- Date Range & Inspecting Data
- Indexing & Slicing on DataFrame
- Concatination & Descriptive Statistics
- Merging DataFrames
- Working with Text Data
- Function Application
Prerequisites
What are the prerequisites for this course?
- Basic experience with the Python programming language
Curriculum
Check out the detailed breakdown of what’s inside the course
Data Analysis using NumPy and Pandas
19 Lectures
-
Introduction
01:09
01:09
-
NumPy Introduction
34:09
34:09
-
Python Numpy Array
22:32
22:32
-
Indexing & Slicing - 1
19:29
19:29
-
Indexing & Slicing - 2
30:21
30:21
-
Statistical Functions, Operators & Random Numbers
20:12
20:12
-
Introduction Series & DataFrame
41:00
41:00
-
Date Range & Inspecting Data
29:36
29:36
-
Indexing & Slicing on DataFrame - 1
30:13
30:13
-
Loc & iloc
31:18
31:18
-
Indexing & Slicing on DataFrame - 2
18:24
18:24
-
Concatenation & Descriptive Statistics
31:54
31:54
-
Merging DataFrames
29:28
29:28
-
Working with Text Data
18:40
18:40
-
Function Application & Loading data in Python
40:33
40:33
-
Loading Data from CSV, Excel & URL
21:24
21:24
-
Data Visualization using Pandas
19:33
19:33
-
What is Data Science
30:42
30:42
-
What is Machine Learning
25:06
25:06
Instructor Details
DATAhill Solutions Srinivas Reddy
Data ScientistMr. Srinivas Reddy is Founder & MD of DATAhill Solutions
He is Research Scholar (Ph.D) on Artificial Intelligence & Machine Learning
He Received Masters of Technology in Computer Science & Engineering from JNTU, MICROSOFT Certified Professional, IBM Certified Professional & Certified from IIT Kanpur & IIT Ropar.
Having 10+ Years of Experience in Software & Training.
His Experience includes Managing, Data Processing, Data Cleaning, Predicting and Analyzing of Large volume of Business Data.
Expertise in Data Science, Data Analytics, Machine Learning, Deep Learning, Artificial Intelligence, Python, R, Weka, Data Management & BI Technologies.
Having Patents and Publications in Various Fields such as Artificial Intelligence, Machine Learning and Data Science Technologies.
Professionally, He is Data Science Management Consultant with over 7+ years of Experience in Finance, Retail, Transport and other Industries.
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