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What you'll learn?
- 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.
Course Overview
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!
Whether you're a new data analyst or have spent years (*cough* too long *cough*) in Excel, Data Analysis with pandas and Python offers you an incredible introduction to one of the most powerful data toolkits available today!
Pre-requisites
- Basic experience with the Python programming language.
Target Audience
- Data analysts and business analysts.
- Excel users looking to learn a more powerful software for data analysis.
Curriculum 19 Lectures 08:15:43
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Section 1 : Introduction.
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Section 2 : NumPy Introduction.
- Lecture 1 :
- NumPy Introduction.
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Section 3 : Python Numpy Array.
- Lecture 1 :
- Python Numpy Array.
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Section 4 : Indexing & Slicing - 1
- Lecture 1 :
- Indexing & Slicing - 1
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Section 5 : Indexing & Slicing - 2
- Lecture 1 :
- Indexing & Slicing - 2
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Section 6 : Statistical Functions, Operators & Random Numbers.
- Lecture 1 :
- Statistical Functions, Operators & Random Numbers.
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Section 7 : Introduction Series & DataFrame.
- Lecture 1 :
- Introduction Series & DataFrame.
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Section 8 : Date Range & Inspecting Data.
- Lecture 1 :
- Date Range & Inspecting Data.
-
Section 9 : Indexing & Slicing on DataFrame - 1
- Lecture 1 :
- Indexing & Slicing on DataFrame - 1
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Section 10 : loc & iloc.
- Lecture 1 :
- loc & iloc.
-
Section 11 : Indexing & Slicing on DataFrame - 2
- Lecture 1 :
- Indexing & Slicing on DataFrame - 2
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Section 12 : Concatenation & Descriptive Statistics.
- Lecture 1 :
- Concatenation & Descriptive Statistics.
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Section 13 : Merging DataFrames.
- Lecture 1 :
- Merging DataFrames.
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Section 14 : Working with Text Data.
- Lecture 1 :
- Working with Text Data.
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Section 15 : Function Application & Loading data in Python.
- Lecture 1 :
- Function Application & Loading data in Python.
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Section 16 : Loading Data from CSV, Excel & URL.
- Lecture 1 :
- Loading Data from CSV, Excel & URL.
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Section 17 : Data Visualization using Pandas.
- Lecture 1 :
- Data Visualization using Pandas.
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Section 18 : What is Data Science.
- Lecture 1 :
- What is Data Science.
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Section 19 : What is Machine Learning.
- Lecture 1 :
- What is Machine Learning.
Our learners work at
Frequently Asked Questions
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It's simple. When you sign up, you'll immediately have unlimited viewing of thousands of expert courses, paths to guide your learning, tools to measure your skills and hands-on resources like exercise files. There’s no limit on what you can learn and you can cancel at any time. -
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Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic. -
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Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on. -
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Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want. -
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Brilliant question? Isn't it? You can access the courses on any device like PC, Mobile, Tablet & even on a smart tv. For mobile & a tablet you can download the Learnfly android or an iOS app. If mobile app is not available in your country, you can access the course directly by visting our website, its fully mobile friendly. -
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Instructor
399664 Course Views
7 Courses
Having 10+ Years of Experience in Software Industry which includes Development, Support & Training.
My Experience Includes Managing, Processing, Predicting and Analyzing of Large volume of Business Data.
Expertise in Data Management, BI Technologies & Data Science with Data Analytics, Machine Learning, Deep Learning & Artificial Intelligence using R Programming, Python Programming, WEKA and EXCEL.
Having publications and patents in various fields such as machine learning, data security, and data science technologies.
I received my Masters of Technology in Computer Science & Engineering from JNTU.
Professionally, I am a Data Science management consultant with over 8 years of experience in finance, retail, transport and other industries.
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