Exploratory Data Analysis (EDA) Using Python | Python Data Analysis | Python Training | Edureka

This Edureka video on the 'Exploratory Data Analysis Using Python' will help you understand how we can use Python to perform EDA for significant insights and data-driven conclusions.

-----------------------------------------------------------------------------

#Edureka #PythonEdureka #EDA #exploratorydataanalysis #pythonprojects #pythonprogramming #pythontutorial #PythonTraining
-----------------------------------------------------------------------------
How it Works?
1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!
-----------------------------------------------------------------------------
About the course

Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing.

Edureka's Python Certification Training not only focuses on the fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands-on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problems that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross-Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds.

Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms.

Edureka’s Python course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master concepts like Python machine learning, scripts, and sequence.
-----------------------------------------------------------------------------
Why learn Python?

It's continued to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built-in debugger.

It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for commercial products, because of its OSI-approved open source license.

It has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that it is the " Next Big Thing " and a must for Professionals in the Data Analytics domain.
-----------------------------------------------------------------------------
Who Should Go For This Course?

Programmers, Developers, Technical Leads, Architects
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models
-----------------------------------------------------------------------------

[jeongyeonnime]

Thanks man, I always trust India guys whose explain about data scientist, it is really easy to understand. India guys really smart

[claudiusandika]

very clear and easy to understand.. thank you so much.. keep creating!

[mohamedanuarbinibrahim]

As someone who is new to data analysis, this is the best tutorial I've come across. Most times I get lost in trying to learn (googling) so many different functions and ways to acquire one basic insight. So it helps when I can refer to a systemic approach and explanation behind each process.

[Vintagetube]

My question is, does EDA process vary by the type of project you have, or should these steps be standard approach for every project? This is where EDA confuses me.

[dhrutibhanushali]

It is easy to understand 👍👍 keep creating like this❤️

[christianarnaudwandji]

so happy to discover your channel it brings me a lot thank you

[Abhi_interiors]

so nicely explained EDA, made it easily understandable .

[sp-francinagoh]

Thank you. Your explanation is very clear and easy to understand.

[GooseHandler]

Why do you explain things better than any lecturer I ever had?

[RaihanRisad]

6 months semester and here i am last night before submission! you just said what i need to hear. no extra 1 word. thanks

[MyName-urir]

thank you so much! it is very helpful :) you do an amazing job)

[ramsiyamuhammed]

how to resolve the null values, its very effective when you use dataset with nullvalues..thanks.its beautifully explained

[snehalbhartiya]

Replicating this made me happy. Thanks bhaijaan :D

[divyachandel]

you really explained this complete part very thoroughly and also very easily.. it was then fun to perform all this

[haripriyamenon]

Thank you Sir for that class. Excellent instructor and excellent teaching.

[sudheerraj]

Very informative..!!👍

Please try to provide dataset (csv) link in the description. So that we can download and perform the operations on them and learn more effectively using the dataset.

[ourutube]

Really the tutor explain ed in very simpler so those know the basic fundamentals can easily grasp the taught content..

[ashiradekunle]

I really love the way you explained ❣❣
Very understandable. Kudos to you💯
Please where can I get the data set

[grandmasgarden]

@edureka This is amazing and beautifully explained. Can I get the link to data pls.

[ritulgupta]

Great session! We need more session like this👏👏👏👏