Python Pandas Tutorial | Data Analysis with Python Pandas | Python Training | Edureka

///Python Pandas Tutorial | Data Analysis with Python Pandas | Python Training | Edureka

Python Pandas Tutorial | Data Analysis with Python Pandas | Python Training | Edureka

FavoriteLoadingAdd to favorites

🔥Edureka Python Certification Training:
This Edureka video on ‘Python Pandas Tutorial’ will help you get started with Python Pandas Library for various applications including Data analysis. Following are the topics discussed:

Introduction to Pandas
DataFrames and Series
How To View Data?
Selecting Data
Handling Missing Data
Pandas Operations
Merge, Group, Reshape Data
Time Series And Categoricals
Plotting Using Pandas

🔹Python Tutorial Playlist:
🔹Blog Series:

Do subscribe to our channel and hit the bell icon to never miss an update from us in the future:
——————————————————————————-
Instagram:
Facebook:
Twitter:
LinkedIn:
Castbox:
SlideShare:

#Edureka #PythonEdureka #pythonPandas #pandas #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 24×7 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

Edureka’s Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you:

1. Master the Basic and Advanced Concepts of Python
2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs
3. Master the Concepts of Sequences and File operations
4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions and using modules in Python
5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
7. Master the concepts of MapReduce in Hadoop
8. Learn to write Complex MapReduce programs
9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python
10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics
11. Master the concepts of Web scraping in Python
12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience
——————————————————————————-
Why learn Python?

Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source licence.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next “Big Thing” and a must for Professionals in the Data Analytics domain.
——————————————————————————-
Who should go for python?

The Python Programming Certification Course is a good fit for the below professionals:
Programmers, Developers, Technical Leads, Architects, Freshers
Data Scientists, Data Analysts
Statisticians and Analysts
Business Analysts
Project Managers
Business Intelligence Managers
——————————————————————————-
For more information, Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775

source

By |2020-07-31T08:39:49+00:00July 31st, 2020|Python Video Tutorials|17 Comments

17 Comments

  1. edureka! July 31, 2020 at 8:39 am - Reply

    Got a question on the topic? Share it in the comment section below. Please drop a comment if you need the data-sets and codes discussed in this video. For Edureka Python Data Science Course curriculum, Visit our Website: http://bit.ly/2OpzQWw Use code "YOUTUBE20" to get Flat 20% off on this training.

  2. vijay vjay July 31, 2020 at 8:39 am - Reply

    yes

  3. Nandini Dodiya July 31, 2020 at 8:39 am - Reply

    Thank you sir for providing great tutorials

  4. Yatendra Jain July 31, 2020 at 8:39 am - Reply

    Really nice explanation ! Can i get the source code ! thanks 🙂

  5. Pradeep kumar Kumar July 31, 2020 at 8:39 am - Reply

    Yes

  6. Ragul VPS July 31, 2020 at 8:39 am - Reply

    What are list of all frequencies in pandas in date_range??

  7. Agent Norse July 31, 2020 at 8:39 am - Reply

    Thanks for the Pandas tutorial

  8. Benjamen Aremu July 31, 2020 at 8:39 am - Reply

    Great video. I need the dataset and the source codes if possible. Thanks.

  9. Raju Ravi July 31, 2020 at 8:39 am - Reply

    More useful…now I cleared about the basics of pandas…thank you

  10. Arun Poudel July 31, 2020 at 8:39 am - Reply

    Yes

  11. Tamil Navi July 31, 2020 at 8:39 am - Reply

    Because I tried in one code in which when one sound is played then another sound is stopped…
    How to play two sounds in same time

  12. yes

  13. nkosinathi ndhlovu July 31, 2020 at 8:39 am - Reply

    Yes

  14. Ruby Pinu July 31, 2020 at 8:39 am - Reply

    Yes

  15. Twin Sisters Heba and Hafsa July 31, 2020 at 8:39 am - Reply

    Good content

  16. Santosh Roy July 31, 2020 at 8:39 am - Reply

    Yes

  17. Twin Sisters Heba and Hafsa July 31, 2020 at 8:39 am - Reply

    Very informative 👍👍👍

Leave A Comment

*