Crash course: Data analytics in Python using Pandas (Udemy.com)
Let's get to grips with the Python Pandas library for data analytics / analysis
Created by: Kieran Keene
Last updated September 2023
What you will learn
- Perform data analysis with the Pandas library
- Learn about dataframes and how to conduct data analysis in Python
- Understand how to handle missing values in your data
- Understand how to handle & clean up messy data
How it compares
Against the other 388 rated Udemy courses in Python on CourseDuck:
- Rating4.6 out of 5higher than 70% of them
- Reviews593#228 of 389 by number of reviews
- Length1 hourshorter than 97% of them
- Last updatedSeptember 2023more recently than 50% of them
Course Description
Unleash Data Magic with Python Pandas:
Ready to supercharge your data skills? Dive into our Python Pandas course, where data becomes your playground and insights are your treasure.
Why Choose This Course?
Elevate Your Data Game: Python Pandas is the secret sauce behind cutting-edge data analysis. Become a data virtuoso in just a few clicks!
Unlock Hidden Insights: I'll teach you to cleanse, manipulate, and analyze data like a pro. Say goodbye to messy datasets, and hello to crystal-clear conclusions!
Real-World Experience: Dive into captivating, real-world projects that put your newfound skills to the test. Learn by doing and conquer any data challenge.
What's In Store For You?
Data Transformation Mastery: Harness Python Pandas to transform raw data into invaluable insights. You'll wonder how you ever lived without it!
Data Wizardry: Learn the art of data ingestion, where you'll effortlessly extract, clean, and prepare data for analysis. No more data headaches!
Data Brilliance: By the course's end, you'll have the power to wield Python and Pandas like a seasoned pro, extracting untold gems of wisdom from your own datasets.
Join me and embark on a journey where data isn't just numbers; it's your passport to making data-driven decisions with confidence. Get ready to chart your course in the data-driven world. Enroll now and let your data adventures begin!
You will need to have Python installed and the Pandas library installed - which you can do using 'pip install pandas'.
Instructor Details
- 4.6 Rating
593 Reviews
Kieran Keene
Hey guys! I am a data engineer by trade and specialize in Python, SQL, Spark, Hive, MongoDB and more. I've come on Udemy to try and make simple, short crash courses into these technologies as I personally find the longer courses too drawn out & I often lose interest. The idea is to keep it short and sharp!
For loads of advanced Spark, Python & Big Data topics, please visit my website (the button on this page will take you there) - where I talk about scaling up to enterprise grade solutions.
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Reviews
By Gilberto Gonzalez on 10/17/2024
This was a great introduction to pandas. It was straightforward, simple, and fun to follow along with short videos. The content was detailed and well explained, allowing the end user to pause and soak it in. I really enjoyed this course!
By Anthony Morgan on 1/25/2023
An excellent introduction to pandas, which will teach you enough to be confident with some basic data analysis. All the concepts were explained in clear, easily understandable terms and broken down step by step. I'd recommend it for anyone who knows a little Python and wants to start getting to grips with pandas.
By Jason Poole on 7/12/2022
The author of this course did a great job of reviewing the code as he implements it. Most instructors will type the code, execute it, then move on, so that was a refreshing and effective change in teaching tactics. Good job!
By John on 12/29/2021
This was a really good course in teaching me the fundamentals of pandas as an introduction with clear practical examples. Just what I needed. Thank you.
By Glynda Finister on 3/25/2021
I loved this course. It was worth every cent. In fact knowing what I know now, I would have paid more. It was super easy thorough and not the least bit boring. I learned a lot and will definitely take more of this Instructor's courses. A co-worker told me it took him a year to learn Pandas, so I've been scared to learn it. Now, I learnt Pandas in 1 hour - yah!! Excellent course!! What I loved most is that you repeated the steps. Most Udemy Instructors feel that if they tell you once that's enough. I didn't have to go back and rewind. Again, I loved this course. Thank you,
By Sanil Pandit on 1/22/2021
Very short and concise course which will get you on your way to learning pandas and data analytics. I own a Data analytics Udemy course which is 20+ hrs long. I have not gotten around to starting it due to the length. This one is 1 hr course, which gives you a small taste of the delicacies that await you. I have already bought the book recommended here and started reading up and analysing data from work. Thank you.
By Jyothi S Bhandari on 1/9/2021
Yes, definately a Awesome match. I would like to learn more as it was precise and compact. I would love more videos like this, it would be great if you provide such practice videos for people like us who want to practice data science or guide us where we can get short challenges as you provided in the video. I would rate the person 5/5
By Celine Hernia on 11/3/2020
This is a well-crafted course. I've been watching courses on Pandas with longer timeframes and had trouble digesting the info. This course made learning Pandas much easier. Will definitely watch the other courses the instructor has to offer. Highly recommended! :)
By Arulmurugan R on 6/25/2020
This course is a very good place to start with Pandas. The examples given were very clear and understandable. The author has done a very good job of making sure that the course would be easy to understand for beginners in Pandas.
By Ang Gali on 6/7/2020
Yes, but the sample.csv file has been corrupted/changed so its now original.xls. Not sure how that happened. I had to put the data into a text file and load into excel, but other people might not know how to do the same.
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 92 / 100





