Perform data analysis with the Pandas library Learn about dataframes and how to…
In the real-world, data is anything but clean, which is why Python libraries like Pandas are so valuable.Now get Udemy Coupon 100% Off, all expire in few hours Hurry. you should always try to take Online Classes or Online Courses rather than Udemy Data Manipulation in Python: A Pandas Crash Course Download, as we update lots of resources every now and then.
If data manipulation is setting your data analysis workflow behind then this course is the key to taking your power back.
Own your data, don’t let your data own you!
When data manipulation and preparation accounts for up to 80% of your work as a data scientist, learning data munging techniques that take raw data to a final product for analysis as efficiently as possible is essential for success.
Data analysis with Python library Pandas makes it easier for you to achieve better results, increase your productivity, spend more time problem-solving and less time data-wrangling, and communicate your insights more effectively.
This course prepares you to do just that!
With Pandas DataFrame, prepare to learn advanced data manipulation, preparation, sorting, blending, and data cleaning approaches to turn chaotic bits of data into a final pre-analysis product. This is exactly why Pandas is the most popular Python library in data science and why data scientists at Google, Facebook, JP Morgan, and nearly every other major company that analyzes data use Pandas.
If you want to learn how to efficiently utilize Pandas to manipulate, transform, pivot, stack, merge and aggregate your data for preparation of visualization, statistical analysis, or machine learning, then this course is for you.
Here’s what you can expect when you enrolled with your instructor, Ph.D. Samuel Hinton:
Performing data analysis with Python’s Pandas library can help you do a lot, but it does have its downsides. And this course helps you beat them head-on:
1. Pandas has a steep learning curve: As you dive deeper into the Pandas library, the learning slope becomes steeper and steeper. This course guides beginners and intermediate users smoothly into every aspect of Pandas.
2. Inadequate documentation: Without proper documentation, it’s difficult to learn a new library. When it comes to advanced functions, Pandas documentation is rarely helpful. This course helps you grasp advanced Pandas techniques easily and saves you time in searching for help.
After this course, you will feel comfortable delving into complex and heterogeneous datasets knowing with absolute confidence that you can produce a useful result for the next stage of data analysis.
Here’s a closer look at the curriculum:
Lastly, this course is packed with a cheatsheet and practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice with Pandas too.