– It can serve as a Pandas Encyclopedia covering all relevant Methods, Attributes and workflows for real life projects. From my own experience, working with and relying on outdated code can be painful. Pandas Library has experienced massive improvements in the last couple of months. – It is the most up-to-date course incorporating all recent Pandas updates (latest in Jan 2019). – It is the most relevant and comprehensive course on Pandas. This Python Intro is tailor-made and more than sufficient for Data Science purposes!Īs a Summary, if you primarily want to use Python for Data Science or as a replacement for Excel, then this course is a perfect match! In the Appendix of this course, you can find 4 hours of Python Basics. You require some Python Basics like Data Types, simple Operations/Operators, Lists and Numpy Arrays. In reality, all of these tasks require high proficiency in Pandas! Data Scientist typically spend up to 85% of their time with manipulating Data in Pandas. Pandas enables you to import, clean, join/merge/concatenate, manipulate and deeply understand your Data and finally prepare/process Data for further Statistical Analysis, Machine Learning or Data Presentation.
And the Pandas Library is the Heart of Python Data Science. Python is a great platform/environment for Data Science with powerful Tools for Science, Statistics and Machine Learning. It´s time to switch from Soap Box Cars (Spreadsheet Software like Excel) to High Tuned Racing Cars (Pandas)! New professions like Data Scientist are gaining ground with $100k+ salaries. The world is getting more and more Data-Driven. In the last part of this course (PART IV), you will learn how to import, handle and work with (financial) Time Series Data. This course is structured in four parts, beginning from Zero with all the Pandas Basics (PART I), and finally, testing your skills in a comprehensive Project Challenge that is frequently used in Data Science job applications / assessment centres (PART III). This course has one goal: Bringing your Data Handling skills to the next level to build your career in Data Science, Finance & co.
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