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Dates and times in Pandas

Pandas has extensive facilities for parsing, converting, retrieving, and extracting time-and-date data. Learn all about them in this webinar.

What you should know

Course Content

Course length

3 hours

Number of lessons

Training materials

1 Jupyter notebook

Coding exercises

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About the Course

It’s no surprise that Pandas has become a superstar in the world of data analytics: With it, we can easily load, analyze, and plot all sorts of numeric and textual data.

Many experienced Pandas users aren’t aware that it can also work with dates and times — making it particularly powerful for creating and analyze time-series data.

If you work with data that involves dates and times, then this class will help you to take advantage of the many ways that Pandas can make your life easier.

This course assumes that you have a basic familiarity with Pandas: Reading and writing CSV file, dtypes, indexes, sorting, and grouping.

The class will take place live on November 6th, and will include numerous hands-on exercises, as well as plenty of chances to ask questions.

If you work with real-world data that includes dates and times, then you won’t want to miss this live course!

What you’ll learn

Different date-related dtypes
Reading datetime data from a CSV file
Retrieving data from datetime columns
Calculating and comparing with timedelta (“interval”) data
Handling different date-time formats
Grouping with datetime data
Indexes with datetime values
Resampling

Instructor

This course, like all others on LernerPython.com, is taught by Reuven Lerner.

Pricing

100% Money Back Guarantee

I’m a one-person company dedicatedto improving your career via Python and related technologies. If you haven’t gotten value from any of my courses, then just tell me — and I’ll refund your money.

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$40

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