Python Tutorial: Dates in Python
Key Takeaways
The video tutorial covers working with dates in Python, specifically creating date objects, extracting information, and performing basic operations using the datetime package.
Full Transcript
hi my name is max rone I will be your instructor for this course on working with dates and times in Python dates are everywhere in data science stock prices go up and down experiments begin and end people are born politicians take votes and on and on all these events happen at a particular point in time knowing how to analyze data over time is a core science skill this course is divided into four chapters first chapter will be about working with dates and calendars in Chapter two we will add time into the mix and combine dates and times in Chapter three we'll tackle one of the toughest parts of working with time time zones and daylight saving and finally in Chapter four we'll connect what we've learned about working with dates and times to explore how pandas can make answering even complex questions about dates much easier let's begin python has a special date class called date which you will use to represent dates a date like a string or a number or an umpire Ray has special rules for creating it and methods for working with it in this lesson we're going to discuss creating dates and extracting some basic information out of them why do we need a special date class let's have a look to understand how dates work in this chapter you're going to be exploring 67 years of hurricane landfalls in the US state of florida to underscore hurricanes is a list with the dates of two hurricanes represented as strings the last 2016 hurricane on October 7 2016 and the 1st 2017 hurricane on June 21st 2017 represented in the u.s. style with the month than the day than the year suppose you want to do something interesting with these dates how would you figure out how many days had elapsed between them how would you check that they were ordered from earliest to latest how do you know which day of the week each was doing these things manually would be challenging but Python makes all of them easy by the end of this chapter you don't know how to do each of these things yourself to create a date object we start by importing the date class the collection of date and time related classes are stored in the date time package we create a date using the date function here we've created dates corresponding to the two hurricanes now as Python date objects the inputs to date are the Year month and day the first date is October 7th 2016 and the second date is June 21st 2017 the order is easy to remember it goes from biggest to smallest year month day later in this chapter you'll create dates directly from lists of strings but in this lesson you're going to stick to creating dates by hand or using lists have already created dates you can access individual components of a date using the dates attributes you can access the year of the date using the Year attribute like so and the result is 2016 similarly you can access the month and day using the month and day attributes like so you can also ask Python to do more complicated work here we call the weekday method on a date and see that the weekday is for what is forming here Python counts weekdays from 0 starting on Monday 1 is Tuesday 2 is Wednesday and so on up to 6 being a Sunday this date was a Friday in the next few exercises you'll implement what you've seen in this video to see how much you can already do
Original Description
Want to learn more? Take the full course at https://learn.datacamp.com/courses/working-with-dates-and-times-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work.
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Hi! My name is Max Shron, I will be your instructor for this course on working with dates and times in Python.
Dates are everywhere in data science. Stock prices go up and down, experiments begin and end, people are born, politicians take votes, and on and on. All these events happen at a particular point in time. Knowing how to analyze data over time is a core data science skill.
This course is divided into four chapters. The first chapter will be about working with dates and calendars. In chapter two, we will add time into the mix, and combine dates and times. In chapter three, we'll tackle one of the toughest parts of working with time: time zones and Daylight Saving. And finally, in chapter four, we'll connect what we've learned about working with dates and times to explore how Pandas can make answering even complex questions about dates much easier.
Let's begin. Python has a special date class, called "date", which you will use to represent dates. A date, like a string, or a number, or a numpy array, has special rules for creating it and methods for working with it. In this lesson, we're going to discuss creating dates and extracting some basic information out of them.
Why do we need a special date class? Let's have a look.
To understand how dates work, in this chapter you're going to be exploring 67 years of Hurricane landfalls in the U.S. state of Florida.
two_hurricanes is a list with the dates of two hurricanes represented as strings: the last 2016 hurricane (on October 7th, 2016) and the first 2017 hurricane (on June 21st, 2017). The dates are represented in the U.S. style, with the month, then the day, then the year.
Suppose you want to do something interesting with these dates. How would you figure out how many days
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