Python for Data Analysis: Dealing With Dates

Channel:
United States DataDaft
Subscribers:
53,100
Published on ● Video Link: https://www.youtube.com/watch?v=fpf0p7-xdbo


Duration: 11:05
3,462 views
106

This video covers the basics of loading in and extracting features from date data using the Pandas library in Python.

Subscribe:
► https://www.youtube.com/c/DataDaft?sub_confirmation=1

This is lesson 17 of a 30-part introduction to the Python programming language for data analysis and predictive modeling. Link to the code notebook below:

Python for Data Analysis: Dealing With Dates
https://www.kaggle.com/hamelg/python-for-data-17-dealing-with-dates

Link to Pandas Date code information:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Period.strftime.html

Link to Pandas Time Series functionality documentation:
https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html


This guide does not assume any prior exposure to Python, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn Python.

I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can copy and edit each lesson so that you can follow along and run code yourself.

Introduction to Python Playlist:
https://www.youtube.com/playlist?list=PLiC1doDIe9rCYWmH9wIEYEXXaJ4KAi3jc

Link to the Python for Data Analysis written guide index page:
https://www.kaggle.com/hamelg/python-for-data-analysis-index .


⭐ Kite is a free AI-powered coding assistant that integrates with popular editors and IDEs to give you smart code completions and docs while you’re typing. It is a cool application of machine learning that can also help you code faster! Check it out here: https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=datadaft&utm_content=description-only



Other Videos By DataDaft


2020-08-25Python Programming Practice: LeetCode #70 -- Climbing Stairs
2020-08-14Top 15 MMA Fighters Over Time Ranked by Elo (1980-2020)
2020-08-11Python Programming Practice: LeetCode #2 -- Add Two Numbers
2020-08-11Python for Data Analysis: Confidence Intervals
2020-08-10Python for Data Analysis: Probability Distributions
2020-08-08Dragon Ball MAX Power Levels Over Time
2020-08-04Python for Data Analysis: Descriptive Statistics
2020-07-31Python for Data Analysis: Plotting With Pandas
2020-07-30Python for Data Analysis: Frequency Tables
2020-07-29Python for Data Analysis: Joining Data
2020-07-28Python for Data Analysis: Dealing With Dates
2020-07-27Python for Data Analysis: Preparing Numeric Data
2020-07-24Python for Data Analysis: Working With Text Data
2020-07-23Python for Data Analysis: Exploring and Cleaning Data
2020-07-22Python for Data Analysis: List Comprehensions
2020-07-21Python for Data Analysis: Functions
2020-07-21Python for Data Analysis: Control Flow (if, else, for, while)
2020-07-20Python for Data Analysis: Reading and Writing Data
2020-07-17Python for Data Analysis: Pandas Data Frames
2020-07-16Python for Data Analysis: Numpy Arrays
2020-07-15Python for Data Analysis: Dictionaries and Sets


Tags:
dates in python
dates in pandas
pandas date objects
pandas timestamp
timestamp python
python datetime
python date time
pandas date time
pandas datetime
timestamps in python
timestamps in pandas
date time formats
datetime formats
datetime data processing
date time data processing
datetime codes
date time codes
timestamp codes
parsing dates
reading dates
formatting dates
date formats
python dates
python timestamps
python
pandas
datetime
dates