Playlist Duration

Playlist · Corey Schafer

Pandas Tutorials

by Corey Schafer · 11 videos

Total watch time

5h 19m

at 1× speed · exactly 5 hours, 19 minutes, 11 seconds at 1×

At an hour a day you'd finish in 6 days

The shape of the course

Each column is one video, to scale

23:01
33:35
17:27
23:04
40:03
16:55
15:40
49:06
31:54
35:41
32:45

WatchedTo watch

Compare Open on YouTube JSON

Next time, skip the copying: change youtube.com to playlistduration.com in any playlist, video or channel address and it opens here. Or see the total on YouTube itself, with our extension for Chrome, Firefox or Edge.

Your plan

Plan to finish

About 6 days at an hour a day

Pick a daily pace and the days you'll watch. Ticked videos are skipped.

Days

At one hour a day, every day, this playlist takes about 6 days. Turn on JavaScript to plan around your week.

Videos (11)

5h 19m in total · tick what you've watched

Tick videos you've watched — progress is saved in this browser. Titles open on YouTube in a new tab.

Videos to
Watched Leave out of the total
1 Python Pandas Tutorial (Part 1): Getting Started with Data Analysis - Installation and Loading Data 23:01 2020-01-09
2 Python Pandas Tutorial (Part 2): DataFrame and Series Basics - Selecting Rows and Columns 33:35 2020-01-10
3 Python Pandas Tutorial (Part 3): Indexes - How to Set, Reset, and Use Indexes 17:27 2020-01-13
4 Python Pandas Tutorial (Part 4): Filtering - Using Conditionals to Filter Rows and Columns 23:04 2020-01-17
5 Python Pandas Tutorial (Part 5): Updating Rows and Columns - Modifying Data Within DataFrames 40:03 2020-01-24
6 Python Pandas Tutorial (Part 6): Add/Remove Rows and Columns From DataFrames 16:55 2020-02-01
7 Python Pandas Tutorial (Part 7): Sorting Data 15:40 2020-02-06
8 Python Pandas Tutorial (Part 8): Grouping and Aggregating - Analyzing and Exploring Your Data 49:06 2020-02-14
9 Python Pandas Tutorial (Part 9): Cleaning Data - Casting Datatypes and Handling Missing Values 31:54 2020-02-24
10 Python Pandas Tutorial (Part 10): Working with Dates and Time Series Data 35:41 2020-03-17
11 Python Pandas Tutorial (Part 11): Reading/Writing Data to Different Sources - Excel, JSON, SQL, Etc 32:45 2020-04-01
For your README

Embed a badge

Show the watch time in a README or course description — it links back here and updates itself

Watch time: 5h 19m · 11 videos

Markdown
[![Watch time: 5h 19m · 11 videos](https://playlistduration.com/badge/playlist/PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS.svg)](https://playlistduration.com/playlist/PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS)
HTML
<a href="https://playlistduration.com/playlist/PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS"><img src="https://playlistduration.com/badge/playlist/PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS.svg" alt="Watch time: 5h 19m · 11 videos" width="203" height="20"></a>

Add ?speed=1.5 to the image URL for the time at that speed, ?label=Course to change the left text, or ?style=flat-square for square corners.

Want the numbers themselves? GET https://playlistduration.com/api/v1/playlist/PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS returns them as JSON — free, no key. API docs →

Data from the YouTube Data API as of 2026-11-09 (cached). Private or deleted videos are excluded from totals.