Network of The Witcher | Relationship Extraction & Network Analysis with Spacy & NetworkX

Hey data nerds 👋, in this video we made an attempt to extract relationships between The Witcher's characters from the books. We also did some graph analyses (centrality measures and community detection) and visualization using NetworkX and Pyvis. The analyses are still quite preliminary and I might have glossed over some details, but hopefully, this is a bit interesting and you learned something from it 🤓. This is the second project in the Witcher project series where we will analyze the relationships between characters. The next episode of this series will be all about network graph visualization 😁. I hope you enjoyed this video and any questions and thoughts are welcome! Thank you for watching 🙌🏽

👩🏻‍💻 COURSES & RESOURCES
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🙋🏻‍♀️ LET'S CONNECT!
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🔑 TIMESTAMPS
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0:00 - Intro & objectives
0:47 - Installing packages & project setup
2:07 - Plan for the project 🧭
3:34 - Get data & process data
5:13 - Read in character names
7:06 - Get character list per sentence
9:47 - Create relationship df
14:22 - Network graph visualization & analysis
18:40 - Centrality measures
20:26 - Community detection
21:54 - Characters' importance over time
25:25 - Where to learn graph analytics
26:18 - Some announcement 😉

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#networkanalysis #Datanerd #DataAnalysis #datascience #ThuVu #dataanalytics

[Thuvu]

The video many of you were looking forward to! 🤓 It was really fun to make. I hope you enjoyed it and found it useful for your own projects! 😊

[nervous]

We NEED more of this kind of projects!! I love this series so much... So please, we need the finale of this project...

[LukeBarousse]

Heck yeah! Loving where you are taking this video series, Thu!!! 🙌🏼🙌🏼

[dragonboy]

I thought I love your videos, but now you made a video about The Witcher's universe?
Aw...! I didn't think I could love them even more...

[youngzproduction]

Graph algorithms are quite useful as well as beautiful in their own right.
I’m glad there are some people using them.
More importantly, use them with a fun-to-do use case.

Thanks for your effort.

[uhdgygl]

3:48 Where was "Season of Storms"? 😂😂

Seriously though, I really loved this vid! It's such a great way to learn - doing something fun.

[santosluiza]

Your content is great! I found your video because I was lost in my data analysis class when it came to the module of Network Analysis. I'm going to recommend you to all my classmates. Thank you for putting so much thought in this!

[juanrassis]

Seriously, Data Science is just mind blowing! Specially when you consider all the real-world applications for those resources.

[KanaanGM]

this was incredible!
following thru took me 3 hours, i didn't know data science could be this fun, please make more!!

[yd_]

Coming from the life sciences, I’ve only used cytoscape for network related stuff. It’s rest api isn’t very good, so it’s a bit difficult to automate, but it has more features than networkx imo. Great tutorial. I did something similar in a side project a while ago for Japanese novels. Was a lot of fun.

[dipanshuhaldar]

Hi I loved this video and lot of it is familier with my current project on static graphs on player interactions playing pc/console games. However, my current research takes it a noch higher on the same lines but with dynamic graphs. Currently I amtrying to implement the same with networkX + dynetX, with a keen eye at pathpyG as well. I would love to see a future video on dynamic graphs!

[edniraf]

Omg, amazing video!!! I am starting with graph theory and visualization and this video has very important information for my project. Special thanks for the hints on extra material. You teach very well! Keep up the excellent work😊

[vinni_codes]

I was looking forward to this video. I'm loving the series of video. I can't wait to put this into practice.

[a.]

Wow, the best explanation of the DS project on YT I have seen! 👏🏻Thank you for educating us!

[hris]

Love the flow of this video. Amazing step by step. Thanks Vu.

[davidr]

Wow Thu, just found your channel and I'm hooked! Thank you!!

[Davidkiania]

Thu, I absolutely love this video series and lost count of how many times I have watched it for tips & tricks. Thank you 🙏 can’t wait for the computation.

[princeganer]

Hey Thu Vu, this stuff is really very cool!! Watching what amazing things we can do using Data Science excites me. Thanks for sharing it with us.😀

[Zaycancode]

This project is unbelievably fucking cool

[alecd]

Love your videos. Is it possible to make a video regarding to the data cleaning, such as how to treat outliers, etc? thanks