Using Pymol to create Porcupine plot for PCA analysis (Modevector.py)
Published August 6, 2013
At a glance
Views
5,746
Likes
16
Comments
19
Performance vs. channel
All-time outlier score
Engagement rate
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About
A simple method to create Porcupine plot for PCA analysis using Modevector.py python scripts Requirement: 1. extreme1.pdb; 2. PML script, 3. modevector.py(python code) Please download the python script from http://www.pymolwiki.org/index.php/Modevectors The PML script goes like this: #----------------START-----------…
- Published
- August 6, 2013
- Made for kids
- No
More features coming
We're working on new analytics and tools. Stay tuned.
How Using Pymol to create Porcupine plot for PCA analysis (Modevector.py) is doing
It has 5.74K views in total. It ranks #13,544,254 among tracked YouTube videos by views.
Key facts about Using Pymol to create Porcupine plot for PCA analysis (Modevector.py)
- Total views
- 5.74K
- Total likes
- 16
- Total comments
- 19
- Published
- August 6, 2013
- Global rank by views
- #13,544,254
Frequently asked questions
How many views does Using Pymol to create Porcupine plot for PCA analysis (Modevector.py) have?
Using Pymol to create Porcupine plot for PCA analysis (Modevector.py) has 5,746 views, 16 likes and 19 comments, ranking #13,544,254 among tracked YouTube videos by views.
How accurate are these YouTube video analytics?
View, like, and comment counts come from YouTube's public API and refresh regularly. Growth and revenue figures are estimates built from tracked historical data, so they can differ slightly from what the creator sees privately in YouTube Studio.
What is the outlier score?
How this video's views compare to the channel's usual Shorts or long-form video. A 2x score means double the usual views for that channel, 0.5x means half.
What is engagement rate and how is it calculated?
Likes and comments per view, compared to this channel's typical engagement rate — shown as above or below what's usual for the channel.
How is the revenue estimate calculated?
It's a rough public estimate based on a $0.7–$2.0 CPM (revenue per 1,000 views) applied to view count — not actual creator earnings, which depend on ad rates, audience geography, and monetization settings YouTube doesn't expose publicly.
Is this YouTube video analytics checker free?
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