Did you manage to get it running? You must use a console where the WK open framework is loaded, as in https://www.wanikani.com/*.
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Yeah, that’s what I did 
Thanks for the help nevertheless 
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Well I absolutely don’t understand how to paste something into the javascript console… any ideas? I have open framework running and all…
Edit: ok it’s doing it, I’m a hacker now
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Accuracy:
Apprentice 1: 98.70%
Apprentice 2: 99.56%
Apprentice 3: 99.19%
Apprentice 4: 99.10%
Guru 1: 96.96%
Guru 2: 95.53%
Master: 93.26%
Enlightened: 91.81%
I think that the apprentice is so high because I’m super used to having the first SRS interval be 1 day due to my Anki deck…
Accuracy:
Apprentice 1: 96.79%
Apprentice 2: 98.12%
Apprentice 3: 98.54%
Apprentice 4: 97.23%
Guru 1: 94.51%
Guru 2: 93.25%
Master: 91.70%
Enlightened: 91.18%
How are all of the numbers lower than my stats on the color-coded table on wkstats?
Accuracy:
Apprentice 1: 79.97%
Apprentice 2: 89.87%
Apprentice 3: 90.19%
Apprentice 4: 90.33%
Guru 1: 84.99%
Guru 2: 84.90%
Master: 86.18%
Enlightened: 87.81%
Apparently I’m really bad at stuff I’ve just learned…
Accuracy:
Apprentice 1: 78.44%
Apprentice 2: 97.24%
Apprentice 3: 98.26%
Apprentice 4: 97.63%
Guru 1: 96.26%
Guru 2: 94.92%
Master: 94.13%
Enlightened: 97.39%
On wkstats, reading and meaning are counted independently.
wkstats: correct meaning + incorrect reading == 50%
code above: correct meaning + incorrect reading == 0% <-- like Wanikani
I’m going to add a new section on the new version of wkstats that also calculates the combined way. And it will show accuracy by srs level. And maybe a graph with accuracy over time.
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I still haven’t had any master/enlightened reviews so 
Accuracy:
Apprentice 1: 91.70%
Apprentice 2: 96.35%
Apprentice 3: 97.39%
Apprentice 4: 95.16%
Guru 1: 93.63%
Guru 2: 98.91%
Master: NaN%
Enlightened: NaN%
Hmm, why is apprentice 1 my lowest? Maybe I should read the lessons after all.
Also, it’s interesting to see the dip in accuracy for guru 2 and master before it goes back up. I.e. if you make it to enlightened, you are mostly golden 
(or black, without the proper script badum tss)
Maybe, as @jprspereira said, review intervals are a bit too far apart around there.
But meh, it’s still reasonable
Apprentice 1: 96.69%
Apprentice 2: 99.05%
Apprentice 3: 99.23%
Apprentice 4: 99.23%
Guru 1: 98.23%
Guru 2: 97.26%
Master: 97.14%
Enlightened: 98.26%
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I really loved this, thank you! No surprises here, I’m reckless with the reviews at Apprentice 1 until the mnemonic sticks (honestly I thought it would be lower but there are a lot of easy vocab/radicals propping that number up). As the SRS intervals increase I get a bit more forgetful.
Apprentice 1: 73.98%
Apprentice 2: 95.49%
Apprentice 3: 96.66%
Apprentice 4: 96.94%
Guru 1: 93.35%
Guru 2: 92.71%
Master: 91.42%
Enlightened: NaN%
Level 15 stats: my memory fades over time 
Accuracy:
Apprentice 1: 96.17%
Apprentice 2: 97.47%
Apprentice 3: 96.26%
Apprentice 4: 95.68%
Guru 1: 91.85%
Guru 2: 92.63%
Master: 89.08%
Enlightened: 89.71%
Hanging on to that 99%. It’d probably be a humble brag to bemoan how many of those reading failures are due to a typo since i do most of my reviews on my phone. Never thought I’d be annoyed by u, i and o being right next to each other…
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Oof.
Accuracy:
Apprentice 1: 72.56%
Apprentice 2: 84.65%
Apprentice 3: 87.72%
Apprentice 4: 89.92%
Guru 1: 85.74%
Guru 2: 85.26%
Master: 84.38%
Enlightened: —
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Wa! That level-by-level accuracy is what I’ve been wanting to make. I’m going to have to look at that code when I have more time to see how it works.
Accuracy:
Apprentice 1: 81.75%
Apprentice 2: 96.03%
Apprentice 3: 96.65%
Apprentice 4: 96.06%
Guru 1: 93.09%
Guru 2: 92.20%
Master: 95.54%
Enlightened: —
Looks like the guru intervals might just be giving my memory a bit more stretch than the others, AND that I could stand to have a speed dial to shorten them all a bit. I’d like them all to be about 90.
Still low level though.
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Misc. unimportant data nerdery that I’ll eventually get around to trying, probably using @rfindley 's excellent script above as a base:
Of all items that have ever been failed:
- where are they now? (by SRS level)
- where are they now? (by next scheduled review date)
Of all items that have been failed and not subsequently passed (current fail status)
- where are they now? (by SRS level)
- where are they now? (by next review date)
List of all learned kanji, ordered by most failed (personal hardest kanji list)
In [another thread], @Chopper asked if there was a script to view accuracy by time of day.
So… here’s a Javascript snippet that calculates it:
Click to open code
wkof.include('Apiv2');
wkof.ready('Apiv2').then(fetch_data).then(process_data);
function fetch_data() {
return wkof.Apiv2.fetch_endpoint('/reviews');
}
function process_data(json) {
let reviews = json.data;
let hourCount = new Array(12).fill(0);
let hourCorrect = new Array(12).fill(0);
reviews.forEach(review => {
let hour = new Date(review.data.created_at).getHours();
let bin = Math.floor(hour/2);
hourCount[bin]++;
if (review.data.ending_srs_stage > review.data.starting_srs_stage) {
hourCorrect[bin]++;
}
});
let output = ['Accuracy:'];
for (let i=0; i<12; i++) {
let time = ('0'+(i*2)).slice(-2)+':00 - '+('0'+((i+1)*2)).slice(-2)+':00';
if (hourCount[i] > 0) {
output.push(' '+time+': '+(hourCorrect[i] / hourCount[i] * 100).toFixed(2)+'%');
} else {
output.push(' '+time+': ---');
}
}
console.log(output.join('\n'));
}
If you have Open Framework installed, paste the following code in your Javascript console (press F12 and click on the Console tab):
You’ll get something like this:
Accuracy:
00:00 - 02:00: 62.22%
02:00 - 04:00: ---
04:00 - 06:00: ---
06:00 - 08:00: 95.24%
08:00 - 10:00: 68.32%
10:00 - 12:00: 69.28%
12:00 - 14:00: 68.22%
14:00 - 16:00: 67.92%
16:00 - 18:00: 67.24%
18:00 - 20:00: 49.93%
20:00 - 22:00: 65.35%
22:00 - 24:00: 61.85%
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