8 measurements spanning 19 days, net -11. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 3,113–3,128 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
25 Aug 2026, 12:39
3,115
-5
22 Aug 2026, 14:08
3,120
+4
19 Aug 2026, 00:45
3,116
-4
16 Aug 2026, 06:22
3,120
+2
12 Aug 2026, 09:25
3,118
-5
9 Aug 2026, 00:54
3,123
-3
6 Aug 2026, 04:51
3,126
no change
6 Aug 2026, 03:06
3,126
first reading
Engagement
9 posts held, back to 21 June 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
26.9%
avg views ÷ 3,115 subscribers
Avg views / post
839
1 post measured
Reaction rate
1.55%
reactions ÷ views · ER floor
Posts in window
1
of 9 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 28 July 2026
Posts held
9 (21 June 2026 – 28 July 2026)
Views total
839
Reactions total
13
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 23:56 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Video runtime
1m 43s
Average length
1m 43s
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
92 reactions across 8 posts, in 3 distinct kinds. The most used accounts for 93.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
86
93.5%
💔
5
5.43%
🤔
1
1.09%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 8 of the 9 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 92reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 9 most recent posts we hold, published 21 June 2026 to 28 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Я уже писала, что 7 августа стартует мой дистанционный курс «Визуализация данных», на котором можно попрактиковать применение алгоритма Δλ на учебных кейсах.
Этот курс будет особенным! Помимо вебинаров по теории, я проведу две встречи, посвящённых применению ИИ-инструментов для визуализации данных. Покажу, как использовать современные модели внутри Даталенс и как создавать отдельностоящие html-дашборды на базе библи…
Как обещала, публикую полную версию интерактивной объяснялки, которая иллюстрирует последовательность шагов алгоритма Δλ и их связь между собой.
🍒 https://datalaboratory.ru/delta-lyambda/
На мой взгляд, такой формат позволяет увидеть и понять моменты, которые сложно передать текстом. Если у вас остались вопросы по алгоритму, пишите в комментариях. Буду рада ответить.
Ну и кстати, уже в августе я провожу очередной поток дистанционного курса по визуализации, где слушатели не просто знакомятся с алгоритмом, но и учатся применять его на практике под моим чутким руководством. Вот фрагменты отзывов участников апрельского курса.
Сегодня до вечера можно записаться со скидкой 30%. Приходите, «будет весело» 😌
https://bureau.ru/courses/data/
Подвожу итоги двухлетней серии советов об алгоритме Δλ. Собрала все теоретические материалы в одной заметке:
https://bureau.ru/soviet/20260708/
В следующий раз всё то же самое покажу в виде интерактивной объяснялочки — не пропустите «вишенку на торте» 🍒
Показываю в советах, как визуализирую свою ипотеку — выплаченную и оставшуюся части. И снова с собранным в Курсоре интерактивным прототипом. Суммы условны, м² и проценты настоящие.
https://bureau.ru/soviet/20260624/
Интересно, вы видите, где на этой визуализации сработал подход алгоритма Δλ? Напишите в комментариях, буду рада почитать ваши мысли.
Помимо этих сокровищ, у меня есть россыпь самоцветов попроще. Каждый год я прохожусь по всевозможным спискам лучших визуализаций и выбираю те, которые мне хочется отложить в свою шкатулку. Каждый год я публикую эти примеры с короткими пояснениями, чем именно они хороши. Именно к этим подборкам я обращаюсь, когда ищу примеры для советов или новых лекций.
2025 — https://bureau.ru/soviet/20260107/
2024 — https://bureau…
Шкатулка любимых визуализаций
Самый яркий пример вандер-момента в моей жизни — это знакомство с книгами Эдварда Тафти. Я училась на четвёртом курсе университета, уже успела разочароваться в «научном» академическом пути и жила с открытым вопросом, куда плыть дальше — где не будет скучно моему натренированному на олимпиадные задачки уму. (Отчётливо помню, что именно это, а не стабильность или высокий доход, было главн…
❤8
Signed Таня Мисютина
Showing the 9 most recent of 9 posts we hold for @datalaboratory. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 25 August 2026 — this
entry's latest reading, not the date you are reading this.
“Лаборатория данных” (@datalaboratory), 3,115 subscribers as measured 25 August 2026. Telegram Register, tgregister.com/channel/datalaboratory.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.
