Carnets - Jupyter
Research answer
What AppTrendKit can say about Carnets - Jupyter today
AppTrendKit estimates Carnets - Jupyter's App Store USD gross consumer spend at $198–$1.4K and downloads at 223–1.8K during 2026-08-09 to 2026-09-07 (30-day window) with storefront contributor coverage unavailable.
These are modeled public App Store estimates, not official publisher-reported figures. Storefront scope is stated only when persisted contributor lineage identifies it.
Performance intelligence
Observed trajectory and estimates
Store ranks are observations. Downloads and gross store consumer spend are AppTrendKit estimates and only appear when persisted evidence exists.
Estimated downloads · 30D
Modeled223–1.8K
Likely range · modeled estimate
Estimated App Store gross consumer spend · 30D
Modeled$198–$1.4K
Likely range · modeled estimate
Estimated downloads · 7D
Modeled223–1.8K
Likely range · modeled estimate
Estimated App Store gross consumer spend · 7D
Modeled$198–$1.4K
Likely range · modeled estimate
Evidence history
Collected daily performance
1 observed day · missing days are left blank
| Date | Downloads | Gross store revenue | Confidence |
|---|---|---|---|
| Sep 7, 2026 | 631 | $534 | 16% |
Rank history
Observed chart positions
Lower rank is better. Only collected observations are shown.
Coverage note
What the ranks mean
A missing rank is not treated as zero downloads or zero revenue. Apple chart feeds are bounded and may return censored or not-ranked observations outside the visible chart depth.
Read the methodStorefront mix
Top countries by estimated contribution
Country estimates are aggregated only after country-level predictions exist.
| Storefront | Revenue | Share | Downloads | Rank | Confidence |
|---|---|---|---|---|---|
| United KingdomGB | $534 | 100.0% | 631 | — | 1% |
Monetization
Observed store economics signals
These are listing and product observations. They are not company revenue, subscriber counts, or advertising revenue.
App details
Store metadata
- Version
- 1.9.1
- Released
- Apr 17, 2019
- Last updated
- Nov 26, 2025
- Content rating
- 17+
- Default storefront
- GB
Public IAP observations
Validated in-app purchase prices
Only persisted rows with an explicit public publication boundary are shown. Missing price, currency, country, or date values stay unknown.
Listing detail
What the store says
Jupyter notebooks are a powerful tool used in education and research. You can write small snippets of Python code and observe the result on screen, combine with paragraphs of text, using Markdown. Carnets provides a complete, stand-alone, implementation of Jupyter notebooks. Everything runs on your device, using the embedded Python interpreter; you do not need an internet connection. You can chose between Jupyter notebooks and the more advance Jupyterlab using Settings. Numpy, Sympy, Matplotlib, Pandas, lxml, bokeh, nbextensions (including ipywidgets) and many other packages are pre-installed. To see the full list of installed packages, type "%pip list" in a code window. You can add more packages using "%pip install packageName", but only if they are pure Python. If you need scipy, seaborn or scikit-learn, please use our other App, "Carnets - Jupyter (with scipy)". You can share your notebooks with other apps and also open notebooks or directories managed by other apps. Partial list of installed packages: astropy, babel, bokeh, cryptography, cvxopt, Fiona, geopandas, geopy, lxml, matplotlib, numpy, openCV, pandas, pillow, pyFFTW, pyproj, rasterio, regex, shapely, sympy, wordcloud.
Publisher websiteStore creative
Screenshots
Competitive set
Similar apps
Deterministic links to real stored apps matched by category, publisher, and comparable performance bands.
Carnets - Jupyter (with scipy)
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Python Editor - .py Editor
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Andromeda Corp Limited
Python3 IDE Fresh Edition
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Methodology and provenance
Read every number with its evidence
Metadata source: Apple iTunes Search API; observed Sep 7, 2026, 8:37 PM.
Rankings: collected chart positions from the listed storefront. Missing ranks are not zeros.
Economics: downloads and gross store consumer spend are estimated, not official Apple or publisher figures.
Model: No persisted model version.
Confidence: 1%; intervals widen when evidence or history is limited.
Last observation: Sep 7, 2026, 11:40 PM.
See how AppTrendKit separates observations, estimates, coverage, and confidence.
Open methodology