zalizedata/app-store-apps-charts-reviews-sample

App Store Apps, Charts & Review Sentiment — Free Sample

Free samples from a mobile-app intelligence dataset of 6,384 chart apps built entirely from Apple's official public APIs (iTunes RSS charts, Search & Lookup) plus Google Play public pages: app metadata, chart-rank snapshots, review-derived sentiment metrics, and a unique "Category Opportunity Index" that ranks every US App Store category by high demand × low rating — where the most underserved app markets are.

➡️ Full dataset & slices: https://data.zalize.com/datasets/app-store-apps-review-sentiment-dataset

Files

File	Rows	Description
data/apps_sample_500.csv	500	App metadata (name, developer, genre, rating, ratingCount, price, IAP, released/updated, size, content rating, …), stratified by store × country
data/chart_snapshots_sample_500.csv	500	Chart-rank snapshots (free / paid / top-grossing, per genre × country)
data/review_metrics_sample_500.csv	500	Per-app monthly review-derived metrics: language mix, rating histogram, sentiment mean/shares, complaint-topic tags — derived metrics only, no review texts
data/category_opportunity.csv	25	All 25 US App Store categories ranked by opportunity score (weighted avg rating, low-rated share, opportunity index)
data/apps_top_opportunity_sample.csv	100	Top-100 apps by opportunity index (demandScore / painScore / opportunityIndex per app)

Example insight (2026-08-01 snapshot)

Education is the biggest opportunity pocket: Schoology (130k ratings, 1.35★) scores opportunity index 84. "Forced-use" apps — school portals, dental insurance, cable TV streaming — combine huge installed bases with chronically low ratings.

Use cases

• ASO benchmarking & mobile market analysis
• Finding underserved app niches (indie devs, studios, VCs)
• App-traction signals for due diligence
• Sentiment-model evaluation against rating-paired aggregates

Provenance & compliance

• 100% public, login-free sources: Apple iTunes RSS/Search/Lookup APIs and Google Play public pages; no anti-bot circumvention.
• No review texts are redistributed here — derived metrics only; reviewer identities are never collected.
• Every row carries store/country/snapshot provenance fields; each app links back to its public App Store page.

Known limitations (disclosed honestly)

• Apple makes up the large majority of rows; not an Apple/Google-balanced corpus.
• Chart snapshots in this sample are from the initial runs, not a long daily time series.
• Sentiment scoring covers English reviews; complaint topics use keyword rules.

License

This sample: CC BY-NC 4.0 (non-commercial evaluation). Full dataset (incl. deeper history and category slices) under a tiered commercial license at data.zalize.com.

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Full dataset catalog: https://data.zalize.com — inquiries: data@zalize.com

Citation

In-text: Data: DataForge (data.zalize.com), app-store-apps-charts-reviews-sample, retrieved . Underlying sources: see datasheet.

@misc{dataforge_app_store_apps_charts_reviews_sample,
  author       = {{DataForge}},
  title        = {app-store-apps-charts-reviews-sample},
  year         = {2026},
  publisher    = {DataForge (Zalize)},
  howpublished = {\url{https://data.zalize.com/datasets/app-store-apps-charts-reviews-sample}},
  note         = {Collected from publicly accessible sources; see datasheet for upstream attribution}
}

Attribution required: "DataForge (data.zalize.com)" with a link back to https://data.zalize.com. Cite upstream providers per the datasheet. Full guidelines: https://data.zalize.com/citation.

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DataForge — The open web, forged into datasets. A Zalize product. Catalog: https://data.zalize.com · Open data: https://data.zalize.com/open-data · Kaggle · GitHub · Apify · Contact: data@zalize.com

Data files & schema (Dataset Viewer)

apps_sample_500 — 500 rows

Column	Type	Description
store	large_string
appId	large_string
bundleId	large_string
name	large_string
developer	large_string
developerId	large_string
primaryGenre	large_string
genres	large_string
rating	double
ratingCount	double
price	double
currency	large_string
free	bool
hasInAppPurchases	bool
installs	double
version	large_string
released	large_string
updated	large_string
sizeBytes	double
contentRating	large_string
descriptionLength	int64
screenshotCount	int64
supportedLanguages	double
country	large_string
snapshotDate	large_string
capturedAt	large_string

apps_top_opportunity_sample — 100 rows

Column	Type	Description
trackId	int64
bundleId	large_string
trackName	large_string
sellerName	large_string
primaryGenreId	int64
primaryGenreName	large_string
genreIds	large_string
genres	large_string
price	double
currency	large_string
averageUserRating	double
userRatingCount	int64
averageUserRatingForCurrentVersion	double
userRatingCountForCurrentVersion	int64
currentVersionReleaseDate	large_string
releaseDate	large_string
version	large_string
minimumOsVersion	double
fileSizeBytes	int64
contentAdvisoryRating	large_string
trackViewUrl	large_string
bestChartRank	int64
chartFeeds	large_string
demandScore	double
painScore	double
opportunityIndex	double

category_opportunity — 25 rows

Column	Type	Description
genreId	int64
genreName	large_string
appCount	int64
totalRatingCount	int64
weightedAvgRating	double
lowRatedShare	double
medianOpportunityIndex	double
maxOpportunityIndex	double
categoryOpportunityScore	double

chart_snapshots_sample_500 — 500 rows

Column	Type	Description
store	large_string
appId	int64
bundleId	large_string
name	large_string
chart	large_string
genreId	int64
genre	large_string
country	large_string
rank	int64
snapshotDate	large_string
capturedAt	large_string

review_metrics_sample_500 — 500 rows

Column	Type	Description
store	large_string
appId	large_string
country	large_string
reviewsAnalyzed	int64
primaryLang	large_string
englishShare	double
langCounts	large_string
ratingCount1	int64
ratingCount2	int64
ratingCount3	int64
ratingCount4	int64
ratingCount5	int64
ratingShare1	double
ratingShare2	double
ratingShare3	double
ratingShare4	double
ratingShare5	double
sentimentMean	double
sentimentPosShare	double
sentimentNeuShare	double
sentimentNegShare	double
sentimentReviewsScored	int64
avgRating30D	double
reviewCount30D	int64
avgRating90D	double
reviewCount90D	int64
negativeReviewCount	int64
complaintShare_crash_bug	double
complaintShare_ads	double
complaintShare_billing_subscription	double
complaintShare_login_account	double
complaintShare_performance	double
complaintShare_ux_design	double
complaintShare_support	double
complaintShare_privacy_permissions	double
topKeywords	large_string

Usage

from datasets import load_dataset

ds = load_dataset("zalizedata/app-store-apps-charts-reviews-sample", "apps_sample_500", split="train")
print(ds[0])

Available configs: apps_sample_500, apps_top_opportunity_sample, category_opportunity, chart_snapshots_sample_500, review_metrics_sample_500.

Related datasets

More DataForge open datasets in Apps & E-commerce:

• App Review Complaint Benchmarks — Category Baselines + App Complaint Profiles
• Paid-Validated App Niche Index — Apps Proving Willingness-to-Pay
• High-Demand Low-Rating App Category Opportunity Scan
• shopify-products-catalog-sample

Full catalog (25 datasets): https://data.zalize.com/open-data · all HF repos: https://huggingface.co/zalizedata