App Store Top Charts Data: Daily Ranks for 10 Storefronts

A row is one app in one chart on one day. The 22 fields are the same for the overall feed and the category chart pages, so every storefront loads into one table. Everything is as Apple publishes it on the day of the read.

Collected by Proxies.sx Data Works from the App Store charts Apple publishes. Proxies.sx is not affiliated with Apple or the developers listed. Ten storefronts are read: United States (us), Mexico (mx), Argentina (ar), Chile (cl), Colombia (co), Spain (es), Netherlands (nl), Italy (it), Romania (ro) and France (fr). Apple keys the storefront by the URL, so each storefront's charts are what a user in that country sees.

Two surfaces are read for each storefront. The first is the feed Apple publishes through its Marketing Tools, which gives the overall top 100 free and top 100 paid apps with the app and developer names and Apple's own update time, but no price, rating or bundle id. The second is the chart page on apps.apple.com for each category, including All Apps, Games and the Games sub-genres, which gives the top 50 free and the top 50 paid apps with the bundle id, developer name, price label, rating and the abbreviated rating count. The chart pages are read for iPhone.

The run starts at 05:30 UTC every day. It reads the feed first and then the chart pages, under a fixed request budget. A chart already stored for the day is not read again, so a run that stops early is completed by the next one. Collection started on 20 October 2026, and there is no earlier history.

Because the same charts are read every day, each row carries its own comparison with the previous collected day. The rank change is the earlier rank minus today's, so a positive number means the app climbed and a negative one that it fell. An app that was not in the chart on the previous collected day is marked as a new entry. An app that was in the chart and is not any more gets a row of its own, marked dropped, with no rank. The first collected day of a chart has nothing to compare with, so its change fields are empty, and so are the rows of the first run.

Read the changes within one chart. The overall feed and a category chart rank different sets of apps over different depths, and a move from rank 48 to rank 52 in a 50-entry chart shows up as a drop and a later re-entry, not as a small change.

The charts are Apple's ranking, as published at the time of the read. Apple does not say how it ranks apps, and the feed does not publish download or revenue figures, so this feed holds none and estimates none. The rating count on a chart page is the abbreviated string Apple shows, such as 11M, not an exact number. The feed carries no price or rating at all, so those fields are empty on its rows. Genre names are shown in the storefront's language; the genre id is the same everywhere.

Developer names are the names Apple shows on the storefront. Some developers publish under a personal name, and the feed keeps that name as published and nothing else about them. No review text, reviewer names, descriptions, screenshots or artwork are collected, and no app pages are read.

Google Play is not offered. Its ranked charts are served only by an endpoint that play.google.com/robots.txt disallows, and no page its robots.txt allows returns them, so the collector has no Play adapter. Per-app facts from robots-allowed Play detail pages are a different product, and not a chart.

Which apps entered or left the top 50 of a category in a storefront this week, and where a named competitor moved. How the paid chart of a category differs between Mexico, Spain and the United States, and what price labels the apps in it carry. How long a new release held a top-10 place in its category after launch. Each of these is a filter on one table: country, chart, day and rank, with the app id to follow one app across storefronts and days.

What it does not answer is why a rank moved, or how many downloads it took. For that, the chart data is one input beside your own install and spend figures.

Sign in to Data Works in the Proxies.sx dashboard and pick the dataset. The storefront needs an account. You get a sample first, you approve it and a rate, and only then does anything bill. Each finished run can be downloaded as a CSV file with the header row below.

Say which storefronts and categories you need when you ask. The sample is cut from the charts already stored.

Sign in to Data Works in the Proxies.sx dashboard to request a free sample. The storefront needs an account, and you approve the sample and a rate before anything bills. To collect from other sites, see custom Data Works projects.