Five ways to explore every play
Search for a Spotify history analyzer and you’ll find everything from Wrapped lookalikes to Jupyter notebooks. They differ in two ways that matter: how much of your history they can see, and what they let you ask. Here are the five approaches, compared honestly.
· 5 min read
First: what can an analyzer actually see?
Every Spotify history analyzer (or analyser, if you’re in the UK) gets its data one of two ways, and that decides most of what it can tell you.
Signing in with Spotify
Spotify’s API lets an app read your top artists and tracks over a few fixed time ranges, plus your last 50 plays. It doesn’t give play counts or your history from five years ago. Apps that rely on it can show what you’re into now, and they start tracking from the day you connect.
Your Extended Streaming History
The export is a log of every play since you opened your account: what played, when, for how long, whether you skipped it, on which device and in which country. It’s free to request from Spotify’s privacy page and usually arrives within a few days (our export guide shows how). Anything that talks about your all-time listening is reading this file.
The five approaches
1. Spotify’s own recaps
Wrapped, the yearly Your Top Songs playlists and, in 2026, the limited-time Your Party of the Year(s) anniversary recap. Zero effort and made to share. They’re also fixed: you get the cards Spotify picked, mostly for one year at a time.
2. Stats apps that sign in with Spotify
Apps like stats.fm show your top lists, track new listening as it happens and let you compare with friends. Out of the box they only see what the API offers. For older history, the better ones let you import your export, sometimes as a paid feature, so check their current plans. What you see is the charts and lists the app was designed around.
3. Open-source viewers and dashboards
Search GitHub for “Spotify extended streaming history” and you’ll find dozens of projects that load the JSON files and draw charts. Some run entirely in your browser, so the data never leaves your computer. They’re free and often clever. They also answer the questions their author thought of, quality varies, and some need a Python setup or Spotify developer keys.
4. A spreadsheet or a Python script
The most flexible option, and the most work. The files are JSON, so a spreadsheet needs them converted first (Excel’s Power Query can do it). A long-time listener’s export can hold 300,000 plays across 20 files, which makes spreadsheet formulas sluggish. In Python, pandas handles it in seconds; our all-time stats guide covers the traps to avoid (UTC timestamps, skips, one song under several IDs).
5. Chatting with your history
Instead of picking from charts or writing formulas, you ask: “Who did I play most the year I graduated?” A model turns the question into a query over your plays and explains the result. You can do a rough version today by uploading the export to ChatGPT or Claude (see how to ask ChatGPT or Claude about your Spotify history), or use a tool built for it.
Side by side
| Approach | Whole history | Effort | What you can ask | Where your data goes |
|---|---|---|---|---|
| Spotify recaps | Highlights only | None | Nothing; you get fixed cards | Stays with Spotify |
| Stats apps | With an import | Low | The app’s charts and lists | The app’s servers |
| Open-source viewers | Yes | Low to medium | The author’s charts | Your computer, if it runs locally |
| Spreadsheet or Python | Yes | High | Anything you can write | Your computer |
| AI chat | Yes | Low | Anything you can put into words | The AI provider, plus the tool if you use one |
Which one to pick
- You want something to post: Spotify’s recaps.
- You want to keep tracking from now on: a stats app.
- You want classic charts and full privacy: an open-source viewer that runs in your browser.
- You want total control and like code: Python.
- You have questions, not chart preferences: chat.
Where ListenLens fits
ListenLens is the fifth approach, built for the job. You upload the zip as it is and ask in plain English, on ListenLens or from Claude or ChatGPT. The cleanup a script would need is done for you, and each answer comes with a table or chart and a note on how it was worked out.
A few things it does differently from uploading files to a chatbot:
- A database of your own. Your plays go into a separate database, not a shared table.
- Read-only. Nothing the AI does can change your history.
- The AI sees answers, not your file. It gets your question and the rows it looked up, never the whole export.
- IP addresses stay out. Spotify logs one for every play. They never go into the history you or an AI can query.
Two honest limits: it covers music only for now (podcasts and audiobooks are skipped), and it reads your export, so it’s as current as the last one you uploaded. Get started with ListenLens.
Questions
Is there a free Spotify history analyzer?
Yes. Spotify’s own recaps are free, many open-source viewers are free, and a spreadsheet or Python script costs nothing but time. Requesting your Extended Streaming History is free too.
Can I analyze my Spotify history without requesting the export?
Only the recent part. Apps that sign in with Spotify can read your top artists and tracks for a few fixed time ranges and your last 50 plays. Anything older needs the Extended Streaming History export.
Is it safe to upload my Spotify data to an analyzer?
Treat it as personal data: the export is your full listening log and includes an IP address for every play. Check what the tool keeps, whether it sells data, and where it runs. Tools that run entirely in your browser never upload it.
Does the export include podcasts?
Yes, podcast and audiobook plays are in it alongside music, marked by their own fields. Many analyzers, including ListenLens today, look at music only.