The song Puccini: Madama Butterfly, Act 1: "Questa è la cameriera" (Goro, Pinkerton, Suzuki, Sharpless) by Giacomo Puccini, Herbert von Karajan, Lucia Danieli, Mario Borriello, Nicolai Gedda, Renato Ercolani, Orchestra Del Teatro Alla Scala, Milano has been played
107,750 times on Spotify since its release on June 23, 2023.
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Other songs from Giacomo Puccini, Herbert von Karajan, Lucia Danieli, Mario Borriello, Nicolai Gedda, Renato Ercolani, Orchestra Del Teatro Alla Scala, Milano
Giacomo Puccini, Transylvania State Philharmonic Orchestra of Cluj-Napoca, Lawrence Foster, Lawrence Foster, Marius Vlad, Marius Vlad, Melody Moore, Melody Moore, Lester Lynch, Lester Lynch, Transylvania State Philharmonic Choir of Cluj-Napoca, Transylvania State Philharmonic Choir of Cluj-Napoca, Kevin Short, Kevin Short, Radu Cîmpan, Radu Cîmpan
Antonio Vivaldi, Michel Schwalbé, Thomas Brandis, Leon Spierer, Hans-Joachim Westphal, Eberhard Finke, Horst Gobel, Berliner Philharmoniker, Herbert von Karajan
Giacomo Puccini, Orchestra e Coro del teatro Municipale di Reggio Emilia, Francesco Molinari-Pradelli, Vito Mattioli, Walter De Ambrosis, Luciano Pavarotti, Dmitri Nabokov
Giacomo Puccini, Maria Callas, Giuseppe Di Stefano, Manuel Spatafora, Nicola Zaccaria, Rolando Panerai, Antonino Votto, Orchestra Del Teatro Alla Scala, Milano
Frequently asked questions
Due to Spotify's policy of not publicly sharing daily stream counts, our system independently records this data on a daily basis for millions of tracks. Given the vast number of tracks we monitor, there may be occasions where certain tracks are not processed on specific days, leading to missing data points. Rest assured, we continuously work to minimize these gaps and provide comprehensive coverage.
There are two primary reasons you might notice irregularities in the data points:
- Inconsistent Stream Counts for a Day: Sometimes, a data point may represent the stream count for two days instead of one. This inconsistency arises because Spotify does not update its public stream count at a fixed time daily. If our data recording aligns with these fluctuations, it can lead to inaccuracies.
- Anomalous Data Points (including negative streams): On occasion, you might observe highly irregular data points, such as negative daily streams. These are typically the result of metadata discrepancies on Spotify's end, like different tracks sharing the same International Standard Recording Code (ISRC). In such cases, reaching out to us can be very helpful. We can often disregard these erroneous data points to present a more accurate graph.
In both situations, we're committed to continuously improving our data accuracy and are here to assist with any specific concerns you might have.
The extent of our historical data varies depending on the track. For some tracks, our records go as far back as September 2023. However, there are tracks for which we may not have any historical data yet. But here's the good news: once you look up a specific track on our system, you activate our tracking for that track. From that point forward, we will diligently record its data daily, ensuring you have continuous and up-to-date insights from the moment you start using our service.
Currently, our platform does not provide a direct option to export data. However, we understand the importance of this feature, and we're excited to announce that a CSV export functionality is on our roadmap and will be introduced soon. For developers seeking more integrated solutions, we offer an API service. If you're interested in accessing our API for your specific use case, please feel free to reach out to us. We're always eager to collaborate and support your unique needs!
This occurs due to Spotify's policy of only displaying public stream counts for tracks that have surpassed 1,000 streams. Consequently, if you see a stream count marked as 0 in our system, it indicates that the total stream count for that track is currently below 1,000. As the track accumulates more streams and crosses this threshold, the accurate stream count will start being reflected in our data.
