Bach, JS: Partita No. 6 in E Minor, BWV 830: II. Allemande

The song Bach, JS: Partita No. 6 in E Minor, BWV 830: II. Allemande by Johann Sebastian Bach, Walter Gieseking has been played less than 1,000 times on Spotify since its release on January 05, 2025.

Other songs from Johann Sebastian Bach, Walter Gieseking

15 Inventions, BWV 772-786: 9. Invention In F Minor, BWV 780

Johann Sebastian Bach, Walter Gieseking
15 Two-part Inventions, BWV 772/786: No. 12 in A, BWV 783

Johann Sebastian Bach, Janine Jansen, Maxim Rysanov
Clair de lune

Pyotr Ilyich Tchaikovsky, Percy Grainger, Ermanno Wolf-Ferrari, Edward Elgar, Antonio Vivaldi, Charles Gounod, George Frideric Handel, Giuseppe Verdi, Johann Strauss II, Johann Strauss I, Edvard Grieg, Johann Sebastian Bach, Ronald Binge, Arthur Benjamin, Felix Mendelssohn, Wolfgang Amadeus Mozart, Jules Massenet, William Walton, Émile Waldteufel, Pietro Mascagni, Ambroise Thomas, Emil Nikolaus von Reznicek, Johann Nepomuk Hummel, Enrique Granados, Léo Delibes, Claude Debussy, Jean Sibelius, London Symphony Orchestra, Vilem Tausky
Prelude & Fugue in F-Sharp Minor (Well-Tempered Clavier, Book I, No. 14), BWV 859: Prelude

Johann Sebastian Bach, Wilhelm Kempff
Bach: Chromatic Fantasia and Fugue in D Minor, BWV 903: Fugue

Johann Sebastian Bach, Mayako Sone

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.