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Cybermidnight Club Podcast Analytics Report

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Manage episode 493367703 series 2535026
Content provided by Alberto Daniel Hill. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alberto Daniel Hill or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Cybermidnight Club Podcast Analytics Report.

The source showcases a data analysis project focused on the performance of a Spotify podcast titled "Cybermidnight Club." It begins by illustrating Python code utilizing the pandas library to load and inspect podcast data from a CSV file, revealing information about columns like "Hora (UTC)," "Reproducciones" (Plays), "Streams," "Horas de consumo" (Consumption Hours), and "Seguidores" (Followers). Subsequent code demonstrates data cleaning (filling missing values), descriptive statistics, and the generation of visualizations using matplotlib, including time-series plots for plays and followers, and a scatter plot comparing plays to streams. Finally, the source presents a summary of key podcast metrics and provides interpretations of the generated graphs, offering insights into the podcast's reach and growth.

  continue reading

511 episodes

Artwork
iconShare
 
Manage episode 493367703 series 2535026
Content provided by Alberto Daniel Hill. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Alberto Daniel Hill or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Cybermidnight Club Podcast Analytics Report.

The source showcases a data analysis project focused on the performance of a Spotify podcast titled "Cybermidnight Club." It begins by illustrating Python code utilizing the pandas library to load and inspect podcast data from a CSV file, revealing information about columns like "Hora (UTC)," "Reproducciones" (Plays), "Streams," "Horas de consumo" (Consumption Hours), and "Seguidores" (Followers). Subsequent code demonstrates data cleaning (filling missing values), descriptive statistics, and the generation of visualizations using matplotlib, including time-series plots for plays and followers, and a scatter plot comparing plays to streams. Finally, the source presents a summary of key podcast metrics and provides interpretations of the generated graphs, offering insights into the podcast's reach and growth.

  continue reading

511 episodes

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