How to Create Seasonal Market Charts Using Python
AI poses an existential threat to the entertainment industry as we know it, and it is entirely justified by the Writers Guild of America (WGA)
to demand control over its usage. Networks and studios have a troubling history of adopting new technologies. In 2008, studios commanded a $16.9 billion market in DVDs and home videos, but their lack of understanding and adaptation to streaming technology caused an 86 percent loss within the first decade. Change happens rapidly in the entertainment sector, with sound movies replacing silent films and television superseding network radio. The rise of streaming has significantly impacted artists’ income and studio financing, wiping out billions in revenue.
Throughout these technological transitions, studios have historically pursued a scorched-earth policy, leaving entire generations of artists and technicians, along with the culture they created, behind.
Seasonal charts focus on analyzing price or performance data over different seasons, months, or weeks within a year. This analysis is based on the idea that certain assets or markets exhibit repetitive patterns or behaviors during particular times of the year.
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