September 2024
Intermediate to advanced
338 pages
9h 21m
Spanish
Content preview from Python para Excel
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Capítulo 6. Análisis de series temporales con pandas
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Una serie temporal es una serie de puntos de datos a lo largo de un eje temporal que desempeña un papel central en muchos escenarios diferentes: mientras que los operadores utilizan los precios históricos de las acciones para calcular medidas de riesgo, la previsión meteorológica se basa en series temporales generadas por sensores que miden la temperatura, la humedad y la presión atmosférica. Y el departamento de marketing digital se basa en series temporales generadas por páginas web, por ejemplo, la fuente y el número de páginas vistas por hora, y las utilizará para sacar conclusiones respecto a sus campañas de marketing.
El análisis de series temporales es uno de los principales motivos por los que los científicos y analistas de datos han empezado a buscar una alternativa mejor a Excel. Los siguientes puntos resumen algunas de las razones que hay detrás de este movimiento:
- Grandes conjuntos de datos
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Las series temporales pueden crecer rápidamente más allá del límite de Excel de aproximadamente un millón de filas por hoja. Por ejemplo, si trabajas con cotizaciones bursátiles intradía en un nivel de datos de ticks, ¡a menudo estás tratando con cientos de miles de registros por acción y día!
- Fecha y hora
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Como hemos visto en el Capítulo 3, Excel tiene varias limitaciones a la hora de manejar la fecha y la hora, ...
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