March 2025
Intermediate to advanced
504 pages
12h 7m
Spanish
Content preview from Python Polars: la guía definitiva
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Capítulo 14. Unir y concatenar
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A menudo, los datos proceden de varias fuentes que tendrás que conectar y combinar de forma que tengan sentido. Hay varias formas de combinar los DataFrames, que repasaremos en este capítulo.
Curiosamente, aquí es donde Polars empezó una vez. Enfrentado a la combinación de dos archivos CSV en Rust, Ritchie Vink inició su viaje que, en última instancia, le llevó a donde estamos ahora. Esto da un sentimiento especial a las operaciones de este capítulo.
En este capítulo aprenderás
-
Que puedes utilizar
df.join()para combinar los DataFrames basándote en los valores de los DataFrames y en las estrategias aquí descritas -
Ese
df.join_asof()es un join especial que une DataFrames basándose en el valor más cercano del otro DataFrame -
Cómo combinar DataFrames utilizando
pl.concat(),df.vstack(),df.hstack(), ydf.extend() -
Cómo combinar Series con
series.append() -
Las diferencias entre todos estos métodos y cuándo utilizarlos
Las instrucciones para obtener los archivos que puedas necesitar están en el Capítulo 2. Suponemos que tienes los archivos en el subdirectorio de datos.
Únete a
Para combinar diferentes DataFrames en , Polars ofrece el método df.join(). Toma los argumentos que aparecen en la Tabla 14-1.
| Argumento | Descripción |
|---|---|
|
El DataFrame con el que unir. |
|
La columna sobre ... |
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