La analítica de datos ha avanzado considerablemente en los últimos años y ahora existen diversas herramientas que nos permiten realizar tareas o procesos que antes eran complicados de realizar. Gracias a su versatilidad, el lenguaje de programación Python posee una serie de librerías que permiten realizar proyectos de analítica de datos de una forma muy sencilla y una de las librerías más populares es Pandas.
Analíticas de Datos con Pandas
Analíticas de Datos con Pandas
Instructor: Jesus Aguilar Gonzalez
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4.3
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Beginner level
No prior experience required
24 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace
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Assessments
15 assignments
Taught in Spanish
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There are 4 modules in this course
En este primer tema nos enfocaremos a entender cómo instalar y preparar todo para utilizar la librería Pandas y aprenderemos los elementos fundamentales de la librería; además, conoceremos un poco de la historia de esta librería y el porqué es tan popular.
What's included
2 videos13 readings4 assignments1 discussion prompt
Una parte fundamental de Pandas es la manipulación de estructuras de datos y en este apartado estaremos enfocándonos a conocer la forma en la que Pandas maneja las estructuras de datos (series, dataframes, etc.). Adicionalmente estaremos aprendiendo las principales funciones que utiliza Pandas para manipular y analizar los datos.
What's included
2 videos10 readings3 assignments1 discussion prompt
La popularidad de Pandas radica en que muchos lo llaman el Excel con esteroides, pues ha desarrollado funciones que permiten que ciertas operaciones sean muy sencillas y fáciles de implementar para realizar análisis muy complejos. En este apartado, revisaremos las operaciones básicas y avanzadas que maneja Pandas para realizar cálculos en estructuras de datos, columnas, renglones o datos de tipo cadena.
What's included
2 videos9 readings3 assignments1 peer review1 discussion prompt
El Análisis Exploratorio de Datos o EDA es una forma de analizar datos que fue definido por John W. Turkey; este es una parte fundamental para la realización de proyectos de ciencia de datos. En este apartado nos centraremos en aprender a realizar un EDA usando Pandas. Adicionalmente, otra de las etapas importantes de la ciencia de datos es la visualización de datos y en este apartado conoceremos como realizar este proceso en Pandas con la ayuda de librerías que apoyan a Pandas.
What's included
3 videos10 readings5 assignments1 discussion prompt
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