En este curso adquirirás los fundamentos de la extracción, transformación y carga (ETL) de datos, así como la exploración de datos en la ciencia de datos. Aprenderás a trabajar con Pandas y dataframes, a leer archivos CSV y XLSX, y a comprender los conceptos de series temporales. Además, aprenderás la visualización de datos utilizando Matplotlib, creando gráficas individuales y personalizadas. También utilizarás NumPy y la manipulación de arrays, realizando las operaciones básicas y calculando gradientes. A lo largo del curso, desarrollarás buenas prácticas en el flujo de trabajo en ciencia de datos y en los conceptos avanzados como multi-índices en series temporales. Finalmente, sabrás como usar paquetes de manera local.
Python: de usuario a explorador de datos
Python: de usuario a explorador de datos
This course is part of Python: de cero a analista de datos Specialization
Instructor: Guillermo Barrios del Valle
Included with 
Gain insight into a topic and learn the fundamentals.
Beginner level
No prior experience required
16 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
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Shareable certificate
Add to your LinkedIn profile
Taught in Spanish
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This course is part of the Python: de cero a analista de datos Specialization
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There are 5 modules in this course
What's included
21 videos1 reading1 programming assignment
What's included
14 videos1 programming assignment
What's included
16 videos1 programming assignment
What's included
16 videos1 programming assignment
What's included
2 videos1 programming assignment
Instructor
Offered by
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Universitat Autònoma de Barcelona
Pontificia Universidad Católica de Chile
University of Michigan
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