EdX

Visualizando datos con Python (edX)

Offered by IBM,
Visualizando datos con Python (edX)

La visualización de datos es la representación gráfica de los datos para transmitir de manera interactiva y eficiente las ideas a los clientes y partes interesadas en general.

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"Una imagen vale más que mil palabras." Todos estamos familiarizados con esta expresión. Se aplica especialmente cuando se trata de explicar las ideas obtenidas del análisis de conjuntos de datos cada vez más grandes. La visualización de datos juega un papel esencial en la representación de datos tanto a pequeña como a gran escala.
Una de las habilidades clave de un científico de datos es la capacidad de contar una historia convincente, visualizar datos y hallazgos de una manera accesible y estimulante.
En este curso, aprenderás cómo aprovechar una herramienta de software para visualizar datos que también te permitirán extraer información, comprender mejor los datos y tomar decisiones más efectivas.
Cuando te registras en este curso, obtienes acceso gratuito a IBM Watson Studio. En Watson Studio, podrás comenzar a crear tus propios proyectos de ciencia de datos y colaborar con otros científicos de datos. ¡Comienza ahora y aprovecha todo lo que esta plataforma tiene para ofrecer!
Ten en cuenta que los foros de discusión de este curso están abiertos para que los estudiantes publiquen y se comuniquen entre sí. Sin embargo, los foros ya no serán supervisados por el equipo de IBM. Las preguntas técnicas relacionadas con tu experiencia en el curso deben dirigirse al equipo de soporte de edX a través de la información de contacto proporcionada en el curso. Gracias.
This course is part of the Ciencia de datos con Python Professional Certificate and IBM: Ciencia de datos Professional Certificate.
What you'll learn

  • Cómo presentar datos usando algunas de las bibliotecas de visualización de datos en Python, incluyendo Matplotlib, Seaborn y Folium
  • Cómo usar las herramientas básicas de visualización, que incluyen gráficos de área, histogramas y gráficos de barras
  • Cómo usar herramientas de visualización especializadas, incluidos gráficos circulares, gráficos de caja, gráficos de dispersión y gráficos de burbujas
  • Cómo usar herramientas de visualización avanzadas, que incluyen gráficos de Waffle, nubes de palabras y gráficos de regresión y Seaborn
  • Cómo crear mapas y ver datos geoespaciales
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