This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework. The third week will be a tutorial of functionality available in matplotlib, and demonstrate a variety of basic statistical charts helping learners to identify when a particular method is good for a particular problem. The course will end with a discussion of other forms of structuring and visualizing data.
Este curso forma parte de Programa Especializado - Ciencias de los Datos Aplicada con Python
Applied Plotting, Charting & Data Representation in Python
ofrecido por
Acerca de este Curso
Resultados profesionales del estudiante
36%
38%
14%
Qué aprenderás
Describe what makes a good or bad visualization
Understand best practices for creating basic charts
Identify the functions that are best for particular problems
Create a visualization using matplotlb
Habilidades que obtendrás
Resultados profesionales del estudiante
36%
38%
14%
100 % en línea
Fechas límite flexibles
Nivel intermedio
Aprox. 18 horas para completar
Inglés (English)
ofrecido por
Universidad de Míchigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
Programa - Qué aprenderás en este curso
Module 1: Principles of Information Visualization
In this module, you will get an introduction to principles of information visualization. We will be introduced to tools for thinking about design and graphical heuristics for thinking about creating effective visualizations. All of the course information on grading, prerequisites, and expectations are on the course syllabus, which is included in this module.
Module 2: Basic Charting
In this module, you will delve into basic charting. For this week’s assignment, you will work with real world CSV weather data. You will manipulate the data to display the minimum and maximum temperature for a range of dates and demonstrate that you know how to create a line graph using matplotlib. Additionally, you will demonstrate the procedure of composite charts, by overlaying a scatter plot of record breaking data for a given year.
Module 3: Charting Fundamentals
In this module you will explore charting fundamentals. For this week’s assignment you will work to implement a new visualization technique based on academic research. This assignment is flexible and you can address it using a variety of difficulties - from an easy static image to an interactive chart where users can set ranges of values to be used.
Module 4: Applied Visualizations
In this module, then everything starts to come together. Your final assignment is entitled “Becoming a Data Scientist.” This assignment requires that you identify at least two publicly accessible datasets from the same region that are consistent across a meaningful dimension. You will state a research question that can be answered using these data sets and then create a visual using matplotlib that addresses your stated research question. You will then be asked to justify how your visual addresses your research question.
Revisiones
Principales revisiones sobre APPLIED PLOTTING, CHARTING & DATA REPRESENTATION IN PYTHON
Practical course with hands on exercise to make you well versed in Applied Plotting, Charting & Data Representation in Python. I recommend at least every college student should experience this course
It contains very good recommended lectures, good material and explanation about matplotlib to grasp a big picture. However, you must invest a lot of time on your own to research deeper in the topic
Week 1 is a little bit theory and boring for me because that doesn't interest me but week 2 and week 4 is amazing. Especially week 4 assignment is too good. Overall the course is worth learning.
Loved the course! This course teaches you details about matplotlib and enables you to produce beautiful and accurate graphs.. Assignments are challanging, and helps to build a solid foundation.
I thought this was a really good introduction to matplotlib and some of the things you can do with it. The final project we got to apply what we'd learned to real data, which was a lot of fun.
Good course to learned matplotlib and other Graphs libraries, but the course goes further than Python and also encourages the studies to create more meaningful and beautiful Graphic views.
Very helpful to understand what it takes to make a scientific and sensible visual. Recommended for someone who is interested in learning data visualization and does not have a background.
It's a good intermediate level course . Prior work in Python plotting functions does help . Assignments are good and make you stretch your skills . Discussion forum is quite supportive.
Excellent introduction to matplotlib and hands on projects to learn the concepts. I'm happy with the visualizations I've built. Also got a foundation to delve further into this field.
This was good course, but a little heavy going at times. I actually stopped it, then came back to it after doing course 4 in the specialization. It is worth it tho, so keep going!
Really interesting course covering matplotlib functionality. There is a lot of self-study required, but that's okay. Liked the demo's about Panda's and Seaborn in week 4 as well.
Pretty awesome course! it's not a walk in the park, though. If you do love data science, and apply what you learn on the course, with some grit and perseverance, you'll prevail.
Acerca de Programa especializado Ciencias de los Datos Aplicada con Python
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Cuál es la política de reembolsos?
¿Hay ayuda económica disponible?
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