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.
Этот курс входит в специализацию ''Специализация Прикладная наука о данных с Python'
Applied Plotting, Charting & Data Representation in Python
от партнера
Об этом курсе
Карьерные результаты учащихся
36%
38%
14%
Приобретаемые навыки
Карьерные результаты учащихся
36%
38%
14%
100% онлайн
Курс 2 из 5 в программе
Гибкие сроки
Промежуточный уровень
Прибл. 17 часа на выполнение
Английский
Программа курса: что вы изучите
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.
Рецензии
Лучшие отзывы о курсе 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.
О Мичиганский университет
Специализация Прикладная наука о данных с Python: общие сведения
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