Unit 6. Data VisualizationRevision Date: Jan 04, 2020 (Version 3.0)
Continuing the focus on data analysis from Unit Five, students will use the browser-based Dataquest learning environment (http://www.dataquest.io) and supplementary materials to explore more ways in which Python can be used to analyze data. For the first week, students will explore Dataquest through the browser-based "missions" on the website. Each lesson begins with a warm-up/journal entry, and students then spend the rest of the time working through the missions at their own pace. For the second part of the lesson, students will design and implement their own data analysis project in order to prepare them to complete a data-focused Create Performance task.
Week One: Learning Dataquest
Week Two: Data Analysis Project
Student computer usage for this lesson is: required
DataQuest.io website: https://www.dataquest.io/learn
Week One Materials: Unit 6 Resources -> DataQuest.io -> Week One Lesson Materials -> Mission #
Week Two Materials:
Datasets: Unit 6 Resources -> Dataquest.io - > Week Two Project Datasets and Materials -> Datasets
Sample Project: Unit 6 Resources -> Dataquest.io - > Week Two Project Datasets and Materials -> Sample Project
Project Rubric: Unit 6 Resources -> Dataquest.io - > Week Two Project Datasets and Materials -> "Data Analysis Project Rubric"
(Quizzes for Week One and Week Two are in the corresponding teacher-only resource folders)
Note: all worksheets and quizzes can be found in the teacher-only resource folder, Unit Six -> DataQuest.io -> Week One Lesson Materials -> Mission #
Directions for working in Dataquest.io
Quizzes should be done in class, and should take a minimum of 10-20 minutes to complete. It is advisable to not give a quiz out in the last ten minutes of class. If there are only a few minutes left, the student can use the time to add to their notes.
If a student fails one of the quizzes, they may be given the chance to go back and add to their worksheet before attempting the quiz again. (Multiple versions of all coding quizzes are available.)
There are four Missions for the Data Analyst In Python Path. Students are only required to do the first three to review and prepare for the create task they should do the first six missions.
The fourth Mission has worksheets/quizzes for those students who get to it, and can be counted as extra credit/normal grade at the teacher’s discretion. Additional useful courses include data visulization, data cleaning and introductory statisitics.
Show the first two minutes of the introductory video in Mission 1 on the Dataquest.io website. Students will discuss their reactions and thoughts about Data Science.
This warm-up time is used for class discussion on progress through the missions. You can use this time to gauge the students' comfort with Python concepts by having students vote with their heads down. If enough students are having trouble, you may want to have a separate review session during the class.
This warm-up time can be used for reviewing a Python concept (such as Dictionaries) or looking at a current news article involving data analysis (any article about a topic of interest to the students that uses statistics would be appropriate). Students should think-pair-share on additional ways in which data could be used.
Students should do a show of hands to see where everyone is in the missions. The class should have a general discussion about progress.
Note: All materials for this section can be found in Unit 6 Resources -> Dataquest.io - > Week Two Project Datasets and Materials
For this week, students will be pairing up to create and implement a data analysis program of their own design.
For the rest of the week, students should work on their projects in their groups. At the end, teachers can optionally have them present their PowerPoints to the class, exchange presentations in pairs, or merely turn everything in.
Week two project.