cc for EDAV 2021
1 Community contribution assignment
- 1.1 Logistics
  - 1.1.1 Groups
  - 1.1.2 Submitting your assignment
2 GitHub submission instructions
3 Sample project
I Cheatsheets
4 Date-Time Handling in R Cheatsheet
5 Tidy data Cheatsheet
6 GGvis cheatsheet
7 Statistical_hypothesis_testing_cheatsheet
8 Basics R Cheatsheet
9 Alluvial Diagram Cheatsheet
10 ggplot2_cheatsheet
11 Patchwork Cheatsheet
II Translations
12 Colors_in_R_Chinese_translation
- 12.1 在R中使用颜色
13 Managing Data Frames with dplyr Package in Chinese
14 Introduction to Rstudio in Portuguese
15 Chinese translation of using ARIMA models in R
- 15.1 ARIMA模型
16 Chinese translation of broom package
17 Translation of Visualizations That Really Work
18 Chinese Translation of Bar Chart and Cleveland Dot Plot
- 18.1 图表：条形图
- 18.2 图表：克利夫兰点图
  - 18.2.1 综述
  - 18.2.2 多点图
19 Translation of critical covid data visualizations paper
20 Translate IBM Website about Design Language into Chinese
21 Chinese Translation Exploratory Data Analysis and Data Visualization
22 Chinese translation of stringr package
23 Chinese Translation–Beautiful Soup Tutorial
24 Translation of ggplot2 tutorial in Korean
25 R markdown Tutorial Translation in Chinese.
26 R Quantmod Package Tutorial & Translation
- 26.1 “R的quantmod软件包旨在帮助定量交易者开发，测试和部署基于统计交易的模型。”
III Tutorials
27 Creating R Packages
28 Introduction to Quandl()
- 28.1 INTRODUCTION
29 Getting data using APIs
30 Introdution to Time Series Analysis
31 Intro to Tableau with R
32 Sentiment analysis and wordcloud
33 Twitter sentiment analysis in R
34 Introduction to pyecharts
35 Up and Running (Quickly) with Leaflet
36 Introduction to geographic chart in R
37 Interview questions for data visualization
38 Introduction to Supervised Machine Learning
39 Data acquisition and wrangling
40 Complete EDA Process and Visualizations in Python
41 Data Transformation with Dplyr Video Tutorial
42 Data science ethics
43 3D plot in R
44 Ben Shneiderman’s Visualization Mantra
45 Choose Your Adventure - How to choose the right visualization for your data
46 Common Errors in R
47 Collaborating on RStudio with GitHub
48 Math Finance in R
49 Introduction to Topology Data Analysis
50 An introduction of web scrapping using rvest
51 Mschart
52 A brief introduction to ggraph
53 Using SQL with R
54 Plotly R graphing
IV Topical Discussions
55 Zoom session in Finance and Data-Science
56 Data science, the environment, and sustainability
57 Absentee ballot voting in 2020 presidental election
58 Final project Zoom meetup - sports
59 In-Person Fitness Hour
- 59.1 Piazza Announcement
- 59.2 Final Event
60 Work culture and time management
61 Data Science for Social Good
- 61.1 R Markdown
62 Wine and wine tasting
63 Meet the pets zoom session
64 Intro to Data Science – videos
65 Data science student community environment build
- 65.1 Community contribution overview
  - 65.1.1 Part 1: Online Meeting Session
  - 65.1.2 Part 2: Build Community Servers
66 NBA data useful for a final project
V Appendices
67 Github initial setup
- 67.1 GitHub Actions
- 67.2 DESCRIPTION file
68 Tutorial for pull request mergers
Published with bookdown

Spring 2021 EDAV Community Contributions

Chapter 61 Data Science for Social Good

Rahul Subramaniam and Tushar Agrawal

61.1 R Markdown

Data Science has a plenitude of applications. With virtually every sector incorporating data science to bolster their efficiency/sales/revenues/performance, novel applications of Data Science come to light every day.

One such field is the field of Social Good. A lot of Government/Non-Profit organizations use Data Science to develop applications/models that will benefit the society as a whole.

https://drive.google.com/file/d/1cnZwDFeIhi4RqTITP6OHwMutynk7jeuI/view?usp=sharing

Rahul Subramaniam and Tushar Agrawal conducted a Zoom session that discussed various applications of Data Science for Social Good. Click the link above to view the session.