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![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54)
![R](https://img.shields.io/badge/r-%23276DC3.svg?style=for-the-badge&logo=r&logoColor=white)


**Team Members (in alphabetical order)**

* **Core Team**: Qinyue Hao, Jasmine Hwang, Dan Li, Peishan Li, Rina Shin, Connie Xu, Hanyu Zhang
* **Supporting Team**: Zhiwen Huang, Cara Latinazo, Xingchen Li, Soobin Oh, Lizabeth Singh, Mengying Xu, Tianqing Zhou


## Project Description

This project is developed by graduate students in the Social Sciences program of Columbia University in collaboration with the UN SDG Fund. The objectives of this project was to develop models that could define and quantitatively measure the networks among the 17 Sustainable Development Goals (SDG). To do this we built two models, one text model based on indicator descriptions from UN SDG Indicator Metadata, and coefficient networks based on coefficients calculated using UN SDG Indicator Database. The team also looked at the similarity between the two models, and the generalizability of the network model from the two example countries.
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3. QAP Analysis: Calculation of similarity and associations between text and network models.

## Initial Results:
![cute cat image](https://github.com/PeishanLi/G5055_Practicum_Project2/blob/main/Visualizations/Interactive/Social%20Network%20Model-Guatemala-negative.html)


## Final Deliverables

1. [Blog](https://docs.google.com/presentation/d/1zmhJTMVDWkgyJlh7xcl0nNyeMsjiqfmjNm4FKSYFkJ4/edit)
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4. **The team's key findings including other visualization works could be seen the team's [final presentation slides](https://github.com/PeishanLi/G5055_Practicum_Project2/blob/main/G5055%20Project%202%20Deck%20.pdf).**

## Repository Directory:

├── cs_repayment_rate
├── cs_student_debt
├── twitter_data
├── shiny
├── data
├── temp
├── www
├── solutions_and_visualizations
├── census_student_debt_etc
# exploratory data about poverty and student debt - not really used in current iteration of project
├── repay_rate
├── repay_rate_visuals
├── student_debt
├── twitter
├── twitter_visuals
## Repository Directory Contents:

├── Codes
├── Composite (1b)
├── Correlation Analysis (1c)
├── Data Accessing and Preprocessing (1a)
├── Data Visualization (4)
├── coefficient network
├── text network
├── data missingness and disaggregation
├── Pick Central Variable (1) ^^
├── Regression Models (3)
├── Text Model (2)
├── Data
├── Centrality_representative_results (1) ^^
├── centrality_scores(after removing disaggregation)
├── indicator_picked(before removing disaggregation)
├── measure_picked(before removing disaggregation)
├── Guatemala & Indonesia Correlation among Indicators (1) ^^
├── Guatemala & Indonesia Correlation among Targets (1) ^^
├── Guatemala & Indonesia Correlation among measurements (1) ^^
├── Guatemala & Indonesia Correlation among measurements-WITHOUT disaggregation ^^ (1)
Guatemala & Indonesia Correlation among Targets Ungrouped.csv ^^
Indonesia.csv & Guatemala.csv ^^
Guatemala & Indonesia data after selecting one measurement for each indicator.csv ^^
Guatmala & Indonesia Data Without Disaggregation.csv ^^
├── variable_types (1) ^^
├── variables_picked (1) ^^
├── List of indicators (1)
├── Data_preprocessed_for_PCA (1)
├── PCA_results (1)
├── coefficient_network (1) ^^

├── SDG-indicator-metadata (2)
├── Text_Model_Data (2)
├── Voluntary National Reviews (2) ^^

├── Literature

├── Visualizations
├── Disaggregated_Data (1a)
├── Missing_Data (1a)
├── Model_Viz (1c)
├── Interactive (1c)
├── Text_Model_Viz (2)
├── goal_hexcodes_edge.csv
├── goal_hexcodes.csv

^^ - item is likely deprecated
(1), (2), (1 & 2) - refers to model that the folder is corresponding to.

### Codes

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4. Data Visualization

### Data

**Original data sources include:**

* [UN SDG Indicators](https://unstats.un.org/sdgs/indicators/database/)
* [UN SDG Indicator Metadata](https://unstats.un.org/sdgs/metadata/)

**Preprocessed data:**

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