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https://github.com/reycn/data-analytics-in-julia
Notebooks for data analysis in social science using Julia, replicating frequent analytical steps in Python & R.
https://github.com/reycn/data-analytics-in-julia
data data-analysis data-science data-visualization julia
Last synced: about 5 hours ago
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Notebooks for data analysis in social science using Julia, replicating frequent analytical steps in Python & R.
- Host: GitHub
- URL: https://github.com/reycn/data-analytics-in-julia
- Owner: reycn
- License: other
- Created: 2024-12-11T03:50:13.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-12-24T06:30:28.000Z (19 days ago)
- Last Synced: 2024-12-24T07:28:30.289Z (19 days ago)
- Topics: data, data-analysis, data-science, data-visualization, julia
- Language: Jupyter Notebook
- Homepage: https://data-julia.rongxin.me
- Size: 2.38 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Data Analytics in Julia [[🔗 Book](https://data-julia.rongxin.me)]
[![CC BY-NC 4.0][cc-by-nc-shield]][cc-by-nc]
By [Rongxin Ouyang](https://rongxin.me/cv), PhD student in Computational Communication, NUS
# Scope
This short book provides a practical guide for data analysis in social science using Julia. It replicates common analytical steps in the field.
Because of its speed.
# Outline
- [✅ Chapter 1. Installation](https://reynards-org.gitbook.io/data-analysis-in-julia/1.installation.basics.jl)
- ✅ Why do we need Julia
- ✅ How to install Julia
- ✅ How to install Julia as a Jupyter kernal for notebooks
- ✅ The basics of operations, data structures, packages, methods, and define functions
- [✅ Chapter 2. Data Loading and Selection](https://reynards-org.gitbook.io/data-analysis-in-julia/2.data.loading.selection.jl)
- ✅ Load a dataframe from a local file, an online link, and a common datasets; or create it from scratch
- ✅ Select by rows, columns, and conditions.
- [✅ Chapter 3. Transformation and calculation](https://reynards-org.gitbook.io/data-analysis-in-julia/3.transform.calculate.jl)
- ✅ Split and combine
- ✅ Grouping
- ✅ Sorting
- ✅ Transforming between long / wide tables
- ✅ Find / fill / drop missing values
- [✅ Chapter 4. Pipeline and Useful Packages](https://reynards-org.gitbook.io/data-analysis-in-julia/4.pipeline.tools.jl)
- ✅ Data pipeline
- ✅ Manipulate strings
- ✅ Network
- [✅ Chapter 5.1 Models and Tests](https://reynards-org.gitbook.io/data-analysis-in-julia/5.1.models.jl)
1. ✅ Common parametric tests (t-tests and ANOVA)
2. ✅ Regression (multi-variate regression and fixed effects models)
3. ✅ Path Analysis
1. ✅ Mediation
2. ✅ Moderation
3. ✅ Conditional Path Analysis
- [✅ Chapter 5.2 Models and Tests (continued)](https://reynards-org.gitbook.io/data-analysis-in-julia/5.2.models.jl)
1. 🚧 / ✅ Counterfactual Framework
1. 🚧 / ✅ Instrumental Variables
2. 🚧 / ✅ Regression Discontinuity Design
3. 🚧 / ✅ Difference-in-Difference
4. 🚧 / ✅ Synthetic Control
5. 🚧 / ✅ Synthetic Difference-in-Difference
- [✅ Chapter 6. Visualization](https://reynards-org.gitbook.io/data-analysis-in-julia/6.visualize.jl) (ggplot2-like)
- ✅ Scatterplot, barplot, lineplot, and histogram
- ✅ Styles and themes
- ✅ Multiple-plots in facets
- [✅ Chapter 7. Using R and Python in Julia](https://reynards-org.gitbook.io/data-analysis-in-julia/7.r.and.python.in.julia.jl)
- ✅ Using R functions and R code blocks in Julia
- ✅ Using Python functions and Python code blocks in Julia
# License
This work is licensed under a
[Creative Commons Attribution-NonCommercial 4.0 International License][cc-by-nc].
[![CC BY-NC 4.0][cc-by-nc-image]][cc-by-nc]
[cc-by-nc]: https://creativecommons.org/licenses/by-nc/4.0/
[cc-by-nc-image]: https://licensebuttons.net/l/by-nc/4.0/88x31.png
[cc-by-nc-shield]: https://img.shields.io/badge/License-CC%20BY--NC%204.0-lightgrey.svg