https://github.com/akbaritabar/parallelised-analysis-of-large-scale-bibliometric-and-text-data

Materials for the lecture on "Parallelised analysis of large-scale bibliometric and text data (with Dask in Python, DuckDB and DBeaver in SQL)"
https://github.com/akbaritabar/parallelised-analysis-of-large-scale-bibliometric-and-text-data

Last synced: 6 days ago
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Materials for the lecture on "Parallelised analysis of large-scale bibliometric and text data (with Dask in Python, DuckDB and DBeaver in SQL)"

• Host: GitHub
• URL: https://github.com/akbaritabar/parallelised-analysis-of-large-scale-bibliometric-and-text-data
• Owner: akbaritabar
• License: gpl-3.0
• Created: 2022-10-25T13:46:37.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-07-13T14:01:03.000Z (4 months ago)
• Last Synced: 2024-07-13T15:22:32.960Z (4 months ago)
• Language: Python
• Size: 9.44 MB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: Readme.md
  • License: LICENSE

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# Materials for the lecture on "Parallelised analysis of large-scale bibliometric and text data (with Dask in Python, DuckDB and DBeaver in SQL)"

Speaker:

- **Aliakbar Akbaritabar**, research scientist at the Max Planck Institute for Demographic Research (MPIDR), GitHub: [https://github.com/akbaritabar](https://github.com/akbaritabar), ([email protected])

## Instructions for participants

0. Please clone or download this repository ([https://github.com/akbaritabar/Parallelised-analysis-of-large-scale-bibliometric-and-text-data](https://github.com/akbaritabar/Parallelised-analysis-of-large-scale-bibliometric-and-text-data.git)) by clicking on the green button on top right (see photo)

![Clone or download](99_images/download_from_github.png)

1. Please go over the presentation files in the `2_presentations` directory, some are *self-study* materials that in combination with Python and R scripts in `0_code` directory should help you set-up and get started. You can ask your clarification questions by email or during the Q&A sessions.

2. For `Python` users to replicate the results, you should follow steps outlined in `0_code\01_Required_installation_setup_python.md` to have all necessary libraries installed.

3. For `R` users to replicate the results, you should follow steps outlined in `0_code\02_Required_installation_setup_R.md` to have all necessary libraries installed.