A recipe on elementary techniques to explore categorical data

Provide guidance to process text data with Python, including text cleaning, feature engineering, label classification and etc.

regarding .DS_Store files like this: https://github.com/NCSU-Libraries/data-science-cookbook/blob/main/.DS_Store

I think these are created by GitHub Desktop for Mac OS. @csbailey5t Any thoughts about a .gitignore file?

And apparently we would need a rule to ignore a previously committed file?
$ echo debug.log >> .gitignore $ git rm --cached debug.log rm 'debug.log' $ git commit -m "Start ignoring debug.log"

The following Colab notebook includes a code snippet that I created to convert an HDF5 file to a TIFF file. Converting an HDF file to one or more TIFF files is necessary for visualization and/or spatial analysis of the data within GIS softwares/packages.

This particular code snippet uses data from the Global Fire Emissions Database (https://www.geo.vu.nl/~gwerf/GFED/GFED4/) and converts the data for the month of June into a TIFF file.

https://colab.research.google.com/drive/1OHmjAacJZW7rlmSGR73D1pJo8Mppf2G3?usp=sharing

The above notebook was created last semester to help a patron.

Transforming data downloaded from Crimson Hexagon into a hashtag network graph. In this hashtag co-occurrence graph, the nodes are the hashtags in the corpus of tweets, and the edges represent co-occurrences of two hashtags in the same tweet.

Resources

python notebook from former Consultant https://github.com/shreyasabu22/Hashtag-Network-Graph

https://trello-attachments.s3.amazonaws.com/5581bcf471e9c010571d7237/5d8c2c75d923b465fa8b9c7c/fe7d59056691e0c7c943e4a08bf7c91f/hashtag_test_5.html

Here is a Colab notebook for timestamp-based filtering of Pandas data frames. The code includes converting specific columns in pandas data frame to "datetime" type. This is a code snippet that I used to help a patron last semester.

Colab Notebook: https://colab.research.google.com/drive/1L-3vUhsFkKmUYrDhJJAuV3Uh1o56uHRZ?usp=sharing
Data: https://drive.google.com/drive/folders/1oWS1yut249Ur_F5i5pcGcwm6Fd4UtEWf?usp=sharing

Colab notebook from former data science consultant https://github.com/xn2333/OpenCV/blob/master/Seminar_Image_Processing_in_Python.ipynb

I would like to add code that a patron worked out to get his code running in parallel on HPC cluster. I would confirm this is ok with him and indicate code was written by him and his sources.

I think it could be very helpful for people encountering issues with HPC parallel code.

A recipe for elementary exploratory data analysis of quantitative (continuous or discrete) data.

Introduce the basic syntax of SQL queries

• select, join, where, order, limit...
• window function

Queries example:
https://github.com/rhuang44/SQL_cookbook/blob/main/SQL_album.sql

A recipe for using theme_update() and theme_replace() with ggplot