worldcup
qcoder
worldcup | qcoder | |
---|---|---|
6 | 2 | |
169 | 125 | |
- | 1.6% | |
6.5 | 0.0 | |
10 months ago | 7 months ago | |
HTML | HTML | |
- | GNU General Public License v3.0 only |
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worldcup
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Generate Data Warehouse
Hi guys, I have a school project for building a Data warehouse using an open-source dataset. I currently dive into one dataset which is The Fjelstul World Cup Database (Github: https://github.com/jfjelstul/worldcup). This dataset has multiple tables which combine a variety of properties. It's hard to figure out the whole following process to build a Dataware house from scratch. I just get some ideas and make out a sample of this. Can you guys help me examine that? What are the best ways to build Fact and Dimension tables from this generous dataset? What properties and table I should put in that case?
- Where to find database of World Cup penalty statistics? Including penalties awarded and the score line of when this happened
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[OC] Brazil and Argentina are the top goal-scorers in World Cup history.
Source: Fjelstul World Cup Database
- Ask about Day 5 of #25daysofDAXFridays
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Announcing the 25 days of DAX Fridays! second edition!
let Source = Web.BrowserContents("https://github.com/jfjelstul/worldcup/tree/master/data-csv"), #"Extracted Table From Html" = Html.Table( Source, {{"FileName", ".js-navigation-open.Link\-\-primary"}}, [RowSelector = ".Box-row + *"] ), fxCSVs = (FileName as text) as table => let Source = Csv.Document( Web.Contents( "https://raw.githubusercontent.com/jfjelstul/worldcup/master/data-csv/" & FileName ), [Delimiter = ",", Encoding = 65001, QuoteStyle = QuoteStyle.None] ), #"Promoted Headers" = Table.PromoteHeaders(Source, [PromoteAllScalars = true]) in #"Promoted Headers", #"Invoked Custom Function" = Table.AddColumn( #"Extracted Table From Html", "CSV_Data", each fxCSVs([FileName]) ) in #"Invoked Custom Function"
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Ask about Day 1 of #25daysofDAXFridays
= Csv.Document(Web.Contents("https://github.com/jfjelstul/worldcup/blob/master/data-csv/award_winners.csv"),[Delimiter=",", Encoding=65001, QuoteStyle=QuoteStyle.None])
qcoder
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[R] Qualitative analysis software
Because we're on a statistics subreddit, I have to mention there are a handful of packages for doing qualitative work in R - RQDA, Q-Coder, some others - but I would not recommend it if you're not already familiar with R, or at least some programming language. There are graphical interfaces that will serve you well.
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[Q] Does anyone use R to code qualitative data?
qcoder is also out there. It's still under active maintenance, but it's not on CRAN. It has a handy user interface, but you can obviously insert the qual tags yourself.
What are some alternatives?
football_analytics - 📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
QualCoder - Qualitative data analysis for text, images, audio, video. Cross platform. Python 3.10 or newer and PyQt6.
sofifa-web-scraper - It has over 18k detailed players info and stats from EA FC 24 scrapped from SoFIFA.com.
tidytext - Text mining using tidy tools :sparkles::page_facing_up::sparkles:
FielDHub - FielDHub is an R Shiny design of experiments (DOE) app that aids in the creation of traditional, unreplicated, augmented and partially replicated (p-rep) designs applied to agriculture, plant breeding, forestry, animal and biological sciences.
trackdown - R package for collaborative writing and editing of R Markdown (or Sweave) documents in Google Docs.
drat - Drat R Archive Template
webR-quarto-demos - Experiments with generating a standalone Quarto Document using Web R