3 - Data Visualization & Grouped Barplots [JuliaLang for Categorical Data]
#shorts Welcome back to Categorical Data Analysis with Julia! In this video, we'll cover a common scenario of data visualization for categorical data that involves the comparison of two categorical variables. ... https://www.youtube.com/watch?v=M5Cj4o3QiiM
Following the R-Ladies tutorial, to extract those columns whose names end with "e" or start with "desc" you have the corresponding functions, while checking whether there are columns that include an underscore in their name, you can use the contains() function.
Julia apart from its own startswith() and endswith() functions allows the direct use of regular expressions for doing these string-related column selections within the select() function.
Link to the ikea dataset:
https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-11-03/ikea.csv
Ladies Freiburg (Kyla McConnell and Julia Müller) - Tidy Data: Zero to sHero {Part 2}:
https://www.youtube.com/watch?v=ivSgLWKhNrw
R-Ladies material on github:
https://github.com/rladies/meetup-presentations_freiburg/tree/master/2021-02-17_tidydata_ZerotoShero
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https://www.youtube.com/watch?v=mesFqSQGV4o
This is a newer version of the video on the GLC.sample package uploaded earlier, completely rewritten for beginners.
After explaining in simple terms what an R package is, the tutorial guides you through the installation of the package.
0:11 - Why use the GLC.sample package
0:37 - What is an R package?
0:55 - The contents of the GLC.sample package
1:36 - Two steps in using an R package
2:19 - Installing the GLC.sample package
4:44 - Loading the GLC.sample package
5:01 - Browsing through the GLC.sample package
6:32 - Code summary
Download link of the Greek Learner Corpus site on Clarin:
https://inventory.clarin.gr/resources/browse/greek-learner-corpus-uam-corpus-tool-version-3/7d9c64c0c83311e6b526aa3fc6ebde2ceadb41214f994fb9bc568e74a6fe3edb/
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https://www.youtube.com/watch?v=8peOp_ghmDw
YT video JuliaLang code: https://gist.github.com/atantos/40c29e8ce72e4bbfab4ba5a337d01725
Official Tidier.jl webpage:
https://tidierorg.github.io/Tidier.jl/dev/
Singh Karandeep's github account:
https://github.com/kdpsingh
Julia Sigle personal web page:
https://juliasilge.com/
Today, we'll handle a real-world data analysis scenario. We are going to clean a horror movies dataset and prepare it for calculating movie similarities using cosine distance based on OpenAI embeddings of the movies' overviews.
CHAPTERS:
0:00 Tidyerverse and Tidier.jl
1:11 Hoor movies dataset
1:30 Julia Silge's R code
1:53 CCleaning the dataset with and without Tidier.jl
5:45 Fetching the OpenAI embeddings
7:10 Preparing the embeddings matrix
10:20 Compting the cosine distance
11:10 Movies closer/distant to the movie "Belbo the Clown"
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https://www.youtube.com/watch?v=BFKubJwDKtw
Welcome to this video on the 5 key terms used in any study that employs statistical methods! Often introduced within the context of advanced topics like parameter estimation or probabilities, these terms may seem familiar, yet they often lead to uncertainty in their application until later in the academic year. Today, we're setting a solid foundation for these concepts, crucial for our upcoming videos on using R for statistical analysis.
0:00 - Intro to the 5 key terms
0:29 - On "Population"
1:36 - On "Sample"
2:18 - On "Parameter"
2:57 - On "Statistic"
3:46 - On "Distribution"
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https://www.youtube.com/watch?v=5yp57NmGyW4
In this video you will learn how to navigate your file system programmatically with R. All the necessary concepts are explained clearly by using tree representations of file system.
To that end, you will learn what an absolute and a relative file path is and how to use it with the following functions in R:
getwd()
setwd()
list.files()
list.dirs()
file.info()
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https://www.youtube.com/watch?v=twiac_hSSGQ
In this video you will see a) what an R script is, b) why it is useful when using R and c) how to write, load and run an R script on RStudio.
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https://www.youtube.com/watch?v=o3yuy4knAJM
#shorts
Welcome back to Categorical Data Analysis with Julia! In this video, we'll use cross-tabulations as a means for descriptive statistics for categorical data.
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https://www.youtube.com/watch?v=GxFbBXqECr8