I needed an excuse to make a word cloud shaped like a brain and I finally found one. Who said dreams don’t come true?
But in all seriousness, I learned a couple of things about how to work with text data, especially short text across multiple languages and I’ve shared that here:
https://neurofrontiers.blog/how-people-find-us/
#WordCloud #TextData #DataAnalysis #DataIsBeautiful #multilingual
Do your eyes still get stung by profanity in text data?
Well, there is an R script that enables you to handle it. Really useful for working with social media data.
Check out the script on github:
Master Advanced Analytics with SAS Viya | CoListy
Learn advanced analytics, machine learning, and AI with SAS Viya. Optimize models, forecasting, and more. | CoListy
#freeonlinelearning #colisty #courselist #sasviya #advancedanalytics #predictivemodeling #machinelearning #timeseriesforecasting #optimization #aialgorithms #generativeai #imagedata #textdata #streamingdata #modelops #trustworthyai
https://colisty.netlify.app/courses/sas-analytics_-getting-started/
A script I just wrote to process text files for a reconciliation for a vendor.
A script I just wrote to process text files for a reconciliation for a vendor.
In today's post, I discuss using `grep()` in R for extracting substrings from text data.
While `grep()` finds pattern matches, it doesn’t return the substrings directly. I explain combining it with `regexpr()` and `substr()`, or `gregexpr()` and `regmatches()` to achieve this.
Practical examples include filtering email addresses and data frames.
Post: https://www.spsanderson.com/steveondata/posts/2024-09-09/
In today's post, I discuss using `grep()` in R for extracting substrings from text data.
While `grep()` finds pattern matches, it doesn’t return the substrings directly. I explain combining it with `regexpr()` and `substr()`, or `gregexpr()` and `regmatches()` to achieve this.
Practical examples include filtering email addresses and data frames.
Post: https://www.spsanderson.com/steveondata/posts/2024-09-09/
In today's blog post, I introduce the `grep()` function in R, a key tool for searching patterns in text data.
It allows case-sensitive searches by default but can perform case-insensitive searches with the `ignore.case` argument.
This flexibility is essential for text mining, data cleaning, and analysis. I outline the basic syntax, usage examples, and common mistakes.
Post: https://www.spsanderson.com/steveondata/posts/2024-09-04/
#R #RStats #RProgramming #Programming #Coding #textdata #stringr #grep
In today's blog post, I introduce the `grep()` function in R, a key tool for searching patterns in text data.
It allows case-sensitive searches by default but can perform case-insensitive searches with the `ignore.case` argument.
This flexibility is essential for text mining, data cleaning, and analysis. I outline the basic syntax, usage examples, and common mistakes.
Post: https://www.spsanderson.com/steveondata/posts/2024-09-04/
#R #RStats #RProgramming #Programming #Coding #textdata #stringr #grep
Today's blog post discusses using OR logic with the `grep()` function in R, which enhances pattern matching in character vectors.
By employing the pipe symbol (`|`), users can search for multiple patterns simultaneously, such as `grep("apple|banana", text_vector)`.
It also highlights the option to ignore case with `ignore.case = TRUE`.
Post: https://www.spsanderson.com/steveondata/posts/2024-09-03/
#R #RStats #RProgramming #Programming #Coding #textdata #grep
Neurofrontiers
iCode2
CoListy
Steven Sanderson
Steven P. Sanderson II, MPH