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R Shiny Application Split Into Multiple Files

R Shiny Application Split Into Multiple Files

Blog, Data Science, Recent Posts
A R Shiny application can be completely made of just one file that includes your UI and server code. Depending on the application you're creating this can get messy as the number of lines grows. Splitting the app across multiple files also helps with debugging and being able to reuse code for another project. Separating the files for a Shiny Application also helps with version control For this post, the actual code and what it's doing will not be covered. The code is more of a placeholder and this is creating a project framework to start Shiny applications. Creating a new project The best practice is to create a new project for each application. This is simple with RStudio and using the "File" dropdown to select "New Project" Select "New Directory" Choose "Shiny We...
What is Data Science?

What is Data Science?

Recent Posts, Data Science
The data science field encompasses a wide scope, ranging from collecting data to data management, analysis, and visualization. Pulling all these areas together, a data scientist can gather information from obtained data and create visualizations to communicate results. Collect and organize data The collection and organization of data is arguably the most important factor within the data science field. You cannot do anything without having data to work with, so you must have a method of collecting data. This can be done independently/on your own, for example scraping the web or applications or even conducting a survey for respondents to take. You may also have access to data that has already been collected either by open source repositories, or sites such as Kaggle. You may get the d...
Renaming Columns with R

Renaming Columns with R

Recent Posts, Blog, Data Science
Often data you’re working with has abstract column names, such as (x1, x2, x3…). Typically, the first step I take when renaming columns with r is opening my web browser.  For some reason no matter the amount of times doing this it’s just one of those things. (Hoping that writing about it will change that) The dataset cars is data from the 1920s on "Speed and Stopping Distances of Cars". There is only 2 columns shown below. colnames(datasets::cars) [1] "speed" "dist" If we wanted to rename the column "dist" to make it easier to know what the data is/means we can do so in a few different ways. Using dplyr: cars %>% rename("Stopping Distance (ft)" = dist) %>% colnames() [1] "speed" "Stopping Distance (ft)" cars %>% rename("St...
How To Select Multiple Columns Using Grep & R

How To Select Multiple Columns Using Grep & R

Blog, Data Science, Recent Posts
Why you need to be using Grep when programming with R. There's a reason that grep is included in most if not all programming language to this day 44 years later from creation. It's useful and simple to use. Below is an example of using grep to make selecting multiple columns in R simple and easy to read. The dataset below has the following column names. names(data) # Column Names [1] "fips" "state" "county" "metro_area" [5] "population" "med_hh_income" "poverty_rate" "population_lowaccess" [9] "lowincome_lowaccess" "no_vehicle_lowaccess" "s_grocery" "s_supermarket" [13] "s_convenience" "s_specialty" "s_farmers_market" "r_fastfood" &#...
Turing In-Complete (part 1)

Turing In-Complete (part 1)

Recent Posts, Data Science, Hardware, Software
Before man-built machines that could be used to manually calculate all the same mathematical problems we now regard as computation, we – humans were regarded as the “computers”, not the artificial machines. This explains the label “manually” calculated. Man built the machines. This has only been true for a relatively short period of time when compared to the timeline man has existed in the current evolutionary state. This technology goes back much farther than the existence of our most popular desktop pc, laptops, tablets, or smartphones. Major developments in the twentieth century progressed at a very rapid pace, not with the help of Extraterrestrial beings, but by some very brilliant humans. Maybe you could make a case for “math” from outer space in ancient history, and you’d be technic...