Publications by Jamal Rogers
Applied Data Science: Module 1 Lesson 2 Application
Table of contents ggplot2 + dplyr Module 1 Lesson 2 Application Author Jamal Rogers Published May 12, 2023 library(nycflights13) library(tidyverse) ggplot2 + dplyr The relevant variables are: month, Date of departure carrier, Two letter carrier abbreviation air_time, Amount of time spent in the air, in minutes distance, Distance between ...
393 sym 1 img
Applied Data Science: Module 1 Lesson 3 Abstraction 1
Table of contents Why ensure your data is tidy? Tidy Data Author Jamal Rogers Published May 12, 2023 We shall use the built-in datasets from the tidyr package. library(tidyverse) There are three interrelated rules that make a dataset tidy: Each variable is a column; each column is a variable. Each observation is a row; each row is an obs...
1194 sym 1 img
Applied Data Science: Module 1 Lesson 3 Abstraction 2
Table of contents Data in column names Lengthening Data Author Jamal Rogers Published May 12, 2023 We shall use billboard built-in dataset from the tidyr package. We load the tidyverse to use tidyr. library(tidyverse) The principles of tidy data might seem so obvious that you wonder if you’ll ever encounter a dataset that isn’t tidy. ...
3705 sym 1 img
Applied Data Science: Module 1 Lesson 3 Abstraction 3
Widening Data Author Jamal Rogers Published May 12, 2023 We shall use cms_patient_experience built-in dataset from the tidyr package. We load the tidyverse to use tidyr. library(tidyverse) So far we’ve used pivot_longer() to solve the common class of problems where values have ended up in column names. Next we’ll pivot to pivot_wider(),...
1871 sym Python (4208 sym/9 pcs)
Applied Data Science: Module 1 Lesson 1 Application
Table of contents The mpg dataset Module 1 Lesson 1 Application Author Jamal Rogers Published May 11, 2023 library(palmerpenguins) library(tidyverse) The mpg dataset The relevant variables are: displ, a car’s engine size, in litres. hwy, a car’s fuel efficiency on the highway, in miles per gallon (mpg). class, type of car. ggplot(da...
468 sym 1 img
Applied Data Science: Module 1 Lesson 1 Abstraction 1
Table of contents Creating a ggplot Adding aesthetics and layers ggplot2 calls Data Visualization with ggplot2 Author Jamal Rogers Published May 11, 2023 Creating a ggplot First, we need to use the palmerpenquins library for the penguins dataset. We will also load the tidyverse library to use the gglot2 package. Additionally, the ggthemes p...
8761 sym 11 img
Applied Data Science: Module 1 Lesson 1 Abstraction 3
Table of contents A numerical and a categorical variable Two categorical variables Two numerical variables Three or more variables Visualizing Relationships with ggplot2 Author Jamal Rogers Published May 11, 2023 To visualize a relationship we need to have at least two variables mapped to aesthetics of a plot. In the following sections you ...
4908 sym 8 img
Applied Data Science: Module 1 Lesson 1 Abstraction 2
Table of contents A categorical variable A numerical variable Visualizing Distributions with ggplot2 Author Jamal Rogers Published May 11, 2023 We wil still use the palmerpenquins library for the penguins dataset and the tidyverse library for the gglot2 package. library(palmerpenguins) library(tidyverse) A categorical variable A variable...
3114 sym 6 img
Forecasting using Modeltime
Loading the Required Libraries for Modeling and Forecasting library(tidyverse) #data science library(tidymodels) #training algorithms library(lubridate) #transform to date class library(modeltime) #forecasting library(timetk) #bike_sharing_daily, plotting functions, splitting data Reading the Data tsdata <- bike_sharing_daily glimpse(tsdata)...
410 sym R (4089 sym/21 pcs)
Forecasting Poultry Gases Part 1
Loading the Required Libraries for Modeling and Forecasting library(tidyverse) library(tidymodels) library(lubridate) library(modeltime) library(timetk) Reading the Sensor Data from File sensordata <- read_csv("sensordata.csv") Data Wrangling sensordata <- sensordata %>% select(-sdataId, -Alarm, -ccsId, -gaitScore) %>% mutate(sDataDate ...
378 sym R (4332 sym/29 pcs) 15 img