Publications by Patrick Ford
Winning Small
Lottery Roll-Down Mathematics: Winfall Lottery vs. UK National Lottery Introduction In the movies and real life, there have been cases where savvy players identified opportunities to profit from lottery roll-downs. One famous example is depicted in the film Jerry and Marge Go Large, which was based on the real-life story of Jerry Selbee exploitin...
3238 sym 1 tbl
Didactic Paradoxes Observed in the Management of Euclid's Theorems
# Load necessary libraries pacman::p_load(pacman, ggplot2, igraph, dplyr, readr) # Load datasets paradox_data <- read_csv("paradox_data.csv") ## Rows: 7 Columns: 2 ## ── Column specification ───────────────────────────────────────────────────�...
19 sym Python (4277 sym/12 pcs) 4 img
Douay-Rheims Bible: Sentiment Analysis (a)
Load required libraries pacman::p_load(pacman, tidytext, dplyr, tidyr, ggplot2, readr, topicmodels, udpipe, gridExtra, wordcloud, RColorBrewer, quanteda, quanteda.textstats) Load the CSV file bible_data <- read_csv(“Douay_Rheims_Bible2.csv”) Rename columns colnames(bible_data) <- c(“Book”, “Chapter”, “Verse”, “Verse_Text”) Ad...
4042 sym
Douay-Rheims Bible: Sentiment Analysis (b)
Load required libraries pacman::p_load(pacman, tidytext, dplyr, tidyr, ggplot2, readr, wordcloud, RColorBrewer, udpipe) Load the CSV file bible_data <- read_csv(“Douay_Rheims_Bible2.csv”) Rename columns for easier reference colnames(bible_data) <- c(“Book”, “Chapter”, “Verse”, “Verse_Text”) Bigram Analysis Tokenize into bigr...
1397 sym
Modern Slavery
Modern slavery encompasses practices such as forced labour, forced marriage, debt bondage, human trafficking, and the exploitation of children. # Load necessary libraries pacman::p_load(readr, ggplot2, dplyr, tidyr, viridis, ggthemes, RColorBrewer, countrycode, gridExtra) # Load the dataset data <- read.csv("Age-of-Sexual-Consent.csv") # Clean co...
194 sym Python (10516 sym/10 pcs) 4 img
Quran Sentiment Analysis
# Load required libraries pacman::p_load(pacman, tidytext, dplyr, tidyr, ggplot2, readr, topicmodels, udpipe, gridExtra, wordcloud, RColorBrewer, quanteda, quanteda.textstats) # Specify the CSV file name csv_file <- "Quran_english.csv" # Load the CSV file text_data <- read_csv(csv_file, col_names = FALSE) ## Rows: 6237 Columns: 4 ## ── Column...
35 sym Python (31387 sym/25 pcs) 7 img
7 x 3D Surface Plots
# Load necessary libraries pacman::p_load(pacman, plotly, dplyr, viridis, akima) # List of file names with corresponding NCEI Accession numbers file_list <- list( "SAOcean20140607_20140717.csv" = "0157403", "SAOcean20170205_20170501.csv" = "0184841", "SAOcean20190107_20190122.csv" = "0208364(a)", "SAOcean20190223_20190414.csv" = "0208364(b...
4 sym
NCEI 0157403
# Load required libraries pacman::p_load(pacman, dplyr, ggplot2, lubridate, gridExtra, viridis, tidyr, maps) # Load the dataset data <- read.csv("SAOcean20140607_20140717.csv") # Rename the time column to match the expected format names(data)[names(data) == "TIME_UTC_hh.mm.ss"] <- "TIME_UTC_hh:mm:ss" # Convert date and time to proper datetime fo...
6 sym Python (7751 sym/2 pcs) 1 img
NCEI 0184481
# Load required libraries pacman::p_load(pacman, dplyr, ggplot2, lubridate, gridExtra, viridis, tidyr, maps) # Load the dataset data <- read.csv("SAOcean20170205_20170501.csv") # Rename the time column to match the expected format names(data)[names(data) == "TIME_UTC_hh.mm.ss"] <- "TIME_UTC_hh:mm:ss" # Convert date and time to proper datetime fo...
6 sym Python (7750 sym/2 pcs) 1 img
NCEI 0208364(a)
# Load required libraries pacman::p_load(pacman, dplyr, ggplot2, lubridate, gridExtra, viridis, tidyr, maps) # Load the dataset data <- read.csv("SAOcean20190107_20190122.csv") # Rename the time column to match the expected format names(data)[names(data) == "TIME_UTC_hh.mm.ss"] <- "TIME_UTC_hh:mm:ss" # Convert date and time to proper datetime fo...
6 sym Python (7747 sym/2 pcs) 1 img