Publications by Patrick Ford
eBay Sales
Chart explanation, below code. pacman::p_load(pacman,tidyverse,gridExtra,zoo) # Read the data ebay_data <- read_csv("eBay.csv", col_types = cols( Year = col_character(), `Billion USD` = col_double() )) # Convert Year to a date format for easier plotting ebay_data <- ebay_data %>% separate(Year, into = c("Year", "Quarter"), sep = " ") %>% ...
2667 sym Python (1987 sym/2 pcs) 1 img
Alibabas Sales
Chart explanation,below code. pacman::p_load(pacman,tidyverse,gridExtra,zoo) # Read the data alibaba_data <- read_csv("Alibaba.csv", col_types = cols( Year = col_character(), `Billion CYD` = col_double() )) # Convert Year to a date format for easier plotting alibaba_data <- alibaba_data %>% separate(Year, into = c("Year", "Quarter"), sep = ...
2843 sym Python (2023 sym/2 pcs) 1 img
Amazon Sales
Chart explanation, below code. pacman::p_load(pacman,tidyverse,gridExtra,zoo) # Read the data amazon_data <- read_csv("Amazon.csv", col_types = cols( Year = col_character(), `Billion USD` = col_double() )) # Convert Year to a date format for easier plotting amazon_data <- amazon_data %>% separate(Year, into = c("Year", "Quarter"), sep = " "...
2608 sym Python (2011 sym/2 pcs) 1 img
Travelling Salesman Problem 1
Travelling Salesman Problem: Visit Each City Once In The Shortest Route and Finish Where You Started. pacman::p_load(pacman,geosphere,GA) # Read the CSV file correctly cities <- read.csv("UK_Cities.csv", header = TRUE, sep = ",") # Split the City, Latitude, Longitude, and Population into separate columns cities_split <- do.call(rbind, strsplit(as...
1856 sym Python (5739 sym/16 pcs)
Travelling Salesman Problem 3
Travelling Salesman Problem: Visit Each City Once In The Shortest Route and Finish Where You Started. pacman::p_load(pacman,geosphere,GA) # Read the CSV file as a single column cities_raw <- read.csv("UK_Cities.csv", header = TRUE, sep = ",") # Split the single column into multiple columns cities <- data.frame(do.call('rbind', strsplit(as.charact...
2680 sym
Travelling Salesman Problem 4
Travelling Salesman Problem: Visit Each City Once In The Shortest Route and Finish Where You Started. # Load necessary packages pacman::p_load(pacman, geosphere, leaflet) # Read the CSV file correctly cities <- read.csv("UK_Cities.csv", header = TRUE, sep = ",") # Split the City, Latitude, Longitude, and Population into separate columns cities_sp...
125 sym Python (8393 sym/17 pcs)
Travelling Salesman Problem 2
Travelling Salesman Problem: Visit Each City Once In The Shortest Route and Finish Where You Started. pacman::p_load(pacman,geosphere, GA) # Load the cities data cities <- read.csv("UK_Cities.csv", header = TRUE, sep = ",") # Split the City, Latitude, Longitude, and Population into separate columns cities_split <- do.call(rbind, strsplit(as.chara...
123 sym
Total Influenza Cases Over Time
# Load necessary libraries pacman::p_load(pacman, readr, dplyr, ggplot2, reshape2, scales) # Read the CSV file with appropriate encoding my_data <- read_csv("VIW_FNT.csv", locale = locale(encoding = "UTF-8")) ## Rows: 156291 Columns: 49 ## ── Column specification ───────────────────────────...
7 sym Python (2512 sym/3 pcs) 1 img
FluNet
# Load necessary libraries pacman::p_load(pacman, readr, dplyr, skimr, naniar, ggplot2, tidyr, patchwork) # Load the dataset with appropriate encoding my_data <- read_csv("VIW_FNT.csv", locale = locale(encoding = "UTF-8")) ## Rows: 156291 Columns: 49 ## ── Column specification ──────────────────────�...
96 sym 4 img 4 tbl
Box Plots - Sheet 2
# Load necessary libraries library(ggplot2) library(tidyr) # Read data from CSV file Sheet2 <- read.csv("Sheet2.csv") # Convert `% Improved`, `% Unchanged`, `% Worsened` to numeric Sheet2$X..Improved <- as.numeric(sub("%", "", Sheet2$X..Improved)) Sheet2$X..Unchanged <- as.numeric(sub("%", "", Sheet2$X..Unchanged)) Sheet2$X..Worsened <- as.numeri...
5 sym R (1055 sym/1 pcs) 1 img