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.Rhistory
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install.packages("renv")
renv::restore()
renv::init()
renv::restore()
renv::restore
renv::restore()
renv::restore()
renv::status()
renv::restore()
# Sample data frame with HTML links
df <- data.frame(
Title = c(
"[EARL 2024](https://www.ascent.io/earl)",
"[Shiny in Production 2024](https://shiny-in-production.jumpingrivers.com/)",
"[IFoA Life Conference 2024](https://actuaries.org.uk/LifeConference2024/)",
"[2024 Government & Public Sector R Conference](https://www.rstats.ai/gov)"
),
StartDate = c("September 4, 2024", "October 9, 2024", "October 14, 2024", "October 29, 2024"),
end_date = c("September 5, 2024", "October 10, 2024", "October 16, 2024", "October 30, 2024"),
location = c("Brighton", "Newcastle upon Tyne", "Manchester", "Washington D.C."),
type = c("Conference", "Conference", "Conference", "Conference"),
stringsAsFactors = FALSE
)
# Load necessary libraries
library(gt)
# Create a gt table and use fmt_markdown() to render HTML links
gt_table <- gt(df) %>%
cols_label(
Title = "Title",
StartDate = "Start Date",
end_date = "End Date",
location = "Location",
type = "Type",
) %>%
# Render the 'Link' column as HTML using fmt_markdown()
fmt_markdown(columns = c(Title))
# Print the gt table
gt_table
# Sample data frame with HTML links
df <- data.frame(
Title = c(
"[EARL 2024](https://www.ascent.io/earl)",
"[Shiny in Production 2024](https://shiny-in-production.jumpingrivers.com/)",
"[IFoA Life Conference 2024](https://actuaries.org.uk/LifeConference2024/)",
"[2024 Government & Public Sector R Conference](https://www.rstats.ai/gov)"
),
StartDate = c("Sept 4, 2024", "Oct 9, 2024", "Oct 14, 2024", "Oct 29, 2024"),
end_date = c("Sept 5, 2024", "Oct 10, 2024", "Oct 16, 2024", "Oct 30, 2024"),
location = c("Brighton, UK", "Newcastle upon Tyne, UK", "Manchester, UK", "Washington D.C., USA"),
type = c("Conference", "Conference", "Conference", "Conference"),
stringsAsFactors = FALSE
)
# Load necessary libraries
library(gt)
# Create a gt table and use fmt_markdown() to render HTML links
gt_table <- gt(df) %>%
cols_label(
Title = "Title",
StartDate = "Start Date",
end_date = "End Date",
location = "Location",
type = "Type",
) %>%
# Render the 'Link' column as HTML using fmt_markdown()
fmt_markdown(columns = c(Title))
# Print the gt table
gt_table
#| echo: false
#| warning: false
#| message: false
library(lubridate)
library(gt)
library(tidyverse)
# For every day of the conference, have data laid out in this way
Events <- df <- tibble(
title_link = c("https://www.ascent.io/earl", "https://shiny-in-production.jumpingrivers.com/", "https://actuaries.org.uk/LifeConference2024/", "https://www.rstats.ai/gov"),
title = c("EARL 2024", "Shiny in Production 2024", "IFoA Life Conference 2024", "2024 Government & Public Sector R Conference"),
start_date = c("September 4, 2024", "October 9, 2024", "October 14, 2024", "October 29, 2024"),
end_date = c("September 5, 2024", "October 10, 2024", "October 16, 2024", "October 30, 2024"),
location = c("Brighton", "Newcastle upon Tyne", "Manchester", "Washington D.C."),
type = c("Conference", "Conference", "Conference", "Conference"))
renv::status()
?renv::status()
renv::restore()
renv::status()
renv::status()
renv::restore()
install.packages("Matrix", type = "source")
?renv::status()
# Sample data frame with HTML links
df <- data.frame(
Title = c(
"[EARL 2024](https://www.ascent.io/earl)",
"[Shiny in Production 2024](https://shiny-in-production.jumpingrivers.com/)",
"[IFoA Life Conference 2024](https://actuaries.org.uk/LifeConference2024/)",
"[2024 Government & Public Sector R Conference](https://www.rstats.ai/gov)"
),
StartDate = c("Sept 4, 2024", "Oct 9, 2024", "Oct 14, 2024", "Oct 29, 2024"),
end_date = c("Sept 5, 2024", "Oct 10, 2024", "Oct 16, 2024", "Oct 30, 2024"),
location = c("Brighton, UK", "Newcastle upon Tyne, UK", "Manchester, UK", "Washington D.C., USA"),
type = c("Conference", "Conference", "Conference", "Conference"),
stringsAsFactors = FALSE
)
# Load necessary libraries
library(gt)
# Create a gt table and use fmt_markdown() to render HTML links
gt_table <- gt(df) %>%
cols_label(
Title = "Title",
StartDate = "Start Date",
end_date = "End Date",
location = "Location",
type = "Type",
) %>%
# Render the 'Title' column as HTML using fmt_markdown()
fmt_markdown(columns = c(Title))
# Add thick borders to the table
tab_options(
table.border.top.width = px(4),
table.border.bottom.width = px(4),
table.border.sides.width = px(4)
)
# Sample data frame with HTML links
df <- data.frame(
Title = c(
"[EARL 2024](https://www.ascent.io/earl)",
"[Shiny in Production 2024](https://shiny-in-production.jumpingrivers.com/)",
"[IFoA Life Conference 2024](https://actuaries.org.uk/LifeConference2024/)",
"[2024 Government & Public Sector R Conference](https://www.rstats.ai/gov)"
),
StartDate = c("Sept 4, 2024", "Oct 9, 2024", "Oct 14, 2024", "Oct 29, 2024"),
end_date = c("Sept 5, 2024", "Oct 10, 2024", "Oct 16, 2024", "Oct 30, 2024"),
location = c("Brighton, UK", "Newcastle upon Tyne, UK", "Manchester, UK", "Washington D.C., USA"),
type = c("Conference", "Conference", "Conference", "Conference"),
stringsAsFactors = FALSE
)
# Load necessary libraries
library(gt)
# Create a gt table and use fmt_markdown() to render HTML links
gt_table <- gt(df) %>%
cols_label(
Title = "Title",
StartDate = "Start Date",
end_date = "End Date",
location = "Location",
type = "Type",
) %>%
# Render the 'Title' column as HTML using fmt_markdown()
fmt_markdown(columns = c(Title))
# Add thick borders to the top and bottom of the table
tab_options(
table.border.top.width = px(4),
table.border.bottom.width = px(4),
table.border.top.color = "black",
table.border.bottom.color = "black",
# Add borders to all sides of the table
table.border.left.width = px(4),
table.border.right.width = px(4),
table.border.left.color = "black",
table.border.right.color = "black"
)
RecentEvents <- df <- data.frame(Title = c(
'<a href="https://www.r-project.org/conferences/" target="_blank" rel="noreferrer noopener">useR! 2024</a>',
'<a href="https://posit.co/conference/" target="_blank" rel="noreferrer noopener">posit::conf 2024</a>',
'Henrick Bengtsson invited to speak at the Swiss Re Conference',
'<a href="https://cascadiarconf.com/" target="_blank" rel="noreferrer noopener">Cascadia R Conference</a>',
'<a href="https://www.rstats.nyc/" target="_blank" rel="noreferrer noopener">New York R Conference</a>',
'<a href="https://www.rinfinance.com/" target="_blank" rel="noreferrer noopener">R/Finance 2024</a>',
'<a href="https://satrday-london-2024.jumpingrivers.com/" target="_blank" rel="noreferrer noopener">SatRdays London 2024</a>',
'<a href="https://www.r-consortium.org/r-medicine-quarto-for-reproducible-medical-manuscripts" target="_blank" rel="noreferrer noopener">R/Medicine: Quarto for Reproducible Medical Manuscripts</a>',
'<a href="https://www.r-consortium.org/new-webinar-tidy-finance-and-accessing-financial-data" target="_blank" rel="noreferrer noopener">New Webinar: Tidy Finance and Accessing Financial Data</a>',
'<a href="https://www.r-consortium.org/escape-the-data-dungeon-unlock-scalable-r-analytics-and-ml" target="_blank" rel="noreferrer noopener">Escape the Data Dungeon: Unlock Scalable R Analytics and ML</a>',
'<a href="https://www.r-consortium.org/from-vision-to-action-the-r-pfizer-r-center-of-excellence-led-journey-to-r-adoption" target="_blank" rel="noreferrer noopener">From Vision to Action: The Pfizer R Center of Excellence-led journey to R Adoption</a>',
'<a href="https://www.r-consortium.org/r-insurance-series-for-everyone-in-insurance-or-actuarial-science" target="_blank" rel="noreferrer noopener">R/Insurance Series: High performance programming in R</a>',
'<a href="https://www.r-consortium.org/r-insurance-series-for-everyone-in-insurance-or-actuarial-science" target="_blank" rel="noreferrer noopener">Dan Sjoberg presenting on Plotting Survival with {ggsurvfit}</a>',
'<a href="https://www.r-consortium.org/r-insurance-series-for-everyone-in-insurance-or-actuarial-science" target="_blank" rel="noreferrer noopener">R/Insurance Series: R performance culture</a>',
'<a href="https://www.r-consortium.org/r-insurance-series-for-everyone-in-insurance-or-actuarial-science" target="_blank" rel="noreferrer noopener">R/Insurance Series: From programming in R to putting R into production</a>',
'<a href="https://www.r-consortium.org/r-insurance-series-for-everyone-in-insurance-or-actuarial-science" target="_blank" rel="noreferrer noopener">R/Insurance Series: From Excel to Programming in R</a>',
'<a href="https://www.r-consortium.org/r-adoption-series-the-adoption-of-r-in-japans-pharma-industry-confirmation" target="_blank" rel="noreferrer noopener">The use of R in Japan’s Pharma Industry</a>'
),
Dates = c(
'July 8-11, 2024',
'August 12-14, 2024',
'June 25, 2024 – 7:00 AM ET',
'June 21-22, 2024',
'May 16-17, 2024',
'May 17-18, 2024',
'April 27, 2024',
'March 20, 2024',
'March 6, 2024',
'February 27, 2024',
'February 8, 2024',
'January 31, 2024',
'January 25, 2024',
'January 24, 2024',
'January 17, 2024',
'January 10, 2024',
'January 8, 2024'
),
Location = c(
'Salzburg, Austria',
'Seattle, WA, USA',
'Virtual',
'Seattle, WA, USA',
'New York City, NY, USA',
'Chicago, IL, USA',
'London, UK',
'Virtual',
'Virtual',
'Virtual',
'Virtual',
'Virtual',
'Virtual',
'Virtual',
'Virtual',
'Virtual',
'Virtual'
),
Type = c('Conference', 'Conference', 'Conference', 'Conference', 'Conference', 'Conference',
'Conference', 'Conference', 'Webinar', 'Webinar', 'Webinar', 'Webinar', 'Webinar', 'Webinar',
'Webinar', 'Webinar', 'Webinar'))
#view data frame
knitr::kable(df[1:17,], )
# Sample data frame with HTML links
df <- data.frame(
Title = c(
"[Optimize Portfolios using the Markowitz Model](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#optimize-portfolios-using-the-markowitz-model)",
"[EARL 2024](https://www.ascent.io/earl)",
"[Evaluate Performance using the Capital Asset Pricing Model](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#evaluate-performance-using-the-capital-asset-pricing-model)",
"[Shiny in Production 2024](https://shiny-in-production.jumpingrivers.com/)",
"[2024 Government & Public Sector R Conference](https://www.rstats.ai/gov)",
"[Analyze Companies using Financial Ratios](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#analyze-companies-using-financial-ratios)",
"[LatinR 2024](https://latinr.org/en/)",
"[Value Companies using Discounted Cash Flow Analysis](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#value-companies-using-discounted-cash-flow-analysis)"
),
StartDate = c("Sept 4, 2024", "Sept 4, 2024", "Oct 9, 2024", "Oct 9, 2024", "Oct 29, 2024", "Nov 6, 2024", "Nov 18, 2024", "Dec 4, 2024"),
end_date = c("Sept 4, 2024", "Sept 5, 2024", "Oct 9, 2024", "Oct 10, 2024", "Oct 30, 2024", "Nov 6, 2024", "Nov 22, 2024", "Dec 4, 2024"),
location = c("Virtual", "Brighton, UK", "Virtual", "Newcastle upon Tyne, UK", "Washington D.C., USA", "Virtual", "Virtual", "Virtual"),
type = c("Webinar", "Conference", "Webinar", "Conference", "Conference","Webinar", "Conference", "Webinar"),
stringsAsFactors = FALSE
)
# Load necessary libraries
library(gt)
# Create a gt table and use fmt_markdown() to render HTML links
gt_table <- gt(df) %>%
cols_label(
Title = "Title",
StartDate = "Start Date",
end_date = "End Date",
location = "Location",
type = "Type",
) %>%
tab_options(
heading.background.color = "lightblue",
column_labels.background.color = "lightblue",
column_labels.font.weight = "bold",
) %>%
# Render the 'Link' column as HTML using fmt_markdown()
fmt_markdown(columns = c(Title))
# Print the gt table
gt_table
suppressPackageStartupMessages({
library(dplyr)
library(gt)
})
df <- data.frame(
Benefits = c("One seat on the Board of Directors with full voting rights", "One seat on the ISC with full voting rights", "Elect Silver representatives to the Board and ISC (1 Board seat per 3 Silver members, 1 ISC seat for all Silver members)", "Company logo on R Consortium website and collateral", "R Consortium logo on company website", "Membership dues (annually)"),
Platinum = c("Check", "Check", "None", "Check", "Check", "US$100,000"),
Silver = c("None", "None", "Check", "Check", "Check", "100+ FTE US $25,000 <100 FTE / non-profits, universities US $10,000"),
stringsAsFactors = FALSE
)
df <- df |>
dplyr::mutate(
Platinum = case_when(Platinum == "Check" ~ "check", Platinum == "None" ~ "xmark",TRUE ~ Platinum )
) |>
dplyr::mutate(
Silver = case_when(Silver == "Check" ~ "check", Silver == "None" ~ "xmark",TRUE ~ Silver )
)
gt(df) %>%
fmt_icon(columns = c(Platinum, Silver), rows = c(1:5), fill_color = c("check" = "green", "xmark" = "darkred")) %>%
cols_label(
Benefits = "Benefits by member class",
Platinum = "Platinum",
Silver = "Silver"
) %>%
tab_options(
heading.background.color = "lightblue",
column_labels.background.color = "lightblue",
column_labels.font.weight = "bold",
table.font.size = "14px",
column_labels.font.size = "16px"
) %>%
cols_align(align="center", columns=c(Platinum, Silver)) %>%
opt_horizontal_padding(scale = 3) %>%
opt_vertical_padding(scale = 2)
# Sample data frame with HTML links
df <- data.frame(
Title = c(
"[Evaluate Performance using the Capital Asset Pricing Model](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#evaluate-performance-using-the-capital-asset-pricing-model)",
"[Shiny in Production 2024](https://shiny-in-production.jumpingrivers.com/)",
"[2024 Government & Public Sector R Conference](https://www.rstats.ai/gov)",
"[Analyze Companies using Financial Ratios](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#analyze-companies-using-financial-ratios)",
"[LatinR 2024](https://latinr.org/en/)",
"[Value Companies using Discounted Cash Flow Analysis](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#value-companies-using-discounted-cash-flow-analysis)"
),
dates = c("Oct 9, 2024", "Oct 9-10, 2024",
"Oct 29-30, 2024", "Nov 6, 2024", "Nov 18-22, 2024", "Dec 4, 2024"),
location = c("Virtual", "Newcastle upon Tyne, UK", "Washington D.C., USA", "Virtual", "Virtual", "Virtual"),
icon = c("Webinar", "Conference", "Conference","Webinar", "Conference", "Webinar"),
Type = c("Webinar", "Conference", "Conference","Webinar", "Conference", "Webinar"),
stringsAsFactors = FALSE
)
df <- df |>
dplyr::filter(icon %in% c("Conference", "Webinar")) |>
dplyr::mutate(
icon = ifelse(icon == "Webinar", "chalkboard-user", "handshake")
)
# Load necessary libraries
library(gt)
# Create a gt table and use fmt_markdown() to render HTML links
gt_table <- gt(df) %>%
fmt_icon(columns = icon) %>%
cols_label(
Title = "Title",
dates = "Dates",
location = "Location",
icon = "Type",
) %>%
tab_options(
heading.background.color = "lightblue",
column_labels.background.color = "lightblue",
column_labels.font.weight = "bold",
table.font.size = "14px",
column_labels.font.size = "16px"
) %>%
opt_horizontal_padding(scale = 3) %>%
opt_vertical_padding(scale = 2) %>%
#
cols_merge(columns = c(Type, icon),
pattern="{2} {1}") %>%
# Render the 'Link' column as HTML using fmt_markdown()
fmt_markdown(columns = c(Title))
# Print the gt table
gt_table
# Sample data frame with HTML links
df <- data.frame(
Title = c(
"[Evaluate Performance using the Capital Asset Pricing Model](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#evaluate-performance-using-the-capital-asset-pricing-model)",
"[Shiny in Production 2024](https://shiny-in-production.jumpingrivers.com/)",
"[2024 Government & Public Sector R Conference](https://www.rstats.ai/gov)",
"[R/Pharma 2024](https://rinpharma.com/)",
"[Analyze Companies using Financial Ratios](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#analyze-companies-using-financial-ratios)",
"[LatinR 2024](https://latinr.org/en/)",
"[Value Companies using Discounted Cash Flow Analysis](https://rconsortium.netlify.app/webinars/tidy-finance-webinar-series#value-companies-using-discounted-cash-flow-analysis)"
),
dates = c("Oct 9, 2024", "Oct 9-10, 2024",
"Oct 29-30, 2024", "Oct 29-31, 2024", "Nov 6, 2024", "Nov 18-22, 2024", "Dec 4, 2024"),
location = c("Virtual", "Newcastle upon Tyne, UK", "Washington D.C., USA", "Virtual", "Virtual", "Virtual", "Virtual"),
icon = c("Webinar", "Conference", "Conference", "Conference", "Webinar", "Conference", "Webinar"),
Type = c("Webinar", "Conference", "Conference", "Conference", "Webinar", "Conference", "Webinar"),
stringsAsFactors = FALSE
)
df <- df |>
dplyr::filter(icon %in% c("Conference", "Webinar")) |>
dplyr::mutate(
icon = ifelse(icon == "Webinar", "chalkboard-user", "handshake")
)
# Load necessary libraries
library(gt)
# Create a gt table and use fmt_markdown() to render HTML links
gt_table <- gt(df) %>%
fmt_icon(columns = icon) %>%
cols_label(
Title = "Title",
dates = "Dates",
location = "Location",
icon = "Type",
) %>%
tab_options(
heading.background.color = "lightblue",
column_labels.background.color = "lightblue",
column_labels.font.weight = "bold",
table.font.size = "14px",
column_labels.font.size = "16px"
) %>%
opt_horizontal_padding(scale = 3) %>%
opt_vertical_padding(scale = 2) %>%
#
cols_merge(columns = c(Type, icon),
pattern="{2} {1}") %>%
# Render the 'Link' column as HTML using fmt_markdown()
fmt_markdown(columns = c(Title))
# Print the gt table
gt_table