data-raw/square_usa_data.R
In EmilHvitfeldt/tilemapr: R functions for square and hextile maps
states <- c("alabama", "alaska", "arizona", "arkansas", "california",
"colorado", "connecticut", "delaware", "district of columbia", "florida","georgia",
"hawaii", "idaho", "illinois", "indiana", "iowa", "kansas",
"kentucky", "louisiana", "maine", "maryland", "massachusetts",
"michigan", "minnesota", "mississippi", "missouri", "montana",
"nebraska", "nevada", "new hampshire", "new jersey", "new mexico",
"new york", "north carolina", "north dakota", "ohio", "oklahoma",
"oregon", "pennsylvania", "rhode island", "south carolina",
"south dakota", "tennessee", "texas", "utah", "vermont",
"virginia", "washington", "west virginia", "wisconsin", "wyoming")
# NPR
long <- c(8, 1, 3, 6, 2, 4, 11, 11, 10, 10, 9,
1, 3, 7, 7, 6, 5, 7, 6, 12, 10,
12, 9, 6, 7, 6, 4, 5, 3, 12, 10,
4, 10, 8, 5, 8, 5, 2, 9, 11, 9,
5, 7, 5, 3, 11, 9, 2, 8, 8, 4)
lat <- c(2, 8, 3, 3, 4, 4, 5, 4, 3, 1, 2,
1, 6, 6, 5, 5, 3, 4, 2, 8, 4,
6, 6, 6, 2, 4, 6, 4, 5, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 6, 3,
5, 3, 1, 4, 7, 4, 6, 4, 6, 5)
dat_npr <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "NPR")
# The New York Times
long <- c(7, 1, 3, 6, 1, 4, 11, 11, 9, 8, 8,
1, 3, 7, 8, 6, 5, 7, 5, 12, 10,
12, 8, 6, 6, 6, 3, 5, 2, 11, 11,
4, 10, 9, 4, 9, 5, 2, 10, 12, 9,
5, 7, 4, 3, 10, 8, 2, 8, 7, 4)
lat <- c(2, 7, 3, 3, 4, 4, 6, 4, 4, 1, 2,
2, 5, 5, 5, 5, 4, 4, 2, 8, 4,
7, 6, 6, 2, 4, 6, 5, 4, 7, 5,
3, 6, 3, 6, 5, 3, 5, 5, 6, 2,
6, 3, 2, 4, 7, 3, 6, 4, 6, 5)
dat_tnyt <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "The New York Times")
# 538
long <- c(7, 2, 2, 5, 1, 3, 10, 10, NA, 9, 8,
1, 2, 6, 6, 5, 4, 6, 5, 11, 9,
10, 7, 5, 6, 5, 3, 4, 2, 11, 9,
3, 9, 7, 4, 7, 4, 1, 8, 11, 8,
4, 6, 4, 2, 10, 8, 1, 7, 6, 3)
lat <- c(2, 1, 3, 3, 4, 4, 5, 4, NA, 1, 2,
1, 6, 6, 5, 5, 3, 4, 2, 8, 4,
6, 6, 6, 2, 4, 6, 4, 5, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 5, 3,
5, 3, 1, 4, 7, 4, 6, 4, 7, 5)
dat_538 <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "538")
# Propublica
long <- c(8, 2, 3, 6, 2, 4, 11, 11, NA, 10, 9,
1, 3, 7, 7, 6, 5, 7, 6, 12, 10,
11, 8, 6, 7, 6, 4, 5, 3, 12, 10,
4, 10, 8, 5, 8, 5, 2, 9, 12, 9,
5, 7, 5, 3, 11, 9, 2, 8, 6, 4)
lat <- c(2, 1, 3, 3, 4, 4, 5, 4, NA, 1, 2,
1, 6, 6, 5, 5, 3, 4, 2, 8, 4,
6, 6, 7, 2, 4, 6, 4, 5, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 5, 3,
5, 3, 1, 4, 7, 4, 6, 4, 6, 5)
dat_Propublica <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "Propublica")
# Bloomberg
long <- c(8, 1, 3, 6, 2, 4, 11, 11, NA, 10, 9,
1, 3, 7, 7, 6, 5, 7, 6, 12, 10,
11, 8, 6, 7, 6, 4, 5, 3, 12, 10,
4, 10, 10, 5, 8, 5, 2, 9, 12, 9,
5, 8, 6, 3, 11, 9, 2, 8, 7, 4)
lat <- c(2, 7, 3, 3, 4, 4, 5, 4, NA, 1, 2,
2, 6, 5, 4, 5, 3, 3, 2, 8, 4,
6, 6, 6, 2, 4, 6, 4, 4, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 6, 3,
5, 3, 1, 5, 7, 4, 6, 4, 6, 5)
dat_Bloomberg <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "Bloomberg")
# The Guardian
long <- c(8, 2, 3, 6, 2, 4, 12, 11, 11, 9, 9,
1, 3, 7, 8, 6, 5, 8, 6, 13, 12,
12, 8, 6, 7, 6, 4, 5, 3, 13, 11,
4, 10, 10, 5, 9, 5, 2, 10, 13, 10,
5, 7, 5, 3, 12, 10, 2, 9, 7, 4)
lat <- c(2, 8, 2, 3, 3, 3, 5, 5, 4, 1, 2,
1, 5, 4, 4, 5, 3, 3, 2, 8, 4,
6, 5, 6, 2, 4, 5, 4, 4, 7, 6,
2, 6, 3, 6, 4, 2, 4, 5, 6, 2,
5, 3, 1, 3, 7, 4, 5, 3, 5, 4)
dat_Guardian <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "The Guardian")
# Wall street journal
long <- c(7, 1, 2, 5, 1, 3, 11, 11, 9, 9, 8,
1, 2, 6, 7, 5, 4, 7, 5, 11, 10,
10, 7, 5, 6, 5, 3, 4, 2, 11, 10,
3, 9, 7, 4, 8, 4, 1, 9, 11, 8,
4, 6, 4, 2, 10, 9, 1, 8, 6, 3)
lat <- c(2, 8, 3, 3, 4, 4, 5, 4, 3, 1, 2,
1, 6, 4, 5, 5, 3, 4, 2, 8, 4,
6, 6, 6, 2, 4, 6, 4, 4, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 6, 3,
5, 3, 1, 5, 7, 4, 6, 4, 5, 5)
dat_wsj <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "Wall Street Journal")
# WNYC
long <- c(8, 1, 3, 6, 2, 4, 11, 10, 12, 10, 9,
1, 3, 7, 7, 6, 5, 8, 6, 12, 9,
12, 8, 6, 7, 6, 4, 5, 3, 11, 11,
4, 10, 10, 5, 8, 5, 2, 9, 12, 10,
5, 7, 5, 3, 10, 9, 2, 8, 7, 4)
lat <- c(2, 7, 3, 3, 4, 4, 5, 4, 2, 1, 2,
1, 6, 4, 5, 5, 3, 4, 2, 7, 4,
6, 6, 6, 2, 4, 6, 4, 5, 6, 4,
3, 5, 3, 6, 5, 2, 5, 5, 5, 2,
5, 3, 1, 4, 6, 3, 6, 3, 6, 5)
dat_wnyc <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "WNYC")
# The Marshall Project
long <- c(7, 1, 2, 5, 1, 3, 10, 9, NA, 10, 8,
2, 2, 6, 6, 5, 4, 7, 5, 11, 8,
11, 7, 5, 6, 5, 3, 4, 2, 10, 10,
3, 9, 9, 4, 7, 4, 1, 8, 11, 9,
4, 6, 4, 2, 9, 8, 1, 7, 6, 3)
lat <- c(2, 1, 3, 3, 4, 4, 5, 4, NA, 1, 2,
1, 6, 4, 5, 5, 3, 4, 2, 7, 4,
6, 6, 6, 2, 4, 6, 4, 5, 6, 4,
3, 5, 3, 6, 5, 2, 5, 5, 5, 2,
5, 3, 1, 4, 6, 3, 6, 3, 6, 5)
dat_marshall <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "The Marshall Project")
square_usa_data <- rbind(dat_538, dat_Bloomberg, dat_Guardian, dat_marshall,
dat_Propublica, dat_tnyt, dat_wnyc, dat_wsj, dat_npr)
EmilHvitfeldt/tilemapr documentation built on May 20, 2019, 5:09 p.m.
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states <- c("alabama", "alaska", "arizona", "arkansas", "california",
"colorado", "connecticut", "delaware", "district of columbia", "florida","georgia",
"hawaii", "idaho", "illinois", "indiana", "iowa", "kansas",
"kentucky", "louisiana", "maine", "maryland", "massachusetts",
"michigan", "minnesota", "mississippi", "missouri", "montana",
"nebraska", "nevada", "new hampshire", "new jersey", "new mexico",
"new york", "north carolina", "north dakota", "ohio", "oklahoma",
"oregon", "pennsylvania", "rhode island", "south carolina",
"south dakota", "tennessee", "texas", "utah", "vermont",
"virginia", "washington", "west virginia", "wisconsin", "wyoming")
# NPR
long <- c(8, 1, 3, 6, 2, 4, 11, 11, 10, 10, 9,
1, 3, 7, 7, 6, 5, 7, 6, 12, 10,
12, 9, 6, 7, 6, 4, 5, 3, 12, 10,
4, 10, 8, 5, 8, 5, 2, 9, 11, 9,
5, 7, 5, 3, 11, 9, 2, 8, 8, 4)
lat <- c(2, 8, 3, 3, 4, 4, 5, 4, 3, 1, 2,
1, 6, 6, 5, 5, 3, 4, 2, 8, 4,
6, 6, 6, 2, 4, 6, 4, 5, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 6, 3,
5, 3, 1, 4, 7, 4, 6, 4, 6, 5)
dat_npr <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "NPR")
# The New York Times
long <- c(7, 1, 3, 6, 1, 4, 11, 11, 9, 8, 8,
1, 3, 7, 8, 6, 5, 7, 5, 12, 10,
12, 8, 6, 6, 6, 3, 5, 2, 11, 11,
4, 10, 9, 4, 9, 5, 2, 10, 12, 9,
5, 7, 4, 3, 10, 8, 2, 8, 7, 4)
lat <- c(2, 7, 3, 3, 4, 4, 6, 4, 4, 1, 2,
2, 5, 5, 5, 5, 4, 4, 2, 8, 4,
7, 6, 6, 2, 4, 6, 5, 4, 7, 5,
3, 6, 3, 6, 5, 3, 5, 5, 6, 2,
6, 3, 2, 4, 7, 3, 6, 4, 6, 5)
dat_tnyt <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "The New York Times")
# 538
long <- c(7, 2, 2, 5, 1, 3, 10, 10, NA, 9, 8,
1, 2, 6, 6, 5, 4, 6, 5, 11, 9,
10, 7, 5, 6, 5, 3, 4, 2, 11, 9,
3, 9, 7, 4, 7, 4, 1, 8, 11, 8,
4, 6, 4, 2, 10, 8, 1, 7, 6, 3)
lat <- c(2, 1, 3, 3, 4, 4, 5, 4, NA, 1, 2,
1, 6, 6, 5, 5, 3, 4, 2, 8, 4,
6, 6, 6, 2, 4, 6, 4, 5, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 5, 3,
5, 3, 1, 4, 7, 4, 6, 4, 7, 5)
dat_538 <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "538")
# Propublica
long <- c(8, 2, 3, 6, 2, 4, 11, 11, NA, 10, 9,
1, 3, 7, 7, 6, 5, 7, 6, 12, 10,
11, 8, 6, 7, 6, 4, 5, 3, 12, 10,
4, 10, 8, 5, 8, 5, 2, 9, 12, 9,
5, 7, 5, 3, 11, 9, 2, 8, 6, 4)
lat <- c(2, 1, 3, 3, 4, 4, 5, 4, NA, 1, 2,
1, 6, 6, 5, 5, 3, 4, 2, 8, 4,
6, 6, 7, 2, 4, 6, 4, 5, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 5, 3,
5, 3, 1, 4, 7, 4, 6, 4, 6, 5)
dat_Propublica <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "Propublica")
# Bloomberg
long <- c(8, 1, 3, 6, 2, 4, 11, 11, NA, 10, 9,
1, 3, 7, 7, 6, 5, 7, 6, 12, 10,
11, 8, 6, 7, 6, 4, 5, 3, 12, 10,
4, 10, 10, 5, 8, 5, 2, 9, 12, 9,
5, 8, 6, 3, 11, 9, 2, 8, 7, 4)
lat <- c(2, 7, 3, 3, 4, 4, 5, 4, NA, 1, 2,
2, 6, 5, 4, 5, 3, 3, 2, 8, 4,
6, 6, 6, 2, 4, 6, 4, 4, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 6, 3,
5, 3, 1, 5, 7, 4, 6, 4, 6, 5)
dat_Bloomberg <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "Bloomberg")
# The Guardian
long <- c(8, 2, 3, 6, 2, 4, 12, 11, 11, 9, 9,
1, 3, 7, 8, 6, 5, 8, 6, 13, 12,
12, 8, 6, 7, 6, 4, 5, 3, 13, 11,
4, 10, 10, 5, 9, 5, 2, 10, 13, 10,
5, 7, 5, 3, 12, 10, 2, 9, 7, 4)
lat <- c(2, 8, 2, 3, 3, 3, 5, 5, 4, 1, 2,
1, 5, 4, 4, 5, 3, 3, 2, 8, 4,
6, 5, 6, 2, 4, 5, 4, 4, 7, 6,
2, 6, 3, 6, 4, 2, 4, 5, 6, 2,
5, 3, 1, 3, 7, 4, 5, 3, 5, 4)
dat_Guardian <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "The Guardian")
# Wall street journal
long <- c(7, 1, 2, 5, 1, 3, 11, 11, 9, 9, 8,
1, 2, 6, 7, 5, 4, 7, 5, 11, 10,
10, 7, 5, 6, 5, 3, 4, 2, 11, 10,
3, 9, 7, 4, 8, 4, 1, 9, 11, 8,
4, 6, 4, 2, 10, 9, 1, 8, 6, 3)
lat <- c(2, 8, 3, 3, 4, 4, 5, 4, 3, 1, 2,
1, 6, 4, 5, 5, 3, 4, 2, 8, 4,
6, 6, 6, 2, 4, 6, 4, 4, 7, 5,
3, 6, 3, 6, 5, 2, 5, 5, 6, 3,
5, 3, 1, 5, 7, 4, 6, 4, 5, 5)
dat_wsj <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "Wall Street Journal")
# WNYC
long <- c(8, 1, 3, 6, 2, 4, 11, 10, 12, 10, 9,
1, 3, 7, 7, 6, 5, 8, 6, 12, 9,
12, 8, 6, 7, 6, 4, 5, 3, 11, 11,
4, 10, 10, 5, 8, 5, 2, 9, 12, 10,
5, 7, 5, 3, 10, 9, 2, 8, 7, 4)
lat <- c(2, 7, 3, 3, 4, 4, 5, 4, 2, 1, 2,
1, 6, 4, 5, 5, 3, 4, 2, 7, 4,
6, 6, 6, 2, 4, 6, 4, 5, 6, 4,
3, 5, 3, 6, 5, 2, 5, 5, 5, 2,
5, 3, 1, 4, 6, 3, 6, 3, 6, 5)
dat_wnyc <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "WNYC")
# The Marshall Project
long <- c(7, 1, 2, 5, 1, 3, 10, 9, NA, 10, 8,
2, 2, 6, 6, 5, 4, 7, 5, 11, 8,
11, 7, 5, 6, 5, 3, 4, 2, 10, 10,
3, 9, 9, 4, 7, 4, 1, 8, 11, 9,
4, 6, 4, 2, 9, 8, 1, 7, 6, 3)
lat <- c(2, 1, 3, 3, 4, 4, 5, 4, NA, 1, 2,
1, 6, 4, 5, 5, 3, 4, 2, 7, 4,
6, 6, 6, 2, 4, 6, 4, 5, 6, 4,
3, 5, 3, 6, 5, 2, 5, 5, 5, 2,
5, 3, 1, 4, 6, 3, 6, 3, 6, 5)
dat_marshall <- data.frame(long = long,
lat = lat,
group = 1:51,
region = states,
region_abr = c(state.abb[1:8], "DC", state.abb[9:50]),
subregion = rep(NA, 51),
stringsAsFactors = FALSE,
style = "The Marshall Project")
square_usa_data <- rbind(dat_538, dat_Bloomberg, dat_Guardian, dat_marshall,
dat_Propublica, dat_tnyt, dat_wnyc, dat_wsj, dat_npr)
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