Closed
Description
Hello, When I was running a code that was supposed to draw a scatterplot and color and resize a single dot of it, I realized that it wasn't working properly. The only way to fix this problem was to add an "arrange" function for the State Initial in the input dataset of plotly. Otherwise, this code was coloring and resizing the shape of Arkansas instead of the US.
It seems like the code was coloring and resizing it according to the alphabetical order of the states initial and not according to the 'ifelse' function inside the marker list.
Here's the code and the file "national_county.txt" is attached:
# Code to extractdata from FRED
library(alfred)
library(tidyverse)
library(lubridate)
library(plotly)
library(zoo)
library(data.table)
library(BBmisc)
calculate_acum_growth_S_months <- function(x, s) { aux <- rollapply(x, width = s, FUN = sum); return(c(rep(NA, s - 1),(aux / lag(aux, s) - 1) * 100)) }
calculate_acelleration_S_months <- function(x, s, k) { aux <- diff(calculate_acum_growth_S_months(x, s), k); return(c(NA, aux)) }
# List of US States initials
county_corresp <- tbl_df(fread("national_county.txt"))
names(county_corresp) <- c("STATE", "STATEFP", "COUNTYFP", "COUNTYNAME", "CLASSFP")
states_initials <- unique(county_corresp$STATE)
# United States first (all join will be after the first grab)
string_grab = c("UNRATENSA", paste0(states_initials, "URN"))
# Inspired in https://stackoverflow.com/questions/11254524/omit-rows-containing-specific-column-of-na
# Just modified a little bit in order to use the column name "dplyr's wise"
completeFun <- function(data, desiredCols) {
completeVec <- complete.cases(data[, desiredCols])
return(data[completeVec, ])
}
get_fred_series_paese <- function(series_id, series_name = NULL,
observation_start = NULL, observation_end = NULL) {
length_series_id <- nchar(series_id)
if (is.character(series_id) == FALSE) {
stop("series_id is always in characters")
}
if (is.null(series_name) == TRUE ) {
series_name <- series_id
}
if (is.null(observation_start) == TRUE) {
observation_start <- "1776-07-04"
}
if (is.null(observation_end) == TRUE) {
observation_end <- "9999-12-31"
}
df_series <-
try({
fromJSON(
paste0("https://api.stlouisfed.org/fred/series/observations?series_id=",
series_id,
"&observation_start=",
observation_start,
"&observation_end=",
observation_end,
"&output_type=2",
"&api_key=98f9f5cad7212e246dc5955e9b744b24&file_type=json")
)$observations %>%
mutate_(date = ~as_date(date))
}, silent = TRUE)
print(class(df_series))
if (!class(df_series) == "try-error") {
colnames(df_series)[!(colnames(df_series) %in% "date")] <- series_name
df_series[, 2] <- as.numeric(unlist(df_series[, 2]))
df_series
} else {
df_series <- tibble(date = as.Date(NA))
}
}
create_df <- function(i) {
x <- get_fred_series_paese(string_grab[i])
if (!is.error(x)) # Even if FRED doesn't the series, it won't stop
{x} else
{tibble(date = as.Date(NA))}}
data = 1:length(string_grab) %>%
map(create_df) %>%
reduce(full_join, by = "date") %>%
completeFun("date")
data_clean <- data %>%
rename(USURN = UNRATENSA) %>%
gather(Raw_Type, UR, -date) %>%
separate(Raw_Type, into = c("State", "Seasonal_Type"), sep = 2) %>%
mutate(year = year(date),
month = month(date)) %>%
group_by(State, Seasonal_Type) %>%
mutate(Var = calculate_acum_growth_S_months(UR, 12),
Ace = calculate_acelleration_S_months(Var, s = 12, k = 1))
base_aux = data_clean %>%
filter(Seasonal_Type == "URN",
year == 2016,
month == 10) #%>%
#arrange(State)
# Spatial Unemployment
base_aux %>%
plot_ly(x = ~Ace,
y = ~Var,
type = 'scatter',
mode = 'markers',
marker = list(size = ifelse(base_aux$State == "US", 20, 10),
#sizeref = .10,
color = ifelse(base_aux$State == "US", "red","#004B82")#,
#symbol = 1:length(base_aux$State)
),
hoverinfo = "text",
text = paste("", base_aux$State, "<br>",
"Growth: ", round(base_aux$Var, 3), "<br>",
"Acelleration: ", round(base_aux$Ace, 3)),
showlegend = TRUE)