You can use the sf package to convert it to a simple features geography.
In order to get this to work you need to know what coordinate system you are working with, and based on the description you provide (State Plane NAD83 and are near St. Louis), My first guess was EPSG 26996 (NAD83 / Missouri East USFT), but that plotted in the middle of lake Huron, so I tried ESRI: 102696. You can look up projections at spatialreference.org.
library(sf)
library(tidyverse)
library(ggmap)
my_df <- read_csv("C:/Users/Brian/Documents/temp.csv")
my_sf_df <- st_as_sf(my_df, coords = c("XCoord", "YCoord"), crs = 102696)
This sets the x and y to spatial coordinates. You need to re-project into a geographic system like WGS84 to convert to lat long. st_transform does this for us using crs = 4326, which is the WGS 84 coordinate system
my_latlon_df <- st_transform(my_sf_df, crs = 4326 )
my_latlon_df <- my_latlon_df%>%
mutate( lat= st_coordinates(my_latlon_df)[,1],
lon = st_coordinates(my_latlon_df)[,2])
my_latlon_df
# Simple feature collection with 6 features and 5 fields
# geometry type: POINT
# dimension: XY
# bbox: xmin: -93.26566 ymin: 35.80151 xmax: -90.19163 ymax: 38.63065
# epsg (SRID): 4326
# proj4string: +proj=longlat +datum=WGS84 +no_defs
# # A tibble: 6 x 6
# X1 CodedMonth Description geometry lat lon
# * <chr> <chr> <chr> <POINT [°]> <dbl> <dbl>
# 1 1: 2019-09 AUTO THEFT-PERM RETNT/UNRECOV OVER 48HR (-90.19163 38.63065) -82.2 44.7
# 2 2: 2019-09 ASSLT-AGGRAV-OTH-WPN-2ND-CHILD-DOMESTIC (-90.20674 38.6187) -82.3 44.7
# 3 3: 2019-09 FORGERY-ISSUING FALSE INSTRUMENT OR CERTIFICAT (-93.26566 35.80151) -93.3 35.8
# 4 4: 2019-09 STLG BY DECEIT/IDENTITY THEFT REPORT (-90.25329 38.60893) -82.4 44.6
# 5 5: 2019-09 STALKING (HARASSMENT ONLY, NO THREAT) (-90.2869 38.60251) -82.5 44.6
# 6 6: 2019-09 LARCENY-MTR VEH PARTS UNDER $500 (-90.28065 38.56034) -82.5 44.5
We now have geographic coordinates with lat and long as columns of our data frame. The no location information is going to cause problems, since it will plot at the origin of the state plane coordinate plane, which is down in Arkansas somewhere. Let's remove it so we can focus on the good points
# let's exclude point 3 for now
my_latlon_df <- my_latlon_df[-3,]
box <- st_bbox(my_latlon_df) # bounding box
names(box) <- NULL # removing non-complient labels
buffer = .2
box2 <- box + c(-buffer, -buffer, buffer, buffer) # buffering
base_map <- get_map(location = box2, source = "osm") # getting base map
# plotting
ggmap(base_map)+
geom_sf(data = my_latlon_df,
color = "red",
size = 2
)+
scale_x_continuous(limits = c(-90.35, -90.1))+
scale_y_continuous(limits = c(38.5, 38.7))
Unfortunately, if you don't know what coordinate system your x and y points are in, it can become a frustrating game of trial and error. The projected coordinate systems basically create a Cartesian plane on the surface of the globe, and the choice of origin, scale and other parameters are specific to each projection. There isn't nearly as much difference in geographic coordinate systems such as WGS84.
