Data 607 project 2 (DS 2)

A dataset from the Bureau of Land Management of uranium mines in Colorado and Utah from the earl-mid 90’s

library(tidyr)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(leaflet)
library(ggplot2)
options(scipen = 999)

ur <- read.csv("https://raw.githubusercontent.com/jconno/Uranium-Mines/main/BLM%20COLORADO%20UTAH%20URANIUM.csv")

Variables of original dataset

str(names(ur))

##  chr [1:217] "ï..BLM_KEY" "GEO_STATE" "DIST_RA" "RA" "SITE_ID" "MINE_NAME" ...

Mines visited: variables: GEO_STATE, MINE_NAME, DIFFICULTY || “DIFFICULTY” describes means of transportation to arrive at mine–indicates proof of visitation ||

visit <- ur %>% select(DATE, GEO_STATE, MINE_NAME, SITE_ACRES, DIFFICULTY, HUMAN_USE, ANIML_EVID, ANIML_PRES, ANIML_DES)
head(visit)

##   DATE GEO_STATE            MINE_NAME SITE_ACRES DIFFICULTY HUMAN_USE
## 1             CO              Unknown        0.7        4WD         N
## 2             CO  White Star Prospect         NA                     
## 3             CO Maybell Uranium Mine      250.0        4WD         N
## 4             CO            Sage Mine         NA        4WD         N
## 5             CO      Sugar Loaf Mine        0.2       HIKE         N
## 6             CO              Unknown        0.2       HIKE         N
##   ANIML_EVID ANIML_PRES          ANIML_DES
## 1          Y          Y            BURROWS
## 2                                         
## 3          Y          Y                  -
## 4          Y          Y                  -
## 5          Y          Y    DEER & ANTELOPE
## 6          Y            DROPPINGS & PRINTS

Mine waste: variables: GEO_STATE, MINE_NAME, LEAKING, DUMPSITES, HAZ_MITIG, ASBESTOS, CHEM_PILES, ACID_ODOR, PETROCHEMS, WASTE_PH, TAILS_PH

waste <- ur %>% select(GEO_STATE, MINE_NAME, LEAKING, DUMPSITES, HAZ_MITIG, ASBESTOS, CHEM_PILES, ACID_ODOR, PETROCHEMS, WASTE_PH, TAILS_PH)
head(waste)

##   GEO_STATE            MINE_NAME LEAKING DUMPSITES HAZ_MITIG ASBESTOS
## 1        CO              Unknown                NA        NA       NA
## 2        CO  White Star Prospect                NA        NA       NA
## 3        CO Maybell Uranium Mine                NA        NA       NA
## 4        CO            Sage Mine                NA        NA       NA
## 5        CO      Sugar Loaf Mine                NA        NA       NA
## 6        CO              Unknown                NA        NA       NA
##   CHEM_PILES ACID_ODOR PETROCHEMS WASTE_PH TAILS_PH
## 1         NA        NA         NA       NA       NA
## 2         NA        NA         NA       NA       NA
## 3         NA        NA         NA       NA       NA
## 4         NA        NA         NA       NA       NA
## 5         NA        NA         NA       NA       NA
## 6         NA        NA         NA       NA       NA

List of funds contributed to each mine: variables: GEO_STATE, MINE_NAME, FUNDS.CONTRIBUTED1" “FUNDS.CONTRIBUTED2” “FUNDS.CONTRIBUTED3”, “TOTAL.FUNDS.CONTRIBUTED (create sum of all 3)”

project_fund <- ur %>% select(GEO_STATE, MINE_NAME, SITE_ACRES, EST.COST, ACT.COST, FUNDS.CONTRIBUTED1, FUNDS.CONTRIBUTED2, FUNDS.CONTRIBUTED3)
head(project_fund)

##   GEO_STATE            MINE_NAME SITE_ACRES EST.COST ACT.COST
## 1        CO              Unknown        0.7       NA       NA
## 2        CO  White Star Prospect         NA       NA       NA
## 3        CO Maybell Uranium Mine      250.0       NA       NA
## 4        CO            Sage Mine         NA       NA       NA
## 5        CO      Sugar Loaf Mine        0.2       NA       NA
## 6        CO              Unknown        0.2       NA       NA
##   FUNDS.CONTRIBUTED1 FUNDS.CONTRIBUTED2 FUNDS.CONTRIBUTED3
## 1                 NA                 NA                 NA
## 2                 NA                 NA                 NA
## 3                 NA                 NA                 NA
## 4                 NA                 NA                 NA
## 5                 NA                 NA                 NA
## 6                 NA                 NA                 NA

summary(project_fund)

##   GEO_STATE          MINE_NAME           SITE_ACRES      EST.COST      
##  Length:660         Length:660         Min.   :   0.00   Mode:logical  
##  Class :character   Class :character   1st Qu.:   0.20   NA's:660      
##  Mode  :character   Mode  :character   Median :   1.00                 
##                                        Mean   :   6.48                 
##                                        3rd Qu.:   2.00                 
##                                        Max.   :1200.00                 
##                                        NA's   :9                       
##  ACT.COST       FUNDS.CONTRIBUTED1 FUNDS.CONTRIBUTED2 FUNDS.CONTRIBUTED3
##  Mode:logical   Mode:logical       Mode:logical       Mode:logical      
##  NA's:660       NA's:660           NA's:660           NA's:660          
##                                                                         
##                                                                         
##                                                                         
##                                                                         
##

Sites that are threatened, cultural, or historic

site_status <- ur %>% select(MINE_NAME, THREATNED, CULTURAL, HISTORIC)
summary(site_status)

##   MINE_NAME         THREATNED        CULTURAL        HISTORIC      
##  Length:660         Mode :logical   Mode :logical   Mode :logical  
##  Class :character   FALSE:660       FALSE:660       FALSE:660      
##  Mode  :character

Plot the mining sites with it’s status Variables: MINE_NAME, LATITUDE, LONGITUDE

sites <- ur %>% select(MINE_NAME, THREATNED, CULTURAL, HISTORIC, LATITUDE, LONGITUDE)

tag <- paste(sites$MINE_NAME, sites$THREATNED, sites$CULTURAL, sites$HISTORIC, sites$LATITUDE, sites$LONGITUDE )

leaflet() %>%
  addTiles() %>%
  addCircleMarkers(lat = sites$LATITUDE, lng = sites$LONGITUDE, popup = tag, color = "purple", stroke = FALSE, fillOpacity = 0.5)

## Warning in validateCoords(lng, lat, funcName): Data contains 16 rows with either
## missing or invalid lat/lon values and will be ignored

Data 607 project 2 (DS 2)

Joe Connolly

3/13/2021