post code areas plotting in R - how to add legend - r

Question

I am new to R and need some help.
could you please help me with the below ? I would like to add gradient legend next to the plot from 0 to 1 showing different color as value change, but this is best I was able to get. As well please some tips how to add text with the post code inside of the map ? Thanks.
rm(list=ls())
library(tidyverse)
library(maptools)
library(raster)
library(plotrix)
# collection data set load + post codes lo la - 2016
df2016 <- read.csv('C:/Users/thomas/desktop/coll2016WORKINGFILE.csv')
colnames(df2016) <- c('name','value','amount')
df2016$amount <- NULL
df2016$name <- as.character(df2016$name)
# OPTIONAL: Depending on your data, you may need to rescale it for the color ramp to work
df2016$value <- rescale(df2016$value, newrange = c(0, 1))
# Download a shapefile of postal codes into your working directory
download.file(
"http://www.opendoorlogistics.com/wp-content/uploads/Data/UK-postcode-boundaries-Jan-2015.zip",
"postal_shapefile"
)
# Unzip the shapefile
unzip("postal_shapefile")
# Read the shapefile
postal <- readShapeSpatial("./Distribution/Areas")
postal.df <- fortify(postal, region = "name")
# Join your data to the shapefile
postal <- raster::merge(postal, df2016, by = "name")
postal$value[is.na(postal$value)] <- 0.50
# Get centroids of spatialPolygonDataFrame and convert to dataframe
# for use in plotting area names.
postal.centroids.df <- data.frame(long = coordinates(postal)[, 1],
lat = coordinates(postal)[, 2],
id=postal$name,
ratio = postal$value)
plot(postal, col = gray(postal$value))
title("UK Success Rate")
legend("right",NULL,legend = postal$value,col = gray(postal$value))
Original dataset from csv has below 3 columns:
Row Labels Success/Failed ratio N of coll
LD 1 3
ZE 1 2
WS 0.79 19
ML 0.75 12
HS 0.75 4
TQ 0.74 38
WN 0.73 15
CA 0.71 28
HU 0.7 33
FY 0.69 16
HG 0.69 16
IV 0.68 19
DL 0.68 25
CB 0.68 115
TS 0.67 46
IP 0.67 87
AB 0.67 66
NP 0.67 45
FK 0.67 18
IM 0.67 9
SM 0.66 50
HD 0.66 32
EN 0.66 61
CO 0.65 52
ME 0.65 54
PE 0.64 266
EX 0.64 81
WV 0.63 49
JE 0.63 24
NE 0.62 148
YO 0.62 47
DE 0.62 78
LN 0.61 36
SN 0.61 109
IG 0.6 63
NR 0.6 90
SP 0.59 37
BA 0.59 93
UB 0.59 127
TN 0.59 95
BT 0.59 180
BD 0.59 51
HP 0.59 126
TA 0.59 46
PO 0.58 113
DH 0.58 55
WD 0.58 102
BH 0.57 96
DG 0.57 14
CV 0.57 225
RG 0.57 255
BN 0.56 158
DY 0.56 48
HA 0.56 148
W 0.56 359
WA 0.56 77
DA 0.55 38
CT 0.55 62
GU 0.55 231
RH 0.55 132
BL 0.55 33
HX 0.55 11
BS 0.54 184
SS 0.54 46
EH 0.54 185
DT 0.54 37
G 0.54 137
B 0.54 283
LU 0.54 41
NG 0.54 97
OX 0.53 208
S 0.53 179
CM 0.53 100
DD 0.53 17
GL 0.53 87
AL 0.53 89
HR 0.53 38
LS 0.52 122
TF 0.52 21
RM 0.52 44
SL 0.52 155
MK 0.52 136
SY 0.52 46
DN 0.52 81
N 0.52 191
M 0.52 226
SR 0.52 29
SK 0.52 64
BB 0.51 140
KY 0.51 41
WF 0.51 51
PR 0.51 63
L 0.51 81
KT 0.5 185
CF 0.5 118
ST 0.5 84
TR 0.5 46
CW 0.5 44
TD 0.5 12
P 0.5 2
SW 0.5 317
LL 0.49 49
CH 0.49 43
E 0.49 275
EC 0.48 364
PA 0.48 27
SO 0.48 157
CR 0.48 84
PL 0.48 61
SG 0.47 59
KA 0.47 15
LA 0.47 43
SA 0.46 78
LE 0.46 194
TW 0.45 125
OL 0.44 41
SE 0.44 297
NN 0.43 143
NW 0.42 236
WC 0.41 138
WR 0.38 73
BR 0.37 62
GY 0.26 35
PH 0.23 13

Answer 1

Here you go. Use sf with new ggplot or stuff from my misc package for base graphs.
# collection data set load + post codes lo la - 2016
df2016 <- read.table(stringsAsFactors=FALSE, header=TRUE, text="
name value amount
LD 1 3
ZE 1 2
WS 0.79 19
# YOUR OTHER VALUES FROM ABOVE
PH 0.23 13")
if(FALSE){ # don't run when sourcing file
# Download a shapefile of postal codes into your working directory
download.file(
"http://www.opendoorlogistics.com/wp-content/uploads/Data/UK-postcode-boundaries-Jan-2015.zip",
"postal_shapefile.zip"
)
# Unzip and read the shapefile
unzip("postal_shapefile.zip")
}
# install.packages("sf")
postal <- sf::st_read("Distribution/Areas.shp")
# Join your data to the shapefile
postal2 <- merge(postal, df2016, by="name")
#devtools::install_github("tidyverse/ggplot2") # need newer ggplot2 version for geom_sf
library(ggplot2)
ggplot(postal2) + geom_sf(aes(fill = value))
# Want to remain in base graphs?
#install.packages("berryFunctions")
library(berryFunctions)
cols <- seqPal(n=100)
cls <- classify(postal2$value, breaks=100)$index
plot(postal2[,c("value","geometry")], col=cols[cls], graticule=TRUE, axes=TRUE) # ?sf::plot_sf
colPointsLegend(postal2$value, colors=cols, horizontal=FALSE, title="UK value")