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library(rgdal)
## Loading required package: sp
## rgdal: version: 1.3-6, (SVN revision 773)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 2.1.3, released 2017/20/01
## Path to GDAL shared files: /usr/share/gdal/2.1
## GDAL binary built with GEOS: TRUE
## Loaded PROJ.4 runtime: Rel. 4.9.2, 08 September 2015, [PJ_VERSION: 492]
## Path to PROJ.4 shared files: (autodetected)
## Linking to sp version: 1.3-1
library(sf)
## Linking to GEOS 3.5.1, GDAL 2.1.3, PROJ 4.9.2
library(sp)
library(cartography)
library(RColorBrewer)
install.packages("magick")
## Installing package into '/home/rstudio-user/R/x86_64-pc-linux-gnu-library/3.5'
## (as 'lib' is unspecified)
library(magick)
## Linking to ImageMagick 6.9.7.4
## Enabled features: fontconfig, freetype, fftw, lcms, pango, x11
## Disabled features: cairo, ghostscript, rsvg, webp
str(magick::magick_config())
## List of 21
## $ version :Class 'numeric_version' hidden list of 1
## ..$ : int [1:4] 6 9 7 4
## $ modules : logi TRUE
## $ cairo : logi FALSE
## $ fontconfig : logi TRUE
## $ freetype : logi TRUE
## $ fftw : logi TRUE
## $ ghostscript : logi FALSE
## $ jpeg : logi TRUE
## $ lcms : logi TRUE
## $ libopenjp2 : logi FALSE
## $ lzma : logi TRUE
## $ pangocairo : logi TRUE
## $ pango : logi TRUE
## $ png : logi TRUE
## $ rsvg : logi FALSE
## $ tiff : logi TRUE
## $ webp : logi FALSE
## $ wmf : logi TRUE
## $ x11 : logi TRUE
## $ xml : logi TRUE
## $ zero-configuration: logi FALSE
library(magick)
tiger <- image_read_svg('/cloud/project/literate-and-illiterate-world-population (2).svg', width = 2000)
print(tiger)
## format width height colorspace matte filesize density
## 1 PNG 2000 1412 sRGB TRUE 0 72x72
library(magick)
tiger <- image_read_svg('/cloud/project/projections-of-the-rate-of-no-education-based-on-current-global-education-trends-1970-2050 (1).svg', width = 2000)
print(tiger)
## format width height colorspace matte filesize density
## 1 PNG 2000 1412 sRGB TRUE 0 72x72
library(magick)
tig <- image_read_svg('/cloud/project/number-of-out-of-school-children.svg', width = 2000)
tig
# load GGplot2
library(ggplot2)
# Create test data.
dat = data.frame(count=c(95, 5), category=c("Primary school completion rate for both sex", "droped out of primary school"))
# Add addition columns, needed for drawing with geom_rect.
dat$fraction = dat$count / sum(dat$count)
dat = dat[order(dat$fraction), ]
dat$ymax = cumsum(dat$fraction)
dat$ymin = c(0, head(dat$ymax, n=-1))
# Make the plot
p1 = ggplot(dat, aes(fill=category, ymax=ymax, ymin=ymin, xmax=4, xmin=3)) +
geom_rect() +
coord_polar(theta="y") +
xlim(c(0, 4)) +
theme(panel.grid=element_blank()) +
theme(axis.text=element_blank()) +
theme(axis.ticks=element_blank()) +
annotate("text", x = 0, y = 0, label = "the indicaor of the rate
of studentS who completd
the primary school
in morocco") +
labs(title="")
p1
# Define the cars vector with 5 values
studentrate <- c(25, 50, 75, 100)
years <- c(1960,1980,2005,2015)
# Graph the cars vector with all defaults
plot(years,studentrate)
# Define the cars vector with 5 values
#cars <- c(1, 3, 6, 4, 9)
studentrate <- c(25, 50, 75, 100)
years <- c(1960,1980,2005,2015)
# Graph cars using blue points overlayed by a line
plot(years, studentrate,type="o", col="blue")
# Create a title with a red, bold/italic font
title(main="student inrollement in primary schools in morocco between 1960 and2015", col.main="red", font.main=4)
# Define cars vector with 5 values
studentpergender <- c(57,43 )
# Create test data.
# Create a pie chart for cars
pie(studentpergender)
# custom colors and labels
pie(studentpergender, main="student enrollement in primary school per gender in morocco ", col=rainbow(length(studentpergender)),
labels=c("boys","girls"))
barplot( c(45, 42,68), main="Education expenditure in morocco", xlab="the last three years",ylab="billions Moroccan Dirham")
library(plotrix)
slices <- c(40.99, 43.75, 14.29, 1.08)
lbls <- c("morocco", "algeria", "tunisia", "muritania")
pie3D(slices,labels=lbls,explode=0.1,
main="Pie Chart of Countries ")
library(readr)
cr<-read_csv("/cloud/project/API_MAR_DS2_en_csv_v2_10322524.csv")
## Warning: Missing column names filled in: 'X3' [3]
## Parsed with column specification:
## cols(
## `Data Source` = col_character(),
## `World Development Indicators` = col_character(),
## X3 = col_character()
## )
## Warning: 1601 parsing failures.
## row col expected actual file
## 2 -- 3 columns 63 columns '/cloud/project/API_MAR_DS2_en_csv_v2_10322524.csv'
## 3 -- 3 columns 63 columns '/cloud/project/API_MAR_DS2_en_csv_v2_10322524.csv'
## 4 -- 3 columns 63 columns '/cloud/project/API_MAR_DS2_en_csv_v2_10322524.csv'
## 5 -- 3 columns 63 columns '/cloud/project/API_MAR_DS2_en_csv_v2_10322524.csv'
## 6 -- 3 columns 63 columns '/cloud/project/API_MAR_DS2_en_csv_v2_10322524.csv'
## ... ... ......... .......... ...................................................
## See problems(...) for more details.
cr
## # A tibble: 1,602 x 3
## `Data Source` `World Development In… X3
## <chr> <chr> <chr>
## 1 Last Updated D… 2018-11-14 <NA>
## 2 Country Name Country Code Indicator Name
## 3 Morocco MAR Presence of peace keepers (numbe…
## 4 Morocco MAR Intentional homicides (per 100,0…
## 5 Morocco MAR Intentional homicides, male (per…
## 6 Morocco MAR Intentional homicides, female (p…
## 7 Morocco MAR Internally displaced persons, to…
## 8 Morocco MAR Internally displaced persons, ne…
## 9 Morocco MAR Internally displaced persons, ne…
## 10 Morocco MAR Battle-related deaths (number of…
## # … with 1,592 more rows