Transform defined columns to character.

Description

col2char transform columns type to character.

Usage

col2char(x, start, end = ncol(x))

Arguments

Value

Return a dataframe with transformed columns.

Examples

v=data.frame(c(3,2,5,6,5,4))
class(v[,1]) #here class is numeric
v=col2char(v,1)
class(v[,1]) #now class is character

Transform defined columns to factor.

Description

col2factor transform columns type to factor.

Usage

col2factor(x, start, end = ncol(x))

Arguments

Value

Return a dataframe with transformed columns.

Examples

v=data.frame(c(3,2,5,6,5,4))
class(v[,1]) #here class is numeric
v=col2factor(v,1)
class(v[,1]) #now class is character

Transform defined columns to numeric.

Description

col2num transform columns type to numeric.

Usage

col2num(x, start, end = ncol(x))

Arguments

Value

Return a dataframe with transformed columns.

Examples

v=data.frame(c('3','2','5','6','5','4'))
class(v[,1]) #here class is factor
v=col2num(v,1)
class(v[,1]) #now class is character

Add percent in column

Description

col2percent transform columns to percent.

Usage

col2percent(x, start, end = ncol(x), mult100 = FALSE)

Arguments

Value

Return a dataframe with transformed columns.

Examples

v=data.frame(c(15,5,20,50,10))
col2percent(v,start=1)

v=data.frame(c(0.15,0.05,0.2,0.5,0.1))
col2percent(v,start=1,mult100=TRUE)

Remove percent from a column, and transform in number

Description

When use col2percent function to add a percent in a column, the type of this column now is character, colpct2num function remove percent from this column and transform in number.

Usage

colpct2num(x, start, end = ncol(x), div100 = TRUE)

Arguments

Value

Return a dataframe with transformed columns.

Examples

v=data.frame(c(15,5,20,50,10))
v=col2percent(v,start=1)
v=colpct2num(v,start=1,div100=TRUE)

Round defined columns

Description

colround round defined columns.

Usage

colround(x, start, end = ncol(x), digits)

Arguments

Value

Return a dataframe with transformed columns.

Examples

v=data.frame(c(3.255,5.826,4.567,2.462))
v=colround(v,1,digits=1)

Accumulated variation

Description

cum_var calculates an accumulated variation of a rate, _var means the data must be a percentage variation.

Usage

cum_var(data, colnum, t, div100 = FALSE)

Arguments

Value

Return a dataframe.

Examples

v=data.frame(c(0.03,0.02,0.05))
cum_var(v,colnum=1,t=3)

v=data.frame(c('3%','2%','5%'))
v=colpct2num(v,start=1,div100=TRUE)
cum_var(v,colnum=1,t=3)

Accumulated variation in year

Description

cuminyear calculates an accumulated variation in year of a index. Data must be start in january, use start to set this, if you data don't start in january and you need use this values, consider complete the previous months with 0.

Usage

cuminyear(data, coldate, colnum, start = 1)

Arguments

Value

Return a dataframe.

Examples

v=data.frame(
"Date"=c(seq.Date(as.Date("2018-01-01"),as.Date("2019-12-01"),by='month'))
,"Value"=c(rep(2,6),rep(3,6),rep(1,6),rep(5,6)))
cuminyear(v,coldate=1,colnum=2)

v=data.frame(
"Date"=c(seq.Date(as.Date("2018-06-01"),as.Date("2019-12-01"),by='month'))
,"Value"=c(rep(3,7),rep(1,6),rep(5,6)))

#this case, we can start in january 2019
cuminyear(v,coldate=1,colnum=2,start=8)

#or if we need the previous values i can complete january 2018 to may 2018 with 0.
v1=data.frame(Date=c(seq.Date(as.Date("2018-01-01"),as.Date("2018-05-01"),by='month')),
"Value"=c(rep(0,5)))
v=rbind(v1,v)
cuminyear(v,coldate=1,colnum=2)

Accumulated variation in year

Description

cuminyear_var calculates an accumulated variation in year of a rate, _var means the data must be a percentage variation. Data must be start in january, if you data don't start in january and you need use this values, consider complete the previous months with 0.

Usage

cuminyear_var(data, coldate, colnum, div100 = FALSE)

Arguments

Value

Return a dataframe.

Examples

v=data.frame(
"Date"=c(seq.Date(as.Date("2018-01-01"),as.Date("2019-12-01"),by='month'))
,"Value"=c(rep(0.02,12),rep(0.03,12)))
cuminyear_var(v,coldate=1,colnum=2)

v=data.frame(
"Date"=c('january','february','march')
,"Value"=c('1%','3%','2%'))
v=colpct2num(v,start=2,div100=TRUE)
v[[1]]=month2num(v[[1]])
v[[1]]=paste('2018',v[[1]],'01',sep="-")
v[[1]]=as.Date(v[[1]])
cuminyear_var(v,coldate=1,colnum=2)

Bar Graphic Model

Description

gm.col make a bar plot. Graphic models function family do graphic creation easy, is recommended for new programers, they have less and easyful parameters then p.col_ord but the graphic customize is more limited.

Usage

gm.col(
  data,
  ncolx,
  ncoly,
  ntimes,
  title,
  xlab = NULL,
  ylab = NULL,
  div100 = FALSE,
  percent = FALSE,
  fontsize = 0,
  cserie = "#17B221",
  clines = "white",
  ctext = "white",
  cbackground = "#141414",
  cbserie = cbackground
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq(from=1,to=4,by=1),"y"=c(5,3,7,2))

gm.col(v,1,2,title="Simple example",ntimes=3)

Ordered Bar Graphic Model

Description

gm.col_ord make a ordered bar plot. Graphic models function family do graphic creation easy, is recommended for new programers, they have less and easyful parameters then p.col_ord but the graphic customize is more limited.

Usage

gm.col_ord(
  data,
  ncolx,
  ncoly,
  ntimes,
  title,
  xlab = NULL,
  ylab = NULL,
  percent = FALSE,
  div100 = FALSE,
  dec = FALSE,
  fontsize = 0,
  cserie = "#17B221",
  clines = "white",
  ctext = "white",
  cbackground = "#141414",
  cbserie = cbackground
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq(from=1,to=4,by=1),"y"=c(5,3,7,2))

gm.col_ord(v,1,2,title="Simple example",ntimes=3)

Ordered Bar Graphic with Legend Model

Description

gm.col_ord_wl make a bar plot. Graphic models function family do graphic creation easy, is recommended for new programers, they have less and easyful parameters then p.col_ord but the graphic customize is more limited.

Usage

gm.col_ord_wl(
  data,
  ncolx,
  ncoly,
  ntimes,
  title,
  legtitle,
  xlab = NULL,
  ylab = NULL,
  dec = FALSE,
  div100 = FALSE,
  percent = FALSE,
  fontsize = 0,
  colors = grDevices::rainbow(n = ntimes, v = 0.7),
  clines = "white",
  ctext = "white",
  cbackground = "#141414",
  cbserie = cbackground,
  legwpos = 0,
  legheight = 0.5
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq(from=1,to=4,by=1),"y"=c(5,3,7,2))

gm.col_ord_wl(v,1,2,title="Simple example",ntimes=3,legwpos=-2.5)

Bar Graphic with Legend Model

Description

gm.col_wl make a bar plot. Graphic models function family do graphic creation easy, is recommended for new programers, they have less and easyful parameters then p.col_ord but the graphic customize is more limited.

Usage

gm.col_wl(
  data,
  ncolx,
  ncoly,
  ntimes,
  title,
  legtitle,
  xlab = NULL,
  ylab = NULL,
  div100 = FALSE,
  percent = FALSE,
  fontsize = 0,
  colors = grDevices::rainbow(n = ntimes, v = 0.7),
  clines = "white",
  ctext = "white",
  cbackground = "#141414",
  cbserie = cbackground,
  legwpos = 0,
  legheight = 0.5
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq(from=1,to=4,by=1),"y"=c(5,3,7,2))

gm.col_wl(v,1,2,title="Simple example",ntimes=3,legwpos=-2.5)

Line Graphic Model

Description

gm.line make a line plot. Graphic models function family do graphic creation easy, is recommended for new programers, they have less and easyful parameters then p.line but the graphic customize is more limited.

Usage

gm.line(
  data,
  ncolx,
  ncoly,
  ntimes,
  title,
  xlab = NULL,
  ylab = NULL,
  div100 = FALSE,
  percent = FALSE,
  fontsize = 0,
  lwdserie = 1.5,
  cserie = "white",
  clines = "white",
  ctext = "white",
  cbackground = "#141414"
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq(from=1,to=4,by=1),"y"=c(5,3,7,2))

gm.line(v,1,2,title="Simple example",ntimes=3)

Time serie bar Graphic Model

Description

gm.tscol make a bar plot in time serie format. Graphic models function family make graphic creation easy, is recommended for new programers, they have less and easyful parameters then p.tscol but the graphic customize is more limited . The data don't need be a ts object.

Usage

gm.tscol(
  data,
  ncolx,
  ncoly,
  ntimes,
  title,
  ylab = NULL,
  percent = FALSE,
  div100 = FALSE,
  fontsize = 0,
  datebreaks = "1 months",
  dateformat = "%b/%y",
  clines = "white",
  ctext = "white",
  cbackground = "#141414",
  cbserie = cbackground
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-04-01'),by='month'),"y"=c(5,3,7,2))

gm.tscol(v,1,2,title="Simple example",ntimes=3)

Time serie bar Graphic Model

Description

gm.tscol2 make a bar plot in time serie format. The difference between gm.tscol2 and gm.tscol is possibility to select serie color. Graphic models function family make graphic creation easy, is recommended for new programers, they have less and easyful parameters then p.tscol but the graphic customize is more limited. The data don't need be a ts object.

Usage

gm.tscol2(
  data,
  ncolx,
  ncoly,
  ntimes,
  title,
  ylab = NULL,
  percent = FALSE,
  div100 = FALSE,
  fontsize = 0,
  datebreaks = "1 months",
  dateformat = "%b/%y",
  cserie = "white",
  clines = "white",
  ctext = "white",
  cbackground = "#141414",
  cbserie = cbackground
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-04-01'),by='month'),"y"=c(5,3,7,2))

gm.tscol2(v,1,2,title="Simple example",ntimes=3)

Time serie line Graphic Model

Description

gm.tsl make a line plot in time serie format. Graphic models function family make graphic creation easy, is recommended for new programers, they have less and easyful parameters then p.tsl but the graphic customize is more limited. The data don't need be a ts object.

Usage

gm.tsl(
  data,
  ncolx,
  ncoly,
  ntimes,
  title,
  ylab = NULL,
  percent = FALSE,
  div100 = FALSE,
  fontsize = 0,
  lwdserie = 1,
  datebreaks = "1 months",
  dateformat = "%b/%y",
  cserie = "white",
  clines = "white",
  ctext = "white",
  cbackground = "#141414"
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-04-01'),by='month'),"y"=c(5,3,7,2))

gm.tsl(v,1,2,title="Simple example",ntimes=3)

Lag a data

Description

me.lag lag a vector if t>0 or lead a vector if t<0.

Usage

me.lag(x, t = 1, nafill = NA, extrapolate = FALSE)

Arguments

Value

Return a vector.

Examples

v=c(3,2,5,6,5,4)
me.lag(v)

#now lead

me.lag(v,t=-1)

Spread an dataframe.

Description

Transforms columns into rows and rows into columns.

Usage

me.spread(data, namenc = " ", mode = FALSE)

Arguments

Value

Return a dataframe.

Examples

v=data.frame('date'=c('2016','2017'),'value1'=c(12,10),'value2'=c(8,6))
me.spread(v,namenc='old header')

Macroeconomics Tools

Description

The 'metools' package provides a number of functions to facilitate the handling and production of reports using time series data. The package was developed to be understandable for beginners, so some functions aim to transform processes that would be complex into functions with a few lines. The main advantage of using the 'metools' package is the ease of producing reports and working with time series using a few lines of code, so the code is clean and easy to understand/maintain. Learn more about the 'metools' at <https://metoolsr.wordpress.com>.

Details

metools: A package for work with macroeconomics time series.

The 'metools' package provide two categorys of functions: Data manipulate: don't have prefix. Graphics: have p. prefix.

Author(s)

João Victor Gomes (jvg.santana@gmail.com)

See Also

Useful links:

https://metoolsr.wordpress.com https://github.com/jvg0mes/metools https://jvg0mes.github.io/metoolsr

Metools Help

Description

Use this function to receive help to use metools.

Usage

metools.help()

Value

Return a info.

Examples

metools.help()

Transform month names to month numbers

Description

month2num transform month names to month numbers

Usage

month2num(date)

Arguments

Value

Return a month numbers.

Examples

v=c("jan","fev","mar","abr","mai","jun","jul","ago","set","out","nov","dez")
month2num(v)

v=data.frame('date'=c("janeiro","fevereiro",'março','abril'),'values'=c(18,27,10,48))
month2num(v$date)
#or
month2num(v[[1]])

#you can substitute column with function:
v$date = month2num(v$date)
v[[1]] = month2num(v[[1]])

Multi serie plot

Description

mp.s make a plot with one or more series. The object parameter require a ggplot object (Look at the examples).

Usage

mp.s(
  object,
  xaxis,
  yaxis,
  ybreaks = 10,
  percent = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "Title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cticks = "black",
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  xlim = NULL
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=c('a','b','c','d','e'),"y"=c(5,3,7,10,9),"y2"=c(7,2,5,8,7))

g= ggplot2::ggplot()+ggplot2::geom_line(mapping=ggplot2::aes(x=v$x,y=v$y,group=1),lwd=2)+
ggplot2::geom_line(mapping=ggplot2::aes(x=v$x,y=v$y2,group=1),color='blue',lwd=2)

mp.s(object=g,xaxis=v$x,yaxis=v$y,title="Simple example")

mp.s(g,v$x,v$y,percent=TRUE,title="Example with percent data",xlab=NULL,ylab=NULL)

mp.s(g,v$x,v$y,percent=TRUE,yaccuracy=1,title="y accuracy set",xlab=NULL,ylab=NULL)

g= ggplot2::ggplot()+ggplot2::geom_area(mapping=ggplot2::aes(x=v$x,y=v$y),
fill='red',lwd=2,group=1)+
ggplot2::geom_area(mapping=ggplot2::aes(x=v$x,y=v$y2),fill='blue',lwd=2,group=1)

mp.s(g,v$x,v$y,title="Example with area plot")

v=data.frame("x"=c('a','b','c','d','e'),"y"=c(5,-3,-6,10,7))

g= ggplot2::ggplot()+ggplot2::geom_col(ggplot2::aes(x=v$x,y=v$y,group=1),
fill=p.colorbypositive(v$y),color='black',lwd=1)+
ggplot2::geom_line(ggplot2::aes(x=v$x,y=v$y,group=1),color='black',lwd=1)

mp.s(g,v$x,v$y,title="Example with colorbypositive",xlab=NULL,ylab=NULL)

Multi serie plot in time serie format

Description

mp.ts make plot in time serie format with one or more series. The data don't need be a ts object. The object parameter require a ggplot object (Look at the examples).

Usage

mp.ts(
  object,
  xaxis,
  yaxis,
  dateformat = "%Y-%m",
  datebreaks = "1 month",
  ybreaks = 10,
  percent = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "Title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cticks = "black",
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  xlim = NULL
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-05-01'),by='month'),"y"=c(5,3,7,10,9),"y2"=c(7,2,5,8,7))

g= ggplot2::ggplot()+ggplot2::geom_line(mapping=ggplot2::aes(x=v$x,y=v$y),lwd=2)+
ggplot2::geom_line(mapping=ggplot2::aes(x=v$x,y=v$y2),color='blue',lwd=2)

mp.ts(object=g,xaxis=v$x,yaxis=v$y,title="Simple example")

mp.ts(g,v$x,v$y,percent=TRUE,title="Example with percent data",xlab=NULL,ylab=NULL)

mp.ts(g,v$x,v$y,percent=TRUE,yaccuracy=1,title="y accuracy set",xlab=NULL,ylab=NULL)

g= ggplot2::ggplot()+ggplot2::geom_area(mapping=ggplot2::aes(x=v$x,y=v$y),
fill='red',lwd=2)+
ggplot2::geom_area(mapping=ggplot2::aes(x=v$x,y=v$y2),fill='blue',lwd=2)

mp.ts(g,v$x,v$y,dateformat="%B",title="Example with area plot")

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-05-01'),by='month'),"y"=c(5,-3,-6,10,7))

g= ggplot2::ggplot()+ggplot2::geom_col(ggplot2::aes(x=v$x,y=v$y),
fill=p.colorbypositive(v$y),color='black',lwd=1)+
ggplot2::geom_line(ggplot2::aes(x=v$x,y=v$y),color='black',lwd=1)

mp.ts(g,v$x,v$y,title="Example with colorbypositive",xlab=NULL,ylab=NULL)

Transform month numbers to month names

Description

num2month transform month numbers to month names

Usage

num2month(date, abbreviate = FALSE, ptbr = FALSE)

Arguments

Value

Return a month names.

Examples

v=c(01,02,03,04,05,06,07,08,09,10,11,12)
num2month(v)
num2month(v,abbreviate=TRUE)
num2month(v,abbreviate=FALSE,ptbr=TRUE)
num2month(v,abbreviate=TRUE,ptbr=TRUE)

v=data.frame('date'=c(01,02,03,04),'values'=c(18,27,10,48))
num2month(v$date)
#or
num2month(v[[1]])

#you can substitute column with function:
v$date = num2month(v$date)
v[[1]] = num2month(v[[1]])

#The data can be a string, but is recommended use numbers,
#see a string examples:
v=c('01','02','03','04','05','06','07','08','09','10','11','12')
num2month(v)

v=c('1','2','3','4','5','6','7','8','9','10','11','12')
num2month(v)

Bar plot

Description

p.col make a bar plot.

Usage

p.col(
  data,
  xaxis,
  yaxis,
  ybreaks = 10,
  percent = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "Title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cserie = "black",
  cbserie = cserie,
  cticks = "black",
  lwdserie = 1,
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  xlim = NULL
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=1:5,"y"=c(10,4,8,5,2))
p.col(v,xaxis= v$x,yaxis=v$y)
#or
p.col(v,xaxis= v[[1]],yaxis=v[[2]])

Ordered bar plot

Description

p.col_ord make a ordered bar plot.

Usage

p.col_ord(
  data,
  xaxis,
  yaxis,
  ybreaks = 10,
  dec = FALSE,
  percent = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "Title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cserie = "black",
  cbserie = cserie,
  cticks = "black",
  lwdserie = 1,
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  xlim = NULL
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=1:5,"y"=c(10,4,8,5,2))
p.col_ord(v,xaxis= v$x,yaxis=v$y)
#or
p.col_ord(v,xaxis= v[[1]],yaxis=v[[2]])

p.col_ord(v,xaxis= v$x,yaxis=v$y,dec=TRUE,percent=FALSE)
p.col_ord(v,xaxis= v$x,yaxis=v$y,dec=TRUE,percent=TRUE)
p.col_ord(v,xaxis= v$x,yaxis=v$y,dec=FALSE,percent=FALSE)
p.col_ord(v,xaxis= v$x,yaxis=v$y,dec=FALSE,percent=TRUE)

Ordered bar plot with legend

Description

p.col_ord_wl make a ordered bar plot with legend.

Usage

p.col_ord_wl(
  data,
  xaxis,
  yaxis,
  ybreaks = 10,
  percent = FALSE,
  dec = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "Title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cbserie = "black",
  cticks = "black",
  lwdserie = 1,
  legtitle = "Legend",
  legsize = 8,
  cleg = ctitles,
  legheight = 0.5,
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  legpos = "right",
  legdir = "horizontal",
  legcol = "white",
  legspa = 1,
  legvjust = 0.5,
  colors = grDevices::rainbow(length(xaxis), v = 0.7)
)

Arguments

Value

Return ordered bar plot with legend.

Examples

v=data.frame("x"=1:5,"y"=c(10,4,8,5,2))
p.col_ord_wl(v,xaxis= v$x,yaxis=v$y)
#or
p.col_ord_wl(v,xaxis= v[[1]],yaxis=v[[2]])

p.col_ord_wl(v,xaxis= v$x,yaxis=v$y,dec=TRUE,percent=FALSE)
p.col_ord_wl(v,xaxis= v$x,yaxis=v$y,dec=TRUE,percent=TRUE)
p.col_ord_wl(v,xaxis= v$x,yaxis=v$y,dec=FALSE,percent=FALSE)
p.col_ord_wl(v,xaxis= v$x,yaxis=v$y,dec=FALSE,percent=TRUE)

#Layout example
p.col_ord_wl(v,v$x,v$y,note = "metools - 2020",title = "Layout example",
stitle = "Ordered bar plot",ylab=NULL,wordssize = 10,titlesize = 32,
legspa = 0.5,legvjust = -2.5,legsize = 10,cplot='grey',
cbgrid="black",clgrid= "grey",ctitles = 'white',cleg = 'white',
legcol='black',colors=topo.colors(length(v$x),alpha=0.8))

Bar plot with legend

Description

p.col_wl make a bar plot with legend.

Usage

p.col_wl(
  data,
  xaxis,
  yaxis,
  ybreaks = 10,
  percent = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cbserie = "black",
  cticks = "black",
  lwdserie = 1,
  legtitle = "Legend",
  legsize = 8,
  cleg = ctitles,
  legheight = 0.5,
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  legpos = "right",
  legdir = "horizontal",
  legcol = "white",
  legspa = 1,
  legvjust = 0.5,
  colors = grDevices::rainbow(length(xaxis), v = 0.7)
)

Arguments

Value

Return a dataframe with transformed columns.

Examples

v=data.frame("x"=1:5,"y"=c(10,4,8,5,2))
p.col_wl(v,xaxis= v$x,yaxis=v$y)

p.col_wl(v,xaxis= v$x,yaxis=v$y,colors=c('red','blue','green','grey','yellow'))

Color by positive or negative

Description

p.colorbypositive is a function to create a vector with colors by positive or negative. Recommended to color graphics created with metools p.functions.

Usage

p.colorbypositive(x, colorp = "#17B221", colorn = "#B21717")

Arguments

Value

Return a vector with colors.

Examples

v=c(-3,-2,2,-2,3,2)
p.colorbypositive(x=v,colorp="blue",colorn="grey")

barplot(v,col=p.colorbypositive(v))

Color by variation

Description

p.colorbyvar is a function to create a vector with colors by variation. Recommended to color graphics created with metools p.functions.

Usage

p.colorbyvar(x, colorp = "#17B221", colorn = "#B21717", lag = 1)

Arguments

Value

Return a vector with colors.

Examples

v=c(3,2,5,6,5,4)
p.colorbyvar(x=v,colorp="blue",colorn="grey")

barplot(v,col=p.colorbyvar(v))

Create Gradient

Description

p.gradientcolor is a function to make easy create gradient pallet. Recommended to color graphics created with metools p.functions.

Usage

p.gradientcolor(color1, color2, n)

Arguments

Value

Return a vector with colors.

Examples

p.gradientcolor(color1="white",color2="blue",n=10)

v = p.gradientcolor("white","blue",n=20)
barplot(seq.int(from=1,to=20,by=1),col=v)

Line plot

Description

p.line make a line plot.

Usage

p.line(
  data,
  xaxis,
  yaxis,
  ybreaks = 10,
  percent = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "Title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cserie = "black",
  cticks = "black",
  lwdserie = 1,
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  xlim = NULL
)

Arguments

Value

Return a line graphic.

Examples

v=data.frame("x"=1:5,"y"=c(10,4,8,5,2))
p.line(v,xaxis= v$x,yaxis=v$y)
#or
p.line(v,xaxis= v[[1]],yaxis=v[[2]])

Create Date Interval

Description

p.seqdatebreaks is a function to break a time axis from graphic in specific interval. This function are recommended to select timeinterval of graphics created with metools p.functions.

Usage

p.seqdatebreaks(x, periodicity)

Arguments

Value

Return a vector with timeinterval.

Examples

x <- seq.Date(from=as.Date("2019-01-01"),to=as.Date("2020-01-01"),by=1)
 p.seqdatebreaks(x,periodicity= "2 month")

Bar plot in time serie format

Description

p.tscol make a bar plot in time serie format. The data don't need be a ts object.

Usage

p.tscol(
  data,
  xaxis,
  yaxis,
  dateformat = "%Y-%m",
  datebreaks = "1 month",
  ybreaks = 10,
  percent = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "Title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cserie = "black",
  cbserie = cserie,
  cticks = "black",
  lwdserie = 1,
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  xlim = NULL
)

Arguments

Value

Return a graphic.

Examples

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-04-01'),by='month'),"y"=c(5,3,7,2))

p.tscol(v,v$x,v$y,title="Simple example")

p.tscol(v,v$x,v$y,dateformat="%B",title="Example with colorbyvar",
ylab="Values",xlab=NULL,cserie=p.colorbyvar(v$y))

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-04-01'),by='month'),"y"=c(0.03,-0.05,0.08,-0.02))

p.tscol(v,v$x,v$y,percent=TRUE,title="Example with percent data",xlab=NULL,ylab=NULL)

p.tscol(v,v$x,v$y,percent=TRUE,yaccuracy=1,title="y accuracy set",xlab=NULL,ylab=NULL)

p.tscol(v,v$x,v$y,percent=TRUE,yaccuracy=1,title="Example with colorbypositive",xlab=NULL,ylab=NULL,
cserie=p.colorbypositive(v$y),cbserie="black",lwdserie=1) #lwdserie change the board in this case

Line plot in time serie format

Description

p.tsl make a line plot in time serie format. The data don't need be a ts object.

Usage

p.tsl(
  data,
  xaxis,
  yaxis,
  dateformat = "%Y-%m",
  datebreaks = "1 month",
  ybreaks = 10,
  percent = FALSE,
  yaccuracy = 0.01,
  ydecimalmark = ".",
  title = "Title",
  xlab = "X axis",
  ylab = "Y axis",
  stitle = NULL,
  note = NULL,
  ctitles = "black",
  cscales = ctitles,
  cbgrid = "white",
  clgrid = cbgrid,
  cplot = "white",
  cserie = "black",
  cticks = "black",
  lwdserie = 1,
  pnote = 1,
  cbord = cplot,
  titlesize = 20,
  wordssize = 12,
  snote = 11,
  xlim = NULL
)

Arguments

Value

Return a dataframe with transformed columns.

Examples

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-04-01'),by='month'),"y"=c(5,3,7,2))

p.tsl(v,v$x,v$y,title="Simple example")

v=data.frame("x"=seq.Date(as.Date('2020-01-01'),
to = as.Date('2020-04-01'),by='month'),"y"=c(0.03,-0.05,0.08,-0.02))

p.tsl(v,v$x,v$y,percent=TRUE,title="Example with percent data",xlab=NULL,ylab=NULL)

p.tsl(v,v$x,v$y,percent=TRUE,yaccuracy=1,title="y accuracy set",xlab=NULL,ylab=NULL)

Percentual change

Description

pct_change calculate the percentual change in t periods of a serie. We can use this function to calculate the acumulated variation of an index, for example to calculate the accumulated variation in 12 months just set t parameter to 12

Usage

pct_change(data, colnum, t = nrow(data[colnum]) - 1, nafill = NA)

Arguments

Value

Return a dataframe.

Examples

v=data.frame(test=c(1,2,3,4,5,6,7,8,9,10,11,12,13))
pct_change(v)

Descritive statistic table

Description

stattable make a descritive statistic table.

Usage

stattable(data, horiz = FALSE, translate = FALSE)

Arguments

Value

Return a dataframe with descritive statistics.

Examples

v=data.frame(dataone=c(3,2,5,6,5,4),datatwo=c(33,22,55,66,55,44)
,datathree=c(133,122,155,166,155,144))
stattable(v) #vertical table
stattable(v,translate=TRUE) #vertical table translated
stattable(v,horiz=TRUE) #horizontal table
stattable(v,horiz=TRUE,translate=TRUE) #horizontal table translated