| Title: | Macroeconomics Tools |
|---|---|
| Description: | 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>. |
| Authors: | João Victor Gomes de Araujo Santana [aut, cre] |
| Maintainer: | João Victor Gomes de Araujo Santana <[email protected]> |
| License: | GPL-3 |
| Version: | 1.0.0 |
| Built: | 2024-11-21 03:04:12 UTC |
| Source: | https://github.com/jvg0mes/metools |
col2char transform columns type to character.
col2char(x, start, end = ncol(x))col2char(x, start, end = ncol(x))
x |
a dataframe |
start |
number of start column |
end |
number of last column (default=last) |
Return a dataframe with transformed columns.
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 characterv=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
col2factor transform columns type to factor.
col2factor(x, start, end = ncol(x))col2factor(x, start, end = ncol(x))
x |
a dataframe |
start |
number of start column |
end |
number of last column (default=last) |
Return a dataframe with transformed columns.
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 characterv=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
col2num transform columns type to numeric.
col2num(x, start, end = ncol(x))col2num(x, start, end = ncol(x))
x |
a dataframe |
start |
number of start column |
end |
number of last column (default=last) |
Return a dataframe with transformed columns.
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 characterv=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
col2percent transform columns to percent.
col2percent(x, start, end = ncol(x), mult100 = FALSE)col2percent(x, start, end = ncol(x), mult100 = FALSE)
x |
a dataframe |
start |
number of start column |
end |
number of last column (default=last) |
mult100 |
multiply by 100 if the number is a decimal fraction(T or F)(default=F) |
Return a dataframe with transformed columns.
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)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)
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.
colpct2num(x, start, end = ncol(x), div100 = TRUE)colpct2num(x, start, end = ncol(x), div100 = TRUE)
x |
a dataframe |
start |
number of start column |
end |
number of last column (default=last) |
div100 |
division by 100 (T or F)(default=T) |
Return a dataframe with transformed columns.
v=data.frame(c(15,5,20,50,10)) v=col2percent(v,start=1) v=colpct2num(v,start=1,div100=TRUE)v=data.frame(c(15,5,20,50,10)) v=col2percent(v,start=1) v=colpct2num(v,start=1,div100=TRUE)
colround round defined columns.
colround(x, start, end = ncol(x), digits)colround(x, start, end = ncol(x), digits)
x |
a dataframe |
start |
number of start column |
end |
number of last column (default=last) |
digits |
number of round digits |
Return a dataframe with transformed columns.
v=data.frame(c(3.255,5.826,4.567,2.462)) v=colround(v,1,digits=1)v=data.frame(c(3.255,5.826,4.567,2.462)) v=colround(v,1,digits=1)
cum_var calculates an accumulated variation of a rate, _var means the data must be a percentage variation.
cum_var(data, colnum, t, div100 = FALSE)cum_var(data, colnum, t, div100 = FALSE)
data |
a dataframe |
colnum |
number of column |
t |
number of periods to accumulate |
div100 |
divide data by 100, use if data is not fraction |
Return a dataframe.
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)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)
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.
cuminyear(data, coldate, colnum, start = 1)cuminyear(data, coldate, colnum, start = 1)
data |
a dataframe |
coldate |
number of date column |
colnum |
number of values column |
start |
number of start row |
Return a dataframe.
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)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)
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.
cuminyear_var(data, coldate, colnum, div100 = FALSE)cuminyear_var(data, coldate, colnum, div100 = FALSE)
data |
a dataframe |
coldate |
number of date column |
colnum |
number of values column |
div100 |
divide data by 100, use if data is not fraction |
Return a dataframe.
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)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)
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.
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 )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 )
data |
a dataframe |
ncolx |
number of x column in data frame |
ncoly |
number of y column in data frame |
ntimes |
number of observations to plot (count by tail) |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
div100 |
If data percent are not in decimal format set TRUE. |
percent |
If TRUE, y axis in percent (default=F) |
fontsize |
change size of all words in graphic (only numbers) |
cserie |
change color of serie |
clines |
color of lines in graphic |
ctext |
color of words in graphic |
cbackground |
color of graphic background |
cbserie |
color of serie border (default= same cbackground) |
Return a graphic.
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)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)
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.
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 )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 )
data |
a dataframe |
ncolx |
number of x column in data frame |
ncoly |
number of y column in data frame |
ntimes |
number of observations to plot (count by tail) |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
percent |
If TRUE, y axis in percent (default=F) |
div100 |
If data percent are not in decimal format set TRUE. |
dec |
If TRUE, bars plot in decrescent order. |
fontsize |
change size of all words in graphic (only numbers) |
cserie |
change color of serie |
clines |
color of lines in graphic |
ctext |
color of words in graphic |
cbackground |
color of graphic background |
cbserie |
color of serie border (default= same cbackground) |
Return a graphic.
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)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)
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.
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 )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 )
data |
a dataframe |
ncolx |
number of x column in data frame |
ncoly |
number of y column in data frame |
ntimes |
number of observations to plot (count by tail) |
title |
title of plot |
legtitle |
title of legendbox |
xlab |
x axis label |
ylab |
y axis label |
dec |
If TRUE serie come be decrescent,if FALSE crescent(default=F) |
div100 |
If data percent are not in decimal format set TRUE. |
percent |
If TRUE, y axis in percent (default=F) |
fontsize |
change size of all words in graphic (only numbers) |
colors |
colors of bars |
clines |
color of lines in graphic |
ctext |
color of words in graphic |
cbackground |
color of graphic background |
cbserie |
color of serie border (default= same cbackground) |
legwpos |
legend words position (numeric) |
legheight |
height of legend box |
Return a graphic.
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)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)
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.
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 )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 )
data |
a dataframe |
ncolx |
number of x column in data frame |
ncoly |
number of y column in data frame |
ntimes |
number of observations to plot (count by tail) |
title |
title of plot |
legtitle |
title of legendbox |
xlab |
x axis label |
ylab |
y axis label |
div100 |
If data percent are not in decimal format set TRUE. |
percent |
If TRUE, y axis in percent (default=F) |
fontsize |
change size of all words in graphic (only numbers) |
colors |
colors of bars |
clines |
color of lines in graphic |
ctext |
color of words in graphic |
cbackground |
color of graphic background |
cbserie |
color of serie border (default= same cbackground) |
legwpos |
legend words position (numeric) |
legheight |
height of legend box |
Return a graphic.
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)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)
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.
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" )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" )
data |
a dataframe |
ncolx |
number of x column in data frame |
ncoly |
number of y column in data frame |
ntimes |
number of observations to plot (count by tail) |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
div100 |
If data percent are not in decimal format set TRUE. |
percent |
If TRUE, y axis in percent (default=F) |
fontsize |
change size of all words in graphic (only numbers) |
lwdserie |
size of serie |
cserie |
change color of serie |
clines |
color of lines in graphic |
ctext |
color of words in graphic |
cbackground |
color of graphic background |
Return a graphic.
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)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)
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.
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 )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 )
data |
a dataframe |
ncolx |
number of x column in data frame |
ncoly |
number of y column in data frame |
ntimes |
number of observations to plot (count by tail) |
title |
title of plot |
ylab |
y axis label |
percent |
If TRUE y axis in percent (default=F) |
div100 |
If data percent are not in decimal format set TRUE. |
fontsize |
change size of all words in graphic (only numbers) |
datebreaks |
datebreaks in x axis (default="1 month") |
dateformat |
format of date in x axis (need a dataformat string) (default ="%Y-%m") |
clines |
color of lines in graphic |
ctext |
color of words in graphic |
cbackground |
color of graphic background |
cbserie |
color of serie border (default= same cbackground) |
Return a graphic.
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)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)
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.
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 )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 )
data |
a dataframe |
ncolx |
number of x column in data frame |
ncoly |
number of y column in data frame |
ntimes |
number of observations to plot (count by tail) |
title |
title of plot |
ylab |
y axis label |
percent |
If TRUE y axis in percent (default=F) |
div100 |
If data percent are not in decimal format set TRUE. |
fontsize |
change size of all words in graphic (only numbers) |
datebreaks |
datebreaks in x axis (default="1 month") |
dateformat |
format of date in x axis (need a dataformat string) (default ="%Y-%m") |
cserie |
color of serie |
clines |
color of lines in graphic |
ctext |
color of words in graphic |
cbackground |
color of graphic background |
cbserie |
color of serie border (default= same cbackground) |
Return a graphic.
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)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)
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.
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" )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" )
data |
a dataframe |
ncolx |
number of x column in data frame |
ncoly |
number of y column in data frame |
ntimes |
number of observations to plot (count by tail) |
title |
title of plot |
ylab |
y axis label |
percent |
If TRUE y axis in percent (default=F) |
div100 |
If data percent are not in decimal format set TRUE. |
fontsize |
change size of all words in graphic (only numbers) |
lwdserie |
size of serie |
datebreaks |
datebreaks in x axis (default="1 month") |
dateformat |
format of date in x axis (need a dataformat string) (default ="%Y-%m") |
cserie |
color of serie |
clines |
color of lines in graphic |
ctext |
color of words in graphic |
cbackground |
color of graphic background |
Return a graphic.
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)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)
me.lag lag a vector if t>0 or lead a vector if t<0.
me.lag(x, t = 1, nafill = NA, extrapolate = FALSE)me.lag(x, t = 1, nafill = NA, extrapolate = FALSE)
x |
a vector |
t |
number of times to lag (default=1) |
nafill |
set value to fill NA's before first t value |
extrapolate |
if TRUE extrapolate excedent values, only if t>0 (default=FALSE) |
Return a vector.
v=c(3,2,5,6,5,4) me.lag(v) #now lead me.lag(v,t=-1)v=c(3,2,5,6,5,4) me.lag(v) #now lead me.lag(v,t=-1)
Transforms columns into rows and rows into columns.
me.spread(data, namenc = " ", mode = FALSE)me.spread(data, namenc = " ", mode = FALSE)
data |
a dataframe |
namenc |
name of new column (first column) (default="") |
mode |
if results are incorretly try set this to TRUE |
Return a dataframe.
v=data.frame('date'=c('2016','2017'),'value1'=c(12,10),'value2'=c(8,6)) me.spread(v,namenc='old header')v=data.frame('date'=c('2016','2017'),'value1'=c(12,10),'value2'=c(8,6)) me.spread(v,namenc='old header')
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>.
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.
João Victor Gomes ([email protected])
Useful links:
https://metoolsr.wordpress.com https://github.com/jvg0mes/metools https://jvg0mes.github.io/metoolsr
Use this function to receive help to use metools.
metools.help()metools.help()
Return a info.
metools.help()metools.help()
month2num transform month names to month numbers
month2num(date)month2num(date)
date |
a month names vector |
Return a month numbers.
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$date) v[[1]] = month2num(v[[1]])v=c("jan","fev","mar","abr","mai","jun","jul","ago","set","out","nov","dez") month2num(v) v=data.frame('date'=c("janeiro","fevereiro",'março','abril'),'values'=c(18,27,10,48)) month2num(v$date) #or month2num(v[[1]]) #you can substitute column with function: v$date = month2num(v$date) v[[1]] = month2num(v[[1]])
mp.s make a plot with one or more series. The object parameter require a ggplot object (Look at the examples).
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 )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 )
object |
a ggplot graphic object |
xaxis |
x axis of one of your graphics |
yaxis |
y axis of one of your graphics |
ybreaks |
number of y axis breaks (default=10) |
percent |
If TRUE y axis in percent (default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cticks |
color of axis ticks |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
xlim |
limit of x axis (default=NULL) |
Return a graphic.
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$y,title="Example with colorbypositive",xlab=NULL,ylab=NULL)v=data.frame("x"=c('a','b','c','d','e'),"y"=c(5,3,7,10,9),"y2"=c(7,2,5,8,7)) g= ggplot2::ggplot()+ggplot2::geom_line(mapping=ggplot2::aes(x=v$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)
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).
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 )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 )
object |
a ggplot graphic object |
xaxis |
x axis of one of your graphics |
yaxis |
y axis of one of your graphics |
dateformat |
format of date in x axis (need a dataformat string) (default ="%Y-%m") |
datebreaks |
datebreaks in x axis (default="1 month") |
ybreaks |
number of y axis breaks (default=10) |
percent |
If TRUE y axis in percent (default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cticks |
color of axis ticks |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
xlim |
limit of x axis (default=NULL) |
Return a graphic.
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$y,title="Example with colorbypositive",xlab=NULL,ylab=NULL)v=data.frame("x"=seq.Date(as.Date('2020-01-01'), to = as.Date('2020-05-01'),by='month'),"y"=c(5,3,7,10,9),"y2"=c(7,2,5,8,7)) g= ggplot2::ggplot()+ggplot2::geom_line(mapping=ggplot2::aes(x=v$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)
num2month transform month numbers to month names
num2month(date, abbreviate = FALSE, ptbr = FALSE)num2month(date, abbreviate = FALSE, ptbr = FALSE)
date |
a month numbers vector |
abbreviate |
abbreviate months name |
ptbr |
transalate result to "Portugues (Brasil)". |
Return a month names.
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$date) v[[1]] = num2month(v[[1]]) #The data can be a string, but is recommended use numbers, #see a string examples: v=c('01','02','03','04','05','06','07','08','09','10','11','12') num2month(v) v=c('1','2','3','4','5','6','7','8','9','10','11','12') num2month(v)v=c(01,02,03,04,05,06,07,08,09,10,11,12) num2month(v) num2month(v,abbreviate=TRUE) num2month(v,abbreviate=FALSE,ptbr=TRUE) num2month(v,abbreviate=TRUE,ptbr=TRUE) v=data.frame('date'=c(01,02,03,04),'values'=c(18,27,10,48)) num2month(v$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)
p.col make a bar plot.
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 )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 )
data |
a dataframe |
xaxis |
x axis data |
yaxis |
y axis data |
ybreaks |
number of y axis breaks (default=10) |
percent |
If TRUE y axis in percent (default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cserie |
color of serie |
cbserie |
color of serie border (default= same cserie) |
cticks |
color of axis ticks |
lwdserie |
size of serie |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
xlim |
limit of x axis (default=NULL) |
Return a graphic.
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]])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]])
p.col_ord make a ordered bar plot.
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 )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 )
data |
a dataframe |
xaxis |
x axis data |
yaxis |
y axis data |
ybreaks |
number of y axis breaks (default=10) |
dec |
If TRUE serie come be decrescent,if FALSE crescent(default=F) |
percent |
If TRUE y axis in percent (default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cserie |
color of serie |
cbserie |
color of serie border (default= same cserie) |
cticks |
color of axis ticks |
lwdserie |
size of serie |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
xlim |
limit of x axis (default=NULL) |
Return a graphic.
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)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)
p.col_ord_wl make a ordered bar plot with legend.
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) )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) )
data |
a dataframe |
xaxis |
x axis data |
yaxis |
y axis data |
ybreaks |
number of y axis breaks (default=10) |
percent |
If TRUE y axis in percent (default=F) |
dec |
If TRUE serie come be decrescent,if FALSE crescent(default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cbserie |
color of serie border (default= same cserie) |
cticks |
color of axis ticks |
lwdserie |
size of serie |
legtitle |
title of legend box |
legsize |
size of legend |
cleg |
color of legend words |
legheight |
height of legend box |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
legpos |
legend position |
legdir |
legend direction |
legcol |
color of legend box |
legspa |
spacement in legend box |
legvjust |
vertical adjust in legend box |
colors |
colors of bars, need same number of correspondencies. |
Return ordered bar plot with legend.
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$x),alpha=0.8))v=data.frame("x"=1:5,"y"=c(10,4,8,5,2)) p.col_ord_wl(v,xaxis= v$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))
p.col_wl make a bar plot with legend.
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) )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) )
data |
a dataframe |
xaxis |
x axis data |
yaxis |
y axis data |
ybreaks |
number of y axis breaks (default=10) |
percent |
If TRUE y axis in percent (default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cbserie |
color of serie border (default= same cserie) |
cticks |
color of axis ticks |
lwdserie |
size of serie |
legtitle |
title of legend box |
legsize |
size of legend |
cleg |
color of legend words |
legheight |
height of legend box |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
legpos |
legend position |
legdir |
legend direction |
legcol |
color of legend box |
legspa |
spacement in legend box |
legvjust |
vertical adjust in legend box |
colors |
colors of bars, need same number of correspondencies. |
Return a dataframe with transformed columns.
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'))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'))
p.colorbypositive is a function to create a vector with colors by positive or negative. Recommended to color graphics created with metools p.functions.
p.colorbypositive(x, colorp = "#17B221", colorn = "#B21717")p.colorbypositive(x, colorp = "#17B221", colorn = "#B21717")
x |
a numeric vector |
colorp |
Positive values color (default=Green) |
colorn |
Negative values color (default=Red) |
Return a vector with colors.
v=c(-3,-2,2,-2,3,2) p.colorbypositive(x=v,colorp="blue",colorn="grey") barplot(v,col=p.colorbypositive(v))v=c(-3,-2,2,-2,3,2) p.colorbypositive(x=v,colorp="blue",colorn="grey") barplot(v,col=p.colorbypositive(v))
p.colorbyvar is a function to create a vector with colors by variation. Recommended to color graphics created with metools p.functions.
p.colorbyvar(x, colorp = "#17B221", colorn = "#B21717", lag = 1)p.colorbyvar(x, colorp = "#17B221", colorn = "#B21717", lag = 1)
x |
a numeric vector |
colorp |
Positive changes color (default=Green) |
colorn |
Negative changes color (default=Red) |
lag |
Lag to comparison (default=1) |
Return a vector with colors.
v=c(3,2,5,6,5,4) p.colorbyvar(x=v,colorp="blue",colorn="grey") barplot(v,col=p.colorbyvar(v))v=c(3,2,5,6,5,4) p.colorbyvar(x=v,colorp="blue",colorn="grey") barplot(v,col=p.colorbyvar(v))
p.gradientcolor is a function to make easy create gradient pallet. Recommended to color graphics created with metools p.functions.
p.gradientcolor(color1, color2, n)p.gradientcolor(color1, color2, n)
color1 |
First gradient color |
color2 |
Last gradient color |
n |
Number of colors |
Return a vector with colors.
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)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)
p.line make a line plot.
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 )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 )
data |
a dataframe |
xaxis |
x axis data |
yaxis |
y axis data |
ybreaks |
number of y axis breaks (default=10) |
percent |
If TRUE y axis in percent (default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cserie |
color of serie |
cticks |
color of axis ticks |
lwdserie |
size of serie |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
xlim |
limit of x axis (default=NULL) |
Return a line graphic.
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]])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]])
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.
p.seqdatebreaks(x, periodicity)p.seqdatebreaks(x, periodicity)
x |
Time data from a Timeserie |
periodicity |
Time interval (string) |
Return a vector with timeinterval.
x <- seq.Date(from=as.Date("2019-01-01"),to=as.Date("2020-01-01"),by=1) p.seqdatebreaks(x,periodicity= "2 month")x <- seq.Date(from=as.Date("2019-01-01"),to=as.Date("2020-01-01"),by=1) p.seqdatebreaks(x,periodicity= "2 month")
p.tscol make a bar plot in time serie format. The data don't need be a ts object.
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 )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 )
data |
a dataframe |
xaxis |
x axis data |
yaxis |
y axis data |
dateformat |
format of date in x axis (need a dataformat string) (default ="%Y-%m") |
datebreaks |
datebreaks in x axis (default="1 month") |
ybreaks |
number of y axis breaks (default=10) |
percent |
If TRUE y axis in percent (default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cserie |
color of serie |
cbserie |
color of serie border (default= same cserie) |
cticks |
color of axis ticks |
lwdserie |
size of serie |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
xlim |
limit of x axis (default=NULL) |
Return a graphic.
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 casev=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
p.tsl make a line plot in time serie format. The data don't need be a ts object.
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 )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 )
data |
a dataframe |
xaxis |
x axis data |
yaxis |
y axis data |
dateformat |
format of date in x axis (need a dataformat string) (default ="%Y-%m") |
datebreaks |
datebreaks in x axis (default="1 month") |
ybreaks |
number of y axis breaks (default=10) |
percent |
If TRUE y axis in percent (default=F) |
yaccuracy |
a round for y axis (default=0.01) |
ydecimalmark |
y decimal mark (default=".") |
title |
title of plot |
xlab |
x axis label |
ylab |
y axis label |
stitle |
subtitle |
note |
note |
ctitles |
color of titles (title,xlab,ylab) |
cscales |
color of the scales (default= same ctitles) |
cbgrid |
color of grid background |
clgrid |
color of grid lines |
cplot |
color of plot background |
cserie |
color of serie |
cticks |
color of axis ticks |
lwdserie |
size of serie |
pnote |
position of note (default=1) (only numbers) |
cbord |
color of plot border (default= same cplot) |
titlesize |
size of title (default=20) (only numbers) |
wordssize |
size of words (default=12) (only numbers) |
snote |
size of note (default=11) (only numbers) |
xlim |
limit of x axis (default=NULL) |
Return a dataframe with transformed columns.
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)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)
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
pct_change(data, colnum, t = nrow(data[colnum]) - 1, nafill = NA)pct_change(data, colnum, t = nrow(data[colnum]) - 1, nafill = NA)
data |
a dataframe |
colnum |
number of column |
t |
number of periods to accumulate (default= number of rows) |
nafill |
set value to fill NA's before first t value |
Return a dataframe.
v=data.frame(test=c(1,2,3,4,5,6,7,8,9,10,11,12,13)) pct_change(v)v=data.frame(test=c(1,2,3,4,5,6,7,8,9,10,11,12,13)) pct_change(v)
stattable make a descritive statistic table.
stattable(data, horiz = FALSE, translate = FALSE)stattable(data, horiz = FALSE, translate = FALSE)
data |
a dataframe |
horiz |
defines table be a horizontal table (default=FALSE) |
translate |
if TRUE translate table to PT-BR (default=FALSE) |
Return a dataframe with descritive statistics.
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 translatedv=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