Package 'lar'

Title: History of labour relations package
Description: This package is intended for researchers studying historical labour relations (see http://www.historyoflabourrelations.org). The package allows for easy access of excel files in the standard defined by the Global Collaboratory on the History of Labour Relations. The package also allows for visualisation of labour relations according to the Collaboratory's format.
Authors: Richard Zijdeman [aut, cre], Josemiguel Lana-Berasain [ctb]
Maintainer: Richard Zijdeman <[email protected]>
License: GPL-3
Version: 0.1-2
Built: 2024-11-09 06:30:56 UTC
Source: CRAN

Help Index

Labour Relations

Description

This package is intended for researchers studying historical labour relations (see http://www.historyoflabourrelations.org). The package allows for easy access of excel files in the standard defined by the Global Collaboratory on the History of Labour Relations. The package also allows for visualisation of labour relations according to the Collaboratory's format.

Details

Package: lar
Type: Package
Version: 0.1-2
Date: 2014-04-29
License: GPL-3

Author(s)

Richard L. Zijdeman <[email protected]>

References

Project website: http://historyoflabourrelations.org

Examples

## Not run: 
  ## First read in a labour relations formatted excel file:
  df <- read.lar("Spain_1900_(JMTL-Sept2011).xlsx")

  ## Next, draw a treemap of the labour relations:
  draw.lar(df)
  
  ## Treemap with example data set for Spain in 1900
  data(spain.1900)
  draw.lar(spain.1900)
  
## End(Not run)

Draw Labour Relations

Description

This function draws a treemap of labour relations (http://historicallabourrelations.org). It is a convenience wrapper for the Treemap package by Martijn Tennekens. Before this function is used, data should be setup in a specific data format (see read.lar()).

Usage

draw.lar(data.frame, sex)

Arguments

data.frame

A data.frame in labour relations format. Required. See read.lar for more information on the format.
sex

One of "total" (default), "male", "female", to indicate respectively: the total population, the male population or the female population.

Note

The creation of this package was made by possible by the International Institute of Social History and research grants by the Gerda Henkel Stiftung and the Netherlands Organisation for Scientific Research (NWO).

Author(s)

Richard L. Zijdeman

References

Project website: http://historyoflabourrelations.org

See Also

read.lar, treemap.

Examples

## Not run:  
  ## First read in a labour relations pre-defined excel file:
  df <- read.lar("Spain_1900_(JMTL-Sept2011).xlsx")

  ## Next, draw a treemap of the labour relations:
  draw.lar(df)
  
  ## Treemap with example data set for Spain in 1900
  data(spain.1900)
  draw.lar(spain.1900)
  
  ## Save treemap image as .png
  data(spain.1900)
  ppi <- 300  # define pixels: increase this number for even better quality
  png(file = "tm_spain_1900.png",
      , width=10*ppi, height=8*ppi, res=ppi)
  draw.lar(spain.1900)
  dev.off() 
  
## End(Not run)

Labour Relation Taxonomy labels

Description

This dataset is for internal use of the lar package only. It attaches the official Labour Relations Taxonomy labels to data read in by the read.lar function.

Format

A data frame with 49 observations on the following 4 variables.

lr.cat

a factor with levels -1 1 10 1012 11 12 12013 12013014 12013014018 12014 12014018 1201404 12015 1213 13 13012 13014 14 14012 14015 14018 142 143 15 16 17 171 172 18 181 182 183 2 3 4 4014 405 405012 5 5012014 5014 508014 5a 5b 6 7 7018 8 9

lr.txt.1

a factor with levels Commodified EitherOr Non working Reciprocal Tributary Unknown

lr.txt.2

a factor with levels Community EitherOr Household Market Non-market Unknown

lr.txt.3.ext

a factor with levels Affluent (2) Cannot work (1) EitherOr Employers (13) Household Indent.lbr. (15) Indent.lbr. (9) Kin non-prod. (5b) Kin prod. (5) Kin prod. (5a) Leading prod. (4) Multiple Obligatory lbr. (8) Redist.lbr. (7) Self-Employed (12) Serfs (10) Serfs (16) Servants (6) Slaves (11) Slaves (17) Unemployed (3) Unknown Wage-Earners (14) Wage-Earners (18)

Details

Currently (lar package version 0.1), the labels still contain a label for labrel 5, but users should be aware that currently only labrels 5a and 5b should be used.

Source

https://collab.iisg.nl/c/document_library/get_file?p_l_id=273223&folderId=277142&name=DLFE-186117.pdf

References

International Institute of Social History. 2014. Codebook and manual for gathering and entering data in the database of the global collaboratory on the history of labour relations 1500-2000. Version 13, January 14

Read in labour relations file (read.lar)

Description

The function read.lar() reads in a labour relations excel-input-file and attaches convenience labels for labour relations to be used with draw.lar().

Usage

read.lar(file)

Arguments

file

An excel file (.xlsx) in labour relations input-format. Required.

Note

The creation of this package was made by possible by the International Institute of Social History and research grants by the Gerda Henkel Stiftung and the Netherlands Organisation for Scientific Research (NWO).

Author(s)

Richard L. Zijdeman

References

Project website: http://historyoflabourrelations.org

See Also

draw.lar.

Examples

## Not run: 
  ## Read in a labour relations pre-defined excel file:
  df <- read.lar("Spain_1900_(JMTL-Sept2011).xlsx")
  
## End(Not run)

Spain_1900_(JMTL-Sept2011).xlsx (MS Excel file)

Description

This file describes the labour relations in Spain in 1900. The file was kindly provided by Prof. Lana-Berasain. See details for restricted use of this data.

Usage

data(spain.1900)

Format

A data frame with 823 observations on the following 52 variables.

labour.rel.3

a numeric vector

labour.rel.2

a numeric vector

labour.rel.1

a numeric vector

id.labrel

a numeric vector

id.pop

a numeric vector

day

a numeric vector

month

a numeric vector

year

a numeric vector

year.start

a numeric vector

year.end

a numeric vector

locality

a factor with levels [Text/NA] NA

urbanized

a factor with levels [Y/N/NA] NA Y

region

a factor with levels [Text/NA] NA

country

a factor with levels [mandatory] [Text] Spain

total

a numeric vector

minimum

a numeric vector

maximum

a numeric vector

quality.total

a factor with levels [A/C/E] [mandatory] A C

gender

a factor with levels [mandatory] [T/M/F/U] F M T

mar.stat

a factor with levels [mandatory] [T/M/S/W/D/U] M S T U W

age.start

a numeric vector

age.end

a numeric vector

type.activity

a factor with levels [mandatory] [P/L (+a/c/d/j)] L P

branch

a factor with levels Affluents Agricultural and animal husbandry workers Architects, engineers, etc Authors, journalists and related writers beggars,tramps and prostitutes Bookkeepers, cashiers and related workers Bookkeepers, cashiers, etc Bricklayers, carpenters, etc Buyers Cabinetmakers and related woodworkers Chemical processors Children Clerical and related workers Composers and perfoming artists Composers and performing artists Convicts and prisoners Cook, waiters, bartenders, etc Cooks, waiters, bartenders, etc Electrical fitters and related electrical and electronical workers Food and beverages processors Glass formers, potters,etc Government executive officials Housekeeping services workers Jurists Machinery fitters, machine assemblers, etc Machinery fitters, machine assemblers,etc Maids and Housekeeping services workers Mail distribution clerks Managers Material handling and related equipment operators, etc Medical, dental, veterinary, etc Metal processors Miners, quarrymen, well-drillers,etc NA Not working Other production workers Patients, people in hospices, mads and alienated Primary school Printers and related workers Protective services workers Retired and State pensioners Sales workers Salesmen, shop assistants, etc Sculptors, painters, photographers,etc Service workers not classified Spinners, weavers, knitters, dyers,etc Stenographers, typists,etc Students Tailors, dressmakers, sewers, upholsterers, etc Tanners, fellmongers and pelt dressers Teachers Text/NA Transport equipment operators Unemployed Wood preparation workers Workers Workers in Religion Workers not elsewhere classified Working proprietors (wholesale and retail)

branch.hisco

a factor with levels [0-9/NA] [note instructions] 0 1 2 3 4 5 6 7 8 9 NA

occup

a factor with levels "corretaje, comisión, exportación" "negociantes, comerciantes, tratantes" [Text/NA] Actors and performing artists Agricultural workers Architects and engineers Army Assistants to the cult Authors Bookkeepers and cashiers Building sales workers Cabinetmakers and woodworkers Chemical processors Chemical product,hardware and paint sales workers Circus performers Civil service workers Clerical and related workers (empleados) Clothing industry Combustible sales workers Composers, musicians and singers Construction workers Creative artists Domestic servant Domestic service Double counted professions Dress and hat sales workers Energy workers Finance clerk and Insurance Fishermen and hunters Food and beverages processors Food and beverages sales workers Furniture sales workers General managers (industriales, fabricantes) Hotels, coffe bars, guest houses and bars Individuals without profession Jurists ('profesiones judiciales') Leather and hide workers Leather sales workers Livestock workers Luxury products, Sciences and Arts products sales Machinery mechanic Mail, telephone and telegraph Medical workers Members of Religious Orders (clero regular) Metal workers Metals sales workers Military Miners and quarrymen Ministers of non catolic cults Ministers of religion (clero católico secular) Momentarily unemployed NA Policemen (guardia civil, carabineros y policía) Pottery sales workers Pottery workers Printers and related workers Prostitute Sales workers not clasified Salesmen, shop assistants and demonstrators Stenographers, typists, translators Teachers Textile sales workers Textile workers Transport by railway Transport by rivers and canals Transport by sea Transport by streets, roads and bridges Transport machine makers Transport sales workers Undertakers and embalmers Unknown profession Waiters (mozo de almacén,mozo de comedor,camarero) Warehouse porters Waste materials processors and other industries Waste materials sales workers Wood sales workers Wood treaters Workers (jornaleros,braceros,peones,destajistas)

occup.hisco

a factor with levels [010-999/NA] 020 061 120 130 141 149 151 161 171 173 175 211 310 321 331 339 370 393 410 422 451 490 532 540 582 583 592 599 621 624 649 711 720 731 749 750 761 779 791 810 841 849 859 892 920 949 950 971 981 984 989 999 NA

position

a factor with levels [Text/NA] Affluents (personas que viven de sus rentas) Family members NA Retired and State pensioners

nationality

a factor with levels [Text/NA] NA

ethnicity

a factor with levels [Text/NA] NA

race

a factor with levels [Text/NA] NA

religion

a factor with levels [Text/NA] NA

social.group

a factor with levels [Text/NA] NA

source

a numeric vector

volume

a numeric vector

page

a factor with levels [#/Text/NA] 210-219 27-29 298-323 323 479

labour.rel.1.pct

a numeric vector

labour.rel.2.pct

a numeric vector

labour.rel.3.pct

a numeric vector

remark

a factor with levels [Text/NA] 349 settlements with more than 5000 inhabitants Also classificable as HISCO 441 Children included in the group "retirados, pensionistas del Estado y de otras administraciones públicas y privadas" It has been supposed that children and old persons were kin producers Marital status unknown NA The shares of self-employed and wage earners has been estimated according to the average of salaried workers in 1860 and 1955 (sources 14 and 15, pp.162-163) The shares of self-employed and wage earners has been estimated according to the share of patrons in the census of 1920 (source 11, V, pp.421-424, 487) The source gives that number as age unclasified The source warns that the excess of 135,120 were persons registered with more than one profession Youngmen included in the group "retirados, pensionistas del Estado y de otras administraciones públicas y privadas"

txt1.1

a factor with levels Commodified EitherOr Non working Reciprocal Tributary Unknown

txt1.2

a factor with levels Community EitherOr Household Market Non-market Unknown

txt1.3.ext

a factor with levels Affluent (2) Cannot work (1) EitherOr Employers (13) Household Indent.lbr. (15) Indent.lbr. (9) Kin non-prod. (5b) Kin prod. (5) Kin prod. (5a) Leading prod. (4) Multiple Obligatory lbr. (8) Redist.lbr. (7) Self-Employed (12) Serfs (10) Serfs (16) Servants (6) Slaves (11) Slaves (17) Unemployed (3) Unknown Wage-Earners (14) Wage-Earners (18)

txt2.1

a character vector

txt2.2

a factor with levels Community EitherOr Household Market Non-market Unknown

txt2.3.ext

a factor with levels Affluent (2) Cannot work (1) EitherOr Employers (13) Household Indent.lbr. (15) Indent.lbr. (9) Kin non-prod. (5b) Kin prod. (5) Kin prod. (5a) Leading prod. (4) Multiple Obligatory lbr. (8) Redist.lbr. (7) Self-Employed (12) Serfs (10) Serfs (16) Servants (6) Slaves (11) Slaves (17) Unemployed (3) Unknown Wage-Earners (14) Wage-Earners (18)

txt3.1

a numeric vector

txt3.2

a factor with levels Community EitherOr Household Market Non-market Unknown

txt3.3.ext

a factor with levels Affluent (2) Cannot work (1) EitherOr Employers (13) Household Indent.lbr. (15) Indent.lbr. (9) Kin non-prod. (5b) Kin prod. (5) Kin prod. (5a) Leading prod. (4) Multiple Obligatory lbr. (8) Redist.lbr. (7) Self-Employed (12) Serfs (10) Serfs (16) Servants (6) Slaves (11) Slaves (17) Unemployed (3) Unknown Wage-Earners (14) Wage-Earners (18)

sortID2

a numeric vector

ctry.time

a character vector

bmyear

a numeric vector

Details

This dataset originates from the Labour Relations Collaboratory and specifically describes labour relations in Spain in 1900. The dataset and others in the project including full documentation and licenses are available from: http://www.historyoflabourrelations.org, hosted by the International Institute of Social History (http://socialhistory.org). The dataset is constructed by Professor José-Miguel Lana-Berasain who has kindly agreed for this dataset to be used in the lar-package. Use of the dataset is limited to the conditions specified at the Collaboratory website: http://www.historyoflabourrelations.org .

Source

https://collab.iisg.nl/c/document_library/get_file?p_l_id=273223&folderId=283117&name=DLFE-91302.pdf

References

Lana-Berasain, J-M. ?. Labour Relations in Spain, 1800, 1900 and 2001: A methodological approach. URL: https://collab.iisg.nl/c/document_library/get_file?p_l_id=273223&folderId=283117&name=DLFE-91302.pdf. Last accessed: April 28, 2014.

Examples

data(spain.1900)