* Re: Re; TABLE help
2010-12-10 16:51 barney schwartz
@ 2010-12-10 17:24 ` Wolfgang Schuster
0 siblings, 0 replies; 3+ messages in thread
From: Wolfgang Schuster @ 2010-12-10 17:24 UTC (permalink / raw)
To: barney schwartz; +Cc: mailing list for ConTeXt users
Am 10.12.2010 um 17:51 schrieb barney schwartz:
> full file is attached
When you don’t write many formulas in your document you can use \asciimode which makes $ and & normal letters which can be written without a leading backslash, there is also a alternative mode for natural tables which is suitable for tables with many small fields.
<example>
\asciimode
\starttext
\chapter{Data Description}
The data is from The Survey of Family Income and Expenditure for
Taiwan. This is the micro response data provided by The
Directorate General of Budget, Accounting and Statistics of the
Republic of China.
Taiwan also conducts a Monthly Manpower Utilization Survey. This
survey is also run by DGBAS, however at a cost of \$80 per ten
items and hundreds of items within the survey just one year of
this data is beyond my meager resources. Zveglich et al used this
survey.
I chose the Survey of Family Income and Expenditure for the
richness of the data set, and because it should be a
representative sample of the Taiwan population. Also, it is
comparable to the Current Population Survey (CPS) in the U.~S.~
and the Survey of Consumer Finances (SCF) in Canada. My data does
not depend on sources of income, rather all components of income
are included. It contains variables that will allow future
in-depth research into the dynamics of income distribution in
Taiwan. There is much yet to be done in this area.
This survey is conducted annually. In all years it uses a
two-stage stratified random sample of between 14,000 and 16,500
families by physical location. . It is an in-person survey
conducted by interview. A small percentage of households are
required to keep daily accounts of income and expenditures. These
accounts are used to adjust figures in the remaining sample for
inaccuracies of memory.
\placetable[here,split][tab:five]{Descriptive Statistics for Salaried Men & Women}
{\startTABLE[split=repeat]
\startTABLEhead[style=bold]
\NC Group \NC N \NC MEAN \NC STD \NC MIN \NC MAX \NC Gini \NC 80/20 \NC\NR
\stopTABLEhead
\startTABLEbody
\NC[nc=8] 1980 \NC\NR
\NC ALL \NC 14202 \NC $ 195,727.9 \NC 912.89 \NC $ 3600 \NC $ 1,320,000 \NC 0.278 \NC 4.54 \NC\NR
\NC Men \NC 9852 \NC $ 224,678.5 \NC 1123.61 \NC $ 3600 \NC $ 1,320,000 \NC 0.242 \NC 3.68 \NC\NR
\NC Women \NC 4350 \NC $ 130,159.7 \NC 991.05 \NC $ 5000 \NC $ 448,000 \NC 0.259 \NC 3.91 \NC\NR
\NC[nc=8] 1982 \NC\NR
\NC ALL \NC 14706 \NC $ 164,247 \NC 766 \NC $ 7200 \NC $ 1,257,630 \NC 0.284 \NC 4.59 \NC\NR
\NC Men \NC 9943 \NC $ 201,482 \NC 1008 \NC $ 7200 \NC $ 1,257,630 \NC 0.247 \NC 3.79 \NC\NR
\NC Women \NC 4673 \NC $ 19,910 \NC 951 \NC $ 12000 \NC $ 650,000 \NC 0.275 \NC 4.14 \NC\NR
\NC[nc=8] 1984 \NC\NR
\NC ALL \NC 15872 \NC $ 189,845 \NC 867 \NC $ 4000 \NC $ 1,500,000 \NC 0.286 \NC 4.54 \NC\NR
\NC Men \NC 10291 \NC $ 222,035 \NC 1121 \NC $ 4000 \NC $ 1,500,000 \NC 0.249 \NC 3.75 \NC\NR
\NC Women \NC 5581 \NC $ 130,488 \NC 917 \NC $ 7500 \NC $ 850,000 \NC 0.264 \NC 3.91 \NC\NR
\NC[nc=8] 1986 \NC\NR
\NC ALL \NC 16371 \NC $ 200,997 \NC 966 \NC $ 3,600 \NC $ 2,990,000 \NC 0.294 \NC 4.69 \NC\NR
\NC Men \NC 10213 \NC $ 237,554 \NC 1299 \NC $ 5,000 \NC $ 2,990,000 \NC 0.257 \NC 3.94 \NC\NR
\NC Women \NC 6158 \NC $ 140,367 \NC 1001 \NC $ 3,600 \NC $ 965,000\NC 0.273 \NC 4.08 \NC\NR
\NC[nc=8] 1988 \NC\NR
\NC ALL \NC 16032 \NC $ 234,304 \NC 1015 \NC $ 9,000 \NC $ 1,800,000 \NC 0.277 \NC 4.29 \NC\NR
\NC Men \NC 10058 \NC $ 273,829 \NC 1306 \NC $ 9,000 \NC $ 1,800,000 \NC 0.238 \NC 3.55 \NC\NR
\NC Women \NC 5974 \NC $ 167,760 \NC 1189 \NC $ 28,000 \NC $ XXXXXXX \NC 0.262 \NC 3.75 \NC\NR
\NC[nc=8] 1990 \NC\NR
\NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR
\NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR
\NC Women \NC 6199 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR
\NC[nc=8] 1992 \NC\NR
\NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR
\NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR
\NC Women \NC 6199 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR
\NC[nc=8] 1994 \NC\NR
\NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR
\NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR
\NC Women \NC 6199 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR
\NC[nc=8] 1996 \NC\NR
\NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR
\NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR
\NC Women \NC 6199 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR
\NC[nc=8] 1998 \NC\NR
\NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR
\NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR
\NC Women \NC 6009 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR
\NC[nc=8] 1999 \NC\NR
\NC ALL \NC — \NC $ 362,625.2 \NC 1775.50 \NC $ 25,247 \NC $ 10,600,000 \NC 0.269 \NC 3.99 \NC\NR
\NC Men \NC 8034 \NC $ 419,193.3 \NC 2614.59 \NC $ 25,247 \NC $ 10,600,000 \NC 0.249 \NC 3.63 \NC\NR
\NC Women \NC 6101 \NC $ 288,134.4 \NC 1861.66 \NC $ 54,000 \NC $ 1,900,000 \NC 0.249 \NC 3.52 \NC\NR
\stopTABLEbody
\stopTABLEfoot
\NC[nc=8]* $ = New Taiwan Dollars \NC\NR
\stopTABLEfoot
\stopTABLE}
Table~\in[tab:five] on page~\at[tab:five] gives the group in column one, number in sample
in column two, mean in column three, standard deviation in column
four, minimum salary in column five, maximum salary in column six,
Gini coefficient in column seven and the 80/20 ratio in column
eight. The overall mean as well as means for both men and women
rose from 1980 through 1999. The population GINI fell while the
GINI for men dropped between 1980 and 190, then rose from 1990 to
1999. The GINI for women fell continuously. The population 80/20
ration fell across years, while the men’s 80/20 ratio dropped then
rose, and the women’s 80/20 ration fell continuously. However,
these figures do not tell us what has happened within or between
the distributions during this 20 year span.
I used salaried earnings, \formula{SAL}; women’s salary, \formula{Y^f} and men’s
salary, \formula{Y^m}, . I restricted my sample by \formula{AGE} to those of legal
working age. In Taiwan these are individuals greater than 14 years
old but less than 66. I also restrict to non-farm, full-time
salaried employees. The primary reasons for restricting the sample
to fulltime salaries employees is control for unobserved
heterogeneity in the fulltime versus part time, and salaried
versus self-employed decisions of individuals.
\stoptext
</example>
Wolfgang
___________________________________________________________________________________
If your question is of interest to others as well, please add an entry to the Wiki!
maillist : ntg-context@ntg.nl / http://www.ntg.nl/mailman/listinfo/ntg-context
webpage : http://www.pragma-ade.nl / http://tex.aanhet.net
archive : http://foundry.supelec.fr/projects/contextrev/
wiki : http://contextgarden.net
___________________________________________________________________________________
^ permalink raw reply [flat|nested] 3+ messages in thread