The default font size of the likert plot of the HH package is small and I want to increase its size for reading. I also want to control the order of the labeling value of the legend.
To get my value labels to be ordered correctly I have had to recode my data as "1 Not Valuable", "2 Neutral", and "3 Valuable". I do not want to have the "1", "2", and "3" listed, and simply want it listed as "Not Valuable", "Neutral", and "Valuable", however, when I try and list the values as categorical variables, the value defaults to alphabetical order (e.g., "Neutral", "Not Valuable", "Valuable"). I want the values to be in the order "Not Valuable", "Neutral", "Valuable".
Here is my current code and data (a)
Value
Age 1 Not Valuable 2 Neutral 3 Valuable
18-25 8 4 8
25.01-35 17 12 22
35.01-45 10 19 18
45.01-55 11 15 22
55.01-65 27 25 34
65.01-93 37 40 30
age=likert(a, ylab='Age Category', main='AGE DISTRIBUTION',
as.percent=TRUE, col=c('gray70', 'gray48', 'black'))
I have also tried using the "theme" function to control text size with the code:
+theme(legend.text=element_text(size=12))
However, I get the R error that states
could not find function theme
I have not found any information on controlling the order of value scale in the legend.
check ?likert.plot :
you can then use
plot (age, legend.position="right", group.order = a$Age)
I had the same issue and had to use a command from the lattice package. Add this to your code:
auto.key.in = list(cex = 1.2)
adjusting the number to the font size you desire.
Related
If i enter 17.0for a data value, the datalabels displays only 17 (the ".0" is missing)
How to fix that?
Example:
Input: 17.1 -> ok, data.y = 17.1, dataLabel = 17.1
Input: 17.0 -> nok: data.y = 17, dataLabel = 17
(BTW: i do not mean do display always one number after dot, i need to have the exact value that i got, so it may also be 17.00 or 17.000, depending on the source)
In this example, in the tooltip of May, Serie 1, i need 144.0 displayed and in October, Series 2 in need 176.0, i mean the same "value" i see in the data-Array: http://jsfiddle.net/gh/get/library/pure/highcharts/highcharts/tree/master/samples/highcharts/tooltip/formatter-shared/ (this is the second example linked here: http://api.highcharts.com/highcharts/tooltip.formatter )
You can create a simple condition inside tooltip's formatter, which will check if number have decimals. If not (e.g. 144), it will add one additional digit (0) as a decimal.
if (value.toString().indexOf('.') === -1) {
value = value.toFixed(1);
}
API Reference:
http://api.highcharts.com/highcharts/tooltip.formatter
https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Number/toFixed
Example:
http://jsfiddle.net/k4nvjm29/
I have a "raw" data set that I´m trying to clean. The data set consists of individuals with the variable age between year 2000 and 2010. There are around 20000 individuals in the data set with the same problem.
The variable age is not increasing in the years 2004-2006. For example, for one individual it looks like this:
2000: 16,
2001: 17,
2002: 18,
2003: 19,
2004: 19,
2005: 19,
2006: 19,
2007: 23,
2008: 24,
2009: 25,
2010: 26,
So far I have tried to generate variables for the max age and max year:
bysort id: egen last_year=max(year)
bysort id: egen last_age=max(age)
and then use foreach combined with lags to try to replace age variable in decreasing order so that when the new variable last_age (that now are 26 in all years) rather looks like this:
2010: 26
2009: 25 (26-1)
2008: 24 (26-2) , and so on.
However, I have some problem with finding the correct code for this problem.
Assuming that for each individual the first value of age is not missing and is correct, something like this might work
bysort id (year): replace age = age[1]+(year-year[1])
Alternatively, if the last value of age is assumed to always be accurate,
bysort id (year): replace age = age[_N]-(year[_N]-year)
Or, just fix the ages where there is no observation-to-observation change in age
bysort id (year): replace age = age[_n-1]+(year-year[_n-1]) if _n>1 & age==age[_n-1]
In the absence of sample data none of these have been tested.
William's code is very much to the point, but a few extra remarks won't fit easily into a comment.
Suppose we have age already and generate two other estimates going forward and backward as he suggests:
bysort id (year): gen age2 = age[1] + (year - year[1])
bysort id (year): gen age3 = age[_N] - (year[_N] - year)
Now if all three agree, we are good, and if two out of three agree, we will probably use the majority vote. Either way, that is the median; the median will be, for 3 values, the sum MINUS the minimum MINUS the maximum.
gen median = (age + age2 + age3) - max(age, age2, age3) - min(age, age2, age3)
If we get three different estimates, we should look more carefully.
edit age* if max(age, age2, age3) > median & median > min(age, age2, age3)
A final test is whether medians increase in the same way as years:
bysort id (year) : assert (median - median[_n-1]) == (year - year[_n-1]) if _n > 1
How i can use my refined number as shown below :
1> game:num().
provide a number between 1 and 100 : 10.
10 is not my number. It is greater than 10.
provide a number between 11 and 100 : 44.
44 is not my number. It is lesser than 44.
provide a number between 1 and 43 :
Once you've refined the lower/upper bound, you have to use that. So the last message should be:
"provide a number between 11 and 43".
You just need to keep track of two bounds (upper and lower) to achieve what you want. I'm not providing code, though.
I have a variable named A in SPSS database.
A
--
102102
23453212
142378
2367890654
2345
45
I want to split this variable by 2 lengths and create multiple variables as follows.
A_1 A_2 A_3 A_4 A_5
--- --- --- --- ---
10 21 02
23 45 32 12
14 23 78
23 67 89 06 54
23 45
45
Can anyone write SPSS macro to compute this operation?
Using STRING manipulations (after converting the NUMERIC field to STRING, if necessary), specifically SUBSTR you can extract out pairs of digits as you wish.
/* Simulate data */.
data list list / x (f8.0).
begin data.
102102
23453212
142378
2367890654
2345
45
end data.
dataset name dsSim.
If you have a known maximum value, in your example a value of 10 digits long then you'll need 5 variables to store the pairs of digits, which the follow does:
preserve.
set mxwarns 0 /* temporarily supress warning messages */ .
string #xstr (a10).
compute #xstr=ltrim(string(x,f18.0)).
compute A_1=number(substr(#xstr,1,2), f8.0).
compute A_2=number(substr(#xstr,3,2), f8.0).
compute A_3=number(substr(#xstr,5,2), f8.0).
compute A_4=number(substr(#xstr,7,2), f8.0).
compute A_5=number(substr(#xstr,9,2), f8.0).
exe.
restore.
However, you may prefer to code something like this more dynamically (using python) where the code itself would read the maximum value in the data and create as many variables as needed.
begin program.
import spssdata, math
spss.Submit("set mprint on.")
# get maximum value
spss.Submit("""
dataset declare dsAgg.
aggregate outfile=dsAgg /MaxX=max(x).
dataset activate dsAgg.
""")
maxvalue = spssdata.Spssdata().fetchone()[0]
ndigits=math.floor(math.log(maxvalue,10))+1
cmd="""
dataset close dsAgg.
dataset activate dsSim.
preserve.
set mxwarns 0.
string #xstr (a10).
compute #xstr=ltrim(string(x,f18.0)).
"""
for i in range(1,int(math.ceil(ndigits/2))+1):
j=(i-1)*2+1
cmd+="\ncompute B_%(i)s=number(substr(#xstr,%(j)s,2), f8.0)." % locals()
cmd+="\nexe.\nrestore."
spss.Submit(cmd)
spss.Submit("set mprint off.")
end program.
You would need to weigh up the pros on cons of each method to asses which suits you best, for how you anticipate your data to arrive and how you then go onto work with in later. I haven't attempted to wrap either of these up in a macro but that could just as easily be done.
My dataset includes TWO main variables X and Y.
Variable X represents distinct codes (e.g. 001X01, 001X02, etc) for multiple computer items with different brands.
Variable Y represents the tax charged for each code of variable X (e.g. 15 = 15% for 001X01) at a store.
I've created categories for these computer items using dummy variables (e.g. HD dummy variable for Hard-Drives, takes value of 1 when variable X represents a HD, etc). I have a list of over 40 variables (two of them representing X and Y, and the rest is a bunch of dummy variables for the different categories I've created for computer items).
I would like to display the averages of all these categories using a loop in Stata, but I'm not sure how to do this.
For example the code:
mean Y if HD == 1
Mean estimation Number of obs = 5
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
Tax | 7.1 2.537716 1.154172 15.24583
gives me the mean Tax for the category representing Hard Drives. How can I use a loop in Stata to automatically display all the mean Taxes charged for each category? I would do it by hand without a problem, but I want to repeat this process for multiple years, so I would like to use a loop for each year in order to come up with this output.
My goal is to create a separate Excel file with each of the computer categories I've created (38 total) and the average tax for each category by year.
Why bother with the loop and creating the indicator variables? If I understand correctly, your initial dataset allows the use of a simple collapse:
clear all
set more off
input ///
code tax str10 categ
1 0.15 "hd"
2 0.25 "pend"
3 0.23 "mouse"
4 0.29 "pend"
5 0.16 "pend"
6 0.50 "hd"
7 0.54 "monitor"
8 0.22 "monitor"
9 0.21 "mouse"
10 0.76 "mouse"
end
list
collapse (mean) tax, by(categ)
list
To take to Excel you can try export excel or put excel.
Run help collapse and help export for details.
Edit
Because you insist, below is an example that gives the same result using loops.
I assume the same data input as before. Some testing using this example database
with expand 1000000, shows that speed is virtually the same. But almost surely,
you (including your future you) and your readers will prefer collapse.
It is much clearer, cleaner and concise. It is even prettier.
levelsof categ, local(parts)
gen mtax = .
quietly {
foreach part of local parts {
summarize tax if categ == "`part'", meanonly
replace mtax = r(mean) if categ == "`part'"
}
}
bysort categ: keep if _n == 1
keep categ mtax
Stata has features that make it quite different from other languages. Once you
start getting a hold of it, you will find that many things done with loops elsewhere,
can be made loop-less in Stata. In many cases, the latter style will be preferred.
See corresponding help files using help <command> and if you are not familiarized with saved results (e.g. r(mean)), type help return.
A supplement to Roberto's excellent answer: After collapse, you will need a loop to export the results to excel.
levelsof categ, local(levels)
foreach x of local levels {
export excel `x', replace
}
I prefer to use numerical codes for variables such as your category variable. I then assign them value labels. Here's a version of Roberto's code which does this and which, for closer correspondence to your problem, adds a "year" variable
input code tax categ year
1 0.15 1 1999
2 0.25 2 2000
3 0.23 3 2013
4 0.29 1 2010
5 0.16 2 2000
6 0.50 1 2011
7 0.54 4 2000
8 0.22 4 2003
9 0.21 3 2004
10 0.76 3 2005
end
#delim ;
label define catl
1 hd
2 pend
3 mouse
4 monitor
;
#delim cr
label values categ catl
collapse (mean) tax, by(categ year)
levelsof categ, local(levels)
foreach x of local levels {
export excel `:label (categ) `x'', replace
}
The #delim ; command makes it possible to easily list each code on a separate line. The"label" function in the export statement is an extended macro function to insert a value label into the file name.