Line graph

[Thomas Lemma]

Hi Stata users,

I have 4 time periods ( round 1, round 2, round 3, and round 4) and a food insecurity score (Yes or No). I wanted to make a line graph for the food insecurity score using

graph twoway line Food_secure Chronic_food_insecruity round

But it does not give the proper line graph with time on the x-axis and food insecurity scores on the Y-axis. What could be my mistake?

[Nick Cox]

That command means that you are plotting two variables against round. That is not what you describe otherwise. What's wrong with the graph?

[Thomas Lemma]

Thank you, Nick. The command can of course be edited as

graph twoway line Food_secure round.

However, even with this command, the graph is messed up with no pattern.

[Nick Cox]

Either you need a sort option or you have panel or longitudinal data and need something different. Without a graph or data example we’re guessing here.

[Thomas Lemma]

Yes, Nick, I do have panel data of 3 rounds and 4 countries. Below is an example bar graph I produced. I either want to replace it with a line graph or put a trend line on the bar graphs.

[Maarten Buis]

You are not giving us an example of your dataset. That makes it much harder for us to help you. I will assume that your data looks something like the example below. If that is not the case then you and I wasted a lot of time unnecessarily. Even if I guessed right, I still had to unnecessarily spent time to create that example data. So in future use dataex to give us an example for us to work with. How to do that is described in the statalist FAQ (black bar near the top of this page).

// create example data
clear
input byte(country round pid secure mod mild chron)
1 3  1 1 0 0 0
1 3  2 0 0 1 0
1 3  3 0 0 1 0
1 3  4 0 1 0 0
1 3  5 0 0 1 0
1 3  6 0 0 1 0
1 3  7 0 0 1 0
1 3  8 0 1 0 0
1 3  9 1 0 0 0
1 3 10 0 1 0 0
1 3 11 1 0 0 0
1 3 12 0 0 1 0
1 3 13 0 0 1 0
1 3 14 1 0 0 0
1 3 15 0 0 1 0
1 3 16 0 0 1 0
1 3 17 0 1 0 0
1 3 18 0 0 1 0
1 3 19 0 0 1 0
1 3 20 1 0 0 0
1 4  1 0 0 1 0
1 4  2 0 0 1 0
1 4  3 0 0 1 0
1 4  4 0 0 1 0
1 4  5 0 0 1 0
1 4  6 0 0 1 0
1 4  7 0 0 0 1
1 4  8 1 0 0 0
1 4  9 0 0 1 0
1 4 10 0 1 0 0
1 4 11 0 0 1 0
1 4 12 1 0 0 0
1 4 13 0 0 1 0
1 4 14 1 0 0 0
1 4 15 0 0 1 0
1 4 16 0 1 0 0
1 4 17 1 0 0 0
1 4 18 0 1 0 0
1 4 19 0 0 0 1
1 4 20 0 1 0 0
1 5  1 0 1 0 0
1 5  2 0 0 1 0
1 5  3 0 0 1 0
1 5  4 0 1 0 0
1 5  5 0 0 1 0
1 5  6 0 0 0 1
1 5  7 0 0 1 0
1 5  8 0 0 1 0
1 5  9 1 0 0 0
1 5 10 0 0 1 0
1 5 11 0 0 1 0
1 5 12 0 0 1 0
1 5 13 0 0 1 0
1 5 14 0 0 1 0
1 5 15 0 0 1 0
1 5 16 0 1 0 0
1 5 17 0 0 1 0
1 5 18 0 1 0 0
1 5 19 0 0 1 0
1 5 20 0 0 0 1
2 3  1 0 0 1 0
2 3  2 0 0 1 0
2 3  3 0 0 0 1
2 3  4 0 1 0 0
2 3  5 0 1 0 0
2 3  6 1 0 0 0
2 3  7 0 0 1 0
2 3  8 1 0 0 0
2 3  9 0 1 0 0
2 3 10 0 0 1 0
2 3 11 0 0 1 0
2 3 12 0 1 0 0
2 3 13 1 0 0 0
2 3 14 0 1 0 0
2 3 15 0 1 0 0
2 3 16 0 0 0 1
2 3 17 0 0 1 0
2 3 18 0 0 1 0
2 3 19 0 1 0 0
2 3 20 0 1 0 0
2 4  1 0 1 0 0
2 4  2 0 1 0 0
2 4  3 0 1 0 0
2 4  4 0 0 1 0
2 4  5 0 1 0 0
2 4  6 0 1 0 0
2 4  7 0 0 1 0
2 4  8 0 0 1 0
2 4  9 0 0 1 0
2 4 10 0 0 1 0
2 4 11 0 0 1 0
2 4 12 0 0 0 1
2 4 13 0 0 1 0
2 4 14 1 0 0 0
2 4 15 0 0 1 0
2 4 16 0 0 0 1
2 4 17 0 0 1 0
2 4 18 0 0 0 1
2 4 19 0 0 0 1
2 4 20 0 1 0 0
2 5  1 1 0 0 0
2 5  2 0 0 1 0
2 5  3 1 0 0 0
2 5  4 0 0 1 0
2 5  5 1 0 0 0
2 5  6 0 1 0 0
2 5  7 0 0 1 0
2 5  8 1 0 0 0
2 5  9 0 1 0 0
2 5 10 1 0 0 0
2 5 11 1 0 0 0
2 5 12 1 0 0 0
2 5 13 1 0 0 0
2 5 14 1 0 0 0
2 5 15 1 0 0 0
2 5 16 1 0 0 0
2 5 17 1 0 0 0
2 5 18 1 0 0 0
2 5 19 0 1 0 0
2 5 20 1 0 0 0
3 3  1 1 0 0 0
3 3  2 1 0 0 0
3 3  3 0 0 1 0
3 3  4 0 1 0 0
3 3  5 0 0 1 0
3 3  6 1 0 0 0
3 3  7 0 1 0 0
3 3  8 1 0 0 0
3 3  9 1 0 0 0
3 3 10 0 0 1 0
3 3 11 1 0 0 0
3 3 12 1 0 0 0
3 3 13 0 1 0 0
3 3 14 0 0 1 0
3 3 15 0 1 0 0
3 3 16 0 1 0 0
3 3 17 0 0 1 0
3 3 18 1 0 0 0
3 3 19 1 0 0 0
3 3 20 0 0 1 0
3 4  1 1 0 0 0
3 4  2 0 1 0 0
3 4  3 0 0 1 0
3 4  4 0 0 1 0
3 4  5 1 0 0 0
3 4  6 1 0 0 0
3 4  7 1 0 0 0
3 4  8 1 0 0 0
3 4  9 0 0 1 0
3 4 10 1 0 0 0
3 4 11 1 0 0 0
3 4 12 0 0 1 0
3 4 13 1 0 0 0
3 4 14 1 0 0 0
3 4 15 0 0 1 0
3 4 16 1 0 0 0
3 4 17 1 0 0 0
3 4 18 0 1 0 0
3 4 19 0 0 0 1
3 4 20 0 1 0 0
3 5  1 0 1 0 0
3 5  2 1 0 0 0
3 5  3 0 0 0 1
3 5  4 0 0 1 0
3 5  5 0 1 0 0
3 5  6 0 0 1 0
3 5  7 0 0 1 0
3 5  8 0 1 0 0
3 5  9 0 1 0 0
3 5 10 0 0 0 1
3 5 11 1 0 0 0
3 5 12 0 1 0 0
3 5 13 0 1 0 0
3 5 14 0 0 0 1
3 5 15 1 0 0 0
3 5 16 1 0 0 0
3 5 17 1 0 0 0
3 5 18 0 0 0 1
3 5 19 1 0 0 0
3 5 20 0 0 0 1
4 3  1 0 0 1 0
4 3  2 0 0 1 0
4 3  3 0 1 0 0
4 3  4 0 0 1 0
4 3  5 0 1 0 0
4 3  6 1 0 0 0
4 3  7 0 0 1 0
4 3  8 1 0 0 0
4 3  9 0 1 0 0
4 3 10 1 0 0 0
4 3 11 1 0 0 0
4 3 12 1 0 0 0
4 3 13 1 0 0 0
4 3 14 1 0 0 0
4 3 15 1 0 0 0
4 3 16 0 0 1 0
4 3 17 0 0 1 0
4 3 18 0 1 0 0
4 3 19 0 1 0 0
4 3 20 1 0 0 0
4 4  1 0 0 1 0
4 4  2 0 1 0 0
4 4  3 1 0 0 0
4 4  4 1 0 0 0
4 4  5 1 0 0 0
4 4  6 0 0 1 0
4 4  7 1 0 0 0
4 4  8 0 1 0 0
4 4  9 0 0 1 0
4 4 10 1 0 0 0
4 4 11 0 1 0 0
4 4 12 1 0 0 0
4 4 13 0 1 0 0
4 4 14 0 1 0 0
4 4 15 0 0 1 0
4 4 16 0 1 0 0
4 4 17 0 0 1 0
4 4 18 1 0 0 0
4 4 19 1 0 0 0
4 4 20 0 1 0 0
4 5  1 1 0 0 0
4 5  2 0 1 0 0
4 5  3 0 0 1 0
4 5  4 0 0 1 0
4 5  5 1 0 0 0
4 5  6 1 0 0 0
4 5  7 0 1 0 0
4 5  8 1 0 0 0
4 5  9 1 0 0 0
4 5 10 1 0 0 0
4 5 11 0 0 1 0
4 5 12 1 0 0 0
4 5 13 0 1 0 0
4 5 14 0 1 0 0
4 5 15 0 1 0 0
4 5 16 0 0 1 0
4 5 17 1 0 0 0
4 5 18 0 1 0 0
4 5 19 1 0 0 0
4 5 20 1 0 0 0
end
label values country country
label def country 1 "Ethopia", modify
label def country 2 "Vietnam", modify
label def country 3 "Peru", modify
label def country 4 "India", modify

label var secure "food secure"
label var mod "moderate food insecure"
label var mild "mild food insecure"
label var chron "chronic food insecure"
// finish creating example dataset

// turn the data in a dataset of proportions
collapse (mean) secure mod mild chron, by(country round)
// optionally look at the result
list , sepby(country)

// turn proportions into percentages
replace secure = secure * 100
replace mod = mod * 100
replace mild = mild * 100
replace chron = chron * 100

// fix variable labels
label var secure "food secure"
label var mod "moderate food insecure"
label var mild "mild food insecure"
label var chron "chronic food insecure"

// create graph
twoway connected secure mod mild chron round, ///
   by(country, note("") compact) xlab(3/5) ytitle("percent") ///
   xscale(range(2.9 5.1))

[Nick Cox]

I riffed on @Maarten Buis's helpful fake data example using floatplot (SSC, intended but not submitted at the time of writing). Here's the kit and caboodle, apart from the code for floatplot.

 // create example data
clear
input byte(country round pid secure mod mild chron)
1 3  1 1 0 0 0
1 3  2 0 0 1 0
1 3  3 0 0 1 0
1 3  4 0 1 0 0
1 3  5 0 0 1 0
1 3  6 0 0 1 0
1 3  7 0 0 1 0
1 3  8 0 1 0 0
1 3  9 1 0 0 0
1 3 10 0 1 0 0
1 3 11 1 0 0 0
1 3 12 0 0 1 0
1 3 13 0 0 1 0
1 3 14 1 0 0 0
1 3 15 0 0 1 0
1 3 16 0 0 1 0
1 3 17 0 1 0 0
1 3 18 0 0 1 0
1 3 19 0 0 1 0
1 3 20 1 0 0 0
1 4  1 0 0 1 0
1 4  2 0 0 1 0
1 4  3 0 0 1 0
1 4  4 0 0 1 0
1 4  5 0 0 1 0
1 4  6 0 0 1 0
1 4  7 0 0 0 1
1 4  8 1 0 0 0
1 4  9 0 0 1 0
1 4 10 0 1 0 0
1 4 11 0 0 1 0
1 4 12 1 0 0 0
1 4 13 0 0 1 0
1 4 14 1 0 0 0
1 4 15 0 0 1 0
1 4 16 0 1 0 0
1 4 17 1 0 0 0
1 4 18 0 1 0 0
1 4 19 0 0 0 1
1 4 20 0 1 0 0
1 5  1 0 1 0 0
1 5  2 0 0 1 0
1 5  3 0 0 1 0
1 5  4 0 1 0 0
1 5  5 0 0 1 0
1 5  6 0 0 0 1
1 5  7 0 0 1 0
1 5  8 0 0 1 0
1 5  9 1 0 0 0
1 5 10 0 0 1 0
1 5 11 0 0 1 0
1 5 12 0 0 1 0
1 5 13 0 0 1 0
1 5 14 0 0 1 0
1 5 15 0 0 1 0
1 5 16 0 1 0 0
1 5 17 0 0 1 0
1 5 18 0 1 0 0
1 5 19 0 0 1 0
1 5 20 0 0 0 1
2 3  1 0 0 1 0
2 3  2 0 0 1 0
2 3  3 0 0 0 1
2 3  4 0 1 0 0
2 3  5 0 1 0 0
2 3  6 1 0 0 0
2 3  7 0 0 1 0
2 3  8 1 0 0 0
2 3  9 0 1 0 0
2 3 10 0 0 1 0
2 3 11 0 0 1 0
2 3 12 0 1 0 0
2 3 13 1 0 0 0
2 3 14 0 1 0 0
2 3 15 0 1 0 0
2 3 16 0 0 0 1
2 3 17 0 0 1 0
2 3 18 0 0 1 0
2 3 19 0 1 0 0
2 3 20 0 1 0 0
2 4  1 0 1 0 0
2 4  2 0 1 0 0
2 4  3 0 1 0 0
2 4  4 0 0 1 0
2 4  5 0 1 0 0
2 4  6 0 1 0 0
2 4  7 0 0 1 0
2 4  8 0 0 1 0
2 4  9 0 0 1 0
2 4 10 0 0 1 0
2 4 11 0 0 1 0
2 4 12 0 0 0 1
2 4 13 0 0 1 0
2 4 14 1 0 0 0
2 4 15 0 0 1 0
2 4 16 0 0 0 1
2 4 17 0 0 1 0
2 4 18 0 0 0 1
2 4 19 0 0 0 1
2 4 20 0 1 0 0
2 5  1 1 0 0 0
2 5  2 0 0 1 0
2 5  3 1 0 0 0
2 5  4 0 0 1 0
2 5  5 1 0 0 0
2 5  6 0 1 0 0
2 5  7 0 0 1 0
2 5  8 1 0 0 0
2 5  9 0 1 0 0
2 5 10 1 0 0 0
2 5 11 1 0 0 0
2 5 12 1 0 0 0
2 5 13 1 0 0 0
2 5 14 1 0 0 0
2 5 15 1 0 0 0
2 5 16 1 0 0 0
2 5 17 1 0 0 0
2 5 18 1 0 0 0
2 5 19 0 1 0 0
2 5 20 1 0 0 0
3 3  1 1 0 0 0
3 3  2 1 0 0 0
3 3  3 0 0 1 0
3 3  4 0 1 0 0
3 3  5 0 0 1 0
3 3  6 1 0 0 0
3 3  7 0 1 0 0
3 3  8 1 0 0 0
3 3  9 1 0 0 0
3 3 10 0 0 1 0
3 3 11 1 0 0 0
3 3 12 1 0 0 0
3 3 13 0 1 0 0
3 3 14 0 0 1 0
3 3 15 0 1 0 0
3 3 16 0 1 0 0
3 3 17 0 0 1 0
3 3 18 1 0 0 0
3 3 19 1 0 0 0
3 3 20 0 0 1 0
3 4  1 1 0 0 0
3 4  2 0 1 0 0
3 4  3 0 0 1 0
3 4  4 0 0 1 0
3 4  5 1 0 0 0
3 4  6 1 0 0 0
3 4  7 1 0 0 0
3 4  8 1 0 0 0
3 4  9 0 0 1 0
3 4 10 1 0 0 0
3 4 11 1 0 0 0
3 4 12 0 0 1 0
3 4 13 1 0 0 0
3 4 14 1 0 0 0
3 4 15 0 0 1 0
3 4 16 1 0 0 0
3 4 17 1 0 0 0
3 4 18 0 1 0 0
3 4 19 0 0 0 1
3 4 20 0 1 0 0
3 5  1 0 1 0 0
3 5  2 1 0 0 0
3 5  3 0 0 0 1
3 5  4 0 0 1 0
3 5  5 0 1 0 0
3 5  6 0 0 1 0
3 5  7 0 0 1 0
3 5  8 0 1 0 0
3 5  9 0 1 0 0
3 5 10 0 0 0 1
3 5 11 1 0 0 0
3 5 12 0 1 0 0
3 5 13 0 1 0 0
3 5 14 0 0 0 1
3 5 15 1 0 0 0
3 5 16 1 0 0 0
3 5 17 1 0 0 0
3 5 18 0 0 0 1
3 5 19 1 0 0 0
3 5 20 0 0 0 1
4 3  1 0 0 1 0
4 3  2 0 0 1 0
4 3  3 0 1 0 0
4 3  4 0 0 1 0
4 3  5 0 1 0 0
4 3  6 1 0 0 0
4 3  7 0 0 1 0
4 3  8 1 0 0 0
4 3  9 0 1 0 0
4 3 10 1 0 0 0
4 3 11 1 0 0 0
4 3 12 1 0 0 0
4 3 13 1 0 0 0
4 3 14 1 0 0 0
4 3 15 1 0 0 0
4 3 16 0 0 1 0
4 3 17 0 0 1 0
4 3 18 0 1 0 0
4 3 19 0 1 0 0
4 3 20 1 0 0 0
4 4  1 0 0 1 0
4 4  2 0 1 0 0
4 4  3 1 0 0 0
4 4  4 1 0 0 0
4 4  5 1 0 0 0
4 4  6 0 0 1 0
4 4  7 1 0 0 0
4 4  8 0 1 0 0
4 4  9 0 0 1 0
4 4 10 1 0 0 0
4 4 11 0 1 0 0
4 4 12 1 0 0 0
4 4 13 0 1 0 0
4 4 14 0 1 0 0
4 4 15 0 0 1 0
4 4 16 0 1 0 0
4 4 17 0 0 1 0
4 4 18 1 0 0 0
4 4 19 1 0 0 0
4 4 20 0 1 0 0
4 5  1 1 0 0 0
4 5  2 0 1 0 0
4 5  3 0 0 1 0
4 5  4 0 0 1 0
4 5  5 1 0 0 0
4 5  6 1 0 0 0
4 5  7 0 1 0 0
4 5  8 1 0 0 0
4 5  9 1 0 0 0
4 5 10 1 0 0 0
4 5 11 0 0 1 0
4 5 12 1 0 0 0
4 5 13 0 1 0 0
4 5 14 0 1 0 0
4 5 15 0 1 0 0
4 5 16 0 0 1 0
4 5 17 1 0 0 0
4 5 18 0 1 0 0
4 5 19 1 0 0 0
4 5 20 1 0 0 0
end
label values country country
label def country 1 "Ethopia", modify
label def country 2 "Vietnam", modify
label def country 3 "Peru", modify
label def country 4 "India", modify

gen score = secure + 2 * mild + 3 * mod + 4 * chron 
label def score 1 none 2 mild 3 moderate 4 chronic 
label val score score  
label var score "food insecurity"

set scheme s1color 
floatplot score, over(round) by(country, note("percents")) fcolors(blue*0.4 red*0.2 red*0.6 red) lcolors(blue red red red) highnegative(2) name(secure1, replace)

floatplot score, over(round) by(country, compact row(1) note("percents", pos(11)) legend(pos(3) col(1))) fcolors(blue*0.4 red*0.2 red*0.6 red) lcolors(blue red red red) highnegative(2) vertical  legend(symxsize(*.2) size(small)) offset(0.4) name(secure2, replace)

[Andrew Musau]

This design will make stacked bar charts very popular. Nick Cox, I would create a new thread once it is available from SSC so that it is easier to find and reference.

[Nick Cox]

Andrew Musau Indeed, I intend to announce the command in due course in a devoted thread.

[Thomas Lemma]

Have been disconnected last week. Thank you very much, Nick, Andrew and Maarteen. I learnt a lot from this tread.