Within Divisions
Across Divisions
With the regular NFL season wrapping up, are you ready for some SAS ODS Graphics football? A bit oversimplified on the rankings (left as an exercise for you NFL tiebreaking procedures experts!) but here's a SAS ODS Graphics 100% Win-Loss-Tie Bar Chart take on the latest intra and inter-divisional NFL Standings using SGPANEL and SGPLOT.
* Fun With SAS ODS Graphics: A Bar Chart Look at Intra and Inter-Conference NFL Standings
Data source: google.com/search?q=nfl+standings;
* Import data from Excel;
proc import datafile='/home/ted.conway/NFLstandings20241219.xlsx' dbms=xlsx
out=nflstats(rename=(c=TEAM d=W_CHAR e=L_CHAR f=T_CHAR)) replace;
getnames=no;
* Cleanup and eshape data for charting;
data nflstats2chart(keep=TEAM_CONF_DIV CONF_DIV TEAM pct wlt wlt_order games w l t);
set nflstats;
length CONF_DIV $ 25.; retain CONF_DIV; * Get conference/division from column A and retain it;
if a=:'NFC' or a=:'AFC' then CONF_DIV=A;
if a=:'NFC' or a=:'AFC' or team in ('','Team') then delete; * Only output rows with standings;
TEAM_CONF_DIV=catt(TEAM, ' (', CONF_DIV, ')'); * Create composite column for ranking across conferences/divisions;
w=input(w_char,best.); * Convert wins/losses/ties to numeric;
l=input(l_char,best.);
t=input(t_char,best.);
pct=w/(w+l+t); * Calc winning percentage for ranking;
wlt='W'; wlt_order=1; games=W; output; * Create 1 row for each type (wins/losses/ties);
wlt='L'; wlt_order=2; games=L; output;
wlt='T'; wlt_order=3; games=T; output;
%SGANNO; * Create annotation dataset with NFL logo, location using SAS macros;
data nflimg; * Source: en.wikipedia.org/wiki/File:National_Football_League_logo.svg;
%SGIMAGE (image="/home/ted.conway/National_Football_League_logo.svg.png",drawspace="GRAPHPERCENT",x1=94.4,y1=6,height=10,heightunit="PERCENT",anchor="bottomright");
* Rank teams by winning % within divisions;
proc sort data=nflstats2chart; by conf_div descending pct team wlt_order;
* SGPANEL bar chart of standings within conferences;
ods graphics / reset height=7in width=9in noborder imagefmt=svg;
proc sgpanel data=nflstats2chart noautolegend pad=(left=.2in right=.2in) pctlevel=group sganno=nflimg;
styleattrs datacolors=(green red lightgrey); * Colors for wins/losses/ties;
panelby CONF_DIV / headerbackcolor=white columns=1 layout=rowlattice uniscale=column onepanel noheaderborder noborder rowheaderpos=left novarname spacing=3;
hbar team / response=games group=WLT barwidth=1 stat=percent dataskin=crisp grouporder=data fill seglabel seglabelattrs=(color=white weight=bold);
colaxis values=(0 to 1 by .1) valuesformat=percent6. display=(nolabel noline) refticks=(values) offsetmin=.02;
rowaxis discreteorder=data display=(nolabel noticks noline) offsetmin=.15 offsetmax=.15 labelattrs=(weight=bold size=12pt);
rowaxistable games / classorder=data position=left valueattrs=(size=8.5pt) pad=0;
refline (.1 to 1 by .1) / axis=x label="";
%SGANNO; * Create annotation dataset with NFL logo, location using SAS macros;
data nflimg; * Source: en.wikipedia.org/wiki/File:National_Football_League_logo.svg;
%SGIMAGE (image="/home/ted.conway/National_Football_League_logo.svg.png",drawspace="GRAPHPERCENT",x1=94.6,y1=7.6,height=10,heightunit="PERCENT",anchor="bottomright");
* Rank teams by winning % across divisions;
proc sort data=nflstats2chart; by descending pct team wlt_order;
* SGPLOT bar chart of standings across conferences;
proc sgplot data=nflstats2chart(drop=pct) noborder noautolegend pad=(left=.2in right=.2in) pctlevel=group sganno=nflimg;;
styleattrs datacolors=(green red lightgrey); * Colors for wins/losses/ties;
hbar TEAM_CONF_DIV / response=games dataskin=crisp stat=percent group=WLT barwidth=1 grouporder=data seglabel seglabelattrs=(color=white weight=bold);
xaxis values=(0 to 1 by .1) valuesformat=percent6. display=(nolabel noline) refticks=(values) offsetmin=.02;
yaxis discreteorder=data display=(noline noticks nolabel) labelattrs=(weight=bold size=11pt);
refline (.1 to 1 by .1) / axis=x label="";
yaxistable games / classorder=data position=left location=inside valueattrs=(size=8.5pt);
run;
Sample Input Data
Go Bills!
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