Cookbook part 3: Stats with and without out-of-stream variables¶
Overview¶
One of Miller’s strengths is its compact notation: for example, given input of the form
head -n 5 ../data/medium
a=pan,b=pan,i=1,x=0.3467901443380824,y=0.7268028627434533
a=eks,b=pan,i=2,x=0.7586799647899636,y=0.5221511083334797
a=wye,b=wye,i=3,x=0.20460330576630303,y=0.33831852551664776
a=eks,b=wye,i=4,x=0.38139939387114097,y=0.13418874328430463
a=wye,b=pan,i=5,x=0.5732889198020006,y=0.8636244699032729
you can simply do
mlr --oxtab stats1 -a sum -f x ../data/medium
x_sum 4986.019681679581
or
mlr --opprint stats1 -a sum -f x -g b ../data/medium
b x_sum
pan 965.7636699425815
wye 1023.5484702619565
zee 979.7420161495838
eks 1016.7728571314786
hat 1000.192668193983
rather than the more tedious
mlr --oxtab put -q '
@x_sum += $x;
end {
emit @x_sum
}
' data/medium
x_sum 4986.019681679581
or
mlr --opprint put -q '
@x_sum[$b] += $x;
end {
emit @x_sum, "b"
}
' data/medium
b x_sum
pan 965.7636699425815
wye 1023.5484702619565
zee 979.7420161495838
eks 1016.7728571314786
hat 1000.192668193983
The former (mlr stats1 et al.) has the advantages of being easier to type, being less error-prone to type, and running faster.
Nonetheless, out-of-stream variables (which I whimsically call oosvars), begin/end blocks, and emit statements give you the ability to implement logic – if you wish to do so – which isn’t present in other Miller verbs. (If you find yourself often using the same out-of-stream-variable logic over and over, please file a request at https://github.com/johnkerl/miller/issues to get it implemented directly in Go as a Miller verb of its own.)
The following examples compute some things using oosvars which are already computable using Miller verbs, by way of providing food for thought.
Mean without/with oosvars¶
mlr --opprint stats1 -a mean -f x data/medium
x_mean
0.49860196816795804
mlr --opprint put -q '
@x_sum += $x;
@x_count += 1;
end {
@x_mean = @x_sum / @x_count;
emit @x_mean
}
' data/medium
x_mean
0.49860196816795804
Keyed mean without/with oosvars¶
mlr --opprint stats1 -a mean -f x -g a,b data/medium
a b x_mean
pan pan 0.5133141190437597
eks pan 0.48507555383425127
wye wye 0.49150092785839306
eks wye 0.4838950517724162
wye pan 0.4996119901034838
zee pan 0.5198298297816007
eks zee 0.49546320772681596
zee wye 0.5142667998230479
hat wye 0.49381326184632596
pan wye 0.5023618498923658
zee eks 0.4883932942792647
hat zee 0.5099985721987774
hat eks 0.48587864619953547
wye hat 0.4977304763723314
pan eks 0.5036718595143479
eks eks 0.5227992666570941
hat hat 0.47993053101017374
hat pan 0.4643355557376876
zee zee 0.5127559183726382
pan hat 0.492140950155604
pan zee 0.4966041598627583
zee hat 0.46772617655014515
wye zee 0.5059066170573692
eks hat 0.5006790659966355
wye eks 0.5306035254809106
mlr --opprint put -q '
@x_sum[$a][$b] += $x;
@x_count[$a][$b] += 1;
end{
for ((a, b), v in @x_sum) {
@x_mean[a][b] = @x_sum[a][b] / @x_count[a][b];
}
emit @x_mean, "a", "b"
}
' data/medium
a b x_mean
pan pan 0.5133141190437597
pan wye 0.5023618498923658
pan eks 0.5036718595143479
pan hat 0.492140950155604
pan zee 0.4966041598627583
eks pan 0.48507555383425127
eks wye 0.4838950517724162
eks zee 0.49546320772681596
eks eks 0.5227992666570941
eks hat 0.5006790659966355
wye wye 0.49150092785839306
wye pan 0.4996119901034838
wye hat 0.4977304763723314
wye zee 0.5059066170573692
wye eks 0.5306035254809106
zee pan 0.5198298297816007
zee wye 0.5142667998230479
zee eks 0.4883932942792647
zee zee 0.5127559183726382
zee hat 0.46772617655014515
hat wye 0.49381326184632596
hat zee 0.5099985721987774
hat eks 0.48587864619953547
hat hat 0.47993053101017374
hat pan 0.4643355557376876
Variance and standard deviation without/with oosvars¶
mlr --oxtab stats1 -a count,sum,mean,var,stddev -f x data/medium
x_count 10000
x_sum 4986.019681679581
x_mean 0.49860196816795804
x_var 0.08426974433144456
x_stddev 0.2902925151144007
cat variance.mlr
@n += 1;
@sumx += $x;
@sumx2 += $x**2;
end {
@mean = @sumx / @n;
@var = (@sumx2 - @mean * (2 * @sumx - @n * @mean)) / (@n - 1);
@stddev = sqrt(@var);
emitf @n, @sumx, @sumx2, @mean, @var, @stddev
}
mlr --oxtab put -q -f variance.mlr data/medium
n 10000
sumx 4986.019681679581
sumx2 3328.652400179729
mean 0.49860196816795804
var 0.08426974433144456
stddev 0.2902925151144007
You can also do this keyed, of course, imitating the keyed-mean example above.
Min/max without/with oosvars¶
mlr --oxtab stats1 -a min,max -f x data/medium
x_min 4.509679127584487e-05
x_max 0.999952670371898
mlr --oxtab put -q '
@x_min = min(@x_min, $x);
@x_max = max(@x_max, $x);
end{emitf @x_min, @x_max}
' data/medium
x_min 4.509679127584487e-05
x_max 0.999952670371898
Keyed min/max without/with oosvars¶
mlr --opprint stats1 -a min,max -f x -g a data/medium
a x_min x_max
pan 0.00020390740306253097 0.9994029107062516
eks 0.0006917972627396018 0.9988110946859143
wye 0.0001874794831505655 0.9998228522652893
zee 0.0005486114815762555 0.9994904324789629
hat 4.509679127584487e-05 0.999952670371898
mlr --opprint --from data/medium put -q '
@min[$a] = min(@min[$a], $x);
@max[$a] = max(@max[$a], $x);
end{
emit (@min, @max), "a";
}
'
a min max
pan 0.00020390740306253097 0.9994029107062516
eks 0.0006917972627396018 0.9988110946859143
wye 0.0001874794831505655 0.9998228522652893
zee 0.0005486114815762555 0.9994904324789629
hat 4.509679127584487e-05 0.999952670371898
Delta without/with oosvars¶
mlr --opprint step -a delta -f x data/small
a b i x y x_delta
pan pan 1 0.3467901443380824 0.7268028627434533 0
eks pan 2 0.7586799647899636 0.5221511083334797 0.41188982045188116
wye wye 3 0.20460330576630303 0.33831852551664776 -0.5540766590236605
eks wye 4 0.38139939387114097 0.13418874328430463 0.17679608810483793
wye pan 5 0.5732889198020006 0.8636244699032729 0.19188952593085962
mlr --opprint put '
$x_delta = is_present(@last) ? $x - @last : 0;
@last = $x
' data/small
a b i x y x_delta
pan pan 1 0.3467901443380824 0.7268028627434533 0
eks pan 2 0.7586799647899636 0.5221511083334797 0.41188982045188116
wye wye 3 0.20460330576630303 0.33831852551664776 -0.5540766590236605
eks wye 4 0.38139939387114097 0.13418874328430463 0.17679608810483793
wye pan 5 0.5732889198020006 0.8636244699032729 0.19188952593085962
Keyed delta without/with oosvars¶
mlr --opprint step -a delta -f x -g a data/small
a b i x y x_delta
pan pan 1 0.3467901443380824 0.7268028627434533 0
eks pan 2 0.7586799647899636 0.5221511083334797 0
wye wye 3 0.20460330576630303 0.33831852551664776 0
eks wye 4 0.38139939387114097 0.13418874328430463 -0.3772805709188226
wye pan 5 0.5732889198020006 0.8636244699032729 0.36868561403569755
mlr --opprint put '
$x_delta = is_present(@last[$a]) ? $x - @last[$a] : 0;
@last[$a]=$x
' data/small
a b i x y x_delta
pan pan 1 0.3467901443380824 0.7268028627434533 0
eks pan 2 0.7586799647899636 0.5221511083334797 0
wye wye 3 0.20460330576630303 0.33831852551664776 0
eks wye 4 0.38139939387114097 0.13418874328430463 -0.3772805709188226
wye pan 5 0.5732889198020006 0.8636244699032729 0.36868561403569755
Exponentially weighted moving averages without/with oosvars¶
mlr --opprint step -a ewma -d 0.1 -f x data/small
a b i x y x_ewma_0.1
pan pan 1 0.3467901443380824 0.7268028627434533 0.3467901443380824
eks pan 2 0.7586799647899636 0.5221511083334797 0.3879791263832706
wye wye 3 0.20460330576630303 0.33831852551664776 0.36964154432157387
eks wye 4 0.38139939387114097 0.13418874328430463 0.37081732927653055
wye pan 5 0.5732889198020006 0.8636244699032729 0.3910644883290776
mlr --opprint put '
begin{ @a=0.1 };
$e = NR==1 ? $x : @a * $x + (1 - @a) * @e;
@e=$e
' data/small
a b i x y e
pan pan 1 0.3467901443380824 0.7268028627434533 0.3467901443380824
eks pan 2 0.7586799647899636 0.5221511083334797 0.3879791263832706
wye wye 3 0.20460330576630303 0.33831852551664776 0.36964154432157387
eks wye 4 0.38139939387114097 0.13418874328430463 0.37081732927653055
wye pan 5 0.5732889198020006 0.8636244699032729 0.3910644883290776