In [1] I showed how quantiles in GAMS are difficult, and how they can be calculated better in R. Here is some Python code to do the same:
import pandas as pd
df = pd.read_csv("p.csv")
q=df.groupby(['i','j']).quantile([0,.25,.5,.75,1])
print(q)
q.to_csv("q.csv") |
The q data frame looks like:
Val
i j
i1 j1 0.00 18.002966
0.25 28.242058
0.50 33.222936
0.75 62.736221
1.00 85.770764
j2 0.00 7.644259
0.25 41.375281
0.50 61.313381
0.75 82.127640
1.00 99.813645
j3 0.00 14.017667
0.25 16.559221
0.50 30.775334
0.75 38.482815
1.00 67.223932
i2 j1 0.00 11.938737
0.25 29.259331
0.50 55.029177
0.75 69.633259
1.00 83.258388
j2 0.00 16.857103
0.25 28.783298
0.50 53.358812
0.75 65.534761
1.00 87.373769
j3 0.00 5.608600
0.25 17.433855
0.50 33.311746
0.75 45.566497
1.00 64.926986 |
This is pretty clean. Data frames can easily be read in from CSV files or databases.
References
- http://yetanothermathprogrammingconsultant.blogspot.nl/2017/08/quantiles.html