Get pheno info

pheno_info.py

@@ -0,0 +1,45 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+"""
+
+Describe phenotypical info
+
+Usage:
+  pheno_info.py
+  pheno_info.py (-h | --help)
+
+Options:
+  -h --help           Show this screen
+
+"""
+
+from docopt import docopt
+from utils import (load_phenotypes)
+
+
+if __name__ == "__main__":
+
+    arguments = docopt(__doc__)
+
+    pheno_path = "./data/phenotypes/Phenotypic_V1_0b_preprocessed1.csv"
+    pheno = load_phenotypes(pheno_path)
+
+    for site, df_site in pheno.groupby("SITE_ID"):
+        asd = df_site[df_site["DX_GROUP"] == 0]
+        tc = df_site[df_site["DX_GROUP"] == 1]
+        fmt = "% 8s &    % 8.1f (% 8.1f) & % 8.1f (% 8.1f)    &  M % 3d, F % 3d &    % 8.1f (% 8.1f) &  M % 3d, F % 3d \\\\"
+
+        print (fmt % (
+            site,
+            asd["AGE"].mean(),
+            asd["AGE"].std(),
+            asd["ADOS"].mean(),
+            asd["ADOS"].std(),
+            int(asd[asd["SEX"] == "M"].shape[0]),
+            int(asd[asd["SEX"] == "F"].shape[0]),
+            tc["AGE"].mean(),
+            tc["AGE"].std(),
+            int(tc[tc["SEX"] == "M"].shape[0]),
+            int(tc[tc["SEX"] == "F"].shape[0]),
+        )).replace("   nan", "$\dag$").replace("_", " ")