diff --git a/py/20190116_tidy_efo.py b/py/20190116_tidy_efo.py
index 5ebbfd3..14b2db5 100644
--- a/py/20190116_tidy_efo.py
+++ b/py/20190116_tidy_efo.py
@@ -8,6 +8,11 @@
 #%%
 
 import pandas as pd
+import seaborn as sns
+
+import matplotlib.pyplot as plt
+
+sns.set(color_codes=True)
 
 def tidy_efo_preproc_csv(csv, output_csv):
   df = pd.read_csv(csv)
@@ -32,13 +37,26 @@
 
   tidy_df = tidy_df.append(ef_df, ignore_index=True)
   
-  tidy_df.to_csv(output_csv)
-  print(f"Tidy dataset written successfully to {output_csv}")
-
+  return tidy_df
 
 # params
 csv_path = "/Users/morteza/workspace/efo_kickoff/datasets/efo_pubmed_hits.20200114_preproc.csv"
 output_csv_path = csv_path.replace('_preproc.csv', '_tidy.csv')
 
 # make things tidy!
-tidy_efo_preproc_csv(csv_path, output_csv_path)
\ No newline at end of file
+df = tidy_efo_preproc_csv(csv_path, output_csv_path)
+
+
+# exploratory diagrams
+wm_df = df[(df.context == 'EF') & (df.construct == 'Working Memory') & (df.task_hits<1000)]
+
+sns.kdeplot(wm_df.task_hits)
+
+#sns.pairplot(ef_df)
+#sns.distplot(ef_df.task_hits, rug=True)
+
+#f, ax = plt.subplots(figsize=(6, 6))
+#sns.jointplot(ef_df.task_hits,ef_df.construct_hits, kind='kde', ax=ax)
+#sns.rugplot(ef_df.task_hits, color="g", ax=ax)
+#sns.rugplot(ef_df.construct_hits, color="b", vertical=True, ax=ax)
+#sns.jointplot(ef_df.task_hits,ef_df.construct_hits)