diff --git a/Dropout.py b/Dropout.py
new file mode 100644
index 0000000..00e87de
--- /dev/null
+++ b/Dropout.py
@@ -0,0 +1,18 @@
+import pandas as pd
+import numpy as np
+
+# Dropout function: if number of non-null columns is below threshold, return
+# 'True' for each of these columns, and return as a vector (that can be used to
+# subset the training and testing dfs)
+
+def Dropcols(df, threshold = 0.02):
+    TFvec = np.zeros(len(df.columns), dtype = bool)
+    for i in range(len(df.columns)):
+        percent_null = sum(df.iloc[:,i].isnull())/len(df.iloc[:,i])
+        if 1- percent_null > threshold:
+            TFvec[i] = False
+        else:
+            TFvec[i] = True
+    return(TFvec)
+
+