diff --git a/lstm_model.py b/lstm_model.py
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..3037d0f0b01df37613cac4028224540304d61b84 100644
--- a/lstm_model.py
+++ b/lstm_model.py
@@ -0,0 +1,29 @@
+from pandas import DataFrame
+from pandas import concat
+
+def  series_to_supervised(data, n_in=1, n_out=1, dropnan=True):
+    n_vars = 1 if type(data) is list else data.shape[1]
+    df = DataFrame(data)
+    cols, names = list(), list()
+	# input sequence (t-n, ... t-1)
+    for i in range(n_in, 0, -1):
+        cols.append(df.shift(i))
+        names += [('var%d(t-%d)' % (j+1, i)) for j in range(n_vars)]
+	# forecast sequence (t, t+1, ... t+n)
+    for i in range(0, n_out):
+        cols.append(df.shift(-i))
+        if i == 0:
+            names += [('var%d(t)' % (j+1)) for j in range(n_vars)]
+        else:
+            names += [('var%d(t+%d)' % (j+1, i)) for j in range(n_vars)]
+	# put it all together
+    agg = concat(cols, axis=1)
+    agg.columns = names
+	# drop rows with NaN values
+    if dropnan:
+        agg.dropna(inplace=True)
+        return agg
+
+
+
+