Merge pull request eriklindernoren#43 from miku/fix-deprecated-as-matrix

df.as_matrix has been deprecated since 0.23.0
Rohit-Kumar18 · Aug 30, 2018 · f278751 · f278751
2 parents d8d8660 + 68182ad
commit f278751
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Showing 7 changed files with 14 additions and 14 deletions.
diff --git a/mlfromscratch/examples/bayesian_regression.py b/mlfromscratch/examples/bayesian_regression.py
@@ -12,8 +12,8 @@ def main():
     # Load temperature data
     data = pd.read_csv('mlfromscratch/data/TempLinkoping2016.txt', sep="\t")
 
-    time = np.atleast_2d(data["time"].as_matrix()).T
-    temp = np.atleast_2d(data["temp"].as_matrix()).T
+    time = np.atleast_2d(data["time"].values).T
+    temp = np.atleast_2d(data["temp"].values).T
 
     X = time # fraction of the year [0, 1]
     y = temp

diff --git a/mlfromscratch/examples/decision_tree_regressor.py b/mlfromscratch/examples/decision_tree_regressor.py
@@ -14,8 +14,8 @@ def main():
     # Load temperature data
     data = pd.read_csv('mlfromscratch/data/TempLinkoping2016.txt', sep="\t")
 
-    time = np.atleast_2d(data["time"].as_matrix()).T
-    temp = np.atleast_2d(data["temp"].as_matrix()).T
+    time = np.atleast_2d(data["time"].values).T
+    temp = np.atleast_2d(data["temp"].values).T
 
     X = standardize(time)        # Time. Fraction of the year [0, 1]
     y = temp[:, 0]  # Temperature. Reduce to one-dim

diff --git a/mlfromscratch/examples/elastic_net.py b/mlfromscratch/examples/elastic_net.py
@@ -13,8 +13,8 @@ def main():
     # Load temperature data
     data = pd.read_csv('mlfromscratch/data/TempLinkoping2016.txt', sep="\t")
 
-    time = np.atleast_2d(data["time"].as_matrix()).T
-    temp = data["temp"].as_matrix()
+    time = np.atleast_2d(data["time"].values).T
+    temp = data["temp"].values
 
     X = time # fraction of the year [0, 1]
     y = temp

diff --git a/mlfromscratch/examples/gradient_boosting_regressor.py b/mlfromscratch/examples/gradient_boosting_regressor.py
@@ -17,8 +17,8 @@ def main():
     # Load temperature data
     data = pd.read_csv('mlfromscratch/data/TempLinkoping2016.txt', sep="\t")
 
-    time = np.atleast_2d(data["time"].as_matrix()).T
-    temp = np.atleast_2d(data["temp"].as_matrix()).T
+    time = np.atleast_2d(data["time"].values).T
+    temp = np.atleast_2d(data["temp"].values).T
 
     X = time.reshape((-1, 1))               # Time. Fraction of the year [0, 1]
     X = np.insert(X, 0, values=1, axis=1)   # Insert bias term

diff --git a/mlfromscratch/examples/lasso_regression.py b/mlfromscratch/examples/lasso_regression.py
@@ -13,8 +13,8 @@ def main():
     # Load temperature data
     data = pd.read_csv('mlfromscratch/data/TempLinkoping2016.txt', sep="\t")
 
-    time = np.atleast_2d(data["time"].as_matrix()).T
-    temp = data["temp"].as_matrix()
+    time = np.atleast_2d(data["time"].values).T
+    temp = data["temp"].values
 
     X = time # fraction of the year [0, 1]
     y = temp

diff --git a/mlfromscratch/examples/polynomial_regression.py b/mlfromscratch/examples/polynomial_regression.py
@@ -13,8 +13,8 @@ def main():
     # Load temperature data
     data = pd.read_csv('mlfromscratch/data/TempLinkoping2016.txt', sep="\t")
 
-    time = np.atleast_2d(data["time"].as_matrix()).T
-    temp = data["temp"].as_matrix()
+    time = np.atleast_2d(data["time"].values).T
+    temp = data["temp"].values
 
     X = time # fraction of the year [0, 1]
     y = temp

diff --git a/mlfromscratch/examples/ridge_regression.py b/mlfromscratch/examples/ridge_regression.py
@@ -13,8 +13,8 @@ def main():
     # Load temperature data
     data = pd.read_csv('mlfromscratch/data/TempLinkoping2016.txt', sep="\t")
 
-    time = np.atleast_2d(data["time"].as_matrix()).T
-    temp = data["temp"].as_matrix()
+    time = np.atleast_2d(data["time"].values).T
+    temp = data["temp"].values
 
     X = time # fraction of the year [0, 1]
     y = temp