diff --git a/numpy/piecewise​/README.md b/numpy/piecewise​/README.md
index a678a4f..87f4c18 100644
--- a/numpy/piecewise​/README.md
+++ b/numpy/piecewise​/README.md
@@ -29,5 +29,49 @@ b = np.piecewise(a, [a < 5, a == 0, a > 5], [-1, 0, 1])
 print(a)  # -> [ 1  2  3  4  5  6  7  8  9 10]
 print(b)  # -> [-1 -1 -1 -1  0  1  1  1  1  1]
 ```
+Instead of values we can use functions (Or you can use lambda functions...​): 
+
+```python
+import numpy as np
+
+
+def function_a(input):
+    return input**2
+
+
+def function_b(input):
+    return np.sqrt(input)
+
+
+a = np.arange(1, 11)
+b = np.piecewise(a, [a < 5, a == 0, a > 5], [function_a, 0, function_b])
+
+print(a)  # -> [ 1  2  3  4  5  6  7  8  9 10]
+print(b)  # -> [ 1  4  9 16  0  2  2  2  3  3]
+```
+
+**However, the results for the sqrt are strange.** Here we see a case where the automatic dtype switch to float64 failed.​ This is why I overzealously mange / define the dtypes.​
+
+```python
+import numpy as np
+
+
+def function_a(input):
+    return input**2
+
+
+def function_b(input):
+    return np.sqrt(input)
+
+
+a = np.arange(1, 11).astype(dtype=np.float32)
+b = np.piecewise(a, [a < 5, a == 0, a > 5], [function_a, 0, function_b])
+
+print(a)  # -> [ 1.  2.  3.  4.  5.  6.  7.  8.  9. 10.]
+print(b)  # -> [ 1.    4.    9.   16.    0.    2.45  2.65  2.83  3.    3.16]
+```
+
+
+