Merge 59f97ba into 2ba25c5

README.md

@@ -26,6 +26,9 @@ pip install datascience
 
 This project adheres to [Semantic Versioning](http://semver.org/).
 
+### v0.12.1
+* Adds a new optional argument to `make_array` to specify the dtype of the data.
+
 ### v0.12.0
 * Changes `Table#scatter`'s argument name of `colors` to `group` to mirror `Table#hist`.
 * Makes a grouped scatterplot's legend identical to a group histogram's legend.

datascience/util.py

@@ -17,7 +17,7 @@
 # Change matplotlib formatting. TODO incorporate into a style?
 plt.rcParams["patch.force_edgecolor"] = True
 
-def make_array(*elements):
+def make_array(*elements, dtype=None):
     """Returns an array containing all the arguments passed to this function.
     A simple way to make an array with a few elements.
 
@@ -33,6 +33,8 @@ def make_array(*elements):
     >>> make_array()
     array([], dtype=float64)
     """
+    if dtype:
+        return np.array(elements, dtype=dtype)
     return np.array(elements)
 
 

datascience/version.py

@@ -1 +1 @@
-__version__ = '0.12.0'
+__version__ = '0.12.1'

tests/test_util.py

@@ -4,11 +4,24 @@
 from datascience import util
 import numpy as np
 
-
 def test_doctests():
     results = doctest.testmod(util, optionflags=doctest.NORMALIZE_WHITESPACE)
     assert results.failed == 0
 
+def test_make_array_dtype():
+    test1 = ds.make_array(0)
+    assert len(test1) == 1
+    test2 = ds.make_array(2, 3, 4)
+    assert sum(test2) == 9
+    test3 = ds.make_array("foo", "bar")
+    assert test3.dtype == "<U3"
+    test4 = ds.make_array(1, 2, 3, dtype="int32")
+    assert test4.dtype == "int32"
+    test5 = ds.make_array(1, 2, 3, dtype="int64")
+    assert test5.dtype == "int64"
+    test6 = ds.make_array("foo", "bar", dtype="<U6")
+    assert test6.dtype == "<U6"
+
 
 def test_percentile():
     assert ds.percentile(0, [1, 3, 5, 9]) == 1