Numpy - 편집 역사

2018년 2월 21일 (수) 08:58에 Admin님의 편집

2018-02-21T08:58:33Z

2018-02-05T09:39:41Z

array of arbitrary length strings

2018-02-05T09:39:17Z

set_printoptions

2018-02-05T06:59:17Z

Array to column vector

2018-02-05T06:58:55Z

Array to column vector

2017-08-07T10:36:25Z

set_printoptions

2017-08-01T02:20:55Z

set_printoptions

2017-08-01T02:20:02Z

2017-08-01T02:16:21Z

Array to column vector

2017-05-08T08:23:56Z

Get a distance matrix

← 이전 판		2018년 2월 21일 (수) 08:58 판
74번째 줄:		74번째 줄:
	write <code>dtype=object</code> when create an array.		write <code>dtype=object</code> when create an array.
	<nowiki>np.array([['']*3 for _ in range(wc)], dtype=object)</nowiki>		<nowiki>np.array([['']*3 for _ in range(wc)], dtype=object)</nowiki>
		+
		+	==from string data to one hot vector==
		+	[https://stackoverflow.com/a/33010943/766330]
		+	<pre><nowiki>
		+	from sklearn.feature_extraction import DictVectorizer
		+	import pandas as pd
		+
		+	dv = DictVectorizer(sparse=False)
		+	df = pd.DataFrame(M).convert_objects(convert_numeric=True)
		+	dv.fit_transform(df.to_dict(orient='records'))
		+
		+	array([[ 5. , 0.2, 1. , 0. , 1. , 0. ],
		+	[ 2. , 1.3, 1. , 0. , 0. , 1. ],
		+	[ 1. , 2.3, 0. , 1. , 0. , 1. ]])
		+	</nowiki></pre>

@@ 73번째 줄: / 73번째 줄: @@
 ==array of arbitrary length strings==
 write <code>dtype=object</code> when create an array.
-  np.array([['']*3 for _ in range(wc)], dtype=object)
+  <nowiki>np.array([['']*3 for _ in range(wc)], dtype=object)</nowiki>

← 이전 판		2018년 2월 5일 (월) 09:39 판
70번째 줄:		70번째 줄:
	blablablabla...</pre>		blablablabla...</pre>
	[https://docs.scipy.org/doc/numpy/reference/generated/numpy.set_printoptions.html numpy manual]		[https://docs.scipy.org/doc/numpy/reference/generated/numpy.set_printoptions.html numpy manual]
		+
		+	==array of arbitrary length strings==
		+	write <code>dtype=object</code> when create an array.
		+	np.array([['']*3 for _ in range(wc)], dtype=object)

@@ 32번째 줄: / 32번째 줄: @@
 >>> a[np.newaxis, :]
 array([[1, 2, 3]])
->>> np.newaxis is None
+>>> np.newaxis is None # so you can use None instead of np.newaxis
 True</pre>
 http://stackoverflow.com/a/17428859/766330

@@ 31번째 줄: / 31번째 줄: @@
         [3]])
 >>> a[np.newaxis, :]
-array([[1, 2, 3]])</pre>
+array([[1, 2, 3]])
 http://stackoverflow.com/a/17428859/766330
 <pre>

@@ 61번째 줄: / 61번째 줄: @@
         [ 0.42103587,  0.43982509,  0.42412681, ...,  0.04823858,
 .94207207,  0.46931123]])
->>> np.set_printoptions(threshold=100000)
+>>> np.set_printoptions(threshold=100000) # see `linewidth' also
 >>> np.random.rand(100,100)
 array([[  8.62450822e-02,   3.64229303e-01,   5.15339939e-01,
@@ 67번째 줄: / 67번째 줄: @@
 .69844754e-01,   2.78414489e-01,   5.24304684e-01,
            blablablabla...</pre>

@@ 46번째 줄: / 46번째 줄: @@
 ==<c>set_printoptions</c>==
 <pre>>>> np.random.rand(100,100)
 array([[ 0.46154546,  0.12353798,  0.27590724, ...,  0.24265687,

← 이전 판		2017년 8월 1일 (화) 02:20 판
45번째 줄:		45번째 줄:
	<br>{{c\|pdist}} means ''pairwise distance''. From this, {{c\|scipy.spatial.distance.squareform(X)}} can make the distance matrix.[https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.squareform.html#scipy.spatial.distance.squareform]		<br>{{c\|pdist}} means ''pairwise distance''. From this, {{c\|scipy.spatial.distance.squareform(X)}} can make the distance matrix.[https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.squareform.html#scipy.spatial.distance.squareform]

−	==a==	+	==<c>set_printoptions</c>==
		+	<pre>>>> np.random.rand(100,100)
		+	array([[ 0.46154546, 0.12353798, 0.27590724, ..., 0.24265687,
		+	0.84255677, 0.95283526],
		+	[ 0.73838516, 0.47949374, 0.23105863, ..., 0.08543431,
		+	0.91986747, 0.14417515],
		+	[ 0.31065035, 0.28328507, 0.29925302, ..., 0.79512885,
		+	0.09237567, 0.49872117],
		+	...,
		+	[ 0.63830484, 0.53113463, 0.22787907, ..., 0.41847976,
		+	0.42330993, 0.78735475],
		+	[ 0.94555611, 0.68517865, 0.82703527, ..., 0.84290377,
		+	0.75802783, 0.20678318],
		+	[ 0.42103587, 0.43982509, 0.42412681, ..., 0.04823858,
		+	0.94207207, 0.46931123]])
		+	>>> np.set_printoptions(threshold=100000)
		+	>>> np.random.rand(100,100)
		+	array([[ 8.62450822e-02, 3.64229303e-01, 5.15339939e-01,
		+	4.24720591e-01, 4.27696324e-02, 6.75689424e-01,
		+	2.69844754e-01, 2.78414489e-01, 5.24304684e-01,
		+	blablablabla...</pre>

@@ 38번째 줄: / 38번째 줄: @@
   X : ndarray
 X is m by n matrix, and ''rows'' are observations. So X is ''m'' observations.
 ==a==