np.array returning numpy.ndarray with "..."
<p>I created a script to generate a list:</p>

<pre><code>import random

nota1 = range (5, 11)
nota2 = range (5, 11)
nota3 = range (5, 11)
nota4 = range (0, 2)

dados = []

for i in range(1000):

    dados_dado = []

    n1 = random.choice(nota1)
    n2 = random.choice(nota2)
    n3 = random.choice(nota3)
    n4 = random.choice(nota4)

    n1 = float (n1)
    n2 = float (n2)
    n3 = float (n3)
    n4 = float (n4)

    dados_dado.append (n1)
    dados_dado.append (n2)
    dados_dado.append (n3)
    dados_dado.append (n4)

    dados.append (dados_dado)
</code></pre>

<p>When i print <code>type (dados)</code> python return: <code>&lt;type 'list'&gt;</code>, a huge list that looks like this:</p>

<pre><code>[[5.0, 8.0, 10.0, 1.0], [8.0, 9.0, 9.0, 1.0], [7.0, 5.0, 6.0, 1.0], [5.0, 8.0, 7.0, 0.0], [9.0, 7.0, 10.0, 0.0], [6.0, 7.0, 9.0, 1.0], [6.0, 9.0, 8.0, 1.0]]
</code></pre>

<p>I need to transform it to <code>&lt;type 'numpy.ndarray'&gt;</code> so i made :</p>

<pre><code>data = np.array(dados)
</code></pre>

<p>What i expected to return was something like this:</p>

<pre><code> [[ 6.8  3.2  5.9  2.3]
 [ 6.7  3.3  5.7  2.5]
 [ 6.7  3.   5.2  2.3]
 [ 6.3  2.5  5.   1.9]
 [ 6.5  3.   5.2  2. ]
 [ 6.2  3.4  5.4  2.3]
 [ 5.9  3.   5.1  1.8]]
</code></pre>

<p>But, what i get instead is:</p>

<pre><code> [[  7.  10.   6.   1.]
  [  8.   6.   6.   1.]
  [  6.   9.   5.   0.]
  ..., 
  [  9.   7.  10.   0.]
  [  6.   7.   9.   1.]
  [  6.   9.   8.   1.]]
</code></pre>

<p>What am i doing wrong?</p>

<p>Your array is fine. NumPy just suppresses display of the whole array for large arrays by default.</p>

<p>(If you actually <em>were</em> expecting your array to be short enough not to trigger this behavior, or if you were actually expecting it to have non-integer entries, you'll have to explain why you expected that.)</p>

python arrays numpy