blocks|key|1837735|text|您可以将列表列表传递给np.array：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1837736|lol+=+[[1,2,+3,+4],+[5,+6,+7,+8],+[9,+10,+11,+12]]
np.array(lol)|code-block|syntax|javascript|1837737|不过，看起来您的names_of_variables_in_a_list是一个字符串列表，而不是对列表变量的引用列表。您可以使用eval来获取实际的变量，而不是字符串表示：|1837738|names_of_variables_in_a_list+=+eval("l"%2Bstr(i))+for+i+in+range(1,+100)]
np.array(names_of_variables_in_a_list)|1837739|尽管eval确实不是一件通常建议/安全的事情。你最好重新考虑让这100个不同的变量。在字典中，每个键是名称，值是列表，这可能会让您更容易做到这一点。|1837740|entityMap^0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Q|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|R|8|@]|9|@]|A|$E|F]]|$1|K|3|L|5|6|7|S|8|@]|9|@]|A|$]]|$1|M|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|N|$]]

You can pass a list of lists to np.array:

<pre><code>lol = [[1,2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
np.array(lol)
</code></pre>

It looks like your names_of_variables_in_a_list is a list of strings and not a list of references to the list variables, though. You can use eval to get the actual variable instead of the string representation:

<pre><code>names_of_variables_in_a_list = eval("l"+str(i)) for i in range(1, 100)]
np.array(names_of_variables_in_a_list)
</code></pre>

though eval really is not a generally advisable/safe thing to do. You're better off reconsidering making those 100 different variables. A dict where each key is the name and the value is the list might make this easier for you.

blocks|key|5622428|text|您可以使用eval函数：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5622429|>>>+l0=[1,2,3]
>>>+l1=[2,4,6]
>>>+np.asarray(list(map(eval,+['l0','l1'])))
array([[1,+2,+3],
+++++++[2,+4,+6]])|code-block|syntax|javascript|5622430|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

You can use eval function:

<pre><code>&gt;&gt;&gt; l0=[1,2,3]
&gt;&gt;&gt; l1=[2,4,6]
&gt;&gt;&gt; np.asarray(list(map(eval, ['l0','l1'])))
array([[1, 2, 3],
 [2, 4, 6]])
</code></pre>

blocks|key|1837806|text|您可以这样做：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1837807|np.array([eval('l'+%2B+str(i))+for+i+in+range(100)])|code-block|syntax|javascript|1837808|或者如果你想使用你已经创建的list_of_names，|offset|length|style|CODE|1837809|np.array([eval(name)+for+name+in+list_of_names])|1837810|或者就像Vicrobot回答的那样|1837811|np.array(list(map(eval,+list_of_names)))|1837812|都是等价的。|1837813|eval('var')返回变量var，有other+(safer)+ways可以做到这一点，但在这里可能没什么问题。[...+for+i+in+range(100)]是一个list+comprehension，它的作用类似于一个创建列表的for循环。|1837814|但我必须指出:像这样命名100个单独的变量是非常糟糕的做法，使用小写l命名变量也是非常糟糕的做法。|1837815|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/9437726/how-to-get-the-value-of-a-variable-given-its-name-in-a-string|1|https://www.pythonforbeginners.com/basics/list-comprehensions-in-python^0|0|0|E|D|0|0|0|0|0|0|B|F|3|1M|P|K|I|0|2E|I|1|0|0^^$0|@$1|2|3|4|5|6|7|18|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|19|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|1A|8|@$I|1B|J|1C|K|L]]|9|@]|A|$]]|$1|M|3|N|5|D|7|1D|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|1E|8|@]|9|@]|A|$]]|$1|Q|3|R|5|D|7|1F|8|@]|9|@]|A|$E|F]]|$1|S|3|T|5|6|7|1G|8|@]|9|@]|A|$]]|$1|U|3|V|5|6|7|1H|8|@$I|1I|J|1J|K|L]|$I|1K|J|1L|K|L]|$I|1M|J|1N|K|L]]|9|@$I|1O|J|1P|1|1Q]|$I|1R|J|1S|1|1T]]|A|$]]|$1|W|3|X|5|6|7|1U|8|@]|9|@]|A|$]]|$1|Y|3|-4|5|6|7|1V|8|@]|9|@]|A|$]]]|Z|$10|$5|11|12|13|A|$14|15]]|16|$5|11|12|13|A|$14|17]]]]

You can do this as

<pre class="lang-py prettyprint-override"><code>np.array([eval('l' + str(i)) for i in range(100)])
</code></pre>

or if you want to use the <code>list_of_names</code> you already created,

<pre class="lang-py prettyprint-override"><code>np.array([eval(name) for name in list_of_names])
</code></pre>

or as Vicrobot answered,

<pre class="lang-py prettyprint-override"><code>np.array(list(map(eval, list_of_names)))
</code></pre>

All equivalent.

<code>eval('var')</code> returns the variable <code>var</code>, and there are <a href="https://stackoverflow.com/questions/9437726/how-to-get-the-value-of-a-variable-given-its-name-in-a-string">other (safer) ways</a> to do this, but it's probably fine here. The <code>[... for i in range(100)]</code> is a <a href="https://www.pythonforbeginners.com/basics/list-comprehensions-in-python" rel="nofollow noreferrer">list comprehension</a> that acts like a for-loop to create a list.

But I have to mention: it is very bad practice to name 100 separate variables like this, and also very bad practice to name variables using lowercase l.

blocks|key|5622514|text|要嵌入list的名称，最自然的方法是使用dictionary：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|5622515|l0+=+[35.467,+1785387,+9984670,+0.913]
l1+=+[63.951,+2833687,+640679,+0.888]
l2+=+[80.940,+3874437,+357114,+0.916]
l3+=+[60.665,+2167744,+301336,+0.873]
l4+=+[127.061,+4602367,+377930,+0.891]
l5+=+[64.511,+2950039,+242495,+0.907]
l6+=+[318.523,+17348075,+9525067,+0.915]

d+=+{}
for+i+in+range(7):
++++d['l{:d}'.format(i)]+=+eval('l{:d}'.format(i))|code-block|syntax|javascript|5622516|那么结果是|5622517|In+[2]:+d
Out[2]:
{'l0':+[35.467,+1785387,+9984670,+0.913],
+'l1':+[63.951,+2833687,+640679,+0.888],
+'l2':+[80.94,+3874437,+357114,+0.916],
+'l3':+[60.665,+2167744,+301336,+0.873],
+'l4':+[127.061,+4602367,+377930,+0.891],
+'l5':+[64.511,+2950039,+242495,+0.907],
+'l6':+[318.523,+17348075,+9525067,+0.915]}|5622518|较短的字典理解：|5622519|d+=+{'l{:d}'.format(i):+eval('l{:d}'.format(i))+for+i+in+range(7)}|5622520|使用f-string时更短(python+>=+3.6)：|5622521|d+=+{f'l{i}':+eval(f'l{i}')+for+i+in+range(7)}|5622522|5622523|如果您想创建numpy+ndarray而不保留list的名称：|5622524|import+numpy+as+np
array2d+=+np.array([eval('l{}'.format(i))+for+i+in+range(7)])|5622525|5622526|In+[4]:+array2d
Out[4]:
array([[3.5467000e%2B01,+1.7853870e%2B06,+9.9846700e%2B06,+9.1300000e-01],
+++++++[6.3951000e%2B01,+2.8336870e%2B06,+6.4067900e%2B05,+8.8800000e-01],
+++++++[8.0940000e%2B01,+3.8744370e%2B06,+3.5711400e%2B05,+9.1600000e-01],
+++++++[6.0665000e%2B01,+2.1677440e%2B06,+3.0133600e%2B05,+8.7300000e-01],
+++++++[1.2706100e%2B02,+4.6023670e%2B06,+3.7793000e%2B05,+8.9100000e-01],
+++++++[6.4511000e%2B01,+2.9500390e%2B06,+2.4249500e%2B05,+9.0700000e-01],
+++++++[3.1852300e%2B02,+1.7348075e%2B07,+9.5250670e%2B06,+9.1500000e-01]])|5622527|其中array2d[i,:]是list+i-th+list。|style|CODE|5622528|使用f-string+(python+>=+3.6)的较短方法：|5622529|array2d+=+np.array([eval(f'l{i}')+for+i+in+range(7)])|5622530|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.python.org/3/tutorial/datastructures.html#dictionaries|1|https://numpy.org/doc/1.18/reference/generated/numpy.ndarray.html^0|K|A|0|0|0|0|0|0|0|0|0|0|6|D|1|0|0|0|0|2|C|K|1|0|0|0^^$0|@$1|2|3|4|5|6|7|1K|8|@]|9|@$A|1L|B|1M|1|1N]]|C|$]]|$1|D|3|E|5|F|7|1O|8|@]|9|@]|C|$G|H]]|$1|I|3|J|5|6|7|1P|8|@]|9|@]|C|$]]|$1|K|3|L|5|F|7|1Q|8|@]|9|@]|C|$G|H]]|$1|M|3|N|5|6|7|1R|8|@]|9|@]|C|$]]|$1|O|3|P|5|F|7|1S|8|@]|9|@]|C|$G|H]]|$1|Q|3|R|5|6|7|1T|8|@]|9|@]|C|$]]|$1|S|3|T|5|F|7|1U|8|@]|9|@]|C|$G|H]]|$1|U|3|-4|5|6|7|1V|8|@]|9|@]|C|$]]|$1|V|3|W|5|6|7|1W|8|@]|9|@$A|1X|B|1Y|1|1Z]]|C|$]]|$1|X|3|Y|5|F|7|20|8|@]|9|@]|C|$G|H]]|$1|Z|3|J|5|6|7|21|8|@]|9|@]|C|$]]|$1|10|3|11|5|F|7|22|8|@]|9|@]|C|$G|H]]|$1|12|3|13|5|6|7|23|8|@$A|24|B|25|14|15]|$A|26|B|27|14|15]]|9|@]|C|$]]|$1|16|3|17|5|6|7|28|8|@]|9|@]|C|$]]|$1|18|3|19|5|F|7|29|8|@]|9|@]|C|$G|H]]|$1|1A|3|-4|5|6|7|2A|8|@]|9|@]|C|$]]]|1B|$1C|$5|1D|1E|1F|C|$1G|1H]]|1I|$5|1D|1E|1F|C|$1G|1J]]]]

To embed the name of list, the natural way would be to use <a href="https://docs.python.org/3/tutorial/datastructures.html#dictionaries" rel="nofollow noreferrer">dictionary</a> :

<pre class="lang-py prettyprint-override"><code>l0 = [35.467, 1785387, 9984670, 0.913]
l1 = [63.951, 2833687, 640679, 0.888]
l2 = [80.940, 3874437, 357114, 0.916]
l3 = [60.665, 2167744, 301336, 0.873]
l4 = [127.061, 4602367, 377930, 0.891]
l5 = [64.511, 2950039, 242495, 0.907]
l6 = [318.523, 17348075, 9525067, 0.915]

d = {}
for i in range(7):
 d['l{:d}'.format(i)] = eval('l{:d}'.format(i))
</code></pre>

then the result is

<pre><code>In [2]: d
Out[2]:
{'l0': [35.467, 1785387, 9984670, 0.913],
 'l1': [63.951, 2833687, 640679, 0.888],
 'l2': [80.94, 3874437, 357114, 0.916],
 'l3': [60.665, 2167744, 301336, 0.873],
 'l4': [127.061, 4602367, 377930, 0.891],
 'l5': [64.511, 2950039, 242495, 0.907],
 'l6': [318.523, 17348075, 9525067, 0.915]}
</code></pre>

Shorter with dictionary comprehension :

<pre class="lang-py prettyprint-override"><code>d = {'l{:d}'.format(i): eval('l{:d}'.format(i)) for i in range(7)}
</code></pre>

and even shorter with f-string (python >= 3.6) :

<pre class="lang-py prettyprint-override"><code>d = {f'l{i}': eval(f'l{i}') for i in range(7)}
</code></pre>

<hr>

If you want to create an <a href="https://numpy.org/doc/1.18/reference/generated/numpy.ndarray.html" rel="nofollow noreferrer">numpy ndarray</a> without keeping the name of list :

<pre class="lang-py prettyprint-override"><code>import numpy as np
array2d = np.array([eval('l{}'.format(i)) for i in range(7)])
</code></pre>

then the result is

<pre><code>In [4]: array2d
Out[4]:
array([[3.5467000e+01, 1.7853870e+06, 9.9846700e+06, 9.1300000e-01],
 [6.3951000e+01, 2.8336870e+06, 6.4067900e+05, 8.8800000e-01],
 [8.0940000e+01, 3.8744370e+06, 3.5711400e+05, 9.1600000e-01],
 [6.0665000e+01, 2.1677440e+06, 3.0133600e+05, 8.7300000e-01],
 [1.2706100e+02, 4.6023670e+06, 3.7793000e+05, 8.9100000e-01],
 [6.4511000e+01, 2.9500390e+06, 2.4249500e+05, 9.0700000e-01],
 [3.1852300e+02, 1.7348075e+07, 9.5250670e+06, 9.1500000e-01]])
</code></pre>

where <code>array2d[i,:]</code> is list <code>i</code>-th list. 
And the shorter way with f-string (python >= 3.6) :

<pre class="lang-py prettyprint-override"><code>array2d = np.array([eval(f'l{i}') for i in range(7)])
</code></pre>

blocks|key|4154201|text|你是如何获得这些列表的？是否从文件加载？复制粘贴？|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4154202|如果将您的示例复制-n-粘贴到ipython会话中，我可以使用以下命令获得列表列表：|offset|length|style|CODE|4154203|In+[866]:+alist+=+[globals()[f'l{i}']+for+i+in+range(0,6)]+++++++++++++++++++++++++++++++++++++++++++++
In+[867]:+alist++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Out[867]:+
[[35.467,+1785387,+9984670,+0.913],
+[63.951,+2833687,+640679,+0.888],
+[80.94,+3874437,+357114,+0.916],
+[60.665,+2167744,+301336,+0.873],
+[127.061,+4602367,+377930,+0.891],
+[64.511,+2950039,+242495,+0.907]]
In+[868]:+np.array(alist)++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Out[868]:+
array([[3.546700e%2B01,+1.785387e%2B06,+9.984670e%2B06,+9.130000e-01],
+++++++[6.395100e%2B01,+2.833687e%2B06,+6.406790e%2B05,+8.880000e-01],
+++++++[8.094000e%2B01,+3.874437e%2B06,+3.571140e%2B05,+9.160000e-01],
+++++++[6.066500e%2B01,+2.167744e%2B06,+3.013360e%2B05,+8.730000e-01],
+++++++[1.270610e%2B02,+4.602367e%2B06,+3.779300e%2B05,+8.910000e-01],
+++++++[6.451100e%2B01,+2.950039e%2B06,+2.424950e%2B05,+9.070000e-01]])|code-block|syntax|javascript|4154204|globals()是当前在会话中定义的所有变量的字典。|4154205|In+[869]:+globals()['l1']++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Out[869]:+[63.951,+2833687,+640679,+0.888]|4154206|像这样使用globals与使用exec类似|4154207|像这样提供一长串变量并不是好的Python风格。最好是直接提供列表的列表。如果源程序完成了所有的输入工作：|4154208|l0+=+...
11+=+...|4154209|他们也可以提供alist+=+[l0,+l1,+...]或输入列表列表，如我在[876]中所示|4154210|entityMap^0|0|F|7|0|0|0|9|0|0|5|7|F|4|0|0|0|7|L|13|5|0^^$0|@$1|2|3|4|5|6|7|10|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|11|8|@$D|12|E|13|F|G]]|9|@]|A|$]]|$1|H|3|I|5|J|7|14|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|15|8|@$D|16|E|17|F|G]]|9|@]|A|$]]|$1|O|3|P|5|J|7|18|8|@]|9|@]|A|$K|L]]|$1|Q|3|R|5|6|7|19|8|@$D|1A|E|1B|F|G]|$D|1C|E|1D|F|G]]|9|@]|A|$]]|$1|S|3|T|5|6|7|1E|8|@]|9|@]|A|$]]|$1|U|3|V|5|J|7|1F|8|@]|9|@]|A|$K|L]]|$1|W|3|X|5|6|7|1G|8|@$D|1H|E|1I|F|G]|$D|1J|E|1K|F|G]]|9|@]|A|$]]|$1|Y|3|-4|5|6|7|1L|8|@]|9|@]|A|$]]]|Z|$]]

How do you get those lists? Load from a file? copy-n-paste?

If copy-n-paste your sample to an <code>ipython</code> session, I can get a list of lists with:

<pre><code>In [866]: alist = [globals()[f'l{i}'] for i in range(0,6)] 
In [867]: alist 
Out[867]: 
[[35.467, 1785387, 9984670, 0.913],
 [63.951, 2833687, 640679, 0.888],
 [80.94, 3874437, 357114, 0.916],
 [60.665, 2167744, 301336, 0.873],
 [127.061, 4602367, 377930, 0.891],
 [64.511, 2950039, 242495, 0.907]]
In [868]: np.array(alist) 
Out[868]: 
array([[3.546700e+01, 1.785387e+06, 9.984670e+06, 9.130000e-01],
 [6.395100e+01, 2.833687e+06, 6.406790e+05, 8.880000e-01],
 [8.094000e+01, 3.874437e+06, 3.571140e+05, 9.160000e-01],
 [6.066500e+01, 2.167744e+06, 3.013360e+05, 8.730000e-01],
 [1.270610e+02, 4.602367e+06, 3.779300e+05, 8.910000e-01],
 [6.451100e+01, 2.950039e+06, 2.424950e+05, 9.070000e-01]])
</code></pre>

<code>globals()</code> is a dictionary of all variables currently defined in the session. 

<pre><code>In [869]: globals()['l1'] 
Out[869]: [63.951, 2833687, 640679, 0.888]
</code></pre>

Using <code>globals</code> like this is similar to using <code>exec</code>

Providing a long list of variables like this is not good Python style. It's better to provide a list of the lists directly. If the source went to all the work of typing: 

<pre><code>l0 = ...
11 = ...
</code></pre>

they could also have provided <code>alist = [l0, l1, ...]</code> or entered a list of lists as I show in <code>[876]</code>

I have 100 lists :

<pre class="lang-py prettyprint-override"><code>l0 = [35.467, 1785387, 9984670, 0.913]
l1 = [63.951, 2833687, 640679, 0.888]
l2 = [80.940, 3874437, 357114, 0.916]
l3 = [60.665, 2167744, 301336, 0.873]
l4 = [127.061, 4602367, 377930, 0.891]
l5 = [64.511, 2950039, 242495, 0.907]
l6 = [318.523, 17348075, 9525067, 0.915]
</code></pre>

I want to create it as a Numpy array of 100 rows and 4 columns. I am wondering if there's a way to pass the names of the list into the Numpy array function directly?

I have used <code>for</code> loop to create a list which then stores : 
<code>names_of_variables_in_a_list = ['l0,', 'l1,', 'l2,', 'l3,', 'l4,', 'l5,', 'l6,'....,'l99','l100']</code>

But when I am trying to pass it like : 
<code>Employee_data = np.array(names_of_variables_in_a_list)</code>. 
It's not working, could anyone know if this is possible?

Passing list names as a list to create a numpy array in Python

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我有100个列表：l0 = [35.467, 1785387, 9984670,  0.913]l1 = [63.951, 2833687, 640679,  0.888]l2 = [80.940, 3874437, 357114,  0.916]l3 = [60.665, 2167744, 301336,  0.87...

问将列表名称作为列表传递以在Python中创建numpy数组
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问将列表名称作为列表传递以在Python中创建numpy数组EN