blocks|key|794808|text|Python+2：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|794809|>>>+theArray+=+[['a','b','c'],['d','e','f'],['g','h','i']]
>>>+zip(*theArray)
[('a',+'d',+'g'),+('b',+'e',+'h'),+('c',+'f',+'i')]|code-block|syntax|javascript|794810|Python+3：|794811|>>>+[*zip(*theArray)]
[('a',+'d',+'g'),+('b',+'e',+'h'),+('c',+'f',+'i')]|794812|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

Python 2:

<pre><code>&gt;&gt;&gt; theArray = [['a','b','c'],['d','e','f'],['g','h','i']]
&gt;&gt;&gt; zip(*theArray)
[('a', 'd', 'g'), ('b', 'e', 'h'), ('c', 'f', 'i')]
</code></pre>

Python 3:

<pre><code>&gt;&gt;&gt; [*zip(*theArray)]
[('a', 'd', 'g'), ('b', 'e', 'h'), ('c', 'f', 'i')]
</code></pre>

blocks|key|1009441|text|>>>+theArray+=+[['a','b','c'],['d','e','f'],['g','h','i']]
>>>+[list(i)+for+i+in+zip(*theArray)]
[['a',+'d',+'g'],+['b',+'e',+'h'],+['c',+'f',+'i']]|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1009442|列表生成器创建具有列表项而不是元组的新的2d数组。|unstyled|1009443|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$B|C]]|$1|D|3|E|5|F|7|J|8|@]|9|@]|A|$]]|$1|G|3|-4|5|F|7|K|8|@]|9|@]|A|$]]]|H|$]]

<pre><code>&gt;&gt;&gt; theArray = [['a','b','c'],['d','e','f'],['g','h','i']]
&gt;&gt;&gt; [list(i) for i in zip(*theArray)]
[['a', 'd', 'g'], ['b', 'e', 'h'], ['c', 'f', 'i']]
</code></pre>

the list generator creates a new 2d array with list items instead of tuples.

blocks|key|794915|text|如果行不相等，也可以使用map|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|794916|>>>+uneven+=+[['a','b','c'],['d','e'],['g','h','i']]
>>>+map(None,*uneven)
[('a',+'d',+'g'),+('b',+'e',+'h'),+('c',+None,+'i')]|code-block|syntax|javascript|794917|编辑:在Python3中，map的功能发生了变化，可以使用itertools.zip_longest：|794918|来源：What’s+New+In+Python+3.0|794919|>>>+import+itertools
>>>+uneven+=+[['a','b','c'],['d','e'],['g','h','i']]
>>>+list(itertools.zip_longest(*uneven))
[('a',+'d',+'g'),+('b',+'e',+'h'),+('c',+None,+'i')]|794920|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.python.org/3/whatsnew/3.0.html#views-and-iterators-instead-of-lists^0|C|3|0|0|D|3|T|L|0|3|O|0|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@$9|Z|A|10|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|11|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|12|8|@$9|13|A|14|B|C]|$9|15|A|16|B|C]]|D|@]|E|$]]|$1|M|3|N|5|6|7|17|8|@]|D|@$9|18|A|19|1|1A]]|E|$]]|$1|O|3|P|5|H|7|1B|8|@]|D|@]|E|$I|J]]|$1|Q|3|-4|5|6|7|1C|8|@]|D|@]|E|$]]]|R|$S|$5|T|U|V|E|$W|X]]]]

If your rows are not equal you can also use <code>map</code>:

<pre><code>&gt;&gt;&gt; uneven = [['a','b','c'],['d','e'],['g','h','i']]
&gt;&gt;&gt; map(None,*uneven)
[('a', 'd', 'g'), ('b', 'e', 'h'), ('c', None, 'i')]
</code></pre>

Edit: In Python 3 the functionality of <code>map</code> changed, <code>itertools.zip_longest</code> can be used instead: 
 Source: <a href="http://docs.python.org/3/whatsnew/3.0.html#views-and-iterators-instead-of-lists" rel="noreferrer">What’s New In Python 3.0</a>

<pre><code>&gt;&gt;&gt; import itertools
&gt;&gt;&gt; uneven = [['a','b','c'],['d','e'],['g','h','i']]
&gt;&gt;&gt; list(itertools.zip_longest(*uneven))
[('a', 'd', 'g'), ('b', 'e', 'h'), ('c', None, 'i')]
</code></pre>

blocks|key|795090|text|使用numpy要容易得多：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|795091|>>>+arr+=+np.array([[1,2,3],[4,5,6],[7,8,9]])
>>>+arr
array([[1,+2,+3],
+++++++[4,+5,+6],
+++++++[7,+8,+9]])
>>>+arr.T
array([[1,+4,+7],
+++++++[2,+5,+8],
+++++++[3,+6,+9]])
>>>+theArray+=+np.array([['a','b','c'],['d','e','f'],['g','h','i']])
>>>+theArray+
array([['a',+'b',+'c'],
+++++++['d',+'e',+'f'],
+++++++['g',+'h',+'i']],+
++++++dtype='%7CS1')
>>>+theArray.T
array([['a',+'d',+'g'],
+++++++['b',+'e',+'h'],
+++++++['c',+'f',+'i']],+
++++++dtype='%7CS1')|code-block|syntax|javascript|795092|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|$]]

Much easier with numpy:

<pre><code>&gt;&gt;&gt; arr = np.array([[1,2,3],[4,5,6],[7,8,9]])
&gt;&gt;&gt; arr
array([[1, 2, 3],
 [4, 5, 6],
 [7, 8, 9]])
&gt;&gt;&gt; arr.T
array([[1, 4, 7],
 [2, 5, 8],
 [3, 6, 9]])
&gt;&gt;&gt; theArray = np.array([['a','b','c'],['d','e','f'],['g','h','i']])
&gt;&gt;&gt; theArray 
array([['a', 'b', 'c'],
 ['d', 'e', 'f'],
 ['g', 'h', 'i']], 
 dtype='|S1')
&gt;&gt;&gt; theArray.T
array([['a', 'd', 'g'],
 ['b', 'e', 'h'],
 ['c', 'f', 'i']], 
 dtype='|S1')
</code></pre>

blocks|key|1008948|text|原始代码的问题在于您在每个元素上都初始化了transpose[t]，而不是每行只初始化一次：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1008949|def+matrixTranspose(anArray):
++++transposed+=+[None]*len(anArray[0])
++++for+t+in+range(len(anArray)):
++++++++transposed[t]+=+[None]*len(anArray)
++++++++for+tt+in+range(len(anArray[t])):
++++++++++++transposed[t][tt]+=+anArray[tt][t]
++++print+transposed|code-block|syntax|javascript|1008950|这是可行的，尽管有更多Pythonic式的方法来完成相同的事情，包括@J.F.的zip应用程序。|1008951|entityMap^0|L|C|0|0|14|3|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|S|8|@$9|T|A|U|B|C]]|D|@]|E|$]]|$1|M|3|-4|5|6|7|V|8|@]|D|@]|E|$]]]|N|$]]

The problem with your original code was that you initialized <code>transpose[t]</code> at every element, rather than just once per row:

<pre><code>def matrixTranspose(anArray):
 transposed = [None]*len(anArray[0])
 for t in range(len(anArray)):
 transposed[t] = [None]*len(anArray)
 for tt in range(len(anArray[t])):
 transposed[t][tt] = anArray[tt][t]
 print transposed
</code></pre>

This works, though there are more Pythonic ways to accomplish the same things, including @J.F.'s <code>zip</code> application.

blocks|key|1009542|text|“最佳”答案已经提交，但我想补充一句，您可以使用嵌套列表理解，如Python+Tutorial中所示。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1009543|下面是如何获得转置数组的方法：|1009544|def+matrixTranspose(+matrix+):
++++if+not+matrix:+return+[]
++++return+[+[+row[+i+]+for+row+in+matrix+]+for+i+in+range(+len(+matrix[+0+]+)+)+]|code-block|syntax|javascript|1009545|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.python.org/3/tutorial/datastructures.html#nested-list-comprehensions^0|W|F|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@$A|T|B|U|1|V]]|C|$]]|$1|D|3|E|5|6|7|W|8|@]|9|@]|C|$]]|$1|F|3|G|5|H|7|X|8|@]|9|@]|C|$I|J]]|$1|K|3|-4|5|6|7|Y|8|@]|9|@]|C|$]]]|L|$M|$5|N|O|P|C|$Q|R]]]]

The "best" answer has already been submitted, but I thought I would add that you can use nested list comprehensions, as seen in the <a href="http://docs.python.org/3/tutorial/datastructures.html#nested-list-comprehensions" rel="noreferrer">Python Tutorial</a>. 

Here is how you could get a transposed array:

<pre><code>def matrixTranspose( matrix ):
 if not matrix: return []
 return [ [ row[ i ] for row in matrix ] for i in range( len( matrix[ 0 ] ) ) ]
</code></pre>

blocks|key|1009675|text|这将保留矩形形状，以便后续的转置将获得正确的结果：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1009676|import+itertools
def+transpose(list_of_lists):
++return+list(itertools.izip_longest(*list_of_lists,fillvalue='+'))|code-block|syntax|javascript|1009677|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|$]]

This one will preserve rectangular shape, so that subsequent transposes will get the right result:

<pre><code>import itertools
def transpose(list_of_lists):
 return list(itertools.izip_longest(*list_of_lists,fillvalue=' '))
</code></pre>

blocks|key|1009940|text|您可以尝试使用列表理解，如下所示|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1009941|matrix+=+[['a','b','c'],['d','e','f'],['g','h','i']]+n+=+len(matrix)+transpose+=+[[row[i]+for+row+in+matrix]+for+i+in+range(n)]+print+(transpose)|offset|length|style|CODE|1009942|entityMap^0|0|0|41|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@$D|L|E|M|F|G]]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

you can try this with list comprehension like the following

<code>matrix = [['a','b','c'],['d','e','f'],['g','h','i']]
n = len(matrix)
transpose = [[row[i] for row in matrix] for i in range(n)]
print (transpose)</code>

blocks|key|1009868|text|如果您想转置一个像A=+np.array([+1,2，3,4])这样的矩阵，那么您可以简单地使用A.T，但是对于像a=1，2这样的向量，a.T不会返回转置！并且您需要使用a.reshape(-1，1)，如下所示|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1009869|import+numpy+as+np
a+=+np.array([1,2])
print('a.T+not+transposing+Python!\n','a+=+',a,'\n','a.T+=+',+a.T)
print('Transpose+of+vector+a+is:+\n',a.reshape(-1,+1))

A+=+np.array([[1,2],[3,4]])
print('Transpose+of+matrix+A+is:+\n',A.T)|code-block|syntax|javascript|1009870|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|$]]

If you want to transpose a matrix like A = np.array([[1,2],[3,4]]), then you can simply use A.T, but for a vector like a = [1,2], a.T does not return a transpose! and you need to use a.reshape(-1, 1), as below

<pre><code>import numpy as np
a = np.array([1,2])
print('a.T not transposing Python!\n','a = ',a,'\n','a.T = ', a.T)
print('Transpose of vector a is: \n',a.reshape(-1, 1))

A = np.array([[1,2],[3,4]])
print('Transpose of matrix A is: \n',A.T)
</code></pre>

blocks|key|1009896|text|你可以简单地使用python+comprehension来完成。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1009897|arr+=+[
++++['a',+'b',+'c'],+
++++['d',+'e',+'f'],+
++++['g',+'h',+'i']
]
transpose+=+[[arr[y][x]+for+y+in+range(len(arr))]+for+x+in+range(len(arr[0]))]|code-block|syntax|javascript|1009898|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 may do it simply using python comprehension.

<pre class="lang-py prettyprint-override"><code>arr = [
 ['a', 'b', 'c'], 
 ['d', 'e', 'f'], 
 ['g', 'h', 'i']
]
transpose = [[arr[y][x] for y in range(len(arr))] for x in range(len(arr[0]))]
</code></pre>

blocks|key|1008962|text|def+matrixTranspose(anArray):
++transposed+=+[None]*len(anArray[0])

++for+i+in+range(len(transposed)):
++++transposed[i]+=+[None]*len(transposed)

++for+t+in+range(len(anArray)):
++++for+tt+in+range(len(anArray[t])):++++++++++++
++++++++transposed[t][tt]+=+anArray[tt][t]
++return+transposed

theArray+=+[['a','b','c'],['d','e','f'],['g','h','i']]

print+matrixTranspose(theArray)|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1008963|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>def matrixTranspose(anArray):
 transposed = [None]*len(anArray[0])

 for i in range(len(transposed)):
 transposed[i] = [None]*len(transposed)

 for t in range(len(anArray)):
 for tt in range(len(anArray[t])): 
 transposed[t][tt] = anArray[tt][t]
 return transposed

theArray = [['a','b','c'],['d','e','f'],['g','h','i']]

print matrixTranspose(theArray)
</code></pre>

blocks|key|1009949|text|import++numpy+as+np+#Import+Numpy+

m=int(input("Enter+row"))+#Input+Number+of+row

n=int(input("Enter+column"))+#Input+number+of+column

a=[]+#Blank+Matrix

for+i+in+range(m):+#Row+Input

++++b=[]+#Blank+List

++++for+j+in+range(n):#column+Input

++++++++j=int(input("Enter+Number+in+Pocket+["%2Bstr(i)%2B"]["%2Bstr(j)%2B"]"))+#sow+Row+Column+Number+

++++++++b.append(j)+#addVlaue+to+list

++++a.append(b)#Add+List+To+Matrix

a=np.array(a)#convert+1matrix+as+Numpy

b=a.transpose()#transpose+Using+Numpy

print(a)+#Print+Matrix+

print(b)#print+Transpose+Matrix|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1009950|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>import numpy as np #Import Numpy 

m=int(input(&quot;Enter row&quot;)) #Input Number of row

n=int(input(&quot;Enter column&quot;)) #Input number of column

a=[] #Blank Matrix

for i in range(m): #Row Input

 b=[] #Blank List

 for j in range(n):#column Input

 j=int(input(&quot;Enter Number in Pocket [&quot;+str(i)+&quot;][&quot;+str(j)+&quot;]&quot;)) #sow Row Column Number 

 b.append(j) #addVlaue to list

 a.append(b)#Add List To Matrix

a=np.array(a)#convert 1matrix as Numpy

b=a.transpose()#transpose Using Numpy

print(a) #Print Matrix 

print(b)#print Transpose Matrix
</code></pre>

blocks|key|1009564|text|#generate+matrix
matrix=[]
m=input('enter+number+of+rows,+m+=+')
n=input('enter+number+of+columns,+n+=+')
for+i+in+range(m):
++++matrix.append([])
++++for+j+in+range(n):
++++++++elem=input('enter+element:+')
++++++++matrix[i].append(elem)

#print+matrix
for+i+in+range(m):
++++for+j+in+range(n):
++++++++print+matrix[i][j],
++++print+'\n'

#generate+transpose
transpose=[]
for+j+in+range(n):
++++transpose.append([])
++++for+i+in+range+(m):
++++++++ent=matrix[i][j]
++++++++transpose[j].append(ent)

#print+transpose
for+i+in+range+(n):
++++for+j+in+range+(m):
++++++++print+transpose[i][j],
++++print+'\n'|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1009565|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>#generate matrix
matrix=[]
m=input('enter number of rows, m = ')
n=input('enter number of columns, n = ')
for i in range(m):
 matrix.append([])
 for j in range(n):
 elem=input('enter element: ')
 matrix[i].append(elem)

#print matrix
for i in range(m):
 for j in range(n):
 print matrix[i][j],
 print '\n'

#generate transpose
transpose=[]
for j in range(n):
 transpose.append([])
 for i in range (m):
 ent=matrix[i][j]
 transpose[j].append(ent)

#print transpose
for i in range (n):
 for j in range (m):
 print transpose[i][j],
 print '\n'
</code></pre>

blocks|key|1009603|text|a=[]
def+showmatrix+(a,m,n):
++++for+i+in+range+(m):
++++++++for+j+in+range+(n):
++++++++++++k=int(input("enter+the+number")
++++++++++++a.append(k)++++++
print+(a[i][j]),

print('\t')


def+showtranspose(a,m,n):
++++for+j+in+range(n):
++++++++for+i+in+range(m):
++++++++++++print(a[i][j]),
++++++++print('\t')

a=((89,45,50),(130,120,40),(69,79,57),(78,4,8))
print("given+matrix+of+order+4x3+is+:")
showmatrix(a,4,3)


print("Transpose+matrix+is:")
showtranspose(a,4,3)|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1009604|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>a=[]
def showmatrix (a,m,n):
 for i in range (m):
 for j in range (n):
 k=int(input("enter the number")
 a.append(k) 
print (a[i][j]),

print('\t')


def showtranspose(a,m,n):
 for j in range(n):
 for i in range(m):
 print(a[i][j]),
 print('\t')

a=((89,45,50),(130,120,40),(69,79,57),(78,4,8))
print("given matrix of order 4x3 is :")
showmatrix(a,4,3)


print("Transpose matrix is:")
showtranspose(a,4,3)
</code></pre>

blocks|key|1009710|text|def+transpose(matrix):
+++x=0
+++trans=[]
+++b=len(matrix[0])
+++while+b!=0:
+++++++trans.append([])
+++++++b-=1
+++for+list+in+matrix:
+++++++for+element+in+list:
++++++++++trans[x].append(element)
++++++++++x%2B=1
+++++++x=0
+++return+trans|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1009711|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>def transpose(matrix):
 x=0
 trans=[]
 b=len(matrix[0])
 while b!=0:
 trans.append([])
 b-=1
 for list in matrix:
 for element in list:
 trans[x].append(element)
 x+=1
 x=0
 return trans
</code></pre>

blocks|key|1009728|text|def+transpose(matrix):
++++listOfLists+=+[]
++++for+row+in+range(len(matrix[0])):
++++++++colList+=+[]
++++++++for+col+in+range(len(matrix)):
++++++++++++colList.append(matrix[col][row])
++++listOfLists.append(colList)

++++return+listOfLists|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1009729|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>def transpose(matrix):
 listOfLists = []
 for row in range(len(matrix[0])):
 colList = []
 for col in range(len(matrix)):
 colList.append(matrix[col][row])
 listOfLists.append(colList)

 return listOfLists
</code></pre>

blocks|key|795245|text|`|type|unstyled|depth|inlineStyleRanges|entityRanges|data|795246|​|795247|def+transpose(m):
++++return(list(map(list,list(zip(*m)))))|code-block|syntax|javascript|795248|795249|`此函数将返回转置|795250|entityMap^0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|P|8|@]|9|@]|A|$G|H]]|$1|I|3|C|5|6|7|Q|8|@]|9|@]|A|$]]|$1|J|3|K|5|6|7|R|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|M|$]]

`

<div class="snippet" data-lang="js" data-hide="false" data-console="true" data-babel="false">
<div class="snippet-code">
<pre class="snippet-code-html lang-html prettyprint-override"><code>def transpose(m):
 return(list(map(list,list(zip(*m)))))</code></pre>
</div>
</div>


`This function will return the transpose

blocks|key|1009823|text|转置矩阵的Python程序：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1009824|row,col+=+map(int,input().split())
matrix+=+list()

for+i+in+range(row):
++++r+=+list(map(int,input().split()))
++++matrix.append(r)

trans+=+[[0+for+y+in+range(row)]for+x+in+range(col)]

for+i+in+range(len(matrix[0])):
++++for+j+in+range(len(matrix)):
++++++++trans[i][j]+=+matrix[j][i]+++++

for+i+in+range(len(trans)):
++++for+j+in+range(len(trans[0])):
++++++++print(trans[i][j],end='+')
++++print('+')|code-block|syntax|javascript|1009825|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|$]]

Python Program to transpose matrix:

<pre><code>row,col = map(int,input().split())
matrix = list()

for i in range(row):
 r = list(map(int,input().split()))
 matrix.append(r)

trans = [[0 for y in range(row)]for x in range(col)]

for i in range(len(matrix[0])):
 for j in range(len(matrix)):
 trans[i][j] = matrix[j][i] 

for i in range(len(trans)):
 for j in range(len(trans[0])):
 print(trans[i][j],end=' ')
 print(' ')
</code></pre>

I am trying to create a matrix transpose function for python but I can't seem to make it work.
Say I have 

<pre><code>theArray = [['a','b','c'],['d','e','f'],['g','h','i']]
</code></pre>

and I want my function to come up with

<pre><code>newArray = [['a','d','g'],['b','e','h'],['c', 'f', 'i']]
</code></pre>

So in other words, if I were to print this 2D array as columns and rows I would like the rows to turn into columns and columns into rows.

I made this so far but it doesn't work

<pre><code>def matrixTranspose(anArray):
 transposed = [None]*len(anArray[0])
 for t in range(len(anArray)):
 for tt in range(len(anArray[t])):
 transposed[t] = [None]*len(anArray)
 transposed[t][tt] = anArray[tt][t]
 print transposed
</code></pre>

Matrix Transpose in Python

Python

我正在尝试为python创建一个矩阵转置函数，但是我似乎不能让它工作。假设我有theArray = [['a','b','c'],['d','e','f'],['g','h','i']]我想让我的函数newArray = [['a','d','g'],['b','e','h'],['c', 'f', 'i']]换句话说，如果我把这个二维数组打印成列和行，我希望行变成列，列变成行。到目前为止，我做了

问Python中的矩阵转置
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