[英]Having trouble with lists and matrix using xlrd and python
So my problem is to take a couple of long vectors (each being 15000 rows long) with the appearence: 所以我的问题是采用几个长矢量(每个长15000行)并出现:
Origin Destination Distance
and the corresponding values in the columns. 以及列中的相应值。 I want however to convert these, using Python and the xlrd package, into a distance matrix having
但是我想使用Python和xlrd包将这些转换为具有
Destination1 Destination2
Origin1 Distance11 Distance12
Origin2 Distance21 Distance22
and so forth. 等等。
What I have tried thus far is: 到目前为止,我尝试过的是:
matrix ={}, i=0, list3 = [], list1 = []
for row in range(orksheet.nrows):
matrix[i] = {}
cell = worksheet.cell(row,2)
distance = cell.value
if float(distance) < 25000:
list1 = [int(worksheet.cell_value(row,0))]
list3 = list3.append(list1)
list2 = [int(worksheet.cell_value(row,1))]
for l in list1:
for j in list2:
matrix[l, j]=math.ceil(worksheet.cell_value(row,2))
i+=1
This works somewhat. 这有点奏效。 When I use print(l,j,matrix[l,j]
当我使用print(l,j,matrix [l,j]
within the loop over l and j I get what I get the desired values. 在l和j的循环中,我得到了所需的值。 However, using print(matrix) gives the (general, ie the output like that but with the corresponding values instead) output:
但是,使用print(matrix)会给出(常规,即类似的输出,但具有相应的值)输出:
(Origin, Destination): Distance and sometimes: distance: {}, distance: {},
and so on. 等等。
What I've perceived is the problem is with the matrix. 我已经意识到问题出在矩阵上。 I cannot understand why it prints like that which I believe has something to do with the lists?
我不明白为什么打印出来的照片与我认为与列表有关? The list1 and list2 has len 1 which seems odd to me.
list1和list2有len 1,这对我来说似乎很奇怪。 I've tried to use list3 to append list1 but it also get len 1.
我尝试使用list3追加list1,但它也得到len 1。
Regards, 问候,
I could not recommend pandas more for data-manipulation tasks. 对于数据处理任务,我不能推荐更多熊猫 。
For example, the operation you seek in pandas is called pivot : 例如,您在大熊猫中寻求的操作称为ivot :
In [11]: df = pd.DataFrame({'origin': list('aabbccdd'), 'destination': ['d1', 'd2'] * 4, 'distance': np.arange(8)})
In [12]: df
Out[12]:
destination distance origin
0 d1 0 a
1 d2 1 a
2 d1 2 b
3 d2 3 b
4 d1 4 c
5 d2 5 c
6 d1 6 d
7 d2 7 d
In [13]: df.pivot('origin', 'destination', 'distance')
Out[13]:
destination d1 d2
origin
a 0 1
b 2 3
c 4 5
d 6 7
And to read actual excel file there's pandas.read_excel which AFAIR uses xlrd under the hood: 要读取实际的excel文件,有pandas.read_excel ,AFAIR在后台使用xlrd:
df = read_excel('path_to_file.xls', 'Sheet1', index_col=None, na_values=['NA'])
And there's a lot more to find in the documentation 在文档中还有更多内容可以找到
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