在Python中:创建一个表来可视化成对数据
在Python中:创建一个表来可视化成对数据
提问于 2012-12-12 09:33:51
我执行了一系列成对比较(准确地说是241x241)。
生成的文件如下所示：
A,X,10
A,Y,20
X,Y,15我想把它转换成一个表格，显示所有的成对比较。也就是说，像这样的东西
,A,X,Y
A,,10,20
X,10,,15
Y,20,15,,我甚至不知道如何开始解决这个问题。任何帮助，建议都将不胜感激！
回答 2
Stack Overflow用户
回答已采纳
发布于 2012-12-12 09:51:22
将配对数据存储到字典中：
result_dict = {
(A, X): 10,
(A, Y): 20,
(X, Y): 15,
}和行/列标签：
cols = sorted(set(a for a, b in result_dict.iterkeys()))
rows = sorted(set(b for a, b in result_dict.iterkeys()))然后就是如何打印行了.
for b in rows:
row = list(result_dict.get((a, b), None) for a in cols)
# print the rowStack Overflow用户
发布于 2012-12-12 09:51:33
我有一种感觉，有更有效的方法，但你可以尝试一下这样的东西。它使用csv模块来加载/解析您的数据，然后也将其写回csv (假设您希望将输出放在一个文件中，也就是说，如果不是这样，可以对其进行调整)：
import csv
from collections import defaultdict
# Open the input file and read it all into a defaultdict
with open('table.csv', 'rb') as f:
reader = csv.reader(f)
# Dictionary to hold the nested values
# This will be keyed by the letter ID, and each line of
# the file will be written twice (so A,X,10 will be represented
# as {'A': {'X': 10}, 'X': {'A': 10}}
d = defaultdict(dict)
for row in reader:
d[row[0]][row[1]] = row[2]
d[row[1]][row[0]] = row[2]
# Now we open the output file and write out our defaultdict
with open('t_out.csv', 'wb') as o:
# Here our fieldnames will start with the 'empty' first header
# and then be comprised of the keys of the dictionary (which
# should contain all possible values for the table)
fieldnames = [' '] + d.keys()
writer = csv.DictWriter(o, fieldnames=fieldnames)
# In Python 2.7, you can use writer.writeheaders()
writer.writerow(dict((h, h) for h in fieldnames))
# Now iterate through our dictionary, creating a row
# dictionary that will contain the information to be written
for k, v in d.iteritems():
# Here we are putting the key in the 'empty' first column
v[' '] = k
writer.writerow(v)页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/13831400
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