Question

我是python的新手（真的是任何类型的编码）。所以，如果有点混乱，我很抱歉

我有一个像以下

的csv文件

A    B     C              D        E            F         G      H
14  BP1 BP1-19119308    OR1A1   19119308    chip-chip   Hs578T  human   11/23/09 
15  BP1 BP1-19119308    PTPRE   19119308    chip-chip   Hs578T  human   11/23/09 
16  BP1 BP1-19119308    SELE    19119308    chip-chip   Hs578T  human   11/23/09 
17  BP1 BP1-19119308    TAC3    19119308    chip-chip   Hs578T  human   11/23/09 
18  BP1 BP1-19119308    VEGFA   19119308    chip-chip   Hs578T  human   11/23/09 
19  CHD7 CHD7-19251738  APOA1   19251738    chip-chip   MESC    mouse   11/23/09 
20  CHD7 CHD7-19251738  ARHGAP26 19251738   chip-chip   MESC    mouse  11/23/09

我需要让它看起来像这样

BP1-19119308-chip-chip-Hs578T-human OR1A1 PTPRE SELE TAC3 VEGFA 
CHD7-19251738-chip-chip-MESC-mouse  APOA1 ARHGAP26

我确实在第一栏中使用此

来管理C-F-G-H

import csv

out = open ('test.csv','rt', encoding='utf8') 
data =  csv.reader(out)
output = csv.writer(out) 

data = [row for row in data]
new_data = [[row[2]+'-'+row[5]+'-'+row[6] +'-'+ row[7], row[3]] for row in data] 

print (new_data)

out = open('new_data.csv','wt') 
output = csv.writer(out)  

for row in new_data:
   output.writerow(row)    

out.close()





A                                  B
BP1-19119308-chip-chip-Hs578T-human OR1A1
BP1-19119308-chip-chip-Hs578T-human PTPRE
BP1-19119308-chip-chip-Hs578T-human SELE
BP1-19119308-chip-chip-Hs578T-human TAC3
BP1-19119308-chip-chip-Hs578T-human VEGFA
CHD7-19251738-chip-chip-MESC-mouse  APOA1
CHD7-19251738-chip-chip-MESC-mouse  ARHGAP26
CHD7-19251738-chip-chip-MESC-mouse  ATP11A

但现在我在A中有这些副本，我不知道如何删除它们并转置B中分配给这些重复项的所有值。

我再次尝试循环以将当前值与之前的值进行比较，我只是搞砸了整个事情。

有什么建议吗？

Answer 1

您想使用字典。如果您正在进行进一步分析，请将聚合值保存在每个标识符的列表中。您的标识符字符串是一个键，在每个键下，您都有一个值列表。

new_keys = [row[2] + '-' + row[5] + '-' + row[6] + '-' + row[7] for row in data] 
new_values = [row[3] for row in data]

aggregate_values = {} # An empty dictionary
# Iterate across the paired lists together
for key, value in zip(new_keys, new_values): 
    if key not in aggregate_values:
        aggregate_values[key] = [value]
    else: 
        aggregate_values[key].append(value)

# printed output
for key in aggregate_values:
    print key + " " + " ".join(aggregate_values[key])

Answer 2

一种解决方案是在对数据进行分组时使用字典：

import csv

out = open ('test.csv','rt', encoding='utf8') 
data =  csv.reader(out)
output = csv.writer(out) 

data = [row for row in data]
new_data = [[row[2]+'-'+row[5]+'-'+row[6] +'-'+ row[7], row[3]] for row in data] 

my_dict = {}
for row in new_data:
   if row[0] in my_dict:
      my_dict[row[0]] += " " + row[1]
   else:
      my_dict[row[0]] = row[1]

new_data = [[my_key,my_dict[my_key]] for my_key in my_dict]

print (new_data)

out = open('new_data.csv','wt') 
output = csv.writer(out)  

for row in new_data:
   output.writerow(row)    

out.close()

Answer 3

从这里得到的明星：
test.txt

A                                   B
BP1-19119308-chip-chip-Hs578T-human OR1A1
BP1-19119308-chip-chip-Hs578T-human PTPRE
BP1-19119308-chip-chip-Hs578T-human SELE
BP1-19119308-chip-chip-Hs578T-human TAC3
BP1-19119308-chip-chip-Hs578T-human VEGFA
CHD7-19251738-chip-chip-MESC-mouse  APOA1
CHD7-19251738-chip-chip-MESC-mouse  ARHGAP26
CHD7-19251738-chip-chip-MESC-mouse  ATP11A

现在，您可以使用以下代码来创建所需的形状：

with open("test.txt") as f:
    data = f.readlines()[1:]
mydata = [x.strip() for x in data]

final = {}

for x in mydata:
    k, v = x.split()
    if final.has_key(k):
        l = final[k]
        l.append(v)
    else:
        final[k] = [v]

for d in final:
    print d, " ".join(final[d])

输出：

CHD7-19251738-chip-chip-MESC-mouse APOA1 ARHGAP26 ATP11A
BP1-19119308-chip-chip-Hs578T-human OR1A1 PTPRE SELE TAC3 VEGFA

如果需要，可以在此处将其写入文件。

Answer 4

使用itertools.groupby和operator.itemgetter。在初始化new_data和output：

后，将其添加到您的代码中

for k, g in itertools.groupby(new_data, operator.itemgetter(0)):
    row = [k]
    row.extend(map(g, operator.itemgetter(1)))
    output.writerow(row)

完整的改进的（重构）代码可能如下所示：

import csv
import itertools
import operator

with open('test.csv','rt', encoding='utf8') as f_in:
    inp = csv.reader(f_in)
    new_data = (('-'.join(operator.itemgetter(2, 5, 6, 7)), row[3])
                for row in inp)
    with open('new_data.csv','wt') as f_out:
        output = csv.writer(f_out)
        for k, g in itertools.groupby(new_data, operator.itemgetter(0)):
                row = [k]
                row.extend(map(g, operator.itemgetter(1)))
                output.writerow(row)

迭代并丢弃顺序重复项

4 个答案: