python - 从相应的行 CSV Python 中获取值

Question

我有多个这样的 csv 文件:

csv1:

h1,h2,h3
aa,34,bd9
bb,459,jg0

csv2:

h1,h5,h2
aa,rg,87
aa,gru,90
bb,sf,459

对于标题为 h1 的第 0 列中的每个值，我想从文件夹中的所有 csv 文件中获取其对应的 h2 值。示例输出可以是

csv1: (aa,34),(bb,459)
csv2: (aa,87,90),(bb,459)

我对如何着手做这件事有点无能为力。

PS- 我不想使用 Pandas 。

PPS- 我可以通过对第 0 列的值进行硬编码来做到这一点，但我不想那样做，因为有数百行。

这是我试过的一小段代码。它在不同的行中打印 'aa' 的 h2 值。我希望它们打印在同一行。

import csv
with open("test1/sample.csv") as csvfile:
     reader = csv.DictReader(csvfile,  delimiter = ",")
     for row in reader:
         print(row['h1'], row['h2'])

Answer 1

import glob
import csv
import os
from collections import defaultdict
d = defaultdict(list)
path = "path_to_folder"
for fle in (glob.glob("*.csv")):
    with open(os.path.join(path,fle)) as f:
        header = next(f).rstrip().split(",")
        # if either does not appear in header the value will be None
        h1 = next((i for i, x in enumerate(header) if x == "h1"),None)
        h2 = next((i for i, x in enumerate(header) if x == "h2"),None)
        # make sure we have both columns before going further
        if h1 is not None and h2 is not None:
            r = csv.reader(f,delimiter=",")
            # save file name as key appending each h1 and h2 value
            for row in r:
                d[fle].append([row[h1],row[h2]])
print(d)

defaultdict(<class 'list'>, {'csv1.csv': [['aa', '34'], ['bb', '459']], 'csv2.csv': [['aa', '87'], ['aa', '90'], ['bb', '459']]})

这是一个快速草稿，它假设所有文件都由 , 分隔，并且所有 h1 和 h2 列都有值，如果是这样，它将找到所有保持顺序的配对。

要获得一组唯一值，我们可以使用 set 和 set.update:

d = defaultdict(set) # change to set

for fle in (glob.glob("*.csv")):
    with open(os.path.join(path,fle)) as f:
        header = next(f).rstrip().split(",")
        h1 = next((i for i, x in enumerate(header) if x == "h1"),None)
        h2 = next((i for i, x in enumerate(header) if x == "h2"),None)
        if h1 is not None and h2 is not None:
            r = csv.reader(f,delimiter=",")
            for row in r:
                d[fle].update([row[h1],row[h2]) # set.update

print(d)
defaultdict(<class 'set'>, {'csv1.csv': {'459', '34', 'bb', 'aa'}, 'csv2.csv': {'459', '90', '87', 'bb', 'aa'}})

如果您确定始终有 h1 和 h2，则可以将代码简化为:

d = defaultdict(set)
path = "path/"
for fle in (glob.glob("*.csv")):
    with open(os.path.join(path, fle)) as f:
        r = csv.reader(f,delimiter=",")
        header = next(r)
        h1 = header.index("h1")
        h2 = header.index("h2")
        for row in r:
            d[fle].update([row[h1], row[h2]])

最后，如果您想保持找到的元素的顺序，我们不能使用集合，因为它们是无序的，所以我们需要检查列表中是否已经存在任何一个元素:

for fle in (glob.glob("*.csv")):
    with open(os.path.join(path, fle)) as f:
        r = csv.reader(f,delimiter=",")
        header = next(r)
        h1 = header.index("h1")
        h2 = header.index("h2")
        for row in r:
            h_1, h_2 = row[h1], row[h2]
            if h_1 not in d[fle]:
                d[fle].append(h_1)
            if h_2 not in d[fle]:
                d[fle].append(h_2)
print(d)
defaultdict(<class 'list'>, {'csv2.csv': ['aa', '87', '90', 'bb', '459'], 'csv1.csv': ['aa', '34', 'bb', '459']})