如何根据字段合并两个CSV文件并保持每条记录的属性数量相同？

Question

我正在尝试根据每个文件中的特定字段合并两个CSV文件。

file1.csv

id,attr1,attr2,attr3
1,True,7,"Purple"
2,False,19.8,"Cucumber"
3,False,-0.5,"A string with a comma, because it has one"
4,True,2,"Nope"
5,True,4.0,"Tuesday"
6,False,1,"Failure"

file2.csv

id,attr4,attr5,attr6
2,"python",500000.12,False
5,"program",3,True
3,"Another string",-5,False

这是我正在使用的代码：

import csv
from collections import OrderedDict

with open('file2.csv','r') as f2:
    reader = csv.reader(f2)
    fields2 = next(reader,None) # Skip headers
    dict2 = {row[0]: row[1:] for row in reader}

with open('file1.csv','r') as f1:
    reader = csv.reader(f1)
    fields1 = next(reader,None) # Skip headers
    dict1 = OrderedDict((row[0], row[1:]) for row in reader)

result = OrderedDict()
for d in (dict1, dict2):
    for key, value in d.iteritems():
        result.setdefault(key, []).extend(value)

with open('merged.csv', 'wb') as f:
    w = csv.writer(f)
    for key, value in result.iteritems():
        w.writerow([key] + value)

我得到的输出是这样的，合并得不错，但并不是所有行的属性数量都一样：

1,True,7,Purple
2,False,19.8,Cucumber,python,500000.12,False
3,False,-0.5,"A string with a comma, because it has one",Another string,-5,False
4,True,2,Nope
5,True,4.0,Tuesday,program,3,True
6,False,1,Failure

file2中不会有每个file1中的id的记录。我希望输出的合并文件中，file2的空字段也能显示出来。例如，id为1的记录应该是这样的：

1,True,7,Purple,,,

我该如何为那些在file2中没有数据的记录添加空字段，以确保合并后的CSV中所有记录的属性数量都是一样的呢？

Answer 1

使用字典中的字典，然后更新它。可以这样做：

import csv
from collections import OrderedDict

with open('file2.csv','r') as f2:
    reader = csv.reader(f2)
    lines2 = list(reader)

with open('file1.csv','r') as f1:
    reader = csv.reader(f1)
    lines1 = list(reader)

dict1 = {row[0]: dict(zip(lines1[0][1:], row[1:])) for row in lines1[1:]}
dict2 = {row[0]: dict(zip(lines2[0][1:], row[1:])) for row in lines2[1:]}

#merge
updatedDict = OrderedDict()
mergedAttrs = OrderedDict.fromkeys(lines1[0][1:] + lines2[0][1:], "?")
for id, attrs in dict1.iteritems():
    d = mergedAttrs.copy()
    d.update(attrs)
    updatedDict[id] = d

for id, attrs in dict2.iteritems():
    updatedDict[id].update(attrs)

#out
with open('merged.csv', 'wb') as f:
    w = csv.writer(f)
    for id, rest in sorted(updatedDict.iteritems()):
        w.writerow([id] + rest.values())

Answer 2

你可以使用pandas来完成这个任务：

import pandas

csv1 = pandas.read_csv('filea1.csv')
csv2 = pandas.read_csv('file2.csv')
merged = csv1.merge(csv2, on='id')
merged.to_csv("output.csv", index=False)

我还没有测试过这个代码，但它应该能让你朝着正确的方向前进，等我有机会试一下再说。这个代码其实很简单明了；首先，你需要导入pandas库，这样你才能使用它。接着，使用pandas.read_csv来读取两个csv文件，然后用merge方法将它们合并在一起。on参数指定了哪个列作为“关键字”。最后，合并后的csv文件会被写入到output.csv中。

Answer 3

如果我们不使用 pandas 这个库，我会把代码改成下面这样：

import csv
from collections import OrderedDict

filenames = "file1.csv", "file2.csv"
data = OrderedDict()
fieldnames = []
for filename in filenames:
    with open(filename, "rb") as fp: # python 2
        reader = csv.DictReader(fp)
        fieldnames.extend(reader.fieldnames)
        for row in reader:
            data.setdefault(row["id"], {}).update(row)

fieldnames = list(OrderedDict.fromkeys(fieldnames))
with open("merged.csv", "wb") as fp:
    writer = csv.writer(fp)
    writer.writerow(fieldnames)
    for row in data.itervalues():
        writer.writerow([row.get(field, '') for field in fieldnames])

这样做会得到：

id,attr1,attr2,attr3,attr4,attr5,attr6
1,True,7,Purple,,,
2,False,19.8,Cucumber,python,500000.12,False
3,False,-0.5,"A string with a comma, because it has one",Another string,-5,False
4,True,2,Nope,,,
5,True,4.0,Tuesday,program,3,True
6,False,1,Failure,,,

为了对比，使用 pandas 的话，代码大概是这样的：

df1 = pd.read_csv("file1.csv")
df2 = pd.read_csv("file2.csv")
merged = df1.merge(df2, on="id", how="outer").fillna("")
merged.to_csv("merged.csv", index=False)

在我看来，这样的写法简单多了，这样你就可以花更多时间处理数据，而不是花时间去重复造轮子。