Question

我有两个csv文件： csv文件1包含以下内容：

California,C1,G1,K1,Dine-In,B,25
California,C2,G2,K1,Dine-In,A,8
Hawaii,H1,J1,L1,Dine-In,A,22
Hawaii,H2,J2,L2,Dine-In,A,20

csv文件2包含：

Hawaii,10
California,20

我希望我的输出为：

California,C1,G1,K1,Dine-In,B,25,20
California,C2,G2,K1,Dine-In,A,8,20
Hawaii,H1,J1,L1,Dine-In,A,22,10
Hawaii,H2,J2,L2,Dine-In,A,20,10

我完成了我的代码：

with open(r'file 1.csv', 'r') as f:
    r = csv.reader(f)
    dict2 = {row[0]: row[1:] for row in r}

with open(r'file 2.csv','r') as f:
    r = csv.reader(f)
    dict1 = OrderedDict((row[0], row[1:]) for row in r)

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

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

但它给了我一个输出：

California,C1,G1,K1,Dine-In,B,25
California,C2,G2,K1,Dine-In,A,8
Hawaii,H1,J1,L1,Dine-In,A,22
Hawaii,H2,J2,L2,Dine-In,A,20
Hawaii,10
California,20

对此有什么想法？

Answer 1

您只需要将file 2.csv作为字典加载，然后在阅读file 1.csv时将其附加到每一行，如下所示：

import csv

with open(r'file 2.csv','rb') as f_file2:
    dict2 = {row[0]: row[1:] for row in csv.reader(f_file2)}

with open(r'file 1.csv', 'rb') as f_file1, open('combined data.csv', 'wb') as f_output:
    csv_output = csv.writer(f_output)

    for row in csv.reader(f_file1):
        csv_output.writerow(row + dict2[row[0]])

给你：

California,C1,G1,K1,Dine-In,B,25,20
California,C2,G2,K1,Dine-In,A,8,20
Hawaii,H1,J1,L1,Dine-In,A,22,10
Hawaii,H2,J2,L2,Dine-In,A,20,10

Answer 2

A pandas解决方案

import pandas pd

df1 = pd.read_csv('file1.csv', header=None)
df2 = pd.read_csv('file2.csv', header=None)
res = pd.merge(df1, df2, on=0)
res.to_csv('combined.csv', header=None, index=False)

combined.csv：

California,C1,G1,K1,Dine-In,B,25,20
California,C2,G2,K1,Dine-In,A,8,20
Hawaii,H1,J1,L1,Dine-In,A,22,10
Hawaii,H2,J2,L2,Dine-In,A,20,10

步骤

将第一个文件读入数据框：

df1 = pd.read_csv('file1.csv', header=None)

看起来像这样：

            0   1   2   3        4  5   6
0  California  C1  G1  K1  Dine-In  B  25
1  California  C2  G2  K1  Dine-In  A   8
2      Hawaii  H1  J1  L1  Dine-In  A  22
3      Hawaii  H2  J2  L2  Dine-In  A  20

对第二个文件执行相同的操作：

df2 = pd.read_csv('file2.csv', header=None)

结果：

            0   1
0      Hawaii  10
1  California  20

合并到0列：

res = pd.merge(df1, df2, on=0)

现在，res看起来像这样：

            0 1_x   2   3        4  5   6  1_y
0  California  C1  G1  K1  Dine-In  B  25   20
1  California  C2  G2  K1  Dine-In  A   8   20
2      Hawaii  H1  J1  L1  Dine-In  A  22   10
3      Hawaii  H2  J2  L2  Dine-In  A  20   10

最后，写入没有标题和索引的csv文件：

res.to_csv('combined.csv', header=None, index=False)

合并两个具有公共列但长度不均匀的csv文件

2 个答案:

A pandas解决方案

步骤