比较2个列表并返回不匹配项

Question

我正在努力处理我导入的2个csv文件

csv文件如下所示：

csv1

planet,diameter,discovered,color
sceptri,33.41685587,28-11-1611 05:15, black
...

csv2

planet,diameter,discovered,color
sceptri,33.41685587,28-11-1611 05:15, blue
...

在两个csv文件中，存在相同的行星，但顺序不同，有时具有不同的值（不匹配）

每个行星的数据（直径、发现和颜色）都是独立输入的。我想交叉检查这两张表，找出所有不匹配的字段。然后我想生成一个新文件，每个错误包含一行错误描述

例如： 权杖：不匹配（黑色/蓝色）

这是到目前为止我的代码

with open('planets1.csv') as csvfile:
    a = csv.reader(csvfile, delimiter=',')
    data_a= list(a)
    for row in a:
        print(row)

with open('planets2.csv') as csvfile:
    b = csv.reader(csvfile, delimiter=',')
    data_b= list(b)
    for row in b:
        print(row)

print(data_a)
print(data_b)

c= [data_a]
d= [data_b]```


thank you in advance for your help!

Answer 1

通过对csv文件中的行进行排序，然后比较相应的行以查看是否存在差异，可以解决此类问题

此方法使用函数样式执行比较，并将比较任意数量的csv文件

它假定CSV包含相同数量的记录，并且列的顺序相同

import contextlib
import csv


def compare_files(readers):
    colnames = [next(reader) for reader in readers][0]
    sorted_readers = [sorted(r) for r in readers]
    for gen in [compare_rows(colnames, rows) for rows in zip(*sorted_readers)]:
        yield from gen


def compare_rows(colnames, rows):
    col_iter = zip(*rows)
    # Be sure we're comparing the same planets.
    planets = set(next(col_iter))
    assert len(planets) == 1, planets
    planet = planets.pop()
    for (colname, *vals) in zip(colnames, col_iter):
        if len(set(*vals)) > 1:
            yield f"{planet} mismatch {colname} ({'/'.join(*vals)})"


def main(outfile, *infiles):
    with contextlib.ExitStack() as stack:
        csvs = [stack.enter_context(open(fname)) for fname in infiles]
        readers = [csv.reader(f) for f in csvs]
        with open(outfile, 'w') as out:
            for result in compare_files(readers):
                out.write(result + '\n')


if __name__ == "__main__":
    main('mismatches.txt', 'planets1.csv', 'planets2.csv')

Answer 2

假设两个文件中的行星名称都正确，下面是我的建议

# Working with list of list, which could be get csv file reading:
csv1 = [["sceptri",33.41685587,"28-11-1611 05:15", "black"],
        ["foo",35.41685587,"29-11-1611 05:15", "black"],
        ["bar",38.7,"29-11-1611 05:15", "black"],]
csv2 = [["foo",35.41685587,"29-11-1611 05:15", "black"],
        ["bar",38.17,"29-11-1611 05:15", "black"],
        ["sceptri",33.41685587,"28-11-1611 05:15", "blue"]]

# A list to contain the errors:
new_file = []
# A dict to check if a planet has already been processed:
a_dict ={}
# Let's read all planet data:
for planet in csv1+csv2:
    # Check if planet is already as a key in a_dict:
    if planet[0] in a_dict:
        # Yes, sir, need to check discrepancies.
        if a_dict[planet[0]] != planet[1:]:
            # we have some differences in some values.
            # Put both set of values in python sets to differences:
            error = set(planet[1:]) ^ set(a_dict[planet[0]])
            # Append [planet_name, diff.param1, diff_param2] to new_file:
            new_file.append([planet[0]]+list(error))
    else:
        # the planet name becomes a dict key, other param are key value:
        a_dict[planet[0]] = planet[1:]

print(new_file)
# [['bar', 38.17, 38.7], ['sceptri', 'black', 'blue']]

列表new_file可以另存为新文件，请参见Writing a list to file

Answer 3

我建议用熊猫来完成这样的任务

首先，您需要将csv内容读入dataframe对象。这可以通过以下方式完成：

import pandas as pd

# make a dataframe from each csv file
df1 = pd.read_csv('planets1.csv')
df2 = pd.read_csv('planets2.csv')

如果CSV文件中没有每列的名称，则可能需要为每列声明名称

colnames = ['col1', 'col2', ..., 'coln']

df1 = pd.read_csv('planets1.csv', names=colnames, index_col=0) 
df2 = pd.read_csv('planets2.csv', names=colnames, index_col=0) 
# use index_col=0 if csv already has an index column

---

为了代码的可复制性，我将在下面定义没有csv的dataframe对象：

import pandas as pd

# example column names
colnames = ['A','B','C']

# example dataframes
df1 = pd.DataFrame([[0,3,6], [4,5,6], [3,2,5]], columns=colnames)
df2 = pd.DataFrame([[1,3,1], [4,3,6], [3,6,5]], columns=colnames)

请注意，df1如下所示：

    A   B   C
       -
0   0   3   6
1   4   5   6
2   3   2   5

df2看起来是这样的：

    A   B   C
       -
0   1   3   1
1   4   3   6
2   3   6   5

以下代码比较数据帧，将比较连接到新数据帧，然后将结果保存到CSV：

# define the condition you want to check for (i.e., mismatches)
mask = (df1 != df2)

# df1[mask], df2[mask] will replace matched values with NaN (Not a Number), and leave mismatches
# dropna(how='all') will remove rows filled entirely with NaNs
errors_1 = df1[mask].dropna(how='all')
errors_2 = df2[mask].dropna(how='all')

# add labels to column names
errors_1.columns += '_1' # for planets 1
errors_2.columns += '_2' # for planets 2

# you can now combine horizontally into one big dataframe
errors = pd.concat([errors_1,errors_2],axis=1)

# if you want, reorder the columns of `errors` so compared columns are next to each other
errors = errors.reindex(sorted(errors.columns), axis=1)

# if you don't like the clutter of NaN values, you can replace them with fillna()
errors = errors.fillna('_')

# save to a csv
errors.to_csv('mismatches.csv')

最终结果如下所示：

    A_1 A_2 B_1 B_2 C_1 C_2
              -
0   0   1   _   _   6   1
1   _   _   5   3   _   _
2   _   _   2   6   _   _

希望这有帮助