连接Python中具有相同第一列值的CSV文件的所有行

Question

I have a CSV file that goes something like this:

['Name1', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '+']
['Name1', '', '', '', '', '', 'b', '', '', '', '', '', '', '', '', '', '', '', '', '', '']
['Name2', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 'a', '']
['Name3', '', '', '', '', '+', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']

Now, I need a way to join all of the rows that have the same 1st column name into one column, for instance:

['Name1', '', '', '', '', '', 'b', '', '', '', '', '', '', '', '', '', '', '', '', '', '+']
['Name2', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 'a', '']
['Name3', '', '', '', '', '+', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']

I can think of a way to do this by sorting the CSV and then going trough each row and column and compare each value, but there should probably be an easier way to do it.

Any ideas?

Answer 1

You should use itertools.groupby:

t = [ 
['Name1', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '+'],
['Name1', '', '', '', '', '', 'b', '', '', '', '', '', '', '', '', '', '', '', '', '', ''],
['Name2', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 'a', ''],
['Name3', '', '', '', '', '+', '', '', '', '', '', '', '', '', '', '', '', '', '', '', ''] 
]

from itertools import groupby

# TODO: if you need to speed things up you can use operator.itemgetter
# for both sorting and grouping
for name, rows in groupby(sorted(t), lambda x:x[0]):
    print join_rows(rows)

It's obvious that you'd implement the merging in a separate function. For example like this:

def join_rows(rows):
    def join_tuple(tup):
        for x in tup:
            if x: 
                return x
        else:
            return ''
    return [join_tuple(x) for x in zip(*rows)]

Answer 2

def merge_rows(row1, row2):
    # merge two rows with the same name
    merged_row = ...
    return merged_row

r1 = ['Name1', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '+']
r2 = ['Name1', '', '', '', '', '', 'b', '', '', '', '', '', '', '', '', '', '', '', '', '', '']
r3 = ['Name2', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 'a', '']
r4 = ['Name3', '', '', '', '', '+', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']
rows = [r1, r2, r3, r4]
data = {}
for row in rows:
    name = row[0]
    if name in data:
        data[name] = merge_rows(row, data[name])
    else:
        data[name] = row

You now have all the rows in data where each key of this dictionary is the name and the corresponding value is that row. You can now write this data to a CSV file.

Answer 3

You can also use defaultdict :

>>> from collections import defaultdict
>>> d = defaultdict(list)
>>> _ = [d[i[0]].append(z) for i in t for z in i[1:]]
>>> d['Name1']
['', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '+', '', '', '', '', '', 'b', '', '', '', '', '', '', '', '', '', '', '', '', '', '']

Then do your column joining