[英]Python group values in 2d list from CSV
I have the following CSV 我有以下CSV
BBCP1,Grey,2140,805EC0FFFFE2,0000000066
BBCP1,Test,2150,805EC0FFFFE2,0000000066
BBCP1,Test,2151,805EC0FFFFE1,0000000066
BBCP1,Centre,2141,805EC0FFFFE3,000000077
BBCP1,Yellow,2142,805EC0FFFFE3,000000077
BBCP1,Purple,2143,805EC0FFFFE3,000000077
BBCP1,Green,2144,805EC0FFFFE3,000000077
BBCP1,Pink,2145,805EC0FFFFE3,000000077
I'm reading this data in using 我正在使用读取数据
data = list(csv.reader(open(csvFile)))
I want to turn this data into a 2d array or equivilent and group by the value in the 4th column (the MAC address), preserving the order they were in in the original list. 我想将此数据转换为2d数组或等效数组,并按第4列 (MAC地址)中的值进行分组 ,并保留它们在原始列表中的顺序 。 So it would look like
所以看起来像
[(BBCP1,Grey,2140,805EC0FFFFE2,0000000066),(BBCP1,Test,2150,805EC0FFFFE2,0000000066)],
[(BBCP1,Test,2151,805EC0FFFFE1,0000000066)],
[(BBCP1,Centre,2141,805EC0FFFFE3,000000077),
(BBCP1,Yellow,2142,805EC0FFFFE3,000000077),
(BBCP1,Purple,2143,805EC0FFFFE3,000000077),
(BBCP1,Green,2144,805EC0FFFFE3,000000077),
(BBCP1,Pink,2145,805EC0FFFFE3,000000077)]
Hopefully i've displayed the array correctly and it makes sense. 希望我已经正确显示了数组,这很有意义。
I then need to loop the arrays to output the data to file. 然后,我需要循环数组以将数据输出到文件。 Which i'm pretty sure i'm ok with a nested for loop.
我很确定我可以使用嵌套的for循环。
Thanks in advance for any help 预先感谢您的任何帮助
use defaultdict
to group the data ( groupby
would require sorting and would be unefficient / would kill the order), then print the sorted dictionary values (sorting isn't really necessary, it's just to stabilize the output): 使用
defaultdict
对数据进行分组( groupby
将需要排序,并且效率不高/会杀死订单),然后打印已排序的字典值(排序不是真正必要的,只是为了稳定输出):
import csv,collections
d = collections.defaultdict(list)
for row in csv.reader(txt):
mac_address = row[3]
d[mac_address].append(row)
print(sorted(d.values()))
resulting in: 导致:
[[['BBCP1', 'Centre', '2141', '805EC0FFFFE3', '000000077'],
['BBCP1', 'Yellow', '2142', '805EC0FFFFE3', '000000077'],
['BBCP1', 'Purple', '2143', '805EC0FFFFE3', '000000077'],
['BBCP1', 'Green', '2144', '805EC0FFFFE3', '000000077'],
['BBCP1', 'Pink', '2145', '805EC0FFFFE3', '000000077']],
[['BBCP1', 'Grey', '2140', '805EC0FFFFE2', '0000000066'],
['BBCP1', 'Test', '2150', '805EC0FFFFE2', '0000000066']],
[['BBCP1', 'Test', '2151', '805EC0FFFFE1', '0000000066']]]
sorting according to key (the mac address): 根据密钥(mac地址)排序:
values = [v for _,v in sorted(d.items())]
yields: 收益率:
[[['BBCP1', 'Test', '2151', '805EC0FFFFE1', '0000000066']],
[['BBCP1', 'Grey', '2140', '805EC0FFFFE2', '0000000066'],
['BBCP1', 'Test', '2150', '805EC0FFFFE2', '0000000066']],
[['BBCP1', 'Centre', '2141', '805EC0FFFFE3', '000000077'],
['BBCP1', 'Yellow', '2142', '805EC0FFFFE3', '000000077'],
['BBCP1', 'Purple', '2143', '805EC0FFFFE3', '000000077'],
['BBCP1', 'Green', '2144', '805EC0FFFFE3', '000000077'],
['BBCP1', 'Pink', '2145', '805EC0FFFFE3', '000000077']]]
hi i used pandas
and groupby
to solve the problem. 嗨,我用
pandas
和groupby
来解决这个问题。 Hope this helps!! 希望这可以帮助!!
data = pd.read_csv('data.txt', header=None)
data.columns = ['A','B','C','D','E'] # random names to the column
def check(data):
data_item = []
for index,item in data.iterrows():
data_item.append(item.tolist()))
return data_item
grouped_data = data.groupby('D',sort=False).apply(check)
for data in grouped_data:
print(data)
Output #preserving the order 输出#保留订单
[['BBCP1', 'Grey', 2140, '805EC0FFFFE2', 66], ['BBCP1', 'Test', 2150, '805EC0FFFFE2', 66]]
[['BBCP1', 'Test', 2151, '805EC0FFFFE1', 66]]
[['BBCP1', 'Centre', 2141, '805EC0FFFFE3', 77], ['BBCP1', 'Yellow', 2142, '805EC0FFFFE3', 77], ['BBCP1', 'Purple', 2143, '805EC0FFFFE3', 77], ['BBCP1', 'Green', 2144, '805EC0FFFFE3', 77], ['BBCP1', 'Pink', 2145, '805EC0FFFFE3', 77]]
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