CSV 分组 w/o Pandas

Question

我想将数据分组到 .csv 文件中。我的数据如下：

code,balance
CN,999.99
CN,1.01
LS,177.77
LS,69.42
LA,200.43
WO,100

我想按代码对项目进行分组，然后将类似代码的余额相加。期望的输出将是：

code,blance
CN,1001
LS,247.19
...

我最初使用 Pandas 来完成这项任务，但没有可用的包来将该库放在服务器上。

mydata = pd.read_csv('./tmp/temp.csv')
out = mydata.groupby('code').sum()

解决方案最好与 Python 2.6 兼容。如果这是重复的，我很抱歉，其他帖子的分组方式似乎不同。

我也想避免在 -

中这样做

if code = x
    add balance to x_total

-种方式

我的解决方案：

def groupit():
    groups = defaultdict(list)
    with open('tmp.csv') as fd:
        reader = csv.DictReader(fd)
        for row in reader:
            groups[row['code']].append(float(row['balance.']))
    total={key:sum(groups[key]) for key in groups}
    total=str(total)
    total=total.replace(' ','')
    total=total.replace('{','')
    total=total.replace('}','')
    total=total.replace("'",'')
    total=total.replace(',','\n')
    total=total.replace(':',',')

    outfile = open('out.csv','w+')
    outfile.write('code,balance\n')
    outfile.write(total)

Answer 1

以下是我的处理方式：

with open("data.csv", 'r') as f:
data = f.readlines()

result = {}
for val in range(1, len(data)-1):
    x = data[val].split(",")
    if x[0] not in result:
        result[x[0]] = float(x[1].replace('\n', ""))
    else:
        result[x[0]] = result[x[0]] + float(x[1].replace('\n', ""))

result 字典将包含感兴趣的值，然后可以将其保存为 csv。

import csv

with open('mycsvfile.csv', 'wb') as f:  # Just use 'w' mode in 3.x
    w = csv.DictWriter(f, result.keys())
    w.writeheader()
    w.writerow(result)

希望这对您有所帮助:)

Answer 2

Python > 2.6:

from collections import defaultdict
import csv

groups = defaultdict(list)
with open('text.txt') as fd:
    reader = csv.DictReader(fd)
    for row in reader:
        groups[row['code']].append(float(row['balance']))

totals = {key: sum(groups[key]) for key in groups}
print(totals)

这输出：

{'CN': 1001.0, 'LS': 247.19, 'LA': 200.43, 'WO': 100.0}

Python = 2.6:

from collections import defaultdict
import csv

groups = defaultdict(list)
with open('text.txt') as fd:
    reader = csv.DictReader(fd)
    for row in reader:
        groups[row['code']].append(float(row['balance']))

totals = dict((key, sum(groups[key])) for key in groups)
print(totals)

CSV 分组 w/o Pandas

CSV Grouping w/o Pandas

python

python-2.x

Python > 2.6:

Python = 2.6: