假设我有一个与此类似的 CSV 文件,只是更大:
Cost center number,Month,Amount 1,Amount 2
1234,1,755,9356
1234,2,6758,786654
1234,1,-954,31234
1234,2,2345,778
1234,5,680,986
5678,6,876,456
5678,6,1426,321
5678,5,823,164
5678,7,4387,3485
91011,11,1582,714
91011,12,778,963
91011,10,28,852
91011,12,23475,147
我想模仿 Excel 数据透视表功能,并按成本中心、月份和两个金额的总和对数据进行分组,因此输出如下所示:
Cost center number,Month,Amount 1 + Amount 2
1234,1,Amount 1 value + Amount 2 value
1234,2,Amount 1 value + Amount 2 value
1234,5,Amount 1 value + Amount 2 value
5678,6,Amount 1 value + Amount 2 value
5678,5,Amount 1 value + Amount 2 value
5678,7,Amount 1 value + Amount 2 value
91011,11,Amount 1 value + Amount 2 value
91011,10,Amount 1 value + Amount 2 value
91011,12,Amount 1 value + Amount 2 value
到目前为止,我已经尝试迭代每一行并为我感兴趣的数据创建列表,但我不知道从哪里开始:
import csv
filename = 'APAC.csv'
with open(filename) as f:
reader = csv.reader(f)
headers = next(reader)
for header in enumerate(headers):
print(header)
cost_centers = []
months = []
amounts1 = []
amounts2 = []
for row in reader:
cost_centers.append(row[1])
months.append(row[2)]
amounts1.append(row[3])
amounts2.append(row[4])
我知道 Pandas 可以选择“group by”和“agg”,但这对我来说是一个列表和字典的练习(但是我对不同的方法持开放态度),我更愿意留在本地Python 库。
最佳答案
使用groupby
并聚合 sum
,然后如果需要对所有列求和,请添加 sum
和 axis=1
:
#create DataFrame
df = pd.read_csv('APAC.csv')
df = df.groupby(['Cost center number','Month']).sum().sum(axis=1).reset_index(name='sum')
print (df)
Cost center number Month sum
0 1234 1 40391
1 1234 2 796535
2 1234 5 1666
3 5678 5 987
4 5678 6 3079
5 5678 7 7872
6 91011 10 880
7 91011 11 2296
8 91011 12 25363
详细信息:
print (df.groupby(['Cost center number','Month']).sum())
Amount 1 Amount 2
Cost center number Month
1234 1 -199 40590
2 9103 787432
5 680 986
5678 5 823 164
6 2302 777
7 4387 3485
91011 10 28 852
11 1582 714
12 24253 1110
如果想要一个类轮,请先回答 add
,然后按列groupby
和最后聚合sum
:
df = (
df['Amount 1'].add(df['Amount 2'])
.groupby([df['Cost center number'], df['Month']])
.sum()
.reset_index(name='sum')
)
print (df)
Cost center number Month sum
0 1234 1 40391
1 1234 2 796535
2 1234 5 1666
3 5678 5 987
4 5678 6 3079
5 5678 7 7872
6 91011 10 880
7 91011 11 2296
8 91011 12 25363
关于python - 按多个条件聚合 CSV 行,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/48853867/