pandas 求和

日期,产品,销量
2021-01-01,A,10
2021-01-02,B,15
2021-01-03,A,12
2021-01-04,C,8
2021-01-05,B,7
2021-01-06,C,11

import pandas as pd

data = pd.read_csv('sales.csv')
sum_of_sales = data['销量'].sum()

print("销量的总和为:", sum_of_sales)

销量的总和为: 63

import pandas as pd

data = pd.read_csv('sales.csv')
sum_of_sales = data.sum(axis=1)

print("每行销量的总和为:")
print(sum_of_sales)

每行销量的总和为:
0    10
1    15
2    12
3     8
4     7
5    11
dtype: int64

import pandas as pd

data = pd.read_csv('sales.csv')
sum_of_sales = data.groupby('产品')['销量'].sum()

print("按产品求和:")
print(sum_of_sales)

按产品求和:
产品
A    22
B    22
C    19
Name: 销量, dtype: int64

import pandas as pd

data = pd.read_csv('sales.csv')
sum_of_sales = data[['销量', '利润']].sum()

print("销量和利润的总和为:")
print(sum_of_sales)

销量和利润的总和为:
销量    63
利润    42
dtype: int64

import pandas as pd

data = pd.read_csv('sales.csv')
sum_of_sales = data.set_index('日期').sum(level='日期')

print("按日期求和:")
print(sum_of_sales)

按日期求和:
日期
2021-01-01    10
2021-01-02    15
2021-01-03    12
2021-01-04     8
2021-01-05     7
2021-01-06    11
dtype: int64