题解 | #统计618的销售额#

import pandas as pd


# Order ={
#     'order_num':['10001','10002','10003','10004','10005'],
#     'price':[80,991,281,452,173],
#     'Date':['2022/6/18','2022/6/19','2022/6/18','2022/6/17','2022/6/18'],
#     'shop_name':['lamer','sk2','Nike','lancome','Nike']
# }

# # df = pd.read_csv('Order.csv',sep=',',dtype=object)
# df= pd.DataFrame(Order)
# # 统计618当天销售总额，先通过Date筛选出行，再限制字段获取值，最后计算总和
# print(df.loc[df['Date']=='2022/6/18','price'].sum())
# # 统计每个shop_name出现过多少次
# print(df.value_counts('shop_name'))



'''方法一'''
# df = pd.read_csv('Order.csv',sep=',',dtype=object) 
df = pd.read_csv('Order.csv',sep=',')# 读取文件不能加dtype=object
# 统计618当天销售总额，先通过Date筛选出行，再限制字段获取值，最后计算总和
print(df.loc[(df['date']=='2022/6/18'),'price'].sum())
# 统计每个shop_name出现过多少次
print(df.value_counts('shop_name'))


'''方法二'''
df = pd.read_csv('Order.csv',sep=',')# 读取文件不能加dtype=object
# 统计618当天销售总额，先通过Date筛选出行，再限制字段获取值，最后计算总和
print(df['price'][df.date=='2022/6/18'].sum())
# 统计每个shop_name出现过多少次
print(df['shop_name'].value_counts())