DA39. 多报名表的运动项目人数统计
描述
某公司计划举办一场运动会，现有部分运动会项目数据集items.csv。 包含以下字段：
有员工报名情况数据集signup.csv。包含以下字段：
另有signup1.csv，是education部门的报名情况，包含字段同signup.csv。
请你将signup.csv与signup1.csv的数据集合并后，统计各类型项目的报名人数。
Python 3 解法, 执行用时: 770ms, 内存消耗: 524288KB, 提交时间: 2022-07-05
import pandas as pd
signup = pd.read_csv('signup.csv')
signup1 = pd.read_csv('signup1.csv')
items = pd.read_csv('items.csv')
signup2=pd.concat([signup,signup1],axis=0)
result1=pd.merge(items,signup2,how='inner',on='item_id')
result=result1.groupby('item_name')
print(result.size())
Python 3 解法, 执行用时: 779ms, 内存消耗: 524288KB, 提交时间: 2022-07-13
import pandas as pd
signup = pd.read_csv('signup.csv')
signup1 = pd.read_csv('signup1.csv')
items = pd.read_csv('items.csv')
## s = pd.concat([signup,signup1],axis=0)
# s = signup.append(signup1)
# print(pd.merge(items,s,how="left").groupby('item_name').employee_id.count())
df3 = pd.concat([signup,signup1],axis=0,join='outer')
df3 = pd.merge(items,df3,on='item_id')
print(df3.groupby('item_name')['employee_id'].count())
Python 3 解法, 执行用时: 780ms, 内存消耗: 524288KB, 提交时间: 2022-07-25
import pandas as pd
signup = pd.read_csv('signup.csv')
signup1 = pd.read_csv('signup1.csv')
items = pd.read_csv('items.csv')
a = pd.concat([signup,signup1],axis=0)
b = pd.merge(a,items,how='left',on='item_id')
cnt = b.groupby('item_name')['employee_id'].count()
print(cnt)
Python 3 解法, 执行用时: 780ms, 内存消耗: 524288KB, 提交时间: 2022-07-04
import pandas as pd
signup = pd.read_csv('signup.csv')
signup1 = pd.read_csv('signup1.csv')
items = pd.read_csv('items.csv')
total_s=pd.concat([signup,signup1])
output=items.merge(total_s,on='item_id',how='inner')
output1=output.groupby('item_name')['employee_id'].count()
print(output1)
Python 3 解法, 执行用时: 784ms, 内存消耗: 524288KB, 提交时间: 2022-07-02
import pandas as pd
signup = pd.read_csv('signup.csv')
signup1 = pd.read_csv('signup1.csv')
items = pd.read_csv('items.csv')
signup2=pd.concat([signup,signup1])
output=items.merge(signup2,on='item_id',how='inner')
output1=output.groupby('item_name')['employee_id'].count()
print(output1)