模拟 数据（连这数据我都模拟出来了）
signup.csv 
employee_id,name,sex,department,item_id
NC001,liming,f,functional,N100
NC002,zhangsan,f,functional,N101
NC003,sunli,m,functional,N103
NC004,lina,m,functional,N103
NC005,wanger,m,technology,N101
NC006,shenteng,m,education,N104
NC007,mali,f,operation,N102
NC008,reba,f,technology,N100
NC009,ailun,m,education,N101
NC010,changyuan,f,technology,N102
NC011,geyou,m,operation,N102
NC012,cls,f,technology,N102
NC013,zhangwei,m,education,N102
NC014,liufang,m,education,N102
NC015,wanglei,f,education,N104
NC016,zhangli,f,education,N101
NC017,wangyan,f,operation,N103
NC018,liangfeifan,f,operation,N103
items.csv 
item_id,item_name,location
N100,athletics,area01
N101,longJump,area02
N102,highJump,area03
N103,javelin,area04
N104,pingPong,area05
N105,relayRace,area06
实现代码 
import pandas as pd

signup = pd.read_csv("signup.csv")
items = pd.read_csv("items.csv")

df_all = pd.merge(
    signup, items, how="left", left_on=signup["item_id"], right_on=items["item_id"]
)

print(
    pd.pivot_table(
        df_all,
        index=["sex", "department"],
        columns=["item_name"],
        values=["employee_id"],
        aggfunc="count",
        fill_value=0,
    )
)