题解 | #某店铺用户消费特征评分#

import sys

import pandas as pd 
import numpy as np
df = pd.read_csv('sales.csv')
df['R_Quartile'] = df['recency'].apply(lambda x: 4 if x <= df['recency'].quantile(0.25) else (3 if x > df['recency'].quantile(0.25) and x <= df['recency'].quantile(0.5) else (2 if x > df['recency'].quantile(0.5) and x <= df['recency'].quantile(0.75) else 1)))

df['F_Quartile'] = df['frequency'].apply(lambda x: 4 if x >  df['frequency'].quantile(0.75) else (3 if x >=  df['frequency'].quantile(0.5) and x <  df['frequency'].quantile(0.75) else (2 if x >=  df['frequency'].quantile(0.25) and x <  df['frequency'].quantile(0.5) else 1)))

df['M_Quartile'] = df['monetary'].apply(lambda x: 4 if x > df['monetary'].quantile(0.75) else (3 if x >= df['monetary'].quantile(0.5) and x < df['monetary'].quantile(0.75) else (2 if x >= df['monetary'].quantile(0.25) and x < df['monetary'].quantile(0.5) else 1)))

print(df.head(5))

for line in sys.stdin:
    a = line.split()
    print(int(a[0]) + int(a[1]))