我想找到兩列的最小劃分，只有列表中第三列中的值。我的數據框是： ID size price0 1 5 3001 2 10 5002 3 20 6003 4 35 8004 5 65 9005 6 70 1000 我想找到最低價格/尺寸，只能從列表中具有值的 ids 中找到。ids_wanted = [1,4,6]我寫了這段代碼，它可以工作，但我覺得為這個任務制作一個新的數據框既昂貴又沒必要。import numpy as npimport pandas as pdindex = [0,1,2,3,4,5]i = pd.Series([1,2,3,4,5,6], index=index)s = pd.Series([5,10,20,35,65,70],index= index)p = pd.Series([300,500,600,800,900,1000],index= index)df = pd.DataFrame(np.c_[i,s,p],columns = ["ID","size","price"])print("original df:\n",df,"\n")ids_wanted = [1,4,6]df_with_ids_wanted = df.loc[df['ID'].isin(ids_wanted)]print("df with ids wanted:\n",df_with_ids_wanted,"\n")price_per_byte = df_with_ids_wanted['price'] / df_with_ids_wanted['size']df_with_ids_wanted_ppb = df_with_ids_wanted.assign(pricePerByte=price_per_byte)print("df with ids wanted and price/size column:\n",df_with_ids_wanted_pps,"\n")min_ppb = df_with_ids_wanted_pps['pricePerByte'].min()print("min price per byte:",min_ppb)輸出：original df: ID size price0 1 5 3001 2 10 5002 3 20 6003 4 35 8004 5 65 9005 6 70 1000 df with ids wanted: ID size price0 1 5 3003 4 35 8005 6 70 1000 df with ids wanted and price/size column: ID size price pricePerByte0 1 5 300 60.0000003 4 35 800 22.8571435 6 70 1000 14.285714 min price per byte: 14.285714285714286
2 回答
手掌心
TA貢獻1942條經驗 獲得超3個贊
如果你想簡潔，你可以試試這個：
i = range(1,7)
s = [5,10,20,35,65,70]
p = [300,500,600,800,900,1000]
df = pd.DataFrame({"ID":i,"size":s,"price":p})
df
輸出：
ID size price
0 1 5 300
1 2 10 500
2 3 20 600
3 4 35 800
4 5 65 900
5 6 70 1000
下一行看起來像這樣：
id_chosen = [1,4,6]
(df[df.ID.isin(id_chosen)]["price"]/df[df.ID.isin(id_chosen)]["size"]).min()
輸出：
14.285714285714286
要么
min_div = (df[df.ID.isin(id_chosen)]["price"]/df[df.ID.isin(id_chosen)]["size"]).min()
print("the minimum price/size is {}".format(min_div))
輸出：
the minimum price/size is 14.285714285714286
這樣，您就不必創建新的數據框。希望這可以幫助。
慕哥6287543
TA貢獻1831條經驗 獲得超10個贊
我會做這樣的事情：
import numpy as np
import pandas as pd
dict = {'id': [1, 2, 3, 4, 5, 6],
'size': [5, 10, 20, 35, 65, 70],
'price': [300, 500, 600, 800, 900, 1000]
}
df = pd.DataFrame(dict)
df['price/byte'] = df['price'] / df['size']
ids_wanted = [1, 4, 6]
subset = df[df['id'].isin(ids_wanted)]
sorted_values = subset.sort_values(by='price/byte', ascending = True)
print(sorted_values['price/byte'].iloc[0])
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