這 5 個(gè)國家在歷屆奧運(yùn)會(huì)上獲得的獎(jiǎng)牌總數(shù)中，他們各自獲得的獎(jiǎng)牌數(shù)所占的百分比是多少？我已使用 panda dataframe 將所有 excel 文件合并到一個(gè)文件中，但現(xiàn)在仍堅(jiān)持查找百分比? ? Country? ? ? Gold? ? ?Silver? ? Bronze? Total0? ?USA? ? ? ? ? 10? ? ? ?13? ? ? ? ?11? ? ? 341? ?China? ? ? ? 2? ? ? ? 2? ? ? ? ? 4? ? ? ?82? ?UK? ? ? ? ? ?1? ? ? ? 0? ? ? ? ? 1? ? ? ?23? ?Germany? ? ? 12? ? ? ?16? ? ? ? ?8? ? ? ?364? ?Australia? ? 2? ? ? ? 0? ? ? ? ? 0? ? ? ?20? ?USA? ? ? ? ? 9? ? ? ? 9? ? ? ? ? 7? ? ? ?251? ?China? ? ? ? 2? ? ? ? 4? ? ? ? ? 5? ? ? ?112? ?UK? ? ? ? ? ?0? ? ? ? 1? ? ? ? ? 0? ? ? ?13? ?Germany? ? ? 11? ? ? ?12? ? ? ? ?6? ? ? ?294? ?Australia? ? 1? ? ? ? 0? ? ? ? ? 1? ? ? ?20? ?USA? ? ? ? ? 9? ? ? ? 15? ? ? ? ?13? ? ? 371? ?China? ? ? ? 5? ? ? ? 2? ? ? ? ? 4? ? ? ?112? ?UK? ? ? ? ? ?1? ? ? ? 0? ? ? ? ? 0? ? ? ?13? ?Germany? ? ? 10? ? ? ?13? ? ? ? ?7? ? ? ?304? ?Australia? ? 2? ? ? ? 1? ? ? ? ? 0? ? ? ?3import pandas as pdimport numpy as npimport matplotlib.pyplot as pltdf= pd.DataFrame()for f in ['E:\\olympics\\Olympics-2002.xlsx','E:\\olympics\\Olympics-?2006.xlsx','E:\\olympics\\Olympics-2010.xlsx',? ? ? 'E:\\olympics\\Olympics-2014.xlsx','E:\\olympics\\Olympics-?2018.xlsx']:data = pd.read_excel(f,'Sheet1')df = df.append(data)df.to_excel("E:\\olympics\\combineddata.xlsx")data = pd.read_excel("E:\\olympics\\combineddata.xlsx")print(data)final_Data={}for i in data['Country']:x=it1=(data[(data.Country==x)].Total).tolist()print("Name of Country=",i, int(sum(t1)))final_Data.update({i:int(sum(t1))})t3=data.groupby('Country').Total.sum()t2= df['Total'].sum()t4= t3/t2*100print(t3)print(t2)print(t4)這是如何得到答案的......現(xiàn)在我需要將其拉入情節(jié)我想把它放在餡餅中
2 回答
慕標(biāo)琳琳
TA貢獻(xiàn)1830條經(jīng)驗(yàn) 獲得超9個(gè)贊
假設(shè)您已將 DataFrame 創(chuàng)建為'df'. 然后您可以執(zhí)行以下操作，首先分組，然后計(jì)算百分比。
df = df.groupby('Country').sum()
df['Gold_percent'] = (df['Gold'] / df['Gold'].sum()) * 100
df['Silver_percent'] = (df['Silver'] / df['Silver'].sum()) * 100
df['Bronze_percent'] = (df['Bronze'] / df['Bronze'].sum()) * 100
df['Total_percent'] = (df['Total'] / df['Total'].sum()) * 100
df.round(2)
print (df)
輸出如下：
Gold Silver Bronze ... Silver_percent Bronze_percent Total_percent
Country ...
Australia 5 1 1 ... 1.14 1.49 3.02
China 9 8 13 ... 9.09 19.40 12.93
Germany 33 41 21 ... 46.59 31.34 40.95
UK 2 1 1 ... 1.14 1.49 1.72
USA 28 37 31 ... 42.05 46.27 41.38
眼眸繁星
TA貢獻(xiàn)1873條經(jīng)驗(yàn) 獲得超9個(gè)贊
我沒有你所擁有的確切數(shù)據(jù)集。我正在用類似的數(shù)據(jù)集進(jìn)行解釋。嘗試添加一列，其中包含跨行的獎(jiǎng)牌總和。然后通過將所有行除以整列的總和來找到百分比。
我將此作為模型發(fā)布，請(qǐng)檢查此
import pandas as pd
cars = {'Brand': ['Honda Civic','Toyota Corolla','Ford Focus','Audi A4'],
'ExshowroomPrice': [21000,26000,28000,34000],'RTOPrice': [2200,250,2700,3500]}
df = pd.DataFrame(cars, columns = ['Brand', 'ExshowroomPrice','RTOPrice'])
Brand ExshowroomPrice RTOPrice
0 Honda Civic 21000 2200
1 Toyota Corolla 26000 250
2 Ford Focus 28000 2700
3 Audi A4 34000 3500
df['percentage']=(df.ExshowroomPrice +df.RTOPrice) * 100
/(df.ExshowroomPrice.sum() +df.RTOPrice.sum())
print(df)
Brand ExshowroomPrice RTOPrice percentage
0 Honda Civic 21000 2200 19.719507
1 Toyota Corolla 26000 250 22.311942
2 Ford Focus 28000 2700 26.094348
3 Audi A4 34000 3500 31.874203
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