這是我的字典列表：array_of_dictionaries = [{ "name": "Budi", "age": 23, "test_scores": [100.0, 98.0, 89.0]},{ "name": "Charlie", "age": 24, "test_scores": [90.0, 100.0]}]這是我的代碼：def get_all_time_max_avg_score(dictionary_list): for element in dictionary_list: lensum = len(element['test_scores']) elesum = sum(element['test_scores']) meansum = elesum / lensum for attribute in element.keys(): print("Mr. " + str(element['name']) + " with age(years) " + str(element['age']) + " get the highest average scores, " + str(round(meansum, 2))) breakget_all_time_max_avg_score(array_of_dictionaries)所以我想從這兩個(gè)詞典中獲得最高的平均分。我想要的輸出是：Mr. Budi with age(years) 23 get the highest average scores, 95.67但我得到的是：Mr. Budi with age(years) 23 get the highest average scores, 95.67Mr. Charlie with age(years) 24 get the highest average scores, 95.0我真的很感激我能得到的每一個(gè)幫助。
5 回答
LEATH
TA貢獻(xiàn)1936條經(jīng)驗(yàn) 獲得超7個(gè)贊
此代碼迭代并打印列表中的每個(gè)元素。相反，通過(guò)與平均值max比較來(lái)執(zhí)行列表。
最大（可迭代，*，默認(rèn)=無(wú)，鍵=功能）
這是一個(gè)列表理解的解決方案。
def get_all_time_max_avg_score(dictionary_list):
text = "Mr. {name} with age(years) {age} get the highest average scores, {average:.2f}"
def average(element):
return sum(element['test_scores']) / len(element['test_scores'])
e = max((element for element in dictionary_list), key=average, default=0)
return text.format(name=e['name'], age=e['age'], average=average(e))
print(get_all_time_max_avg_score(array_of_dictionaries))
輸出：
Mr. Budi with age(years) 23 get the highest average scores, 95.67
慕勒3428872
TA貢獻(xiàn)1848條經(jīng)驗(yàn) 獲得超6個(gè)贊
在打印任何內(nèi)容之前，您需要計(jì)算每一項(xiàng)的平均值
def get_all_time_max_avg_score(dictionary_list):
for element in dictionary_list:
lensum = len(element['test_scores'])
elesum = sum(element['test_scores'])
element['mean'] = elesum / lensum
first = sorted(dictionary_list, key=lambda x: x['mean'], reverse=True)[0]
print("Mr.", first['name'], "with age(years)", first['age'], "get the highest average scores,",
round(first['mean'], 2))
或者使用Dataframe
def get_all_time_max_avg_score(dictionary_list):
df = pd.DataFrame(dictionary_list)
df['mean'] = df['test_scores'].apply(np.mean)
first = df.loc[df['mean'].idxmax()]
print("Mr.", first['name'], "with age(years)", first['age'],
"get the highest average scores,", round(first['mean'], 2))
30秒到達(dá)戰(zhàn)場(chǎng)
TA貢獻(xiàn)1828條經(jīng)驗(yàn) 獲得超6個(gè)贊
使用帶有自定義鍵的內(nèi)置max函數(shù)來(lái)找出平均分?jǐn)?shù)最高的條目。
array_of_dictionaries = [{
"name": "Budi",
"age": 23,
"test_scores": [100.0, 98.0, 89.0]
},
{
"name": "Charlie",
"age": 24,
"test_scores": [90.0, 100.0]
}]
all_time_max_avg_score = max(
array_of_dictionaries,
key=lambda d: sum(d['test_scores']) / len(d['test_scores'])
)
meansum = sum(all_time_max_avg_score['test_scores']) / len(all_time_max_avg_score['test_scores'])
print("Mr. " + str(all_time_max_avg_score['name']) + " with age(years) " + str(all_time_max_avg_score['age']) + " get the highest average scores, " + str(round(meansum, 2)))
慕無(wú)忌1623718
TA貢獻(xiàn)1744條經(jīng)驗(yàn) 獲得超4個(gè)贊
收集所有名稱的平均值并選擇最大值
def get_all_time_max_avg_score(dictionary_list):
means = []
for d in dictionary_list:
means.append(sum(d['test_scores']) / len(d['test_scores']))
maxmean = max(means)
winner = dictionary_list[means.index(maxmean)]
print(
f'Mr. {winner["name"]}, with {winner["age"]} years of age, has the ' +
f'highest average scores: {maxmean:.2f}'
)
get_all_time_max_avg_score(array_of_dictionaries)
輸出
Mr. Budi, with 23 years of age, has the highest average scores: 95.67
飲歌長(zhǎng)嘯
TA貢獻(xiàn)1951條經(jīng)驗(yàn) 獲得超3個(gè)贊
通過(guò)一些額外的循環(huán)，您可以確定具有最大平均值的人
def get_all_time_max_avg_score(dictionary_list):
maxPersonIndex=0
maxAver=0
index=0
for element in dictionary_list:
lensum = len(element['test_scores'])
elesum = sum(element['test_scores'])
meansum = elesum / lensum
if(meansum>maxAver):
maxAver=meansum
maxPersonIndex=index
index+=1
for attribute in dictionary_list[maxPersonIndex].keys():
print("Mr. " + str(element['name']) + " with age(years) " + str(element['age']) + " get the highest average scores, " + str(round(meansum, 2)))
break
get_all_time_max_avg_score(array_of_dictionaries)
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