{"id":69,"date":"2024-02-05T12:51:02","date_gmt":"2024-02-05T04:51:02","guid":{"rendered":"https:\/\/www.tchepai.com\/?p=69"},"modified":"2024-02-05T12:51:02","modified_gmt":"2024-02-05T04:51:02","slug":"_it","status":"publish","type":"post","link":"https:\/\/www.kdjingpai.com\/en\/_it\/","title":{"rendered":"\u4ee3\u7801\u4f18\u5316_IT\u4e13\u7528Prompt"},"content":{"rendered":"
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\u591a\u8fdb\u7a0b\u5e76\u884c\u8fd0\u7b97\u81ea\u52a8\u8f6c\u6362<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u628a\u4e0b\u9762\u8fd9\u6bb5 Python \u4ee3\u7801\u8f6c\u6362\u4e3a\u591a\u8fdb\u7a0b\u5e76\u884c\u8fd0\u7b97 \u2014\u2014<\/p>\n<\/div>\n

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**Python \u4ee3\u7801<\/p>\n<\/div>\n<\/div>\n<\/div>\n

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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u628a\u4e0b\u9762\u8fd9\u6bb5 Python \u4ee3\u7801\u8f6c\u6362\u4e3a\u591a\u8fdb\u7a0b\u5e76\u884c\u8fd0\u7b97 \u2014\u2014<\/p>\n<\/div>\n

\n

import time
\ndef calc_square(numbers):
\nfor n in numbers:
\nprint(f’\\n{n} ^ 2 = {n*n}’)
\ntime.sleep(0.1)<\/p>\n<\/div>\n

\n

def calc_cube(numbers):
\nfor n in numbers:
\nprint(f’\\n{n} ^ 3 = {nn<\/em>n}’)
\ntime.sleep(0.1)<\/p>\n<\/div>\n

\n

numbers = [2, 3, 5, 8]
\nstart = time.time()
\ncalc_square(numbers)
\ncalc_cube(numbers)
\nend = time.time()<\/p>\n<\/div>\n

\n

print(‘Execution Time: {}’.format(end-start))<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

\n
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\u4ee3\u7801\u6548\u7387\u5bf9\u6bd4<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u6d4b\u8bd5\u5de5\u7a0b\u5e08\uff0c\u6211\u60f3\u5bf9\u6bd4\u4ee5\u4e0b\u4e24\u6bb5\u6267\u884c\u76f8\u540c\u4efb\u52a1\u7684\u7b97\u6cd5\u4ee3\u7801\u7684\u8fd0\u884c\u6548\u7387\uff0c\u8bf7\u5199\u51fa\u4e00\u6bb5\u5faa\u73af\u6267\u884c\u4ee5\u4e0b\u7b97\u6cd5\u00a0[ \u53c2\u6570 ]<\/strong>\u00a0\u7684\u4ee3\u7801\uff0c\u5e76\u7ed9\u51fa\u4e24\u6bb5\u4ee3\u7801\u5404\u81ea\u7684\u6267\u884c\u65f6\u95f4\u4ee5\u53ca\u76f8\u5173\u7684\u7edf\u8ba1\u4fe1\u606f<\/p>\n<\/div>\n

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\u4ee3\u7801 1:<\/strong><\/p>\n<\/div>\n

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\u4ee3\u7801 2:<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n

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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u6d4b\u8bd5\u5de5\u7a0b\u5e08\uff0c\u6211\u60f3\u5bf9\u6bd4\u4ee5\u4e0b\u4e24\u6bb5\u6267\u884c\u76f8\u540c\u4efb\u52a1\u7684\u7b97\u6cd5\u4ee3\u7801\u7684\u8fd0\u884c\u6548\u7387\uff0c\u8bf7\u5199\u51fa\u4e00\u6bb5\u5faa\u73af\u6267\u884c\u4ee5\u4e0b\u7b97\u6cd5\u00a0[ 10\u6b21 ]<\/strong>\u00a0\u7684\u4ee3\u7801\uff0c\u5e76\u7ed9\u51fa\u4e24\u6bb5\u4ee3\u7801\u5404\u81ea>\u7684\u6267\u884c\u65f6\u95f4\u4ee5\u53ca\u76f8\u5173\u7684\u7edf\u8ba1\u4fe1\u606f<\/p>\n<\/div>\n

\n
# \u4ee3\u78011:\ndef compute1(a, b):\n    return (a+b) \/ (a*b)\n\n# \u4ee3\u78012:\nimport numpy as np\ndef compute2(a, b):\n    return np.divide(np.sum([a,b]), np.multiply(a,b))\n\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
\u81ea\u52a8\u5355\u5143\u5316\u6d4b\u8bd5<\/h1>\n
\n
\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u6d4b\u8bd5\u5de5\u7a0b\u5e08\uff0c\u8bf7\u7f16\u5199\u00a0[ \u51fd\u6570 ]<\/strong>\u00a0\u7684\u5355\u5143\u6d4b\u8bd5\u4ee3\u7801\uff0c\u6d4b\u8bd5\u6761\u4ef6\u4e3a\uff1a<\/p>\n<\/div>\n
\n
\u6d4b\u8bd5\u6761\u4ef6<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
\n
\n
\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u6d4b\u8bd5\u5de5\u7a0b\u5e08\uff0c\u8bf7\u7f16\u5199\u00a0[ def compute(a, b) ]<\/strong>\u00a0\u7684\u5355\u5143\u6d4b\u8bd5\u4ee3\u7801\uff0c\u6d4b\u8bd5\u6761\u4ef6\u4e3a\uff1a<\/p>\n<\/div>\n
\n
\u8f93\u5165\uff1a1\u30011.2\u30010.99 | \u8f93\u51fa\uff1a1\u30011.2\u30010.99\n\u8f93\u5165\uff1a-1\u3001-1.2\u3001-0.99 | \u8f93\u51fa\uff1a1\u30011.2\u30010.99\n\u8f93\u5165\uff1a0 | \u8f93\u51fa\uff1a0\n\u8f93\u5165\uff1aNone\u3001[]\u3001{} | \u8f93\u51fa\uff1aTypeError\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
\u4ee3\u7801\u52a0\u901f<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u5de5\u7a0b\u5e08\uff0c\u5e2e\u6211\u4f18\u5316\u4ee5\u4e0b\u4ee3\u7801\u7684\u6267\u884c\u6548\u7387 \u2014\u2014<\/p>\n<\/div>\n
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Python \u4ee3\u7801<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\n
\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u5de5\u7a0b\u5e08\uff0c\u5e2e\u6211\u4f18\u5316\u4ee5\u4e0b\u4ee3\u7801\u7684\u6267\u884c\u6548\u7387 \u2014\u2014<\/p>\n<\/div>\n
\n
def test(y):
\nsum = 0
\nfor i in range (y+1):
\nsum += 1
\nreturn sum<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
Pandas \u4ee3\u7801\u4f18\u5316<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u4f18\u5316\u5668\uff0c\u5e2e\u6211\u4f18\u5316\u4ee5\u4e0b Pandas \u4ee3\u7801 \u2014\u2014<\/p>\n<\/div>\n
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Python \u4ee3\u7801<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u4f18\u5316\u5668\uff0c\u5e2e\u6211\u4f18\u5316\u4ee5\u4e0b Pandas \u4ee3\u7801 \u2014\u2014<\/p>\n<\/div>\n
\n
import pandas as pd<\/p>\n<\/div>\n
\n
df = pd.read_csv(data_path + “titles.csv”)
\ndf_bad = df.query(“runtime > 30 & type == ‘SHOW'”)
\ndf_bad [“score”] = df_bad”imdb_score”, “tmdb_score”.sum(axis=1)
\ndf_bad = df_bad”seasons”, “score”
\ndf_bad = df_bad.groupby(“seasons”).agg([“count”, “mean”])
\ndf_bad = df_bad.droplevel(axis=1, level=0)
\ndf_bad = df_bad.query(“count > 10”)<\/p>\n<\/div>\n
\n
df_bad.head()<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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\u4f4e\u7ea7\u4ee3\u7801\u6539\u5199<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u4f18\u5316\u5668\uff0c\u4e0b\u9762\u7684\u4ee3\u7801\u5199\u7684\u6bd4\u8f83\u4f4e\u7ea7\uff0c\u8bf7\u5e2e\u6211\u4fee\u6539 \u2014\u2014<\/p>\n<\/div>\n
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Python \u4ee3\u7801<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u4f18\u5316\u5668\uff0c\u4e0b\u9762\u7684\u4ee3\u7801\u5199\u7684\u6bd4\u8f83\u4f4e\u7ea7\uff0c\u8bf7\u5e2e\u6211\u4fee\u6539 \u2014\u2014<\/p>\n<\/div>\n
\n
numbers = [1, 2, 3]
\nletters =[“A”, “B”, “C”]<\/p>\n<\/div>\n
\n
for index in range (len(numbers)):
\nprint(numbers[index], letters[index])<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
\u4ee3\u7801\u7b80\u5316<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u4f18\u5316\u5668\uff0c\u7b80\u5316\u4e0b\u9762\u7684\u4ee3\u7801 \u2014\u2014<\/p>\n<\/div>\n
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Python \u4ee3\u7801<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n
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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u4f18\u5316\u5668\uff0c\u7b80\u5316\u4e0b\u9762\u7684\u4ee3\u7801 \u2014\u2014<\/p>\n<\/div>\n
\n
classes = [‘Intro to Python’,
\n‘R Data Analysis’,
\n‘Python Machine Learning’]
\ngrades = [98,
\n96,
\n89]
\ngrade_dict = {}
\nfor idx in range(len(classes)):
\ngrade_dict[classes[idx]] = grades[idx]
\nprint(grade_dict)<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
<\/div>\n
\u4ee3\u7801\u6392\u9519<\/h1>\n
\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u5de5\u7a0b\u5e08\uff0c\u5e2e\u6211\u6392\u9664\u4ee5\u4e0b\u4ee3\u7801\u4e2d\u7684\u9519\u8bef \u2014\u2014<\/p>\n<\/div>\n
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Python \u4ee3\u7801<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n
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<\/div>\n
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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u5de5\u7a0b\u5e08\uff0c\u5e2e\u6211\u6392\u9664\u4ee5\u4e0b\u4ee3\u7801\u4e2d\u7684\u9519\u8bef \u2014\u2014<\/p>\n<\/div>\n
\n
def add_from_1_to_k(k):
\nif (k > 0):
\nresult = k + add_from_1_to_k(k – 1)
\nreturn result<\/p>\n<\/div>\n
\n
add_from_1_to_k(-10)<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
\u591a\u8fdb\u7a0b\u5e76\u884c\u8fd0\u7b97\u81ea\u52a8\u8f6c\u6362 \u6307\u4ee4\u683c\u5f0f \u8bf7\u628a\u4e0b\u9762\u8fd9\u6bb5 Python \u4ee3\u7801\u8f6c\u6362\u4e3a\u591a\u8fdb\u7a0b\u5e76\u884c\u8fd0\u7b97 \u2014\u2014 **Python \u4ee3\u7801 \u6307\u4ee4\u793a\u4f8b \u8bf7\u628a\u4e0b\u9762\u8fd9\u6bb5 Python \u4ee3\u7801\u8f6c\u6362\u4e3a\u591a\u8fdb\u7a0b\u5e76\u884c\u8fd0\u7b97 \u2014\u2014 import time def calc_squar…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[23],"class_list":["post-69","post","type-post","status-publish","format-standard","hentry","category-prompts","tag-daima"],"_links":{"self":[{"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/posts\/69","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/comments?post=69"}],"version-history":[{"count":0,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/posts\/69\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/media?parent=69"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/categories?post=69"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/tags?post=69"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}