and manipulate financial data. Many recruiters look for SQL programming knowledge when reviewing resumes for Financial Analyst positions. Knowledge of SQL also benefits those seeking other types of finance jobs including professions that work with data processing platforms and statistical modeling. Learn mo...
Python、Php相关岗位的公司名称、招聘城市、岗位名称、薪资待遇等进行爬取,然后将招聘信息存入数据库,使...
Python可以与Excel集成,在金融行业中使用的也不交广泛,轻松集成,方便在两者之间进行数据传出和操作。比...
jobs=[] for id in positionId['positionId']: job_desc=crawl_detail(id) jobs.append(job_desc) jobs=pd.DataFrame(jobs,columns=['职位详情']) jobs=pd.concat([positionId,jobs],axis=1) #合并职位ID和职位详情 jobs.to_excel('职位详情.xlsx',index=False) (之前爬过所有职位的详情,但是可能爬得...
定义 get_page_info(jobs_list) 函数, 其作用为获取 整个的岗位信息的列表,一条职业数据列表中包含“companyFullName”,“companyShortName”,“companySize”,“financeStage”,“district”,“positionName”,“workYear”,“education”,“skillLables”,“salary”,“positionAdvantage”十一项内容。 1.4 主函数 ...
教科书给的评估方式是单一评判correlation高或者mse低没有意义。要同时结合因子指标和pnl来衡量(Meucci A. Risk and Asset Allocation[J]. springer finance, 2005)图8举例说明控制变量后,correlation差的因子回测曲线可能更好。因此要尊重以下“因子指标”与PnL衡量共同的结论。
Python is a programming language that develops applications for various domains. You can find the use of Python in healthcare, IT, finance, and every other business field. Though most IT companies hire Python professionally, there can be better job offers in other industries. The table below sh...
for j in position_result['result']: python_job = [] # 公司全名 python_job.append(j['companyFullName']) # 公司简称 python_job.append(j['companyShortName']) # 公司规模 python_job.append(j['companySize']) # 融资 python_job.append(j['financeStage']) ...
Together these skills can be used for personal investment, algorithmic trading, portfolio building and more. Being able to quickly generate statistical insights, visualize relationships and pinpoint trends in financial data is invaluable for any analyst or data scientist interested in finance. ...
location=url.split('&')[-1].split('=')[1]key=url.split('/')[-1].split('?')[0].split('_')[1]soup=BeautifulSoup(response.text,'lxml')pages=soup.find('span',{'class':'span totalNum'}).get_text()foriinrange(1,int(pages)+1):url='https://www.lagou.com/jobs/positionAjax...