循环使用函数中的数据，使用Django在模板中创建表

Question

我有一个名为def get_scraped_data():t的函数，它本质上是一个web scrapper。它返回一个名为newlaw的DataFrame，包含我想要的所有数据。整个代码如下。

def get_scraped_data():
    from bs4 import BeautifulSoup
    import requests
    import pandas as pd

    urlh = 'http://solicitors.lawsociety.org.uk/search/results?Type=1&IncludeNlsp=True&Pro=True&parameters=%2C1%3BAPL%2C0%3B%2C1%3BPUB%2C0%3B%2C1%3BADV%2C0%3B%2C1%3BAGR%2C0%3B%2C1%3BAVI%2C0%3B%2C1%3BBAN%2C1%3B%2C1%3BBEN%2C0%3B%2C1%3BCHA%2C0%3B%2C1%3BCHI%2C0%3B%2C1%3BCLI%2C0%3B%2C1%3BCOL%2C1%3B%2C1%3BPCO%2C1%3B%2C1%3BCCL%2C0%3B%2C1%3BCOS%2C1%3B%2C1%3BCOM%2C1%3B%2C1%3BCON%2C1%3B%2C1%3BCSU%2C0%3B%2C1%3BCSF%2C0%3B%2C1%3BCSG%2C0%3B%2C1%3BCUT%2C0%3B%2C1%3BCTR%2C1%3B%2C1%3BPRE%2C0%3B%2C1%3BCFI%2C1%3B%2C1%3BCRD%2C0%3B%2C1%3BCRF%2C0%3B%2C1%3BCRG%2C0%3B%2C1%3BCRJ%2C0%3B%2C1%3BCRL%2C0%3B%2C1%3BCRM%2C0%3B%2C1%3BCRS%2C0%3B%2C1%3BCRO%2C1%3B%2C1%3BDEB%2C0%3B%2C1%3BDTR%2C1%3B%2C1%3BDEF%2C0%3B%2C1%3BDRC%2C0%3B%2C1%3BDRO%2C1%3B%2C1%3BEDU%2C0%3B%2C1%3BELC%2C0%3B%2C1%3BELH%2C0%3B%2C1%3BEMP%2C1%3B%2C1%3BENE%2C0%3B%2C1%3BENV%2C0%3B%2C1%3BEUN%2C0%3B%2C1%3BFDS%2C0%3B%2C1%3BFAM%2C0%3B%2C1%3BFAL%2C0%3B%2C1%3BFMC%2C0%3B%2C1%3BFME%2C0%3B%2C1%3BFML%2C0%3B%2C1%3BFPL%2C0%3B%2C1%3BFIS%2C0%3B%2C1%3BHRI%2C0%3B%2C1%3BIMA%2C0%3B%2C1%3BIML%2C0%3B%2C1%3BIMM%2C0%3B%2C1%3BIMG%2C0%3B%2C1%3BIMN%2C0%3B%2C1%3BITE%2C1%3B%2C1%3BINS%2C1%3B%2C1%3BIUR%2C1%3B%2C1%3BIPR%2C1%3B%2C1%3BJRW%2C0%3B%2C1%3BJRL%2C0%3B%2C1%3BLCO%2C1%3B%2C1%3BLRE%2C0%3B%2C1%3BPOA%2C0%3B%2C1%3BLIC%2C1%3B%2C1%3BLIV%2C0%3B%2C1%3BLIS%2C0%3B%2C1%3BLIT%2C0%3B%2C1%3BLPH%2C0%3B%2C1%3BLPP%2C0%3B%2C1%3BMAR%2C0%3B%2C1%3BMED%2C1%3B%2C1%3BMHE%2C0%3B%2C1%3BMHL%2C0%3B%2C1%3BMAA%2C1%3B%2C1%3BMIL%2C0%3B%2C1%3BNDI%2C0%3B%2C1%3BPEN%2C1%3B%2C1%3BPIN%2C0%3B%2C1%3BPIR%2C0%3B%2C1%3BPLA%2C0%3B%2C1%3BPRZ%2C0%3B%2C1%3BPRP%2C0%3B%2C1%3BPRT%2C0%3B%2C1%3BPRW%2C0%3B%2C1%3BPCI%2C0%3B%2C1%3BPCP%2C0%3B%2C1%3BPCT%2C0%3B%2C1%3BPCW%2C0%3B%2C1%3BPNE%2C0%3B%2C1%3BTAX%2C0%3B%2C1%3BTAC%2C1%3B%2C1%3BTAE%2C0%3B%2C1%3BTAH%2C1%3B%2C1%3BTAM%2C0%3B%2C1%3BTAP%2C0%3B%2C1%3BTAT%2C0%3B+'
    r = requests.get(urlh)
    soup = BeautifulSoup(r.content, 'html.parser')

    names = []
    roles = []
    offices = []
    locations = []

    for i in range(1,2):
        url = 'http://solicitors.lawsociety.org.uk/search/results?Type=1&IncludeNlsp=True&Pro=True&parameters=%2C1%3BAPL%2C0%3B%2C1%3BPUB%2C0%3B%2C1%3BADV%2C0%3B%2C1%3BAGR%2C0%3B%2C1%3BAVI%2C0%3B%2C1%3BBAN%2C1%3B%2C1%3BBEN%2C0%3B%2C1%3BCHA%2C0%3B%2C1%3BCHI%2C0%3B%2C1%3BCLI%2C0%3B%2C1%3BCOL%2C1%3B%2C1%3BPCO%2C1%3B%2C1%3BCCL%2C0%3B%2C1%3BCOS%2C1%3B%2C1%3BCOM%2C1%3B%2C1%3BCON%2C1%3B%2C1%3BCSU%2C0%3B%2C1%3BCSF%2C0%3B%2C1%3BCSG%2C0%3B%2C1%3BCUT%2C0%3B%2C1%3BCTR%2C1%3B%2C1%3BPRE%2C0%3B%2C1%3BCFI%2C1%3B%2C1%3BCRD%2C0%3B%2C1%3BCRF%2C0%3B%2C1%3BCRG%2C0%3B%2C1%3BCRJ%2C0%3B%2C1%3BCRL%2C0%3B%2C1%3BCRM%2C0%3B%2C1%3BCRS%2C0%3B%2C1%3BCRO%2C1%3B%2C1%3BDEB%2C0%3B%2C1%3BDTR%2C1%3B%2C1%3BDEF%2C0%3B%2C1%3BDRC%2C0%3B%2C1%3BDRO%2C1%3B%2C1%3BEDU%2C0%3B%2C1%3BELC%2C0%3B%2C1%3BELH%2C0%3B%2C1%3BEMP%2C1%3B%2C1%3BENE%2C0%3B%2C1%3BENV%2C0%3B%2C1%3BEUN%2C0%3B%2C1%3BFDS%2C0%3B%2C1%3BFAM%2C0%3B%2C1%3BFAL%2C0%3B%2C1%3BFMC%2C0%3B%2C1%3BFME%2C0%3B%2C1%3BFML%2C0%3B%2C1%3BFPL%2C0%3B%2C1%3BFIS%2C0%3B%2C1%3BHRI%2C0%3B%2C1%3BIMA%2C0%3B%2C1%3BIML%2C0%3B%2C1%3BIMM%2C0%3B%2C1%3BIMG%2C0%3B%2C1%3BIMN%2C0%3B%2C1%3BITE%2C1%3B%2C1%3BINS%2C1%3B%2C1%3BIUR%2C1%3B%2C1%3BIPR%2C1%3B%2C1%3BJRW%2C0%3B%2C1%3BJRL%2C0%3B%2C1%3BLCO%2C1%3B%2C1%3BLRE%2C0%3B%2C1%3BPOA%2C0%3B%2C1%3BLIC%2C1%3B%2C1%3BLIV%2C0%3B%2C1%3BLIS%2C0%3B%2C1%3BLIT%2C0%3B%2C1%3BLPH%2C0%3B%2C1%3BLPP%2C0%3B%2C1%3BMAR%2C0%3B%2C1%3BMED%2C1%3B%2C1%3BMHE%2C0%3B%2C1%3BMHL%2C0%3B%2C1%3BMAA%2C1%3B%2C1%3BMIL%2C0%3B%2C1%3BNDI%2C0%3B%2C1%3BPEN%2C1%3B%2C1%3BPIN%2C0%3B%2C1%3BPIR%2C0%3B%2C1%3BPLA%2C0%3B%2C1%3BPRZ%2C0%3B%2C1%3BPRP%2C0%3B%2C1%3BPRT%2C0%3B%2C1%3BPRW%2C0%3B%2C1%3BPCI%2C0%3B%2C1%3BPCP%2C0%3B%2C1%3BPCT%2C0%3B%2C1%3BPCW%2C0%3B%2C1%3BPNE%2C0%3B%2C1%3BTAX%2C0%3B%2C1%3BTAC%2C1%3B%2C1%3BTAE%2C0%3B%2C1%3BTAH%2C1%3B%2C1%3BTAM%2C0%3B%2C1%3BTAP%2C0%3B%2C1%3BTAT%2C0%3B+' + '=&Page=' + str(i)
        response = requests.get(url)
        response.raise_for_status()
        soup = BeautifulSoup(response.content, 'html.parser')

        hp_sol_data = soup.find_all('section', {'class':'solicitor'})

        for sol in hp_sol_data:
            try:
                addy = sol.contents[7].find_all('dd', {'class':'feature highlight'})[0].text
                locations.append(addy)
            except IndexError:
                locations.append('None Found')
            try:
                office_names = sol.contents[7].find_all('dd', {'class':'highlight'})[0].text
                offices.append(office_names)
            except IndexError:
                offices.append('None Found')

        for link in soup.find_all('a', href=True):
            if link.get('href').startswith('/person/'):
                tags = (link.get('href'))

                url2 = 'http://solicitors.lawsociety.org.uk' + str(tags)
                r2 = requests.get(url2)
                soup = BeautifulSoup(r2.content, 'html.parser')

                s_data = soup.find_all('article', {'class':'solicitor solicitor-type-individual details'})

                for item in s_data:
                    solicitor_names = (item.contents[3].find_all('h1')[0].text)
                    names.append(solicitor_names)

                    try:
                        role = (item.find_all('div', {'class':'panel-half'})[1].find('dd').get_text(''))
                        roles.append(role)
                    except IndexError:
                        roles.append('Role not specified')

    tls_solicitors = pd.DataFrame({'Solicitor_Name': names,
                                'Role': roles,
                                'Office': offices,
                                'Address': locations},
                                columns = ['Solicitor_Name', 'Office', 'Address', 'Role'])

    law = tls_solicitors
    newd = law['Role'].str.split('\n', n=3, expand = True)
    law['Primary_Role'] = newd[0]
    law['Secondary_Role'] = newd[1]
    law['Other_Role'] = newd[2]
    law['Other_Role_1'] = newd[3]
    law['Other_Role_2'] = ''
    law['Other_Role_3'] = ''
    law['Other_Role_4'] = ''
    newlaw = law.drop('Role', axis=1)
    return newlaw

然后我编辑了views.py以调用该函数并将其保存为变量数据（data = get_scraped_data（））。

from django.shortcuts import render
from .tls import get_scraped_data
from django.http import HttpResponse


def law_view(request, *args, **kwargs):
     data = get_scraped_data()
     return render(request, "law.html", {'data': data})

在我尝试显示数据的过程中，我创建了一个模板'law.html'并插入了此代码。

<table class="table table-striped">
    <thead>
      <tr>
          {% for row in data %}
        <th>{{ row }}</th>
            {% endfor %}
      </tr>
    </thead>
    <tbody>
        <tr> 
            {% for data in data %}
        <td>{{ data }}</td>
            {% endfor %}
        </tr>
    </tbody>
</table>

这里的问题是只显示DataFrame newlaw的标题。对于前者

Solicitor_name，Office，Address等。

我也尝试了{{data}}，这显示了我想要的东西，但我似乎无法找到一种方法来操纵数据并将其放入表中，以便更令人愉悦。

我会喜欢一些帮助。