View in the BP2C Reviews app (Django) to display descriptive statistics for the different answers in the survey for a company

view_stats.py

from django.http import HttpResponseRedirect, HttpResponse
from django.shortcuts import render
from django.urls import reverse
from django.contrib.auth.decorators import login_required
from django.contrib import messages
from django.contrib.auth import get_user
from django.db.models import Max, Avg, Count
from .models import ReviewInstance, Criteria,Contact
from .choices import CATEGORIES

import numpy as np
import pandas as pd
from bokeh.plotting import figure, output_file, show
from bokeh.embed import components

def get_plot(series):
    p = figure(plot_height = 300, plot_width = 400, title = "", x_axis_label = 'Calificación', y_axis_label = '# de respuestas')
    p.xaxis.ticker = list(range(1,11))
    hist, edges = np.histogram(series, range=(0.5,10.5))
    p.quad(bottom=0, top=hist, left=edges[:-1], right=edges[1:], line_color='#c0c0c0')
    return p

def make_category_tree():
    tree = []
    for cat_key, cat_name in CATEGORIES:
        criterias = Criteria.objects.filter(category=cat_key)
        criteria_list = []
        for c in criterias:
            crit_obj = {
                'machineName' : c.machineName,
                'description' : c.description,
            }
            criteria_list.append(crit_obj)

        cat_obj = {
            'title' : cat_name,            
            'criteria_list' : criteria_list,
        }
        tree.append(cat_obj)
    return tree   

def fill_criteria_stats():
    return

@login_required
def results_report(request, revId):

    try:
        user_company = Contact.objects.get(user=get_user(request)).company
    except Contact.DoesNotExist:
        user_company = False

    revInstance = ReviewInstance.objects.get(id=revId)    
    if(revInstance.company != user_company and not request.user.is_staff):
        messages.warning(request, 'No tienes permiso para ver evaluaciones de esta empresa.')
        return HttpResponseRedirect(reverse('reviews:error', args=())) 

    from django.db import connection
    import pandas as pd
    query_text = "SELECT * from reviews_view_answers where verified is not False and review_id = {}".format(revId)
    df = pd.read_sql(query_text, connection.connection)

    score_sum = 0
    tree = make_category_tree()
    plots = {}

# Because of how components() works, we need to go through the tree twice. 
# First time to set fields and generate the plots, 
    for cat in tree:
        for c in cat['criteria_list']:
            name = c['machineName']
            c['count'] = df[name].count()
            c['median'] = df[name].median()
            try:
                c['mode'] = int(df[name].mode()[0])
            except IndexError:
                c['mode'] = 0
            c['mean'] = df[name].mean()
            plots[name] = get_plot(df[name])

# Once we have all the plots we call components()
    script, divs = components(plots)

# Once we have the divs, we go through the list again to set them for each criteria.
# Since we have all the medians, we can also do the average.
    for cat in tree:
        median_sum = 0        
        for c in cat['criteria_list']:
            name = c['machineName']
            c['div'] = divs[name]
            median_sum += c['median']
        cat['score'] = round(median_sum * 10 / len(cat['criteria_list']),0)
        score_sum += cat['score']

    context = {
        'rev_instance' : revInstance,
        'count' : df['id'].count(),
        'score' : round(score_sum / len(tree),0),
        'script' : script,
        'results_tree' : tree
    }

    return render(request, 'results_report.html', context)

# This view should only be accesible to logged in users.
@login_required
def results_xls(request, revId):

    try:
        user_company = Contact.objects.get(user=get_user(request)).company
    except Contact.DoesNotExist:
        user_company = False

    revInstance = ReviewInstance.objects.get(id=revId)    
    if(revInstance.company != user_company and not request.user.is_staff):
        messages.warning(request, 'No tienes permiso para ver evaluaciones de esta empresa.')
        return HttpResponseRedirect(reverse('reviews:error', args=())) 

    from django.db import connection
    import pandas as pd
    query_text = "SELECT * from reviews_view_answers where verified is not False and review_id = {}".format(revId)
    df = pd.read_sql(query_text, connection.connection)

    score_sum = 0
    tree = make_category_tree()
    plots = {}

    for cat in tree:
        median_sum = 0
        for c in cat['criteria_list']:
            name = c['machineName']
            c['count'] = int(df[name].count())
            try:
                c['median'] = int(df[name].median())
            except ValueError:
                c['median'] = 0 
            try:
                c['mode'] = int(df[name].mode()[0])
            except IndexError:
                c['mode'] = 0
            c['mean'] = round(df[name].mean(),1)
            c['std'] = round(df[name].std(),1)
            median_sum += c['median']
        cat['score'] = int(round(median_sum * 10 / len(cat['criteria_list']),0))
        score_sum += cat['score']


    # Create the HttpResponse object with the appropriate CSV header.
    response = HttpResponse(content_type='application/ms-excel')
    response['Content-Disposition'] = 'attachment; filename="bestplacetocode-resultados.xls"'

    import xlwt

    wb = xlwt.Workbook(encoding='utf-8')
    ws = wb.add_sheet('Resumen')

    normal = xlwt.easyxf()
    bold = xlwt.easyxf("font: bold on")
    big = xlwt.easyxf("font: height 320")

    row_num = 0    
    ws.write(row_num, 0, str(revInstance), big)
    row_num += 1
    ws.write(row_num,0,'Respuestas', normal)
    ws.write(row_num,1,int(round(df['id'].count(),0)), normal)
    row_num += 1
    ws.write(row_num,0,'Calificación global', normal)
    ws.write(row_num,1, int(round(score_sum / len(tree),0)), normal)

    for cat in tree:
        row_num += 1
        ws.write(row_num, 0, cat['title'], normal)
        ws.write(row_num, 1, cat['score'], normal)

    ws = wb.add_sheet('Detalles')

    columns = ['Criterio', 'Categoria', 'Respuestas', 'Mediana', 'Moda', 'Promedio', 'Desviación estándar']

    row_num = 0
    for col_num in range(len(columns)):
        ws.write(row_num, col_num, columns[col_num], bold)

    for cat in tree:
        for c in cat['criteria_list']:
            row_num += 1
            ws.write(row_num,0,c['description'], normal)
            ws.write(row_num,1,cat['title'], normal)
            ws.write(row_num,2,c['count'], normal)
            ws.write(row_num,3,c['median'], normal)
            ws.write(row_num,4,c['mode'], normal)
            ws.write(row_num,5,c['mean'], normal)
            ws.write(row_num,6,c['std'], normal)
             

    wb.save(response)
    return response