def group_compare(request):
cluster = get_object_or_404(Cluster, pk=3)
#load csv into pandas.DataFrame
dic = rc.filter_by_cluster(utils.get_whole_survey(), cluster)
df = dic['df']
size_str = "%d / %d" % (len(df.index), dic['orig_size'])
clusters_dict = clustering.get_subclusters_length(cluster, dic['df'])
#load questions textfile into list
file2_ = open(
os.path.join(settings.BASE_DIR, 'clusters/RSQquestionchoices.txt'))
dic_source = rt.read(file2_)
about = dic_source['about']
questions_txt = dic_source['questions']
file2_.close()
#get cluster questions as strings
questions_strs = get_questions_as_str(questions_txt)
#get charts
charts = get_charts(df, questions_txt, cluster, 'a')
context = {
'cluster': cluster,
'charts': charts,
#'compare_chart': compare_chart,
'df_size': size_str, #no of rows in df
'questions_strs': questions_strs,
'about': about,
'subcluster_values': list(clusters_dict.values()),
'num_of_clusters': cluster.num_of_clusters,
'compare': False,
}
return render(request, 'clusters/group_compare.html', context)
def subclusters_list(request, cluster_id):
cluster = get_object_or_404(Cluster, pk=cluster_id)
dic = rc.filter_by_cluster(dataframeAll, cluster)
clusters_dict = clustering.get_subclusters(cluster, dic['df'])
context = {
'cluster_id': cluster_id,
'subcluster_values': list(clusters_dict.values()),
}
return render(request, 'clusters/subcluster_list.html', context)
def json3(request, cluster_id, question_id):
cluster = get_object_or_404(Cluster, pk=cluster_id)
#load csv into pandas.DataFrame
dic = rc.filter_by_cluster(utils.get_whole_survey(), cluster)
df = dic['df']
output = rc2.get_data_for_map3(df, question_id)
return JsonResponse(output, safe=False)
def increase_num_of_clusters(request, cluster_id):
cluster = get_object_or_404(Cluster, pk=cluster_id)
cluster.num_of_clusters += 1
cluster.save()
dic = rc.filter_by_cluster(dataframeAll, cluster)
clustering.get_subclusters(cluster, dic['df'], refresh=True)
print "increased_num_of_clusters"
return redirect('/clusters/' + cluster_id + '/stats')
def json2(request, cluster_id, subcluster_id, question_id, choice_id):
""" creates json for map change
"""
cluster = get_object_or_404(Cluster, pk=cluster_id)
#load csv into pandas.DataFrame
dic = rc.filter_by_cluster(utils.get_whole_survey(), cluster)
df = dic['df']
if subcluster_id != 'a': #if is subcluster, then filter subcluster
tempdf = clustering.get_subcluster_list(cluster, df)
df = clustering.filter_by_subcluster(tempdf, subcluster_id)
output = rc2.get_data_for_map2(df, question_id, choice_id)
return JsonResponse(output, safe=False)
def json1(request, cluster_id, subcluster_id):
""" used for map """
cluster = get_object_or_404(Cluster, pk=cluster_id)
#load csv into pandas.DataFrame
dic = rc.filter_by_cluster(utils.get_whole_survey(), cluster)
df = dic['df']
if subcluster_id != 'a':
df = clustering.get_subclusters(cluster, df)[int(subcluster_id)]
#load questions textfile into list
file2_ = open(
os.path.join(settings.BASE_DIR, 'clusters/RSQquestionchoices.txt'))
dic_source = rt.read(file2_)
about = dic_source['about']
questions_txt = dic_source['questions']
file2_.close()
output = rc2.get_data_for_map(df, questions_txt['WARD'])
return JsonResponse(output, safe=False)
def detail(request, cluster_id):
cluster = get_object_or_404(Cluster, pk=cluster_id)
#load csv into pandas.DataFrame
dic = rc.filter_by_cluster(utils.get_whole_survey(), cluster)
df = dic['df']
group_size = len(df.index)
survey_size = dic['orig_size']
if group_size == 0:
return render(request, 'clusters/emptygroup.html',
{'cluster': cluster})
clusters_dict = clustering.get_subclusters_length(cluster, dic['df'])
#load questions textfile into list
file2_ = open(
os.path.join(settings.BASE_DIR, 'clusters/RSQquestionchoices.txt'))
dic_source = rt.read(file2_)
file2_.close()
about = dic_source['about']
questions_txt = dic_source['questions']
#get cluster questions as strings
questions_strs = get_questions_as_str(questions_txt)
#get charts
charts = get_charts(df, questions_txt, cluster, 'a')
context = {
'cluster': cluster,
'subcluster_id': 'a',
'charts': charts,
'group_size': group_size, #no of rows in df
'survey_size': survey_size,
'questions_strs': questions_strs,
'about': about,
'subcluster_values': list(clusters_dict.values()),
'num_of_clusters': cluster.num_of_clusters,
'compare': False,
}
return render(request, 'clusters/detail.html', context)
def subcluster_detail(request, cluster_id, subcluster_id):
cluster = get_object_or_404(Cluster, pk=cluster_id)
#load csv into pandas.DataFrame
dic = rc.filter_by_cluster(utils.get_whole_survey(), cluster)
df = dic['df']
df = clustering.get_subclusters(cluster, df)[0] #dicitonary
size_str = "%d / %d" % (len(df.index), dic['orig_size'])
clusters_dict = clustering.get_subclusters_length(cluster, dic['df'])
#load questions textfile into list
file2_ = open(
os.path.join(settings.BASE_DIR, 'clusters/RSQquestionchoices.txt'))
dic_source = rt.read(file2_)
about = dic_source['about']
questions_txt = dic_source['questions']
file2_.close()
#get cluster questions as strings
questions_strs = get_questions_as_str(questions_txt)
#get charts
charts = get_charts(df, questions_txt, cluster, subcluster_id)
context = {
'cluster': cluster,
'subcluster_id': subcluster_id,
'charts': charts,
'group_size': len(df.index), #no of rows in df
'survey_size': dic['orig_size'],
'questions_strs': questions_strs,
'about': about,
'subcluster_values': list(clusters_dict.values()),
'num_of_clusters': cluster.num_of_clusters,
'issubcluster': True,
}
return render(request, 'clusters/detail.html', context)
