def law_types_time_series_json(_):
data, types_total = analysis_manager.get_analysis("law_types_time_series")
total_documents = sum(types_total.values())
types_time_series = {}
total_presented = 0
for type_name in sorted(types_total, key=types_total.get, reverse=True)[:17]:
count = types_total[type_name]
types_time_series[type_name] = {"values": [], "key": type_name, "total": count}
total_presented += count
# create a special entry for "others"
# we don't translate 'Outros' since no type is translated to English.
others_time_series = {"values": [], "key": "Outros", "total": total_documents - total_presented}
# populate the values from the analysis
for entry in data:
# append a new entry for this time-point
for type_name in types_time_series:
types_time_series[type_name]["values"].append({"year": entry["from"].strftime("%Y"), "value": 0})
others_time_series["values"].append({"year": entry["from"].strftime("%Y"), "value": 0})
# add value to type or "others"
for type_name in entry["value"]:
if type_name == "Total":
continue
value = entry["value"][type_name]
if type_name in types_time_series:
types_time_series[type_name]["values"][-1]["value"] += value
else:
others_time_series["values"][-1]["value"] += value
# sort them by total
types_time_series = list(types_time_series.values())
types_time_series = sorted(types_time_series, key=lambda x: x["total"], reverse=True)
# and finally, append the "Others" in the end of the list
types_time_series.append(others_time_series)
return HttpResponse(json.dumps(types_time_series), content_type="application/json")
def law_types_time_series_json(_):
data, types_total = analysis_manager.get_analysis('law_types_time_series')
total_documents = sum(types_total.values())
types_time_series = {}
total_presented = 0
for type_name in sorted(types_total, key=types_total.get,
reverse=True)[:17]:
count = types_total[type_name]
types_time_series[type_name] = {
'values': [],
'key': type_name,
'total': count
}
total_presented += count
# create a special entry for "others"
# we don't translate 'Outros' since no type is translated to English.
others_time_series = {
'values': [],
'key': 'Outros',
'total': total_documents - total_presented
}
# populate the values from the analysis
for entry in data:
# append a new entry for this time-point
for type_name in types_time_series:
types_time_series[type_name]['values'].append({
'year':
entry['from'].strftime('%Y'),
'value':
0
})
others_time_series['values'].append({
'year':
entry['from'].strftime('%Y'),
'value':
0
})
# add value to type or "others"
for type_name in entry['value']:
if type_name == 'Total':
continue
value = entry['value'][type_name]
if type_name in types_time_series:
types_time_series[type_name]['values'][-1]['value'] += value
else:
others_time_series['values'][-1]['value'] += value
# sort them by total
types_time_series = list(types_time_series.values())
types_time_series = sorted(types_time_series,
key=lambda x: x['total'],
reverse=True)
# and finally, append the "Others" in the end of the list
types_time_series.append(others_time_series)
return HttpResponse(json.dumps(types_time_series),
content_type="application/json")
def law_types_time_series_json(request):
data = analysis_manager.get_analysis('law_types_time_series')
return HttpResponse(json.dumps(data), content_type="application/json")
