def update_value_empty():
for candidate in models.data_reader.candidates:
c = models.return_index(candidate.name)
last_i = 0
for i in range(0, len(dates_graph)):
#Verifica se o candidato foi para o segundo turno
# if(i <= 21 or models.data_reader.candidates[c].round2 == True):
if (models.data_reader.candidates[c].facebook_male[i] == -100):
models.data_reader.candidates[c].facebook_male[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_male, last_i,
i)
models.data_reader.candidates[c].facebook_female[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_female,
last_i, i)
models.data_reader.candidates[c].facebook_16a24[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_16a24,
last_i, i)
models.data_reader.candidates[c].facebook_25a34[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_25a34,
last_i, i)
models.data_reader.candidates[c].facebook_35a44[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_35a44,
last_i, i)
models.data_reader.candidates[c].facebook_45a54[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_45a54,
last_i, i)
models.data_reader.candidates[c].facebook_55[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_55, last_i,
i)
models.data_reader.candidates[c].facebook_norte_coeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_norte_coeste,
last_i, i)
models.data_reader.candidates[c].facebook_nordeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_nordeste,
last_i, i)
models.data_reader.candidates[c].facebook_sudeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_sudeste,
last_i, i)
models.data_reader.candidates[c].facebook_sul[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_sul, last_i,
i)
models.data_reader.candidates[c].facebook_fundamental[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_fundamental,
last_i, i)
models.data_reader.candidates[c].facebook_medio[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_medio,
last_i, i)
models.data_reader.candidates[c].facebook_superior[
i] = return_new_value_graph(
models.data_reader.candidates[c].facebook_superior,
last_i, i)
else:
last_i = i
def read_json(comLula):
if (comLula == True):
with open(os.getcwd() +
'\..\Data\PresidentialElection-ComLula.json') as js:
poolElection = json.load(js)
else:
with open(os.getcwd() +
'\..\Data\PresidentialElection-SemLula.json') as js:
poolElection = json.load(js)
for data in poolElection['elections_poll']:
for candidate in data['candidates']:
i = models.return_index(candidate['name'])
if (i >= 0):
if (data['institute'] == 'DataFolha'
or data['institute'] == 'Resultado'):
if (data["date"] in data_dfolha):
models.data_reader.candidates[i].dfolha_male.append(
candidate['gender']['male'])
models.data_reader.candidates[i].dfolha_female.append(
candidate['gender']['female'])
models.data_reader.candidates[i].dfolha_16a24.append(
candidate['age_intervals']['age_16_24'])
models.data_reader.candidates[i].dfolha_25a34.append(
candidate['age_intervals']['age_25_34'])
models.data_reader.candidates[i].dfolha_35a44.append(
candidate['age_intervals']['age_35_44'])
models.data_reader.candidates[i].dfolha_45a54.append(
candidate['age_intervals']['age_45_54'])
models.data_reader.candidates[i].dfolha_55.append(
candidate['age_intervals']['above_55'])
models.data_reader.candidates[
i].dfolha_norte_coeste.append(
candidate['regions']['north_midwest'])
models.data_reader.candidates[
i].dfolha_nordeste.append(
candidate['regions']['northeast'])
models.data_reader.candidates[i].dfolha_sudeste.append(
candidate['regions']['southeast'])
models.data_reader.candidates[i].dfolha_sul.append(
candidate['regions']['south'])
models.data_reader.candidates[
i].dfolha_fundamental.append(
candidate['education_status']
['elementary_school'])
models.data_reader.candidates[i].dfolha_medio.append(
candidate['education_status']['high_school'])
models.data_reader.candidates[i].dfolha_superior.append(
candidate['education_status']['higher_education'])
models.data_reader.candidates[i].dfolha_score.append(
candidate['score'])
if (data['institute'] == 'IBOPE'
or data['institute'] == 'Resultado'):
if (data["date"] in data_ibope):
models.data_reader.candidates[i].ibope_male.append(
candidate['gender']['male'])
models.data_reader.candidates[i].ibope_female.append(
candidate['gender']['female'])
models.data_reader.candidates[i].ibope_16a24.append(
candidate['age_intervals']['age_16_24'])
models.data_reader.candidates[i].ibope_25a34.append(
candidate['age_intervals']['age_25_34'])
models.data_reader.candidates[i].ibope_35a44.append(
candidate['age_intervals']['age_35_44'])
models.data_reader.candidates[i].ibope_45a54.append(
candidate['age_intervals']['age_45_54'])
models.data_reader.candidates[i].ibope_55.append(
candidate['age_intervals']['above_55'])
models.data_reader.candidates[
i].ibope_norte_coeste.append(
candidate['regions']['north_midwest'])
models.data_reader.candidates[i].ibope_nordeste.append(
candidate['regions']['northeast'])
models.data_reader.candidates[i].ibope_sudeste.append(
candidate['regions']['southeast'])
models.data_reader.candidates[i].ibope_sul.append(
candidate['regions']['south'])
models.data_reader.candidates[
i].ibope_fundamental.append(
candidate['education_status']
['elementary_school'])
models.data_reader.candidates[i].ibope_medio.append(
candidate['education_status']['high_school'])
models.data_reader.candidates[i].ibope_superior.append(
candidate['education_status']['higher_education'])
models.data_reader.candidates[i].ibope_score.append(
candidate['score'])
# #Repete o resultado da eleição no próximo ponto
# if(data['institute'] == 'Resultado'):
# if(data["round"] == 1 and (candidate['name'] == "Jair Bolsonaro" or candidate['name'] == "Fernando Haddad")):
# models.data_reader.candidates[i].ibope_male.append(models.data_reader.candidates[i].ibope_male[-1])
# models.data_reader.candidates[i].ibope_female.append(models.data_reader.candidates[i].ibope_female[-1])
# models.data_reader.candidates[i].ibope_16a24.append(models.data_reader.candidates[i].ibope_16a24[-1])
# models.data_reader.candidates[i].ibope_25a34.append(models.data_reader.candidates[i].ibope_25a34[-1])
# models.data_reader.candidates[i].ibope_35a44.append(models.data_reader.candidates[i].ibope_35a44[-1])
# models.data_reader.candidates[i].ibope_45a54.append(models.data_reader.candidates[i].ibope_45a54[-1])
# models.data_reader.candidates[i].ibope_55.append(models.data_reader.candidates[i].ibope_55[-1])
# models.data_reader.candidates[i].ibope_norte_coeste.append(models.data_reader.candidates[i].ibope_norte_coeste[-1])
# models.data_reader.candidates[i].ibope_nordeste.append(models.data_reader.candidates[i].ibope_nordeste[-1])
# models.data_reader.candidates[i].ibope_sudeste.append(models.data_reader.candidates[i].ibope_sudeste[-1])
# models.data_reader.candidates[i].ibope_sul.append(models.data_reader.candidates[i].ibope_sul[-1])
# models.data_reader.candidates[i].ibope_fundamental.append(models.data_reader.candidates[i].ibope_fundamental[-1])
# models.data_reader.candidates[i].ibope_medio.append(models.data_reader.candidates[i].ibope_medio[-1])
# models.data_reader.candidates[i].ibope_superior.append(models.data_reader.candidates[i].ibope_superior[-1])
models.complete_data_zero()
def update_value_empty():
for candidate in models.data_reader.candidates:
c = models.return_index(candidate.name)
last_i_dfolha = 0
last_i_ibope = 0
for i in range(0, len(dates_graph)):
#Verifica se o candidato foi para o segundo turno
if (i <= 21 or models.data_reader.candidates[c].round2 == True):
#DataFolha
if (models.data_reader.candidates[c].dfolha_male[i] == -100):
models.data_reader.candidates[c].dfolha_male[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_male,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_female[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_female,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_16a24[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_16a24,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_25a34[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_25a34,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_35a44[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_35a44,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_45a54[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_45a54,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_55[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_55,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_norte_coeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].
dfolha_norte_coeste, last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_nordeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_nordeste,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_sudeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_sudeste,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_sul[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_sul,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_fundamental[
i] = return_new_value_graph(
models.data_reader.candidates[c].
dfolha_fundamental, last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_medio[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_medio,
last_i_dfolha, i)
models.data_reader.candidates[c].dfolha_superior[
i] = return_new_value_graph(
models.data_reader.candidates[c].dfolha_superior,
last_i_dfolha, i)
else:
last_i_dfolha = i
#IBOPE
if (models.data_reader.candidates[c].ibope_male[i] == -100):
models.data_reader.candidates[c].ibope_male[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_male,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_female[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_female,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_16a24[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_16a24,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_25a34[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_25a34,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_35a44[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_35a44,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_45a54[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_45a54,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_55[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_55,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_norte_coeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].
ibope_norte_coeste, last_i_ibope, i)
models.data_reader.candidates[c].ibope_nordeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_nordeste,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_sudeste[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_sudeste,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_sul[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_sul,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_fundamental[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_fundamental,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_medio[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_medio,
last_i_ibope, i)
models.data_reader.candidates[c].ibope_superior[
i] = return_new_value_graph(
models.data_reader.candidates[c].ibope_superior,
last_i_ibope, i)
else:
last_i_ibope = i
import models
import os
import numpy as np
import subprocess
# xticks = ["17\n11", "18\n07", "08\n06", "09\n10", "09\n17", "09\n24", "10\n01", "10\n05", "10\n06", "10\n08", "10\n15", "10\n22", "10\n26", "10\n27", "10\n29"]
xticks = [
"10\n22", "11\n28", "11\n30", "06\n07", "06\n24", "07\n09", "08\n06",
"08\n19", "08\n21", "09\n10", "09\n17", "09\n18", "09\n24", "09\n28",
"09\n30", "10\n01", "10\n02", "10\n04", "10\n05", "10\n06", "10\n07",
"10\n08", "10\n10", "10\n14", "10\n15", "10\n18", "10\n22", "10\n23",
"10\n25", "10\n26", "10\n27", "10\n28", "10\n29"
]
i_bolsonaro = models.return_index("Jair Bolsonaro")
i_haddad = models.return_index("Fernando Haddad")
i_lula = models.return_index("Lula")
i_ciro = models.return_index("Ciro Gomes")
i_marina = models.return_index("Marina Silva")
i_alckmin = models.return_index("Geraldo Alckmin")
i_alvaro = models.return_index("Alvaro Dias")
v_index = [
i_bolsonaro, i_haddad, i_ciro, i_marina, i_alckmin, i_marina, i_alvaro
]
error_facebook_1round = []
error_dfolha_1round = []
error_ibope_1round = []
def read_json(comLula):
set_empty = True
if (comLula == True):
with open(os.getcwd() +
'\Graphics\Data\PresidentialElection-ComLula.json') as js:
poolElection = json.load(js)
else:
with open(os.getcwd() +
'\Graphics\Data\PresidentialElection-SemLula.json') as js:
poolElection = json.load(js)
for date in dates_graph:
vec_data = return_election_by_date(poolElection, date)
set_empty = True
if (len(vec_data) > 1):
set_empty = False
for data in vec_data:
for candidate in data['candidates']:
i = models.return_index(candidate['name'])
if (i >= 0):
if (data['institute'] == 'DataFolha'
or data['institute'] == 'Resultado'):
models.data_reader.candidates[i].dfolha_male.append(
candidate['gender']['male'])
models.data_reader.candidates[i].dfolha_female.append(
candidate['gender']['female'])
models.data_reader.candidates[i].dfolha_16a24.append(
candidate['age_intervals']['age_16_24'])
models.data_reader.candidates[i].dfolha_25a34.append(
candidate['age_intervals']['age_25_34'])
models.data_reader.candidates[i].dfolha_35a44.append(
candidate['age_intervals']['age_35_44'])
models.data_reader.candidates[i].dfolha_45a54.append(
candidate['age_intervals']['age_45_54'])
models.data_reader.candidates[i].dfolha_55.append(
candidate['age_intervals']['above_55'])
models.data_reader.candidates[
i].dfolha_norte_coeste.append(
candidate['regions']['north_midwest'])
models.data_reader.candidates[
i].dfolha_nordeste.append(
candidate['regions']['northeast'])
models.data_reader.candidates[i].dfolha_sudeste.append(
candidate['regions']['southeast'])
models.data_reader.candidates[i].dfolha_sul.append(
candidate['regions']['south'])
models.data_reader.candidates[
i].dfolha_fundamental.append(
candidate['education_status']
['elementary_school'])
models.data_reader.candidates[i].dfolha_medio.append(
candidate['education_status']['high_school'])
models.data_reader.candidates[i].dfolha_superior.append(
candidate['education_status']['higher_education'])
elif (set_empty):
set_value_empty(True, i)
if (data['institute'] == 'IBOPE'
or data['institute'] == 'Resultado'):
models.data_reader.candidates[i].ibope_male.append(
candidate['gender']['male'])
models.data_reader.candidates[i].ibope_female.append(
candidate['gender']['female'])
models.data_reader.candidates[i].ibope_16a24.append(
candidate['age_intervals']['age_16_24'])
models.data_reader.candidates[i].ibope_25a34.append(
candidate['age_intervals']['age_25_34'])
models.data_reader.candidates[i].ibope_35a44.append(
candidate['age_intervals']['age_35_44'])
models.data_reader.candidates[i].ibope_45a54.append(
candidate['age_intervals']['age_45_54'])
models.data_reader.candidates[i].ibope_55.append(
candidate['age_intervals']['above_55'])
models.data_reader.candidates[
i].ibope_norte_coeste.append(
candidate['regions']['north_midwest'])
models.data_reader.candidates[i].ibope_nordeste.append(
candidate['regions']['northeast'])
models.data_reader.candidates[i].ibope_sudeste.append(
candidate['regions']['southeast'])
models.data_reader.candidates[i].ibope_sul.append(
candidate['regions']['south'])
models.data_reader.candidates[
i].ibope_fundamental.append(
candidate['education_status']
['elementary_school'])
models.data_reader.candidates[i].ibope_medio.append(
candidate['education_status']['high_school'])
models.data_reader.candidates[i].ibope_superior.append(
candidate['education_status']['higher_education'])
elif (set_empty):
set_value_empty(False, i)
if (len(vec_data) == 0):
for candidate in models.data_reader.candidates:
set_value_empty(True, models.return_index(candidate.name))
set_value_empty(False, models.return_index(candidate.name))
else:
achou = False
#Seta empty nos candidatos que não estão na pesquisa
for data in vec_data:
for candidate in models.data_reader.candidates:
for c in data['candidates']:
if candidate.name == c["name"]:
achou = True
break
if (achou == False):
set_value_empty(True,
models.return_index(candidate.name))
set_value_empty(False,
models.return_index(candidate.name))
else:
achou = False
break
update_value_empty()