Evolution du pourcentage de vote en fonction du pourcentage total de vote utile gagné par macron

main.py

from collections import OrderedDict
import numpy as np
import matplotlib.pyplot as plt
from pprint import pprint
# data source : https://fr.wikipedia.org/wiki/Liste_de_sondages_sur_l%27%C3%A9lection_pr%C3%A9sidentielle_fran%C3%A7aise_de_2017#Avril_2017
scores_fillon = [
    19.5,
    18.5,
    21,
    19,
    20,
    19,
    18.5,
    19,
    20,
    20
]

mean_fillon = np.mean(scores_fillon)

scores_lepen = [
    23,
    23,
    22,
    22,
    22,
    23,
    23,
    22,
    22,
    22
]
mean_lepen = np.mean(scores_lepen)

with open("raw.txt") as f:
    lines = f.readlines()

sanit_lines = []

for line in lines[1:]:
    elm = ''
    sanit_line = []
    for c in line:
        if c != r'%':
            elm += c
        elif c == r'%':
            token = elm.strip(' \t\n')
            token = token.replace(",", ".")
            token = token.replace("<0.5", "0.4")
            sanit_line.append(float(token))
            elm = ''
    sanit_lines.append(sanit_line)

arr = np.array(sanit_lines)
mean_arr = np.mean(arr, axis=0)

names = ['Nathalie Arthaud ',
         'Philippe Poutou',
         'Jean-Luc Mélenchon',
         'Benoît Hamon',
         'Emmanuel Macron']

ordered_mapping_name_mean = OrderedDict(zip(names, mean_arr))
pprint(ordered_mapping_name_mean)

probas_arr = np.empty_like(mean_arr[:-1])
score_total = sum(mean_arr[:-1])
for i in range(len(mean_arr[:-1])):
    probas_arr[i] = mean_arr[i] / score_total
print(probas_arr)


int_macorn_score = int(ordered_mapping_name_mean[names[-1]])
results = np.zeros((int_macorn_score, len(names)))
# each line, one set of horizontal points
for i in range(int_macorn_score):
    stolen_value_percent = i
    results[i, :-1] = (probas_arr * stolen_value_percent) + mean_arr[:-1]
    results[i, -1] = ordered_mapping_name_mean[names[-1]] - stolen_value_percent

for i in range(len(names)):
    plt.plot(range(int_macorn_score), list(results[:, i]), label=names[i])

plt.plot(range(int_macorn_score), [mean_fillon] * int_macorn_score, label='Fillon')
plt.plot(range(int_macorn_score), [mean_lepen] * int_macorn_score, label='Lepen')
plt.legend()
plt.xlabel("Pourcentage de vote utile pour Macron")
plt.ylabel("Evolution des intentions de votes des candidats (%)")

plt.savefig("result.png")

print(results)

raw.txt

0,5 % 	2 % 	18,5 % 	9 % 	23,5 %
<0,5 % 	1 % 	19 % 	8 % 	24 %
0,5 % 	2 % 	20 % 	7,5 % 	22 %
0 % 	1,5 % 	19 % 	8 % 	24,5 %
0,5 % 	2 % 	19 % 	8 % 	22,5 %
1 % 	1,5 % 	20 % 	7,5 % 	23 %
0,5 % 	2 % 	19,5 % 	8 % 	23 %
1 % 	2 % 	18 % 	8 % 	22 %
0,5 % 	2 % 	18 % 	8 % 	24 %
0,5 % 	2 % 	18 % 	8 % 	24 %