!pip install researchpy==0.3.2

import pandas as pd import numpy as np import matplotlib.pyplot as plt import researchpy as rp import scipy.stats as stats import statsmodels.api as sm

# Loading in the files df_appr = pd.read_csv('voting_sim approval voting-table.csv',index_col = 0,sep=',') df_plur = pd.read_csv('voting_sim plurality voting-table.csv',index_col = 0,sep=',') df_appr_strat = pd.read_csv('voting_sim approval strategic voting-table.csv',index_col = 0,sep=',') df_plur_strat = pd.read_csv('voting_sim plurality voting strategic-table.csv',index_col = 0,sep=',')

# Renaming the columns: df_appr = df_appr.rename(columns={'count links with [color = red]': df_appr.iloc[0][0],\ 'count links with [color = green]': df_appr.iloc[0][1],\ 'count links with [color = blue]': df_appr.iloc[0][2],\ 'count turtles with [color = black]': 'Geen stem'}) df_appr_strat = df_appr_strat.rename(columns={'count links with [color = red]': df_appr_strat.iloc[0][0],\ 'count links with [color = green]': df_appr_strat.iloc[0][1],\ 'count links with [color = blue]': df_appr_strat.iloc[0][2],\ 'count turtles with [color = black]': 'Geen stem'}) df_plur = df_plur.rename(columns={'count turtles with [color = red]': df_plur.iloc[0][0],\ 'count turtles with [color = green]': df_plur.iloc[0][1],\ 'count turtles with [color = blue]': df_plur.iloc[0][2]}) df_plur_strat = df_plur_strat.rename(columns={'count turtles with [color = red]': df_plur_strat.iloc[0][0],\ 'count turtles with [color = green]': df_plur_strat.iloc[0][1],\ 'count turtles with [color = blue]': df_plur_strat.iloc[0][2]})

# Deleting the step before the voting has happened df_appr = df_appr[df_appr['[step]'] != 0] df_plur = df_plur[df_plur['[step]'] != 0]

# Dropping unnecessary columns df_appr = df_appr.drop(['partij1','partij2', 'partij3', 'number_of_voters', '[step]'], axis = 1) df_plur = df_plur.drop(['partij1','partij2', 'partij3', 'number_of_voters', '[step]'], axis = 1) df_appr_strat = df_appr_strat[df_appr_strat['[step]'] != 0] df_plur_strat = df_plur_strat[df_plur_strat['[step]'] != 0] df_appr_strat = df_appr_strat.drop(['partij1','partij2', 'partij3', 'number_of_voters', 'radius', 'third_vote','[step]'], axis = 1) df_plur_strat = df_plur_strat.drop(['partij1','partij2', 'partij3', 'number_of_voters', 'radius', '[step]'], axis = 1)

df_appr.head()

df_plur.head()

rp.ttest(group1= df_appr_strat['first_vote']['second_vote'], group1_name= 'Approval Strategic', group2= df_plur_strat['first_vote']['second_vote'], group2_name= 'Plurality Strategic')

# Get a summary of the values in df_appr_mean = df_appr.mean() df_plur_mean = df_plur.mean() summary, results = rp.ttest(group1= df_appr.mean(), group1_name= 'Approval', group2= df_plur.mean(), group2_name= 'Plurality')

summary

results

sampling_difference = df_appr_mean - \ df_plur_mean stats.shapiro(sampling_difference)

fig = plt.figure(figsize= (20, 10)) ax = fig.add_subplot(111) normality_plot, stat = stats.probplot(sampling_difference, plot= plt, rvalue= True) ax.set_title("Probability plot of sampling difference", fontsize= 20) ax.set plt.show()