<jupyter_start><jupyter_text>Simulations for Maine RCV Election Trials: 1000 sample size: 100,500,1000 n: 132250<jupyter_code>import pandas as pd
df_100 = pd.read_csv("audit_simulations_sample_size_100.csv")
df_500 = pd.read_csv("audit_simulations_sample_size_500.csv")
df_1000 = pd.read_csv("audit_simulations_sample_size_1000.csv")
df_100.__delitem__('Unnamed: 0')
df_500.__delitem__('Unnamed: 0')
df_1000.__delitem__('Unnamed: 0')<jupyter_output><empty_output><jupyter_text>Table below describes the win probability and time for each simulation<jupyter_code>df_100.describe()
df_500.describe()
df_1000.describe()<jupyter_output><empty_output><jupyter_text>Visual Distribution of Win Probability Across Seed<jupyter_code>ax = df_100[df_100.columns[:-2]].plot(title="Win Probability Per Candidate",figsize=(20, 10),marker='.',lw=0, markersize=10,fontsize=20)
ax.title.set_size(25)
ax.set_xlabel("Simulation / Seed",fontsize=20)
ax.set_ylabel("Win Probability",fontsize=20)
ax = df_500[df_500.columns[:-2]].plot(title="Win Probability Per Candidate",figsize=(20, 10),marker='.',lw=0, markersize=10,fontsize=20)
ax.title.set_size(25)
ax.set_xlabel("Simulation / Seed",fontsize=20)
ax.set_ylabel("Win Probability",fontsize=20)
ax = df_1000[df_1000.columns[:-2]].plot(title="Win Probability Per Candidate",figsize=(20, 10),marker='.',lw=0, markersize=10,fontsize=20)
ax.title.set_size(25)
ax.set_xlabel("Simulation / Seed",fontsize=20)
ax.set_ylabel("Win Probability",fontsize=20)<jupyter_output><empty_output>
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