import pandas as pd
# read data from etf_returns.csv.
etf_returns_df = pd.read_csv('etf_returns.csv')
# print etf returns data set.
print(etf_returns_df) financial energy technology
0 5.5 5.2 7.3
1 7.1 7.4 8.2
2 6.9 6.6 7.1
3 5.1 5.7 7.6
4 4.6 5.6 8.2
5 5.3 5.5 11.5
6 5.9 6.4 9.2
7 5.6 6.1 9.5
8 5.5 5.2 7.3
9 7.1 7.4 8.2
10 6.9 6.6 7.1
11 5.1 5.7 7.6
12 4.6 5.6 8.2
13 5.3 5.5 11.5
14 5.9 6.4 9.2
15 5.6 6.1 9.5
16 4.7 4.4 6.2
17 6.4 6.6 7.4
18 6.7 6.4 6.9
19 4.3 4.8 6.4
20 4.1 5.0 7.4
21 5.1 5.3 11.1
22 5.7 6.2 8.9
23 4.7 5.2 8.1
24 5.3 5.0 7.1
25 6.4 6.6 7.4
26 5.8 5.6 6.0
27 4.9 5.5 7.4
28 4.1 5.0 7.4
29 4.8 4.9 10.3
import scipy.stats as st
# save return data for individual sectors for input to f_oneway method.
etf_returns_financial = etf_returns_df['financial']
etf_returns_energy = etf_returns_df['energy']
etf_returns_technology = etf_returns_df['technology']
# print the outputs: the test statistic and the P-value.
test_statistic, p_value = st.f_oneway(etf_returns_financial, etf_returns_energy, etf_returns_technology)
print("test statistic =", round(test_statistic,2))
print("P-value =", round(p_value,4))test statistic = 55.07
P-value = 0.0
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import random
# side-by-side boxplots require the three dataframes to be concatenated and a require variable identifying the type of ETF.
etf_returns_financial_df = etf_returns_df[['financial']]
etf_returns_financial_df = etf_returns_financial_df.rename(columns={"financial": "return"})
etf_returns_financial_df['ETF'] = 'financial'
etf_returns_energy_df = etf_returns_df[['energy']]
etf_returns_energy_df = etf_returns_energy_df.rename(columns={"energy": "return"})
etf_returns_energy_df['ETF'] = 'energy'
etf_returns_technology_df = etf_returns_df[['technology']]
etf_returns_technology_df = etf_returns_technology_df.rename(columns={"technology": "return"})
etf_returns_technology_df['ETF'] = 'technology'
# concatenate dataframes for the three ETFs.
all_etfs_df = pd.concat((etf_returns_financial_df, etf_returns_energy_df, etf_returns_technology_df))
# set a title for the plot, x-axis, and y-axis.
plt.title('Boxplot for comparison', fontsize=20)
# prepare the boxplot.
sns.boxplot(x="ETF",y="return",data=all_etfs_df)
# show the plot.
plt.show()
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