st.header('■t-test')

st.write('To compare the results of two tests. e.g., examine the difference in performance by teaching method.')

st.sidebar.subheader('Data Upload')

df_edu = pd.read_csv("data/eng_sample_data_t_test.csv")

def download_link(object_to_download, download_filename, download_link_text):

if isinstance(object_to_download,pd.DataFrame):

object_to_download = object_to_download.to_csv(index=False, encoding = 'utf_8_sig')

b64 = base64.b64encode(object_to_download.encode()).decode()

return f'<a href="data:file/txt;base64,{b64}" download="{download_filename}">{download_link_text}</a>'

tmp_download_link = download_link(df_edu, 'sample_ttest.csv', 'Download sample csv file.')

st.sidebar.markdown(tmp_download_link, unsafe_allow_html=True)

# st.sidebar.info("""

# [Download the sample csv file](https://github.com/59er/eng_learning_analytics_web/blob/master/sample_data/eng_sample_data_t_test_for_WEB.csv)

# """)

uploaded_file = st.sidebar.file_uploader("File upload (Drag and drop or use [Browse files] button to import csv file. Only utf-8 format is available.)", type=["csv"])

# uploaded_file = st.file_uploader(

# label = 'File Upload（Drag and drop csv/Excel）',

# type = ['csv', 'xlsx']

# )

try:

if uploaded_file is not None:

df_edu = pd.read_csv(uploaded_file)

uploaded_file.seek(0)

display_data = st.sidebar.checkbox(label = 'Show uploaded data')

if display_data:

st.dataframe(df_edu)

else:

df_edu = pd.read_csv('data/eng_sample_data_t_test.csv')

show_df = st.sidebar.checkbox('Show DataFrame')

if show_df == True:

st.write(df_edu)

A_var = np.var(df_edu.iloc[:,0], ddof = 1)

B_var = np.var(df_edu.iloc[:,1], ddof = 1)

A_df = len(df_edu) - 1

B_df = len(df_edu) - 1

f = A_var/B_var

one_sided_pval1 = stats.f.cdf(f,A_df,B_df)

one_sided_pval2 = stats.f.sf(f,A_df,B_df)

two_sided_pval = min(one_sided_pval1, one_sided_pval2)

st.subheader("Confirmation of equality of variance between two groups (p-value < 0.05 for unequal variance (Welch's t-test was applied)),\

Equal variances at p-value > 0.05 (Student's t-test applied))")

dist = round(two_sided_pval,3)

st.write('F ', round(f,3))

st.write('p-value:', round(two_sided_pval,3))

if dist < 0.05:

result_w = stats.ttest_ind(df_edu.iloc[:,0], df_edu.iloc[:,1])

st.subheader('t-test results (welch)')

st.write(result_w)

else:

result_s = stats.ttest_ind(df_edu.iloc[:,0],df_edu.iloc[:,1])

st.subheader('t-test results (Student)')

st.write(result_s)

st.set_option('deprecation.showPyplotGlobalUse', False)

st.write(sns.catplot(x = 'variable', y = 'value', kind = 'box',data = pd.melt(df_edu)))

plt.title('Comparison between the two groups', fontsize = 15)

plt.show()

st.pyplot()

except Exception as e:

st.header('ERROR: Data inconsistency. Check data format to be uploaded.')