Update app.py
Browse files
app.py
CHANGED
@@ -98,7 +98,7 @@ if st.session_state['upload_count'] < max_attempts:
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fig1 = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
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values='score', color='label')
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fig1.update_layout(margin = dict(t=50, l=25, r=25, b=25))
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st.plotly_chart(fig1, key = "
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vectorizer = TfidfVectorizer()
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tfidf_matrix = vectorizer.fit_transform(result)
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tfidf_df = pd.DataFrame(tfidf_matrix.toarray(), columns=vectorizer.get_feature_names_out())
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@@ -116,7 +116,7 @@ if st.session_state['upload_count'] < max_attempts:
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fig2 = px.imshow(cosine_sim_df, text_auto=True, labels=dict(x="Cosine similarity", y="Text", color="Productivity"),
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x=['text1', 'Jon Description'],
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y=['text1', 'Job Description'])
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st.plotly_chart(fig2, key = "
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st.subheader("Cosine Similarity Scores (Job Description vs. Resumes):")
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for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
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@@ -164,7 +164,7 @@ if st.session_state['upload_count'] < max_attempts:
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fig3 = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
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values='score', color='label')
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fig3.update_layout(margin = dict(t=50, l=25, r=25, b=25))
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st.plotly_chart(fig3, key = "
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vectorizer = TfidfVectorizer()
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tfidf_matrix = vectorizer.fit_transform(result)
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@@ -183,7 +183,7 @@ if st.session_state['upload_count'] < max_attempts:
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fig4 = px.imshow(cosine_sim_df, text_auto=True, labels=dict(x="Cosine similarity", y="Text", color="Productivity"),
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x=['text1', 'Jon Description'],
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y=['text1', 'Job Description'])
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st.plotly_chart(fig4, key = "
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st.subheader("Cosine Similarity Scores (Job Description vs. Resumes):")
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for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
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fig1 = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
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values='score', color='label')
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fig1.update_layout(margin = dict(t=50, l=25, r=25, b=25))
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st.plotly_chart(fig1, key = "figure 1")
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vectorizer = TfidfVectorizer()
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tfidf_matrix = vectorizer.fit_transform(result)
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tfidf_df = pd.DataFrame(tfidf_matrix.toarray(), columns=vectorizer.get_feature_names_out())
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fig2 = px.imshow(cosine_sim_df, text_auto=True, labels=dict(x="Cosine similarity", y="Text", color="Productivity"),
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x=['text1', 'Jon Description'],
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y=['text1', 'Job Description'])
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st.plotly_chart(fig2, key = "figure 2")
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st.subheader("Cosine Similarity Scores (Job Description vs. Resumes):")
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for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
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fig3 = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
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values='score', color='label')
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fig3.update_layout(margin = dict(t=50, l=25, r=25, b=25))
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st.plotly_chart(fig3, key = "figure 3")
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vectorizer = TfidfVectorizer()
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tfidf_matrix = vectorizer.fit_transform(result)
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fig4 = px.imshow(cosine_sim_df, text_auto=True, labels=dict(x="Cosine similarity", y="Text", color="Productivity"),
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x=['text1', 'Jon Description'],
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y=['text1', 'Job Description'])
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st.plotly_chart(fig4, key = "figure 4")
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st.subheader("Cosine Similarity Scores (Job Description vs. Resumes):")
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for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
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