Update app.py

app.py

@@ -5,6 +5,7 @@ import matplotlib.pyplot as plt
 from streamlit.components.v1 import html
 import nbformat
 from nbconvert import HTMLExporter
+from wordcloud import WordCloud
 
 # Load the CSV data
 file_path = 'category upwork jobs.csv'
@@ -41,22 +42,47 @@ if option == "Home":
 
 # Plots Page: Display category distribution plot
 elif option == "Plots":
-    st.title("Job Category Distribution")
-    
-    # Count occurrences of each category
+    st.title("Job Visualization")
+
+    # 1. Job Category Distribution Bar Plot
+    st.subheader("Job Category Distribution")
     category_counts = jobs_df[category_column].value_counts()
+    fig1, ax1 = plt.subplots()
+    ax1.bar(category_counts.index, category_counts.values)
+    ax1.set_xlabel("Job Category")
+    ax1.set_ylabel("Number of Jobs")
+    ax1.set_title("Distribution of Jobs Across Categories")
+    plt.xticks(rotation=45, ha="right")
+    st.pyplot(fig1)
+
+    # 2. Pie Chart for Category Distribution
+    st.subheader("Job Category Proportions")
+    fig2, ax2 = plt.subplots(figsize=(10, 25))
+    ax2.pie(category_counts, labels=category_counts.index, autopct='%1.1f%%', startangle=140)
+    ax2.axis('equal')  # Equal aspect ratio ensures the pie chart is circular.
+    st.pyplot(fig2)
 
-    # Create a bar plot using matplotlib
-    fig, ax = plt.subplots(figsize=(12, 6))
-    ax.bar(category_counts.index, category_counts.values)
-    ax.set_xlabel("Job Category")
-    ax.set_ylabel("Number of Jobs")
-    ax.set_title("Distribution of Jobs Across Categories")
+    
+
+    # 4. Top Job Titles Bar Plot
+    st.subheader("Top Job Titles")
+    top_job_titles = jobs_df[job_title_column].value_counts().head(10)
+    fig4, ax4 = plt.subplots()
+    ax4.bar(top_job_titles.index, top_job_titles.values)
+    ax4.set_xlabel("Job Title")
+    ax4.set_ylabel("Count")
+    ax4.set_title("Top 10 Job Titles")
     plt.xticks(rotation=45, ha="right")
-    plt.tight_layout()
+    st.pyplot(fig4)
+
+    # 5. Word Cloud for Job Descriptions
+    st.subheader("Word Cloud for Job Descriptions")
+    wordcloud = WordCloud(width=800, height=400, background_color='white').generate(' '.join(jobs_df[description_column].dropna()))
+    fig5, ax5 = plt.subplots(figsize=(10, 5))
+    ax5.imshow(wordcloud, interpolation='bilinear')
+    ax5.axis('off')  # Turn off the axis
+    st.pyplot(fig5)
 
-    # Display the plot in Streamlit
-    st.pyplot(fig)
 elif option == "Notebook":
     st.title("Jupyter Notebook")