Upload 4 files

github_analytics/bar_chart.py

@@ -0,0 +1,34 @@
+import streamlit as st
+import plotly.graph_objs as go
+from github_analytics.singular_analysis_chat import predict_2vars
+
+
+def create_bar_chart(repo_data):
+    st.subheader("Here's your data visualization of Repositories compared by stars:")
+    # Extract labels and data from repo_data
+    if not repo_data:
+        return None
+
+    labels = [repo['name'] for repo in repo_data]
+    stars = [repo['stargazers_count'] for repo in repo_data]
+
+    # Create a Plotly line chart
+    fig = go.Figure(data=go.Bar(x=labels, y=stars))
+
+    # Customize the chart
+    fig.update_layout(
+        title='Stars by Repository',
+        xaxis_title='Repository',
+        yaxis_title='Number of Stars',
+        hovermode='closest',
+        xaxis=dict(tickangle=-45), # Rotate x-axis labels
+        width=800,  # Set desired width
+        height=600
+    )
+
+    # Customize hover label
+    fig.update_traces(
+        hovertemplate='Repository: %{x}<br>Forks: %{y}'
+    )
+    response = predict_2vars(labels, stars, "repo names", "stars")
+    return st.plotly_chart(fig), st.write(response)

github_analytics/bubble_chart.py

@@ -0,0 +1,48 @@
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+from datetime import datetime
+from github_analytics.singular_analysis_chat import predict_df
+
+
+def create_bubble_chart(repo_data):
+    # Extract data from repo_data
+    if not repo_data:
+        return None
+
+    labels = [repo['name'] for repo in repo_data]
+    stars = [repo['stargazers_count'] for repo in repo_data]
+    forks = [repo['forks_count'] for repo in repo_data]
+    created_at = [datetime.strptime(repo['created_at'], "%Y-%m-%dT%H:%M:%SZ") for repo in repo_data]
+    # age = [(datetime.now() - created) for created in created_at]
+    age = [(datetime.now() - created).days for created in created_at]
+
+    # Create a DataFrame
+    df = pd.DataFrame({
+        'name': labels,
+        'stars': stars,
+        'forks': forks,
+        'age': age
+    })
+
+    # Create a Plotly bubble chart
+    fig = px.scatter(
+        df,
+        x='forks',
+        y='stars',
+        size='age',
+        hover_data=['name', 'forks', 'stars', 'age'],
+        size_max=60  # Adjust the maximum bubble size
+    )
+
+    # Customize the chart
+    fig.update_layout(
+        title='Stars vs. Forks',
+        xaxis_title='Number of Forks',
+        yaxis_title='Number of Stars',
+        hovermode='closest',
+        width=800,
+        height=600
+    )
+    response = predict_df(df)
+    return st.plotly_chart(fig), st.write(response)

github_analytics/line_chart.py

@@ -0,0 +1,33 @@
+import streamlit as st
+import plotly.graph_objs as go
+from github_analytics.singular_analysis_chat import predict_2vars
+
+
+def create_line_chart(repo_data):
+    # Extract labels and data from repo_data
+    if not repo_data:
+        return None
+
+    labels = [repo['name'] for repo in repo_data]
+    forks = [repo['forks_count'] for repo in repo_data]
+
+    # Create a Plotly line chart
+    fig = go.Figure(data=go.Scatter(x=labels, y=forks, mode='lines+markers'))
+
+    # Customize the chart
+    fig.update_layout(
+        title='Forks by Repository',
+        xaxis_title='Repository',
+        yaxis_title='Number of Forks',
+        hovermode='closest',
+        xaxis=dict(tickangle=-45),  # Rotate x-axis labels
+        width=800,  # Set desired width
+        height=600
+    )
+
+    # Customize hover label
+    fig.update_traces(
+        hovertemplate='Repository: %{x}<br>Forks: %{y}'
+    )
+    response = predict_2vars(labels, forks, "repo names", "forks")
+    return st.plotly_chart(fig), st.write(response)

github_analytics/pie_chart.py

@@ -0,0 +1,38 @@
+import streamlit as st
+from github_analytics.singular_analysis_chat import predict_2vars
+import plotly.graph_objs as go
+
+
+def create_pie_chart(repo_data):
+    """Creates an interactive pie chart showing the distribution of repository languages."""
+    if not repo_data:
+        return None
+
+    languages = {}
+    for repo in repo_data:
+        if repo.get("language"):  # Check if language exists
+            languages[repo["language"]] = languages.get(repo["language"], 0) + 1
+
+    language_labels = list(languages.keys())
+    language_counts = list(languages.values())
+
+    if not language_labels:
+        st.write("No languages found in repositories.")
+        return None
+
+    # Create Plotly pie chart
+    fig = go.Figure(data=[go.Pie(labels=language_labels, values=language_counts)])
+
+    fig.update_layout(
+        title="Repository Language Distribution",
+        hoverlabel=dict(
+            bgcolor="white",
+            font_size=16,
+            font_family="Rockwell"
+        ),
+        width=800,
+        height=600
+    )
+
+    response = predict_2vars(language_labels, language_counts, "language_labels", "language_counts")
+    return st.plotly_chart(fig), st.write(response)