Upload folder using huggingface_hub

app.py

@@ -26,85 +26,42 @@ def on_btn_click():
 
 
 def main():
-    st.title(" Corona Dashboard")
+    st.write("Hello, world!")
+    st.header(" Al Generated this app - spotify recommendations")
+    st.subheader(" this application contains the auto generated layout")
     (
         col1,
         col2,
     ) = st.columns(2)
     with col1:
-        option = st.selectbox(" San Francisco", [" San Francisco"])
+        st.write("Hello, world!")
     with col2:
-        option = st.selectbox(" Monthly / Weekly", [" Monthly ", " Weekly"])
-    if st.checkbox(" Show raw data"):
-        st.write("Checkbox checked!")
-    if st.button(" Visualize"):
+        option = st.selectbox(
+            " gender / male / female", [" gender ", " male ", " female"]
+        )
+    (
+        col1,
+        col2,
+    ) = st.columns(2)
+    with col1:
+        value = st.slider(
+            " max predictions", min_value=0, max_value=100, value=50, key=39
+        )
+    with col2:
+        value = st.slider(
+            " num categories", min_value=0, max_value=100, value=50, key=81
+        )
+    (
+        col1,
+        col2,
+    ) = st.columns(2)
+    with col1:
+        option = st.radio("Choose an option:", ["Option 1", "Option 2", "Option 3"])
+    with col2:
+        if st.checkbox("Check me"):
+            st.write("Checkbox checked!")
+    if st.button(" generate recommendations"):
         st.write("Button clicked!")
-    st.subheader(" Global Data")
-    df = pd.read_csv(
-        "https://raw.githubusercontent.com/plotly/datasets/master/volcano_db.csv",
-        encoding="iso-8859-1",
-    )
-    freq = df
-    freq = freq.Country.value_counts().reset_index().rename(columns={"count": "x"})
-    df_v = pd.read_csv(
-        "https://raw.githubusercontent.com/plotly/datasets/master/volcano.csv"
-    )
-    fig = make_subplots(
-        rows=2,
-        cols=2,
-        column_widths=[0.6, 0.4],
-        row_heights=[0.4, 0.6],
-        specs=[
-            [{"type": "scattergeo", "rowspan": 2}, {"type": "bar"}],
-            [None, {"type": "surface"}],
-        ],
-    )
-    fig.add_trace(
-        go.Scattergeo(
-            lat=df["Latitude"],
-            lon=df["Longitude"],
-            mode="markers",
-            hoverinfo="text",
-            showlegend=False,
-            marker=dict(color="crimson", size=4, opacity=0.8),
-        ),
-        row=1,
-        col=1,
-    )
-    fig.add_trace(
-        go.Bar(
-            x=freq["x"][0:10],
-            y=freq["Country"][0:10],
-            marker=dict(color="crimson"),
-            showlegend=False,
-        ),
-        row=1,
-        col=2,
-    )
-    fig.add_trace(go.Surface(z=df_v.values.tolist(), showscale=False), row=2, col=2)
-    fig.update_geos(
-        projection_type="orthographic",
-        landcolor="white",
-        oceancolor="MidnightBlue",
-        showocean=True,
-        lakecolor="LightBlue",
-    )
-    fig.update_xaxes(tickangle=45)
-    fig.update_layout(
-        template="plotly_dark",
-        margin=dict(r=10, t=25, b=40, l=60),
-        annotations=[
-            dict(
-                text="Source: NOAA",
-                showarrow=False,
-                xref="paper",
-                yref="paper",
-                x=0,
-                y=0,
-            )
-        ],
-    )
-    st.plotly_chart(fig)
     (
         col1,
         col2,
@@ -117,6 +74,41 @@ def main():
                 "GDP (trillion USD)": [22.675, 1.843, 2.855, 1.488],
             }
         )
+    with col2:
+        st.line_chart(
+            pd.DataFrame(
+                {
+                    "Apple": yf.download("AAPL", start="2023-01-01", end="2023-07-31")[
+                        "Adj Close"
+                    ],
+                    "Google": yf.download(
+                        "GOOGL", start="2023-01-01", end="2023-07-31"
+                    )["Adj Close"],
+                    "Microsoft": yf.download(
+                        "MSFT", start="2023-01-01", end="2023-07-31"
+                    )["Adj Close"],
+                }
+            )
+        )
+    (
+        col1,
+        col2,
+    ) = st.columns(2)
+    with col1:
+        data = pd.DataFrame(
+            {"X": [1, 2, 3, 4, 5], "Y1": [10, 16, 8, 14, 12], "Y2": [5, 8, 3, 6, 7]}
+        )
+        st.area_chart(data)
+    with col2:
+        st.bar_chart(
+            pd.DataFrame(np.random.randn(20, 3), columns=["Apple", "Banana", "Cherry"])
+        )
+    (
+        col1,
+        col2,
+    ) = st.columns(2)
+    with col1:
+        st.write("Hello, world!")
     with col2:
         df = px.data.gapminder().query("year == 2007").query("continent == 'Americas'")
         fig = px.pie(
@@ -129,6 +121,41 @@ def main():
         )
         fig.update_traces(textposition="inside", textinfo="percent+label")
         st.plotly_chart(fig)
+    source = vds.cars()
+    chart = {
+        "mark": "point",
+        "encoding": {
+            "x": {"field": "Horsepower", "type": "quantitative"},
+            "y": {"field": "Miles_per_Gallon", "type": "quantitative"},
+            "color": {"field": "Origin", "type": "nominal"},
+            "shape": {"field": "Origin", "type": "nominal"},
+        },
+    }
+    tab1, tab2 = st.tabs(["Streamlit theme (default)", "Vega-Lite native theme"])
+    with tab1:
+        st.vega_lite_chart(source, chart, theme="streamlit", use_container_width=True)
+    with tab2:
+        st.vega_lite_chart(source, chart, theme=None, use_container_width=True)
+    (
+        col1,
+        col2,
+    ) = st.columns(2)
+    with col1:
+        st.video("https://www.youtube.com/watch?v=50hVvC7gMR8&t=5s", format="video/mp4")
+    with col2:
+        st.image(
+            "https://assets-global.website-files.com/59e16042ec229e00016d3a66/6441d5f76d21e1e4dee9ffa2_Gen%20AI%20blog_Blog%20hero.png",
+            caption="Image Caption",
+        )
+    st.plotly_chart(
+        ff.create_distplot(
+            [np.random.randn(200) - 2, np.random.randn(200), np.random.randn(200) + 2],
+            ["Negative Shift", "Normal", "Positive Shift"],
+            bin_size=[0.1, 0.25, 0.5],
+        ),
+        use_container_width=True,
+    )
+    st.header(" auto generated by sketch2streamiit")
 
 
 if __name__ == "__main__":