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app.py

@@ -26,90 +26,136 @@ def on_btn_click():
 
 
 def main():
-    st.title(" US Real Estate Data and Market Trends")
+    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(" Monthly / Weekly", [" Monthly ", " Weekly"])
+        st.write("Hello, world!")
     with col2:
-        option = st.selectbox(" Current / Historical", [" Current ", " Historical"])
+        option = st.selectbox(
+            " gender / male / female", [" gender ", " male ", " female"]
+        )
     (
         col1,
         col2,
     ) = st.columns(2)
     with col1:
-        option = st.selectbox(" Median / Mean", [" Median ", " Mean"])
+        value = st.slider(
+            " max predictions", min_value=0, max_value=100, value=50, key=61
+        )
     with col2:
-        option = st.selectbox(" San Francisco", [" San Francisco"])
+        value = st.slider(
+            " num categories", min_value=0, max_value=100, value=50, key=65
+        )
     (
         col1,
         col2,
     ) = st.columns(2)
     with col1:
-        selected_color = st.color_picker(" Choose a palate", "#FF0000")
+        option = st.radio("Choose an option:", ["Option 1", "Option 2", "Option 3"])
     with col2:
-        value = st.slider(" No of colors", min_value=0, max_value=100, value=50, key=45)
-    if st.checkbox(" Show raw data"):
-        st.write("Checkbox checked!")
-    st.subheader(" Global 3D Visualization")
-    st.pydeck_chart(
-        pdk.Deck(
-            map_style=None,
-            initial_view_state=pdk.ViewState(
-                latitude=37.76, longitude=-122.4, zoom=11, pitch=50
-            ),
-            layers=[
-                pdk.Layer(
-                    "HexagonLayer",
-                    data=pd.DataFrame(
-                        np.random.randn(1000, 2) / [50, 50] + [37.76, -122.4],
-                        columns=["lat", "lon"],
-                    ),
-                    get_position="[lon, lat]",
-                    radius=200,
-                    elevation_scale=4,
-                    elevation_range=[0, 1000],
-                    pickable=True,
-                    extruded=True,
-                ),
-                pdk.Layer(
-                    "ScatterplotLayer",
-                    data=pd.DataFrame(
-                        np.random.randn(1000, 2) / [50, 50] + [37.76, -122.4],
-                        columns=["lat", "lon"],
-                    ),
-                    get_position="[lon, lat]",
-                    get_color="[200, 30, 0, 160]",
-                    get_radius=200,
-                ),
-            ],
+        if st.checkbox("Check me"):
+            st.write("Checkbox checked!")
+    if st.button(" generate recommendations"):
+        st.write("Button clicked!")
+    (
+        col1,
+        col2,
+    ) = st.columns(2)
+    with col1:
+        st.table(
+            {
+                "Country": ["USA", "Canada", "UK", "Australia"],
+                "Population (millions)": [331, 38, 66, 25],
+                "GDP (trillion USD)": [22.675, 1.843, 2.855, 1.488],
+            }
         )
-    )
-    st.subheader(" 2D Visualization")
-    st.altair_chart(
-        alt.Chart(
+    with col2:
+        st.line_chart(
             pd.DataFrame(
                 {
-                    "x": np.random.rand(50),
-                    "y": np.random.rand(50),
-                    "size": np.random.randint(10, 100, 50),
-                    "color": np.random.rand(50),
+                    "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"],
                 }
             )
         )
-        .mark_circle()
-        .encode(
-            x="x",
-            y="y",
-            size="size",
-            color="color",
-            tooltip=["x", "y", "size", "color"],
+    (
+        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(
+            df,
+            values="pop",
+            names="country",
+            title="Population of American continent",
+            hover_data=["lifeExp"],
+            labels={"lifeExp": "life expectancy"},
+        )
+        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",
         )
-        .properties(width=600, height=400),
+    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__":