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app.py

@@ -26,109 +26,90 @@ def on_btn_click():
 
 
 def main():
-    st.title(" Corona Dashboard")
+    st.title(" US Real Estate Data and Market Trends")
     (
         col1,
         col2,
     ) = st.columns(2)
     with col1:
-        option = st.selectbox(" San Francisco", [" San Francisco"])
-    with col2:
         option = st.selectbox(" Monthly / Weekly", [" Monthly ", " Weekly"])
-    if st.checkbox(" Show raw data"):
-        st.write("Checkbox checked!")
-    if st.button(" Visualize"):
-        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)
+    with col2:
+        option = st.selectbox(" Current / Historical", [" Current ", " Historical"])
     (
         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],
-            }
-        )
+        option = st.selectbox(" Median / Mean", [" Median ", " Mean"])
     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"},
+        option = st.selectbox(" San Francisco", [" San Francisco"])
+    (
+        col1,
+        col2,
+    ) = st.columns(2)
+    with col1:
+        selected_color = st.color_picker(" Choose a palate", "#FF0000")
+    with col2:
+        value = st.slider(" No of colors", min_value=0, max_value=100, value=50, key=5)
+    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,
+                ),
+            ],
         )
-        fig.update_traces(textposition="inside", textinfo="percent+label")
-        st.plotly_chart(fig)
+    )
+    st.subheader(" 2D Visualization")
+    st.altair_chart(
+        alt.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),
+                }
+            )
+        )
+        .mark_circle()
+        .encode(
+            x="x",
+            y="y",
+            size="size",
+            color="color",
+            tooltip=["x", "y", "size", "color"],
+        )
+        .properties(width=600, height=400),
+        use_container_width=True,
+    )
 
 
 if __name__ == "__main__":