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Book4_Ch01_Python_Codes/Streamlit_Bk4_Ch1_01.py

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+
+###############
+# Authored by Weisheng Jiang
+# Book 4  |  From Basic Arithmetic to Machine Learning
+# Published and copyrighted by Tsinghua University Press
+# Beijing, China, 2022
+###############
+
+
+import streamlit as st
+import plotly.express as px
+
+# load iris data
+df = px.data.iris()
+
+features = df.columns.to_list()[:-2]
+with st.sidebar:
+    st.write('2D scatter plot')
+    x_feature = st.radio('Horizontal axis',
+             features)
+    y_feature = st.radio('Vertical axis',
+             features)    
+
+# Heatmap
+with st.expander('Heatmap'):
+    fig_1 = px.imshow(df.iloc[:,0:4],
+                      color_continuous_scale='RdYlBu_r')
+    st.plotly_chart(fig_1)
+    
+# 2D scatter plot
+with st.expander('2D scatter plot'):
+    fig_2 = px.scatter(df, x=x_feature, y=y_feature, color="species")
+    st.plotly_chart(fig_2)
+
+# 3D scatter plot
+with st.expander('3D scatter plot'):
+    fig_3 = px.scatter_3d(df, 
+                          x='sepal_length', 
+                          y='sepal_width', 
+                          z='petal_width',
+                  color='species')
+    st.plotly_chart(fig_3)
+
+# Pairwise scatter plot
+with st.expander('Pairwise scatter plot'):
+    fig_4 = px.scatter_matrix(df, 
+                            dimensions=["sepal_width", 
+                                        "sepal_length", 
+                                        "petal_width", 
+                                        "petal_length"], 
+                            color="species")
+    st.plotly_chart(fig_4)
+    
+    
+    
+