Delete Book4_Ch01_Python_Codes directory

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)    
-
-#%% original data
-
-with st.expander('Original data'):
-    st.write(df)
-    
-
-#%% 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)
-    
-    
-    
-