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README (3).md

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+---
+title: 🧠Visualization Plotly Sunbursts Treemaps WebGL🩺
+emoji: 6-Vis🧠
+colorFrom: indigo
+colorTo: purple
+sdk: streamlit
+sdk_version: 1.17.0
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import streamlit as st
+import numpy as np
+import plotly.express as px
+import pandas as pd
+import plotly.graph_objects as go
+
+st.set_page_config(page_title="Plotly Graphing Libraries",layout='wide')
+
+import streamlit as st
+
+uploaded_files = st.file_uploader("Choose a CSV file", accept_multiple_files=True)
+for uploaded_file in uploaded_files:
+    bytes_data = uploaded_file.read()
+    st.write("filename:", uploaded_file.name)
+    st.write(bytes_data)
+    
+    if st.checkbox("FileDetails"):
+
+        filevalue = uploaded_file.getvalue()
+        st.write(filevalue)
+        st.write(uploaded_file.name)
+        st.write(uploaded_file.type)
+        st.write(uploaded_file.size)
+        #st.write(uploaded_file.last_modified)
+        #st.write(uploaded_file.charset)
+        st.write(uploaded_file.getbuffer())
+        st.write(uploaded_file.getbuffer().nbytes)
+        st.write(uploaded_file.getbuffer().tobytes())
+        st.write(uploaded_file.getbuffer().tolist())
+        st.write(uploaded_file.getbuffer().itemsize)
+        st.write(uploaded_file.getbuffer().ndim)
+        st.write(uploaded_file.getbuffer().shape)
+        st.write(uploaded_file.getbuffer().strides)
+        st.write(uploaded_file.getbuffer().suboffsets)
+        st.write(uploaded_file.getbuffer().readonly)
+        st.write(uploaded_file.getbuffer().c_contiguous)
+        st.write(uploaded_file.getbuffer().f_contiguous)
+        st.write(uploaded_file.getbuffer().contiguous)
+        st.write(uploaded_file.getbuffer().itemsize)
+        st.write(uploaded_file.getbuffer().nbytes)
+        st.write(uploaded_file.getbuffer().ndim)
+        st.write(uploaded_file.getbuffer().shape)
+        st.write(uploaded_file.getbuffer().strides)
+        st.write(uploaded_file.getbuffer().suboffsets)
+        st.write(uploaded_file.getbuffer().readonly)
+        st.write(uploaded_file.getbuffer().c_contiguous)
+        st.write(uploaded_file.getbuffer().f_contiguous)
+        st.write(uploaded_file.getbuffer().contiguous)
+        st.write(uploaded_file.getbuffer().itemsize)
+        st.write(uploaded_file.getbuffer().nbytes)
+        st.write(uploaded_file.getbuffer().ndim)
+        st.write(uploaded_file.getbuffer().shape)
+        st.write(uploaded_file.getbuffer().strides)
+        st.write(uploaded_file.getbuffer().suboffsets)
+        st.write(uploaded_file.getbuffer().readonly)
+        st.write(uploaded_file.getbuffer().c_contiguous)
+        st.write(uploaded_file.getbuffer().f_contiguous)
+        myDF = pd.DataFrame(uploaded_file.getbuffer().tolist())
+        
+
+        st.markdown("# Treemaps from upload data file: https://plotly.com/python/treemaps/")
+        #df = myDF.query("year == 2007")
+        df = myDF
+        fig = px.treemap(df, path=[px.Constant("time"), 'message', 'name'], values='content',
+                        color='lifeExp', hover_data=['iso_alpha'],
+                        color_continuous_scale='RdBu',
+                        color_continuous_midpoint=np.average(df['name'], weights=df['content']))  # todo - debug this and get it working with the data
+        fig.update_layout(margin = dict(t=50, l=25, r=25, b=25))
+        #fig.show()
+        st.plotly_chart(fig, use_container_width=True)
+        
+        
+    
+   
+#show replace     
+    if st.checkbox("replace"):
+        mydf = st.dataframe(df)
+        columns = st.selectbox("Select  column", df.columns)
+        old_values = st.multiselect("Current Values",list(df[columns].unique()),list(df[columns].unique()))
+        with st.form(key='my_form'):
+            col1,col2 = st.beta_columns(2)
+            st_input = st.number_input if is_numeric_dtype(df[columns]) else st.text_input
+        with col1:
+            old_val = st_input("old value")
+        with col2:
+            new_val = st_input("new value")
+            if st.form_submit_button("Replace"):
+                df[columns]=df[columns].replace(old_val,new_val)
+                st.success("{} replace with {} successfully ".format(old_val,new_val))
+                excel = df.to_excel(r"F:\book2.xlsx", index = False, header=True,encoding="utf-8")
+                df =pd.read_excel(r"F:\book2.xlsx")       
+                mydf.add_rows(df)    
+
+st.markdown("WebGL Rendering with 1,000,000 Points")
+import plotly.graph_objects as go
+import numpy as np
+N = 1000000
+fig = go.Figure()
+fig.add_trace(
+    go.Scattergl(
+        x = np.random.randn(N),
+        y = np.random.randn(N),
+        mode = 'markers',
+        marker = dict(
+            line = dict(
+                width = 1,
+                color = 'DarkSlateGrey')
+        )
+    )
+)
+#fig.show()
+st.plotly_chart(fig, use_container_width=True)
+
+
+
+st.markdown("# WebGL Graph - ScatterGL")
+fig = go.Figure()
+trace_num = 10
+point_num = 5000
+for i in range(trace_num):
+    fig.add_trace(
+        go.Scattergl(
+                x = np.linspace(0, 1, point_num),
+                y = np.random.randn(point_num)+(i*5)
+        )
+    )
+fig.update_layout(showlegend=False)
+#fig.show()
+st.plotly_chart(fig, use_container_width=True)
+
+
+st.markdown("# Treemaps: https://plotly.com/python/treemaps/")
+df = px.data.gapminder().query("year == 2007")
+fig = px.treemap(df, path=[px.Constant("world"), 'continent', 'country'], values='pop',
+                  color='lifeExp', hover_data=['iso_alpha'],
+                  color_continuous_scale='RdBu',
+                  color_continuous_midpoint=np.average(df['lifeExp'], weights=df['pop']))
+fig.update_layout(margin = dict(t=50, l=25, r=25, b=25))
+#fig.show()
+st.plotly_chart(fig, use_container_width=True)
+
+
+st.markdown("# Sunburst: https://plotly.com/python/sunburst-charts/")
+
+
+st.markdown("# Life Expectancy Sunburst")
+df = px.data.gapminder().query("year == 2007")
+fig = px.sunburst(df, path=['continent', 'country'], values='pop',
+                  color='lifeExp', hover_data=['iso_alpha'],
+                  color_continuous_scale='RdBu',
+                  color_continuous_midpoint=np.average(df['lifeExp'], weights=df['pop']))
+st.plotly_chart(fig, use_container_width=True)
+
+
+st.markdown("# Coffee Aromas and Tastes Sunburst")
+df1 = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/718417069ead87650b90472464c7565dc8c2cb1c/sunburst-coffee-flavors-complete.csv')
+df2 = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/718417069ead87650b90472464c7565dc8c2cb1c/coffee-flavors.csv')
+fig = go.Figure()
+fig.add_trace(go.Sunburst(
+    ids=df1.ids,
+    labels=df1.labels,
+    parents=df1.parents,
+    domain=dict(column=0)
+))
+fig.add_trace(go.Sunburst(
+    ids=df2.ids,
+    labels=df2.labels,
+    parents=df2.parents,
+    domain=dict(column=1),
+    maxdepth=2
+))
+fig.update_layout(
+    grid= dict(columns=2, rows=1),
+    margin = dict(t=0, l=0, r=0, b=0)
+)
+st.plotly_chart(fig, use_container_width=True)
+
+
+
+
+
+# Sunburst
+#data = dict(
+#    character=["Eve", "Cain", "Seth", "Enos", "Noam", "Abel", "Awan", "Enoch", "Azura"],
+#    parent=["", "Eve", "Eve", "Seth", "Seth", "Eve", "Eve", "Awan", "Eve" ],
+#    value=[10, 14, 12, 10, 2, 6, 6, 4, 4])
+#fig = px.sunburst(
+#    data,
+#    names='character',
+#    parents='parent',
+#    values='value',
+#)
+#fig.show()
+#st.plotly_chart(fig, use_container_width=True)
+
+
+df = px.data.tips()
+fig = px.treemap(df, path=[px.Constant("all"), 'sex', 'day', 'time'], 
+                 values='total_bill', color='time',
+                  color_discrete_map={'(?)':'lightgrey', 'Lunch':'gold', 'Dinner':'darkblue'})
+fig.update_layout(margin = dict(t=50, l=25, r=25, b=25))
+#fig.show()
+fig.update_traces(marker=dict(cornerradius=5))
+
+st.plotly_chart(fig, use_container_width=True)
+
+
+df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/96c0bd/sunburst-coffee-flavors-complete.csv')
+fig = go.Figure(go.Treemap(
+    ids = df.ids,
+    labels = df.labels,
+    parents = df.parents,
+    pathbar_textfont_size=15,
+    root_color="lightgrey"
+))
+fig.update_layout(
+    uniformtext=dict(minsize=10, mode='hide'),
+    margin = dict(t=50, l=25, r=25, b=25)
+)
+#fig.show()
+st.plotly_chart(fig, use_container_width=True)
+
+
+df = pd.read_pickle('bloom_dataset.pkl')
+fig = px.treemap(df, path=[px.Constant("ROOTS"), 'Macroarea', 'Family', 'Genus', 'Language', 'dataset_name'],
+                 values='num_bytes', maxdepth=4)
+fig.update_traces(root_color="pink")
+fig.update_layout(margin = dict(t=50, l=25, r=25, b=25))
+
+st.plotly_chart(fig, use_container_width=True)

bloom_dataset.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:27b17d22a1763de24c70da9ab87a6e6887cfdb7b17570e9758f4033217cbaf42
+size 88499

requirements.txt

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+plotly
+pandas
+protobuf~=3.19.0