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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) |