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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')
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"book2.xlsx", index = False, header=True,encoding="utf-8")
df =pd.read_excel(r"book2.xlsx")
mydf.add_rows(df)
#st.markdown("WebGL Rendering with 1,000,000 Points")
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) |