import streamlit as st
# Custom imports
from multipage import MultiPage
from pages import upload, model, Home, state # import your pages here
#from pages import *
# Create an instance of the app
app = MultiPage()
# Title of the main page
source = []
mod = ''
# Add all your applications (pages) here
app.add_page("Home", Home.app)
app.add_page("Upload Data", upload.app)
app.add_page("Model Selector", model.app)
app.add_page("Display", state.app)
#app.add_page("Results", Results.app)
# The main app
app.run()
tar.extractall()
DATADIR = Path(tar.getnames()[0])
config_file = DATADIR/'pages.yaml'
with open(config_file) as fh:
config = yaml.safe_load(fh)
# Create an instance of the app
app = MultiPage()
project_sites = config['pages']
# # results = {
# # 'Summary': ('Summary', Summary.app, DATADIR),
# # 'Path': ('Pathway Analysis', Pathway.app, DATADIR),
# # 'Assembly': ('Assembly', Assembly.app, DATADIR)}
#
available_pages = {'Home': ('Home', Home.app, DATADIR),
'EDA': ('Exploratory Data Analysis', EDA.app, DATADIR),
'DiffAb': ('Differential Expression/Abundance', DiffAb.app, DATADIR),
'Expression': ('Gene Expression', Expression.app, DATADIR)}
for page_name, page in available_pages.items():
if page_name not in project_sites:
continue
app.add_page(page[0], page[1], page[2])
# The main app
app.run()
import sys
from pathlib import Path
file = Path(__file__).resolve()
parent, root = file.parent, file.parents[1]
sys.path.append(str(root))
try:
sys.path.remove(str(parent))
except ValueError: # Already removed
pass
# Custom imports
from multipage import MultiPage
from pages import penguins, session_state, stock_SP500, boston_housing
from pages import home
# Create an instance of the app
app = MultiPage()
# Add all your application here
app.add_page("Home", home.app)
app.add_page("Session State Demos", session_state.app)
app.add_page("Penguins", penguins.app)
app.add_page("Stocks S&P 500", stock_SP500.app)
app.add_page("Boston Housing - Random Forest Regressor", boston_housing.app)
# The main app
app.run()
import streamlit as st
import tarfile
from pathlib import Path
# Custom imports
from multipage import MultiPage
from pages import PCA, DiffAb, Summary
st.set_page_config(page_title="mBARq App", layout='wide')
DATADIR = Path('./data/test')
# Create an instance of the app
app = MultiPage()
# Title of the main page
st.title("NCCR Microbiomes ETHZ prototype")
app.add_page("PCA", PCA.app)
# fname = st.sidebar.file_uploader('Project Results', accept_multiple_files=False)
# if not fname:
# st.stop()
# tar = tarfile.open(fileobj=fname, mode="r:gz")
# tar.extractall(DATADIR)
# project_sites = [s.name for s in DATADIR.glob('**/*') if not s.is_file()]
# project_name = project_sites[0]
#
# st.header(f'Project Name: {project_name}')
#
# results = {'Summary': ('Summary', Summary.app),
# 'PCA': ('PCA', PCA.app),
# 'DiffAb': ('Differential Expression/Abundance', DiffAb.app)}
#
# for page_name, page in results.items():
# if page_name not in project_sites:
import streamlit as st
from multipage import MultiPage
from pages import visual, zillow, ml, main, About
app = MultiPage()
app.add_page('Main', main.app)
app.add_page('About', About.app)
app.add_page('Real Estate Market Visualization', visual.app)
app.add_page('Searching on Zillow', zillow.app)
app.add_page('House Price Estimation', ml.app)
app.run()
import streamlit as st
# Custom imports
from multipage import MultiPage
from pages import home, page1, page2 # import your pages here
# Create an instance of the app
app = MultiPage()
# Title of the main page
st.title("Streamlit multipages")
# Add all your applications (pages) here
app.add_page("Home", home.app)
app.add_page("Pagina1", page1.app)
app.add_page("Pagina2", page2.app)
# The main app
app.run()
import streamlit as st
from multipage import MultiPage
import pull_eval_cases_page
import forecast_modeling_page
app = MultiPage()
st.title("Covid-19 Dashboard")
app.add_page("Confirmed Cases per Region", pull_eval_cases_page.app)
app.add_page("Covid Case Forecast Model", forecast_modeling_page.app)
app.run()
columns_df = pd.DataFrame(columns, columns=['column_name', 'type'])
columns_df.to_csv('data/metadata/column_type_desc.csv', index=False)
# Display columns
st.markdown("**Column Name**-**Type**")
for i in range(columns_df.shape[0]):
st.write(
f"{i + 1}. **{columns_df.iloc[i]['column_name']}** - {columns_df.iloc[i]['type']}"
)
st.markdown(
"""The above are the automated column types detected by the application in the data.
In case you wish to change the column types, head over to the **Column Change** section. """
)
# Create an instance of the app
app = MultiPage()
# Title of the main page
st.title("Data Storyteller Application")
# Add all your applications (pages) here
app.add_page("Upload Data", data_upload.app)
app.add_page("Change Metadata", metadata.app)
app.add_page("Machine Learning", machine_learning.app)
app.add_page("Data Analysis", data_visualize.app)
app.add_page("Y-Parameter Optimization", redundant.app)
# The main app
app.run()