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  1. .gitignore +134 -0
  2. .streamlit/config.toml +9 -0
  3. Dockerfile +23 -0
  4. README.md +15 -0
  5. app.py +36 -0
  6. packages.txt +0 -0
  7. requirements.txt +3 -0
.gitignore ADDED
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+ venv/
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+ # Byte-compiled / optimized / DLL files
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+ __pycache__/
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+ *.py[cod]
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+ *$py.class
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+
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+ # C extensions
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+ *.so
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+
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+ # Distribution / packaging
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+ .Python
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+ build/
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+ develop-eggs/
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+ dist/
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+ downloads/
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+ eggs/
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+ .eggs/
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+ lib/
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+ lib64/
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+ parts/
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+ sdist/
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+ var/
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+ wheels/
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+ pip-wheel-metadata/
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+ share/python-wheels/
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+ *.egg-info/
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+ .installed.cfg
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+ *.egg
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+ MANIFEST
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+
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+ # PyInstaller
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+ # Usually these files are written by a python script from a template
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+ # before PyInstaller builds the exe, so as to inject date/other infos into it.
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+ *.manifest
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+ *.spec
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+
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+ # Installer logs
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+ pip-log.txt
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+ pip-delete-this-directory.txt
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+
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+ # Unit test / coverage reports
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+ htmlcov/
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+ .tox/
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+ .nox/
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+ .coverage
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+ .coverage.*
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+ .cache
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+ nosetests.xml
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+ coverage.xml
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+ *.cover
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+ *.py,cover
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+ .hypothesis/
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+ .pytest_cache/
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+
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+ # Translations
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+ *.mo
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+ *.pot
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+
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+ # Django stuff:
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+ *.log
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+ local_settings.py
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+ db.sqlite3
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+ db.sqlite3-journal
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+
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+ # Flask stuff:
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+ instance/
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+ .webassets-cache
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+
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+ # Scrapy stuff:
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+ .scrapy
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+
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+ # Sphinx documentation
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+ docs/_build/
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+
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+ # PyBuilder
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+ target/
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+
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+ # Jupyter Notebook
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+ .ipynb_checkpoints
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+
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+ # IPython
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+ profile_default/
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+ ipython_config.py
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+
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+ # pyenv
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+ .python-version
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+
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+ # pipenv
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+ # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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+ # However, in case of collaboration, if having platform-specific dependencies or dependencies
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+ # having no cross-platform support, pipenv may install dependencies that don't work, or not
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+ # install all needed dependencies.
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+ #Pipfile.lock
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+
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+ # PEP 582; used by e.g. github.com/David-OConnor/pyflow
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+ __pypackages__/
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+
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+ # Celery stuff
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+ celerybeat-schedule
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+ celerybeat.pid
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+
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+ # SageMath parsed files
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+ *.sage.py
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+
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+ # Environments
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+ .env
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+ .venv
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+ env/
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+ venv/
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+ ENV/
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+ env.bak/
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+ venv.bak/
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+
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+ # Spyder project settings
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+ .spyderproject
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+ .spyproject
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+
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+ # Rope project settings
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+ .ropeproject
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+
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+ # mkdocs documentation
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+ /site
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+
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+ # mypy
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+ .mypy_cache/
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+ .dmypy.json
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+ dmypy.json
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+
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+ # Pyre type checker
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+ .pyre/
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+
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+ .vscode/
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+
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+ data/audio/
.streamlit/config.toml ADDED
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+ [theme]
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+ primaryColor="#e5ab00"
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+ backgroundColor="#0e1117"
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+ secondaryBackgroundColor="#282929"
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+ textColor = "#ffffff"
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+ font="sans serif"
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+
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+ [server]
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+ maxUploadSize = 200
Dockerfile ADDED
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+ FROM python:3.8.9
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+
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+ WORKDIR /app
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+
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+ COPY ./requirements.txt /app/requirements.txt
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+ COPY ./packages.txt /app/packages.txt
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+
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+ RUN apt-get update && xargs -r -a /app/packages.txt apt-get install -y && rm -rf /var/lib/apt/lists/*
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+ RUN pip3 install --no-cache-dir -r /app/requirements.txt
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+
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+ # User
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+ RUN useradd -m -u 1000 user
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+ USER user
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+ ENV HOME /home/user
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+ ENV PATH $HOME/.local/bin:$PATH
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+
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+ WORKDIR $HOME
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+ RUN mkdir app
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+ WORKDIR $HOME/app
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+ COPY . $HOME/app
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+
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+ EXPOSE 8501
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+ CMD streamlit run app.py
README.md ADDED
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+ ---
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+ title: Streamlit Docker Template
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+ emoji: πŸ§ πŸ”Ž
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+ colorFrom: blue
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+ colorTo: green
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+ sdk: docker
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+ app_port: 8501
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+ pinned: true
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+ ---
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+
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+ ## 🧠 Streamlit Docker Template πŸ”Ž
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+
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+ Streamlit Docker Template is a template for creating a Streamlit app with Docker and Hugging Face Spaces.
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+
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+ Code from https://docs.streamlit.io/library/get-started/create-an-app
app.py ADDED
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+ import streamlit as st
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+ import pandas as pd
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+ import numpy as np
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+
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+ st.title('Uber pickups in NYC')
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+
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+ DATE_COLUMN = 'date/time'
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+ DATA_URL = ('https://s3-us-west-2.amazonaws.com/'
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+ 'streamlit-demo-data/uber-raw-data-sep14.csv.gz')
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+
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+ @st.cache
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+ def load_data(nrows):
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+ data = pd.read_csv(DATA_URL, nrows=nrows)
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+ lowercase = lambda x: str(x).lower()
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+ data.rename(lowercase, axis='columns', inplace=True)
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+ data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])
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+ return data
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+
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+ data_load_state = st.text('Loading data...')
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+ data = load_data(10000)
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+ data_load_state.text("Done! (using st.cache)")
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+
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+ if st.checkbox('Show raw data'):
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+ st.subheader('Raw data')
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+ st.write(data)
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+
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+ st.subheader('Number of pickups by hour')
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+ hist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]
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+ st.bar_chart(hist_values)
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+
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+ # Some number in the range 0-23
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+ hour_to_filter = st.slider('hour', 0, 23, 17)
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+ filtered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]
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+
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+ st.subheader('Map of all pickups at %s:00' % hour_to_filter)
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+ st.map(filtered_data)
packages.txt ADDED
File without changes
requirements.txt ADDED
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+ streamlit
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+ numpy
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+ pandas