shao
This commit is contained in:
shao1chuan
parent
9084667634
commit
b4dac82343
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# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
share/python-wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
|
||||
# PyInstaller
|
||||
# Usually these files are written by a python script from a template
|
||||
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
||||
*.manifest
|
||||
*.spec
|
||||
|
||||
# Installer logs
|
||||
pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
.coverage
|
||||
.coverage.*
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
*.cover
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
cover/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
||||
# Django stuff:
|
||||
*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
db.sqlite3-journal
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
.pybuilder/
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
|
||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
# For a library or package, you might want to ignore these files since the code is
|
||||
# intended to run in multiple environments; otherwise, check them in:
|
||||
# .python-version
|
||||
|
||||
# pipenv
|
||||
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
|
||||
# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
||||
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
||||
# install all needed dependencies.
|
||||
#Pipfile.lock
|
||||
|
||||
# PEP 582; used by e.g. github.com/David-OConnor/pyflow
|
||||
__pypackages__/
|
||||
|
||||
# Celery stuff
|
||||
celerybeat-schedule
|
||||
celerybeat.pid
|
||||
|
||||
# SageMath parsed files
|
||||
*.sage.py
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# pytype static type analyzer
|
||||
.pytype/
|
||||
|
||||
# Cython debug symbols
|
||||
cython_debug/
|
||||
|
||||
# JetBrains IDEs
|
||||
.idea/
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||||
|
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@ -1,22 +0,0 @@
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# FastAPI + Dash Sample App
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Sample application that runs a Dash app mounted inside a FastAPI webserver.
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## Quickstart
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1. Install dependencies
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```bash
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poetry install
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```
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2. Run webserver
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```bash
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poetry run python -m app
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```
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3. Load up in browser: http://localhost:8000
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|
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## Routes
|
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|
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| Route | Description | Link |
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|-------------|----------------------------------|------------------------------|
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| GET / | Base route (tests shared prefix) | http://localhost:8000/ |
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| GET /status | Non-Dash route | http://localhost:8000/status |
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| GET /dash | Dash app | http://localhost:8000/dash |
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import uvicorn
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from fastapi import FastAPI
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from fastapi.middleware.wsgi import WSGIMiddleware
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from dashapp import create_dash_app
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app = FastAPI()
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|
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|
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@app.get("/")
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def read_main():
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return {
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"routes": [
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{"method": "GET", "path": "/", "summary": "Landing"},
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{"method": "GET", "path": "/status", "summary": "App status"},
|
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{"method": "GET", "path": "/dash", "summary": "Sub-mounted Dash application"},
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]
|
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}
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|
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|
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@app.get("/status")
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def get_status():
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return {"status": "ok"}
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|
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# A bit odd, but the only way I've been able to get prefixing of the Dash app
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# to work is by allowing the Dash/Flask app to prefix itself, then mounting
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# it to root
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dash_app = create_dash_app(requests_pathname_prefix="/dash/")
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app.mount("/dash", WSGIMiddleware(dash_app.server))
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|
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|
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if __name__ == "__main__":
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uvicorn.run(app, port=8000)
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@ -1,61 +0,0 @@
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import dash
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from dash.dependencies import Input, Output
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from dash import dcc, html
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import flask
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import pandas as pd
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import os
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|
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|
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def create_dash_app(requests_pathname_prefix: str = None) -> dash.Dash:
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"""
|
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Sample Dash application from Plotly: https://github.com/plotly/dash-hello-world/blob/master/app.py
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"""
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server = flask.Flask(__name__)
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server.secret_key = os.environ.get('secret_key', 'secret')
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|
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df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/hello-world-stock.csv')
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app = dash.Dash(__name__, server=server, requests_pathname_prefix=requests_pathname_prefix)
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|
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app.scripts.config.serve_locally = False
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dcc._js_dist[0]['external_url'] = 'https://cdn.plot.ly/plotly-basic-latest.min.js'
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|
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app.layout = html.Div([
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html.H1('Stock Tickers'),
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dcc.Dropdown(
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id='my-dropdown',
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options=[
|
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{'label': 'Tesla', 'value': 'TSLA'},
|
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{'label': 'Apple', 'value': 'AAPL'},
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{'label': 'Coke', 'value': 'COKE'}
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],
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value='TSLA'
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),
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dcc.Graph(id='my-graph')
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], className="container")
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|
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@app.callback(Output('my-graph', 'figure'),
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[Input('my-dropdown', 'value')])
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def update_graph(selected_dropdown_value):
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dff = df[df['Stock'] == selected_dropdown_value]
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return {
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'data': [{
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'x': dff.Date,
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'y': dff.Close,
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'line': {
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'width': 3,
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'shape': 'spline'
|
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}
|
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}],
|
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'layout': {
|
||||
'margin': {
|
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'l': 30,
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'r': 20,
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'b': 30,
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't': 20
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}
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}
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}
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return app
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@ -1,767 +0,0 @@
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[[package]]
|
||||
name = "anyio"
|
||||
version = "3.4.0"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6.2"
|
||||
|
||||
[package.dependencies]
|
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idna = ">=2.8"
|
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sniffio = ">=1.1"
|
||||
|
||||
[package.extras]
|
||||
doc = ["sphinx-rtd-theme", "sphinx-autodoc-typehints (>=1.2.0)"]
|
||||
test = ["coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "pytest (>=6.0)", "pytest-mock (>=3.6.1)", "trustme", "contextlib2", "uvloop (<0.15)", "mock (>=4)", "uvloop (>=0.15)"]
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trio = ["trio (>=0.16)"]
|
||||
|
||||
[[package]]
|
||||
name = "asgiref"
|
||||
version = "3.4.1"
|
||||
description = "ASGI specs, helper code, and adapters"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.extras]
|
||||
tests = ["pytest", "pytest-asyncio", "mypy (>=0.800)"]
|
||||
|
||||
[[package]]
|
||||
name = "black"
|
||||
version = "21.12b0"
|
||||
description = "The uncompromising code formatter."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6.2"
|
||||
|
||||
[package.dependencies]
|
||||
click = ">=7.1.2"
|
||||
mypy-extensions = ">=0.4.3"
|
||||
pathspec = ">=0.9.0,<1"
|
||||
platformdirs = ">=2"
|
||||
tomli = ">=0.2.6,<2.0.0"
|
||||
typing-extensions = [
|
||||
{version = ">=3.10.0.0", markers = "python_version < \"3.10\""},
|
||||
{version = "!=3.10.0.1", markers = "python_version >= \"3.10\""},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
colorama = ["colorama (>=0.4.3)"]
|
||||
d = ["aiohttp (>=3.7.4)"]
|
||||
jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
|
||||
python2 = ["typed-ast (>=1.4.3)"]
|
||||
uvloop = ["uvloop (>=0.15.2)"]
|
||||
|
||||
[[package]]
|
||||
name = "brotli"
|
||||
version = "1.0.9"
|
||||
description = "Python bindings for the Brotli compression library"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "click"
|
||||
version = "8.0.3"
|
||||
description = "Composable command line interface toolkit"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
colorama = {version = "*", markers = "platform_system == \"Windows\""}
|
||||
|
||||
[[package]]
|
||||
name = "colorama"
|
||||
version = "0.4.4"
|
||||
description = "Cross-platform colored terminal text."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
|
||||
[[package]]
|
||||
name = "dash"
|
||||
version = "2.0.0"
|
||||
description = "A Python framework for building reactive web-apps. Developed by Plotly."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
dash-core-components = "2.0.0"
|
||||
dash-html-components = "2.0.0"
|
||||
dash-table = "5.0.0"
|
||||
Flask = ">=1.0.4"
|
||||
flask-compress = "*"
|
||||
plotly = ">=5.0.0"
|
||||
|
||||
[package.extras]
|
||||
dev = ["dash-flow-example (==0.0.5)", "dash-dangerously-set-inner-html", "mock (==4.0.3)", "flake8 (==3.9.2)", "PyYAML (==5.4.1)", "pylint (==2.10.2)", "black (==21.6b0)", "fire (==0.4.0)", "coloredlogs (==15.0.1)", "flask-talisman (==0.8.1)", "isort (==4.3.21)", "orjson (==3.3.1)", "orjson (==3.6.1)"]
|
||||
testing = ["pytest (>=6.0.2)", "pytest-sugar (>=0.9.4)", "pytest-mock (>=3.2.0)", "lxml (>=4.6.2)", "selenium (>=3.141.0)", "percy (>=2.0.2)", "requests[security] (>=2.21.0)", "beautifulsoup4 (>=4.8.2)", "waitress (>=1.4.4)", "diskcache (>=5.2.1)", "multiprocess (>=0.70.12)", "redis (>=3.5.3)", "psutil (>=5.8.0)", "celery[redis] (>=5.1.2)", "flaky (>=3.7.0)", "cryptography (<3.4)"]
|
||||
|
||||
[[package]]
|
||||
name = "dash-core-components"
|
||||
version = "2.0.0"
|
||||
description = "Core component suite for Dash"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "dash-html-components"
|
||||
version = "2.0.0"
|
||||
description = "Vanilla HTML components for Dash"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "dash-table"
|
||||
version = "5.0.0"
|
||||
description = "Dash table"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "fastapi"
|
||||
version = "0.70.0"
|
||||
description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6.1"
|
||||
|
||||
[package.dependencies]
|
||||
pydantic = ">=1.6.2,<1.7 || >1.7,<1.7.1 || >1.7.1,<1.7.2 || >1.7.2,<1.7.3 || >1.7.3,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0"
|
||||
starlette = "0.16.0"
|
||||
|
||||
[package.extras]
|
||||
all = ["requests (>=2.24.0,<3.0.0)", "jinja2 (>=2.11.2,<4.0.0)", "python-multipart (>=0.0.5,<0.0.6)", "itsdangerous (>=1.1.0,<3.0.0)", "pyyaml (>=5.3.1,<6.0.0)", "ujson (>=4.0.1,<5.0.0)", "orjson (>=3.2.1,<4.0.0)", "email_validator (>=1.1.1,<2.0.0)", "uvicorn[standard] (>=0.12.0,<0.16.0)"]
|
||||
dev = ["python-jose[cryptography] (>=3.3.0,<4.0.0)", "passlib[bcrypt] (>=1.7.2,<2.0.0)", "autoflake (>=1.4.0,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "uvicorn[standard] (>=0.12.0,<0.16.0)"]
|
||||
doc = ["mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=7.1.9,<8.0.0)", "mdx-include (>=1.4.1,<2.0.0)", "mkdocs-markdownextradata-plugin (>=0.1.7,<0.3.0)", "typer-cli (>=0.0.12,<0.0.13)", "pyyaml (>=5.3.1,<6.0.0)"]
|
||||
test = ["pytest (>=6.2.4,<7.0.0)", "pytest-cov (>=2.12.0,<4.0.0)", "mypy (==0.910)", "flake8 (>=3.8.3,<4.0.0)", "black (==21.9b0)", "isort (>=5.0.6,<6.0.0)", "requests (>=2.24.0,<3.0.0)", "httpx (>=0.14.0,<0.19.0)", "email_validator (>=1.1.1,<2.0.0)", "sqlalchemy (>=1.3.18,<1.5.0)", "peewee (>=3.13.3,<4.0.0)", "databases[sqlite] (>=0.3.2,<0.6.0)", "orjson (>=3.2.1,<4.0.0)", "ujson (>=4.0.1,<5.0.0)", "python-multipart (>=0.0.5,<0.0.6)", "flask (>=1.1.2,<3.0.0)", "anyio[trio] (>=3.2.1,<4.0.0)", "types-ujson (==0.1.1)", "types-orjson (==3.6.0)", "types-dataclasses (==0.1.7)"]
|
||||
|
||||
[[package]]
|
||||
name = "flask"
|
||||
version = "2.0.2"
|
||||
description = "A simple framework for building complex web applications."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
click = ">=7.1.2"
|
||||
itsdangerous = ">=2.0"
|
||||
Jinja2 = ">=3.0"
|
||||
Werkzeug = ">=2.0"
|
||||
|
||||
[package.extras]
|
||||
async = ["asgiref (>=3.2)"]
|
||||
dotenv = ["python-dotenv"]
|
||||
|
||||
[[package]]
|
||||
name = "flask-compress"
|
||||
version = "1.10.1"
|
||||
description = "Compress responses in your Flask app with gzip, deflate or brotli."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[package.dependencies]
|
||||
brotli = "*"
|
||||
flask = "*"
|
||||
|
||||
[[package]]
|
||||
name = "h11"
|
||||
version = "0.12.0"
|
||||
description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[[package]]
|
||||
name = "idna"
|
||||
version = "3.3"
|
||||
description = "Internationalized Domain Names in Applications (IDNA)"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.5"
|
||||
|
||||
[[package]]
|
||||
name = "itsdangerous"
|
||||
version = "2.0.1"
|
||||
description = "Safely pass data to untrusted environments and back."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[[package]]
|
||||
name = "jinja2"
|
||||
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{file = "pandas-1.3.4.tar.gz", hash = "sha256:a2aa18d3f0b7d538e21932f637fbfe8518d085238b429e4790a35e1e44a96ffc"},
|
||||
]
|
||||
pathspec = [
|
||||
{file = "pathspec-0.9.0-py2.py3-none-any.whl", hash = "sha256:7d15c4ddb0b5c802d161efc417ec1a2558ea2653c2e8ad9c19098201dc1c993a"},
|
||||
{file = "pathspec-0.9.0.tar.gz", hash = "sha256:e564499435a2673d586f6b2130bb5b95f04a3ba06f81b8f895b651a3c76aabb1"},
|
||||
]
|
||||
platformdirs = [
|
||||
{file = "platformdirs-2.4.0-py3-none-any.whl", hash = "sha256:8868bbe3c3c80d42f20156f22e7131d2fb321f5bc86a2a345375c6481a67021d"},
|
||||
{file = "platformdirs-2.4.0.tar.gz", hash = "sha256:367a5e80b3d04d2428ffa76d33f124cf11e8fff2acdaa9b43d545f5c7d661ef2"},
|
||||
]
|
||||
plotly = [
|
||||
{file = "plotly-5.4.0-py2.py3-none-any.whl", hash = "sha256:1e5c1a5c87caaf68ce0d9872d4636e3ce1f82c7f6988eb20905ff5b58e57525c"},
|
||||
{file = "plotly-5.4.0.tar.gz", hash = "sha256:735d50738c760ecbf3a38e2336b8c1b119bff2d857096e4f68af31089b798161"},
|
||||
]
|
||||
pydantic = [
|
||||
{file = "pydantic-1.8.2-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:05ddfd37c1720c392f4e0d43c484217b7521558302e7069ce8d318438d297739"},
|
||||
{file = "pydantic-1.8.2-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:a7c6002203fe2c5a1b5cbb141bb85060cbff88c2d78eccbc72d97eb7022c43e4"},
|
||||
{file = "pydantic-1.8.2-cp36-cp36m-manylinux2014_i686.whl", hash = "sha256:589eb6cd6361e8ac341db97602eb7f354551482368a37f4fd086c0733548308e"},
|
||||
{file = "pydantic-1.8.2-cp36-cp36m-manylinux2014_x86_64.whl", hash = "sha256:10e5622224245941efc193ad1d159887872776df7a8fd592ed746aa25d071840"},
|
||||
{file = "pydantic-1.8.2-cp36-cp36m-win_amd64.whl", hash = "sha256:99a9fc39470010c45c161a1dc584997f1feb13f689ecf645f59bb4ba623e586b"},
|
||||
{file = "pydantic-1.8.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:a83db7205f60c6a86f2c44a61791d993dff4b73135df1973ecd9eed5ea0bda20"},
|
||||
{file = "pydantic-1.8.2-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:41b542c0b3c42dc17da70554bc6f38cbc30d7066d2c2815a94499b5684582ecb"},
|
||||
{file = "pydantic-1.8.2-cp37-cp37m-manylinux2014_i686.whl", hash = "sha256:ea5cb40a3b23b3265f6325727ddfc45141b08ed665458be8c6285e7b85bd73a1"},
|
||||
{file = "pydantic-1.8.2-cp37-cp37m-manylinux2014_x86_64.whl", hash = "sha256:18b5ea242dd3e62dbf89b2b0ec9ba6c7b5abaf6af85b95a97b00279f65845a23"},
|
||||
{file = "pydantic-1.8.2-cp37-cp37m-win_amd64.whl", hash = "sha256:234a6c19f1c14e25e362cb05c68afb7f183eb931dd3cd4605eafff055ebbf287"},
|
||||
{file = "pydantic-1.8.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:021ea0e4133e8c824775a0cfe098677acf6fa5a3cbf9206a376eed3fc09302cd"},
|
||||
{file = "pydantic-1.8.2-cp38-cp38-manylinux1_i686.whl", hash = "sha256:e710876437bc07bd414ff453ac8ec63d219e7690128d925c6e82889d674bb505"},
|
||||
{file = "pydantic-1.8.2-cp38-cp38-manylinux2014_i686.whl", hash = "sha256:ac8eed4ca3bd3aadc58a13c2aa93cd8a884bcf21cb019f8cfecaae3b6ce3746e"},
|
||||
{file = "pydantic-1.8.2-cp38-cp38-manylinux2014_x86_64.whl", hash = "sha256:4a03cbbe743e9c7247ceae6f0d8898f7a64bb65800a45cbdc52d65e370570820"},
|
||||
{file = "pydantic-1.8.2-cp38-cp38-win_amd64.whl", hash = "sha256:8621559dcf5afacf0069ed194278f35c255dc1a1385c28b32dd6c110fd6531b3"},
|
||||
{file = "pydantic-1.8.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8b223557f9510cf0bfd8b01316bf6dd281cf41826607eada99662f5e4963f316"},
|
||||
{file = "pydantic-1.8.2-cp39-cp39-manylinux1_i686.whl", hash = "sha256:244ad78eeb388a43b0c927e74d3af78008e944074b7d0f4f696ddd5b2af43c62"},
|
||||
{file = "pydantic-1.8.2-cp39-cp39-manylinux2014_i686.whl", hash = "sha256:05ef5246a7ffd2ce12a619cbb29f3307b7c4509307b1b49f456657b43529dc6f"},
|
||||
{file = "pydantic-1.8.2-cp39-cp39-manylinux2014_x86_64.whl", hash = "sha256:54cd5121383f4a461ff7644c7ca20c0419d58052db70d8791eacbbe31528916b"},
|
||||
{file = "pydantic-1.8.2-cp39-cp39-win_amd64.whl", hash = "sha256:4be75bebf676a5f0f87937c6ddb061fa39cbea067240d98e298508c1bda6f3f3"},
|
||||
{file = "pydantic-1.8.2-py3-none-any.whl", hash = "sha256:fec866a0b59f372b7e776f2d7308511784dace622e0992a0b59ea3ccee0ae833"},
|
||||
{file = "pydantic-1.8.2.tar.gz", hash = "sha256:26464e57ccaafe72b7ad156fdaa4e9b9ef051f69e175dbbb463283000c05ab7b"},
|
||||
]
|
||||
python-dateutil = [
|
||||
{file = "python-dateutil-2.8.2.tar.gz", hash = "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86"},
|
||||
{file = "python_dateutil-2.8.2-py2.py3-none-any.whl", hash = "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"},
|
||||
]
|
||||
pytz = [
|
||||
{file = "pytz-2021.3-py2.py3-none-any.whl", hash = "sha256:3672058bc3453457b622aab7a1c3bfd5ab0bdae451512f6cf25f64ed37f5b87c"},
|
||||
{file = "pytz-2021.3.tar.gz", hash = "sha256:acad2d8b20a1af07d4e4c9d2e9285c5ed9104354062f275f3fcd88dcef4f1326"},
|
||||
]
|
||||
six = [
|
||||
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
|
||||
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
|
||||
]
|
||||
sniffio = [
|
||||
{file = "sniffio-1.2.0-py3-none-any.whl", hash = "sha256:471b71698eac1c2112a40ce2752bb2f4a4814c22a54a3eed3676bc0f5ca9f663"},
|
||||
{file = "sniffio-1.2.0.tar.gz", hash = "sha256:c4666eecec1d3f50960c6bdf61ab7bc350648da6c126e3cf6898d8cd4ddcd3de"},
|
||||
]
|
||||
starlette = [
|
||||
{file = "starlette-0.16.0-py3-none-any.whl", hash = "sha256:38eb24bf705a2c317e15868e384c1b8a12ca396e5a3c3a003db7e667c43f939f"},
|
||||
{file = "starlette-0.16.0.tar.gz", hash = "sha256:e1904b5d0007aee24bdd3c43994be9b3b729f4f58e740200de1d623f8c3a8870"},
|
||||
]
|
||||
tenacity = [
|
||||
{file = "tenacity-8.0.1-py3-none-any.whl", hash = "sha256:f78f4ea81b0fabc06728c11dc2a8c01277bfc5181b321a4770471902e3eb844a"},
|
||||
{file = "tenacity-8.0.1.tar.gz", hash = "sha256:43242a20e3e73291a28bcbcacfd6e000b02d3857a9a9fff56b297a27afdc932f"},
|
||||
]
|
||||
tomli = [
|
||||
{file = "tomli-1.2.2-py3-none-any.whl", hash = "sha256:f04066f68f5554911363063a30b108d2b5a5b1a010aa8b6132af78489fe3aade"},
|
||||
{file = "tomli-1.2.2.tar.gz", hash = "sha256:c6ce0015eb38820eaf32b5db832dbc26deb3dd427bd5f6556cf0acac2c214fee"},
|
||||
]
|
||||
typing-extensions = [
|
||||
{file = "typing_extensions-4.0.1-py3-none-any.whl", hash = "sha256:7f001e5ac290a0c0401508864c7ec868be4e701886d5b573a9528ed3973d9d3b"},
|
||||
{file = "typing_extensions-4.0.1.tar.gz", hash = "sha256:4ca091dea149f945ec56afb48dae714f21e8692ef22a395223bcd328961b6a0e"},
|
||||
]
|
||||
uvicorn = [
|
||||
{file = "uvicorn-0.16.0-py3-none-any.whl", hash = "sha256:d8c839231f270adaa6d338d525e2652a0b4a5f4c2430b5c4ef6ae4d11776b0d2"},
|
||||
{file = "uvicorn-0.16.0.tar.gz", hash = "sha256:eacb66afa65e0648fcbce5e746b135d09722231ffffc61883d4fac2b62fbea8d"},
|
||||
]
|
||||
werkzeug = [
|
||||
{file = "Werkzeug-2.0.2-py3-none-any.whl", hash = "sha256:63d3dc1cf60e7b7e35e97fa9861f7397283b75d765afcaefd993d6046899de8f"},
|
||||
{file = "Werkzeug-2.0.2.tar.gz", hash = "sha256:aa2bb6fc8dee8d6c504c0ac1e7f5f7dc5810a9903e793b6f715a9f015bdadb9a"},
|
||||
]
|
||||
|
|
@ -1,21 +0,0 @@
|
|||
[tool.poetry]
|
||||
name = "fastapi-plotly-dash"
|
||||
version = "0.1.0"
|
||||
description = "Sample integration of FastAPI and Dash"
|
||||
authors = ["Russ Snyder <ru.snyder@gmail.com>"]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
|
||||
dash = "^2.0.0"
|
||||
fastapi = "*"
|
||||
pandas = "*"
|
||||
uvicorn = "*"
|
||||
|
||||
[tool.poetry.dev-dependencies]
|
||||
black = "*"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry>=0.12"]
|
||||
build-backend = "poetry.masonry.api"
|
||||
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
import plotly.express as px
|
||||
import pandas
|
||||
import pandas as pd
|
||||
df = px.data.gapminder()
|
||||
df2007 = df.query("year == 2007")
|
||||
print(df2007.head())
|
||||
|
|
@ -41,9 +41,25 @@ fig.show()
|
|||
import plotly.express as px
|
||||
|
||||
df = px.data.iris()
|
||||
|
||||
print(df.columns)
|
||||
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species", title="A Plotly Express Figure")
|
||||
# If you print the figure, you'll see that it's just a regular figure with data and layout
|
||||
# print(fig)
|
||||
fig = px.scatter_matrix(df, dimensions=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'],
|
||||
color='species')
|
||||
fig.show()
|
||||
|
||||
import plotly.express as px
|
||||
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
np.random.seed(1)
|
||||
|
||||
N = 100000
|
||||
|
||||
df = pd.DataFrame(dict(x=np.random.randn(N),
|
||||
y=np.random.randn(N)))
|
||||
|
||||
fig = px.scatter(df, x="x", y="y", render_mode='webgl')
|
||||
|
||||
fig.update_traces(marker_line=dict(width=1, color='DarkSlateGray'))
|
||||
|
||||
fig.show()
|
||||
|
|
@ -11,10 +11,8 @@ fig = dict({
|
|||
"y": [1, 3, 2]}],
|
||||
"layout": {"title": {"text": "A Figure Specified By Python Dictionary"}}
|
||||
})
|
||||
|
||||
# To display the figure defined by this dict, use the low-level plotly.io.show function
|
||||
import plotly.io as pio
|
||||
|
||||
pio.show(fig)
|
||||
|
||||
# Figures as Graph Objects
|
||||
|
|
@ -1,9 +0,0 @@
|
|||
import plotly.express as px
|
||||
|
||||
df = px.data.iris()
|
||||
|
||||
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species", title="A Plotly Express Figure")
|
||||
# If you print the figure, you'll see that it's just a regular figure with data and layout
|
||||
# print(fig)
|
||||
|
||||
fig.show()
|
||||
File diff suppressed because one or more lines are too long
|
|
@ -1,16 +0,0 @@
|
|||
import plotly.express as px
|
||||
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
np.random.seed(1)
|
||||
|
||||
N = 100000
|
||||
|
||||
df = pd.DataFrame(dict(x=np.random.randn(N),
|
||||
y=np.random.randn(N)))
|
||||
|
||||
fig = px.scatter(df, x="x", y="y", render_mode='webgl')
|
||||
|
||||
fig.update_traces(marker_line=dict(width=1, color='DarkSlateGray'))
|
||||
|
||||
fig.show()
|
||||
|
|
@ -0,0 +1,341 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import plotly"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'4.1.1'"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"plotly.__version__"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import pandas as pd"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"data = pd.read_csv('data/nz_weather.csv')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>DATE</th>\n",
|
||||
" <th>Auckland</th>\n",
|
||||
" <th>Christchurch</th>\n",
|
||||
" <th>Dunedin</th>\n",
|
||||
" <th>Hamilton</th>\n",
|
||||
" <th>Wellington</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>2000-01</td>\n",
|
||||
" <td>115.4</td>\n",
|
||||
" <td>47.2</td>\n",
|
||||
" <td>174.8</td>\n",
|
||||
" <td>96.2</td>\n",
|
||||
" <td>91.8</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>2000-02</td>\n",
|
||||
" <td>8.4</td>\n",
|
||||
" <td>25.2</td>\n",
|
||||
" <td>41</td>\n",
|
||||
" <td>8.2</td>\n",
|
||||
" <td>35.2</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>2000-03</td>\n",
|
||||
" <td>57.2</td>\n",
|
||||
" <td>60.8</td>\n",
|
||||
" <td>74.2</td>\n",
|
||||
" <td>33.8</td>\n",
|
||||
" <td>53.4</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>2000-04</td>\n",
|
||||
" <td>106.8</td>\n",
|
||||
" <td>58.2</td>\n",
|
||||
" <td>50</td>\n",
|
||||
" <td>129.6</td>\n",
|
||||
" <td>109.8</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>2000-05</td>\n",
|
||||
" <td>128.2</td>\n",
|
||||
" <td>62.0</td>\n",
|
||||
" <td>'-</td>\n",
|
||||
" <td>98.2</td>\n",
|
||||
" <td>78.2</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" DATE Auckland Christchurch Dunedin Hamilton Wellington\n",
|
||||
"0 2000-01 115.4 47.2 174.8 96.2 91.8\n",
|
||||
"1 2000-02 8.4 25.2 41 8.2 35.2\n",
|
||||
"2 2000-03 57.2 60.8 74.2 33.8 53.4\n",
|
||||
"3 2000-04 106.8 58.2 50 129.6 109.8\n",
|
||||
"4 2000-05 128.2 62.0 '- 98.2 78.2"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"data.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import plotly.graph_objects as go"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"line1 = go.Scatter(x=data['DATE'], y=data['Auckland'], name='Auckland')\n",
|
||||
"line2 = go.Scatter(x=data['DATE'], y=data['Wellington'], name='Wellington')\n",
|
||||
"fig = go.Figure([line1, line2])\n",
|
||||
"fig.update_layout(\n",
|
||||
" title = \"New Zealand Weather\",\n",
|
||||
" xaxis_title = \"Date\",\n",
|
||||
" yaxis_title = \"Weather\"\n",
|
||||
")\n",
|
||||
"fig.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%% md\n"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"## Bar Chart"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"data_2010 = data[(data['DATE'] >= '2010-01') & (data['DATE'] < '2011-01')]\n",
|
||||
"data_2010"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"bar1 = go.Bar(x = data_2010['DATE'], y = data_2010['Auckland'], \n",
|
||||
" text = data_2010['Auckland'], textposition='outside')\n",
|
||||
"fig = go.Figure(bar1)\n",
|
||||
"fig.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"bar1 = go.Bar(x = data_2010['DATE'], y = data_2010['Auckland'], \n",
|
||||
" text = data_2010['Auckland'], textposition='outside', name='Auckland')\n",
|
||||
"bar2 = go.Bar(x = data_2010['DATE'], y = data_2010['Wellington'], \n",
|
||||
" text = data_2010['Wellington'], textposition='outside', name='Wellington')\n",
|
||||
"fig = go.Figure([bar1, bar2])\n",
|
||||
"fig.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%% md\n"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"## Histogram"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"hist = go.Histogram(x = data['Auckland'])\n",
|
||||
"fig = go.Figure(hist)\n",
|
||||
"fig.update_layout(bargap=0.1)\n",
|
||||
"fig.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"hist = go.Histogram(x = data['Auckland'], xbins={'size': 10})\n",
|
||||
"fig = go.Figure(hist)\n",
|
||||
"fig.update_layout(bargap=0.1)\n",
|
||||
"fig.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.5.4"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
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Loading…
Reference in New Issue