DatePickerRange | Dash for Python Documentation (2022)

dcc.DatePickerRange is a component for rendering calendars from which users can select a range of dates.

You can use either strings in the form YYYY-MM-DD or date objects from the datetime module to provide dates to Dash components. Strings are preferred because that’s the form dates take as callback arguments. If you are using date objects, we recommend using datetime.date so there is no time part. dcc.DatePickerRange accepts dates with a time part, but this can be confusing, particularly for the initial call of a callback. After the user chooses a new date, there will be no time part—only the date. If you already have adatetime.datetime object, you can convert it with date().

Month and Display Format

The month_format property determines how calendar headers are displayed when the calendar is opened.
The display_format property determines how selected dates are displayed in the dcc.DatePickerRange component.

Both of these properties are configured through strings that use a combination of any of the following tokens.

String TokenExampleDescription
YYYY20144 or 2 digit year
YY142 digit year
Y-25Year with any number of digits and sign
Q1..4Quarter of year. Sets month to first month in quarter.
M MM1..12Month number
MMM MMMMJan..DecemberMonth name
D DD1..31Day of month
Do1st..31stDay of month with ordinal
DDD DDDD1..365Day of year
X1410715640.579Unix timestamp
x1410715640579Unix ms timestamp

Examples

Find a few usage examples below.

For more examples of minimal Dash apps that use dcc.DatePickerRange, go to the community-driven Example Index.

Simple DatePickerRange Example

This is a simple example of a dcc.DatePickerRange component tied to a callback.

The min_date_allowed and max_date_allowed properties define the minimum and maximum selectable dates on the calendar while initial_visible_month defines the calendar month that is first displayed when the dcc.DatePickerRange component is opened.

from datetime import datefrom dash import Dash, dcc, htmlfrom dash.dependencies import Input, Outputapp = Dash(__name__)app.layout = html.Div([ dcc.DatePickerRange( id='my-date-picker-range', min_date_allowed=date(1995, 8, 5), max_date_allowed=date(2017, 9, 19), initial_visible_month=date(2017, 8, 5), end_date=date(2017, 8, 25) ), html.Div(id='output-container-date-picker-range')])@app.callback( Output('output-container-date-picker-range', 'children'), Input('my-date-picker-range', 'start_date'), Input('my-date-picker-range', 'end_date'))def update_output(start_date, end_date): string_prefix = 'You have selected: ' if start_date is not None: start_date_object = date.fromisoformat(start_date) start_date_string = start_date_object.strftime('%B %d, %Y') string_prefix = string_prefix + 'Start Date: ' + start_date_string + ' | ' if end_date is not None: end_date_object = date.fromisoformat(end_date) end_date_string = end_date_object.strftime('%B %d, %Y') string_prefix = string_prefix + 'End Date: ' + end_date_string if len(string_prefix) == len('You have selected: '): return 'Select a date to see it displayed here' else: return string_prefixif __name__ == '__main__': app.run_server(debug=True)

Month Format Examples

You can set month_format to any permutation of the string tokens shown in Month and Display Format above to change how calendar titles are displayed in the dcc.DatePickerRange component.

from dash import dccfrom datetime import datedcc.DatePickerRange( month_format='MMM Do, YY', end_date_placeholder_text='MMM Do, YY', start_date=date(2017, 6, 21))
from dash import dccfrom datetime import datedcc.DatePickerRange( month_format='M-D-Y-Q', end_date_placeholder_text='M-D-Y-Q', start_date=date(2017, 6, 21))
(Video) DatePickerRange - Python Dash Plotly
from dash import dccfrom datetime import datedcc.DatePickerRange( month_format='MMMM Y', end_date_placeholder_text='MMMM Y', start_date=date(2017, 6, 21))

Display Format Examples

You can use any permutation of the string tokens shown in Month and Display Format above to change how selected dates are displayed in the dcc.DatePickerRange component.

from dash import dccfrom datetime import datedcc.DatePickerRange( end_date=date(2017, 6, 21), display_format='MMM Do, YY', start_date_placeholder_text='MMM Do, YY')
from dash import dccfrom datetime import datedcc.DatePickerRange( end_date=date(2017, 6, 21), display_format='M-D-Y-Q', start_date_placeholder_text='M-D-Y-Q')
from dash import dccfrom datetime import datedcc.DatePickerRange( end_date=date(2017, 6, 21), display_format='MMMM Y, DD', start_date_placeholder_text='MMMM Y, DD')
from dash import dccfrom datetime import datedcc.DatePickerRange( end_date=date(2017, 6, 21), display_format='X', start_date_placeholder_text='X')

Vertical Calendar and Placeholder Text

The dcc.DatePickerRange component can be rendered in two orientations, either horizontally or vertically. If calendar_orientation is set to 'vertical', it will be rendered vertically and will default to 'horizontal' if not defined.

start_date_placeholder_text and end_date_placeholder_text define the grey default text defined in the calendar input boxes when no date is selected.

from dash import dccdcc.DatePickerRange( start_date_placeholder_text="Start Period", end_date_placeholder_text="End Period", calendar_orientation='vertical',)
(Video) PyDoc - A Celebration of Documentation || Python Tutorial || Learn Python Programming

Minimum Nights, Calendar Clear, and Portals

The minimum_nights property defines the number of nights that must be in between the range of two selected dates.

When the clearable property is set to True, the dcc.DatePickerRange renders with a small ‘x’ that the user can select to remove selected dates.

The dcc.DatePickerRange component supports two different portal types, one being a full screen portal (with_full_screen_portal) and another being a simple screen overlay, like the one shown below (with_portal).

from dash import dccfrom datetime import datedcc.DatePickerRange( minimum_nights=5, clearable=True, with_portal=True, start_date=date(2017, 6, 21))

Right to Left Calendars and First Day of Week

When the is_RTL property is set to True the calendar will be rendered from right to left.

The first_day_of_week property allows you to define which day of the week will be set as the first day of the week. In the example below, Tuesday is the first day of the week.

from dash import dccfrom datetime import datedcc.DatePickerRange( is_RTL=True, first_day_of_week=3, start_date=date(2017, 6, 21))

DatePickerRange Properties

Access this documentation in your Python terminal with:
```python

help(dash.dcc.DatePickerRange)
```

Our recommended IDE for writing Dash apps is Dash Enterprise’s
Data Science Workspaces,
which has typeahead support for Dash Component Properties.
Find out if your company is usingDash Enterprise.

start_date (string; optional):
Specifies the starting date for the component. Accepts
datetime.datetime objects or strings in the format ‘YYYY-MM-DD’.

end_date (string; optional):
Specifies the ending date for the component. Accepts datetime.datetime
objects or strings in the format ‘YYYY-MM-DD’.

(Video) #15 Python Documentation- Python Tutorials For Beginners

min_date_allowed (string; optional):
Specifies the lowest selectable date for the component. Accepts
datetime.datetime objects or strings in the format ‘YYYY-MM-DD’.

max_date_allowed (string; optional):
Specifies the highest selectable date for the component. Accepts
datetime.datetime objects or strings in the format ‘YYYY-MM-DD’.

disabled_days (list of strings; optional):
Specifies additional days between min_date_allowed and
max_date_allowed that should be disabled. Accepted datetime.datetime
objects or strings in the format ‘YYYY-MM-DD’.

minimum_nights (number; optional):
Specifies a minimum number of nights that must be selected between the
startDate and the endDate.

updatemode (a value equal to: ‘singledate’ or ‘bothdates’; default 'singledate'):
Determines when the component should update its value. If bothdates,
then the DatePicker will only trigger its value when the user has
finished picking both dates. If singledate, then the DatePicker will
update its value as one date is picked.

start_date_placeholder_text (string; optional):
Text that will be displayed in the first input box of the date picker
when no date is selected. Default value is ‘Start Date’.

end_date_placeholder_text (string; optional):
Text that will be displayed in the second input box of the date picker
when no date is selected. Default value is ‘End Date’.

initial_visible_month (string; optional):
Specifies the month that is initially presented when the user opens
the calendar. Accepts datetime.datetime objects or strings in the
format ‘YYYY-MM-DD’.

clearable (boolean; default False):
Whether or not the dropdown is “clearable”, that is, whether or not a
small “x” appears on the right of the dropdown that removes the
selected value.

reopen_calendar_on_clear (boolean; default False):
If True, the calendar will automatically open when cleared.

display_format (string; optional):
Specifies the format that the selected dates will be displayed valid
formats are variations of “MM YY DD”. For example: “MM YY DD” renders
as ‘05 10 97’ for May 10th 1997 “MMMM, YY” renders as ‘May, 1997’ for
May 10th 1997 “M, D, YYYY” renders as ‘07, 10, 1997’ for September
10th 1997 “MMMM” renders as ‘May’ for May 10 1997.

month_format (string; optional):
Specifies the format that the month will be displayed in the calendar,
valid formats are variations of “MM YY”. For example: “MM YY” renders
as ‘05 97’ for May 1997 “MMMM, YYYY” renders as ‘May, 1997’ for May
1997 “MMM, YY” renders as ‘Sep, 97’ for September 1997.

first_day_of_week (a value equal to: 0, 1, 2, 3, 4, 5 or 6; default 0):
Specifies what day is the first day of the week, values must be from
[0, …, 6] with 0 denoting Sunday and 6 denoting Saturday.

show_outside_days (boolean; optional):
If True the calendar will display days that rollover into the next
month.

stay_open_on_select (boolean; default False):
If True the calendar will not close when the user has selected a value
and will wait until the user clicks off the calendar.

calendar_orientation (a value equal to: ‘vertical’ or ‘horizontal’; default 'horizontal'):
Orientation of calendar, either vertical or horizontal. Valid options
are ‘vertical’ or ‘horizontal’.

number_of_months_shown (number; default 1):
Number of calendar months that are shown when calendar is opened.

with_portal (boolean; default False):
If True, calendar will open in a screen overlay portal, not supported
on vertical calendar.

(Video) Dash and Python 4: Callbacks

with_full_screen_portal (boolean; default False):
If True, calendar will open in a full screen overlay portal, will take
precedent over ‘withPortal’ if both are set to True, not supported on
vertical calendar.

day_size (number; default 39):
Size of rendered calendar days, higher number means bigger day size
and larger calendar overall.

is_RTL (boolean; default False):
Determines whether the calendar and days operate from left to right or
from right to left.

disabled (boolean; default False):
If True, no dates can be selected.

start_date_id (string; optional):
The HTML element ID of the start date input field. Not used by Dash,
only by CSS.

end_date_id (string; optional):
The HTML element ID of the end date input field. Not used by Dash,
only by CSS.

style (dict; optional):
CSS styles appended to wrapper div.

className (string; optional):
Appends a CSS class to the wrapper div component.

id (string; optional):
The ID of this component, used to identify dash components in
callbacks. The ID needs to be unique across all of the components in
an app.

loading_state (dict; optional):
Object that holds the loading state object coming from dash-renderer.

loading_state is a dict with keys:

  • component_name (string; optional):
    Holds the name of the component that is loading.

  • is_loading (boolean; optional):
    Determines if the component is loading or not.

  • prop_name (string; optional):
    Holds which property is loading.

persistence (boolean | string | number; optional):
Used to allow user interactions in this component to be persisted when
the component - or the page - is refreshed. If persisted is truthy
and hasn’t changed from its previous value, any persisted_props that
the user has changed while using the app will keep those changes, as
long as the new prop value also matches what was given originally.
Used in conjunction with persistence_type and persisted_props.

persisted_props (list of values equal to: ‘start_date’ or ‘end_date’; default ['start_date', 'end_date']):
Properties whose user interactions will persist after refreshing the
component or the page.

persistence_type (a value equal to: ‘local’, ‘session’ or ‘memory’; default 'local'):
Where persisted user changes will be stored: memory: only kept in
memory, reset on page refresh. local: window.localStorage, data is
kept after the browser quit. session: window.sessionStorage, data is
cleared once the browser quit.

FAQs

How do you use dashes in Python? ›

Just like in Flask we initialize Dash by calling the Dash class of dash. Once that is done we can create the layout for our application. We use the Div class from the dash_html_components to create an HTML Div. We then use the HTML components to generate HTML components such as H1, H2 etc.

Is Dash plotly easy to learn? ›

Using the plotly dash, you can create interactive mobile responsive dashboards using python without knowing HTML, CSS and Javascript. Creating plotly dash dashboards is so simple and easy that you can create your dashboards within a day or two.

Is Dash a Python framework? ›

Dash is an open source framework for building data visualization interfaces. Released in 2017 as a Python library, it's grown to include implementations for R and Julia. Dash helps data scientists build analytical web applications without requiring advanced web development knowledge.

Do you need HTML for Dash? ›

Dash is a web app framework that provides pure Python abstraction around HTML, CSS, and JavaScript. Instead of writing HTML or using an HTML templating engine, you compose your layout using Python with the Dash HTML Components module ( dash.

What is the difference between flask and dash? ›

Dash is a data dashboarding tool, while Flask is a minimalist, generic web framework. Flask has no data analytics tools included, although it can work with other Python libraries that do analytics. Use Dash if you want to build a data dashboard.

How do you type a dash? ›

For desktop PC: press “ctrl+minus” on the numeric keypad (the number section on the far right of your keyboard). The trick will not work if you press the hyphen-key on the typewriter section of the keyboard.

Is plotly or Seaborn better? ›

Plotly Express is a better option for your EDA than Seaborn.

What is the difference between plotly and Dash? ›

Show activity on this post. Actually Dash was made by Plotly's creators as a way to easily implement a web interface and create dashboards with Plotly without having to learn javascript, html and other web technologies. With Dash you don't make visualizations, you build an interface to display Plotly's visualizations.

What is Dash vs plotly? ›

The question by the OP is concerning Dash with Jupyter Dashboards: Dash is for creating interactive web-apps, plotly.py is for graphing. They are separate libraries with separate purposes! Dash uses plotly. js for it's core Graph component but matplotlib could also be used through the dash_html_components.

Can you build a dashboard with Python? ›

Dash is a free Python library built by the same company that created the plotly graphing library. With Dash, you can develop web-based, customizable, interactive dashboards, all in Python, without writing HTML or JavaScript. Each Dash app has two main parts: layout: determines what the Dash app looks like.

Does Dash use plotly? ›

Selecting or hovering over data in one plot will update the other plots with cross filtering. Dash apps are powered by Plotly's popular open source graphing library featuring maps like these, financial charts, scientific graphs, and more.

Is Plotly dash free? ›

Yes. Plotly's Dash analytics application framework is also free and open-source software, licensed under the MIT license.

Is dash a front end framework? ›

Traditional “full-stack” app development is done in teams with some members specializing in backend/server technologies like Python, some specializing in front-end technologies like React, and some specializing in data science. Dash provides a tightly-integrated backend and front-end, entirely written in Python.

What is dash module in Python? ›

Dash is an open-source Python framework used for building analytical web applications. It is a powerful library that simplifies the development of data-driven applications. It's especially useful for Python data scientists who aren't very familiar with web development.

What is Jupyter dash? ›

Jupyter Dash

This library makes it easy to develop Plotly Dash apps interactively from within Jupyter environments (e.g. classic Notebook, JupyterLab, Visual Studio Code notebooks, nteract, PyCharm notebooks, etc.).

Which one is better Django or Flask? ›

Flask is considered more “Pythonic” than Django is basically since Flask web application code is, in most cases, more unequivocal. Flask is the choice of most tenderfoots due to the need of barricades to getting a basic app up and running.

Is Dash better than Shiny? ›

Winner: R Shiny.

It's only boilerplate code, after all. At this initial stage – no, it seems like it doesn't matter. However, for more advanced applications, Dash requires a lot more boilerplate code than Shiny. For instance, there are no reactive intermediate variables with Dash, which is a big drawback.

Is FastAPI better than Flask? ›

FastAPI surpasses Flask in terms of performance, and it is one of the fastest Python web frameworks. Only Starlette and Uvicorn are faster. Because of ASGI, FastAPI supports concurrency and asynchronous code by declaring the endpoints. For concurrent programming, Python 3.4 introduced Async I/O.

What is an en dash symbol? ›

The shorter en dash (–) is used to mark ranges and with the meaning “to” in phrases like “Dover–Calais crossing.” The longer em dash (—) is used to separate extra information or mark a break in a sentence.

Are dash and hyphen the same key? ›

Alternatively known as a dash, subtract, negative, or minus sign, the hyphen ( - ) is a punctuation mark on the underscore key next to the "0" key on US keyboards.

What is em dash example? ›

The em dash can be used in place of a colon when you want to emphasize the conclusion of your sentence. The dash is less formal than the colon. After months of deliberation, the jurors reached a unanimous verdict⁠—guilty. The white sand, the warm water, the sparkling sun⁠—this is what brought them to Fiji.

Should I use Plotly or matplotlib? ›

Plotly has several advantages over matplotlib. One of the main advantages is that only a few lines of codes are necessary to create aesthetically pleasing, interactive plots. The interactivity also offers a number of advantages over static matplotlib plots: Saves time when initially exploring your dataset.

Why use Seaborn instead of matplotlib? ›

Seaborn is more comfortable in handling Pandas data frames. It uses basic sets of methods to provide beautiful graphics in python. Matplotlib works efficiently with data frames and arrays.It treats figures and axes as objects. It contains various stateful APIs for plotting.

Which library is the most used Visualisation library in Python? ›

1. Matplotlib. Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community.

Can Plotly be used offline? ›

Plotly's open-source graphing libraries are free to use, work offline and don't require any account registration. Plotly also has commercial offerings, such as Dash Enterprise and Chart Studio Enterprise.

Is Plotly a framework? ›

Plotly Dash is a reasonably new framework for building machine learning and data science applications. Dash was created by parent company Plotly, who are already well established within the world of data science, due to their 'plotly.py' and 'plotly. js' Python and JavaScript graphing libraries.

Is Dash faster than Streamlit? ›

Streamlit: Streamlit is useful if you want to get a dashboard up and running quickly, and have the flexibility to add lots of components and controls. As well, Streamlit allows you to build a web UI or a dashboard much faster than Dash or Flask.

Can Streamlit replace Flask? ›

Use Streamlit as your Web application base when security is not needed. If you need security from your Web application, use Flask, FastAPI, or Django packages. I am refactoring Flask-based applications into Streamlit-based applications.

Is dash a stateless? ›

Dash is Stateless

Dash was designed to be a stateless framework. Stateless frameworks are more scalable and robust than stateful ones. Most websites that you visit are running on stateless servers.

Can you use Plotly with Flask? ›

In my previous article I demonstrated that you can create a simple web app incorporating Plotly charts without Dash. Instead you can use a combination of Flask and a web page template. This also gives you the advantage to create multi-page apps.

How do I make Python interactive? ›

On Windows, bring up the command prompt and type "py", or start an interactive Python session by selecting "Python (command line)", "IDLE", or similar program from the task bar / app menu. IDLE is a GUI which includes both an interactive mode and options to edit and run files.

What is Plotly in Python? ›

Overview. The plotly Python library is an interactive, open-source plotting library that supports over 40 unique chart types covering a wide range of statistical, financial, geographic, scientific, and 3-dimensional use-cases.

Does plotly use GPU? ›

Dash is an open-source framework from Plotly for building interactive web application-based dashboards using Python. In addition, the RAPIDS suite of open-source software (OSS) libraries gives the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs.

Is Dash low-code? ›

17, 2022 (GLOBE NEWSWIRE) -- Plotly has released Dash Enterprise 5.0, the leading low-code platform for building, scaling, and deploying Python data apps.

How do I build a web-based dashboard? ›

How to Make a Dashboard Website?
  1. Step 1: Find a product-market fit. As the first step, we suggest you research the target audience for your website with dashboard. ...
  2. Step 2: Design. ...
  3. Step 3: Review available tools to speed up development. ...
  4. Step 4: QA. ...
  5. Step 5: Deploy and Maintain.
5 Aug 2020

Is Plotly used in industry? ›

Plotly is most often used by companies with >10000 employees and >1000M dollars in revenue.

How much does Python dash cost? ›

Dash Pricing. Dash has 3 pricing editions, from $74 to $569. A free trial of Dash is also available.

How does Plotly make money? ›

The company behind Plotly is also named Plotly. It has open-sourced a slew of interactive visualization products. It makes money by offering enhanced functionality for many products. It also offers private hosting for a fee.

Is Dash easy to build GUI? ›

Through a couple of simple patterns, Dash abstracts away all of the technologies and protocols that are required to build a full-stack web app with interactive data visualization. Dash is simple enough that you can bind a user interface to your code in less than 10 minutes.

Is Dash better than tableau? ›

Tableau is great for analysing an existing data set, but it is pretty weak at actually calculating things based on user input. Dash is great for that. You have to write code for Dash but that means you can do almost anything with it.

Is Dash full-stack? ›

Dash is an open-source Python library built on top of React. js, Flask, and Plotly. js. The great thing about Dash is that full-stack apps that would typically require a front-end, back-end, and DevOps team to build can now be deployed in hours by data scientists.

How do I create a Dash app? ›

Let's go through this code step-by-step.
  1. 1 — Import Dependencies. Import all necessary libraries inside app.py : import dash. ...
  2. 3.2 — Import Data + Make Plots. The next step is to add your data and the plots you want to be displayed on your app. ...
  3. 3— Initialize App. ...
  4. 3.4 — Design App's Layout. ...
  5. 3.5 —Make your App Interactive.

What is Dash programming? ›

Dash is an open source Python framework for building web applications, created and maintained by the people at Plotly. Dash's web graphics are completely interactive because the framework is built on top of Ploty. js, a JavaScript library written and maintained by Ploty.

What is Python cufflinks? ›

Cufflink is also a python library that connects plotly with pandas so that we can create charts directly on data frames. It basically acts as a plugin.

Can I run dash in Jupyter notebook? ›

Further Learning: For a complete guide on how to build your beautiful dashboard app in pure Python, check out our best-selling book Python Dash with San Francisco Based publisher NoStarch. Problem Formulation: Can you serve a dash app within a Jupyter notebook rather than in a browser? Answer: Yes!

How do I create a jupyter dashboard? ›

Create a new Jupyter notebook document in a language of your choice. Insert markdown and code into the notebook. Run the cells to generate text, plots, widgets, etc. Select either Grid Layout or Report Layout in the Dashboard View toolbar.

How does Dash app work? ›

Dash is an app that enables you to send, pay, receive, save and manage money easily, in a single app, without all the fuss. Built with ironclad security to protect you, your account, money and payments.

What is a dash character? ›

The dash (—), also called the em dash, is the long horizontal bar, much longer than a hyphen. Few keyboards have a dash, but a word processor can usually produce one in one way or another. If your keyboard can't produce a dash, you will have to resort to a hyphen as a stand-in.

What can you do with dash Plotly? ›

Dash Open Source Framework

Plotly stewards Python's leading data viz and UI libraries. With Dash Open Source, you can create data apps on your laptop in pure Python, no JavaScript required. Get familiar with Dash by building a sample app with open source.

Can we create dashboard in Python? ›

Dash by Plotly is an open-source Python package to give an interactive dashboard using Python language and create the flexibility of creating a web application. If you are not familiar with Plotly, it is an interactive visualization package.

What are the 3 types of dashes? ›

There are actually three different types of dashes: the em-dash, the en-dash, and the 3-em dash. The em-dash can be used to replace parentheses, colons, and commas. Generally, using the em-dash makes the writing style more informal—as if you were writing to an old friend.

What is a dash example? ›

Dashes are also used to mark the interruption of a sentence in dialogue: Example: “Help! This horse is going too fast,” the actor yelled. “I think I am fall—.”

What is a dash used for? ›

A dash is a little horizontal line that floats in the middle of a line of text (not at the bottom: that's an underscore). It's longer than a hyphen and is commonly used to indicate a range or a pause. Dashes are used to separate groups of words, not to separate parts of words like a hyphen does.

Is Dash easy to build GUI? ›

Through a couple of simple patterns, Dash abstracts away all of the technologies and protocols that are required to build a full-stack web app with interactive data visualization. Dash is simple enough that you can bind a user interface to your code in less than 10 minutes.

Is Dash better than tableau? ›

Tableau is great for analysing an existing data set, but it is pretty weak at actually calculating things based on user input. Dash is great for that. You have to write code for Dash but that means you can do almost anything with it.

What is the difference between Dash and plotly? ›

Actually Dash was made by Plotly's creators as a way to easily implement a web interface and create dashboards with Plotly without having to learn javascript, html and other web technologies. With Dash you don't make visualizations, you build an interface to display Plotly's visualizations.

How do you visualize data in Python? ›

The process of finding trends and correlations in our data by representing it pictorially is called Data Visualization. To perform data visualization in python, we can use various python data visualization modules such as Matplotlib, Seaborn, Plotly, etc.

How do I make Python interactive? ›

On Windows, bring up the command prompt and type "py", or start an interactive Python session by selecting "Python (command line)", "IDLE", or similar program from the task bar / app menu. IDLE is a GUI which includes both an interactive mode and options to edit and run files.

How do I create a Jupyter dashboard? ›

Create a new Jupyter notebook document in a language of your choice. Insert markdown and code into the notebook. Run the cells to generate text, plots, widgets, etc. Select either Grid Layout or Report Layout in the Dashboard View toolbar.

How do I create a dashboard in PyCharm? ›

Create Your Dash File app.py in Your PyCharm Project
  1. # Run this app with `python app.py` and.
  2. # visit http://127.0.0.1:8050/ in your web browser.
  3. import plotly. express as px.
  4. # assume you have a "long-form" data frame.
  5. # see https://plotly.com/python/px-arguments/ for more options.
  6. id='example-graph',
  7. )
  8. ])

Videos

1. Python Introduction to Panel Widgets & Dashboards
(Ryan Noonan)
2. "Rich" Colorful Dashboard Layout in Shell/Terminal with Python
(1littlecoder)
3. Plotly Tutorial 2021
(Derek Banas)
4. Sphinx - How to generate documentation from python doc strings - Five + Minutes on Tips and Tricks
(Learn Programming with Joel)
5. How to Make a Python Multi Page Application with Plotly Dash
(Charming Data)
6. Plotly Dash Tutorial - Interactive Python Web App Development
(Charming Data)

Top Articles

Latest Posts

Article information

Author: The Hon. Margery Christiansen

Last Updated: 11/03/2022

Views: 6207

Rating: 5 / 5 (50 voted)

Reviews: 89% of readers found this page helpful

Author information

Name: The Hon. Margery Christiansen

Birthday: 2000-07-07

Address: 5050 Breitenberg Knoll, New Robert, MI 45409

Phone: +2556892639372

Job: Investor Mining Engineer

Hobby: Sketching, Cosplaying, Glassblowing, Genealogy, Crocheting, Archery, Skateboarding

Introduction: My name is The Hon. Margery Christiansen, I am a bright, adorable, precious, inexpensive, gorgeous, comfortable, happy person who loves writing and wants to share my knowledge and understanding with you.