matplotlib / matplotlib/mplfinance

Marking / Highlighting After Hours

Open
#365 4 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

question
Dominant language
Python
Stars
4.4k
Forks
678
PR merge metrics
No merged PRs in 30d

Description

I'm working on styling for my charts and I'm wondering if there's a good way to highlight / grey out / mark after hours trading periods in some way like some graphing programs do.

Here's an example of one of my charts at the moment:
![no markers](https://user-images.githubusercontent.com/46771056/111939717-3d177700-8a8a-11eb-80d3-e857cb6f669b.png)

Here's a quick photoshop markup of what I want to do:
![with markers](https://user-images.githubusercontent.com/46771056/111940221-72709480-8a8b-11eb-8b9f-bfdd07a98629.png)

I'm currently pulling from an api that gives data on a multitude of periods and intervals. I saw there was functionality for highlighting between timestamps with the fill_between feature. However, I'm a bit stumped on how to make sure I cover all after hours periods in any given period. Any pointers in the right direction on doing this properly would be greatly appreciated!

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing the existing fill_between functionality and the supplied chart examples. Work out how after-hours periods should be identified across the API's periods and intervals, then verify that the resulting chart marks those periods consistently.

Written by the indexing model from the issue text.

Assessment

Tech stack
matplotlib, python
Domain
data-visualization
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.