A tool for creating SVG timelines from simple JSON input.

Overview

Timeline

A tool for creating SVG timelines from JSON.

Example

You will be able to create timelines that look like this:

simple timeline example

from JSON that looks like this:

{
	"width" : 750,
	"start" : "Oct 8 2015",
	"end" : "Oct 15 2015",	
	"num_ticks" : 14,
	"tick_format" : "%b %d, %Y - %I:%M%p",
	"callouts" : [
		["ABC easy as 123", "Oct 14, 2015 3pm"],		
		["Midnight Event A", "12am Oct 10, 2015", "#DD0000"],
		["Noon Event A", "12pm Oct 10, 2015"],		
		["5pm Event A", "5pm Oct 10, 2015"],				
		["Something amazing happening", "Oct 11, 2015"],
		["Awesome Event B", "Oct 12, 2015", "#DD0000"],
		["C", "Oct 13, 2015"],
		["Event E", "Oct 14, 2015"]
	],
	"eras" : [
		["Era 1", "12pm Oct 8, 2015", "3am Oct 12, 2015", "#CD3F85"],
		["Era 2", "8am Oct 12, 2015", "12am Oct 15, 2015", "#C0C0FF"]
	]
}

Data Format

The input file is a JSON document that describes the start and end points of the timeline, tickmarks along the main axis, as well as callouts to specifc dates/times, and eras which visually mark areas along the axis. Many of the fields are dates, which can be described in several common date formats (e.g., "3/14/15", "Nov 11, 2011", etc.) and may optionally also include a time of day (e.g. "3/14/15 9:26am"). (Date/time parsing is handled by the Python package parsedatetime, which parses many formats.)

Required Fields

The only required fields are width, start, and end. All other fields are optional.

  • width describes the width, in pixels, of the output SVG document. The height will be determined automatically.
  • start is the date/time of the leftmost date/time on the axis.
  • end is the date/time of the rightmost date/time on the axis.

Optional Fields

  • num_ticks contols the number of tickmarks along the axis between the start and end date/times (inclusive). If this field is not present, no tickmarks will be generated except for those at the start and end dates.
  • tick_format describes the string format of the tickmarks along the axis. It follows the Python datetime formatting conventions.

Callouts

Callouts along the axis are described in the callouts list. Each entry in the callouts list is itself a list with either two or three values, all of which are strings. The first two values are required, while the third is optional. The first value is the text description of the callout (e.g., "Pi Day"), and the second value is the date/time of the callout (e.g., "3/14/15 9:26am"). The optional third value can specify a color for the callout, either a color hexcode starting with a # or a SVG color alias.

Example:

["Ultimate Pi Day", "3/14/15 9:26am"]

or, with a custom callout color:

["Ultimate Pi Day", "3/14/15 9:26am", "#CD3F85"]

Eras

Eras are described in the eras list. Like the callout list, each entry in the eras list is itself a list with either three or four values. The first three are required while the fourth is option; all values are strings. The first value is a text description of the era (e.g., "Summer"), while the second and third values are the start and end date/times of the era, respectively (e.g., "6/21/15 12am", and "9/20/15 11:59pm"). The optional fourth value can specify a color for the era, either a color hexcode starting with a # or a SVG color alias.

Example:

["Summer 2015", "6/21/15 12am", "9/20/15 11:59pm"]

or, with a custom era color:

["Summer 2015", "6/21/15 12am", "9/20/15 11:59pm", "Orange"]

Prerequisites

You must have a python 2.7 installation and install the Python packages parsedatetime and svgwrite.

Usage

./make_timeline.py in.json > out.svg

Owner
Jason Reisman
Jason Reisman
Manim is an animation engine for explanatory math videos.

A community-maintained Python framework for creating mathematical animations.

12.4k Dec 30, 2022
A tool to plot and execute Rossmos's Formula, that helps to catch serial criminals using mathematics

Rossmo Plotter A tool to plot and execute Rossmos's Formula using python, that helps to catch serial criminals using mathematics Author: Amlan Saha Ku

Amlan Saha Kundu 3 Aug 29, 2022
Visualize your pandas data with one-line code

PandasEcharts 简介 基于pandas和pyecharts的可视化工具 安装 pip 安装 $ pip install pandasecharts 源码安装 $ git clone https://github.com/gamersover/pandasecharts $ cd pand

陈华杰 2 Apr 13, 2022
This component provides a wrapper to display SHAP plots in Streamlit.

streamlit-shap This component provides a wrapper to display SHAP plots in Streamlit.

Snehan Kekre 30 Dec 10, 2022
Lightspin AWS IAM Vulnerability Scanner

Red-Shadow Lightspin AWS IAM Vulnerability Scanner Description Scan your AWS IAM Configuration for shadow admins in AWS IAM based on misconfigured den

Lightspin 90 Dec 14, 2022
Create 3d loss surface visualizations, with optimizer path. Issues welcome!

MLVTK A loss surface visualization tool Simple feed-forward network trained on chess data, using elu activation and Adam optimizer Simple feed-forward

7 Dec 21, 2022
Make your BSC transaction simple.

bsc_trade_history Make your BSC transaction simple. 中文ReadMe Background: inspired by debank ,Practice my hands on this small project Blog:Crypto-BscTr

foolisheddy 7 Jul 06, 2022
Visualization Library

CamViz Overview // Installation // Demos // License Overview CamViz is a visualization library developed by the TRI-ML team with the goal of providing

Toyota Research Institute - Machine Learning 67 Nov 24, 2022
A TileDB backend for xarray.

TileDB-xarray This library provides a backend engine to xarray using the TileDB Storage Engine. Example usage: import xarray as xr dataset = xr.open_d

TileDB, Inc. 14 Jun 02, 2021
Compute and visualise incidence (reworking of the original incidence package)

incidence2 incidence2 is an R package that implements functions and classes to compute, handle and visualise incidence from linelist data. It refocuss

15 Nov 22, 2022
Lumen provides a framework for visual analytics, which allows users to build data-driven dashboards from a simple yaml specification

Lumen project provides a framework for visual analytics, which allows users to build data-driven dashboards from a simple yaml specification

HoloViz 120 Jan 04, 2023
Plot toolbox based on Matplotlib, simple and elegant.

Elegant-Plot Plot toolbox based on Matplotlib, simple and elegant. 绘制效果 绘制过程 数据准备 每种图标类型的目录下有data.csv文件,依据样例数据填入自己的数据。

3 Jul 15, 2022
Streamlit dashboard examples - Twitter cashtags, StockTwits, WSB, Charts, SQL Pattern Scanner

streamlit-dashboards Streamlit dashboard examples - Twitter cashtags, StockTwits, WSB, Charts, SQL Pattern Scanner Tutorial Video https://ww

122 Dec 21, 2022
Python implementation of the Density Line Chart by Moritz & Fisher.

PyDLC - Density Line Charts with Python Python implementation of the Density Line Chart (Moritz & Fisher, 2018) to visualize large collections of time

Charles L. Bérubé 10 Jan 06, 2023
Generate the report for OCULTest.

Sample report generated in this function Usage example from utils.gen_report import generate_report if __name__ == '__main__': # def generate_rep

Philip Guo 1 Mar 10, 2022
metedraw is a project mainly for data visualization projects of Atmospheric Science, Marine Science, Environmental Science or other majors

It is mainly for data visualization projects of Atmospheric Science, Marine Science, Environmental Science or other majors.

Nephele 11 Jul 05, 2022
Easily convert matplotlib plots from Python into interactive Leaflet web maps.

mplleaflet mplleaflet is a Python library that converts a matplotlib plot into a webpage containing a pannable, zoomable Leaflet map. It can also embe

Jacob Wasserman 502 Dec 28, 2022
WhatsApp Chat Analyzer is a WebApp and it can be used by anyone to analyze their chat. 😄

WhatsApp-Chat-Analyzer You can view the working project here. WhatsApp chat Analyzer is a WebApp where anyone either tech or non-tech person can analy

Prem Chandra Singh 26 Nov 02, 2022
NumPy and Pandas interface to Big Data

Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems. Blaze allows Python users a familiar inte

Blaze 3.1k Jan 01, 2023
Apache Superset is a Data Visualization and Data Exploration Platform

Superset A modern, enterprise-ready business intelligence web application. Why Superset? | Supported Databases | Installation and Configuration | Rele

The Apache Software Foundation 50k Jan 06, 2023