A Python package for creating graphical timelines of historical data using Plotly
Github: https://github.com/dh3968mlq/hdtimelines
Documentation: https://hdtimelines.readthedocs.io/en/
PyPI: https://pypi.org/project/hdtimelines/
An app that uese this package: https://timeflows.uk/
Some starter datasets (.csv): https://github.com/dh3968mlq/historicaldate-data
Uses the historicaldate package for dates:
- Dates in input files are in a natural readable format, such as '25 Dec 1066'
- Dates can be uncertain (e.g. 'circa 1028') and can be BC (e.g. '525 BC')
- It is possible to specify start and end dates of persistent events, such as a wars or monarchs' reigns, and/or birth and death dates of persons
In the timeline display:
- Install this package: pip install hdtimelines
- Download sample data from https://github.com/dh3968mlq/historicaldate-data, and/or
- Create .csv files of data (see below for column names and date formats)
- Create and run a Python program, similar to below, or see sample timeline code in the timelines folder in this repository
# Sample code for a timeline of British monarchs and Prime Ministers
# The folder that historicaldate-data has been downloaded to...
dataroot = "/svol1/pishare/users/pi/repos/timelines2/historicaldate-data"
from hdtimelines import pltimeline
import pandas as pd
df1 = pd.read_csv(f"{dataroot}/data/History/Europe/English and British Monarchs.csv",
na_filter=False)
df2 = pd.read_csv(f"{dataroot}/data/History/Europe/British Prime Ministers.csv",
na_filter=False)
pltl = pltimeline.plTimeLine()
pltl.add_topic_from_df(df1, title="English and British Monarchs")
pltl.add_topic_from_df(df2, title="British Prime Ministers")
pltl.show() # Show in a browser, or...
pltl.write_html("/home/pi/example_timeline.html")Dataframes passed to add_topic_from_df have one row per event or life, and specific column names. label must be present, together with either hdate or both of hdate_birth and hdate_death. All other columns are optional.
| Column | Usage |
|---|---|
| label | Event label, appears on the timeline |
| description | Extended description, used for hovertext |
| hdate | Date of event, or start date if it is a persistent event |
| hdate_end | End date of a persistent event |
| hdate_birth | A person's birth date |
| hdate_death | A person's date of death, defaults to alive if hdate_birth is present |
| htext_end | Hover text linked to the marker drawn at hdate_end |
| color (or colour) | Colour to draw the event or life |
| url | hyperlink, active by clicking on the displayed label |
| rank | An integer, use together with max_rank to control which rows are displayed |
| min_xrange_years | An integer. The event is displayed only if the displayed date range is greater than min_xrange_years |
| max_xrange_years | An integer. The event is displayed only if the displayed date range is less than or equal to max_xrange_years |
Date formats are described in detail at https://historicaldate.readthedocs.io/en/
In brief:
- Two core formats are supported by default:
- 25 Dec 1066 (and variants)
- 1066-12-25
- Additional non-default formats available:
- 25/12/1066
- 12/25/1066
- Dec 25 1066
- Imprecise dates, such as '1066' or 'circa 1066' are allowed
- BC dates are supported such as '385 BC'
- Ongoing events and lives are supported by setting hdate_end or hdate_death to 'ongoing'. A blank value of hdate_death isinterprested as meaning a person is still alive.
max_xrange_years, min_xrange_years
Released to PyPI and documentation on readthedocs
Split from historicaldate package (https://github.com/dh3968mlq/historicaldate)
add_event_set renamed to add_topic_from_df
- BC dates can now be displayed on timelines (xmode=years)
- X-axis (date axis) labels moved to top
add_event_set() now updates yaxes to fit the displayed data
New method plTimeLine().fit_xaxis(self, mindate=None, maxdate=None) that fits the X axis either to the data or to a specified range of dates
X axis date labels moved to top of display
Study range filtering added, parameters study_range_start and study_range_end of the add_event_set method. Event sets lying entirely outside the study range are not displayed.
Filtering on the value of a rank column in input data, parameter max_rank of the add_event_set method.
- New English Football timeline code (english_football.py)
- New hover_datetype parameter to add_event_set
- New htext_end column supported