gantt charts

This section describes various options available for gantt charts in fivecentplots

See the full API

Setup

Import packages:

%load_ext autoreload
%autoreload 2
import fivecentplots as fcp
import pandas as pd
from pathlib import Path
import datetime

The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

Read some made-up Gantt chart data for the recording schedule of one of the greatest albums of one of the greatest bands:

df = pd.read_csv(Path(fcp.__file__).parent / 'test_data/fake_data_gantt.csv')
df.head()

	Task	Assigned	Start	Stop	Category
0	Record drums	Taylor	2010-09-01	2010-09-05	Recording
1	Record bass	Nate	2010-09-04	2010-09-06	Recording
2	Record rhythm guitar	Pat	2010-09-06	2010-09-08	Recording
3	Record rhythm guitar	Dave	2010-09-06	2010-09-08	Recording
4	Record lead guitar	Chris	2010-09-07	2010-09-09	Recording

Optionally set the design theme (skipping here and using default):

#fcp.set_theme('gray')
#fcp.set_theme('white')

Basic chart

We create a basic Gantt chart showing tasks across a time axis specified by start and stop column containing Datetime values:

fcp.gantt(df, x=['Start', 'Stop'], y='Task', ax_size=[600, 400])

As with other plots, tick label fonts, sizes, and rotations can all be controlled using the correct kwarg. See Grids and ticks for more details.

Grouping

Like all other plots in fivecentplots, Gantt charts can grouped in various ways to provide further insight into the data set. This includes:

• legend

• row

• col

• wrap

keyword options. A couple of examples are shown below.

Legends

Legends can be used to further distinguish various tasks by assignee or other factors. If the same task has multiple assignees, they will be split into two different bars in the chart.

fcp.gantt(df, x=['Start', 'Stop'], y='Task', legend='Assigned', ax_size=[600, 400], gantt_tick_labels_x_rotation=45)

When using a legend, we can also sort the y-axis values based on the order in the legend using keyword order_by_legend=True:

fcp.gantt(df, x=['Start', 'Stop'], y='Task', legend='Assigned', ax_size=[600, 400], gantt_tick_labels_x_rotation=45, order_by_legend=True)

Row/column plot

Row grouping (share_y is automatically disabled):

fcp.gantt(df, x=['Start', 'Stop'], y='Task', row='Category', ax_size=[400, 240])

Text(0, 0, 'Category=Post')
> /Users/steve/Code/fivecentplots/src/fivecentplots/engines/mpl.py(3350)set_axes_rc_labels()
   3348 
   3349         # Col/wrap labels
-> 3350         if (ir == 0 and self.label_col.on) or self.label_wrap.on:
   3351             if self.label_wrap.on:
   3352                 if not self.label_wrap.values_only:

Text(0, 0, 'Category=Recording')
> /Users/steve/Code/fivecentplots/src/fivecentplots/engines/mpl.py(3350)set_axes_rc_labels()
   3348 
   3349         # Col/wrap labels
-> 3350         if (ir == 0 and self.label_col.on) or self.label_wrap.on:
   3351             if self.label_wrap.on:
   3352                 if not self.label_wrap.values_only:

Column grouping (share_y is automatically disabled):

fcp.gantt(df, x=['Start', 'Stop'], y='Task', col='Category', ax_size=[400, 240])

Wrap plot

Notice that share_y is enabled for this type of grouping:

fcp.gantt(df, x=['Start', 'Stop'], y='Task', wrap='Category', ax_size=[400, 240])

Styling

Default style:

fcp.gantt(df, x=['Start', 'Stop'], y='Task', ax_size=[600, 400])

Now with various style modifications:

fcp.gantt(df, x=['Start', 'Stop'], y='Task', ax_size=[600, 400], color_by_bar=True,
          gantt_edge_width=2, gantt_edge_color='#555555', gantt_height=0.2, gantt_fill_alpha=1)

Sorting

By default, the sorting order of tasks is “descending” from top to bottom by date. We can flip that behavior with the keyword sort='ascending':

fcp.gantt(df, x=['Start', 'Stop'], y='Task', sort='ascending', ax_size=[600, 400])

df = pd.read_csv(Path(fcp.__file__).parent / 'test_data/fake_data_gantt_milestone.csv')
df

	Quarter	Priority	Workstream	Description	Owner	Start date	End date	Duration	Milestone	Dependency
0	2025-Q1	P0	Design	Pixel layout	Gary Garrison	01-01-2025	NaN	2w	NaN	NaN
1	2025-Q1	P0	Design	Periphery circuits	Andy Anderson	01-20-2025	03-31-2025	NaN	NaN	Pixel layout
2	2025-Q1	P1	Design	TCAD simulation	Sam Samuelson	02-22-2025	NaN	10d	NaN	NaN
3	2025-Q1	P2	Design	Initial tape out	Amber Amberly	02-22-2025	03-15-2025	NaN	NaN	NaN
4	2025-Q2	P0	Design	Finalize tape out	Amber Amberly	NaN	NaN	1.5m	NaN	Pixel layout; Periphery circuits
5	2025-Q2	P0	Design	Deliver tape out	Amber Amberly	05-30-2025	NaN	NaN	NaN	Finalize tape out
6	2025-Q2	P1	Fab	Test chip	Karthik Sweeny	03-01-2025	04-15-2025	NaN	NaN	NaN
7	2025-Q3	P0	Fab	Alpha samples	Karthik Sweeny	06-30-2025	09-15-2025	NaN	NaN	Deliver tape out
8	2025-Q3	P0	Fab	Beta samples	Karthik Sweeny	10-01-2025	02-15-2026	NaN	NaN	Alpha samples
9	2025-Q2	P0	Test	Test chip eval	Denvyr Loud	04-15-2025	05-15-2025	NaN	NaN	NaN
10	2025-Q2	P0	Test	Test chip eval	Denvyr Loud	05-15-2025	NaN	NaN	Decide pixel	NaN
11	2025-Q4	P0	Test	Alpha sample testing	Denvyr Loud	09-15-2025	12-15-2025	NaN	NaN	NaN
12	2025-Q2	P4	Marketing	Lie about performance	Harry Harrison	05-15-2025	06-30-2025	NaN	NaN	NaN
13	2025-Q3	P4	Marketing	Lie about schedule	Harry Harrison	07-15-2025	12-30-2025	NaN	NaN	NaN
14	2025-Q4	P4	Marketing	Stress engineers about schedule	Harry Harrison	01-15-2026	12-20-2026	NaN	NaN	NaN
15	2025-Q4	P4	Marketing	Deliver beta samples	Harry Harrison	12-30-2026	NaN	NaN	NaN	Beta samples

fcp.gantt(df, x=['Start date', 'End date'], y='Description', #legend='Owner',
          ax_size=[600, 400], date_type='quarter', workstreams='Workstream',
          labels_as_yticks=False, #workstreams_title=False,
          show=True, workstreams_label_font_size=12)#, today=False)

> /Users/steve/Code/fivecentplots/src/fivecentplots/engines/mpl.py(1248)add_text()
   1246 
   1247             # Update element with the actual object reference
-> 1248             if element and track_element:
   1249                 if el.obj is None:
   1250                     el.obj = text_obj

'Alpha sample testing'
(np.datetime64('2025-12-15T00:00:00.000000000'), 0)
(np.datetime64('2025-12-15T00:00:00.000000000'), 0)
datetime.timedelta(days=1)
*** TypeError: unsupported operand type(s) for +: 'int' and 'datetime.timedelta'
np.datetime64('2025-12-15T00:00:00.000000000')
np.datetime64('2025-12-15T00:00:00.000000000')
datetime.timedelta(days=1)
*** TypeError: unsupported operand type(s) for +: 'int' and 'datetime.timedelta'

fcp.gantt(df, x=['Start date', 'End date'], y='Description', #legend='Owner',
          ax_size=[600, 400], date_type='quarter', workstreams='Workstream',
          #workstreams_title=False,
          show=True, workstreams_label_font_size=12)#, today=False)

Warning: the following kwargs are not supported:
    - date_type
    - workstreams
    - workstreams_label_font_size

legend position is wrong period. but tick size doesn’t fully translate when moved to the top, must be some other tick_param

df = pd.read_csv(Path(fcp.__file__).parent / 'test_data/fake_data_gantt_milestone.csv')
fcp.gantt(df, x=['Start date', 'End date'], y='Description',
          ax_size=[900, 400],
          # legend='Owner',
          date_type='quarter',
          workstreams='Workstream',
          # bar_labels='Owner',
          # today=datetime.datetime(2026, 3, 6),
          # today_text='Start',
          #xmin=datetime.datetime(2025, 6, 15),
          show=True,
          xmax=datetime.datetime(2027, 3, 1),
          workstreams_label_font_size=12,
          milestone_text_location='right',
          workstreams_match_bar_color=True
          )
# XMAX NOT WORKING MANUALLY OR WITH

Warning: The following kwargs are not supported:
    - milestone_text_location
    - workstreams_match_bar_color

df.loc[9, 'Milestone']

'Decide\\npixel'