Examples#
Data series#
Simple pairs#
import leather
data = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
chart = leather.Chart('Simple pairs')
chart.add_dots(data)
chart.to_svg('examples/charts/simple_pairs.svg')
Table from csv.reader#
Sequence row data, such as is returned by csv.reader() can be accessed by specifying the indices of the columns containing the x and y values.
Note that leather does not automatically convert numerical strings, such as those stored in a CSV. If you want that you’ll need to use a smarter table reader, such as agate
import csv
import leather
with open('examples/realdata/gii.csv') as f:
reader = csv.reader(f)
next(reader)
data = list(reader)[:10]
for row in data:
row[1] = float(row[1]) if row[1] is not None else None
chart = leather.Chart('Data from CSV reader')
chart.add_bars(data, x=1, y=0)
chart.to_svg('examples/charts/csv_reader.svg')
Table from csv.DictReader#
Dict row data, such as is returned by csv.DictReader can be accessed by specifying the indices of the columns containing the x and y values.
See previous example for note on strings from CSVs.
import csv
import leather
with open('examples/realdata/gii.csv') as f:
reader = csv.DictReader(f)
data = list(reader)[:10]
for row in data:
mmr = row['Maternal mortality ratio']
row['Maternal mortality ratio'] = float(mmr) if mmr is not None else None
chart = leather.Chart('Data from CSV reader')
chart.add_bars(data, x='Maternal mortality ratio', y='Country')
chart.to_svg('examples/charts/csv_dict_reader.svg')
Custom data#
Completely custom data formats are also supported via accessor functions.
import leather
data = [
{'x': 0, 'q': {'y': [3]}},
{'x': 4, 'q': {'y': [5]}},
{'x': 7, 'q': {'y': [9]}},
{'x': 8, 'q': {'y': [4]}},
]
def x(row, index):
return row['x']
def y(row, index):
return row['q']['y'][0]
chart = leather.Chart('Line')
chart.add_line(data, x=x, y=y)
chart.to_svg('examples/charts/custom_data.svg')
Multiple series#
Multiple data series can be displayed on a single chart so long as they all use the same type of Scale.
import leather
data1 = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
data2 = [
(2, 4),
(7, 3),
(6, 2),
(5, 9)
]
chart = leather.Chart('Multiple series')
chart.add_dots(data1)
chart.add_dots(data2)
chart.to_svg('examples/charts/multiple_series.svg')
Shapes#
Bars#
import leather
data = [
(3, 'Hello'),
(5, 'How'),
(9, 'Are'),
(4, 'You')
]
chart = leather.Chart('Bars')
chart.add_bars(data)
chart.to_svg('examples/charts/bars.svg')
Columns#
import leather
data = [
('Hello', 3),
('How', 5),
('Are', 9),
('You', 4)
]
chart = leather.Chart('Columns')
chart.add_columns(data)
chart.to_svg('examples/charts/columns.svg')
Dots#
import leather
data = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
chart = leather.Chart('Dots')
chart.add_dots(data)
chart.to_svg('examples/charts/dots.svg')
Lines#
import leather
data = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
chart = leather.Chart('Line')
chart.add_line(data)
chart.to_svg('examples/charts/lines.svg')
Mixing shapes#
You can mix different shapes for different series on the same chart.
import leather
line_data = [
(0, 1),
(2, 5),
(4, 4),
(8, 3)
]
dot_data = [
(1, 3),
(2, 5),
(6, 9),
(10, 4)
]
chart = leather.Chart('Mixed shapes')
chart.add_line(line_data)
chart.add_dots(dot_data)
chart.to_svg('examples/charts/mixed_shapes.svg')
Scales#
Linear#
When using numerical data Linear scales are created automatically and by default. You may override the domain by adding a scale manually.
import leather
data = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
chart = leather.Chart('Linear')
chart.add_x_scale(0, 20)
chart.add_y_scale(-10, 10)
chart.add_line(data)
chart.to_svg('examples/charts/linear.svg')
Ordinal#
When using text data Ordinal scales are created automatically and by default. It is generally not useful to override these defaults.
import leather
data = [
('Hello', 3),
('How', 5,),
('Are', 9),
('You', 4)
]
chart = leather.Chart('Ordinal')
chart.add_columns(data)
chart.to_svg('examples/charts/ordinal.svg')
Temporal#
When using date/time data Temporal scales are created automatically and by default. You may override the domain by adding a scale manually.
from datetime import date
import leather
data = [
(date(2015, 1, 1), 3),
(date(2015, 3, 1), 5),
(date(2015, 6, 1), 9),
(date(2015, 9, 1), 4)
]
chart = leather.Chart('Temporal')
chart.add_x_scale(date(2014, 1, 1), date(2016, 1, 1))
chart.add_line(data)
chart.to_svg('examples/charts/temporal.svg')
Axes#
Changing tick values#
You can change the list of ticks that are displayed using Chart.add_x_axis() and Chart.add_y_axis() methods. This will not adjust automatically adjust the scale, so it is possible to pick tick values that are not displayed.
import leather
data = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
chart = leather.Chart('Line')
chart.add_x_scale(0, 10)
chart.add_x_axis(ticks=[0, 10])
chart.add_line(data)
chart.to_svg('examples/charts/ticks.svg')
Customizing tick format#
You can provide a tick formatter method to change how ticks are displayed using the Chart.add_x_axis() and Chart.add_y_axis() methods.
import leather
data = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
def tick_formatter(value, index, tick_count):
return '%i (%i/%i)' % (value, index, tick_count)
chart = leather.Chart('Line')
chart.add_x_axis(tick_formatter=tick_formatter)
chart.add_line(data)
chart.to_svg('examples/charts/tick_format.svg')
Styling#
Changing theme values#
Chart styles are set using a dead simple theme system. Leather is meant for making quick and dirty charts. It is neither expected nor recommended for user’s to customize these styles.
import leather
line_data = [
(0, 1),
(2, 5),
(4, 4),
(8, 3)
]
dot_data = [
(1, 3),
(2, 5),
(6, 9),
(10, 4)
]
leather.theme.title_font_family = 'Comic Sans MS'
leather.theme.legend_font_family = 'Comic Sans MS'
leather.theme.tick_font_family = 'Comic Sans MS'
leather.theme.default_series_colors = ['#ff0000', '#00ff00']
chart = leather.Chart('Theme')
chart.add_line(line_data)
chart.add_dots(dot_data)
chart.to_svg('examples/charts/theme.svg')
Changing series colors#
More practically, individual default Series colors can be overridden when they are created.
import leather
data = [
('Hello', 3),
('How', 5),
('Are', 9),
('You', 4)
]
chart = leather.Chart('Series color')
chart.add_columns(data, fill_color='#000000')
chart.to_svg('examples/charts/series_color.svg')
Styling data based on value#
Style attributes of individual data points can be set by value using a style_function().
import random
import leather
dot_data = [(random.randint(0, 250), random.randint(0, 250)) for i in range(100)]
def colorizer(d):
return 'rgb(%i, %i, %i)' % (d.x, d.y, 150)
chart = leather.Chart('Colorized dots')
chart.add_dots(dot_data, fill_color=colorizer)
chart.to_svg('examples/charts/colorized_dots.svg')
Creating dashed lines#
When using Chart.add_line(), you can set the stroke_dasharray property.
import leather
data = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
chart = leather.Chart('Line Dashes')
chart.add_line(data, stroke_dasharray='2%')
chart.to_svg('examples/charts/lines_dashes.svg')
Chart grids#
With mixed scales#
You can add charts of completely different types to a single graphic by using Grid.
import leather
data1 = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
data2 = [
(3, 4),
(5, 6),
(7, 10),
(8, 2)
]
chart1 = leather.Chart('Dots')
chart1.add_dots(data1)
chart2 = leather.Chart('Lines')
chart2.add_line(data2)
grid = leather.Grid()
grid.add_one(chart1)
grid.add_one(chart2)
grid.to_svg('examples/charts/grid.svg')
With consistent scales#
A grid of charts can automatically be synchronized to a consistent view using Lattice.
import leather
data1 = [
(0, 3),
(4, 5),
(7, 9),
(8, 4)
]
data2 = [
(3, 4),
(3, 4),
(5, 6),
(7, 10),
(8, 2)
]
data3 = [
(2, 4),
(3, 5),
(6, 2),
(8, 3),
(10, 5)
]
lattice = leather.Lattice()
lattice.add_many([data1, data2, data3], titles=['First', 'Second', 'Third'])
lattice.to_svg('examples/charts/lattice.svg')
