DataTable - Number Formatting
DataTable offers extensive number formatting and localization possibilities with the columns nested prop and
table-wide localization prop .
Most formatting and localization for columns can be done through the
and helpers but it’s also possible to use the d3-format
specifier and locale directly.
See d3-format for additional syntax details.
Using FormatTemplate
The FormatTemplate provides the following predefined templates:
- Money
- Percentage
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash
from dash.dash_table import DataTable, FormatTemplate
app = Dash()
money = FormatTemplate.money(2)
percentage = FormatTemplate.percentage(2)
columns = [
dict(id='account', name='Account'),
dict(id='balance', name='Balance', type='numeric', format=money),
dict(id='rate', name='Rate', type='numeric', format=percentage)
]
data = [
dict(account='A', balance=522.31, rate=0.139),
dict(account='B', balance=1607.9, rate=0.1044),
dict(account='C', balance=-228.41, rate=0.199),
]
app.layout = DataTable(
columns=columns,
data=data
)
if __name__ == '__main__':
app.run(debug=True)
Using Format Helper
Group
Grouping is defined with the format nested props group and groups.
group takes values or to toggle digit grouping.
groups takes a list of numbers used to define the digits grouping pattern.
If the number has more digits than what’s defined in groups, it cycles through the
list again until it runs out of numbers to group.
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash
from dash.dash_table import DataTable
from dash.dash_table.Format import Format, Group
app = Dash()
columns = [
dict(id='a', name='No groups', type='numeric', format=Format()),
dict(id='a', name='Groups of 3', type='numeric', format=Format().group(True)),
dict(id='a', name='Groups of 4', type='numeric', format=Format(group=True, groups=[4])),
dict(id='a', name='Groups of 2,3,2', type='numeric', format=Format(group=Group.yes).groups([2, 3, 2]))
]
values = [123, 123, 1234, 12345, 123456789]
app.layout = DataTable(
columns=columns,
data=[dict(a=value) for value in values]
)
if __name__ == '__main__':
app.run(debug=True)
Align and Fill
Alignment and filling is defined with the format nested props align, fill, and .
The align helper takes values , , and .
fill is single character that will be used for filling.
is the minimum length of the filled string.
If the formatted number requires more space than allows for, it will do so.
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash
from dash.dash_table import DataTable
from dash.dash_table.Format import Format, Align
app = Dash()
columns = [
dict(id='a', name='No fill', type='numeric', format=Format()),
dict(id='a', name='Align left (10)', type='numeric', format=Format().align(Align.left).fill('-').padding_width(10)),
dict(id='a', name='Align right (8)', type='numeric', format=Format(align=Align.right, fill='-', padding_width=8)),
dict(id='a', name='Align center (6)', type='numeric', format=dict(specifier='-^6'))
]
values = [123, 123, 1234, 12345, 123456789]
app.layout = DataTable(
columns=columns,
data=[dict(a=value) for value in values]
)
if __name__ == '__main__':
app.run(debug=True)
Padding and Padding Width
Padding and padding width is defined with the format nested props padding and and they behave similarly
to fill and , but do not allow alignment.
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash
from dash.dash_table import DataTable
from dash.dash_table.Format import Format, Padding
app = Dash()
columns = [
dict(id='a', name='No padding', type='numeric', format=Format()),
dict(id='a', name='Padding 12', type='numeric', format=Format(padding=True, padding_width=12)),
dict(id='a', name='Padding 9', type='numeric', format=Format(padding=Padding.yes).padding_width(9)),
dict(id='a', name='Padding 6', type='numeric', format=dict(specifier='06'))
]
values = [123, 123, 1234, 12345, 123456789]
app.layout = DataTable(columns=columns, data=[dict(a=value) for value in values])
if __name__ == '__main__':
app.run(debug=True)
Precision and Scheme
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash
from dash.html import Br, Div
from dash.dash_table import DataTable
from dash.dash_table.Format import Format, Scheme, Trim
app = Dash()
columns_1 = [
dict(id='a', name='No precision', type='numeric', format=Format()),
dict(id='a', name='Default', type='numeric', format=Format(precision=2)),
dict(id='a', name='Fixed', type='numeric', format=Format(precision=2, scheme=Scheme.fixed)),
dict(id='a', name='Decimal', type='numeric', format=Format(precision=2, scheme=Scheme.decimal)),
dict(id='a', name='Integer', type='numeric', format=Format(precision=2, scheme=Scheme.decimal_integer)),
dict(id='a', name='Decimal/Exponent', type='numeric', format=Format(precision=2, scheme=Scheme.decimal_or_exponent)),
dict(id='a', name='Decimal SI', type='numeric', format=Format(precision=2, scheme=Scheme.decimal_si_prefix)),
dict(id='a', name='Exponent', type='numeric', format=Format(precision=2, scheme=Scheme.exponent)),
]
columns_2 = [
dict(id='a', name='Percentage', type='numeric', format=Format(precision=2, scheme=Scheme.percentage)),
dict(id='a', name='Rounded Percentage', type='numeric', format=Format(precision=2, scheme=Scheme.percentage_rounded)),
dict(id='a', name='Binary', type='numeric', format=Format(precision=2, scheme=Scheme.binary)),
dict(id='a', name='Octal', type='numeric', format=Format(precision=2, scheme=Scheme.octal)),
dict(id='a', name='hex', type='numeric', format=Format(precision=2, scheme=Scheme.lower_case_hex)),
dict(id='a', name='HEX', type='numeric', format=Format(precision=2, scheme=Scheme.upper_case_hex)),
dict(id='a', name='Unicode', type='numeric', format=Format(precision=2, scheme=Scheme.unicode))
]
columns_3 = [
dict(id='a', name='4 decimals', type='numeric', format=Format(precision=4, scheme=Scheme.fixed)),
dict(id='a', name='4 decimals / trimmed', type='numeric', format=Format(precision=4, scheme=Scheme.fixed, trim=Trim.yes)),
dict(id='a', name='Custom 4 decimals / trimmed', type='numeric', format=dict(specifier='.4~f')),
]
values = [123.1, 123.12, 1234.123, 12345.12]
data = [dict(a=value) for value in values]
app.layout = Div([
DataTable(columns=columns_1, data=data),
Br(),
DataTable(columns=columns_2, data=data),
Br(),
DataTable(columns=columns_3, data=data)
])
if __name__ == '__main__':
app.run(debug=True)
Sign
When to display a sign and what type of sign to display is defined with the format nested prop sign.
The Sign helper takes values (show sign when negative), (always show sign), (when negative)
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash
from dash.dash_table import DataTable
from dash.dash_table.Format import Format, Scheme, Sign
app = Dash()
columns = [
dict(id='a', name='Default', type='numeric', format=Format()),
dict(id='a', name='Negative', type='numeric', format=Format(sign=Sign.negative)),
dict(id='a', name='Positive', type='numeric', format=Format(sign=Sign.positive)),
dict(id='a', name='Parentheses', type='numeric', format=Format().sign(Sign.parantheses)),
dict(id='a', name='Percentage/Parentheses', type='numeric', format=Format(scheme=Scheme.percentage, precision=2, sign=Sign.parantheses)),
dict(id='a', name='', type='numeric', format=dict(specifier='('))
]
values = [
123.1, 123.12, 1234.123, 12345.12,
-123.1, -123.12, -1234.123, -12345.12
]
app.layout = DataTable(columns=columns, data=[dict(a=value) for value in values])
if __name__ == '__main__':
app.run(debug=True)
Symbol
Displaying of symbols is defined with the format nested prop symbol and the prefix/suffix symbols are defined with the locale nested prop symbol.
The Symbol helper takes values and .
The locale symbol nested prop is a list of strings of length 2 of the form [prefix, suffix]. Strings in symbol can be of any length.
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash
from dash.html import Br, Div
from dash.dash_table import DataTable
from dash.dash_table.Format import Format, Symbol
app = Dash()
columns_1 = [
dict(id='a', name='Default', type='numeric', format=Format()),
dict(id='a', name='No Symbol', type='numeric', format=Format(symbol=Symbol.no)),
dict(id='a', name='$ Symbol', type='numeric', format=Format(symbol=Symbol.yes)),
dict(id='a', name='@ Symbol / Locale prefix', type='numeric', format=Format().symbol(Symbol.yes).symbol_prefix('@')),
dict(id='a', name='@ Symbol / Locale prefix+suffix', type='numeric', format=Format().symbol(Symbol.yes).symbol_prefix('@').symbol_suffix('*'))
]
columns_2 = [
dict(id='a', name='Binary', type='numeric', format=Format(symbol=Symbol.binary)),
dict(id='a', name='Octal', type='numeric', format=Format(symbol=Symbol.octal)),
dict(id='a', name='Hex', type='numeric', format=Format(symbol=Symbol.hex)),
dict(id='a', name='Custom', type='numeric', format=dict(locale=dict(symbol=['@', '*']), specifier='$'))
]
values = [123.1, 123.12, 1234.123, 12345.12]
data = [dict(a=value) for value in values]
app.layout = Div([
DataTable(columns=columns_1, data=data),
Br(),
DataTable(columns=columns_2, data=data)
])
if __name__ == '__main__':
app.run(debug=True)
Localization
This example has not been ported to R yet - showing the Python version instead.
Visit the old docs site for R at: https://community.plotly.com/c/dash/r/21
from dash import Dash
from dash.html import Br, Div
from dash.dash_table import DataTable
from dash.dash_table.Format import Format, Group, Prefix, Scheme, Symbol
app = Dash()
columns_1 = [
dict(id='a', name='Symbol', type='numeric', format=Format(symbol=Symbol.yes)),
dict(id='a', name='Symbol prefix', type='numeric', format=Format(symbol=Symbol.yes, symbol_prefix='CAD$ ')),
dict(id='a', name='Symbol suffix', type='numeric', format=Format(symbol=Symbol.yes, symbol_suffix=' $CAD')),
dict(id='a', name='Symbol custom', type='numeric', format=dict(specifier='$', locale=dict(symbol=['@', '*'])))
]
columns_2 = [
dict(id='a', name='Decimal', type='numeric', format=Format(decimal_delimiter=':').scheme('f').precision(2)),
dict(id='a', name='Custom decimal', type='numeric', format=dict(specifier='.2f', locale=dict(decimal=':'))),
dict(id='a', name='Group', type='numeric', format=Format(group_delimiter=':', group=Group.yes, groups=[2])),
dict(id='a', name='Custom group', type='numeric', format=dict(specifier=',', locale=dict(group=':', grouping=[2])))
]
columns_3 = [
dict(id='a', name='Custom numerals', type='numeric', format=dict(locale=dict(numerals=['0', 'AA', 'b', 'CC', '', '', '', '77', '88', '99']))),
dict(id='a', name='Percent symbol', type='numeric', format=dict(specifier='.2%', locale=dict(percent='@'))),
dict(id='a', name='Group 4 digits', type='numeric', format=dict(specifier=',.0f', locale=dict(separate_4digits=False))),
dict(id='a', name='SI', type='numeric', format=Format(si_prefix=Prefix.milli).precision(0)),
dict(id='a', name='SI+space', type='numeric', format=Format(si_prefix=Prefix.milli, symbol=Symbol.yes, symbol_suffix=' ').precision(0)),
dict(id='a', name='Explicit SI', type='numeric', format=Format(si_prefix=10 ** -3).precision(0))
]
values = [123, 123, 1234, 12345, 123456789]
data = [dict(a=value) for value in values]
app.layout = Div([
DataTable(columns=columns_1, data=data),
Br(),
DataTable(columns=columns_2, data=data),
Br(),
DataTable(columns=columns_3, data=data)
])
if __name__ == '__main__':
app.run(debug=True)