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  1. Elements
  2. Charts
  3. Table

Filters

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Last updated 1 year ago

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Our tables have the option to enable multiple filters, this brings a lot of flexibility to analyze subsets of data from multiple perspectives.

The filters are available in all columns, but they have different behaviors depending on the type of data, for example category fields have a selection type input and numeric values have different numeric operations:

data = [
    {'date': dt.date(2021, 1, 1), 'x': 5, 'y': 5, 'filtA': 'A', 'filtB': 'B'},
    {'date': dt.date(2021, 1, 2), 'x': 6, 'y': 5, 'filtA': 'B', 'filtB': 'Z'},
    {'date': dt.date(2021, 1, 3), 'x': 4, 'y': 5, 'filtA': 'C', 'filtB': 'W'},
    {'date': dt.date(2021, 1, 4), 'x': 7, 'y': 5, 'filtA': 'B', 'filtB': 'T'},
    {'date': dt.date(2021, 1, 5), 'x': 3, 'y': 5, 'filtA': 'A', 'filtB': 'Z'},
]

s.plt.table(
    data=data, order=0,
    categorical_columns=['filtA', 'filtB'],
)
💡
Date filter of a table