Encodings

The key to creating meaningful visualizations is to map properties of the data to visual properties in order to effectively communicate information. In Altair, this mapping of visual properties to data columns is referred to as an encoding, and is most often expressed through the Chart.encode() method.

For example, here we will visualize the cars dataset using four of the available encodings: x (the x-axis value), y (the y-axis value), color (the color of the marker), and shape (the shape of the point marker):

import altair as alt
from vega_datasets import data
cars = data.cars()

alt.Chart(cars).mark_point().encode(
    x='Horsepower',
    y='Miles_per_Gallon',
    color='Origin',
    shape='Origin'
)

For data specified as a DataFrame, Altair can automatically determine the correct data type for each encoding, and creates appropriate scales and legends to represent the data.

Encoding Channels

Altair provides a number of encoding channels that can be useful in different circumstances; the following table summarizes them:

Position Channels:

Channel Altair Class Description Example
x X The x-axis value Simple Scatter Plot
y Y The y-axis value Simple Scatter Plot
x2 X2 Second x value for ranges Error Bars showing Confidence Interval
y2 Y2 Second y value for ranges Line chart with Confidence Interval Band
longitude Longitude Longitude for geo charts Locations of US Airports
latitude Latitude Latitude for geo charts Locations of US Airports
longitude2 Longitude2 Second longitude value for ranges N/A
latitude2 Latitude2 Second latitude value for ranges N/A

Mark Property Channels:

Channel Altair Class Description Example
color Color The color of the mark Simple Heatmap
fill Fill The fill for the mark N/A
opacity Opacity The opacity of the mark Horizon Graph
shape Shape The shape of the mark N/A
size Size The size of the mark Table Bubble Plot (Github Punch Card)
stroke Stroke The stroke of the mark N/A

Text and Tooltip Channels:

Channel Altair Class Description Example
text Text Text to use for the mark Simple Scatter Plot with Labels
key Key – N/A
tooltip Tooltip The tooltip value Scatter Plot with Tooltips

Hyperlink Channel:

Channel Altair Class Description Example
href Href Hyperlink for points N/A

Level of Detail Channel:

Channel Altair Class Description Example
detail Detail Additional property to group by Selection Detail Example

Order Channel:

Channel Altair Class Description Example
order Order Sets the order of the marks Connected Scatterplot (Lines with Custom Paths)

Facet Channels:

Channel Altair Class Description Example
column Column The column of a faceted plot Trellis Scatter Plot
row Row The row of a faceted plot Becker’s Barley Trellis Plot

Encoding Data Types

The details of any mapping depend on the type of the data. Altair recognizes four main data types:

Data Type Shorthand Code Description
quantitative Q a continuous real-valued quantity
ordinal O a discrete ordered quantity
nominal N a discrete unordered category
temporal T a time or date value

If types are not specified for data input as a DataFrame, Altair defaults to quantitative for any numeric data, temporal for date/time data, and nominal for string data, but be aware that these defaults are by no means always the correct choice!

The types can either be expressed in a long-form using the channel encoding classes such as X and Y, or in short-form using the Shorthand Syntax discussed below. For example, the following two methods of specifying the type will lead to identical plots:

alt.Chart(cars).mark_point().encode(
    x='Acceleration:Q',
    y='Miles_per_Gallon:Q',
    color='Origin:N'
)

alt.Chart(cars).mark_point().encode(
    alt.X('Acceleration', type='quantitative'),
    alt.Y('Miles_per_Gallon', type='quantitative'),
    alt.Color('Origin', type='nominal')
)

The shorthand form, x="name:Q", is useful for its lack of boilerplate when doing quick data explorations. The long-form, alt.X('name', type='quantitative'), is useful when doing more fine-tuned adjustments to the encoding, such as binning, axis and scale properties, or more.

Specifying the correct type for your data is important, as it affects the way Altair represents your encoding in the resulting plot.

Effect of Data Type on Color Scales

As an example of this, here we will represent the same data three different ways, with the color encoded as a quantitative, ordinal, and nominal type, using three vertically-concatenated charts (see Vertical Concatenation):

base = alt.Chart(cars).mark_point().encode(
    x='Horsepower:Q',
    y='Miles_per_Gallon:Q',
).properties(
    width=150,
    height=150
)

alt.vconcat(
   base.encode(color='Cylinders:Q').properties(title='quantitative'),
   base.encode(color='Cylinders:O').properties(title='ordinal'),
   base.encode(color='Cylinders:N').properties(title='nominal'),
)

The type specification influences the way Altair, via Vega-Lite, decides on the color scale to represent the value, and influences whether a discrete or continuous legend is used.

Effect of Data Type on Axis Scales

Similarly, for x and y axis encodings, the type used for the data will affect the scales used and the characteristics of the mark. For example, here is the difference between a quantitative and ordinal scale for an column that contains integers specifying a year:

pop = data.population.url

base = alt.Chart(pop).mark_bar().encode(
    alt.Y('mean(people):Q', axis=alt.Axis(title='total population'))
).properties(
    width=200,
    height=200
)

alt.hconcat(
    base.encode(x='year:Q').properties(title='year=quantitative'),
    base.encode(x='year:O').properties(title='year=ordinal')
)

In altair, quantitative scales always start at zero unless otherwise specified, while ordinal scales are limited to the values within the data.

Overriding the behavior of including zero in the axis, we see that even then the precise appearance of the marks representing the data are affected by the data type:

base.encode(
    alt.X('year:Q',
        scale=alt.Scale(zero=False)
    )
)

Because quantitative values do not have an inherent width, the bars do not fill the entire space between the values. This view also makes clear the missing year of data that was not immediately apparent when we treated the years as categories.

This kind of behavior is sometimes surprising to new users, but it emphasizes the importance of thinking carefully about your data types when visualizing data: a visual encoding that is suitable for categorical data may not be suitable for quantitative data, and vice versa.

Encoding Channel Options

Each encoding channel allows for a number of additional options to be expressed; these can control things like axis properties, scale properties, headers and titles, binning parameters, aggregation, sorting, and many more.

The particular options that are available vary by encoding type; the various options are listed below.

The X and Y encodings accept the following options:

Property Type Description
aggregate Aggregate

Aggregation function for the field (e.g., mean, sum, median, min, max, count).

Default value: undefined (None)
axis anyOf(Axis, null)

An object defining properties of axis’s gridlines, ticks and labels. If null, the axis for the encoding channel will be removed.

Default value: If undefined, default axis properties are applied.
bin anyOf(boolean, BinParams)

A flag for binning a quantitative field, or an object defining binning parameters. If true, default binning parameters will be applied.

Default value: false
field anyOf(string, RepeatRef)

Required. A string defining the name of the field from which to pull a data value or an object defining iterated values from the repeat operator.

Note: Dots (.) and brackets ([ and ]) can be used to access nested objects (e.g., "field": "foo.bar" and "field": "foo['bar']"). If field names contain dots or brackets but are not nested, you can use \\ to escape dots and brackets (e.g., "a\\.b" and "a\\[0\\]"). See more details about escaping in the field documentation.

Note: field is not required if aggregate is count.
scale anyOf(Scale, null)

An object defining properties of the channel’s scale, which is the function that transforms values in the data domain (numbers, dates, strings, etc) to visual values (pixels, colors, sizes) of the encoding channels.

If null, the scale will be disabled and the data value will be directly encoded.

Default value: If undefined, default scale properties are applied.
sort Sort

Sort order for the encoded field.

For continuous fields (quantitative or temporal), sort can be either "ascending" or "descending".

For discrete fields, sort can be one of the following:

  • "ascending" or "descending" – for sorting by the values’ natural order in Javascript.
  • A sort field definition for sorting by another field.
  • An array specifying the field values in preferred order. In this case, the sort order will obey the values in the array, followed by any unspecified values in their original order. For discrete time field, values in the sort array can be date-time definition objects. In addition, for time units "month" and "day", the values can be the month or day names (case insensitive) or their 3-letter initials (e.g., "Mon", "Tue").
  • null indicating no sort.

Default value: "ascending"

Note: null is not supported for row and column.
stack anyOf(StackOffset, null)

Type of stacking offset if the field should be stacked. stack is only applicable for x and y channels with continuous domains. For example, stack of y can be used to customize stacking for a vertical bar chart.

stack can be one of the following values:

  • "zero": stacking with baseline offset at zero value of the scale (for creating typical stacked bar and area chart).
  • "normalize" - stacking with normalized domain (for creating normalized stacked bar and area charts.
    -"center" - stacking with center baseline (for streamgraph).
  • null - No-stacking. This will produce layered bar and area chart.

Default value: zero for plots with all of the following conditions are true: (1) the mark is bar or area; (2) the stacked measure channel (x or y) has a linear scale; (3) At least one of non-position channels mapped to an unaggregated field that is different from x and y. Otherwise, null by default.
timeUnit TimeUnit

Time unit (e.g., year, yearmonth, month, hours) for a temporal field. or a temporal field that gets casted as ordinal.

Default value: undefined (None)
title [string, null]

A title for the field. If null, the title will be removed.

Default value: derived from the field’s name and transformation function (aggregate, bin and timeUnit). If the field has an aggregate function, the function is displayed as part of the title (e.g., "Sum of Profit"). If the field is binned or has a time unit applied, the applied function is shown in parentheses (e.g., "Profit (binned)", "Transaction Date (year-month)"). Otherwise, the title is simply the field name.

Notes:

  1. You can customize the default field title format by providing the [fieldTitle property in the config or fieldTitle function via the compile function’s options.
  2. If both field definition’s title and axis, header, or legend title are defined, axis/header/legend title will be used.
type Type The encoded field’s type of measurement ("quantitative", "temporal", "ordinal", or "nominal"). It can also be a "geojson" type for encoding ‘geoshape’.

The Color, Fill, Opacity, Shape, Size, and Stroke encodings accept the following options:

Property Type Description
aggregate Aggregate

Aggregation function for the field (e.g., mean, sum, median, min, max, count).

Default value: undefined (None)
bin anyOf(boolean, BinParams)

A flag for binning a quantitative field, or an object defining binning parameters. If true, default binning parameters will be applied.

Default value: false
condition anyOf(ConditionalValueDef, array(ConditionalValueDef))

One or more value definition(s) with a selection predicate.

Note: A field definition’s condition property can only contain value definitions since Vega-Lite only allows at most one encoded field per encoding channel.
field anyOf(string, RepeatRef)

Required. A string defining the name of the field from which to pull a data value or an object defining iterated values from the repeat operator.

Note: Dots (.) and brackets ([ and ]) can be used to access nested objects (e.g., "field": "foo.bar" and "field": "foo['bar']"). If field names contain dots or brackets but are not nested, you can use \\ to escape dots and brackets (e.g., "a\\.b" and "a\\[0\\]"). See more details about escaping in the field documentation.

Note: field is not required if aggregate is count.
legend anyOf(Legend, null)

An object defining properties of the legend. If null, the legend for the encoding channel will be removed.

Default value: If undefined, default legend properties are applied.
scale anyOf(Scale, null)

An object defining properties of the channel’s scale, which is the function that transforms values in the data domain (numbers, dates, strings, etc) to visual values (pixels, colors, sizes) of the encoding channels.

If null, the scale will be disabled and the data value will be directly encoded.

Default value: If undefined, default scale properties are applied.
sort Sort

Sort order for the encoded field.

For continuous fields (quantitative or temporal), sort can be either "ascending" or "descending".

For discrete fields, sort can be one of the following:

  • "ascending" or "descending" – for sorting by the values’ natural order in Javascript.
  • A sort field definition for sorting by another field.
  • An array specifying the field values in preferred order. In this case, the sort order will obey the values in the array, followed by any unspecified values in their original order. For discrete time field, values in the sort array can be date-time definition objects. In addition, for time units "month" and "day", the values can be the month or day names (case insensitive) or their 3-letter initials (e.g., "Mon", "Tue").
  • null indicating no sort.

Default value: "ascending"

Note: null is not supported for row and column.
timeUnit TimeUnit

Time unit (e.g., year, yearmonth, month, hours) for a temporal field. or a temporal field that gets casted as ordinal.

Default value: undefined (None)
title [string, null]

A title for the field. If null, the title will be removed.

Default value: derived from the field’s name and transformation function (aggregate, bin and timeUnit). If the field has an aggregate function, the function is displayed as part of the title (e.g., "Sum of Profit"). If the field is binned or has a time unit applied, the applied function is shown in parentheses (e.g., "Profit (binned)", "Transaction Date (year-month)"). Otherwise, the title is simply the field name.

Notes:

  1. You can customize the default field title format by providing the [fieldTitle property in the config or fieldTitle function via the compile function’s options.
  2. If both field definition’s title and axis, header, or legend title are defined, axis/header/legend title will be used.
type Type The encoded field’s type of measurement ("quantitative", "temporal", "ordinal", or "nominal"). It can also be a "geojson" type for encoding ‘geoshape’.

The Row and Column encodings accept the following options:

Property Type Description
aggregate Aggregate

Aggregation function for the field (e.g., mean, sum, median, min, max, count).

Default value: undefined (None)
bin anyOf(boolean, BinParams)

A flag for binning a quantitative field, or an object defining binning parameters. If true, default binning parameters will be applied.

Default value: false
field anyOf(string, RepeatRef)

Required. A string defining the name of the field from which to pull a data value or an object defining iterated values from the repeat operator.

Note: Dots (.) and brackets ([ and ]) can be used to access nested objects (e.g., "field": "foo.bar" and "field": "foo['bar']"). If field names contain dots or brackets but are not nested, you can use \\ to escape dots and brackets (e.g., "a\\.b" and "a\\[0\\]"). See more details about escaping in the field documentation.

Note: field is not required if aggregate is count.
header Header An object defining properties of a facet’s header.
sort Sort

Sort order for the encoded field.

For continuous fields (quantitative or temporal), sort can be either "ascending" or "descending".

For discrete fields, sort can be one of the following:

  • "ascending" or "descending" – for sorting by the values’ natural order in Javascript.
  • A sort field definition for sorting by another field.
  • An array specifying the field values in preferred order. In this case, the sort order will obey the values in the array, followed by any unspecified values in their original order. For discrete time field, values in the sort array can be date-time definition objects. In addition, for time units "month" and "day", the values can be the month or day names (case insensitive) or their 3-letter initials (e.g., "Mon", "Tue").
  • null indicating no sort.

Default value: "ascending"

Note: null is not supported for row and column.
timeUnit TimeUnit

Time unit (e.g., year, yearmonth, month, hours) for a temporal field. or a temporal field that gets casted as ordinal.

Default value: undefined (None)
title [string, null]

A title for the field. If null, the title will be removed.

Default value: derived from the field’s name and transformation function (aggregate, bin and timeUnit). If the field has an aggregate function, the function is displayed as part of the title (e.g., "Sum of Profit"). If the field is binned or has a time unit applied, the applied function is shown in parentheses (e.g., "Profit (binned)", "Transaction Date (year-month)"). Otherwise, the title is simply the field name.

Notes:

  1. You can customize the default field title format by providing the [fieldTitle property in the config or fieldTitle function via the compile function’s options.
  2. If both field definition’s title and axis, header, or legend title are defined, axis/header/legend title will be used.
type Type The encoded field’s type of measurement ("quantitative", "temporal", "ordinal", or "nominal"). It can also be a "geojson" type for encoding ‘geoshape’.

The Text and Tooltip encodings accept the following options:

Property Type Description
aggregate Aggregate

Aggregation function for the field (e.g., mean, sum, median, min, max, count).

Default value: undefined (None)
bin anyOf(boolean, BinParams)

A flag for binning a quantitative field, or an object defining binning parameters. If true, default binning parameters will be applied.

Default value: false
condition anyOf(ConditionalValueDef, array(ConditionalValueDef))

One or more value definition(s) with a selection predicate.

Note: A field definition’s condition property can only contain value definitions since Vega-Lite only allows at most one encoded field per encoding channel.
field anyOf(string, RepeatRef)

Required. A string defining the name of the field from which to pull a data value or an object defining iterated values from the repeat operator.

Note: Dots (.) and brackets ([ and ]) can be used to access nested objects (e.g., "field": "foo.bar" and "field": "foo['bar']"). If field names contain dots or brackets but are not nested, you can use \\ to escape dots and brackets (e.g., "a\\.b" and "a\\[0\\]"). See more details about escaping in the field documentation.

Note: field is not required if aggregate is count.
format string The formatting pattern for a text field. If not defined, this will be determined automatically.
timeUnit TimeUnit

Time unit (e.g., year, yearmonth, month, hours) for a temporal field. or a temporal field that gets casted as ordinal.

Default value: undefined (None)
title [string, null]

A title for the field. If null, the title will be removed.

Default value: derived from the field’s name and transformation function (aggregate, bin and timeUnit). If the field has an aggregate function, the function is displayed as part of the title (e.g., "Sum of Profit"). If the field is binned or has a time unit applied, the applied function is shown in parentheses (e.g., "Profit (binned)", "Transaction Date (year-month)"). Otherwise, the title is simply the field name.

Notes:

  1. You can customize the default field title format by providing the [fieldTitle property in the config or fieldTitle function via the compile function’s options.
  2. If both field definition’s title and axis, header, or legend title are defined, axis/header/legend title will be used.
type Type The encoded field’s type of measurement ("quantitative", "temporal", "ordinal", or "nominal"). It can also be a "geojson" type for encoding ‘geoshape’.

The Detail, Key, Latitude, Latitude2, Longitude, Longitude2, X2 and Y2 encodings accept the following options:

Property Type Description
aggregate Aggregate

Aggregation function for the field (e.g., mean, sum, median, min, max, count).

Default value: undefined (None)
bin anyOf(boolean, BinParams)

A flag for binning a quantitative field, or an object defining binning parameters. If true, default binning parameters will be applied.

Default value: false
field anyOf(string, RepeatRef)

Required. A string defining the name of the field from which to pull a data value or an object defining iterated values from the repeat operator.

Note: Dots (.) and brackets ([ and ]) can be used to access nested objects (e.g., "field": "foo.bar" and "field": "foo['bar']"). If field names contain dots or brackets but are not nested, you can use \\ to escape dots and brackets (e.g., "a\\.b" and "a\\[0\\]"). See more details about escaping in the field documentation.

Note: field is not required if aggregate is count.
timeUnit TimeUnit

Time unit (e.g., year, yearmonth, month, hours) for a temporal field. or a temporal field that gets casted as ordinal.

Default value: undefined (None)
title [string, null]

A title for the field. If null, the title will be removed.

Default value: derived from the field’s name and transformation function (aggregate, bin and timeUnit). If the field has an aggregate function, the function is displayed as part of the title (e.g., "Sum of Profit"). If the field is binned or has a time unit applied, the applied function is shown in parentheses (e.g., "Profit (binned)", "Transaction Date (year-month)"). Otherwise, the title is simply the field name.

Notes:

  1. You can customize the default field title format by providing the [fieldTitle property in the config or fieldTitle function via the compile function’s options.
  2. If both field definition’s title and axis, header, or legend title are defined, axis/header/legend title will be used.
type Type The encoded field’s type of measurement ("quantitative", "temporal", "ordinal", or "nominal"). It can also be a "geojson" type for encoding ‘geoshape’.

The Href encoding accepts the following options:

Property Type Description
aggregate Aggregate

Aggregation function for the field (e.g., mean, sum, median, min, max, count).

Default value: undefined (None)
bin anyOf(boolean, BinParams)

A flag for binning a quantitative field, or an object defining binning parameters. If true, default binning parameters will be applied.

Default value: false
condition anyOf(ConditionalValueDef, array(ConditionalValueDef))

One or more value definition(s) with a selection predicate.

Note: A field definition’s condition property can only contain value definitions since Vega-Lite only allows at most one encoded field per encoding channel.
field anyOf(string, RepeatRef)

Required. A string defining the name of the field from which to pull a data value or an object defining iterated values from the repeat operator.

Note: Dots (.) and brackets ([ and ]) can be used to access nested objects (e.g., "field": "foo.bar" and "field": "foo['bar']"). If field names contain dots or brackets but are not nested, you can use \\ to escape dots and brackets (e.g., "a\\.b" and "a\\[0\\]"). See more details about escaping in the field documentation.

Note: field is not required if aggregate is count.
timeUnit TimeUnit

Time unit (e.g., year, yearmonth, month, hours) for a temporal field. or a temporal field that gets casted as ordinal.

Default value: undefined (None)
title [string, null]

A title for the field. If null, the title will be removed.

Default value: derived from the field’s name and transformation function (aggregate, bin and timeUnit). If the field has an aggregate function, the function is displayed as part of the title (e.g., "Sum of Profit"). If the field is binned or has a time unit applied, the applied function is shown in parentheses (e.g., "Profit (binned)", "Transaction Date (year-month)"). Otherwise, the title is simply the field name.

Notes:

  1. You can customize the default field title format by providing the [fieldTitle property in the config or fieldTitle function via the compile function’s options.
  2. If both field definition’s title and axis, header, or legend title are defined, axis/header/legend title will be used.
type Type The encoded field’s type of measurement ("quantitative", "temporal", "ordinal", or "nominal"). It can also be a "geojson" type for encoding ‘geoshape’.

The Order encoding accepts the following options:

Property Type Description
aggregate Aggregate

Aggregation function for the field (e.g., mean, sum, median, min, max, count).

Default value: undefined (None)
bin anyOf(boolean, BinParams)

A flag for binning a quantitative field, or an object defining binning parameters. If true, default binning parameters will be applied.

Default value: false
field anyOf(string, RepeatRef)

Required. A string defining the name of the field from which to pull a data value or an object defining iterated values from the repeat operator.

Note: Dots (.) and brackets ([ and ]) can be used to access nested objects (e.g., "field": "foo.bar" and "field": "foo['bar']"). If field names contain dots or brackets but are not nested, you can use \\ to escape dots and brackets (e.g., "a\\.b" and "a\\[0\\]"). See more details about escaping in the field documentation.

Note: field is not required if aggregate is count.
sort SortOrder The sort order. One of "ascending" (default) or "descending".
timeUnit TimeUnit

Time unit (e.g., year, yearmonth, month, hours) for a temporal field. or a temporal field that gets casted as ordinal.

Default value: undefined (None)
title [string, null]

A title for the field. If null, the title will be removed.

Default value: derived from the field’s name and transformation function (aggregate, bin and timeUnit). If the field has an aggregate function, the function is displayed as part of the title (e.g., "Sum of Profit"). If the field is binned or has a time unit applied, the applied function is shown in parentheses (e.g., "Profit (binned)", "Transaction Date (year-month)"). Otherwise, the title is simply the field name.

Notes:

  1. You can customize the default field title format by providing the [fieldTitle property in the config or fieldTitle function via the compile function’s options.
  2. If both field definition’s title and axis, header, or legend title are defined, axis/header/legend title will be used.
type Type The encoded field’s type of measurement ("quantitative", "temporal", "ordinal", or "nominal"). It can also be a "geojson" type for encoding ‘geoshape’.

Binning and Aggregation

Beyond simple channel encodings, Altair’s visualizations are built on the concept of the database-style grouping and aggregation; that is, the split-apply-combine abstraction that underpins many data analysis approaches.

For example, building a histogram from a one-dimensional dataset involves splitting data based on the bin it falls in, aggregating the results within each bin using a count of the data, and then combining the results into a final figure.

In Altair, such an operation looks like this:

alt.Chart(cars).mark_bar().encode(
    alt.X('Horsepower', bin=True),
    y='count()'
    # could also use alt.Y(aggregate='count', type='quantitative')
)

Notice here we use the shorthand version of expressing an encoding channel (see Encoding Shorthands) with the count aggregation, which is the one aggregation that does not require a field to be specified.

Similarly, we can create a two-dimensional histogram using, for example, the size of points to indicate counts within the grid (sometimes called a “Bubble Plot”):

alt.Chart(cars).mark_point().encode(
    alt.X('Horsepower', bin=True),
    alt.Y('Miles_per_Gallon', bin=True),
    size='count()',
)

There is no need, however, to limit aggregations to counts alone. For example, we could similarly create a plot where the color of each point represents the mean of a third quantity, such as acceleration:

alt.Chart(cars).mark_circle().encode(
    alt.X('Horsepower', bin=True),
    alt.Y('Miles_per_Gallon', bin=True),
    size='count()',
    color='average(Acceleration):Q'
)

In addition to count and average, there are a large number of available aggregation functions built into Altair; they are listed in the following table:

Aggregate Description Example
argmin An input data object containing the minimum field value. N/A
argmax An input data object containing the maximum field value. N/A
average The mean (average) field value. Identical to mean. Line Chart with Layered Aggregates
count The total count of data objects in the group. Simple Heatmap
distinct The count of distinct field values. N/A
max The maximum field value. Box Plot with Min/Max Whiskers
mean The mean (average) field value. Layered Plot with Dual-Axis
median The median field value Box Plot with Min/Max Whiskers
min The minimum field value. Box Plot with Min/Max Whiskers
missing The count of null or undefined field values. N/A
q1 The lower quartile boundary of values. Box Plot with Min/Max Whiskers
q3 The upper quartile boundary of values. Box Plot with Min/Max Whiskers
ci0 The lower boundary of the bootstrapped 95% confidence interval of the mean. Error Bars showing Confidence Interval
ci1 The upper boundary of the bootstrapped 95% confidence interval of the mean. Error Bars showing Confidence Interval
stderr The standard error of the field values. N/A
stdev The sample standard deviation of field values. N/A
stdevp The population standard deviation of field values. N/A
sum The sum of field values. Streamgraph
valid The count of field values that are not null or undefined. N/A
values ?? N/A
variance The sample variance of field values. N/A
variancep The population variance of field values. N/A

Encoding Shorthands

For convenience, Altair allows the specification of the variable name along with the aggregate and type within a simple shorthand string syntax. This makes use of the type shorthand codes listed in Encoding Data Types as well as the aggregate names listed in Binning and Aggregation. The following table shows examples of the shorthand specification alongside the long-form equivalent:

Shorthand Equivalent long-form
x='name' alt.X('name')
x='name:Q' alt.X('name', type='quantitative')
x='sum(name)' alt.X('name', aggregate='sum')
x='sum(name):Q' alt.X('name', aggregate='sum', type='quantitative')
x='count():Q' alt.X(aggregate='count', type='quantitative')

Ordering marks

The order option and Order channel can sort how marks are drawn on the chart.

For stacked marks, this controls the order of components of the stack. Here, the elements of each bar are sorted alphabetically by the name of the nominal data in the color channel.

import altair as alt
from vega_datasets import data

barley = data.barley()

alt.Chart(barley).mark_bar().encode(
    x='variety:N',
    y='sum(yield):Q',
    color='site:N',
    order=alt.Order("site", sort="ascending")
)

The order can be reversed by changing the sort option to descending.

import altair as alt
from vega_datasets import data

barley = data.barley()

alt.Chart(barley).mark_bar().encode(
    x='variety:N',
    y='sum(yield):Q',
    color='site:N',
    order=alt.Order("site", sort="descending")
)

The same approach works for other mark types, like stacked areas charts.

import altair as alt
from vega_datasets import data

barley = data.barley()

alt.Chart(barley).mark_area().encode(
    x='variety:N',
    y='sum(yield):Q',
    color='site:N',
    order=alt.Order("site", sort="ascending")
)

For line marks, the order channel encodes the order in which data points are connected. This can be useful for creating a scatterplot that draws lines between the dots using a different field than the x and y axes.

import altair as alt
from vega_datasets import data

driving = data.driving()

alt.Chart(driving).mark_line(point=True).encode(
    alt.X('miles', scale=alt.Scale(zero=False)),
    alt.Y('gas', scale=alt.Scale(zero=False)),
    order='year'
)

Sorting Legends and Axes

Specific channels can take a sort property which determines the order of the scale being used for the channel. There are a number of different sort options available:

  • sort='ascending' (Default) will sort the field’s value in ascending order. for string data, this uses standard alphabetical order.
  • sort='descending' will sort the field’s value in descending order
  • passing a list to sort allows you to explicitly set the order in which you would like the encoding to appear
  • passing a EncodingSortField class to sort allows you to sort an axis by the value of some other field in the dataset.

Here is an example of applying these four different sort approaches on the x-axis, using the barley dataset:

import altair as alt
from vega_datasets import data

barley = data.barley()

base = alt.Chart(barley).mark_bar().encode(
    y='mean(yield):Q',
    color=alt.Color('mean(yield):Q', legend=None)
).properties(width=100, height=100)

# Sort x in ascending order
ascending = base.encode(
    alt.X(field='site', type='nominal', sort='ascending')
).properties(
    title='Ascending'
)

# Sort x in descending order
descending = base.encode(
    alt.X(field='site', type='nominal', sort='descending')
).properties(
    title='Descending'
)

# Sort x in an explicitly-specified order
explicit = base.encode(
    alt.X(field='site', type='nominal',
          sort=['Duluth', 'Grand Rapids', 'Morris',
                'University Farm', 'Waseca', 'Crookston'])
).properties(
    title='Explicit'
)

# Sort according to another field
sortfield = base.encode(
    alt.X(field='site', type='nominal',
          sort=alt.EncodingSortField(field='yield', op='mean'))
).properties(
    title='By Yield'
)

ascending | descending | explicit | sortfield

Sorting Legends

While the above examples show sorting of axes by specifying sort in the X and Y encodings, legends can be sorted by specifying sort in the Color encoding:

alt.Chart(barley).mark_rect().encode(
    alt.X('mean(yield):Q', sort='ascending'),
    alt.Y('site:N', sort='descending'),
    alt.Color('site:N',
        sort=['Morris', 'Duluth', 'Grand Rapids',
              'University Farm', 'Waseca', 'Crookston']
    )
)

Here the y-axis is sorted reverse-alphabetically, while the color legend is sorted in the specified order, beginning with 'Morris'.