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Merge branch 'main' into vega-datasets
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dangotbanned authored Oct 4, 2024
2 parents 4d3c550 + d4c3bcf commit 7e65841
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6 changes: 6 additions & 0 deletions .github/release.yml
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changelog:
categories:
- title: Breaking
labels:
- breaking
- title: Deprecation
labels:
- deprecation
- title: Enhancements
labels:
- enhancement
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37 changes: 37 additions & 0 deletions tests/examples_arguments_syntax/calculate_residuals.py
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"""
Calculate Residuals
-------------------
A dot plot showing each movie in the database, and the difference from the average movie rating.
The display is sorted by year to visualize everything in sequential order.
The graph is for all Movies before 2019.
Adapted from `Calculate Residuals <https://vega.github.io/vega-lite/examples/joinaggregate_residual_graph.html>`_.
"""
# category: advanced calculations

import altair as alt
from vega_datasets import data

imdb_rating = alt.datum["IMDB_Rating"]
source = data.movies.url

chart = (
alt.Chart(source)
.mark_point()
.transform_filter(imdb_rating != None)
.transform_filter(
alt.FieldRangePredicate("Release_Date", [None, 2019], timeUnit="year")
)
.transform_joinaggregate(Average_Rating="mean(IMDB_Rating)")
.transform_calculate(Rating_Delta=imdb_rating - alt.datum.Average_Rating)
.encode(
x=alt.X("Release_Date:T", title="Release Date"),
y=alt.Y("Rating_Delta:Q", title="Rating Delta"),
color=alt.Color(
"Rating_Delta:Q",
title="Rating Delta",
scale=alt.Scale(domainMid=0),
),
)
)
chart
33 changes: 33 additions & 0 deletions tests/examples_methods_syntax/calculate_residuals.py
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"""
Calculate Residuals
-------------------
A dot plot showing each movie in the database, and the difference from the average movie rating.
The display is sorted by year to visualize everything in sequential order.
The graph is for all Movies before 2019.
Adapted from `Calculate Residuals <https://vega.github.io/vega-lite/examples/joinaggregate_residual_graph.html>`_.
"""
# category: advanced calculations

import altair as alt
from vega_datasets import data

imdb_rating = alt.datum["IMDB_Rating"]
source = data.movies.url

chart = (
alt.Chart(source)
.mark_point()
.transform_filter(imdb_rating != None)
.transform_filter(
alt.FieldRangePredicate("Release_Date", [None, 2019], timeUnit="year")
)
.transform_joinaggregate(Average_Rating="mean(IMDB_Rating)")
.transform_calculate(Rating_Delta=imdb_rating - alt.datum.Average_Rating)
.encode(
x=alt.X("Release_Date:T").title("Release Date"),
y=alt.Y("Rating_Delta:Q").title("Rating Delta"),
color=alt.Color("Rating_Delta:Q").title("Rating Delta").scale(domainMid=0),
)
)
chart

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