The avatar for @tashapiro
Tanya Shapiro
Independent Data Analytics Consultant, passionate about data visualization and storytelling · she/her 🏳️‍🌈
Public
Edited
Oct 2, 2023
8 forks
21 stars
3
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maxStatValue = d3.max(weekly, (d) => d.stat);
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splitBy = maxStatValue < 50 ? 10 : maxStatValue < 176 ? 25 : maxStatValue < 300 ? 50 : 100;
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roundedMaxStatValue = Math.round(maxStatValue / splitBy) * splitBy;
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function axisValues(maxStatValue, splitBy) {
const values = [];
for (let i = 0; i <= maxStatValue; i += splitBy) {
values.push(i);
}
return values;
}
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db
select b. *
from (
select a. *
,row_number() over () as rank
,(row_number() over ()-1) / 5 as row_num
,row_number() over ()-((row_number() over ()-1) / 5)*5 as col_num
from(
select b.player_id
,p.display_name as player_name
,t.team_abbr
,t.team_logo_espn
,count(distinct week) as games_played
,sum(stat::int)::int as stat
from pbp b
left join players p on p.gsis_id = b.player_id
left join teams t on t.team_abbr = p.team_abbr
where b.player_id <> 'NA' and b.stat <> 'NA'
group by all
having count(distinct week)>=4
order by 6 desc
) a
) b where rank < 26
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db = DuckDBClient.of({
pbp: updated_pbp,
players: players,
teams: teams
})
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db2 = DuckDBClient.of({
pbp: updated_pbp,
players: players,
teams: teams,
totals: totals
})
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pbp.csv
Type Table, then Shift-Enter. Ctrl-space for more options.

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players.csv
Type Table, then Shift-Enter. Ctrl-space for more options.

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teams.csv
Type Table, then Shift-Enter. Ctrl-space for more options.

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Map select stat to column name in pbp data before creating queries. Map playerId to respective player entity (e.g. passer_id)
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updated_pbp = pbp.map((item) => {
// Calculate the "stat" value based on the "yardline_100" property (you can replace this with your logic)
const stat = item[selectedStat];
const player_id = item[playerId];

// Create a new object with the "stat" property added
return { ...item, stat, player_id };
});
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