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Description
Is your feature request related to a problem? Please describe.
A DanfoJS Series shift method seems to be missing
https://pandas.pydata.org/docs/reference/api/pandas.Series.shift.html
Describe the solution you'd like
I want to convert to JS this Python code
df["Lap"] = ((df["Distance"] - df["Distance"].shift()) < 0).astype(int).cumsum()
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
shift method is very convenient to measure difference between 2 consecutive values.
Here is my full code
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<script src="https://cdn.jsdelivr.net/npm/[email protected]/lib/bundle.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/d3-fetch.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/d3-dsv.min.js"></script>
<title>KRP Telemetry</title>
</head>
<body>
<div id="map_div"></div>
<div id="plot_div_Engine"></div>
<div id="plot_div_CylHeadTemp"></div>
<div id="plot_div_WaterTemp"></div>
<div id="plot_div_Gear"></div>
<div id="plot_div_Speed"></div>
<div id="plot_div_LatAcc"></div>
<div id="plot_div_LonAcc"></div>
<div id="plot_div_Steer"></div>
<div id="plot_div_Throttle"></div>
<div id="plot_div_Brake"></div>
<div id="plot_div_FrontBrakes"></div>
<div id="plot_div_Clutch"></div>
<div id="plot_div_YawVel"></div>
<script>
const url = "https://raw.githubusercontent.com/scls19fr/krp_python_telemetry/main/Logdata%20Essay%20mini60%202023-10-31.csv"
parsed = fetch(url)
.then(response => response.text())
.then(text => {
// Normalize line breaks and split segments by double line breaks.
const [metaText, columns, rows] = text.replace(/\r?\n/g, "\n").split(/\n\n/);
// Parse first meta section as csv, then convert to an object
const meta = Object.fromEntries(d3.csvParseRows(metaText));
// Parse the two lines from the headers segment
const [headers, units] = d3.csvParseRows(columns);
// Parse the rows segment into an untyped array of arrays.
const data = d3.csvParseRows(rows);
df_head = new dfd.DataFrame([meta])
df_head.print()
df_units = new dfd.DataFrame([units], {columns: headers})
df_units.print()
df_data = new dfd.DataFrame(data, {columns: headers});
//console.log(df_data);
df_data.print();
//df_data["Lap"] = df_data["Distance"].shift(); // ToFix
//df_data["Lap"].print();
df_data.plot("map_div").scatter({
config: {
x: "PosX", y: "PosY"
}
});
df_data.plot("plot_div_Engine").line({
config: {
x: "Distance", y: "Engine"
}
});
df_data.plot("plot_div_CylHeadTemp").line({
config: {
x: "Distance", y: "CylHeadTemp"
}
});
df_data.plot("plot_div_WaterTemp").line({
config: {
x: "Distance", y: "WaterTemp"
}
});
df_data.plot("plot_div_Gear").line({
config: {
x: "Distance", y: "Gear"
}
});
df_data.plot("plot_div_Speed").line({
config: {
x: "Distance", y: "Speed"
}
});
df_data.plot("plot_div_LatAcc").line({
config: {
x: "Distance", y: "LatAcc"
}
});
df_data.plot("plot_div_LonAcc").line({
config: {
x: "Distance", y: "LonAcc"
}
});
df_data.plot("plot_div_Steer").line({
config: {
x: "Distance", y: "Steer"
}
});
df_data.plot("plot_div_Throttle").line({
config: {
x: "Distance", y: "Throttle"
}
});
df_data.plot("plot_div_Brake").line({
config: {
x: "Distance", y: "Brake"
}
});
df_data.plot("plot_div_FrontBrakes").line({
config: {
x: "Distance", y: "FrontBrakes"
}
});
df_data.plot("plot_div_Clutch").line({
config: {
x: "Distance", y: "Clutch"
}
});
df_data.plot("plot_div_YawVel").line({
config: {
x: "Distance", y: "YawVel"
}
});
return {meta, headers, units, data};
})
//const df = new dfd.DataFrame({'pig': [20, 18, 489, 675, 1776],
// 'horse': [4, 25, 281, 600, 1900]}, {index: [1990, 1997, 2003, 2009, 2014]})
//df.plot("plot_div").line()
</script>
</body>
</html>