statastic:0.1.0

packages/preview/statastic-0.1.0/LICENSE

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+This is free and unencumbered software released into the public domain.
+
+Anyone is free to copy, modify, publish, use, compile, sell, or
+distribute this software, either in source code form or as a compiled
+binary, for any purpose, commercial or non-commercial, and by any
+means.
+
+In jurisdictions that recognize copyright laws, the author or authors
+of this software dedicate any and all copyright interest in the
+software to the public domain. We make this dedication for the benefit
+of the public at large and to the detriment of our heirs and
+successors. We intend this dedication to be an overt act of
+relinquishment in perpetuity of all present and future rights to this
+software under copyright law.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
+OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
+ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+OTHER DEALINGS IN THE SOFTWARE.
+
+For more information, please refer to <https://unlicense.org>

packages/preview/statastic-0.1.0/README.md

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+# Statastic
+
+A library to calculate statistics for numerical data in typst.
+
+## Description
+
+`Statastic` is a Typst library designed to provide various statistical functions for numerical data. It offers functionalities like extracting specific columns from datasets, converting array elements to different data types, and computing various statistical measures such as average, median, mode, variance, standard deviation, and percentiles.
+
+## Features
+
+- **Extract Column**: Extracts a specific column from a given dataset.
+- **Type Conversion**: Convert array elements to floating point numbers or integers.
+- **Statistical Measures**: Calculate average, median, mode, variance, standard deviation, and specific percentiles for an array or a specific column in a dataset.
+
+## Usage
+
+To use the package you can import it through this command `import "@preview/statastical:0.1.0": *` (as soon as the pull request ist accepted). The documentation is found in the `docs.pdf` in the development [repo](https://github.com/Sett17/typst-statastic)
+
+## License
+
+This project is licensed under the Unlicense.

packages/preview/statastic-0.1.0/lib.typ

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+/// Extracts a specific column from the given dataset based on the column.
+/// 
+/// - data (array): The dataset.
+/// - colId (int): The identifier for the column to be extracted.
+/// -> array
+#let extractColumn(data, colId) = {
+    let column = ()
+    for row in data {
+        column.push(row.at(colId))
+    }
+    column
+}
+
+/// Converts an array's elements to floating point numbers.
+///
+/// - arr (array): Array with elements to be converted.
+/// -> array
+#let tofloatArray(arr) = {
+  let res = ()
+  for el in arr {
+    if el == "" {
+      res.push(0.0)
+    } else {
+      res.push(float(el))
+    }
+  }
+  res
+}
+
+/// Converts an array's elements to integers.
+///
+/// - arr (array): Array with elements to be converted.
+/// -> array
+#let toIntArray(arr) = {
+  let res = ()
+  for el in arr {
+    if el == "" {
+      res.push(0)
+    } else {
+      res.push(int(el))
+    }
+  }
+  res
+}
+
+/// Determines if a given value is an integer.
+///
+/// - val (mixed): The value to be checked.
+/// -> boolean
+#let isInt(val) = {
+  let f = float(val)
+  let i = int(f)
+  val == i
+}
+
+/// Calculates a value between two numbers at a specific fraction.
+///
+/// - lower (float): The lower number.
+/// - upper (float): The upper number.
+/// - fraction (float): The fraction between the two numbers.
+/// -> float
+#let lerp(lower, upper, fraction) = {
+  let diff = upper - lower
+  lower + (diff * fraction)
+}
+
+/// Calculates the average of an array's elements.
+///
+/// - arr (array): Array of numbers.
+/// -> float
+#let arrayAvg(arr) = {
+  let col = tofloatArray(arr)
+  col.sum() / col.len()
+}
+
+/// Calculates the average of a specific column in a dataset.
+///
+/// - data (array): The dataset.
+/// - colId (int): The identifier for the column.
+/// -> float
+#let avg(data, colId) = {
+  arrayAvg(extractColumn(data, colId))
+}
+
+/// Calculates the median of an array's elements.
+///
+/// - arr (array): Array of numbers.
+/// -> float
+#let arrayMedian(arr) = {
+  let col = tofloatArray(arr).sorted()
+  let len = col.len()
+  if (calc.rem(len, 2) == 0) {
+    let middle = calc.quo(len, 2)
+    (col.at(middle - 1) + col.at(middle)) / 2
+  } else {
+    let middle = calc.quo(len, 2) - 1
+    col.at(middle-1)
+  }
+}
+
+/// Calculates the median of a specific column in a dataset.
+///
+/// - data (array): The dataset.
+/// - colId (int): The identifier for the column.
+/// -> float
+#let median(data, colId) = {
+  arrayMedian(extractColumn(data, colId))
+}
+
+/// Calculates the mode of an integer array.
+/// Converts all floats to integers.
+///
+/// - arr (array): Array of integers.
+/// -> array
+#let arrayIntMode(arr) = {
+  let col = arr
+  let unique = col.dedup()
+  let counts = (:)
+  for k in unique {
+    counts.insert(str(k), 0)
+  }
+  for k in col {
+    counts.at(str(k)) += 1
+  }
+  let highestModeCount = 0
+  for (k, v) in counts.pairs() {
+    if (v > highestModeCount) {
+      highestModeCount = v
+    }
+  }
+  let modes = ()
+  for (k, v) in counts.pairs() {
+    if (v == highestModeCount) {
+      modes.push(int(k))
+    }
+  }
+  modes
+}
+
+/// Calculates the integer mode of a specific column in a dataset.
+/// Converts all floats to integers.
+///
+/// - data (array): The dataset.
+/// - colId (int): The identifier for the column.
+/// -> array
+#let intMode(data, colId) = {
+  arrayIntMode(toIntArray(tofloatArray((extractColumn(data, colId)))))
+}
+
+/// Calculates the variance of an array's elements.
+///
+/// - arr (array): Array of numbers.
+/// -> float
+#let arrayVar(arr) = {
+  let col = tofloatArray(arr)
+  let len = col.len()
+  let mean = col.sum() / len
+  let varSum = 0
+  for el in col {
+    varSum += calc.pow(el - mean, 2)
+  }
+  varSum / (len - 1)
+}
+
+/// Calculates the variance of a specific column in a dataset.
+///
+/// - data (array): The dataset.
+/// - colId (int): The identifier for the column.
+/// -> float
+#let var(data, colId) = {
+  arrayVar(extractColumn(data, colId))
+}
+
+/// Calculates the standard deviation of an array's elements.
+///
+/// - arr (array): Array of numbers.
+/// -> float
+#let arrayStd(arr) = {
+  let var = arrayVar(arr)
+  calc.sqrt(var)
+}
+
+/// Calculates the standard deviation of a specific column in a dataset.
+///
+/// - data (array): The dataset.
+/// - colId (int): The identifier for the column.
+/// -> float
+#let std(data, colId) = {
+  arrayStd(extractColumn(data, colId))
+}
+
+/// Calculates a specific percentile of an array's elements.
+///
+/// - arr (array): Array of numbers.
+/// - p (float): The desired percentile (between 0 and 1).
+/// -> float
+#let arrayPercentile(arr, p) = {
+  let col = tofloatArray(arr).sorted()
+  let n = col.len() - 1
+  let pos = p * n
+
+  if (isInt(pos)) {
+    col.at(int(pos))
+  } else {
+    let low = col.at(calc.floor(pos))
+    let high = col.at(calc.ceil(pos))
+    lerp(low, high, calc.fract(pos))
+  }
+}
+
+/// Calculates a specific percentile of a column in a dataset.
+///
+/// - data (array): The dataset.
+/// - colId (int): The identifier for the column.
+/// - p (float): The desired percentile (between 0 and 1).
+/// -> float
+#let percentile(data, colId, p) = {
+  arrayPercentile(extractColumn(data, colId), p)
+}
+
+/// Computes a set of statistical measures for an array.
+/// Includes: average, median, integer mode, variance, standard deviation, and some percentiles.
+///
+/// - arr (array): Array of numbers.
+/// -> dictionary
+#let arrayStats(arr) = {
+  (
+    "avg": arrayAvg(arr),
+    "median": arrayMedian(arr),
+    "intMode": arrayIntMode(arr),
+    "var": arrayVar(arr),
+    "std": arrayStd(arr),
+    "25percentile": arrayPercentile(arr, 0.25),
+    "50percentile": arrayPercentile(arr, 0.50),
+    "75percentile": arrayPercentile(arr, 0.75),
+    "95percentile": arrayPercentile(arr, 0.95),
+  )
+}
+
+/// Computes a set of statistical measures for a specific column in a dataset.
+/// Includes: average, median, integer mode, variance, standard deviation, and some percentiles.
+///
+/// - data (array): The dataset.
+/// - colId (int): The identifier for the column.
+/// -> dictionary
+#let stats(data, colId) = {
+  (
+    "avg": avg(data, colId),
+    "median": median(data, colId),
+    "intMode": intMode(data, colId),
+    "var": var(data, colId),
+    "std": std(data, colId),
+    "25percentile": percentile(data, colId, 0.25),
+    "50percentile": percentile(data, colId, 0.50),
+    "75percentile": percentile(data, colId, 0.75),
+    "95percentile": percentile(data, colId, 0.95),
+  )
+}

packages/preview/statastic-0.1.0/typst.toml

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+[package]
+name = "statastic"
+version = "0.1.0"
+entrypoint = "lib.typ"
+authors = "Sett17"
+license = "Unlicense"
+description = "A library to calculate statistics for numerical data"
+repository = "https://github.com/Sett17/typst-statastic"