advance_math 3.3.8

A robust Dart library for comprehensive mathematical programming. Offers complex numbers, algebra, statistics, angles, and geometry for diverse computations.

example/example.dart

import 'package:advance_math/advance_math.dart';

// import 'dart:math';

void printLine([String s = '']) {
  var l = '--- ' * 10;
  print('\n$l$s $l\n');
}

void main() {
  print(gcd([-4.5, 18])); // Output: 6

  print(gcd([-12, -18, -24])); // Output: 6

  printLine();

  print(nthPrime(2));

  print(Fraction.tryParse("4 8/2")!.isImproper());

  printLine();

  List<int> numbers = [1, 2, 3];
  int m = 2;

  // Get all combinations of 2 elements from the list
  var combinationsList = combinations(numbers, m);
  print(combinationsList); // Output: [[1, 2], [1, 3], [2, 3]]

  // Apply a function to each combination (e.g., sum the elements)
  var sums =
      combinations(numbers, m, func: (comb) => comb.reduce((a, b) => a + b));
  print(sums); // Output: [3, 4, 5]

  var cc = combinations(4, 3,
      simplify: true, func: (comb) => comb.reduce((a, b) => a + b));
  print(cc); // 6, 7, 8, 9]

  print(combinations(["A", "B", "C", "D"], 2, generateCombinations: true));
  //[[A, B], [A, C], [A, D], [B, C], [B, D], [C, D]]

  var minCombo = combinations(4, 3, simplify: true, func: (comb) {
    List<num> result = [];
    for (int i = 0; i < comb.length - 1; i++) {
      result.add(min(comb[i], comb[i + 1]));
    }
    return result;
  });
  print(minCombo); //[[1, 2], [1, 2], [1, 3], [2, 3]]

  print(combinations(5, 3).length);

  printLine();
  print(permutations(["A", "B", "C", "D"], 2));
  print(permutations(5, 3).length); // Output: 60
  print(permutations(3, 2));
  var productPermutations =
      permutations(3, 2, func: (perm) => perm.reduce((a, b) => a * b));
  print(productPermutations); // Output: [2, 2, 3, 3, 6, 6] (simplified)

  printLine();

  // DataFrame(
  //   columnNames = ['index',	'date',	'week',	'weekday',	'area',	'count',	'rabate',	'price',	'operator',	'driver',	'delivery_min',	'temperature',	'wine_ordered',	'wine_delivered',	'wrongpizza',	'quality']
  // );

  var df = DataFrame.fromCSV(csv: """
index,date,week,weekday,area,count,rabate,price,operator,driver,delivery_min,temperature,wine_ordered,wine_delivered,wrongpizza,quality
1,01/03/2014,9,6,Camden,5,TRUE,65.655,Rhonda,Taylor,20,53,0,0,FALSE,medium
2,01/03/2014,9,6,Westminster,2,FALSE,26.98,Rhonda,Butcher,19.6,56.4,0,0,FALSE,high
3,01/03/2014,9,6,Westminster,3,FALSE,40.97,Allanah,Butcher,17.8,36.5,0,0,FALSE,NA
4,01/03/2014,9,6,Brent,2,FALSE,25.98,Allanah,Taylor,37.3,NA,0,0,FALSE,NA
5,01/03/2014,9,6,Brent,5,TRUE,57.555,Rhonda,Carter,21.8,50,0,0,FALSE,medium
6,01/03/2014,9,6,Camden,1,FALSE,13.99,Allanah,Taylor,48.7,27,0,0,FALSE,low
7,01/03/2014,9,6,Camden,4,TRUE,89.442,Rhonda,Taylor,49.3,33.9,1,1,FALSE,low
8,01/03/2014,9,6,Brent,NA,NA,NA,Allanah,Taylor,25.6,54.8,NA,NA,FALSE,high
9,01/03/2014,9,6,Westminster,3,FALSE,40.97,Allanah,Taylor,26.4,48,0,0,FALSE,high
10,01/03/2014,9,6,Brent,6,TRUE,84.735,Rhonda,Carter,24.3,54.4,1,1,FALSE,medium
11,01/03/2014,9,6,Westminster,3,FALSE,66.41,Allanah,Miller,11.7,28.8,1,1,FALSE,low
12,01/03/2014,9,6,Brent,5,TRUE,62.955,Rhonda,Carter,19.5,51.3,0,0,FALSE,medium
13,01/03/2014,9,6,Camden,4,TRUE,46.764,Allanah,Taylor,32.7,24.05,0,0,FALSE,low
14,01/03/2014,9,6,Camden,1,FALSE,49.95,Rhonda,Carter,38.8,35.7,1,1,FALSE,low
15,01/03/2014,9,6,Brent,6,TRUE,73.746,Rhonda,Carter,23,53.6,0,0,FALSE,medium
16,01/03/2014,9,6,Westminster,5,TRUE,57.555,Rhonda,Miller,30.8,51.3,0,0,FALSE,<NA>
17,<NA>,NA,NA,Brent,2,FALSE,26.98,Allanah,Carter,27.7,51,0,0,FALSE,high
18,01/03/2014,9,6,Brent,2,FALSE,27.98,Rhonda,Butcher,29.7,47.7,0,0,FALSE,medium
19,01/03/2014,9,6,Brent,3,FALSE,41.97,Rhonda,Carter,9.1,52.8,0,0,FALSE,medium
20,01/03/2014,9,6,Westminster,1,FALSE,11.99,Rhonda,Miller,37.3,20,0,0,FALSE,low
21,01/03/2014,9,6,Brent,4,TRUE,46.764,Allanah,Butcher,21.2,52.4,0,0,FALSE,<NA>
22,01/03/2014,9,6,Brent,4,TRUE,52.164,Rhonda,Butcher,10.6,55.1,0,0,FALSE,medium
23,01/03/2014,9,6,Westminster,3,FALSE,44.97,Rhonda,Butcher,19.5,26.7,0,0,FALSE,low
24,01/03/2014,9,6,Camden,4,TRUE,51.264,Rhonda,Taylor,31,49.8,0,0,FALSE,medium
25,01/03/2014,9,6,Westminster,3,FALSE,38.97,Allanah,Miller,20.8,32.5,0,0,FALSE,low
26,01/03/2014,9,6,Brent,5,TRUE,58.455,Allanah,Taylor,18,36.8,0,0,FALSE,medium
27,01/03/2014,9,6,Brent,5,TRUE,97.065,Rhonda,Butcher,25.6,51,1,1,FALSE,medium
28,01/03/2014,9,6,Westminster,6,TRUE,75.546,Allanah,Miller,11.8,54.4,0,0,FALSE,high
29,01/03/2014,9,6,Camden,5,TRUE,65.655,Rhonda,Taylor,36.5,46.2,0,0,FALSE,medium
30,01/03/2014,9,6,Westminster,2,FALSE,30.98,Rhonda,Butcher,17.4,56.4,0,0,FALSE,<NA>
31,01/03/2014,9,6,Camden,2,FALSE,26.98,Allanah,Carter,23.5,35.7,0,0,FALSE,medium
32,01/03/2014,9,6,Westminster,4,TRUE,51.264,Rhonda,Butcher,24.2,49.1,0,0,FALSE,medium
33,01/03/2014,9,6,Brent,5,TRUE,61.155,Allanah,Carter,15,53.3,0,0,FALSE,<NA>
34,01/03/2014,9,6,Camden,3,FALSE,42.97,Allanah,Carter,36.2,41.7,0,0,FALSE,<NA>
35,01/03/2014,9,6,Westminster,2,FALSE,25.98,Rhonda,Taylor,25.9,47.6,0,0,FALSE,<NA>
36,01/03/2014,9,6,Westminster,5,TRUE,57.555,Allanah,Butcher,32.4,30.3,0,0,FALSE,low
37,01/03/2014,9,6,Brent,3,FALSE,44.97,Allanah,Butcher,15.4,37.8,0,0,FALSE,medium
38,01/03/2014,9,6,Brent,4,TRUE,48.564,Rhonda,Taylor,30.6,23.55,0,0,FALSE,low
39,01/03/2014,9,6,Brent,3,FALSE,40.97,Allanah,Taylor,27.9,49.9,0,0,FALSE,high
40,01/03/2014,9,6,Camden,4,TRUE,49.464,Allanah,Taylor,23,50.7,0,0,FALSE,high
41,01/03/2014,9,6,Brent,2,FALSE,24.98,Rhonda,Taylor,39.7,20.45,0,0,FALSE,low
42,01/03/2014,9,6,Westminster,6,TRUE,74.646,Allanah,Miller,29.1,25.85,0,0,FALSE,low
43,01/03/2014,9,6,Camden,3,FALSE,38.97,Rhonda,Taylor,34.4,43.8,0,0,FALSE,medium
44,02/03/2014,9,7,Camden,4,TRUE,92.466,Rhonda,Farmer,9.5,54.2,1,0,FALSE,medium
45,02/03/2014,9,7,Camden,1,FALSE,56.43,Allanah,Farmer,11.2,55.2,1,1,FALSE,high
46,02/03/2014,9,7,Westminster,4,TRUE,44.964,Rhonda,Farmer,14.4,55.9,0,0,FALSE,high
47,02/03/2014,9,7,Brent,4,TRUE,78.957,Allanah,Hunter,9.2,22.2,1,1,FALSE,low
48,02/03/2014,9,7,Brent,1,FALSE,13.99,Allanah,Hunter,11.9,52.8,0,0,FALSE,high
49,02/03/2014,9,7,Brent,4,TRUE,89.154,Allanah,Butcher,9.4,41,1,1,FALSE,medium
50,02/03/2014,9,7,Brent,3,FALSE,37.97,Allanah,Taylor,21.4,33.2,0,0,FALSE,low
51,02/03/2014,9,7,Brent,2,FALSE,29.98,Rhonda,Hunter,11.5,54.5,0,0,FALSE,medium
52,02/03/2014,9,7,Brent,3,FALSE,47.97,Allanah,Hunter,15.7,54.4,0,0,FALSE,<NA>
53,02/03/2014,9,7,Camden,1,FALSE,13.99,Allanah,Taylor,27.2,46,0,0,FALSE,<NA>
54,02/03/2014,9,7,Camden,3,FALSE,75.47,Rhonda,Taylor,27.7,26.3,1,1,FALSE,low
55,02/03/2014,9,7,Camden,6,TRUE,74.646,Rhonda,Farmer,23.7,51.1,0,0,FALSE,medium
56,02/03/2014,9,7,Camden,3,FALSE,36.97,Rhonda,Farmer,18.2,26.35,0,0,FALSE,low
57,02/03/2014,9,7,Westminster,4,TRUE,49.464,Allanah,Hunter,17.1,37.8,0,0,FALSE,medium
58,02/03/2014,9,7,Camden,1,FALSE,13.99,Rhonda,Farmer,19.9,51.5,0,0,FALSE,<NA>
59,02/03/2014,9,7,Camden,3,FALSE,79.67,Rhonda,Farmer,21.9,53.1,1,1,FALSE,<NA>
60,02/03/2014,9,7,Westminster,2,FALSE,63.78,Rhonda,Farmer,15.5,54.5,1,1,FALSE,medium
61,02/03/2014,9,7,Camden,4,TRUE,54.864,Allanah,Taylor,25.4,48.8,0,0,FALSE,high
62,02/03/2014,9,7,Camden,2,FALSE,25.98,Rhonda,Taylor,25.6,50.3,0,0,FALSE,medium
""");

  print(df.shape);
  print(df.columnNames);
  print(df.tail(5));
  print(df.head(5));
  df.rename({"date": "Date"});
  print(df.columnNames);
  df.drop('index');
  print(df.head(5));
  df.fillna('Charles');
  print(df.head(5));

  print(df.groupBy('area'));
  print(df.valueCounts('area'));

  print(df.limit(10, startIndex: 2));

  df = DataFrame(
    ['A', 'B', 'C', 'D'],
    [
      [1, 2.5, 3, 4],
      [2, 3.5, 4, 5],
      [3, 4.5, 5, 6],
      [4, 5.5, 6, 7],
    ],
  );

  // Describe the DataFrame
  print(df.describe());
}