Merge 0e61465 into d1f0913

CHANGELOG.md

@@ -1,4 +1,4 @@
-## 1.0 yyyy-mm-dd
+## 1.0 2019-07-05
 
 Import of the initial functionality from [benchee](github.com/bencheeorg/benchee).
 

README.md

@@ -27,6 +27,17 @@ iex> samples = [1, 3.0, 2.35, 11.0, 1.37, 35, 5.5, 10, 0, 2.35]
 iex> Statistex.statistics(samples)
 %Statistex{
   average: 7.156999999999999,
+  frequency_distribution: %{
+    0 => 1,
+    1 => 1,
+    10 => 1,
+    35 => 1,
+    1.37 => 1,
+    2.35 => 2,
+    3.0 => 1,
+    5.5 => 1,
+    11.0 => 1
+  },
   maximum: 35,
   median: 2.675,
   minimum: 0,
@@ -35,7 +46,8 @@ iex> Statistex.statistics(samples)
   sample_size: 10,
   standard_deviation: 10.47189577445799,
   standard_deviation_ratio: 1.46316833512058,
-  total: 71.57
+  total: 71.57,
+  variance: 109.6606011111111
 }
 # or just calculate the value you need
 iex> Statistex.average(samples)
@@ -51,11 +63,30 @@ iex> Statistex.statistics([])
 ** (ArgumentError) Passed an empty list ([]) to calculate statistics from, please pass a list containing at least on number.
 ```
 
+## Supported Statistics
+
+For an up to date overview with explanations please check out the documentation.
+
+Statistics currently supported:
+
+* average
+* frequency_distribution
+* maximum
+* median
+* minimum
+* mode
+* percentiles
+* sample_size
+* standard_deviation
+* standard_deviation_ratio
+* total
+* variance
+
 ## Alternatives
 
 In elixir there are 2 notable other libraries that I'm aware of: [statistics](https://github.com/msharp/elixir-statistics) and [Numerix](https://github.com/safwank/Numerix).
 
-Both include more functions than just statistics functions as in general math functions and more. They also have more statistics related functions as of this writing. So if you'e looking for something, that Statistex doesn't provide these are some of the first places I'd look.
+Both include more functions than just for statistics: general math and more (drawing of random values for instance). They also have more statistics related functions as of this writing. So if you'e looking for something, that Statistex doesn't provide (yet) these are some of the first places I'd look.
 
 Why would you still want to use Statistex?
 

lib/statistex.ex

@@ -261,11 +261,11 @@ defmodule Statistex do
 
   A measurement how much samples vary (the higher the more the samples vary). This is the variance of a sample and is hence in its calculation divided by sample_size - 1 (Bessel's correction).
 
+  `Argumenterror` is raised if the given list is empty.
+
   ## Options
   If already calculated, the `:average` and `:sample_size` options can be provided to avoid recalulating those values.
 
-  `Argumenterror` is raised if the given list is empty.
-
   ## Examples
 
       iex> Statistex.variance([4, 9, 11, 12, 17, 5, 8, 12, 12])
@@ -454,6 +454,8 @@ defmodule Statistex do
 
   Goes from a concrete occurence of the sample to the number of times it was observed in the samples.
 
+  `Argumenterror` is raised if the given list is empty.
+
   ## Examples
 
       iex> Statistex.frequency_distribution([1, 2, 4.23, 7, 2, 99])
@@ -504,8 +506,7 @@ defmodule Statistex do
       [1, 3, 5]
   """
   @spec mode(samples, keyword) :: mode
-  defdelegate mode(samples), to: Mode
-  defdelegate mode(samples, opts), to: Mode
+  def mode(samples, opts \\ []), do: Mode.mode(samples, opts)
 
   @doc """
   Calculates the median of the given samples.