README.md in csv_decision-0.4.0 vs README.md in csv_decision-0.4.1

@@ -18,14 +18,14 @@
 
 ### Why use `csv_decision`?
  
 Typical "business logic" is notoriously illogical - full of corner cases and one-off 
 exceptions. 
-A decision table can express data-based decisions in a way that comes more naturally 
-to subject matter experts, who typically prefer spreadsheet models. 
-Business logic may then be encapsulated, avoiding the need to write tortuous 
-conditional expressions in Ruby that draw the ire of `rubocop` and its ilk.
+A decision table can express data-based decisions in a way that comes naturally 
+to subject matter experts, who typically use spreadsheet models. 
+Business logic can be encapsulated in a table, avoiding the need for tortuous conditional 
+expressions.
 
 This gem and the examples below take inspiration from 
 [rufus/decision](https://github.com/jmettraux/rufus-decision).
 (That gem is no longer maintained and CSV Decision has better 
 decision-time performance, at the expense of slower table parse times and more memory -- 
@@ -73,11 +73,11 @@
 The ordering of rows matters. `Ernest`, who is in charge of `finance` for the rest of 
 the world, except for `America` and `Europe`, *must* come after his colleagues 
 `Charlie` and `Donald`. `Zach` has been placed last, catching all the input combos
 not matching any other row.
 
-Here is the example as code:
+Here's the example as code:
  
  ```ruby
   # Valid CSV string
   data = <<~DATA
     in :topic, in :region,  out :team_member
@@ -125,11 +125,11 @@
 
 ### CSV Decision features
  * Either returns the first matching row as a hash (default), or accumulates all matches as an 
  array of hashes (i.e., `parse` option `first_match: false` or CSV file option `accumulate`).
  * Fast decision-time performance (see `benchmarks` folder). Automatically indexes all 
- text-only columns that do not contain any empty strings.
+ constants-only columns that do not contain any empty strings.
  * In addition to simple strings, `csv_decision` can match basic Ruby constants (e.g., `=nil`), 
  regular expressions (e.g., `=~ on|off`), comparisons (e.g., `> 100.0` ) and 
  Ruby-style ranges (e.g., `1..10`)
  * Can compare an input column versus another input hash key - e.g., `> :column`.
  * Any cell starting with `#` is treated as a comment, and comments may appear anywhere in the
@@ -196,10 +196,11 @@
       ,           no
     DATA
  ```
 These comparison operators are also supported: `!=`, `>`, `>=`, `<`, `<=`. 
 In addition, you can also apply a Ruby 0-arity method - e.g., `.present?` or `.nil?`. Negation is
-also supported - e.g., `!.nil?`.
+also supported - e.g., `!.nil?`. Note that `.nil?` can also be written as `:= nil?`, and `!.nil?`
+as `:= !nil?`, depending on preference.
 
 For more simple examples see `spec/csv_decision/examples_spec.rb`.
 
 #### Input `guard` conditions
 Sometimes it's more convenient to write guard expressions in a single column specialized for that purpose. 
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