Update README.md [ci skip]

Author: olekscode

README.md

@@ -18,7 +18,7 @@ Data frames are the one of the essential parts of the data science toolkit. They
 A data frame is like a database inside a variable. It is an object which can be created, modified, copied, serialized, debugged, inspected, and garbage collected. It allows you to communicate with your data quickly and effortlessly, using just a few lines of code. DataFrame project is similar to [pandas](https://pandas.pydata.org/) library in Python or built-in [data.frame](https://www.rdocumentation.org/packages/base/versions/3.5.3/topics/data.frame) class in R.
 
 ## Installation
-The following script installs DataFrame into the Pharo image
+To install DataFrame, go to the Playground (`Ctrl+OW`) in your fresh Pharo image and execute the following Metacello script (select it and press Do-it button or `Ctrl+D`):
 
 ```smalltalk
 Metacello new
@@ -27,65 +27,10 @@ Metacello new
   load.
 ```
 
+## Simple example
+
 ## DataFrame Booklet
 
 For more information, please read [Data Analysis Made Simple with Pharo DataFrame](https://github.com/SquareBracketAssociates/Booklet-DataFrame) - a booklet that serves as the main source of documentation for the DataFrame project. It describes the complete API of DataFrame and DataSeries data structures, and provides examples for each method.
 
 [![DataFrame Booklet](img/booklet.png)](https://github.com/SquareBracketAssociates/Booklet-DataFrame)
-
-## Example
-
-This is a small example that will demonstrate how DataFrame can be used for collecting and preprocessing the dataset of methods. For more detailed information read the [DataFrame booklet](https://github.com/SquareBracketAssociates/Booklet-DataFrame).
-
-### Collecting all methods from the image
-
-First we collect an array of all methods in the image - instances of CompiledMethod class that belong to some package:
-```Smalltalk
-methods := CompiledMethod allInstances select: [ :method |
-	method package isNotNil ].
-```
-From each method we extract its name, source code, package name, and class name. We remove first line of source code of each method to remove method's name from it:
-```Smalltalk
-rows := methods collect: [ :method |
-  {
-    method package name .
-    method methodClass name .
-    method selector .
-    method sourceCode copyAfter: Character cr
-  } ].
-```
-### Creating a DataFrame
-We create a DataFrame and specify the names of its columns:
-```Smalltalk
-methodsData := DataFrame
-  withRows: rows
-  columnNames: #(packageName className methodName sourceCode).
-```
-### Adding a column
-We add a new column with number of arguments for each method. To do that we count the number of occurences of `:` symbol in method's name:
-```Smalltalk
-methodsData
-  addColumn: ((methodsData column: #methodName)
-    collect: [ :name | name occurrencesOf: $: ])
-  named: #numberOfArgs.
-```
-### Filtering data
-Now we select only those methods that belong to package [Renraku](https://github.com/Uko/Renraku), have at least one argument, and source code with less than 5 tokens:
-```Smalltalk
-renrakuMethods := methodsData select: [ :row |
-  ((row at: #packageName) = 'Renraku' and: 
-  (row at: #numberOfArgs) > 0) and:
-  ((row at: #sourceCode) findTokens: ' ') size < 5 ].
-```
-### Sorting rows by values of a column
-First we sort methods by their names and then we sort the result by number of arguments in descending order:
-```Smalltalk
-renrakuMethods
-  sortBy: #methodName;
-  sortDescendingBy: #numberOfArgs.
-```
-### Selecting specific columns
-We selecting only 4 columns (without className) and specify their order. If you inspect the result of this query, you will see the table similar to the one in a screenshot above.
-```Smalltalk
-renrakuMethods columns: #(packageName numberOfArgs methodName sourceCode).
-```