README.md in csv-import-analyzer-0.0.5 vs README.md in csv-import-analyzer-0.0.6

@@ -1,12 +1,10 @@
 # Csv::Import::Analyzer
 
-Perform datatype analysis on desired chunk
-Calculate min-max bounds for each column
-Determine which coulmns are nullable in the csv file
+CsvImportAnalyzer is intended to help perform data analysis on csv (comma seperated), tsv (tab seperated) or ssv (semi-colon seperated) files. It can be used to process large datasets in desired chunk sizes (defaults to 200 rows), gives you a comprehensive analysis on each column with possible datatype, minimum and manimum bounds, if the column can be set to nullable for each column. 
 
-Note: This gem expects the first line to be definitve header, as in like column names if the csv file has to be imported to database.
+<b>Note</b>: This gem expects the first line to be definitve header, as in like column names if the csv file has to be imported to database.
 
 ## Installation
 
 Add this line to your application's Gemfile:
 
@@ -22,33 +20,126 @@
 
     $ gem install csv-import-analyzer
 
 ## Usage
 
-Calling process on a filename would generate a metadata_output.json which has the Delimiter, Datatype Analysis and SQL (create and import) statements for both PostgreSQL and MySQL
+Calling process on a filename would generate metadata for the sample file and return it as a json object. This metadata would have the following
+<ul>
+    <li> High level stats for the given file (E.g. filename, file size, number of rows, number of columns).</li>
+    <li> Data manipulation done for pre-processing the file.</li>
+    <li> Data analysis on each column as key value pairs.</li>
+    <li> By default you would also have MySQL queries that you need to import the file to database.</li>
+</ul>
+```ruby
+  CsvImportAnalyzer.process(filename)
+```
 
+## Demo
+
+Below is a sample test.csv file
+
+```
+Year ID,Make ID,Model ID,Description ID,Price ID
+1997,Ford,E350,"ac, abs, moon","3000.00"
+1999,Chevy,"Venture ""Extended Edition""",,4900.00
+1999,"Chevy","Venture ""Extended Edition, Very Large""","",5000.00
+1996,Jeep,Grand Che'rokee,"MUST SELL!air, moon roof, loaded",4799.00
+```
+To get the data analysis of above file, you can use CsvImportAnalyzer to process the file.
+
 ```ruby
+metadata = CsvImportAnalyzer.process("test.csv", {:distinct => 2})
+```
+### Result
+Now the metadata would hold the json object of the comprehensive analysis. Below is what the metadata would be for the sample csv file
+```ruby
+puts metadata
+```
+```json
+{
+  "csv_file": {
+    "filename": "sampleTab.csv",
+    "file_size": 276,
+    "record_delimiter": ",",
+    "rows": 6,
+    "columns": 5,
+    "processed_filename": "processed_sampleTab.csv",
+    "processed_file_path": "/tmp/processed_sampleTab.csv",
+    "processed_file_size": 279,
+    "error_report": "/tmp/error_report_sampleTab.csv"
+  },
+  "data_manipulations": {
+    "replace_nulls": true,
+    "replace_quotes": true
+  },
+  "csv_headers": {
+    "year_id": {
+      "datatype": "int",
+      "datatype_analysis": {
+        "int": 4
+      },
+      "distinct_values": "2+"
+    },
+    "make_id": {
+      "datatype": "string",
+      "datatype_analysis": {
+        "string": 4
+      },
+      "distinct_values": "2+"
+    },
+    "model_id": {
+      "datatype": "string",
+      "datatype_analysis": {
+        "string": 4
+      },
+      "distinct_values": "2+"
+    },
+    "description_id": {
+      "datatype": "string",
+      "datatype_analysis": {
+        "string": 2
+      },
+      "distinct_values": [
+        "ac, abs, moon",
+        "MUST SELL!air, moon roof, loaded"
+      ],
+      "nullable": true
+    },
+    "price_id": {
+      "datatype": "float",
+      "datatype_analysis": {
+        "float": 4
+      },
+      "distinct_values": "2+"
+    }
+  },
+  "sql": {
+    "mysql": {
+      "create_query": "create table processed_sampletab.csv ( year_id int not null, make_id varchar(255) not null, model_id varchar(255) not null, description_id varchar(255), price_id float not null);",
+      "import_query": "COPY processed_sampletab.csv FROM '/tmp/processed_sampleTab.csv' HEADER DELIMITER ',' CSV NULL AS 'NULL';"
+    }
+  }
+}
 
-  CsvImportAnalyzer.process(filename)
-  
 ```
 
 ## TODO:
   <ul>
-    <li> Handle control of processed input file to user </li>
-    <li> Return the analysis as Json object.</li>
     <li> Better - Structuring the analysis outputted to csv</li>
     <li> Add support to convert and import xlsx files to csv </li>
+    <li> Handle control of processed input file to user </li>
   </ul>
 
 ## Additional Information
 
 ### Dependencies
+
   <ul><li><a href="https://github.com/tilo/smarter_csv">smarter_csv</a> - For processing the csv in chunks</li></ul>
   
 ## Contributing
 
 1. Fork it ( https://github.com/avinash-vllbh/csv-import-analyzer/fork )
 2. Create your feature branch (`git checkout -b my-new-feature`)
 3. Commit your changes (`git commit -am 'Add some feature'`)
 4. Push to the branch (`git push origin my-new-feature`)
 5. Create a new Pull Request
+