Tutorial.md

@@ -14,7 +14,7 @@ Updated with v1.0.
 * [8. Updating the table data](#8-updating-the-table-data)
 
 ## 1. Setting your environment
-In this section we'll look at how to get MonetDB working with hotmapper.
+In this section we'll look at how to get MonetDB working with HOTMapper.
 #### Important: 
     The MonetDB Apr2019 (11.33.3) version should be avoided, because it has a bug when inserting into a table with multiple constraints. It's already fixed in their nightly build so you should be fine using any superior version or the August2018 one.
 
@@ -44,7 +44,7 @@ Install python3-venv, if you don't have it, using the command bellow.
 $ sudo apt-get install python3-venv
 ~~~
 
-Inside the hotmapper folder execute the following commands:
+Inside the HOTMapper folder execute the following commands:
 ~~~Bash
 $ python3 -m venv env
 $ source env/bin/activate
@@ -52,9 +52,9 @@ $ pip install -r requirements.txt
 ~~~
 
 ## 2. Adjusting your HOTMapper Settings
-Now that you have a working monetdb database it's needed to verify the HOTMapper settings to be sure it'll work with it.
+Now that you have a working MonetDB database it's needed to verify the HOTMapper settings to be sure it'll work with it.
 
-First, using your favourite editor, open the file settings.py contained inside your HOTMapper folder.
+First, using your favourite editor, open the file `settings.py` contained inside your HOTMapper folder.
 
 Set the DATABASE variable to yours.
 
@@ -69,7 +69,7 @@ should already be correct and the folders already exist.
 If you want to learn more about all settings of HOTMapper, head to our [Settings page in the wiki](../Settings)
 
 ## 3. Creating your table definition
-The HOTMapper tool uses two files to create a table, a json inside the table_definitions folder and a csv present on the
+The HOTMapper tool uses two files to create a table, a json inside the table_definitions folder and a CSV present on the
 mapping_protocols folder. Both should have as name of the file: "table name + extension". Ex: table_test.json, 
 table_test.csv.
 
@@ -104,7 +104,7 @@ The map protocol file is used to store the information about the table columns a
 from the csv and the database. This file is stored inside the mapping_protocols folder and uses as name the "table name
 \+ .csv"
 
-This csv must contain the following columns:
+This CSV must contain the following columns:
 * Var. Lab -- An unique identifier for the column, this represents a specific column for the HOTMapper and shouldn't 
 be changed after table creation.
 * Novo Rótulo -- A description of this column.
@@ -148,7 +148,7 @@ If you want to learn more about the Mapping Protocol, click [here.](../Mapping-P
     
 ## 5. Creating the table in the database
 
-To create the table in your database we'll execute the hotmapper command 'create'. In the following way:
+To create the table in your database we'll execute the HOTMapper command `create`. In the following way:
 ~~~bash
 $ ./manage.py create <table_name>
 ~~~
@@ -159,7 +159,7 @@ $ ./manage.py create table_test
 
 ## 6. Inserting the data into the table
 
-To insert the csv data into the table, we'll use the hotmapper command 'insert' in the following way:
+To insert the CSV data into the table, we'll use the HOTMapper command `insert` in the following way:
 ~~~bash
 $ ./manage.py insert <file_location> <table_name> <year> --sep=<optional, csv separator>
 ~~~
@@ -174,7 +174,7 @@ $ ./manage.py insert ~/hotmapper/open_data/EAG_GRAD_RATES_2016.csv table_test 20
 * To remove a column, first delete it from the protocol.
 * To rename a column, change the "Nome Banco" (name of the column) in the protocol.
 
-After that, execute the hotmapper command 'remap' in the following way:
+After that, execute the HOTMapper command `remap` in the following way:
 ~~~bash
 $ ./manage.py remap <table_name>
 ~~~
@@ -187,8 +187,8 @@ Now you'll have to update the data in the table
 
 ## 8. Updating the table data
 
-If your data csv suffered any modifications or you changed the table by adding, removing or renaming a column, you'll
-have to update the data of the table. You'll can do that using the hotmapper command 'update_from_file' in a similar way
+If your data CSV suffered any modifications or you changed the table by adding, removing or renaming a column, you'll
+have to update the data of the table. You can do that using the HOTMapper command `update_from_file` in a similar way
 to the insert command:
 ~~~bash
 $ ./manage.py update_from_file <file_location> <table_name> <year> --sep=<optional, csv separator>