Merge pull request #1692 from fedspendingtransparency/stg

Sprint 75 Deploy Stg -> Master

README.md

@@ -44,12 +44,13 @@ Your prompt should then look as below to show you are _in_ the virtual environme
 
 [`pip`](https://pip.pypa.io/en/stable/installing/) `install` application dependencies
 
-:bulb: _(try a different WiFi if you're current one blocks dependency downloads)_
+:bulb: _(try a different WiFi if your current one blocks dependency downloads)_
 
     (usaspending-api) $ pip install -r requirements/requirements.txt
 
 Set environment variables (fill in the connection string placeholders, e.g. `USER`, `PASSWORD`, `HOST`, `PORT`)
-*note: default port for PostgreSQL is `5432`
+
+_Note: the default port for PostgreSQL is `5432`_
 
 ```shell
 

data_reformatting.md

@@ -18,7 +18,7 @@ Making sure our location-related fields are as robust and accurate as possible p
 
 We attempt to match incoming records that have partial location data to already-stored unique combinations of _state code_, _state name_, _city code_, _county code_, and _county name_.
 
-For example, if a record has a state code but no state name, we'll pull in state name from our master list of geographical data and add it to the record during the load.
+For example, if a record has a state code but no state name, we'll pull in the state name from our master list of geographical data and add it to the record during the load.
 
 ### Country Codes and Names
 
@@ -50,7 +50,7 @@ The following fields are canonicalized this way:
 **Data Source:** USAspending history  
 **Code:** `etl/helpers.py`
 
-Codes and descriptions in legacy Usaspending data are often stored in the same field. For example, a funding agency column looks like `7300: SMALL BUSINESS ADMINISTRATION`.
+Codes and descriptions in legacy USAspending data are often stored in the same field. For example, a funding agency column looks like `7300: SMALL BUSINESS ADMINISTRATION`.
 
 In these cases, we extract the code to use in our data load. We then use that code to look up the description against a canonical data source. Using a single, central source for code descriptions ensures data consistency.
 

requirements/requirements.txt

@@ -12,7 +12,7 @@ git+https://github.com/fedspendingtransparency/django-mock-queries#egg=django-mo
 django-queryset-csv==1.0.1
 django-simple-history==1.8.2
 django-spaghetti-and-meatballs==0.2.2
-Django==1.11.15
+Django==1.11.18
 djangorestframework==3.4.6
 drf-extensions==0.3.1
 drf-tracking==1.4.0