More readme

README.md

 # ampli
 
-_Repository for Petra's work at [ampli](https://www.ampli.nz) Jan-Feb 2019_
+_Repository for Petra Lamborn's internship at [ampli](https://www.ampli.nz) Jan-Feb 2019_
+
+This repository serves as both a reference for the folk at ampli to build upon what I produced for them during this internship, and as a CV item for me. Non-ampli people will not be able to directly use all but a handful of the below, but it still demonstrates what I can do.
+
+The purpose of this project was to cluster the electricity demand time series of a large number of ICPs (Installation Control Points), and then project the patterns for these clusters into the future.
 
 ## What isn't in this repository
 
 
 ## SQL
 
-I've included a bunch of annotated SQL queries in `sql/queries.pgsql` and `sql/weather.pgsql`. The latter file is specifically about the weather dataset; the former is more general. Some of the queries are copied into the `py/util.py` file, but changing these two files will do nothing on their own.
+I've included a bunch of annotated SQL queries in `sql/queries.pgsql` and `sql/weather.pgsql`. The latter file is specifically about the weather dataset; the former is more general. Some of the queries are copied into the `py/util.py` file and similar, but changing these two files will do nothing on their own.
+
+The `queries.pgsql` file includes the commands used to create the tables available in the `--table` option of the `downkwh.py` script.
 
 ## Python
 
 * scipy
 * seaborn
 * statsmodels
+* tabview
 
 Virtual environments are loaded with `source venv/bin/activate`. The python scripts are in the `py/` folder. The scripts that are designed to be called directly are called by `python <scriptname.py>`; use `python <scriptname.py> -h` to view help. Note that most options will have a default, which may not be what you want, so always check.
 
 
 The justification for this is that we want to include the deviation from typical value for that time of year in our model, not the value itself.
 
+As written, this script assumes a python virtual environment located in `../venv/`.
+
 ### `combmodels.R`
 
 Taking `../data/9-clusters.agg.pkl` and `../data/weatherharm.csv` as inputs, this script first fits a harmonic model to cluster 1 and tests it with the assigned clusters in `../data/1617-agg.pkl`. It then fits models to all clusters and saves them collectively in `../models/1kmods.rds`.
 
 Similar to the previous, some plots are again commented out.
 
+As written, this script assumes a python virtual environment located in `../venv/`.
+
 ## Shiny App
 
 The [R Shiny](https://shiny.rstudio.com/) app is located in `shiny/app.R`. It requires the outputs from `weathmod.R` and `combmodels.R`, along with a couple of extra packages, installed with: