Customer Obsession

This is a dashboard built with Dash that analyzes shareholder letters from Amazon going back to 1998.

Running the code locally

If you'd like to run my code on your own computer:

I've included the scraped pdf files, but if you'd like to rescrape them you can use the getdata.py script in notebooks.

I had a few goals with this project:

Learn more about Dash
Learn more about sentiment analysis
Finish an end-to-end analytics project, starting from data collection (my selenium script) to a final deliverable (deployed dashboard)

And oh boy did I learn quite a bit:

First and foremost, just the syntax and general workings of Dash, plotly, and nltk
Identifiying "sentences" was harder than I anticipated, as I needed to take into accounts acronyms ("etc.")
pypdf would sometimes combine words as each line broke, for example, if the pdf looked like this:
```
a test sentence
more words
```
The text output would end up being: a test sentencemore words
- I fixed this by using a package called wordninja which will split the above into: ['a', 'test', 'sentence', 'more', 'words']
I built a lot of analysis on top of the lemmatized version of the text instead of the raw version, but I didn't quite crack how to map between the lemmatized -> raw text
- For example, if you search for a term on the search page, the concordance table on the bottom will show the lemmatized version of the text instead of the raw version of the text. Definitely an area for improvement.
I really liked the development experience of Dash, the @callback decorator clicked with me and I feel way more confident building vizzes with plotly and adding interactivity with Dash.
If you deploy an app to Heroku and mistakenly name your Procfile something like ProcFile, none of the dynos will get created in Heroku and the web service wont ever start. I needed to DELETE it, commit the deletion, deploy to Heroku, then re-add the Procfile (named correctly) and deploy.

My webscraping script isn't perfect, for some reason the css selector didn't download the 2007 letter so I just downloaded that one manually
How you define "word" / "sentence" / "punctuation" can change the output your analysis dramatically