hilary_mason_data hilary_mason_data-2014 hilary_mason_data-2014-115 knowledge-graph by maker-knowledge-mining

115 hilary mason data-2014-02-14-Play with your food!


meta infos for this blog

Source: html

Introduction: Play with your food! Posted: February 14, 2014 | Author: Hilary Mason | Filed under: blog | Tags: data , food | Leave a comment » I spent a few minutes this week putting together a quick script to pull data from the Locu API . Locu has done the hard work of gathering and parsing menus from around the US and has a lot of interesting data (and a good data team ). The API is easy to query by menu item (like “cheeseburger”, my favorite ) and by running my little script I quickly had data for the prices of cheeseburgers in my set of zip codes (the 100 most populated metro areas in the US). I’m a big fan of Pete Warden’s OpenHeatMap tool for making quick map visualizations, and was able to come up with the following: The blue map is the average price of a cheeseburger by zip, with the red one showing the average price of pizza. The most expensive average cheeseburger can be found in Santa Clara, CA, ironically the city currently hosting the Str


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 Posted: February 14, 2014 | Author: Hilary Mason | Filed under: blog | Tags: data , food | Leave a comment » I spent a few minutes this week putting together a quick script to pull data from the Locu API . [sent-2, score-1.049]

2 Locu has done the hard work of gathering and parsing menus from around the US and has a lot of interesting data (and a good data team ). [sent-3, score-0.51]

3 The API is easy to query by menu item (like “cheeseburger”, my favorite ) and by running my little script I quickly had data for the prices of cheeseburgers in my set of zip codes (the 100 most populated metro areas in the US). [sent-4, score-1.303]

4 I’m a big fan of Pete Warden’s OpenHeatMap tool for making quick map visualizations, and was able to come up with the following: The blue map is the average price of a cheeseburger by zip, with the red one showing the average price of pizza. [sent-5, score-2.133]

5 The most expensive average cheeseburger can be found in Santa Clara, CA, ironically the city currently hosting the Strata data science conference  this week. [sent-6, score-1.1]

6 You can also see some fun words in the pizza topping options:   In this plot, the x-axis is roughly geographic (ordered by zip code) and the y-axis is in order of popularity, with pepperoni being the most popular common pizza topping, and anchovies among the least. [sent-8, score-1.369]

7 This is just a quick look at some data, but hopefully it’ll encourage you to play with your food (data)! [sent-9, score-0.712]


similar blogs computed by tfidf model

tfidf for this blog:

wordName wordTfidf (topN-words)

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