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Results from the DataKind DataDive #TeamNdizi which is scraping price data from the web for developing countries.

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#TeamNdizi: Scraping global food prices and consumption data

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We are #TeamNdizi (banana in Swahili) in DC at the DataKind World Bank DataDive on March 16, 2013 scraping food prices from websites around the world.

Here's the link to our hackpad.

##Banana

We started our day by scraping crowdsourced banana prices from here. We wrote a scraper here and made the below price visualization by continent. After this, 4 people, new to scraping, set off to write their own scrapers.

Alt text Our data is also posted in the banana directory.

##Africa (especially Kenya)

We scraped the mfarm data from Kenya. This is SMS data sent to kenyan farmers to help them know prices in different markets. We have repurposed these "data exhaust" which can now be visualized like the below:

###This is a placeholder for a custom data interactive... stay tuned.. Alt text

For more on mfarm, see our mfarm directory.

Here is a map with average Maize prices by market over the last 60 days.

We copied/pasted & learned to scrape consumption data from websites in Uganda, Kenya, Tanzania, and Ethiopia. We also looked at some data from South Africa.

![Alt text](/africa/East Africa vs USA.png) ![Alt text](/africa/South Africa diet price.png) ![Alt text](/africa/South Africa Price Data Source Comparison.png) ![Alt text](/africa/Urban vs National Daily Diet Cost.png)

Our data is in this Google Spreadsheet and some data is also posted in the africa directory. A scraper for numbeo Uganda is here.

##Indonesia

We also scraped rice prices from twitter and the carrefour indonesia website. We even used the way-back machine to scrape older price data from carrefour.

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Our data is also posted in the indonesia directory. The scraper is here.

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