Tag archives: scrapping

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Identifying new shop implantation thanks to geo-data analysis

In this blog, we will see how we can perform geospatial data analysis in order to identify new business opportunities.  For this showcase, we will focus on the retail sector and more precisely on the supermarket leading brands in Belgium: Colruyt, Delhaize, Carrefour, and Lidl.  We analyzed the location of supermarkets in Brussels, computed the average time travel to the closest supermarket for Brussels neighborhood and see how these four major brands are sharing their market zone among Brussels neighborhood accordingly.  We are reusing the techniques detailed in the Dynamic Web scrapping blog post.  The techniques described in this post can be useful for all sorts of B2C companies involved in the retail sector, where competition is generally strong and shop implantation matters. ...

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Scrapping social data from Facebook

Nowadays, social networks can be considered as a main source of data.  This is particularly true for business to customer companies which must take into account customer feedback on their products.  In this blog, we will show how to retrieve information from Facebook using the Facebook Graph API... ...

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Scrapping land invest data from dynamic web

In a previous blog post, we have seen how to mine information on static web pages.  In this blog post, I'll explain how we can do the same on dynamically (i.e. javascript) generated web pages.  As a showcase, I will show you how to find the best land investment you can make in Belgium today... ...

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Scrapping movie data from static web

Every data science journey starts by aggregating the data of interest.  In the industry sector, those are often coming directly from sensors, user surveys, software or application used by your customers.  Nonetheless, the information publicly available on the web still remain an important source of additional information like news, weather or even geographical addresses.  Today, we will focus on movie data... ...