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PDF Le Français au pôle Sud / Le Pourquoi-pas ? dans lAntarctique (CLASSIQUES ARTH) (French Edition)

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Two days ago, in my post to extract automatically my own tweets, and to generate some html list, I mentioned that it would be great if there were a function that could be used to distinguish tweets in English, and tweets in French usually, I tweet in one of those two languages. And one more time, 3wen came to rescue me!

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In my previous post, I spent some time to extract mentions to other twitter accounts, and urls. This time, I have to remove those two informations, that are not relevant to get the language of a tweet. There were stats about first names, in the U. Those informations are — somehow — easy to get. But usually, it is more complicated to get the first and the last name together.

For confidentiality issues! Datasets — the ones I deal with — are supposed to be anonymized, so I never see the first and the last names. In that file, we have Social Security numbers, with the date of birth, the date of death as well as the first and the last name. So I did use those files to get stats about the first and the last names of American citizens.

Of course, it is very restrictive. I have only U. Another great thing about that dataset is that I have the date of birth, so I can look at some cohort effect see opendata. Continue reading Names in the U.

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Recently, with 3wen , we wanted to play with isodensity curves. The problem is that it is difficult to get — numerically — the equation of the contour even if we can easily plot it. Consider the following surface just for fun, in order to illustrate the idea. For instance, assume that we want to locate areas where the density exceed 0. The idea of the method was theoretical and difficult to implement. We provide a simple technique — based of properties of Gaussian kernels — to efficiently compute weights to correct border bias on frontiers of the region of interest, with an automatic selection of an optimal radius for the method.

We illustrate the use of that technique to visualize hot spots of car accidents and campsite locations, as well as location of bike thefts. Et comme souvent, Philippe a raison. The idea of the method was theoretical and di cult to implement. We provide a simple technique — based of properties of Gaussian kernels — to compute e efficiently weights to correct border bias on frontiers of the region of interest, with an automatic selection of an optimal radius for the method.

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An illustration on location of bodily-injury car accident and hot spots in the western part of France is discussed, where a lot of accident occur close to large cities, next to the sea. Sketches of the R code can be found in the paper, to produce maps, an to describe the impact of our boundary correction. The code is the same as the one mentioned last year , except perhaps plotting functions. First, one needs to defi ne a color scale and associated breaks.

Now, if one wants to improve the aesthetics of the map, by adding a Google Maps base map, the first thing to do — after loading ggmap package — is to get the base map. Elle regroupe Etats-membre. Rendez-vous sur www.


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    1130 km seul à travers l'Antarctique, Matthieu Tordeur "Objectif Pôle Sud"

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