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How Python Can Be Your Secret Weapon As a Data Scientist

Python is highly versatile and one of the most advanced programming languages in the world. There are tons of reasons why Python is getting extremely popular these days. Many experts consider it as one of the first choices in industries coming to programming languages. 

Also, there have been many sayings about Python that the development of future technologies will solely rely on it. Technologies that include Data Science, AI, ML will take the driver seat to combine with Python. By adding more and more easiness in deep-driven research purposes and better product development.

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Top 10 Python Libraries You Must Know in 2019

In this article, we will discuss some of the top libraries in Python that can be used by developers to prase, clean, and represent data and implement machine learning in their existing applications.

We will be considering the following 10 libraries:

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Bulk Geocode Addresses Using Google Maps and GeoPy

Geocoding is the process of converting addresses (like a street address) into geographic coordinates (like latitude and longitude). With Woosmap you can request nearby location or display on a map a lot of geographic elements like stores or any other point of interest. To take advantages of these features, you first have to push geocoded locations to our system, as we discussed in this previous post. Most of the time, your dataset has addresses but no location information.

The following script, hosted on our Woosmap Github Organization, is a basic utility for geocoding CSV files that have address data included. It will parse the file and add coordinate information as well as some metadata on geocoded results like the location type, as discussed below. It calls the Geocoding API through the GeoPy Python client.