Preparations are well underway for the 2018 edition of Data Natives– the data driven conference of the future, hosted in Dataconomy’s hometown of Berlin. Data Natives brings together a global community of data-driven pioneers to explore the technologies that are shaping our world- from big data to blockchain, from AI

Introduction A couple of months ago a client of mine asked me the following question: “What is the faster data structure object in Python for Big Data analysis today?” I get questions like this one all the time. Some of them are not easy to solve at all and it

This article is part of a media partnership with PyData Berlin, a group helping support open-source data science libraries and tools. To learn more about this topic, please consider attending our fourth annual PyData Berlin conference on June 30-July 2, 2017. Matti Lyra and other experts will be giving talks

This is the continuation of the Frequency Distribution Analysis using Python Data Stack – Part 1 article. Here we’ll be analyzing real production business surveys for your review. Application Configuration File The configuration (config) file config.py is shown in Code Listing 3. This config file includes the general settings for

During my years as a Consultant Data Scientist I have received many requests from my clients to provide frequency distribution reports for their specific business data needs. These reports have been very useful for the company management to make proper business decisions quickly. In this paper I would like to

Ajit Jaokar is a leading expert working at the intersection of Data Science, IoT, AI, Machine Learning, Big Data, Mobile, and Smart Cities. He teaches IoT and Data Science at Oxford and also is a director of Smart Cities Lab in Madrid. Ajit’s work involves applying machine learning techniques to

Social networks, in one form or another, have existed since people first began to interact. Indeed, put two or more people together and you have the foundation of a social network. It is therefore no surprise that, in today’s Internet-everywhere world, online social networks have become entirely ubiquitous. Within this

Katharine Jarmul and Data Natives are joining forces to give you an amazing chance to delve deeply into Python and how to apply it to data manipulation, and data wrangling. By the end of her workshop, Learn Python for Data Analysis,  you will feel comfortable importing and running simple Python analysis on your

During one of our data-munging sessions here at Coralogix, we found ourselves needing to assess the cardinality of large data sets. Getting the accurate result is seemingly trivial: you simply iterate over the data, and count the number of unique elements. In reality, however, the task is more troublesome, mainly

Choosing the right language for data analysis can be almost as complicated as actually learning the language. For many reasons, R and Python are two of the most popular: R is often praised for its great features for data visualization, as it was developed with statisticians in mind; plenty of programmers love multi-purpose Python for its so-simple-a-child-could-do-it syntax. Why