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Among the variety of open source relational databases, PostgreSQL is probably one of the most popular due to its functional capacities. That is why it is frequently used among all the areas of work where databases are involved. In this article, we will go through connection and usage of PostgreSQL in R. R is an open source language for statistical and graphics data analysis providing scientists, statisticians, and academics powerful tools...
What is Exploratory Data Analysis Exploratory data analysis (EDA) is a powerful tool for a comprehensive study of the available information providing answers to basic data analysis questions. What distinguishes it from traditional analysis based on testing a priori hypothesis is that EDA makes it possible to detect — by using various methods — all potential systematic correlations in the...
Introduction Exploratory data analysis (EDA) is an approach to data analysis to summarize the main characteristics of data. It can be performed using various methods, among which data visualization takes a great place. The idea of EDA is to recognize what information can data give us beyond the formal modeling or hypothesis testing task. In other words, if initially we don’t have at all or there are not enough priori ideas about...
In the modern world, the information flow which befalls on a person is daunting. This led to a rather abrupt change in the basic principles of data perception. Therefore visualization is becoming the main tool for presenting information. With the help of visualization, information is presented to the audience in a more accessible, clear, visual form. Properly chosen method of visualization can make it possible to structure large data arrays,...
The more carefully you process the data and go into details, the more valuable information you can get for your benefit. Data visualization is an efficient and handy tool for gaining insights from data. Moreover, you can make the data far more understandable, colorful and pleasant with the help of visualization tools. As data is changing every second, it is an urgent task to investigate it carefully and get the insights as fast as...
In this Jupyter Notebook we will retrieve data from the European Central Bank (ECB). The ECB publishes through the European Open Data Portal, which we discussed in the previous tutorial . Before diving into the code, please take a quick look at the following websites, to get a feel for what we will be dealing with. EU portal: https://data.europa.eu/euodp/en/data/publisher/ecb ECB SDMX 2.1 RESTful web...
Are you looking for real world data science problems to sharpen your skills? In this post, we introduce you to four platforms hosting data science competitions. Data science competitions can be a great way for gaining practical experience with real world data, and for boosting your motivation through the competitive environment they provide. Check them out, competitions are a lot of fun! Kaggle Kaggle is the best known platform...
Companies use machine learning to improve their business decisions. Algorithms select ads, predict consumers’ interest or optimize the use of storage. However, few stories of machine learning applications for public policy are out there, even though public employees often make comparable decisions. Similar to the business examples, decisions by public employees often try to optimize the use of limited resources. Algorithms may assist...
Curious about neural networks and deep learning? This post will inspire you to get started in deep learning. Why are we witnessing this kind of build up for neural networks? It is because of their amazing applications. Some of their applications include image classification, face recognition, pattern recognition, automatic machine translation, and so on. So, let’s get started now. Machine Learning is a field of computer science that...
The open-source project R is among the leading tools for data science and machine learning tasks. Given its open-source framework, there are continuous contributions and new package libraries with new features pop up frequently. Currently, the CRAN package repository features 12,525 available packages. This post takes a look at the most popular and useful packages that have set the standards for solving data manipulation, visualization, and...
  Currently, Python and R are the dominating data science tools and Python will probably even be taking the lead (at least based on the latest KDNuggets survey ). When did the two open source players manage to become the leading platforms for analytics, data science, and machine learning, leaving behind established players such as Matlab or SAS? Here are some insights from Google Trends. Looking at the years 2009 - 2013 in the...
Mobile phone data has a vast scope. Our phones track our location, record social activities by listing who we call or message, and know what we like or what we’re looking for by collecting data on our online behavior and use of apps. The recent Mobile User Demographics Challenge on Kaggle (by the Chinese platform TalkingData ) offers some insight into the volume and precision of the information available on mobile...