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Accessing the News API in Python

27/01/2021

Accessing and analyzing media content is a fascinating part of data analytics. It allows to follow trends of public interest over time or to see how stories evolve (e.g. newslens ). While many media outlets offer APIs, it is cumbersome to collect them individually. News API closes that gap and allows to search and retrieve live articles from all over the web. In this tutorial we will retrieve the latest news...

Improve your Psycopg2 executions for PostgreSQL in Python

01/06/2020

I’m sure everybody who worked with Python and a PostgreSQL database is familiar or definitely heard about the psycopg2 library. It is the most popular PostgreSQL database adapter for the Python programming language. In my work, I come in contact with this library every day and execute hundreds of automated statements. As always, I try to improve my code and execution speed, because, in the cloud, time is money. The longer your code runs the...

Using Azure Functions with Python

10/05/2020

Overview Lately, I worked a lot with the Azure Cloud. Overall I have to say Azure offers a lot but is still not on the same level as its hardest competitors (AWS, Google). One thing that caught my eye is the compatibility of certain programming languages. Azure supports a few different languages (C#, JavaScript, Java, Python, etc.) but the supported features for these languages differ a lot. I think Azure Cloud is really great for...

Support Vector Machines (SVM) in Python

22/04/2020

Support Vector Machine (SVM) is a widely used supervised learning algorithm for classification and regression tasks. It is mostly exploited for classification problems. The points of different classes are separated by a hyperplane, and this hyperplane must be chosen in such a way that the distances from it to the nearest data points on each side should be maximal. Support Vector Machine has some advantages. The first one is that SVM works...

Ridge and Lasso in Python

26/02/2020

For many machine learning problems with a large number of features or a low number of observations, a linear model tends to overfit and variable selection is tricky. Models that use shrinkage such as Lasso and Ridge can improve the prediction accuracy as they reduce the estimation variance while providing an interpretable final model. In this tutorial, we will examine Ridge and Lasso regressions, compare it to the...

Connecting PostgreSQL to your script (Python)

29/07/2019

Introduction Nowadays PostgreSQL is probably one of the most powerful relational databases among the open-source solutions. Its functional capacities are no worse than Oracle’s and definitely way ahead of the MySQL. So if you are working on apps using Python, someday you will face the need of working with databases. Luckily, Python has quite a wide amount of packages that provide an easy way of connecting and using databases. In this...

Sentiment Analysis of Trump Tweets in Python

09/07/2019

The way other people think about one or another product or service has a big impact on our everyday process of making decisions. Earlier, people relied on the opinion of their friends, relatives, or products and services reposts, but the era of the Internet has made significant changes. Today opinions are collected from different people around the world via reviewing e-commerce sites as well as blogs and social nets. To transform gathered...

Top Python Data Visualization Libraries for Data Science

16/05/2019

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,...

A guide to Exploratory Data Analysis in Python

01/03/2019

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 data. Exploratory data...

OpenFIGI & PermID API: Accessing Financial Market Instruments’ Unique Identifiers in Python

03/01/2019

In financial markets, tradable instruments and securities have unique identifiers. The identifiers are very useful, because you can make sure that you and your counterparty are talking about the same instrument while trading. The difficulty is that there isn't really a standard for all the various sorts of instruments or markets. Anyone working in the industry will recognize this issue, especially people working at larger institutions who...

Random Forest in Python with scikit-learn

12/12/2018

The random forest algorithm is the combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. It can be applied to different machine learning tasks, in particular, classification and regression. Random Forest uses an ensemble of decision trees as a basis and therefore has all advantages of decision trees, such as high accuracy,...

Using Python to access the Bank of England's Statistical Interactive Database (IADB)

17/11/2018

In this we will retrieve data from the Bank of England's Statistical Interactive Database (IADB) using Python 3 . Please take a look at the following sites to get a feel for what kind of data is available: https://www.bankofengland.co.uk http://www.bankofengland.co.uk/boeapps/iadb/ As an , we will take a look at the fixed mortgage interest rates in the UK since the year...

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