In a previous tutorial, we saw how a database and table can be created in mySQL. Here is how you can run this on a local machine with the mySQL Installer and mySQL Workbench.

Continue reading »# How To Create a Twitter App and API Interface Via Python

This tutorial illustrates how to use a Python API to connect to a Twitter account using the Twitter library. Specifically, this API allows a user to extract high quantities of data pertaining to a specific Twitter account, as well as […]

Continue reading »# ARIMA Models: Stock Price Forecasting with Python and R

ARIMA (Autoregressive Integrated Moving Average) is a major tool used in time series analysis to attempt to forecast future values of a variable based on its present value. For this particular example, I use a stock price dataset of Johnson […]

Continue reading »# PostgreSQL Databases: Connect To R and Python

PostgreSQL is a commonly used database language for creating and managing large amounts of data effectively. Here, you will see how to: create a PostgreSQL database using the Linux terminal connect the PostgreSQL database to R using the “RpostgreSQL” library, […]

Continue reading »# Creating functions and using lapply in R

Functions are used to simplify a series of calculations. For instance, let us suppose that there exists an array of numbers which we wish to add to another variable. Instead of carrying out separate calculations for each number in the […]

Continue reading »# Creating maps in R and analysing traffic patterns with geolocation

Here is how we can use the maps, mapdata and ggplot2 libraries to create maps in R.

Continue reading »# K-Means Clustering: Analysing City of London Traffic

A K-Means Clustering algorithm allows us to group observations in close proximity to the mean. This allows us to create greater efficiency in categorising the data into specific segments. In this instance, K-Means is used to analyse traffic clusters across […]

Continue reading »# OLS and Logistic Regression Models in R

We use linear models primarily to analyse cross-sectional data; i.e. data collected at one specific point in time across several observations. We can also use such models with time series data, but need to be cautious of issues such as […]

Continue reading »# Cross-Correlation of Currency Pairs In R (ccf)

When working with a time series, one important thing we wish to determine is whether one series “causes” changes in another. In other words, is there a strong correlation between a time series and another given a number of lags? […]

Continue reading »# Chow Test For Structural Breaks in Time Series

A Chow test is designed to determine whether a structural break in a time series exists. That is to say, a sharp change in trend in a time series that merits further study. For instance, a structural break in one […]

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