Introduction Welcome to the exciting world of Forex trading! While it can be thrilling, it’s important to recognize that Forex trading isn’t easy. Success in today’s market requires the ability to test strategies, automate trading, and access crucial information efficiently. In this project, we’ll be provided with the foundation to thrive in the Forex market. We’ll be using the Oanda API service, a powerful tool available in most countries worldwide. This project will require us to: Build a live trading bot Develop a fast and accurate strategy testing system Retrieve live market data including headlines, sentiments, and technicals Utilize databases to store and analyze market data Create a web application displaying real-time market information Master full-stack development using MongoDB, Python, and JavaScript (with React) We’ll kickstart our journey by learning how to use Python to access the Oanda REST API. From there, we’ll dive into strategy testing, backtesting, and automation.…
Below is a dataset with single bets made by gambling customers. Our task is to aggregate them into sessions, group sessions into length groups…
As part of the Safer Gambling initiative, it is important to make sure customers do not gamble above their financial means. One of the…
Introduction ? You’re a marketing analyst and you’ve been told by the Chief Marketing Officer that recent marketing campaigns have not been as effective…
Introduction The dataset that we will be wrangling (and analyzing and visualizing) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs.…
Table of Contents ? IntroductionStep 1: Importing LibrariesStep 2: Gathering DataStep 3: Univariate ExplorationStep 4: Bivariate ExplorationStep 5: Multivariate ExplorationStep 6: Random ExplorationStep 7:…
Women from ethnic minorities have a strong presence in London. We can use data to find which areas they preside in as they could…
The Program for International Student Assessment (PISA) is a system of international assessments that allows countries to compare outcomes of learning as students near the end of compulsory schooling. PISA core assessments measure the performance of 15-year-old students in mathematics, science, and reading literacy every 3 years.
This project is a data wrangling project, which mainly focus on fixing the data quality and tidiness issues using python. The dataset that I am wrangling is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs.