Requesting Crypto Price Data from the REST API in Python

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In this tutorial, we will demonstrate how to use the spot market API to stream cryptocurrency prices in real-time using Python. Streaming prices is crucial for implementing use cases such as analyzing an incoming stream of price data in real-time for generating trading signals or conducting price analytics. One of the benefits of using … Read more

Posting Tweets On Twitter using Python and Tweepy

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In a previous article, we have shown how to retrieve social media data via the Twitter API in Python. However, we can do many more cool things with the Twitter API. Another cool thing is interacting with the Twitter user account and posting automated tweets. This article shows how this works. We will use the … Read more

Requesting Crypto Prices from the Coinmarketcap API using Python

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You can do various things with cryptocurrency price data, such as creating forecasting models, illustrating historical prices, or performing chart analysis. But first, you need to get hold of the data. Nowadays, several APIs provide access to cryptocurrency price data. One of the most important and trusted sources is The website offers multiple API … Read more

Color-Coded Cryptocurrency Price Charts in Python

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Are you intrigued by the fascinating world of cryptocurrency and looking to visually decipher its price trends? Welcome aboard! In this comprehensive tutorial, we will explore creating color-coded line charts using Python and Matplotlib, a powerful tool for effective analysis of changes along a third dimension. The past few years have witnessed a meteoric rise … Read more

Streaming Tweets and Images via the Twitter API in Python

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Twitter is a rich source of data that can be used to understand current and future trends. Because tweets often include hashtags, they can be easily linked to specific contexts such as political discussions or financial instruments. This makes Twitter a valuable tool for collecting and analyzing data. In this article, we’ll demonstrate how to … Read more

Mastering Multivariate Stock Market Prediction with Python: A Guide to Effective Feature Engineering Techniques

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Are you interested in learning how multivariate forecasting models can enhance the accuracy of stock market predictions? Look no further! While traditional time series data provides valuable insights into historical trends, multivariate forecasting models utilize additional features to identify patterns and predict future price movements. This process, known as “feature engineering,” is a crucial step … Read more

Measuring Regression Errors with Python

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Evaluating performance is a crucial step in developing regression models. Because regression models return continuous outputs, such models allow for different gradations of right or wrong. Therefore, we measure the deviation between predictions and actual values in numerical terms. However, a universal metric to measure the performance of regression models does not exist. Instead, there … Read more

Rolling Time Series Forecasting: Creating a Multi-Step Prediction for a Rising Sine Curve using Neural Networks in Python

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Many time forecasting problems can be solved by predicting just one step into the future. However, some problems require a forecast for an extended period of time, which calls for a multi-step time series forecasting approach. This approach involves modeling the distribution of future values of a signal over a prediction horizon. In this article, … Read more

Correlation Matrix in Python: How Correlated are COVID-19 Cases and Different Financial Assets?

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Correlation analysis is a powerful tool in financial market analysis, helping investors to better understand the interdependence of different assets. But what happens when an unprecedented global pandemic like COVID-19 shakes up the market? In this tutorial, we will show you how to create a correlation matrix in Python that will help you visualize the … Read more

Accessing Remote Data Sources via REST APIs in Python

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REST APIs provide straightforward access to remote data sources. Data scientists should learn about REST APIs because APIs (Application Programming Interfaces) are an important way for data scientists to access data from other sources. By using REST APIs, data scientists can access data from a wide range of sources, including databases, web services, and other … Read more