Tag: plotly
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Python Data Science for Real Estate & REIT Amsterdam: (Auto) EDA, NLP, Maps & ML
The Amsterdam real estate market has experienced a significant resurgence, with property prices increasing by double digits annually since 2013. Data science is being used to analyze the city’s housing and rental markets, revealing insights on the impact of Airbnb and empowering communities with the necessary information. Comprehensive data analysis and machine learning techniques are…
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Weather Forecasting & Flood De-Risking using Machine Learning, Markov Chain & Geospatial Plotly EDA
Foto door Pok Rie Scope: Business Value: Table of Contents U.S.A. Weather Forecast Australian Rainfall Prediction Kerala Flood Prediction Squares are categorical associations (uncertainty coefficient & correlation ratio) from 0 to 1. The uncertainty coefficient is asymmetrical, (i.e. ROW LABEL values indicate how much they PROVIDE INFORMATION to each LABEL at the TOP). • Circles are the symmetrical numerical…
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Hugging Face NLP, Streamlit, PyGWalker, TF & Gradio App
Table of Contents Streamlit/Dash/Jupyter PyGWalker EDA Demo PyGWalker and Dash — Creating a Data Visualization Dashboard In Less Than 20 Lines of Code PyGWalker Test PyGWalker Tutorial: A Tableau-Like Python Library for Interactive Data Exploration and Visualization PyGWalker: A Python Library for Visualizing Pandas Dataframes You’ll Never Walk Alone: Use Pygwalker to Visualize Data in…
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Plotly Dash TA Stock Market App
The post explains how to deploy a Plotly Dash stock market app in Python with the dashboard of user-defined stock prices. This includes technical indicators like volume, MACD, and stochastic. The steps include selecting a stock ticker symbol (NVDA), retrieving stock data from yfinance API, adding Moving Averages, saving the stock chart in HTML form,…
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Returns-Volatility Domain K-Means Clustering and LSTM Anomaly Detection of S&P 500 Stocks
This study aims to implement and evaluate the K-means algorithm for ranking/clustering S&P 500 stocks based on average annualized return and volatility. The second goal is to detect anomalies in the best performing S&P 500 stocks using the Isolation Forest algorithm. Additionally, anomalies in the S&P 500 historical stock price time series data will be…
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Morocco Earthquake EDA
Featured design via Canva. Clickable Table of Contents Basic Installations and Imports Let’s set the working directory YOURPATH Let’s install and import the following libraries Download Earthquake Input Data For this project, we’ll use a dataset that contains all seismic events over the last seven days, which have a magnitude of 1.0 or greater: Output:…
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Datapane Stock Screener App from Scratch
This content provides a quick guide for value investors to use the Datapane stock screener API in Python. It includes instructions for installation, importing standard libraries, setting the stock ticker, downloading stock Adj Close price, and creating visualizations. The post also describes how to build a powerful report using Datapane’s layout components.
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Video Game Sales Data Exploration
The post explores the gaming industry’s size and state, highlighting a potential market value of $314bn by 2027. It emphasizes the industry’s three main subsectors: console, PC, and smartphone gaming. Moreover, the post conducts extensive data analysis on video game sales data, using Python to examine aspects such as genre profitability, platform sales prices, and…
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NETFLIX Interactive Visualization with Plotly
This project implements Python-3 EDA, streaming data visualization, and interactive Plotly UI to review Netflix movies and TV shows. It aims to understand content availability in different countries, identify similar content, and analyze the focus on TV shows vs. movies. The Kaggle Netflix dataset details TV shows and movies available on the platform. Netflix is…
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COVID-19 Data Visualization, Impact and Vaccine Sentiment Analysis
The coronavirus COVID-19 pandemic is the defining global health crisis of our time and the greatest challenge we have faced since World War Two. After over two years of living with Covid-19, we are learning to adapt to a world with this disease. 2022 ends with looming risk of a new coronavirus variant, health experts…
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Interactive Global COVID-19 Data Visualization with Plotly
COVID-19, caused by SARS-CoV-2 virus, has affected 227.2 million people and caused 4,672,629 deaths. The disease, first reported in Wuhan, has spread globally. Data visualization tools like Plotly and analysis of Kaggle datasets provide insights into the pandemic’s impact, with the US leading in confirmed cases and deaths. China has managed to control the spread.
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The $ASML Trading Strategies via the Plotly Stock Market Dashboard
Dr. Dividend has shared an insight into a stock market analysis using Plotly’s interactive Stock Market Dashboard. The rundown explains how to fetch live data using yfinance API, create visuals incorporating moving averages, and craft multiple trading signals, including the use of the MACD and Stochastic Oscillator. The tutorial also guides on saving the final…
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