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Human Centered Visual Analytics Seoul Bike Data.pdf (432432, 2023-02-17)
Seoul_Bike_Data_EDA.ipynb (1769651, 2023-02-17)

# human-centered-visual-analytics Source: Data Source :http://data.seoul.go.kr/ SOUTH KOREA PUBLIC HOLIDAYS. URL: publicholidays.go.kr Data Set Information: Currently Rental bikes are introduced in many urban cities for the enhancement of mobility comfort. It is important to make the rental bike available and accessible to the public at the right time as it lessens the waiting time. Eventually, providing the city with a stable supply of rental bikes becomes a major concern. The crucial part is the prediction of bike count required at each hour for the stable supply of rental bikes. The dataset contains weather information (Temperature, Humidity, Windspeed, Visibility, Dewpoint, Solar radiation, Snowfall, Rainfall), the number of bikes rented per hour and date information. Attribute Information: Date : year-month-day Rented Bike count - Count of bikes rented at each hour Hour - Hour of he day Temperature-Temperature in Celsius Humidity - % Windspeed - m/s Visibility - 10m Dew point temperature - Celsius Solar radiation - MJ/m2 Rainfall - mm Snowfall - cm Seasons - Winter, Spring, Summer, Autumn Holiday - Holiday/No holiday Functional Day - NoFunc(Non Functional Hours), Fun(Functional hours) Libraries Used: Python Altair Related Topics: Human Centered Visual Analytics, Interactive visualization, Altair visualization, Exploratory Data Analysis Objective: The objective of this project is to use Python's Altair library to create interactive visualizations that provide optimal human-centered exploratory data analysis of the Seoul Rental Bike dataset. Through these visualizations, the project aims to explore the patterns and trends in the data, identify insights into the usage of rental bikes in Seoul, and communicate these findings in a clear and accessible manner. By doing so, the project seeks to support decision-making related to bike-sharing services in Seoul and to demonstrate the value of human-centered data analysis in promoting data-driven decision-making.

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