Showing 4 open source projects for "analysis"

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  • 1
    Panda-Helper

    Panda-Helper

    Panda-Helper: Data profiling utility for Pandas DataFrames and Series

    Panda-Helper is a simple data-profiling utility for Pandas DataFrames and Series. Assess data quality and usefulness with minimal effort. Quickly perform initial data exploration, so you can move on to more in-depth analysis.
    Downloads: 1 This Week
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  • 2
    Data Preprocessing Automate

    Data Preprocessing Automate

    Data Preprocessing Automation: A GUI for easy data cleaning & visualiz

    ...It allows users to upload Excel files, automatically handle missing values, remove duplicates, and detect and remove outliers using statistical methods. The application provides data visualization tools, including box plots for distribution analysis and scatter plots for exploring relationships between variables. Users can download the processed data for further analysis. Built with Tkinter, Pandas, Matplotlib, and Seaborn, it ensures an intuitive interface and efficient performance. Additionally, it features a custom logo, a clean UI with a green-blue theme, and options for licensing and public release. ...
    Downloads: 0 This Week
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  • 3
    Swiple

    Swiple

    Swiple enables you to easily observe, understand, validate data

    Swiple is an automated data monitoring platform that helps analytics and data engineering teams seamlessly monitor the quality of their data. With automated data analysis and profiling, scheduling and alerting, teams can resolve data quality issues before they impact mission critical resources. Experience hassle-free integration with Swiple's zero-infrastructure and zero-code setup. Seamlessly incorporate data quality checks into your existing workflows without any coding or infrastructure changes, allowing you to focus on what matters most - your data. ...
    Downloads: 0 This Week
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  • 4
    NYCOpenData-Profiling-Analysis

    NYCOpenData-Profiling-Analysis

    Open Data Profiling, Quality and Analysis on NYC OpenData dataset

    Open data often comes with little or no metadata. You will profile a large collection of open data sets and derive metadata that can be used for data discovery, querying, and identification of data quality problems. For each column, identify and summarize the semantic types present in the column. These can be generic types (e.g., city, state) or collection-specific types (NYU school names, NYC agency). For each semantic type T identified, enumerate all the values encountered for T in all...
    Downloads: 0 This Week
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