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Results of the analysis added

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Description of the result of the analysis of the data agent added, as well as some small additions like a table of contents and links to data on activity in the repository.

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  1. README.md +62 -0
README.md CHANGED
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  <div align="center">
 
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  <h1>
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  <a href="https://www.nexdatawork.io/blank">
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  NexDatawork
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  <h2>
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  An AI tool for data analysis without writing code
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  </h2>
 
 
 
 
 
 
 
 
 
 
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  </div>
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  A data agent designed for data analysis specified for particular tasks, quick visualisation and built for adapting for specific requirenments.
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  ## Features
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  - Display of reasoning
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  Sign up with your Gmail, Microsoft account or create a new one on the website.
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  ### Upload your data
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  Choose the **Data Upload** menu and choose a csv file from your computer or drag and drop it in the menu.
 
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  ### Specify what you expect from the result
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  In the windows below choose an **industry**, **topic** and **requirenments** for better results. You can add comments in a seperate window.
 
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  ### Receive the analysed data
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  In the **Data brain** tab you can see the summary, insights and description of the data.
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  In the **Chat** tab you can ask the bot about the details of the data.
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  <div align="center">
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  <h1>
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  <a href="https://www.nexdatawork.io/blank">
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  NexDatawork
 
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  <h2>
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  An AI tool for data analysis without writing code
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  </h2>
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+ <div align='center'>
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+ <a href="https://github.com/NexDatawork/data-agents/graphs/commit-activity"><img alt = "commit activity" src = "https://img.shields.io/badge/commit_activity-blue"/></a>
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+ <a href="https://github.com/NexDatawork/data-agents/issues"><img alt = "issues" src = "https://img.shields.io/badge/issues-blue"/></a>
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+ <a href="https://github.com/NexDatawork/data-agents/pulls"><img alt = "pull requests" src = "https://img.shields.io/badge/pull_requests-blue"/></a>
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+ <a href="https://github.com/NexDatawork/data-agents/blob/main/LICENSE"><img alt = "LICENSE" src = "https://img.shields.io/badge/license-blue"/></a>
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+ </div>
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  </div>
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  A data agent designed for data analysis specified for particular tasks, quick visualisation and built for adapting for specific requirenments.
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+ ## Table of contents
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+ * [Features](##Features)
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+ * [Workflow](##Workflow)
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+ * [Results](##Results)
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  ## Features
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  - Display of reasoning
 
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  Sign up with your Gmail, Microsoft account or create a new one on the website.
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  ### Upload your data
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  Choose the **Data Upload** menu and choose a csv file from your computer or drag and drop it in the menu.
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  ### Specify what you expect from the result
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  In the windows below choose an **industry**, **topic** and **requirenments** for better results. You can add comments in a seperate window.
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  ### Receive the analysed data
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  In the **Data brain** tab you can see the summary, insights and description of the data.
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  In the **Chat** tab you can ask the bot about the details of the data.
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+ ## Results
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+ After the analysis is completed the results are received in two tabs: **Data Brain** and **Dashboard**.
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+ ### Data Brain
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+ General overview of the data is presented as well as the methodology of approaching the dataset which involves:
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+ * determining missing values and erroneous values as well as analyzing columns
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+ * determining typical metrics and patterns according to the chosen requirenments
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+ * analyzing patterns, such as peak values, popular items and more
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+ * deriving insights from the data
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+ * creating recommendations
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+ Afterwards, recommendations on possible aspects of the data are generated:
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+ * recommendations on dealing with missing values
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+ * recommendations on using trends and prominent items for your advantage
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+ * recommendations on what data to focus on
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+ Finally, a conclusive overview of the data and statistical insights are presented, such as:
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+ * Number of total data points
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+ * Data quality
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+ * Variable types
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+ * Distribution of numerical, categorical and temporal variables with specified columns
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+ ### Dashboard
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+ Brief overview of the data with only the most important metrics and figures, such as:
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+ * file information
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+ * number of columns of each type (numerical, categorical and temporal)
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+ * data quality and statistical summary
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+ Brief overview is followed by analysis summary with a rundown of trends needed to derive conclusions from the data based on the user requirenments and recommendations.
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+ Finally, graphs of the most important variables are presented.
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+ ## Contributing
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+ ## License
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+ This project is licensed under [the Apache-2.0 license](LICENSE).
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