A dashboard built using Plotly-Dash for interactive visualization of Dex-connected individuals across the country.

Overview

Dashboard For The DexConnect Platform of Dexterity Global

Working prototype submission for internship at Dexterity Global Group. Dashboard for real time analysis of data of connected individuals and institutes across the country.

Requirements

  • Python
  • Plotly
  • Dash
  • Flask

How to run

  • Install the dependencies by running the command pip install -r requirements.txt
  • Once dependencies are installed, just run python app.py to see it in your browser.

Features

  • Map to visualize the connected individuals and institutes

  • Demographics and age of connected individuals

  • Data table, gender, institutes

Deployment

  • Azure cloud platform

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Issues
  • Bump numpy from 1.18.5 to 1.22.0

    Bump numpy from 1.18.5 to 1.22.0

    Bumps numpy from 1.18.5 to 1.22.0.

    Release notes

    Sourced from numpy's releases.

    v1.22.0

    NumPy 1.22.0 Release Notes

    NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

    • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
    • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
    • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
    • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
    • A new configurable allocator for use by downstream projects.

    These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

    The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

    Expired deprecations

    Deprecated numeric style dtype strings have been removed

    Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

    (gh-19539)

    Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

    numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

    (gh-19615)

    ... (truncated)

    Commits

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    dependencies 
    opened by dependabot[bot] 0
  • Bump jinja2 from 2.11.2 to 2.11.3

    Bump jinja2 from 2.11.2 to 2.11.3

    Bumps jinja2 from 2.11.2 to 2.11.3.

    Release notes

    Sourced from jinja2's releases.

    2.11.3

    This contains a fix for a speed issue with the urlize filter. urlize is likely to be called on untrusted user input. For certain inputs some of the regular expressions used to parse the text could take a very long time due to backtracking. As part of the fix, the email matching became slightly stricter. The various speedups apply to urlize in general, not just the specific input cases.

    Changelog

    Sourced from jinja2's changelog.

    Version 2.11.3

    Released 2021-01-31

    • Improve the speed of the urlize filter by reducing regex backtracking. Email matching requires a word character at the start of the domain part, and only word characters in the TLD. :pr:1343
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    dependencies 
    opened by dependabot[bot] 0
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