Drop out analysis

TITLE: Drop out analysis in government schools.
ABOUT:
It is all about analysing the dropouts in government schools and so can make data visualization of it and spread awareness about the top most dropouts in various states so that they realise and will try to decrease it.
GENERAL REASONS BEHIND IT:
Financial problems, parents’ unwillingness, distance and lack of basic facilities, bad quality of the education, inadequate school environment and building, overloaded class rooms, improper languages of teaching, carelessness of teachers and security problem in girls school are found as major causes of student dropouts…
REQUIREMENTS:
-> past data of dropouts
->geo pandas
->bottle framework

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How are you going to solve these?
Are you representing the data somewhere on webapp/UI?

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We thought to build web app using bottle framework for the data visualization for analysis

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Ok
You already mentioned a lot of reasons here.
How are you going to make sure they are solved ?

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How far is your idea executed till now? I hope it is going on well. As per my knowledge the data collected by your team is a bit limited one ans it will have more impact when you go to an area and do survey.

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Yes we have the limited data so we will see to it that we gather some more data.

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Actually earlier we thought to predict the future reasons that made more impact to dropouts so that we can make sure that specific problem is solved by giving awareness to government and people. But later we ended up with less data so now we are thinking to just visualise the data and analyse and give a little awareness about dropout rates in various years by representing it in bottle

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