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🎯 Worldwide study to address clean drinking water challenges and support NGOs' missions - use of Python, JupyterLab and Tableau (Background research, Data preprocessing, Cleaning, and Data Visualization)

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Global drinking water study


The datasets are coming from the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO).


Tableau Logo

They were preprocessed and cleaned with Python and then visualized with Tableau :
https://public.tableau.com/app/profile/zofiaqlt/viz/Eaupotabledanslemonde/Aspectmondial

Addressing global clean water challenges through strategic funding allocation

The access to clean drinking water remains a major challenge in many regions of the world.

According to the World Health Organization (WHO), approximately 2.2 billion people worldwide lack access to safe drinking water, and 4.2 billion people do not have access to basic sanitation facilities. This situation is particularly concerning in developing countries where access issues are often linked to factors such as poverty, war, corruption, population growth, and climate change.

The consequences of this situation are severe and varied, leading to diseases, loss of productivity, population displacement, and armed conflicts. In many countries, limited access to clean water also hampers the development of education, the economy, and the protection of the environment.

Given these challenges, the implementation of policies, technologies, and projects to ensure access to clean water is essential to guarantee sustainable development and foster socio-economic advancement for the most vulnerable populations.

The accompanying dashboard aims to facilitate the identification of countries in need and to aid non-governmental organizations (NGOs) to effectively allocate fundings.

It focuses on three areas of expertise:

  1. Establishing access to clean water services
  2. Upgrading existing water access services
  3. Consulting with administrations/governments regarding water access policies
Capture d’écran 2023-07-05 à 16 03 50 Capture d’écran 2023-07-05 à 15 53 30 Capture d’écran 2023-07-05 à 15 56 28 Capture d’écran 2023-07-05 à 15 59 42

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🎯 Worldwide study to address clean drinking water challenges and support NGOs' missions - use of Python, JupyterLab and Tableau (Background research, Data preprocessing, Cleaning, and Data Visualization)

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