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Analysis of the prevalence of undernourishment in Africa and Asia using Python


In this article, I want to visualize the percent of undernourishment using data from the Food and Agriculture Organization of the United Nations (FAO).

The visualization will be done using data about African and Asian continents. In each of the continent, we will also use the world undernourishment statistics across as a baseline reference point.
According to FAO, “The prevalence of undernourishment is an estimate of the proportion of the population whose habitual food consumption is insufficient to provide the dietary energy levels that are required to maintain a normal active and healthy life. It is expressed as a percentage.
Undernourishment means that a person is not able to acquire enough food to meet the daily minimum dietary energy requirements, over a period of one year. FAO defines hunger as being synonymous with chronic undernourishment.”
The data period being used for this analysis covers 2005 to 2017, although
only six data years measurements were available.

For this analysis, I am using a stacked barchart with the prevalence of undernourishment plotted inside each region section. This allows an easy comparison by year and also within year for each of the region.

The analysis of the prevalence of undernourishment in the African continent shows some interesting results:
1. Eastern Africa region shows the highest prevalence of undernourishment. The prevalence dropped by three percentage points in 2005 but has remained slightly above 30% since that.
2. Middle or Central Africa region is the next one with a high prevalence of undernourishment. It has not changed that much since 2010 until 2017.
3. The result from Western seems to be surprisingly low. I expected the prevalence of undernourishment to be much higher.
4. Northern and Southern Africa register much lower numbers of undernourishment. They are both below the World prevalence of undernourishment numbers.

As for Asia is concerned, we can make the following observations:
1. Southern Asia, has the highest prevalence of undernourishment throughout Asia during the entire period. It is much higher than the world statistics.
2. Central Asia has the lowest prevalence of undernourishment in Asia. It’s well below the world prevalence of undernourishment.
3. Western Asia has also a comparatively lower prevalence of undernourishment.

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I have over twenty years of work experience in the field of statistics as an Applied Statistician and a Data Scientist. For the last twelve years, I have also been teaching undergraduate college level statistics courses at St Petersburg College.  As a Data scientist, I have developed over the years a strong interest in computational statistics.  I am also interested in teaching data sciences techniques  to students and those interested in using data sciences techniques in their respective fields.   My programming languages of choice are Python and R.  I am also interested in Spark, Databricks, PySpark.


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