Skip to main content

Data Analysis and Manipulation of Dengue outbreak in Nepal in 2022 using Pandas

Dengue outbreak in Nepal in 2022 was really frightening. A lot of people were infected. That includes my friends and Neighbours as well. In this blog we will analyze the dengue outbreak zones, most infected zones, most infected months and try to find the cause of the outbreak.

Brief Background about Dengue


Dengue is a disease caused by bite of infected Aedes mosquitoes. Common symptoms of Dengue can be mild-severe fever, severe headache, joint and muscle pain, vomiting, skin rash etc. Dengue transmitting Aedes mosquitoes breed on stagnant water. So, we should remove stagnant water around the Neighbour and keep surrounding clean to prevent such diseases.

Data source 

The source of data for this project is taken form Government of Nepal, Ministry of Health and Population, Department of Health Services, Epidemiology and Disease Control Division.


Analysis based on District

According to the provided data, all the 76 district of Nepal has reported the Dengue infection reports. However, we will analyze the central point of the outbreak.       

                                   
It is clear from above chart that highest number of Dengue infection zone is Kathmandu(the capital) followed by Lalitpur, Bhaktapur, Makwanpur, Chitwan, Dang, Dhading. It can be roughly assumed that the outbreak zone was probably Kathmandu. Following highest infected Districts i.e Bhaktapur and Lalitpur which are Neighbour District of Kathmandu.

Analysis Based on Month

Well, above bar chart is quite clear explaining the outbreak months in 2022. This chart shows the number of infected people according to the month in all 76 District. September and October were the month that had highest infected numbers.

The rainy season in Nepal generally lasts from June to September and heaviest rain fall in June and August. Possible reason of outbreak may be stagnant water due to the rainfall and negligence of people to clean such water accumulations in Neighborhood.

Geographical Analysis  

Well, it's quite clear that the outbreak zone was Kathmandu. This can be seen through the geographical map aswell.

Map data(latitude and longitude of Districts) are taken from New chat (openai.com)

                                   




Among the highest infection reported places, most of them are from Provience 3 (Bagmati), where the capital Kathmandu lies.

Conclusion

Hence, we should take care of our surroundings and Neighborhood and keep it clean to prevent such outbreaks.

Code for above analysis

Do leave a star if you find it helpful😊





Comments

Post a Comment

Popular posts from this blog

Docker With PostgreSQL

Brief Introduction to Docker img src Docker is a platform as a service (PaaS) for developing, shipping and running applications in containers. By containers, i mean, a lightweight, portable and self-sufficient unit capable of running applications and their dependencies. It is a runnable instance of a Docker image. Docker container runs inside a host machine but completed isolated from host machine. Importance of Docker img src Some of the importance of docker are highlighted as: Dependency Management As data engineers we work on various pipelines and applications. So, to simplify the dependency and make sure we don't end up with conflict across different environment, it is necessary to encapsulate the dependencies of applications in a container and generate an image for it. Portability Docker containers are portable and can be easily moved between different environments, which makes it simpler to deploy and share pipelines and applications across teams or organizations easily. Envi...
Post a Comment
Read more

Make Automation

We can create a Makefile in Python which helps to automate tasks like running your Python scripts, testing, or building your project.  A Makefile is a file used by the make build automation tool to define a set of tasks that should be executed. Each task is written as a target, and it can depend on other tasks or files. In general, structure of makefile are: Target Dependencies Commands Ok, lets understand this with help of an example. Makefile (has no extensions) # Define variables for system Python and pip for virtual environment SYSTEM_PYTHON = python3 VENV_PYTHON = myvenv/bin/python VENV_PIP = myvenv/bin/pip # Target: venv # Creates a virtual environment in 'myvenv' directory using system Python. venv : $(SYSTEM_PYTHON) -m venv myvenv # Target: install # Installs dependencies if 'requirements.txt' exists. install : venv $(VENV_PIP) install -r requirements.txt; # Target: all # Runs venv, install, and run targets. all : venv install In example above...
Post a Comment
Read more

Pyspark Transformation and Actions

 Pyspark Transformation and Actions RDD Transformation Examples Some of the examples of RDD transformations are: flatmap() map() reduceByKey() filter() sortByKey() RDD Actions Example some of the examples of RDD actions are: count() first() max() reduce() take() collect() lets us understand by code how RDD is fault tolerant, immutable, how lazy evaluation works and also understand its distributed nature. lets define a RDD , while converting a data to RDD, it is not directly loaded in memory, first of all  a lineage graph is made for the data, such that even if any node crashes in future, data can be recreated. This lineage graph helps in fault tolerance by allowing Spark to recreate lost data partitions in case of any reason causing node failure. RDDs are distributed across multiple nodes in a cluster, allowing parallel processing of data records. rdd = sc.parallelize([ 1 , 2 , 3 , 4 , 5 ]) the immutability nature of RDD can be understand such that, notice now we didnt changed...
Post a Comment
Read more