DEV Community: Dion Nekesa

DATA MINING AND VISUALISATION.

Dion Nekesa — Wed, 16 Oct 2024 17:22:22 +0000

***My final lesson at Lux Academy was deeply enriching with knowledge. We started by learning how to write an ideal technical article on platforms such as 'Dev.to' and 'Coderlegion.com' to make the learning journey more captivating. I won't dwell much on this since the book _Technical Writing For Dummies*_ very well explains it.
Now onto the hands-on technical project. We were required to fetch data from weatherapi or openweathermap for different regions in Kenya, store it in a database of our own choice(relational or non-relational), then analyse weather patterns using Python.
I signed up for an account with 'weather_api' then fetched the data using an API key on Google 'Colab', which was my preferred Python notebook, stored my data in a non-relational database with MongoDB then proceeded to Tableau to draw insights from it(the data) using different visualisation features. I chose 'Colab' because it makes it easier to use Python libraries such as 'Pandas' and 'Numpy' by simply using the command 'import' ,besides the fact that you can efficiently save the code to a github repository at the tap of a button. I didn't have to clone the repo on my machine then start running the 'add' ,'commit' and 'push' commands. In my books the visualisation part was supposed to be the simplest but I ended up spending the most time on it, moving from tutorial to tutorial just to understand how I can manipulate my dashboard to look better and meaningful.

I am happy to have completed this three-week Data Analysis and Analytics journey at Lux Tech Academy Kenya and gained so much knowledge. Shout out to my cool tutors: Peter Gatitu, Doreen Wanyama, Elvis Wangari and Harun Mbaabu for the great job done.

The numbers were tough but I was definitely tougher!

INTRODUCTION TO PYTHON FOR DATA ANALYTICS

Dion Nekesa — Mon, 07 Oct 2024 01:33:08 +0000

During an engaging and informative session this week with Lux Tech Academy Kenya,we were taken through a comprehensive introducuction to Python for Data and Analytics.

First thing's first, you'll need to install Anaconda download and launch the Jupyter notebook. Here is a link to download Anaconda/Jupyter Notebooks: Anaconda/Jupyter notebooks installation

I feel like a vessel filled to the brim with a bounty of all this knowledge, from which I will share a few highlights.

Tuples refer to in-built data types which facilitate organisation of data, similar to lists but are more unique. They are defined using parantheses;my_cars= (1,2,3). Tuples represent a fixed collection of items that do not change overtime such as latitudes and longitudes. Unlike lists, tuples are not modifiable;once defined, one cannot change or alter the elements in a tuple.

Python lists also refer to in-built data systems that enable you to organise information in certain categories which are slightly different from tuples. Here is an example of a list of fruits: my_fruits=['mangos','apples','grapes']
Lists can store elements of different data types,their elements are modifiable through the use of functions such as .apend(),.remove()etc and can therefore grow dynamically in the program.

NumPy arrays also provide an efficient way of storing large data sets in Python libraries but differ with lists and tuples in the following ways: They only store elements of the same data type, they use less memory space and do not have looping processes since they support vectorised operations.

There are various processes which handle memory usage in Python, but we will majorly focus on Garbage collection.This reserves memory by removing objects that are no longer needed by programs.

1.Garbage collection can be done through:
Reference Counting: which tracks the number of references pointing to a a particular object in a Python program. When the reference count drops to zero, the memory used by the object is dropped.

2.Cyclic collection: this is similar to the latter but is used in cases where objects reference each other in a cycle.

Lastly,I will shade some light on the functions in an analysis script. A function is a reusable line of code which can be called severally to perform the same task. The basic syntax is:
`def function_name(operation)
code block

describing the function

return valueExample:squared_list=[b**2 for b in range(1,10)]
print(squared_list)`
Output: [1,4,9,16,49,64,81]

Jupyter Notebook is very beginner friendly so I highly recommend it for this.
This is just a tip of the iceberg and I can't wait to learn more in my next class. Knowledge is power, so let's keep learning and building to mould ourselves a better future!

GETTING STARTED WITH SQL AT LUX ACADEMY

Dion Nekesa — Sun, 29 Sep 2024 18:05:26 +0000

Early this week,I embarked on a breathe-taking journey with Lux Academy on Database Management tools such as MySQL, Debeaver and Excel. It all began with a captivating lesson on the basic concepts of Structured Query Language, preferrably known as Sequel or SQL which is used in relational databases.The basic queries being: SELECT, INSERT, UPDATE with clauses: GROUP BY, WHERE, etc which manipulate and retrieve data.

The subsequent assignment made me delve deeper into these concepts to work on a project where, I had to write a script
that queries and sums up sales for a particular product and identifies customers who make more than five purchases in a month. This made me scratch my head a bit and collabo with some associates to crack it up.

The whole experience was awesome and enriching in terms of knowledge and synergy. Can't wait for next week's classes!