It’s been awhile since I’ve updated my blog! Wanted to provide a brief update on my career transition from Data Analytics to Private Equity since Oct 2022. It’s not a major transition since I’m still in the real estate space, but I’ve moved on from a pure “analytics & data” role. Currently taking on a dual function role mainly focused on Asset Management in Asia Pacific with a dotted line reporting to the Portfolio Management - Global Data Analytics function. It’s been almost 2 years already and I’m still enjoying my work in Private Equity Real Estate so far!

Is your main form of private transport in Singapore by car? Are you a regular driver in Singapore? Then carpark rates will constitute a significant amount of your total transportation cost! If you’re curious about the weekday car park rates in Singapore and locations with available and free parking lots, then click on Read More or the title of this blog post for the data insights which I’ve derived with a visualization dashboard!

One of the best ways to absorb and retain new concepts that I have learnt about coding in Python is through documentation! As part of my journey to future-proof my data career and also to improve my proficiency in the python language, I have spent some of my free time to solve coding challenges on HackerRank. In this blog post, I shared the solutions to some of the practice challenges which I have completed and successfully passed the code in the compiler on HackerRank. Do click on Read More or the title of this blog post for the Python 3 solutions which I have created.

Documenting the answers to the practice questions which I have successfully completed and passed the code in the compiler on HackerRank. If you have not heard of HackerRank, it is a leading technical assessment platform used by hiring companies to conduct online coding tests and interviews aiming to choose the best among coding talents. Check out this blog post for my correct answers to the SQL Category on Basic and Advanced Select!

Sharing and documenting the basic concepts of batch scripting which I’ve picked up at work. Hopefully this blog post entry can help you to learn the basics of batch scripting and create scripts to automate tasks which are repetitive in nature.

Building on my previous post about text processing in python which covered singular word analysis from a text summary. This post explains on how to identify 2-words & 3-words phrases from a webpage, specifically filtering the large text corpus into bigrams and trigrams using the collocations package. I chose to analyse the text from wikipedia page about the song “Hope” by The Chainsmokers, one of the most played soundtrack on Spotify which I came across recently.

Retrieving semi & unstructured data from the webpage to conduct Natural Language Processing (NLP) is one of the most common tasks in many text/sentiments analysis project. In this post, I covered the basics of web scraping, text processing and basic visualisation using Python, which includes 1) Web Crawling, 2) Tokenisation, 3) Text Normalisation, 4) Lemmatisation and 5) basic frequency distribution & word cloud visualisation. I chose to analyse a text summary of Chapter XXI in ‘The Little Prince’ novel (as one of my favourite books) for it holds a deep & special meaning about relationships in life.

Creating your REST API GET Request can be hassle-free and easy with Python! The entire process can be completed by following a 9-step guide. I constructed a GET request from URA’s web API to fetch rental contract data in .json format and converted the dataset in .csv format for the ease of data load into the database. You can find the .py file stored in my github repository as well.

Are you utilising Microsoft SQL Server Management Studio (SSMS) application for data transformation? Wondering how to build data wrangling pipelines in t-SQL? This post explains on how to convert data in nvarchar format to date and decimal format, as well as pivoting the data from long to wide format.

Sharing a few simple tips on data wrangling using Python Pandas library! Does having to clean messy excel datasets sound familiar to you? This post explains on 1) how to convert dataframes from wide to long format, 2) standardising column names and 3) dividing column values evenly across duplicated Indexes.