Since the conversation has inevitably drifted back to splitting bills in marriage, hereโs my own conclusion.
If there is something you CAN do to make your partnerโs life easier, and you refuse to do it to the best of your ability, you donโt love them and they should dump your ass as soon as possible.
Whether itโs washing plates, or giving them your paycheck, or waking up to cook at 4am, the whole point of love is that everything you have and are, is spent in pursuit of making the lives of your loved ones better.
The idea that you know that waking up to cook at 4am for your husband will make his life better or easier and you refuse to do it Or keeping your paycheck when you know your household needs the money, is practically madness to me.
If you know you cannot do this, donโt date them and donโt marry them.
Understand this, and every 50-50 argument becomes redundant.
e don do me small for this @IBM data course ๐
Iโve been doing SQL and Python, e dey make sense, then one thing just block me. the annoying part? i know exactly where i dey stuck. i see am. i just no fit cross am yet ๐
so instead of forming and guessing, i don comot back small go start the module again๐ฅฒ
Learning SQL today meant learning about Cloud Databases.
Instead of installing a database locally, you can create a database instance in the cloud and start running queries immediately.
Some benefits of cloud databases includes:
- Access from anywhere
- Scalability based on demand
- Built-in backups and disaster recovery
- No hardware setup or software installation
I also created my first Db2 on Cloud instance using IBMโs lite plan and explored how to create tables and run SQL queries from the web console.
Small steps every day in the data journey.
Todayโs @IBMData SQL lab made me think about the hidden structure behind the systems we use every day.
Most apps and platforms rely on database tables quietly organizing everything in the background.
Today I practiced creating, modifying, clearing, and deleting tables using SQL.
Simple commands but powerful foundations.
I finished my @IBM Python for Data Science capstone
The chart function was pre-built and my job was to feed it real data:
- I Scraped $TSLA and $GME revenue from live HTML with BeautifulSoup
- I pulled stock history via yfinance API
- I cleaned everything with Pandas before it could be used
I am still learning the chart libraries but if I can scrape, I can learn anything