Six weeks ago, I launched an Instagram account to market my new website and YouTube channel, Maths with Lily. I hadn’t used any form of social media for over two years, but it was now necessary to jump back into it.
My aim was to get 1,000 organic Instagram followers within the first two months.
Six weeks later I’d already reached my goal, and I actually enjoyed myself while doing it. Here’s how it happened.
I have always set out to create my own content, albeit in small batches to save time.
The more posts I looked through, the more…
Gone are the days where the majority of the world have one income source — the 9-to-5.
In 2021, there are so many opportunities out there for us to diversify our income streams — it’s very much the dawn of the side hustle! The age of the internet and social media has arrived and in the wake up of such an uncertain year in 2020, I think that it is now the perfect time to have a serious look at what is out there beyond our day jobs.
Don’t get me wrong, I am not saying that you should resign…
I myself had not used any form of social media for over two years. I had deactivated all of my accounts and deleted all of the apps from my phone. In this day and age, the constant buzzing, pinging and sense of validation that these apps perpetuated were not something I wanted to expose myself to any longer.
However, in deciding to establish my own blog and YouTube channel, Maths with Lily, I realised that I would need to bite the bullet and re-download these apps — it is clear that in today’s market, a business’s social media presence is…
I have been tutoring maths for almost ten years, through high school, university and now alongside my day job. Since the pandemic began, I have been inundated with requests for maths tuition and ad hoc help to go through topics. This led me to the idea of creating resources to share online to expand my reach and ultimately help more people!
In December 2020, I began to launch my own maths business and brand — Maths with Lily. Maths with Lily is an online maths education business full of accessible tips, tricks, and tutorials, predominantly for high school students, parents…
I was initially exposed to Python and its package, Pandas in particular, to try to move away from manipulating Excel files when working as a Data Analyst. I had automated aspects of my monthly workload using VBA, but found my code to run slower than anticipated even after tuning. I wanted to try out something new which was fast and flexible. When I discovered Pandas, this ticked all the boxes and more, turning out to be fast, flexible and fun to learn!
Below you can find five of the top searched column operations on Google people want to learn how…
It’s not often I need to export records from a SQL query. Every time I have done (up until today), I have done the export and then had to manually add in the column headers.
As exporting from SSMS is not a frequent task I am required to undertake, it hasn’t bothered me too much. I was unsure how I could make this change to SSMS settings as I had not taken the time to look into it — SSMS is not something I use particularly regularly as I generally tend to run SQL queries using the Python library SQLAlchemy.
For the purpose of this article and to shake things up a bit, I’ve decided to use a FIFA 21 dataset from Kaggle — you can download this here. From here, I’ll be analysing these player ratings primarily using the Pandas library, to display a number of different simple yet useful plots.
Let’s get our data into a dataframe. Initially I hadn’t included the
delimiter parameter for the
read_csv() method, however it quickly became obvious that this was required when I took a look at the top five rows. I’ve imported
matplotlib.pyplot to display my plots throughout.
Jumping rope — or skipping — is something I used to do in the playground at school. I probably stopped when becoming self-conscious or hearing from someone it wasn’t cool to skip.
Fifteen years later, I decided to dust off the cobwebs and ordered myself a rope in the hope that I would be motivated to get outside and give it a go. It came at the perfect time, with England going into another lockdown — I really didn’t have any excuses!
I first started learning Python just over a year ago in my previous role as a Data Analyst. The company I was then working for was all about Excel. Every month I had to clean and combine nearly 100 different files gathered from all corners of the globe — as you can imagine, this was a nightmare! Due to the nature of the client, it was the age old story of a really tight turnaround for the analysis to be delivered, causing a reoccurring stressful bottleneck.
Initially I used VBA to automate some of my monthly work, however I found…
For this article, I will assume you’re working in Anaconda/GitHub/VS Code etc having already imported pandas into your script with the alias
This reads your Excel file into a pandas dataframe (the python equivalent of the tabular structure you’re used to). You’ll want to reuse this dataframe, so we’ll save it to the variable
df = pd.read_excel(some_file_path)
It might seem a bit strange at first that you’re not viewing every single row of data like in an Excel file. …