You Don’t Need a CS Degree to Work in Technology

Posted on by

There, I said it. It’s true. Sure, my sample size is small, but hear me out.

I volunteer on a couple of platforms and help other learners with coding questions about Python, SQL, Data Analysis, and Data Science. The one issue, or question I always see is, ‘I don’t have a coding background…can I get a job in tech/can I still become good at programming??’ (or something along those lines.) Short answer: yes. Longer answer: read on.

I have a soft spot for non-tech people who want to have a career in technology, or who just want to learn a programming language because I used to be one. My educational background isn’t computer science, it’s the social sciences. To be more precise: sociology & political science. Everything regarding data science, data analysis, and programming that I’ve learned has been through various jobs and learning to code on my own.

What I’m saying is this:

You don’t need a computer science background or degree to be working in technology and to become proficient at programming. Learning to think computationally is a skill that can be *learned* by anyone. In fact, I will add that having a non-comp sci background is an asset and not a liability. Having a different background gives one a multifaceted perspective. You bring with you other ideas and knowledge that will help you, rather than just having a singular or narrowly-focused perspective. (And no, I’m definitely not saying that CS people are one-dimensional or narrowly-focused.)

Is coding hard? Yes. Will you get frustrated? Yes, but you have to stick with it. You will think you don’t understand anything and you will get upset. But, you have to remember that you’re learning a new language and that this learning process is a marathon and not a sprint. It’s like learning a foreign language. Would you expect to be completely fluent after a day or two? No. Same with coding. It takes practice and repetition. It takes learning how to research why your code won’t run, how to ask those questions, and where to search for answers. I tell people, if you don’t understand a concept, write it out or draw it if it helps you understand. Believe it or not, you will connect those dots and you will have an (or many!) “A-HA!!” moments.

I didn’t come to knowing what I know alone either. I had some really excellent mentors along the way when I was in a data program and outside the program. They were the ones that stuck with me when I was pulling out my hair because I didn’t understand how Python functions work. There are also communities on Discord or YouTube or even LinkedIn that you can join if you wish to. You will find your people.

I will say it again: learning to think computationally is a skill that anyone can learn and ultimately master. Ask questions, listen, be patient with yourself, write, re-write your code, and always, ALWAYS read the documentation. (or, RTFM)

Happy coding!

Spicy Peanut Sauce

Posted on by

Lately, I’ve been making a lot of brown rice and mixed (frozen) vegetables because it’s a quick dinner. I got tired of just adding Bragg’s so I made a quick spicy peanut sauce. You don’t really need that much on a couple servings of rice and veg, so you can adjust and make more for noodles or whatever else. You can also thin it out more, which is what I did. I think it’d be a nice veggie dip alternative to say, plant-based (or regular) Ranch dressing.

Ingredients

  • 1/4C natural peanut butter
  • 1/2C boiling water
  • 1 tsp agave
  • 2-3 tsp of hot sauce (or more!)
  • dash of crushed red pepper flakes
  • dash of Bragg’s (or soy or Tamari sauce)

Put peanut butter and condiments in a small bowl, then slowly add boiling water. I whip it up with a fork rather than a spoon. Get it to the consistency you desire and adjust the spice level. Drizzle over rice and vegetables. A little goes a long way!

How to Easily Upload a CSV File to Google Colab

Posted on by

What prompted me to write this was I was seeing a lot of confusion amongst data analyst/science learners on how to upload data sets/csv files into Google Colab and then share those notebooks. (Colab is a cloud-based DA/DS app where you can write and execute Python code. It is based on Jupyter Notebook and is hosted in the cloud.)

There are several ways you can upload a csv file into your Google Colab notebook. How you do so will affect how others can interact with your notebook. If you’re just doing research and not sharing your notebook (and don’t need anyone to run the code cells in your notebook), then you don’t need to share your data. But if you are working with someone else on a project they will need easy access to the data set(s) so they can run the notebook cells on their machine. Or, another scenario: if you share your notebook in general and you want others to be able to run the code cells they will need access to your data. I will go over the specific code snippets/steps below.

If you’re not sharing your notebook:

  1. Do it locally. Use the following code. This code cell, when run will bring up the “Choose Files” window. Then you can select that and upload the files locally from your computer.
code snippet to import files locally from your machine into colab

2. You can also mount your Google Drive to your Colab notebook with the following code:

code snippet to connect your google drive to your colab notebook.
code snippet to mount your Google Drive to your Colab notebook

The above code will prompt you to follow a link where you get an authorization code. Paste the auth code into the window. And now you can navigate your Drive and add files to your notebook. If you don’t want to type the code, you can grab code snippets from the left pane window here:

image of code snippet window in Google Colab notebook

I like that one can now easily add code to their notebooks. Thanks, Google!

3. My new favorite — and in my opinion the easiest way — to get a csv file into Colab is by adding it via your GitHub repo. This way anyone can run the code cells in the notebook because the link to the data is coming from your public repository on GitHub. (I am also assuming that you’re using Pandas and not the csv library in Python.)

pandas code to create a df from a csv file from GitHub
Pandas code to create a dataframe from a csv file on github.

I have a repo on Github that has a bunch of csv files, or, for specific projects, those csv files are in those repos. (However you want to organize stuff is up to you).

Steps:

a. Upload the csv file to the repo.

b. Click on the csv file and view it in “raw” format.

c. grab the entire URL.

d. paste the URL as I have above in quotes.

Ex: df = pd.read_csv(“https://raw.githubusercontent.com/yourGHfilegoeshere/filename.csv”)

Boom! You’re done.

Happy coding!

*This article also appears over on my Medium page.

Site Update!

Posted on by

Hello, friend.

So, I decided to update the content of the site and add in crochet projects that I’m working on as well as some posts about data science projects, and coding concepts.

But why?

The only constant is change. Well, that and I realized that I don’t write as often as I could, or should update content here. I’m certainly paying my host a lot of money, annually to not write very much.

So, here we are.

  • I haven’t really felt compelled to bake or cook with much frequency lately either. I don’t know about you but I definitely get in ruts where I have zero creativity/cooking seems more like a chore than fun and I end up just assembling food for meals. Plus, it’s been too hot to turn on the oven here during the summer (kinda contradicts the purpose of the A/C).
  • I am also a data science (analytics specialist) and wanted to share what I have learned with Python and what I’m currently learning/working on in my spare time.

  • AND, I love to crochet and am working on adding items to my Etsy store. So, why not showcase or talk about crocheting too?

With that said, let’s go!

Vegan “Egg” Salad

Posted on by

Maybe you don’t like eggs, have an allergy, or are vegan….well, this recipe is for you!

  • 1 pkg firm or extra firm tofu, drained
  • 2 stalks celery, chopped
  • 1 dill pickle, chopped
  • 1/2C – 3/4C vegan mayo
  • Dried yellow mustard
  • Turmeric
  • French’s yellow mustard
  • salt

Directions:

Drain tofu. I do this by putting it in a fine mesh strainer over a large bowl and, using paper towels press out all the excess liquid. (You don’t want watery “egg” salad. Then I toss the excess liquid and use the same bowl to mix the ingredients together. You can also buy one of those tofu presses. Actually, I might buy one of those as I think I’d get a lot of use out of it.

Mash up tofu with fork, add the rest of the ingredients. Add the vegan mayo a little bit at a time; you don’t want soupy egg salad. Trust your instincts when it comes to adding ingredients. I also added a couple teaspoons of pickle juice. (Some recipes I saw online had you adding vinegar. Why? Vegan mayo already has apple cider vinegar). I like the tang from the pickle juice.

This makes a LOT. Probably will last a week.

You’re done! I like to eat the egg salad on crackers or on a toasted bagel. Now that I figured out how to make this I won’t have to buy it pre-packaged from the store any more! Woo!

ingredients, vegan egg salad!