Welcome to my channel! My channel currently features videos about Python, data visualizations packages, and visual explanations of plots and metrics. You can watch my full "Introduction to Seaborn" playlist, check out some specific Matplotlib tips, or see other visual interpretations of data concepts.
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I am currently a freelance data scientist, specializing in data visualizations and data education. Feel free to contact me by email with business opportunities. Thanks for stopping by and let me know what type of content you would like to see next -- cheers!
Thank you, Kimberly, for your excellent videos. Your video is very educational and informative. Even slow person like me could easily follow your instructions, and I could construct density plots of the dataset that I had been playing with (10-yr wind obs in the Hunter Valley NSW) after simply watching your video. Many thanks :)
I just bought the course. No amount of money can pay for the amazing content you are putting out here but that's my little way to support your work. People were wowed by how my the data visualization skills improved and it's all because of the knowledge I have gained from your tutorials on RU-vid
Thanks so much for your purchase, and I am beyond thrilled to hear my channel has helped with your data visualization skills. Wishing you all the best! 👍
Thanks! I'm not sure exactly what you're seeing. I don't remember having problems with this in the past. So my only guess that I might try is saving as a SVG file instead of a PDF and converting it later.
Couldn't be more thrilled with Dr. Fessel's videos. I've probably watched a thousand data science videos. I try to pull what I can into a Microsoft OneNote page that I can make sense of. Usually that's not as easy as it sounds. With her videos, transcripts, and github pages, she sets a standard that makes all those other experts look like bums.
Great question - the output looks very similar but the input can be quite different. For the histplot, you'll have a column of numbers. Those can be integers or floating point numbers with a decimal. Seaborn will automatically make buckets for those numbers and count up how many numbers it sees within the range of each bucket (e.g. how many numbers fall somewhere within 3 to 5?) With the countplot, however, you'll often have a column full of categorical items, such as a column full of text values like dog, cat, and bird. Seaborn will tally up how many of each item it sees in that column (e.g. how many times does the word "dog" appear in the "pets" column?). Things can get fancier from there, but that's the rough gist. 👍
Yes, I believe you can still make a bivariatr KDEplot but you need to use new syntax. Try sns.kdeplot(data=df, x=‘col1’, y=‘col2’) where df is your pandas dataframe and col1 and col2 are names of your dataframe columns. 👍
So it goes for videos about coding libraries 😔- concepts should still be similar but the syntax definitely updates from time to time. Maybe I’ll make a new one… 🤔
It's weird, I generally do quite well academically but I can't for the life of me grasp the difference. If you leave me thinking for a couple of minutes I will be able to tell you which is which but it takes ages
i have been struggling to understand these... .this is the best vid i ever saw for explanation of precision n recall... please make more such vids... kudos...
Hi, this course features all asynchronous materials so you can access them any time you’d like - no time zone issues! Yes, the videos are pre-recorded, self-paced materials.
At 2:10 the meaning of "total number of apples we have..." is "...we have CLASSIFIED as apples and ARE apples" (3) (rather than "we have in total" (4).
Hi there - my PhD is in Applied Mathematics. I created models for the biomechanics of the inner ear. 😀 You can find me on LinkedIn here: www.linkedin.com/in/kimberlyfessel/ 👋
@@KimberlyFessel woah.. I just completed my masters in applied mathematics. Nice to see someone in my branch too. Well I am thinking to pursue PhD in bio informatics or bio-intermediary disciplines.
Yes! Chunksize was so close to making the cut of my favorite arguments to put into this video. (It's even written on the outline I made for the video but then crossed out 😆) I went with nrows instead to limit down the number of rows, but chunksize is great for having little pieces of your dataframe to work with and then throw away before they clog up your memory. This shows a little demo (pandas.pydata.org/pandas-docs/stable/user_guide/io.html#iterating-through-files-chunk-by-chunk), but of course, you would want to perform some actual calculations as opposed to just printing the chunks! 👍
Sure, I don't see why not. You would just want to supply an equation for the pyramid shape instead of the cubic shape I have here in the definition of function_z()... may need a piecewise function to make the edges nice and crisp.
