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Thanks 👍

great video but please turn down the music

You're doing great, please avoid bg music while explaining. Thank you.

I have a question about picking the best features in a huge dataset. If I use a method like F.S, it's going to take forever. What other ways can I use besides PCA for datasets with over a million rows? Could I just pick a random part of the data and use normal methods? Thanks for the videos, they've been a big help.

Love this agreed she is going to be a great scientist and now Kofi wants to help too!

Where are you from bro?

Awesome!

Way more exciting videos coming soon!! Nerd 🚨

thank you!

Very helpful thank you! Im new to data analysis and multiindex is really tough for me, this really helped though!

Hi, thanks for uploading these gems when literaly no one is doing these on youtube. Btw from where i can find the data you used here?

Enjoy your day!!

Thank you very much

How can I modify my jpynb to look like exactly like yours? I don't see a tab like yours while constructing classes. Help!!

If I understand you are using correlation calculations to understand variability in measurement repeatability? What might cause a difference? The equipment or measurement process?

Very informative and helpful video, thank you for sharing it. Chris, if one wanted to also link the raw data of a well in addition to the sample name , how would you approach this? Let's say column one in the excel sheet contains sample information as in your example and column 2 contains the raw data values for each well act... In your video when you executed " map_df" and it created a dataframe , I would like it also to contain the raw values located in column 2 of the excel sheet. I tried to alter your script but was not successful in making this minor edit. Any advise would be greatly appreciated

Sweet! I just found your channel a couple weeks ago. Your content is amazingly clear and useful. Either nobody's doing NIR, or they're missing this goldmine! Keep it up :) It's very much appreciated!! (I'm actually applying all this stuff to Raman spectra, which there are even fewer tutorials for.... regardless, your videos have been literally perfectly exactly what I need anyway!!)

Bro, I'm so proud of you! Thank you for this content :D

Thanks for this! I did a video on this several years ago on my channel, but I loved how quickly you demonstrated the power of the cv, within the first few seconds of your video.

Hi Christopher , thank you for this video, I need your email pls, i have some issues in my data, thank you

Really good one!

Very good video. Thank you.

"First" Love your channel, we should chat one day!

Love your videos!

the audio is so low, man

I have just found your signal processing series. Excellent. I have a question that I hope you can shed some light one. I use SciPy fft, fftfreq, and find_peaks, and have found that the amplitudes of the peaks found are hugely different (i.e. fft amplitude of a peak is 1200 and find_peaks has an amplitude of 0.65. Any insight would be appreciated. Thanks.

Hahaha go for it buddy😅

Thank you

Hello Christopher, Thank you for teaching me python. I am a PhD student in food science, mainly work with FTIR and GC-MS data. I am a three-month years old in python :). And struggling to manage my FTIR/GC-MS data (I work with a lot of data). It would very helpful for me (hope for others also ) if you make in-depth guides: 1. How to manage/organize data (FTIR, GC-MS- which format is suitable for FTIR/GC-MS data storage) 2. Maybe a GC-MS data analysis project that you would demonstrate how to import data, how to clean/ how to visualize/ how to find peaks (which you already did thought), and so on. I mean a complete real case study. 3. Covering Chemometrics would be amazing which is hard to find in youtube. 4. Random forest/PLS/PLS-D/ASCA? 5. Plot/Scatter plot for publication? I am just giving ideas it doesn't mean you should do every thing in this list. You already have created the content which is helping me in my PhD journey! Good luck!

Do you know Poker test or run test? These tests use for controling randomization.

Subscribed👍 succinct, informative.

Finally some animals! I'm stunned.

I stumbled onto your videos. Feels like I stumbled into a new world. I was searching for training data for the purpose of training up a large language model on organic chemistry. Started watching your videos and realised how limited my thinking is/was. Thanx a zillion.

First time I have seen your videos. This is genuinely a very good video. Very well explained and clear. I am subscribing. The music wasn’t off putting either!

So what about if we were to standardize using z-scoring? It seems like that would get largely the same impact, wouldn't it?

Chris😂, some of your videos are awesome, i am still looking at derivatives you did recently. As far as garbage by the watter: police department has to let bums through to spend time somewhere. Bums usually bring through away to these kinds of places, the shopping cart means they walked it from the parking lot of target 🎯 with their bags.

The story is people and people don't deserve the ground they walk on...

Great video man, it’s hard to come by something so easy to follow, keep it up!

Have a day with a ☕️

TRUMP 2024

Now take a walk until you find wildlife. Is that a thing in the city?

I should start counting the steps! 1,2, Welp…

Great video! What I found out that savgol as second derivative does not calculate boundaries of wavelengths. So, I got one wavelength point less. But, when I applied np.gradient as 2nd derivative, I got desired full wavelength range. Probably, from your experience, you can explain the difference between savgol and np.gradient? And dummy question, does it make sense calculate third order derivate? 😅

Howdy!! Here is the data discussed in the video :) github.com/chrisp33/Analytical_YT_Tutorials/blob/main/nir_coffee.csv

Very helpful video! :) I'm a beginner in Python and learning pandas by doing a personal project. For sure, this method is excellent to keep the code organized. Thank you so much for explaining how it works!

We got lots of that in Colorado

First of all, I would like to thank you for your explanation.. I have some questions for this method. My experimental data has 1600 information about modal analysis ( frequencies Vs Magnitudes ) So, how can identify the most good peaks with this PPM? (I'm not good in python)

Explaining complex subjects with your calm, composed, deep voice paired with the slow jazz music background of your choosing make me feel like I am in a private tutoring session with you in an empty bar. I am all for it! Thank you!