Відео

drinks.groupby('continent').mean(numeric_only = True)

orders.choice_description.str.replace('[\[\]]','',regex = True)

Thanks Kevin 👍🤝 . In 2024 it still relevant to learn .

One thing about this guy is that he gives very deep insights which you'll get nowhere else. As much as possible he'll give best practises, I have observed this from way back in the pandas course. Thanks so much Kevin. Please do deep learning and in-depth feature engineering tricks in a future video.

Is the mean() method not working for you? You need to include the argument numeric_only=True, for example: drinks.mean(numeric_only=True). This is a new requirement in pandas for cases in which you want to calculate the mean of numeric rows or columns and the DataFrame contains non-numeric data. Hope that helps!

sir the mean function is not working for me

best pandas tutorial

sir why in the last 2 cases where we didn't specify, in there with mean it is not executed but with min, max and count, it is being executed without showing any error? same for the visual form also?? help

I am using the yearly data....Suppose my data is showing 33 rows and 20 columns (20 columns also including the years (1999 to 2022) in my summary stat analysis. How can I exclude the year's column from my whole analysis? OR I should delete the year's column. Please guide us further regarding any data shape command.

You are a great instructor. I have learned a lot from you regarding pandas. The video with title "How do I merge DataFrames in pandas?" has left some queries in my mind. I would be thankful to you if you clear those too. What type of join is used here movie_ratings = pd.merge(movies , ratings)? if it is inner join it should result in 1682 rows in total in movie_ratings dataframe, as movies dataframe has 1682 rows. But in video i have observed that movie_ratings results in 100,000 rows of data.

Sir, you are the GOAT 🐐🐐

If mean is not working for you: We first have to drop 'country' and 'continent' columns, these columns contain strings so we can't do mean with them. drinks = drinks.drop(['continent','country'],axis = 1)

Hello, for a dataframe with 5000 rows and 13 columns how do we impute multiple entries. Some are numeric and some are categorical

while performing the mean operation, it shows that it could not convert the country's name to numeric , its an error. What to do?

Could you do Pytorch tips like you dod with sklearn ?

The shift tab trick is not working (I have windows and I am operating on vs code , jupyter notebook)

6:50

Es posible obtener mas descuento solo tengo $50 para este curso, estamos en Colombia y esto a ca esta dificil.

omg...thank you so muchhhh

Thank you so much for all your Pandas sessions, it was very detailed and covered almost all required basics.. !!!

just found your channel a few days ago , thanks for helping and Happy marriage ( a lil too late but... 😁)

As always you did great.thank you so much ❤

wow.. much appreciate ur efforts sir.. i learned Pandas 3 years before purely from ur videos.. it helped me to get job as well.. i am very thankful to you. ❤

What about the math concept that comes with this?

This is the outline of my NEW course, "Master Machine Learning with scikit-learn." You can enroll here: courses.dataschool.io/master-machine-learning-with-scikit-learn

Very excited..!

I am from India and your course is way too costly.

This is the overview of my NEW course, "Master Machine Learning with scikit-learn." You can enroll here: courses.dataschool.io/master-machine-learning-with-scikit-learn

Thanks ❤

This is a lesson from my NEW course, "Master Machine Learning with scikit-learn." You can enroll here: courses.dataschool.io/master-machine-learning-with-scikit-learn

Amazing! Thank you for the tip!

This is a lesson from my NEW course, "Master Machine Learning with scikit-learn." You can enroll here: courses.dataschool.io/master-machine-learning-with-scikit-learn

7 years later, this helped me. Thank you.

so far so good

Hello Kevin, thank you very much... I have two questions: 1) after hyper parameters tunning and cross validation, the final model should be some that is trained on the whole dataset (meaning train + validation set)? Am I right? 2) do we need cross validation if the dataset is very big (and how to know how big :) ? i.e. when cross validation is not necessary?

This is a lesson from my NEW course, "Master Machine Learning with scikit-learn." You can enroll here: courses.dataschool.io/master-machine-learning-with-scikit-learn

This is a lesson from my NEW course, "Master Machine Learning with scikit-learn." You can enroll here: courses.dataschool.io/master-machine-learning-with-scikit-learn

As a beginner in ML are there jobs / internships available where they use only SkLearn or most jobs today use advanced Deep Learning Libraries like PyTorch or Tensorflow

Excellent 🇿🇦

Great explanation

This is a lesson from my NEW course, "Master Machine Learning with scikit-learn." You can enroll here: courses.dataschool.io/master-machine-learning-with-scikit-learn

Thank you so much for this awesome playlist it is really helpful

for using ols in statsmodels.api is okay to drop?

amazing information. wow! thank you so much man.

Hello sir you are doing great work for our community,but I have a humble request please make video on maths learning topics which are important to become AI and ml engineer with proper guidance and free learning resources and full roadmap of learning mathematics please sir ! 🙏🙏 But thanks for your hardwork😊.

Superb

.mean() is not working for me

Thanks for coming back sir !! hope you continue uploading videos , your content is clear and more knowledge , , it's hard to find helpfull content these days online , please keep uploading sir.

We can do this for numerical data but what in the case of categoical data? Can you mention any method for that?