Handle Categorical features using Python

Here is a video which provides you the detailed explanation of how we can handle the categorical features using Python. We will basically be applying the get_dummies() function from the pandas library,
#HandlingCategoricalfeatures

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[HrishikeshShinde]

This is the simplest way of encoding the categorical features. Thanks man!!

[amylock]

Exactly what I was looking for! Thank you

[MrKB_SSJ]

Thank you so much... It was so easy...

[timothythampy]

Thank you so much, sir! You are the best teacher

[UnstoppableBird]

thank you so much, this is actually clearer than the stupid class I enrolled earlier

[sreedharsree]

Thanks krish for this video ..

I have a doubt, at last part of the video .. while converting from categorical feature to numerical feature 2001 pincode represented at one instance as 1 and at other instance it is represented as 0 .. on what basis we represented like this ?

[nikhilshingadiya]

what happen if we have all independent variable as categorical i.e. movies data set country origin, movie_type, director now i want to predict the imdb missing data how can i handle those categorical variable

[dilipgawade]

Hi Krish,


can you show how to convert categorical variable to numeric variable through coding ?

[aanniirr]

how can we save the count of a particular category obtained to be used later in any calculation

[inderpreetkaur]

I want to create box plot for categorical variable (like subscribed: yes/no)
Firstly I wrote the code: train= pd.get_dummies(train['subscribed'], drop_first=1)
And then for creating box plot:
But this will show error as- keyword: 'subscribed'
Please let me know my mistake.

[slowhanduchiha]

One Question Sir. I was working on a classification dataset. My out put variable is also categorical in nature . I applied OHE and later when i saw the heatmap it made no sense because the columns were bit blank. Correct me where i am wrong here

[swaruppanda]

At 17:08 u made it clear for 2001 as 1 as output will be 2/3=0.6 what about 2001 as 0 as output?

[ranoyavanniysingam]

if we have more than 5 categorical-feautures column, what to do for that? for example -- country, age group like this?

[simanchalpatnaik]

Thanks for the video Krish.
When I ran the "df" command after concating, why all the values of Florida & New York comes as "NaN" ?

[arjyabasu]

Sir, please upload a video on how to perform mean encoding !!

[priyak]

How to apply onehot encoding if we have categorical data in Y (dependent column).

[somnathbanerjee]

Hi Krish, could you please guide me how can I handle text column for a regression problem. It's not about encoding categorical features. But what I am looking for is---extracting some meaningful information from the existing column containing text data using string manipulation method from regex...Please recommend me an effective way of doing this.

[SuperJg]

what to do if there is mixed data, continuous and categorical?

[kaushal]

Kris, but what if we have a regression problem then we would not have output as 0/1, then how do we encode the categorical features like pincode, do we use frequency/count encoding in there??

[parakhsrivastava]

I have a doubt...
When dealing with categorical values having many classes, you took all 2001's and find out the probability where O/P is 1.
Suppose, that is coming 0.6(as in video). Now you are replacing all 2001's with 0.6, no matter O/P is 0 or 1... WHY?


Should we not replace 2001's by 0.6 only if O/P is 1, else replace it with 0.4?
Thanks for the video btw!