Тёмный
AI ML & GRC 12.0
AI ML & GRC 12.0
AI ML & GRC 12.0
Подписаться
Data Science
AI Generative
4:57
5 месяцев назад
SAP Access Control - Certificate
0:35
11 месяцев назад
Python to convert text to Audio
2:21
Год назад
Extract contact re
2:35
2 года назад
extract phone no _re
4:29
2 года назад
mail_contact_regular expression
6:13
2 года назад
regular_expression
3:07
2 года назад
Data Modelling 01 Power BI
9:06
2 года назад
Data Modelling 02 Power BI
9:53
2 года назад
DAX SUM Measure
9:31
2 года назад
DAX Function and Hierarchy
7:29
2 года назад
Total Sales
3:07
2 года назад
QA Confusion Matrix
3:36
2 года назад
QA Machine Learning 01
3:26
2 года назад
QA Machine Learning 02
2:37
2 года назад
QA Machine Learning 03
2:58
2 года назад
QA Machine Learning 04
2:07
2 года назад
QA Machine Learning 05
1:25
2 года назад
QA Machine Learning 06
1:34
2 года назад
QA Statistics
2:15
2 года назад
QA Statistics 01
2:42
2 года назад
BMW Part 2
3:08
2 года назад
BMW Price Challange Part 1
10:00
2 года назад
Churn Modelling data processing
5:35
2 года назад
Data Cleaning Part 2on bankcsv
9:52
2 года назад
DataCleaning bankcsv Part1
9:25
2 года назад
Комментарии
@23gidnqgue
@23gidnqgue Месяц назад
Thank u 😊
@jayasri-ft8040
@jayasri-ft8040 2 месяца назад
Superb sir
@sivakumar-rz9nc
@sivakumar-rz9nc 4 месяца назад
Hello all, ###the above code requires some changes, this is the modified code df_cat = df.select_dtypes(include=['object']) # Select categorical columns df_num = df.select_dtypes(include=['number']) # Select numeric columns # Convert categorical variables to numerical using one-hot encoding df_cat_encoded = pd.get_dummies(df_cat, drop_first=True) # Apply one-hot encoding # Identify boolean columns and convert them to numeric boolean_cols = df_cat_encoded.columns[df_cat_encoded.dtypes == 'bool'] df_cat_encoded[boolean_cols] = df_cat_encoded[boolean_cols].astype(int) # Concatenate the numerical and encoded categorical columns df_ml = pd.concat([df_num, df_cat_encoded], axis=1) # Concatenate along columns (axis=1) # Display the first few rows of the combined DataFrame df_ml.head(2)
@godi2539
@godi2539 4 месяца назад
The simplest and best I have seen. Thank you so much
@JyotirmoyeeRoy
@JyotirmoyeeRoy 4 месяца назад
It's showing a error "df is not defined ". What to do
@sivakumar-rz9nc
@sivakumar-rz9nc 4 месяца назад
df_cat = df.select_dtypes(include=['object']) # Select categorical columns df_num = df.select_dtypes(include=['number']) # Select numeric columns # Convert categorical variables to numerical using one-hot encoding df_cat_encoded = pd.get_dummies(df_cat, drop_first=True) # Apply one-hot encoding # Identify boolean columns and convert them to numeric boolean_cols = df_cat_encoded.columns[df_cat_encoded.dtypes == 'bool'] df_cat_encoded[boolean_cols] = df_cat_encoded[boolean_cols].astype(int) # Concatenate the numerical and encoded categorical columns df_ml = pd.concat([df_num, df_cat_encoded], axis=1) # Concatenate along columns (axis=1) # Display the first few rows of the combined DataFrame df_ml.head(2)
@shivandchin
@shivandchin 4 месяца назад
My categorical variables are not getting converted into uint8 they are still bool - everything is correct! But why am in unable to convert
@sivakumar-rz9nc
@sivakumar-rz9nc 4 месяца назад
df_cat = df.select_dtypes(include=['object']) # Select categorical columns df_num = df.select_dtypes(include=['number']) # Select numeric columns # Convert categorical variables to numerical using one-hot encoding df_cat_encoded = pd.get_dummies(df_cat, drop_first=True) # Apply one-hot encoding # Identify boolean columns and convert them to numeric boolean_cols = df_cat_encoded.columns[df_cat_encoded.dtypes == 'bool'] df_cat_encoded[boolean_cols] = df_cat_encoded[boolean_cols].astype(int) # Concatenate the numerical and encoded categorical columns df_ml = pd.concat([df_num, df_cat_encoded], axis=1) # Concatenate along columns (axis=1) # Display the first few rows of the combined DataFrame df_ml.head(2)
@user-sk3fg1db8s
@user-sk3fg1db8s 6 месяцев назад
Awesome ! This saves a lot of time converting them one at time. Thank you so much!!
@TheJaebeomPark
@TheJaebeomPark 8 месяцев назад
thanks
@macharlajagapatibabu2654
@macharlajagapatibabu2654 9 месяцев назад
thankyou sir it is helps alot
@thshantakumar
@thshantakumar Год назад
Thanks for sharing. 😊
@NeelimaPuri
@NeelimaPuri Год назад
could you show hoe to execute SQVI pls..... if u could join USR21 & ADR6
@NeelimaPuri
@NeelimaPuri Год назад
We have to check the inheritance also and remove it if it is there before deleting the role. Also you need to do the impact analysis like the role is assigned to how many users and provide the temporary access to the users for this role. correct me if I am wrong!!
@sangitaahire8569
@sangitaahire8569 Год назад
Columns must be same length as key so what I do
@Rahul-op2vc
@Rahul-op2vc 9 месяцев назад
hey did you get the answer to this.. I am getting the same error
@sivakumar-rz9nc
@sivakumar-rz9nc 4 месяца назад
df_cat = df.select_dtypes(include=['object']) # Select categorical columns df_num = df.select_dtypes(include=['number']) # Select numeric columns # Convert categorical variables to numerical using one-hot encoding df_cat_encoded = pd.get_dummies(df_cat, drop_first=True) # Apply one-hot encoding # Identify boolean columns and convert them to numeric boolean_cols = df_cat_encoded.columns[df_cat_encoded.dtypes == 'bool'] df_cat_encoded[boolean_cols] = df_cat_encoded[boolean_cols].astype(int) # Concatenate the numerical and encoded categorical columns df_ml = pd.concat([df_num, df_cat_encoded], axis=1) # Concatenate along columns (axis=1) # Display the first few rows of the combined DataFrame df_ml.head(2)
@Ali-ig4tg
@Ali-ig4tg 3 месяца назад
@@sivakumar-rz9nc sir i did this but in result i dont watch normale table
@shilpakapletiya578
@shilpakapletiya578 3 месяца назад
I tried below code df = data.apply(lambda x: pd.factorize(x)[0]) and it worked it converted all the catagorial values to numerical and returned a new dataset.
@Mighty2987
@Mighty2987 Год назад
Can you teach me this please
@relaxmeditateforyou
@relaxmeditateforyou Год назад
best video
@preciousosokoya6346
@preciousosokoya6346 Год назад
Awesome Video
@sansisalvo6770
@sansisalvo6770 Год назад
Thank you so much brother
@ahmadjibrilhemdi7639
@ahmadjibrilhemdi7639 Год назад
Thanks sir
@karupartikirankumar4866
@karupartikirankumar4866 Год назад
Really Great explanation sir
@donedie1
@donedie1 Год назад
Não da certo no meu campeao
@franciscofelixdesouzaneto496
Qual erro apresenta no seu?
@CaribouDataScience
@CaribouDataScience Год назад
Here is what I am trying to do but it isn't working? punct = string.punctuation def remove_punct(x): return x.translate(str.maketrans("","", punct)) elon_mentions['content'] = elon_mentions['content'].apply(lambda x: remove_punct(x))
@CaribouDataScience
@CaribouDataScience Год назад
Thanks, that was what I was looking for!!
@nihelredjel7627
@nihelredjel7627 Год назад
about the df path what should i do about it or what should i put there can anyone explain please..thanks
@BhanuPrakash-ci7zx
@BhanuPrakash-ci7zx Год назад
Thanks a lot for your efforts to explain the complicated topics in simple way..
@sumeetdey6361
@sumeetdey6361 Год назад
Vido was clear and to the point code.. Please continue uploading videos on NLP with projects
@ganeshtiwari2550
@ganeshtiwari2550 2 года назад
Hello just need Advice i m 28 wanna start sap analyst career plz suggest me roadmap and guidance how to make career in sap security any youtube channel can u suggest
@GKSP324
@GKSP324 2 года назад
Very good video.thank you for sharing
@GKSP324
@GKSP324 2 года назад
Really it is very helpful. Thank you. Keep uploading.
@khushibadgujar9131
@khushibadgujar9131 2 года назад
Which compiler used for this program..??
@RR-iv5fw
@RR-iv5fw 2 года назад
Nice Explanation .. useful for basic BI security
@vijaydeswal5432
@vijaydeswal5432 2 года назад
Grt work sir🙌🏻😊
@hashirazam9927
@hashirazam9927 2 года назад
Finally the most relevant video i found on this topic straight to the point <3
@BharaniBharani
@BharaniBharani 3 года назад
useful video
@kavyak9974
@kavyak9974 3 года назад
Thanks for the explanation it's too clear
@kavyak9974
@kavyak9974 3 года назад
Auth fields are maintained globally if it comes in derived role concept Auth field contains values & activity Org field maintained for company code & sales org etc..
@user-qh7xh6vk3i
@user-qh7xh6vk3i 3 года назад
Very good!
@environven3614
@environven3614 3 года назад
Thanks for posting videos even subscribers are less.... Really helpful...
@muneendragurramkonda7365
@muneendragurramkonda7365 3 года назад
Hi Could you please share this document gurramkondamuneendra@gmail.com
@punamphad6702
@punamphad6702 3 года назад
Role base interview questions also explain
@sriv4603
@sriv4603 3 года назад
Thank you for sharing but please show in the system also if possible.
@sriv4603
@sriv4603 3 года назад
This is V clear but if you show in the system it really helps to many people. thanks for sharing and please do show in the system also.
@sriv4603
@sriv4603 3 года назад
Too good.
@sriv4603
@sriv4603 3 года назад
Two hills and sunrise symbol is called Where Used List-- If you click that Icon we can see the auth. object related to that t-code. THank you for sharing the questions:) please share more videos.
@kurtcrow
@kurtcrow 4 года назад
After S4 1909 Upgrade, for any reason i got discrepancies between DEV/QA and PRD in USOBT. Which could be the most rationale way to remediate this? Could be just replacing the USOB* from PRD in all environments or is any risk that should be considered?
@sravanireddy3830
@sravanireddy3830 4 года назад
Can you send the interview questions like these for grc ac and ecc
@HSS7890
@HSS7890 4 года назад
Very easy to understand & lucid explaination.keep up the amazing & fabulous work!
@venkatr9302
@venkatr9302 4 года назад
Hi Bro, pls use any screen recording software so that video and audio quality will be nice. I suggest Snagit software it's very easy n user-friendly screen recording software.
@datasciences4hanasecurityg739
@datasciences4hanasecurityg739 4 года назад
Thanks for suggesting!!
@venkatr9302
@venkatr9302 4 года назад
@@datasciences4hanasecurityg739 if u want I can send u the software and the keys as well. Pls provide me ur email I'd. And what u r doing is really awesome and very helpful. Thank you for that.
@pranavkumar7952
@pranavkumar7952 4 года назад
Hi Bro! What is your LinkedIn id?
@Saikumar-qo5qn
@Saikumar-qo5qn 4 года назад
Good Information
@HSS7890
@HSS7890 4 года назад
FF ID is created in source system i.e., Central System?