Price Prediction with Python and Power BI

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Learn how to create a machine learning price prediction using Python machine learning linear regression model and a dataset of 54,000 diamonds. This will be ported over to Power BI for a deeper level of interaction.
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You can find the files and dataset here:
github.com/Gae...
#machinelearning
#prediction
#powerbi
#python

Опубликовано:

20 окт 2024

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Комментарии : 40

@chescov 3 года назад

This was awesome!! Thank you so much for teaching us both sides...python and power bi 👏👏👏

@lawrencew8243 2 года назад

Such a great tutorial, I'm familiar with ML concepts but this puts it over the top with PowerBI, thanks! Looking to move into BI so this is super helpful

@absentdata 2 года назад

Im glad it help to pull some concepts together!

@antonietakuz5636 Год назад

Excelente video, estoy aprendiendo mucho como que haces!!! felicitaciones y gracias

@jimmyrico5364 3 года назад

Great content, thanks for sharing! How could one implement this but enabling automatic uploading of data (from a file hosted in SharePoint) and refreshing of the modeling whenever new records are added to the file please? - For a published version of the dashboard, I have a similar model deployed locally and would like users to execute it. Thanks in advance for your guidance!

@arrjunerasiah 3 года назад

This is absolutely amazing holy sht

@SliverHell 3 года назад

LMAOOO. THINKING THE EXACT SAME THING BRUH

@kuramochiyouichi1448 2 года назад

NO CAP BRU THIS SHIT GOOD ASF

@gomolemartifex 3 года назад

Your work is so helpful thank you so much

@absentdata 3 года назад

Your welcome

@rayxie5983 4 года назад

This is really awesome! Could you please try pipeline and grid search and make it dynamic in power bi ? Thanks a lot.

@jean-pierresteenberg 11 месяцев назад

great python lesson as akways! i didnt really understand the symmetery part: There is a high amount of correlation between the the diamond dimensions. So it might be better to eliminate some of these due to the high amount correlation. how does symmetry help here?

@bouseuxlatache4140 3 года назад

great python lesson from a to z. thanks

@Happy_soul57 2 года назад

I have Created whole project except In Transform data there is a Table 1 and I don't know from where I can grt that data please please it's a request please share me that data I have submit the project in COLLEGE. PLEASE absent data

@Abhishek-jj5wo 3 года назад

Absolutely, such a nice video for prediction, Want to do practical to get more understanding. can i have the csv file for same to do the practice . thank you

@teamomiparientes3769 Год назад

so with such diagonal fitted line, it shows that the model is good

@absentdata Год назад

Yes generally if the data points condense around the fitted line then the model is better

@im4485 3 года назад

Awesome video. Hey, I am having trouble pointing power bi to use the python within my anaconda env (you have it down, I can see at 12:48). It defaults, in my case to the python ithin anaconda but not the python in my virtualenv. Any idea how to fix it? Changing the path doesn't work.

@zhangmr7955 2 года назад

I dont get it. How you set the Error Threshold measure of Parameter & parameter2? from where to set it? Too fast to follow. And how to set the prediction error?

@kiliasm1686 3 года назад

thank you very much! I would like to ask a question: why is StandardScaler not applicable to Power BI?

@absentdata 3 года назад

You can use standard scaler in this example the data is on the same scale. Investment dollars.

@geirberge8971 3 года назад

Thanks ,,, amazing

@im4485 3 года назад

What? This is amazing....can i skip learning m language and Dax and just use python instead with power bi?

@absentdata 3 года назад

Well that's a good question. Power BI serves as an interactive dashboard and Bi tool. So this can easily be shared with other users. Python is a language that allows you utilize data science libraries..you can build interactive dashboards with Python but there are limitations.. So it really depends on your use case.

@MrLuxNsk 4 года назад

Thank you for awesome work. I am trying to recreate this step by step and get an error with KNN model. 'Input contains NaN, infinity...' but the dataset after getting dummies is free of any of those. Not sure how to follow up on this. Could you advise, please?

@absentdata 4 года назад

Thank you. Try downloading the Jupyter notebook and following along. However, if you're getting that error then take action and use a function to drop the NaNs .

@MrLuxNsk 4 года назад

@@absentdata thank you. Worked when i moved dropna function before i got my dummies, and not after.

@mamtarajeshirke2981 2 года назад

How did you created Prediction column can you please tell us ???????

@absentdata 2 года назад

There are other videos that show how to create predictions with machine learning algorithm ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-0zveIwThlfE.html

@Monnil46 3 года назад

Great tutorial! Could this code also be modified so that we can predict values for individual manually inserted values, much like what we did in the linear regression modelling in one of your other videos. If possible, could you give me a hint on how to do so? Thanks for the great video!

@absentdata 3 года назад

Yes it could be modified for that certainly!!

@Monnil46 3 года назад

@@absentdata Great, could you give me a hint on how to proceed with that? I have created a individual parameter, but am struggling to write a dax to connect that parameter to my predicted value

@felipelandim2881 3 года назад

That's awesome.

@absentdata 3 года назад

Glad you think so!

@voodi376 4 года назад

Nice video. I'm not seeing the diamonds2.csv on github?

@absentdata 4 года назад

added :)

@theworldiscrazy8732 3 года назад

Thank you so much for making this video. This what I was looking for. I even tried to practice the same, however, while putting the code in BI , I am getting the below error. I would really appreciate if you could help me in solving the below. Thank you. DataSource.Error: ADO.NET: Python script error. C:\Users\Harshit.MMDXB\Anaconda3\lib\site-packages umpy\__init__.py:140: UserWarning: mkl-service package failed to import, therefore Intel(R) MKL initialization ensuring its correct out-of-the box operation under condition when Gnu OpenMP had already been loaded by Python process is not assured. Please install mkl-service package, see github.com/IntelPython/mkl-service from . import _distributor_init Traceback (most recent call last): File "PythonScriptWrapper.PY", line 2, in import os, pandas, matplotlib File "C:\Users\Harshit.MMDXB\Anaconda3\lib\site-packages\pandas\__init__.py", line 16, in raise ImportError( ImportError: Unable to import required dependencies: numpy: IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! Importing the numpy C-extensions failed. This error can happen for many reasons, often due to issues with your setup or how NumPy was installed. We have compiled some common reasons and troubleshooting tips at: numpy.org/devdocs/user/troubleshooting-importerror.html Please note and check the following: * The Python version is: Python3.8 from "C:\Users\Harshit.MMDXB\Anaconda3\python.exe" * The NumPy version is: "1.18.5" and make sure that they are the versions you expect. Please carefully study the documentation linked above for further help. Original error was: DLL load failed while importing _multiarray_umath: The specified module could not be found. Details: DataSourceKind=Python DataSourcePath=Python Message=Python script error. C:\Users\Harshit.MMDXB\Anaconda3\lib\site-packages umpy\__init__.py:140: UserWarning: mkl-service package failed to import, therefore Intel(R) MKL initialization ensuring its correct out-of-the box operation under condition when Gnu OpenMP had already been loaded by Python process is not assured. Please install mkl-service package, see github.com/IntelPython/mkl-service from . import _distributor_init Traceback (most recent call last): File "PythonScriptWrapper.PY", line 2, in import os, pandas, matplotlib File "C:\Users\Harshit.MMDXB\Anaconda3\lib\site-packages\pandas\__init__.py", line 16, in raise ImportError( ImportError: Unable to import required dependencies: numpy: IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! Importing the numpy C-extensions failed. This error can happen for many reasons, often due to issues with your setup or how NumPy was installed. We have compiled some common reasons and troub... ErrorCode=-2147467259 ExceptionType=Microsoft.PowerBI.Scripting.Python.Exceptions.PythonScriptRuntimeException

@absentdata 3 года назад

Create a new python environment and load in the libraries you need. Just Google create python environment

@theworldiscrazy8732 3 года назад

@@absentdata Thank You. I tried that and now no error for libraries but getting the below error. Could you please help in possible solution for this. DataSource.Error: ADO.NET: Python script error. Traceback (most recent call last): File "C:\Users\Harshit.MMDXB\PythonScriptWrapper_12e85b4e-bc88-4155-97de-f2ee931cf648\PythonScriptWrapper.PY", line 25, in knn.fit(X_train,y_train) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn eighbors\_regression.py", line 190, in fit return self._fit(X, y) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn eighbors\_base.py", line 363, in _fit X, y = self._validate_data(X, y, accept_sparse="csr", File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn\base.py", line 433, in _validate_data X, y = check_X_y(X, y, **check_params) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn\utils\validation.py", line 63, in inner_f return f(*args, **kwargs) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn\utils\validation.py", line 814, in check_X_y X = check_array(X, accept_sparse=accept_sparse, File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn\utils\validation.py", line 63, in inner_f return f(*args, **kwargs) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn\utils\validation.py", line 663, in check_array _assert_all_finite(array, File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn\utils\validation.py", line 103, in _assert_all_finite raise ValueError( ValueError: Input contains NaN, infinity or a value too large for dtype('float64'). Details: DataSourceKind=Python DataSourcePath=Python Message=Python script error. Traceback (most recent call last): File "C:\Users\Harshit.MMDXB\PythonScriptWrapper_12e85b4e-bc88-4155-97de-f2ee931cf648\PythonScriptWrapper.PY", line 25, in knn.fit(X_train,y_train) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn eighbors\_regression.py", line 190, in fit return self._fit(X, y) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn eighbors\_base.py", line 363, in _fit X, y = self._validate_data(X, y, accept_sparse="csr", File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn\base.py", line 433, in _validate_data X, y = check_X_y(X, y, **check_params) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packages\sklearn\utils\validation.py", line 63, in inner_f return f(*args, **kwargs) File "C:\Users\Harshit.MMDXB\AppData\Local\Programs\Python\Python39\lib\site-packag... ErrorCode=-2147467259 ExceptionType=Microsoft.PowerBI.Scripting.Python.Exceptions.PythonScriptRuntimeException