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Tag: numpy

pandas df apply condition on multiple columns

I have a df that looks like this: I want to create a new column named promoted from the columns master_feature, epic, and feature: value of promoted will be : master feature if adjacent master_feature column value is not null. feature if adjacent feature column value is not null ,and likewise for epic something like: how can I achieve this

Tensorflow dataset from numpy array

I have two numpy Arrays (X, Y) which I want to convert to a tensorflow dataset. According to the documentation it should be possible to run When doing this however I get the error: ValueError: Shapes (15, 1) and (768, 15) are incompatible This would make sense if the shapes of the numpy Arrays would be incompatible to the expected

Python: Plot sin wav with 3 discrete amplitudes

Using the code below I am able to create a sign wave I would like to create a sin wave which changes it’s amplitude at time 4s, and 8s so that the sin wave looks like the image below I know how to create each of the 3 sin waves in that img, but I don’t know how to combine

How to make clusters of Pandas data frame?

I am trying to make a cluster of the following pandas data frame and trying to give the names. E.g – “Personal Info” is cluster name and it consist of (PERSON,LOCATION,PHONE_NUMBER,EMAIL_ADDRESS,PASSPORT,SSN, DRIVER_LICENSE) and also addition of there Counts. which will be 460. Clusters: for reference I am providing clusters structure Input data: Output: Answer You can create an inverse dictionary

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