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Tag: pandas

Compute rolling z-score in pandas dataframe

Is there a open source function to compute moving z-score like https://turi.com/products/create/docs/generated/graphlab.toolkits.anomaly_detection.moving_zscore.create.html. I have access to pandas rolling_std for computing std, but want to see if it can be extended to compute rolling z scores. Answer rolling.apply with a custom function is significantly slower than using builtin rolling functions (such as mean and std). Therefore, compute the rolling z-score from

How can I pivot a dataframe?

What is pivot? How do I pivot? Long format to wide format? I’ve seen a lot of questions that ask about pivot tables, even if they don’t know it. It is virtually impossible to write a canonical question and answer that encompasses all aspects of pivoting… But I’m going to give it a go. The problem with existing questions and

Fuzzy matching issue with matching nan values

I have a dataframe called RawDatabase which I am am snapping values to a validation list which is called ValidationLists. I take a specific column from the RawDatabase and compare the elements to the validation list. The entry will be snapped to the entry in the validation list it most closely resembles. The code looks like this: In an example

Apply log2 transformation to a pandas DataFrame

I want to apply log2 with applymap and np2.log2to a data and show it using boxplot, here is the code I have written: and below is the boxplot I get for my RAW data which is okay, but I do get the same boxplot after applying log2 transformation !!! can anyone please tell me what I am doing wrong and

Storing 3-dimensional data in pandas DataFrame

I am new to Python and I’m trying to understand how to manipulate data with pandas DataFrames. I searched for similar questions but I don’t see any satisfying my exact need. Please point me to the correct post if this is a duplicate. So I have multiple DataFrames with the exact same shape, columns and index. How do I combine

How can I increase the maximum query time?

I ran a query which will eventually return roughly 17M rows in chunks of 500,000. Everything seemed to be going just fine, but I ran into the following error: Obviously such a query can be expected to take some time; I’m fine with this (and chunking means I know I won’t be breaking any RAM limitations — in fact the

Grouping by multiple columns to find duplicate rows pandas

I have a df I want to group by val1 and val2 and get similar dataframe only with rows which has multiple occurance of same val1 and val2 combination. Final df: Answer You need duplicated with parameter subset for specify columns for check with keep=False for all duplicates for mask and filter by boolean indexing: Detail:

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