Sliding window and flatten rows pandas python
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*tutorial: sliding window and flatten rows in pandas*
sliding window is a common technique used in data processing to analyze data points within a specified window size. in pandas, we can implement a sliding window by using a combination of rolling window functions and custom processing logic.
flattening rows refers to transforming multiple rows into a single row, which can be useful for summarizing or aggregating data.
let's demonstrate how to implement sliding window and flatten rows in pandas with a code example:
*step 1: import necessary libraries*
*step 2: create a sample dataframe*
*step 3: implement sliding window*
*step 4: implement flatten rows*
*step 5: display the results*
in this example, we first create a sample dataframe with timestamps and values. we then implement a sliding window with a window size of 3 using the `rolling` function. next, we flatten the rows by grouping rows in pairs and calculating the sum of values and mean of rolling sum within each pair. finally, we display the original dataframe and the dataframe with rolling window and flattened rows.
you can adjust the window size and flatten size according to your requirements and apply custom processing logic as needed.
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