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Rolling Average in Pandas

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问题 I have a dataframe with 2 columns - Date and Price. The data is sorted with newest date first (23 Jan in first row, 22 Jan in second row and so on). Date Price 23 Jan 100 22 Jan 95 21 Jan 90 . . . I want to calculate 2 days rolling average price for this time series data. I am using this: df.rolling(2).mean() What this does is, it assigns NaN to the first row (23 Jan) and then for the second row gives the output as the mean of prices on 23 Jan and 22 Jan. This is not useful as 22 Jan average

Rolling Average in Pandas

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1 Year Rolling mean pandas on column date

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问题 I would like to compute the 1 year rolling average for each line on the Dataframe below test: index id date variation 2313 7034 2018-03-14 4.139148e-06 2314 7034 2018-03-13 4.953194e-07 2315 7034 2018-03-12 2.854749e-06 2316 7034 2018-03-09 3.907458e-06 2317 7034 2018-03-08 1.662412e-06 2318 7034 2018-03-07 1.346433e-06 2319 7034 2018-03-06 8.731700e-06 2320 7034 2018-03-05 7.145597e-06 2321 7034 2018-03-02 4.893283e-06 ... For example, I would need to calculate: mean of variation of 7034

pandas rolling window mean in the future

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问题 I would like to use the pandas rolling function https://pandas.pydata.org/pandas-docs/version/0.22/generated/pandas.DataFrame.rolling.html on a pandas dataframe with datetime to aggregate future values. It looks it can be done only in the past, is this exact? Thanks! 回答1: IIUC, you can use shift to move you calculation back in time. df = pd.DataFrame({'Data':np.arange(0,11,1)},index=pd.date_range('2018-07-23',periods=11)) df['rolling'] = df.rolling('2D').mean().shift(-1) print(df) Output:

r calculating rolling average with window based on value (not number of rows or date/time variable)

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问题 I'm quite new to all the packages meant for calculating rolling averages in R and I hope you can show me in the right direction. I have the following data as an example: ms <- c(300, 300, 300, 301, 303, 305, 305, 306, 308, 310, 310, 311, 312, 314, 315, 315, 316, 316, 316, 317, 318, 320, 320, 321, 322, 324, 328, 329, 330, 330, 330, 332, 332, 334, 334, 335, 335, 336, 336, 337, 338, 338, 338, 340, 340, 341, 342, 342, 342, 342) correct <- c(1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0,

r calculating rolling average with window based on value (not number of rows or date/time variable)

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r calculating rolling average with window based on value (not number of rows or date/time variable)

阅读更多关于 r calculating rolling average with window based on value (not number of rows or date/time variable)

I'm quite new to all the packages meant for calculating rolling averages in R and I hope you can show me in the right direction. I have the following data as an example: ms <- c(300, 300, 300, 301, 303, 305, 305, 306, 308, 310, 310, 311, 312, 314, 315, 315, 316, 316, 316, 317, 318, 320, 320, 321, 322, 324, 328, 329, 330, 330, 330, 332, 332, 334, 334, 335, 335, 336, 336, 337, 338, 338, 338, 340, 340, 341, 342, 342, 342, 342) correct <- c(1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0) df <-