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program beginner さん @pgbeginnersan

話の題材は、背景の書籍です。

Joined September 2022
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self.data.dropna(inplace=True) self.data[self.features] -= self.mu self.data[self.features] /= self.std self.cols = []

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Add the col column to self.data, add the numerical value of f to self.data[], and use the shift() method to shift the row by the value of lag. Add the value stored in col to self.cols data with the append() method.

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本日の勉強は以上です。 ありがとうございました。 That is all for today's study. Thank you very much.
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self.data['max'] = self.data['mid'].rolling(self.window).max() self.data['vol'] = self.data['return'].rolling(self.window).std()

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In self.data['vol'], add a vol column to store the following In self.data['return'].rolling() method, execute the window function in the return column. The period is self.window. Then, we calculate the standard deviation in the .std() method.

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本日の勉強は以上です。 ありがとうございました。 That's all for today's study. Thank you very much.
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self.data['min'] = self.data['mid'].rolling(self.window).min() self.data['mom'] = np.sign(self.data['return'].rolling(self.window).mean())

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The calculation method executes the window function on the return column with self.data['return'].rolling(self.window). The argument is the value of self.window. The mean() method is executed on the result to calculate the average value.

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本日の勉強は以上です。 ありがとうございました。 That's all for today's study. Thank you very much.
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