In your nyc_taxi data,what is the meaning of the coloum 'detrended_pickups','removed_trend', 'removed_std2016-01-01', and how to obtain.

[xiang526]

No description provided.

[fmpr]

Hi @xiang526. For the NYC Taxi dataset, I computed the historical average (for each day of week and time of day) and then I subtract the historical average from the original time-series in order to remove the cyclic behaviour (recurrent pattern). This is done by subtracting the mean and dividing by the standard deviation (like in regular standardization procedures), where the mean and stddev are computed according to the historical average model. The columns 'removed_trend' and 'removed_std' contains those values (mean and stddev respectively). If you would like, I can also share the data files with you. Just send me and email...

[xiang526]

Hi @xiang526. For the NYC Taxi dataset, I computed the historical average (for each day of week and time of day) and then I subtract the historical average from the original time-series in order to remove the cyclic behaviour (recurrent pattern). This is done by subtracting the mean and dividing by the standard deviation (like in regular standardization procedures), where the mean and stddev are computed according to the historical average model. The columns 'removed_trend' and 'removed_std' contains those values (mean and stddev respectively). If you would like, I can also share the data files with you. Just send me and email...

Thank you very much. my email:[email protected]

[xiang526]

Thank you very much. my email:[email protected]

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------------------&nbsp;原始邮件&nbsp;------------------ 发件人: "Filipe Rodrigues"<[email protected]&gt;; 发送时间: 2020年11月18日(星期三) 晚上8:53 收件人: "fmpr/DeepJMQR"<[email protected]&gt;; 抄送: "goodluck"<[email protected]&gt;; "Mention"<[email protected]&gt;; 主题: Re: [fmpr/DeepJMQR] In your nyc_taxi data,what is the meaning of the coloum &#39;detrended_pickups&#39;,&#39;removed_trend&#39;, &#39;removed_std2016-01-01&#39;, and how to obtain. (#1) Hi @xiang526. For the NYC Taxi dataset, I computed the historical average (for each day of week and time of day) and then I subtract the historical average from the original time-series in order to remove the cyclic behaviour (recurrent pattern). This is done by subtracting the mean and dividing by the standard deviation (like in regular standardization procedures), where the mean and stddev are computed according to the historical average model. The columns 'removed_trend' and 'removed_std' contains those values (mean and stddev respectively). If you would like, I can also share the data files with you. Just send me and email... — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or unsubscribe.

[xiang526]

Hi professor, &nbsp; &nbsp;I have used this method to compute the 'removed_trend' and 'removed_std', but the result was not same as you. Can you tell me your method. my&nbsp; method: df['mean'] =( df.groupby(['day_of_week','hour','minute'])['pickups'].transform('mean')) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;best wishes！

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------------------&nbsp;原始邮件&nbsp;------------------ 发件人: "fmpr/DeepJMQR" ***@***.***&gt;; 发送时间:&nbsp;2020年11月18日(星期三) 晚上8:53 ***@***.***&gt;; ***@***.******@***.***&gt;; 主题:&nbsp;Re: [fmpr/DeepJMQR] In your nyc_taxi data,what is the meaning of the coloum 'detrended_pickups','removed_trend', 'removed_std2016-01-01', and how to obtain. (#1) Hi @xiang526. For the NYC Taxi dataset, I computed the historical average (for each day of week and time of day) and then I subtract the historical average from the original time-series in order to remove the cyclic behaviour (recurrent pattern). This is done by subtracting the mean and dividing by the standard deviation (like in regular standardization procedures), where the mean and stddev are computed according to the historical average model. The columns 'removed_trend' and 'removed_std' contains those values (mean and stddev respectively). If you would like, I can also share the data files with you. Just send me and email... — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or unsubscribe.