Category : dictionary-comprehension

I’m trying to emulate the behavior of R’s mutate(across()) with Pandas, and a one-liner way of doing it is through dictionary comprehensions. For example, if I have a DataFrame that looks like this: df.head() >>> jam_cpi_eop bah_cpi_eop >>> 1980-01-01 3.038 38.714 >>> 1981-01-01 3.183 42.193 >>> 1982-01-01 3.406 44.115 >>> 1983-01-01 3.974 45.653 >>> 1984-01-01 ..

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I’m connecting to a REST service and I get a response in that format { "Outputs": { "Actual": [ "2017-08-29T14:37:47.137", "2017-08-30T13:07:09.563", "2017-08-30T14:41:29.023" ], "Start": [ "2017-08-29T14:36:12.42", "2017-08-30T12:59:53.05", "2017-08-30T14:40:45.34" ], "NumScrapsList": [ 0, 3, … but I would like to have it in that form { "Outputs":[ { "NumScrapsList":0, "Actual":"2017-08-29T14:37:47.137", "Start":"08-29T14:36:12.42" }, { "NumScrapsList":3, "Actual":"2017-08-30T13:07:09.563", "Start":"2017-08-30T12:59:53.05" ..

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I created the following function to pair each letter in the alphabet with its corresponding encoded letter based on a given shift: alphabet = [‘a’, ‘b’, ‘c’, ‘d’, ‘e’, ‘f’, ‘g’, ‘h’, ‘i’, ‘j’, ‘k’, ‘l’, ‘m’, ‘n’, ‘o’, ‘p’, ‘q’, ‘r’, ‘s’, ‘t’, ‘u’, ‘v’, ‘w’, ‘x’, ‘y’, ‘z’] def build_cipher(shift): ”’ Description: takes ..

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I have these columns names that follow this structure in list in orig, that I am trying to rename to "new." There are four groups of these four columns, totaling 16 columns overall. In other words, using orig as an example, columns 5-8 would contain "2" instead of 1, and columns 9-12 would contain a ..

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