Modern Python Cookbook by 2016

Author:2016
Language: eng
Format: epub, mobi
Publisher: Packt Publishing

If needed, define the data structure normalization function. This almost always has to be a generator function. A structural change can't be applied via map(): from ch08_r02 import row_merge

As shown in the Using stacked generator expressions recipe, this generator function will restructure the data from three rows per each leg of the voyage to one row per leg. When all of the columns are in a single row, the data is much easier to work with.

Define the overall data cleansing and enrichment data function. This is a generator function that's built from simpler functions. It's a stack of map() and filter() operations that will derive data from the source fields: def clean_data(source): namespace_iter = map(make_namespace, source) fitered_source = filter(remove_date, namespace_iter) start_iter = map(start_datetime, fitered_source) end_iter = map(end_datetime, start_iter) delta_iter = map(duration, end_iter) fuel_iter = map(fuel_use, delta_iter) per_hour_iter = map(fuel_per_hour, fuel_iter) return per_hour_iter

Each of the map() and filter() operations involves a small function to do a single conversion or computation on the data.

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