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Top Python mistakes when dealing with Big Data
Interesting article.
Reinventing the wheel. For example, writing one-off code to read a CSV instead of using a convenient purpose-built library that could offer deeper functionality. (Python Pandas, to be specific, in this case - interesting stuff, actually!)
Failing to tune for performance. Cuts down on testing cycles per day.
Failing to understand time and timezones. Ain't that the truth.
...
1/22/2015
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