In [1]: from generated import generated
In [2]: import numba as nb
In [3]: @generated(nopython=True)
...: def foo(x, y):
...: if isinstance(x, nb.types.Integer):
...: return lambda x, y: x + y
...: else:
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import ujson | |
from datetime import datetime | |
import pandas as pd | |
from toolz import partition_all, dissoc | |
from castra import Castra | |
def to_json(line): | |
blob = ujson.loads(line) | |
date = blob['created_utc'] |
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from __future__ import print_function | |
import pandas as pd | |
from castra import Castra | |
from toolz import peek | |
def make_frame(year): | |
path = '{0}.csv'.format(year) | |
cols = ['year', 'month', 'day_of_month', 'day_of_week', 'deptime', | |
'crs_deptime', 'arrtime', 'crs_arrtime', 'unique_carrier', | |
'flight_num', 'tail_num', 'actual_elapsed_time', |
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<!DOCTYPE html> | |
<html> | |
<head><meta charset="utf-8" /> | |
<title>dominion</title> | |
<script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script> | |
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script> | |
<style type="text/css"> |
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from __future__ import print_function, absolute_import, division | |
import numbers | |
import warnings | |
import dask.array as da | |
import numpy as np | |
from scipy.optimize import fmin_l_bfgs_b | |
from sklearn import linear_model | |
from sklearn.preprocessing import LabelEncoder |
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