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import numpy as np
import pandas as pd
try:
import pandas.core.computation.expressions as expr
except ImportError:
import pandas.computation.expressions as expr
from .pandas_vb_common import setup # noqa
class Eval(object):
goal_time = 0.2
params = [['numexpr', 'python'], [1, 'all']]
param_names = ['engine', 'threads']
def setup(self, engine, threads):
self.df = pd.DataFrame(np.random.randn(20000, 100))
self.df2 = pd.DataFrame(np.random.randn(20000, 100))
self.df3 = pd.DataFrame(np.random.randn(20000, 100))
self.df4 = pd.DataFrame(np.random.randn(20000, 100))
if threads == 1:
expr.set_numexpr_threads(1)
def time_add(self, engine, threads):
pd.eval('self.df + self.df2 + self.df3 + self.df4', engine=engine)
def time_and(self, engine, threads):
pd.eval('(self.df > 0) & (self.df2 > 0) & '
'(self.df3 > 0) & (self.df4 > 0)', engine=engine)
def time_chained_cmp(self, engine, threads):
pd.eval('self.df < self.df2 < self.df3 < self.df4', engine=engine)
def time_mult(self, engine, threads):
pd.eval('self.df * self.df2 * self.df3 * self.df4', engine=engine)
def teardown(self, engine, threads):
expr.set_numexpr_threads()
class Query(object):
goal_time = 0.2
def setup(self):
N = 10**6
halfway = (N // 2) - 1
index = pd.date_range('20010101', periods=N, freq='T')
s = pd.Series(index)
self.ts = s.iloc[halfway]
self.df = pd.DataFrame({'a': np.random.randn(N), 'dates': s},
index=index)
data = np.random.randn(N)
self.min_val = data.min()
self.max_val = data.max()
def time_query_datetime_index(self):
self.df.query('index < @self.ts')
def time_query_datetime_column(self):
self.df.query('dates < @self.ts')
def time_query_with_boolean_selection(self):
self.df.query('(a >= @self.min_val) & (a <= @self.max_val)')
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