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import numpy as np
import pandas as pd
from .pandas_vb_common import setup # noqa
class FillNa(object):
goal_time = 0.2
params = [True, False]
param_names = ['inplace']
def setup(self, inplace):
N = 10**6
rng = pd.date_range('1/1/2000', periods=N, freq='min')
data = np.random.randn(N)
data[::2] = np.nan
self.ts = pd.Series(data, index=rng)
def time_fillna(self, inplace):
self.ts.fillna(0.0, inplace=inplace)
def time_replace(self, inplace):
self.ts.replace(np.nan, 0.0, inplace=inplace)
class ReplaceDict(object):
goal_time = 0.2
params = [True, False]
param_names = ['inplace']
def setup(self, inplace):
N = 10**5
start_value = 10**5
self.to_rep = dict(enumerate(np.arange(N) + start_value))
self.s = pd.Series(np.random.randint(N, size=10**3))
def time_replace_series(self, inplace):
self.s.replace(self.to_rep, inplace=inplace)
class Convert(object):
goal_time = 0.5
params = (['DataFrame', 'Series'], ['Timestamp', 'Timedelta'])
param_names = ['constructor', 'replace_data']
def setup(self, constructor, replace_data):
N = 10**3
data = {'Series': pd.Series(np.random.randint(N, size=N)),
'DataFrame': pd.DataFrame({'A': np.random.randint(N, size=N),
'B': np.random.randint(N, size=N)})}
self.to_replace = {i: getattr(pd, replace_data) for i in range(N)}
self.data = data[constructor]
def time_replace(self, constructor, replace_data):
self.data.replace(self.to_replace)
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