def setup(self):
    N = (10 ** 5)
    self.categories = list('abcde')
    self.cat_idx = pd.Index(self.categories)
    self.values = np.tile(self.categories, N)
    self.codes = np.tile(range(len(self.categories)), N)
    self.datetimes = pd.Series(pd.date_range('1995-01-01 00:00:00', periods=(N / 10), freq='s'))
    self.datetimes_with_nat = self.datetimes.copy()
    self.datetimes_with_nat.iloc[(- 1)] = pd.NaT
    self.values_some_nan = list(np.tile((self.categories + [np.nan]), N))
    self.values_all_nan = ([np.nan] * len(self.values))
    self.values_all_int8 = np.ones(N, 'int8')
    self.categorical = pd.Categorical(self.values, self.categories)
    self.series = pd.Series(self.categorical)
def setup(self):
    N = (10 ** 5)
    self.categories = list('abcde')
    self.cat_idx = pd.Index(self.categories)
    self.values = np.tile(self.categories, N)
    self.codes = np.tile(range(len(self.categories)), N)
    self.datetimes = pd.Series(pd.date_range('1995-01-01 00:00:00', periods=(N / 10), freq='s'))
    self.datetimes_with_nat = self.datetimes.copy()
    self.datetimes_with_nat.iloc[(- 1)] = pd.NaT
    self.values_some_nan = list(np.tile((self.categories + [np.nan]), N))
    self.values_all_nan = ([np.nan] * len(self.values))
    self.values_all_int8 = np.ones(N, 'int8')
    self.categorical = pd.Categorical(self.values, self.categories)
    self.series = pd.Series(self.categorical)