forked from pandas-dev/pandas
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reindex.py
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reindex.py
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import numpy as np
import pandas.util.testing as tm
from pandas import (DataFrame, Series, MultiIndex, Index,
date_range)
from .pandas_vb_common import lib
class Reindex(object):
def setup(self):
rng = date_range(start='1/1/1970', periods=10000, freq='1min')
self.df = DataFrame(np.random.rand(10000, 10), index=rng,
columns=range(10))
self.df['foo'] = 'bar'
self.rng_subset = Index(rng[::2])
self.df2 = DataFrame(index=range(10000),
data=np.random.rand(10000, 30), columns=range(30))
N = 5000
K = 200
level1 = tm.makeStringIndex(N).values.repeat(K)
level2 = np.tile(tm.makeStringIndex(K).values, N)
index = MultiIndex.from_arrays([level1, level2])
self.s = Series(np.random.randn(N * K), index=index)
self.s_subset = self.s[::2]
def time_reindex_dates(self):
self.df.reindex(self.rng_subset)
def time_reindex_columns(self):
self.df2.reindex(columns=self.df.columns[1:5])
def time_reindex_multiindex(self):
self.s.reindex(self.s_subset.index)
class ReindexMethod(object):
params = ['pad', 'backfill']
param_names = ['method']
def setup(self, method):
N = 100000
self.idx = date_range('1/1/2000', periods=N, freq='1min')
self.ts = Series(np.random.randn(N), index=self.idx)[::2]
def time_reindex_method(self, method):
self.ts.reindex(self.idx, method=method)
class Fillna(object):
params = ['pad', 'backfill']
param_names = ['method']
def setup(self, method):
N = 100000
self.idx = date_range('1/1/2000', periods=N, freq='1min')
ts = Series(np.random.randn(N), index=self.idx)[::2]
self.ts_reindexed = ts.reindex(self.idx)
self.ts_float32 = self.ts_reindexed.astype('float32')
def time_reindexed(self, method):
self.ts_reindexed.fillna(method=method)
def time_float_32(self, method):
self.ts_float32.fillna(method=method)
class LevelAlign(object):
def setup(self):
self.index = MultiIndex(
levels=[np.arange(10), np.arange(100), np.arange(100)],
codes=[np.arange(10).repeat(10000),
np.tile(np.arange(100).repeat(100), 10),
np.tile(np.tile(np.arange(100), 100), 10)])
self.df = DataFrame(np.random.randn(len(self.index), 4),
index=self.index)
self.df_level = DataFrame(np.random.randn(100, 4),
index=self.index.levels[1])
def time_align_level(self):
self.df.align(self.df_level, level=1, copy=False)
def time_reindex_level(self):
self.df_level.reindex(self.index, level=1)
class DropDuplicates(object):
params = [True, False]
param_names = ['inplace']
def setup(self, inplace):
N = 10000
K = 10
key1 = tm.makeStringIndex(N).values.repeat(K)
key2 = tm.makeStringIndex(N).values.repeat(K)
self.df = DataFrame({'key1': key1, 'key2': key2,
'value': np.random.randn(N * K)})
self.df_nan = self.df.copy()
self.df_nan.iloc[:10000, :] = np.nan
self.s = Series(np.random.randint(0, 1000, size=10000))
self.s_str = Series(np.tile(tm.makeStringIndex(1000).values, 10))
N = 1000000
K = 10000
key1 = np.random.randint(0, K, size=N)
self.df_int = DataFrame({'key1': key1})
self.df_bool = DataFrame(np.random.randint(0, 2, size=(K, 10),
dtype=bool))
def time_frame_drop_dups(self, inplace):
self.df.drop_duplicates(['key1', 'key2'], inplace=inplace)
def time_frame_drop_dups_na(self, inplace):
self.df_nan.drop_duplicates(['key1', 'key2'], inplace=inplace)
def time_series_drop_dups_int(self, inplace):
self.s.drop_duplicates(inplace=inplace)
def time_series_drop_dups_string(self, inplace):
self.s_str.drop_duplicates(inplace=inplace)
def time_frame_drop_dups_int(self, inplace):
self.df_int.drop_duplicates(inplace=inplace)
def time_frame_drop_dups_bool(self, inplace):
self.df_bool.drop_duplicates(inplace=inplace)
class Align(object):
# blog "pandas escaped the zoo"
def setup(self):
n = 50000
indices = tm.makeStringIndex(n)
subsample_size = 40000
self.x = Series(np.random.randn(n), indices)
self.y = Series(np.random.randn(subsample_size),
index=np.random.choice(indices, subsample_size,
replace=False))
def time_align_series_irregular_string(self):
self.x + self.y
class LibFastZip(object):
def setup(self):
N = 10000
K = 10
key1 = tm.makeStringIndex(N).values.repeat(K)
key2 = tm.makeStringIndex(N).values.repeat(K)
col_array = np.vstack([key1, key2, np.random.randn(N * K)])
col_array2 = col_array.copy()
col_array2[:, :10000] = np.nan
self.col_array_list = list(col_array)
def time_lib_fast_zip(self):
lib.fast_zip(self.col_array_list)
from .pandas_vb_common import setup # noqa: F401