forked from pandas-dev/pandas
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathframe_methods.py
115 lines (84 loc) · 3.31 KB
/
frame_methods.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
from vbench.api import Benchmark
from datetime import datetime
common_setup = """from pandas_vb_common import *
"""
#----------------------------------------------------------------------
# lookup
setup = common_setup + """
df = DataFrame(np.random.randn(10000, 8), columns=list('abcdefgh'))
df['foo'] = 'bar'
row_labels = list(df.index[::10])[:900]
col_labels = list(df.columns) * 100
row_labels_all = np.array(list(df.index) * len(df.columns), dtype='object')
col_labels_all = np.array(list(df.columns) * len(df.index), dtype='object')
"""
frame_fancy_lookup = Benchmark('df.lookup(row_labels, col_labels)', setup,
start_date=datetime(2012, 1, 12))
frame_fancy_lookup_all = Benchmark('df.lookup(row_labels_all, col_labels_all)',
setup,
start_date=datetime(2012, 1, 12))
#----------------------------------------------------------------------
# fillna in place
setup = common_setup + """
df = DataFrame(randn(10000, 100))
df.values[::2] = np.nan
"""
frame_fillna_inplace = Benchmark('df.fillna(0, inplace=True)', setup,
start_date=datetime(2012, 4, 4))
#----------------------------------------------------------------------
# reindex both axes
setup = common_setup + """
df = DataFrame(randn(1000, 1000))
idx = np.arange(400, 700)
"""
frame_reindex_axis0 = Benchmark('df.reindex(idx)', setup)
frame_reindex_axis1 = Benchmark('df.reindex(columns=idx)', setup)
frame_reindex_both_axes = Benchmark('df.reindex(index=idx, columns=idx)',
setup, start_date=datetime(2011, 1, 1))
frame_reindex_both_axes_ix = Benchmark('df.ix[idx, idx]', setup,
start_date=datetime(2011, 1, 1))
#----------------------------------------------------------------------
# boolean indexing
setup = common_setup + """
df = DataFrame(randn(10000, 100))
bool_arr = np.zeros(10000, dtype=bool)
bool_arr[:1000] = True
"""
frame_boolean_row_select = Benchmark('df[bool_arr]', setup,
start_date=datetime(2011, 1, 1))
#----------------------------------------------------------------------
# iteritems (monitor no-copying behaviour)
setup = common_setup + """
df = DataFrame(randn(10000, 100))
def f():
if hasattr(df, '_item_cache'):
df._item_cache.clear()
for name, col in df.iteritems():
pass
def g():
for name, col in df.iteritems():
pass
"""
# as far back as the earliest test currently in the suite
frame_iteritems = Benchmark('f()', setup,
start_date=datetime(2010, 6, 1))
frame_iteritems_cached = Benchmark('g()', setup,
start_date=datetime(2010, 6, 1))
#----------------------------------------------------------------------
# to_string
setup = common_setup + """
df = DataFrame(randn(100, 10))
"""
frame_to_string_floats = Benchmark('df.to_string()', setup,
start_date=datetime(2010, 6, 1))
# insert many columns
setup = common_setup + """
N = 1000
def f(K=500):
df = DataFrame(index=range(N))
new_col = np.random.randn(N)
for i in range(K):
df[i] = new_col
"""
frame_insert_500_columns = Benchmark('f()', setup,
start_date=datetime(2011, 1, 1))