9
9
10
10
from pandas import NaT , Series , Timestamp , date_range
11
11
from pandas .api .types import CategoricalDtype
12
- from pandas .tests .series .common import TestData
13
12
import pandas .util .testing as tm
14
13
from pandas .util .testing import assert_series_equal
15
14
16
15
17
- class TestSeriesRank ( TestData ) :
16
+ class TestSeriesRank :
18
17
s = Series ([1 , 3 , 4 , 2 , np .nan , 2 , 1 , 5 , np .nan , 3 ])
19
18
20
19
results = {
@@ -25,20 +24,20 @@ class TestSeriesRank(TestData):
25
24
"dense" : np .array ([1 , 3 , 4 , 2 , np .nan , 2 , 1 , 5 , np .nan , 3 ]),
26
25
}
27
26
28
- def test_rank (self ):
27
+ def test_rank (self , datetime_series ):
29
28
pytest .importorskip ("scipy.stats.special" )
30
29
rankdata = pytest .importorskip ("scipy.stats.rankdata" )
31
30
32
- self . ts [::2 ] = np .nan
33
- self . ts [:10 ][::3 ] = 4.0
31
+ datetime_series [::2 ] = np .nan
32
+ datetime_series [:10 ][::3 ] = 4.0
34
33
35
- ranks = self . ts .rank ()
36
- oranks = self . ts .astype ("O" ).rank ()
34
+ ranks = datetime_series .rank ()
35
+ oranks = datetime_series .astype ("O" ).rank ()
37
36
38
37
assert_series_equal (ranks , oranks )
39
38
40
- mask = np .isnan (self . ts )
41
- filled = self . ts .fillna (np .inf )
39
+ mask = np .isnan (datetime_series )
40
+ filled = datetime_series .fillna (np .inf )
42
41
43
42
# rankdata returns a ndarray
44
43
exp = Series (rankdata (filled ), index = filled .index , name = "ts" )
0 commit comments