Lines Matching refs:iloc
72 assert ser.iloc._is_scalar_access((1,))
75 assert df.iloc._is_scalar_access((1, 0))
86 df.iloc[:, [0, 1, 2, 3, 4, 5]]
88 df.iloc[[1, 30]]
90 df.iloc[[1, -30]]
92 df.iloc[[100]]
96 s.iloc[[100]]
98 s.iloc[[-100]]
103 df.iloc[30]
105 df.iloc[-30]
111 s.iloc[30]
113 s.iloc[-30]
116 result = df.iloc[:, 4:10] # 0 < start < len < stop
117 expected = df.iloc[:, 4:]
120 result = df.iloc[:, -4:-10] # stop < 0 < start < len
121 expected = df.iloc[:, :0]
124 result = df.iloc[:, 10:4:-1] # 0 < stop < len < start (down)
125 expected = df.iloc[:, :4:-1]
128 result = df.iloc[:, 4:-10:-1] # stop < 0 < start < len (down)
129 expected = df.iloc[:, 4::-1]
132 result = df.iloc[:, -10:4] # start < 0 < stop < len
133 expected = df.iloc[:, :4]
136 result = df.iloc[:, 10:4] # 0 < stop < len < start
137 expected = df.iloc[:, :0]
140 result = df.iloc[:, -10:-11:-1] # stop < start < 0 < len (down)
141 expected = df.iloc[:, :0]
144 result = df.iloc[:, 10:11] # 0 < len < start < stop
145 expected = df.iloc[:, :0]
149 result = s.iloc[18:30]
150 expected = s.iloc[18:]
153 result = s.iloc[30:]
154 expected = s.iloc[:0]
157 result = s.iloc[30::-1]
158 expected = s.iloc[::-1]
168 check(dfl.iloc[:, 2:3], DataFrame(index=dfl.index))
169 check(dfl.iloc[:, 1:3], dfl.iloc[:, [1]])
170 check(dfl.iloc[4:6], dfl.iloc[[4]])
174 dfl.iloc[[4, 5, 6]]
177 dfl.iloc[:, 4]
195 df.iloc[index_vals, column_vals]
207 s.iloc["a"]
218 df.iloc[array_with_neg_numbers]
220 df.iloc[:, array_with_neg_numbers]
229 expected = df.iloc[0]
230 result = df.iloc[-3]
233 expected = df.iloc[[0]]
234 result = df.iloc[[-3]]
237 expected = s.iloc[0]
238 result = s.iloc[-3]
241 expected = s.iloc[[0]]
242 result = s.iloc[[-3]]
247 result = expected.iloc[[-1]]
257 result = df.iloc[0, 0]
260 result = df.iloc[0, :]
278 _ = s.iloc[index]
293 tm.assert_frame_equal(df.iloc[:, :4], df1)
294 tm.assert_frame_equal(df.iloc[:, 4:], df2)
297 tm.assert_frame_equal(df.iloc[:, :2], df2)
298 tm.assert_frame_equal(df.iloc[:, 2:], df1)
300 exp = concat([df2, df1.iloc[:, [0]]], axis=1)
301 tm.assert_frame_equal(df.iloc[:, 0:3], exp)
305 tm.assert_frame_equal(df.iloc[0:10, :2], df2)
306 tm.assert_frame_equal(df.iloc[0:10, 2:], df1)
307 tm.assert_frame_equal(df.iloc[10:, :2], df2)
308 tm.assert_frame_equal(df.iloc[10:, 2:], df1)
315 df.iloc[1, 1] = 1
316 result = df.iloc[1, 1]
319 df.iloc[:, 2:3] = 0
320 expected = df.iloc[:, 2:3]
321 result = df.iloc[:, 2:3]
326 s.iloc[1:2] += 1
336 df.iloc[[0, 1], [1, 2]]
337 df.iloc[[0, 1], [1, 2]] += 100
352 s.iloc[Series([1, 2])] = [-1, -2]
356 s.iloc[Index([1, 2])] = [-1, -2]
368 inds = np.isnan(df.iloc[:, 0])
370 df.iloc[mask, 0] = df.iloc[mask, 2]
380 df.iloc[[0, 1], [0, 1]] = df.iloc[[0, 1], [0, 1]]
384 df.iloc[[1, 0], [0, 1]] = df.iloc[[1, 0], [0, 1]].reset_index(drop=True)
385 df.iloc[[1, 0], [0, 1]] = df.iloc[[1, 0], [0, 1]].reset_index(drop=True)
393 df.iloc[:, 0] = df.iloc[:, 0].astype("f8")
398 df.iloc[[0, 1], [0, 1]] = df.iloc[[0, 1], [0, 1]]
409 result = df.iloc[2]
413 result = df.iloc[2, 2]
418 result = df.iloc[4:8]
422 result = df.iloc[:, 2:3]
427 result = df.iloc[[0, 1, 3]]
431 result = df.iloc[[0, 1, 3], [0, 1]]
436 result = df.iloc[[-1, 1, 3], [-1, 1]]
441 result = df.iloc[[-1, -1, 1, 3], [-1, 1]]
447 result = df.iloc[s.index]
457 result = df.iloc[1, 1]
461 result = df.iloc[:, 2:3]
466 result = df.iloc[-1, -1]
473 df.iloc[10, 5]
482 df.iloc["j", "D"]
497 result = df.iloc[3:5, 0:2]
506 result = df.iloc[3:5, 0:2]
520 result = df.iloc[1:5, 2:4]
531 df.iloc[1, 1] = 1
532 result = df.iloc[1, 1]
535 df.iloc[:, 2:3] = 0
536 expected = df.iloc[:, 2:3]
537 result = df.iloc[:, 2:3]
542 s.iloc[1] = 1
543 result = s.iloc[1]
546 s.iloc[:4] = 0
547 expected = s.iloc[:4]
548 result = s.iloc[:4]
552 s.iloc[0::2] = [0, 2, 4]
553 s.iloc[1::2] = [1, 3, 5]
565 df.iloc[2:4] = [[10, 11], [12, 13]]
572 df.iloc[2:4] = [["x", 11], ["y", 13]]
584 df.iloc[0, indexer] = value
585 result = df.iloc[0, 0]
596 df.iloc[mask]
600 df.iloc[mask]
603 result = df.iloc[np.array([True] * len(mask), dtype=bool)]
665 expected = df.iloc[idx]
668 result = df3.iloc[idx]
683 df.iloc[:, []],
684 df.iloc[:, :0],
690 df.iloc[[], :],
691 df.iloc[:0, :],
697 df.iloc[[]], df.iloc[:0, :], check_index_type=True, check_column_type=True
703 sliced_df = original_df.iloc[:]
711 sliced_series = original_series.iloc[:]
721 result = df.iloc[np.array(0)]
728 result = s.iloc[np.array(0)]
738 df.iloc[:, 0] = cat[::-1]
746 result.iloc[result.index <= 2] *= 2
750 result.iloc[result.index > 2] *= 2
754 result.iloc[[True, True, False, False]] *= 2
758 result.iloc[[False, False, True, True]] /= 2
765 result = df.iloc[0]
778 result = ser.iloc[0:2]
783 result = ser.iloc[[0, 1]]
788 result = ser.iloc[[True, False, False]]
796 series.iloc[0] = value
807 obj.iloc[nd3] = 0
809 @pytest.mark.parametrize("indexer", [lambda x: x.loc, lambda x: x.iloc])
831 result = df.iloc[indices]
835 result = df["data"].iloc[indices]
842 df.iloc[0, 0] = Series([1, 2, 3])
851 df.iloc[indexer, 1] = df.iloc[indexer, 1] * 2
860 df2.iloc[:, indexer] = df1.iloc[:, [0]]
868 df.iloc[1] = rhs
890 obj.iloc[3.0]
893 obj.iloc[3.0] = 0
902 df.iloc[0, 0] = -1
904 assert df.iloc[0, 0] == -1
905 assert df.iloc[0, 2] == 3
906 assert df.dtypes.iloc[2] == np.int64
912 df.iloc[:, 2] = ["str3"]
921 df.iloc[:, 0] = df.iloc[:, 0].astype(np.float64)
922 assert df.dtypes.iloc[2] == np.int64
931 res = df.iloc[lambda x: [1, 3]]
932 tm.assert_frame_equal(res, df.iloc[[1, 3]])
934 res = df.iloc[lambda x: [1, 3], :]
935 tm.assert_frame_equal(res, df.iloc[[1, 3], :])
937 res = df.iloc[lambda x: [1, 3], lambda x: 0]
938 tm.assert_series_equal(res, df.iloc[[1, 3], 0])
940 res = df.iloc[lambda x: [1, 3], lambda x: [0]]
941 tm.assert_frame_equal(res, df.iloc[[1, 3], [0]])
944 res = df.iloc[[1, 3], lambda x: 0]
945 tm.assert_series_equal(res, df.iloc[[1, 3], 0])
947 res = df.iloc[[1, 3], lambda x: [0]]
948 tm.assert_frame_equal(res, df.iloc[[1, 3], [0]])
950 res = df.iloc[lambda x: [1, 3], 0]
951 tm.assert_series_equal(res, df.iloc[[1, 3], 0])
953 res = df.iloc[lambda x: [1, 3], [0]]
954 tm.assert_frame_equal(res, df.iloc[[1, 3], [0]])
962 res.iloc[lambda x: [1, 3]] = 0
964 exp.iloc[[1, 3]] = 0
968 res.iloc[lambda x: [1, 3], :] = -1
970 exp.iloc[[1, 3], :] = -1
974 res.iloc[lambda x: [1, 3], lambda x: 0] = 5
976 exp.iloc[[1, 3], 0] = 5
980 res.iloc[lambda x: [1, 3], lambda x: [0]] = 25
982 exp.iloc[[1, 3], [0]] = 25
987 res.iloc[[1, 3], lambda x: 0] = -3
989 exp.iloc[[1, 3], 0] = -3
993 res.iloc[[1, 3], lambda x: [0]] = -5
995 exp.iloc[[1, 3], [0]] = -5
999 res.iloc[lambda x: [1, 3], 0] = 10
1001 exp.iloc[[1, 3], 0] = 10
1005 res.iloc[lambda x: [1, 3], [0]] = [-5, -5]
1007 exp.iloc[[1, 3], [0]] = [-5, -5]
1016 result = ser.iloc[i]
1021 result = ser.iloc[slice(1, 3)]
1030 result = ser.iloc[[0, 2, 3, 4, 5]]
1036 assert ser.iloc[2] == 2
1042 ser1.iloc[1:3] = ser2.iloc[1:3]