python - 输入类型不支持 ufunc 'isfinite'，并且无法安全地将输入强制转换为支持的类型 - 想要降级整数列
问题描述
我正在尝试通过将 dtype 'int64' 的列向下转换为 'unsigned' 来优化我的数据框，但实际上具有负值的一列除外。对于那一列，我只想将它从“int64”单独转换为“int8”。但是，当我使用以下代码完成此操作时，出现错误：
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
我正在使用的代码是：
def mem_usage(pandas_obj):
if isinstance(pandas_obj,pd.DataFrame):
usage_b = pandas_obj.memory_usage(deep=True).sum()
else: # we assume if not a df it's a series
usage_b = pandas_obj.memory_usage(deep=True)
usage_mb = usage_b / 1024 ** 2 # convert bytes to megabytes
return "{:03.2f} MB".format(usage_mb)
dtypes = data_pitch_2017_1.drop('launch_angle',axis=1).dtypes
data_pitch_2017_1_int = data_pitch_2017_1.select_dtypes(include=['int'])
converted_int = data_pitch_2017_1_int.apply(pd.to_numeric,downcast='unsigned', errors ='ignore')
print(mem_usage(data_pitch_2017_1_int))
print(mem_usage(converted_int))
compare_ints = pd.concat([data_pitch_2017_1_int.dtypes,converted_int.dtypes],axis=1)
compare_ints.columns = ['before','after']
compare_ints.apply(pd.Series.value_counts)
我收到的完整错误代码是：
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-77-8486ea5172f1> in <module>
8 dtypes = data_pitch_2017_1.drop('launch_angle',axis=1).dtypes
9 data_pitch_2017_1_int = data_pitch_2017_1.select_dtypes(include=['int'])
---> 10 converted_int = data_pitch_2017_1_int.apply(pd.to_numeric,downcast='unsigned', errors ='ignore')
11 print(mem_usage(data_pitch_2017_1_int))
12 print(mem_usage(converted_int))
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py in apply(self, func, axis, raw, result_type, args, **kwds)
7766 kwds=kwds,
7767 )
-> 7768 return op.get_result()
7769
7770 def applymap(self, func, na_action: Optional[str] = None) -> DataFrame:
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/pandas/core/apply.py in get_result(self)
183 return self.apply_raw()
184
--> 185 return self.apply_standard()
186
187 def apply_empty_result(self):
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/pandas/core/apply.py in apply_standard(self)
274
275 def apply_standard(self):
--> 276 results, res_index = self.apply_series_generator()
277
278 # wrap results
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/pandas/core/apply.py in apply_series_generator(self)
288 for i, v in enumerate(series_gen):
289 # ignore SettingWithCopy here in case the user mutates
--> 290 results[i] = self.f(v)
291 if isinstance(results[i], ABCSeries):
292 # If we have a view on v, we need to make a copy because
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/pandas/core/apply.py in f(x)
108
109 def f(x):
--> 110 return func(x, *args, **kwds)
111
112 else:
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/pandas/core/tools/numeric.py in to_numeric(arg, errors, downcast)
182 for dtype in typecodes:
183 if np.dtype(dtype).itemsize <= values.dtype.itemsize:
--> 184 values = maybe_downcast_to_dtype(values, dtype)
185
186 # successful conversion
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/pandas/core/dtypes/cast.py in maybe_downcast_to_dtype(result, dtype)
203 return PeriodArray(result, freq=dtype.freq)
204
--> 205 converted = maybe_downcast_numeric(result, dtype, do_round)
206 if converted is not result:
207 return converted
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/pandas/core/dtypes/cast.py in maybe_downcast_numeric(result, dtype, do_round)
284 return new_result
285 else:
--> 286 if np.allclose(new_result, result, rtol=0):
287 return new_result
288
<__array_function__ internals> in allclose(*args, **kwargs)
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/numpy/core/numeric.py in allclose(a, b, rtol, atol, equal_nan)
2187
2188 """
-> 2189 res = all(isclose(a, b, rtol=rtol, atol=atol, equal_nan=equal_nan))
2190 return bool(res)
2191
<__array_function__ internals> in isclose(*args, **kwargs)
/Volumes/DATASTORE_L/opt/anaconda3/lib/python3.7/site-packages/numpy/core/numeric.py in isclose(a, b, rtol, atol, equal_nan)
2286
2287 xfin = isfinite(x)
-> 2288 yfin = isfinite(y)
2289 if all(xfin) and all(yfin):
2290 return within_tol(x, y, atol, rtol)
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
我确实尝试包含代码errors ='ignore'以忽略可能导致错误的任何 Nan 值或非数字值。
但我仍然没有成功。
数据框信息为：
<class 'pandas.core.frame.DataFrame'>
Int64Index: 721244 entries, 0 to 721243
Data columns (total 85 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 pitcher 721244 non-null int64
1 key_retro 721244 non-null object
2 pitch_type 718006 non-null object
3 Game_Date 721244 non-null datetime64[ns]
4 release_speed 717883 non-null Float64
5 release_pos_x 717862 non-null Float64
6 release_pos_z 717862 non-null Float64
7 player_name 721244 non-null object
8 batter 721244 non-null Int64
9 events 184565 non-null object
10 description 721244 non-null object
11 zone 717862 non-null Int64
12 des 721244 non-null object
13 game_type 721244 non-null object
14 stand 721244 non-null object
15 p_throws 721244 non-null object
16 home_team 721244 non-null object
17 away_team 721244 non-null object
18 type 721244 non-null object
19 hit_location 161307 non-null Int64
20 bb_type 127555 non-null object
21 balls 721244 non-null Int64
22 strikes 721244 non-null Int64
23 game_year 721244 non-null Int64
24 pfx_x 717862 non-null Float64
25 pfx_z 717862 non-null Float64
26 plate_x 717862 non-null Float64
27 plate_z 717862 non-null Float64
28 on_3b 67052 non-null Int64
29 on_2b 132754 non-null Int64
30 on_1b 220388 non-null Int64
31 outs_when_up 721244 non-null Int64
32 inning 721244 non-null Int64
33 inning_topbot 721244 non-null object
34 hc_x 124661 non-null Float64
35 hc_y 124661 non-null Float64
36 fielder_2 719473 non-null Int64
37 vx0 717862 non-null Float64
38 vy0 717862 non-null Float64
39 vz0 717862 non-null Float64
40 ax 717862 non-null Float64
41 ay 717862 non-null Float64
42 az 717862 non-null Float64
43 sz_top 717862 non-null Float64
44 sz_bot 717862 non-null Float64
45 hit_distance_sc 188244 non-null Int64
46 launch_speed 199437 non-null Float64
47 launch_angle 199441 non-null Int64
48 effective_speed 716330 non-null Float64
49 release_spin_rate 703603 non-null Int64
50 release_extension 717862 non-null Float64
51 game_pk 721244 non-null Int64
52 pitcher.1 721244 non-null Int64
53 fielder_2.1 719473 non-null Int64
54 fielder_3 719473 non-null Int64
55 fielder_4 719473 non-null Int64
56 fielder_5 719473 non-null Int64
57 fielder_6 719473 non-null Int64
58 fielder_7 719473 non-null Int64
59 fielder_8 719473 non-null Int64
60 fielder_9 719473 non-null Int64
61 release_pos_y 717862 non-null Float64
62 estimated_ba_using_speedangle 125403 non-null Float64
63 estimated_woba_using_speedangle 125403 non-null Float64
64 woba_value 184565 non-null Float64
65 woba_denom 184565 non-null Int64
66 babip_value 184565 non-null Int64
67 iso_value 184565 non-null Int64
68 launch_speed_angle 125403 non-null Int64
69 at_bat_number 721244 non-null Int64
70 pitch_number 721244 non-null Int64
71 pitch_name 718006 non-null object
72 home_score 721244 non-null Int64
73 away_score 721244 non-null Int64
74 bat_score 721244 non-null Int64
75 fld_score 721244 non-null Int64
76 post_away_score 721244 non-null Int64
77 post_home_score 721244 non-null Int64
78 post_bat_score 721244 non-null Int64
79 post_fld_score 721244 non-null Int64
80 if_fielding_alignment 717029 non-null object
81 of_fielding_alignment 717029 non-null object
82 spin_axis 717862 non-null Int64
83 delta_home_win_exp 721243 non-null Float64
84 delta_run_exp 721121 non-null Float64
dtypes: Float64(26), Int64(40), datetime64[ns](1), int64(1), object(17)
memory usage: 1.1 GB
有人可以帮助解决问题以及如何在代码中解决问题吗？
谢谢你。
解决方案
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