我正在尝试将我的数据集转换为正态分布。
0 8.298511e-03
1 3.055319e-01
2 6.938647e-02
3 2.904091e-02
4 7.422441e-02
5 6.074046e-02
6 9.265747e-04
7 7.521846e-02
8 5.960521e-02
9 7.405019e-04
10 3.086551e-02
11 5.444835e-02
12 2.259236e-02
13 4.691038e-02
14 6.463911e-02
15 2.172805e-02
16 8.210005e-02
17 2.301189e-02
18 4.073898e-07
19 4.639910e-02
20 1.662777e-02
21 8.662539e-02
22 4.436425e-02
23 4.557591e-02
24 3.499897e-02
25 2.788340e-02
26 1.707958e-02
27 1.506404e-02
28 3.207647e-02
29 2.147011e-03
30 2.972746e-02
31 1.028140e-01
32 2.183737e-02
33 9.063370e-03
34 3.070437e-02
35 1.477440e-02
36 1.036309e-02
37 2.000609e-01
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40 1.137169e-02
41 1.957088e-02
42 4.921303e-03
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63 6.565680e-02
64 9.825436e-04
65 9.353639e-02
66 6.535298e-02
67 6.979044e-04
68 2.772859e-02
69 4.378422e-02
70 2.020185e-02
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75 2.548934e-02
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80 4.294570e-02
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85 1.430836e-02
86 3.157232e-02
87 2.241722e-03
88 2.946256e-02
89 1.038383e-01
90 1.868837e-02
91 8.854596e-03
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101 4.497264e-02
102 4.030524e-02
103 8.627087e-02
104 3.248317e-02
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106 1.781355e-02
107 2.377991e-02
108 4.299568e-02
109 3.664353e-02
110 5.167902e-02
111 4.006848e-02
112 7.072990e-02
113 6.744938e-03
114 1.064900e-02
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118 6.817763e-02
119 2.588843e-02
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122 1.035536e-03
123 8.800684e-02
124 5.975065e-02
125 7.365861e-04
126 4.209485e-02
127 4.232421e-02
128 2.371866e-02
129 5.894714e-02
130 7.177195e-02
131 2.116566e-02
132 7.579219e-02
133 3.174744e-02
134 0.000000e+00
135 5.786439e-02
136 1.458493e-02
137 9.820156e-02
138 4.373873e-02
139 4.271649e-02
140 5.532575e-02
141 2.311324e-02
142 1.644508e-02
143 1.328273e-02
144 3.908473e-02
145 2.355468e-03
146 2.519321e-02
147 1.131868e-01
148 1.708967e-02
149 1.027661e-02
150 2.439899e-02
151 1.604058e-02
152 1.134323e-02
153 2.247722e-01
154 3.408590e-02
155 2.222239e-03
156 1.659830e-02
157 2.284733e-02
158 4.618550e-03
159 3.674162e-02
160 4.131283e-02
161 8.846273e-02
162 2.504404e-02
163 6.004396e-03
164 1.986309e-02
165 2.347111e-02
166 3.865636e-02
167 3.672307e-02
168 6.658419e-02
169 3.726879e-02
170 7.600138e-02
171 7.184871e-03
172 1.142840e-02
173 9.741311e-02
174 8.165448e-03
175 1.529210e-01
176 6.648081e-02
177 2.617601e-02
178 9.547816e-02
179 6.857775e-02
180 8.129399e-04
181 7.107914e-02
182 5.884794e-02
183 8.398721e-04
184 6.972981e-02
185 4.461767e-02
186 2.264404e-02
187 5.566633e-02
188 6.595136e-02
189 2.301914e-02
190 7.488919e-02
191 3.108619e-02
192 4.989364e-07
193 4.834949e-02
194 1.422578e-02
195 9.398186e-02
196 4.870391e-02
197 3.841369e-02
198 6.406801e-02
199 2.603315e-02
200 1.692629e-02
201 1.409982e-02
202 4.099215e-02
203 2.093724e-03
204 2.640732e-02
205 1.032129e-01
206 1.581881e-02
207 8.977325e-03
208 1.941141e-02
209 1.502126e-02
210 9.923589e-03
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212 3.096234e-02
213 4.388900e-03
214 1.784778e-02
215 2.179550e-02
216 3.944159e-03
217 3.703552e-02
218 4.033897e-02
219 1.157076e-01
220 2.400446e-02
221 5.761179e-03
222 1.899621e-02
223 2.401468e-02
224 4.458745e-02
225 3.357898e-02
226 5.331003e-02
227 3.488753e-02
228 7.466599e-02
229 6.075236e-03
230 9.815318e-03
231 9.598735e-02
232 7.103607e-03
233 1.100602e-01
234 5.677641e-02
235 2.420500e-02
236 9.213369e-02
237 4.024043e-02
238 6.987694e-04
239 8.612055e-02
240 5.663353e-02
241 4.871693e-04
242 4.533811e-02
243 3.593244e-02
244 1.982537e-02
245 5.490786e-02
246 5.603109e-02
247 1.671653e-02
248 6.522711e-02
249 3.341356e-02
250 2.378629e-06
251 4.299939e-02
252 1.223163e-02
253 8.392798e-02
254 4.272826e-02
255 3.183946e-02
256 4.431299e-02
257 2.661024e-02
258 1.686707e-02
259 4.070924e-03
260 3.325947e-02
261 2.023611e-03
262 2.402284e-02
263 8.369778e-02
264 1.375093e-02
265 8.899898e-03
266 2.148740e-02
267 1.301483e-02
268 8.355791e-03
269 2.549934e-01
270 2.792516e-02
271 4.652563e-03
272 1.556313e-02
273 1.936942e-02
274 3.547794e-03
275 3.412516e-02
276 3.932606e-02
277 5.305868e-02
278 2.354438e-02
279 5.379380e-03
280 1.904203e-02
281 2.045495e-02
282 3.275855e-02
283 3.007389e-02
284 8.227664e-02
285 2.479949e-02
286 6.573835e-02
287 5.165842e-03
288 7.599650e-03
289 9.613557e-02
290 6.690175e-03
291 1.779880e-01
292 5.076263e-02
293 3.117607e-02
294 7.495692e-02
295 3.707768e-02
296 7.086975e-04
297 8.935981e-02
298 5.624249e-02
299 7.105331e-04
300 3.339868e-02
301 3.354603e-02
302 2.041988e-02
303 3.862522e-02
304 5.977081e-02
305 1.730081e-02
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309 4.385336e-02
310 1.391891e-02
311 8.898305e-02
312 3.840141e-02
313 3.214408e-02
314 4.284080e-02
315 1.841022e-02
316 1.528207e-02
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318 3.945481e-02
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320 2.464190e-02
321 7.844914e-02
322 1.526590e-02
323 9.922147e-03
324 1.649218e-02
325 1.341602e-02
326 8.124446e-03
327 2.867380e-01
328 2.663867e-02
329 5.342012e-03
330 1.752612e-02
331 2.010863e-02
332 3.581845e-03
333 3.652284e-02
334 4.484362e-02
335 4.600939e-02
336 2.213280e-02
337 5.494917e-03
338 2.016594e-02
339 2.118010e-02
340 2.964000e-02
341 3.405549e-02
342 1.014185e-01
343 2.451624e-02
344 7.966998e-02
345 5.301538e-03
346 8.198895e-03
347 8.789368e-02
348 7.222417e-03
349 1.448276e-01
350 5.676056e-02
351 2.987054e-02
352 6.851434e-02
353 4.193034e-02
354 7.025054e-03
355 8.557358e-02
356 5.812736e-02
357 2.263676e-02
358 2.922588e-02
359 3.363161e-02
360 1.495056e-02
361 5.871619e-02
362 6.235094e-02
363 1.691340e-02
364 5.361939e-02
365 3.722318e-02
366 9.828477e-03
367 4.155345e-02
368 1.327760e-02
369 7.205372e-02
370 4.151130e-02
371 3.265365e-02
372 2.879418e-02
373 2.314340e-02
374 1.653692e-02
375 1.077611e-02
376 3.481427e-02
377 1.815487e-03
378 2.232305e-02
379 1.005192e-01
380 1.491262e-02
381 3.752658e-02
382 1.271613e-02
383 1.223707e-02
384 8.088923e-03
385 2.572550e-01
386 2.300194e-02
387 2.847960e-02
388 1.782098e-02
389 1.900759e-02
390 3.647629e-03
391 3.723368e-02
392 4.079514e-02
393 5.510332e-02
394 3.072313e-02
395 4.183566e-03
396 1.891549e-02
397 1.870293e-02
398 3.182769e-02
399 4.167840e-02
400 1.343152e-01
401 2.451973e-02
402 7.567017e-02
403 4.837843e-03
404 6.477297e-03
405 7.664675e-02
Name: value, dtype: float64
这是我用于转换数据集的代码:
from scipy import stats
x,_ = stats.boxcox(df)
I get this error:
if any(x <= 0):
-> 1031 raise ValueError("Data must be positive.")
1032
1033 if lmbda is not None: # single transformation
ValueError: Data must be positive
是因为我的值太小了,所以出现了错误吗?不确定我做错了什么。初次使用boxcox,可能在这个例子中使用不正确。欢迎提供建议和替代方案。谢谢!