Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly
Sign up
Appearance settings

Commit 8c63f73

Browse files
Fix Bug Edit arg precision to display precision
Fix Bug Edit argument precision to display precision
1 parent 27b96ab commit 8c63f73

File tree

1 file changed

+195
-14
lines changed

1 file changed

+195
-14
lines changed

‎notebooks/PortfolioManagementClusteringInvestors.ipynb‎

Lines changed: 195 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -376,29 +376,210 @@
376376
},
377377
{
378378
"cell_type": "code",
379-
"execution_count": 8,
379+
"execution_count": 9,
380380
"metadata": {
381381
"_cell_guid": "7bffeec0-5bbc-fffb-18f2-3da56b862ca3"
382382
},
383383
"outputs": [
384384
{
385-
"ename": "OptionError",
386-
"evalue": "'Pattern matched multiple keys'",
387-
"output_type": "error",
388-
"traceback": [
389-
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
390-
"\u001b[1;31mOptionError\u001b[0m Traceback (most recent call last)",
391-
"Cell \u001b[1;32mIn[8], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[39m# describe data\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m set_option(\u001b[39m'\u001b[39;49m\u001b[39mprecision\u001b[39;49m\u001b[39m'\u001b[39;49m, \u001b[39m3\u001b[39;49m)\n\u001b[0;32m 3\u001b[0m dataset\u001b[39m.\u001b[39mdescribe()\n",
392-
"File \u001b[1;32mc:\\Users\\steph\\OneDrive\\Documents\\40-ML-going-forward\\26-unsupervised-learning-clustering\\container\\unsupervised-learning-clustering\\.venv\\lib\\site-packages\\pandas\\_config\\config.py:261\u001b[0m, in \u001b[0;36mCallableDynamicDoc.__call__\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m 260\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m__call__\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwds) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m T:\n\u001b[1;32m--> 261\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__func__\u001b[39m(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwds)\n",
393-
"File \u001b[1;32mc:\\Users\\steph\\OneDrive\\Documents\40円-ML-going-forward\26円-unsupervised-learning-clustering\\container\\unsupervised-learning-clustering\\.venv\\lib\\site-packages\\pandas\\_config\\config.py:156\u001b[0m, in \u001b[0;36m_set_option\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 153\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mTypeError\u001b[39;00m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39m_set_option() got an unexpected keyword argument \u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mkwarg\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m 155\u001b[0m \u001b[39mfor\u001b[39;00m k, v \u001b[39min\u001b[39;00m \u001b[39mzip\u001b[39m(args[::\u001b[39m2\u001b[39m], args[\u001b[39m1\u001b[39m::\u001b[39m2\u001b[39m]):\n\u001b[1;32m--> 156\u001b[0m key \u001b[39m=\u001b[39m _get_single_key(k, silent)\n\u001b[0;32m 158\u001b[0m o \u001b[39m=\u001b[39m _get_registered_option(key)\n\u001b[0;32m 159\u001b[0m \u001b[39mif\u001b[39;00m o \u001b[39mand\u001b[39;00m o\u001b[39m.\u001b[39mvalidator:\n",
394-
"File \u001b[1;32mc:\\Users\\steph\\OneDrive\\Documents\40円-ML-going-forward\26円-unsupervised-learning-clustering\\container\\unsupervised-learning-clustering\\.venv\\lib\\site-packages\\pandas\\_config\\config.py:123\u001b[0m, in \u001b[0;36m_get_single_key\u001b[1;34m(pat, silent)\u001b[0m\n\u001b[0;32m 121\u001b[0m \u001b[39mraise\u001b[39;00m OptionError(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mNo such keys(s): \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mrepr\u001b[39m(pat)\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n\u001b[0;32m 122\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(keys) \u001b[39m>\u001b[39m \u001b[39m1\u001b[39m:\n\u001b[1;32m--> 123\u001b[0m \u001b[39mraise\u001b[39;00m OptionError(\u001b[39m\"\u001b[39m\u001b[39mPattern matched multiple keys\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m 124\u001b[0m key \u001b[39m=\u001b[39m keys[\u001b[39m0\u001b[39m]\n\u001b[0;32m 126\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m silent:\n",
395-
"\u001b[1;31mOptionError\u001b[0m: 'Pattern matched multiple keys'"
396-
]
385+
"data": {
386+
"text/html": [
387+
"<div>\n",
388+
"<style scoped>\n",
389+
" .dataframe tbody tr th:only-of-type {\n",
390+
" vertical-align: middle;\n",
391+
" }\n",
392+
"\n",
393+
" .dataframe tbody tr th {\n",
394+
" vertical-align: top;\n",
395+
" }\n",
396+
"\n",
397+
" .dataframe thead th {\n",
398+
" text-align: right;\n",
399+
" }\n",
400+
"</style>\n",
401+
"<table border=\"1\" class=\"dataframe\">\n",
402+
" <thead>\n",
403+
" <tr style=\"text-align: right;\">\n",
404+
" <th></th>\n",
405+
" <th>ID</th>\n",
406+
" <th>AGE</th>\n",
407+
" <th>EDUC</th>\n",
408+
" <th>MARRIED</th>\n",
409+
" <th>KIDS</th>\n",
410+
" <th>LIFECL</th>\n",
411+
" <th>OCCAT</th>\n",
412+
" <th>RISK</th>\n",
413+
" <th>HHOUSES</th>\n",
414+
" <th>WSAVED</th>\n",
415+
" <th>SPENDMOR</th>\n",
416+
" <th>NWCAT</th>\n",
417+
" <th>INCCL</th>\n",
418+
" </tr>\n",
419+
" </thead>\n",
420+
" <tbody>\n",
421+
" <tr>\n",
422+
" <th>count</th>\n",
423+
" <td>3866.000</td>\n",
424+
" <td>3866.000</td>\n",
425+
" <td>3866.000</td>\n",
426+
" <td>3866.000</td>\n",
427+
" <td>3866.000</td>\n",
428+
" <td>3866.000</td>\n",
429+
" <td>3866.000</td>\n",
430+
" <td>3866.000</td>\n",
431+
" <td>3866.000</td>\n",
432+
" <td>3866.000</td>\n",
433+
" <td>3866.000</td>\n",
434+
" <td>3866.000</td>\n",
435+
" <td>3866.000</td>\n",
436+
" </tr>\n",
437+
" <tr>\n",
438+
" <th>mean</th>\n",
439+
" <td>1933.500</td>\n",
440+
" <td>3.107</td>\n",
441+
" <td>2.906</td>\n",
442+
" <td>1.353</td>\n",
443+
" <td>0.938</td>\n",
444+
" <td>3.697</td>\n",
445+
" <td>1.742</td>\n",
446+
" <td>3.043</td>\n",
447+
" <td>0.717</td>\n",
448+
" <td>2.446</td>\n",
449+
" <td>3.561</td>\n",
450+
" <td>2.976</td>\n",
451+
" <td>3.671</td>\n",
452+
" </tr>\n",
453+
" <tr>\n",
454+
" <th>std</th>\n",
455+
" <td>1116.162</td>\n",
456+
" <td>1.513</td>\n",
457+
" <td>1.066</td>\n",
458+
" <td>0.478</td>\n",
459+
" <td>1.249</td>\n",
460+
" <td>1.618</td>\n",
461+
" <td>0.934</td>\n",
462+
" <td>0.879</td>\n",
463+
" <td>0.451</td>\n",
464+
" <td>0.743</td>\n",
465+
" <td>1.304</td>\n",
466+
" <td>1.463</td>\n",
467+
" <td>1.184</td>\n",
468+
" </tr>\n",
469+
" <tr>\n",
470+
" <th>min</th>\n",
471+
" <td>1.000</td>\n",
472+
" <td>1.000</td>\n",
473+
" <td>1.000</td>\n",
474+
" <td>1.000</td>\n",
475+
" <td>0.000</td>\n",
476+
" <td>1.000</td>\n",
477+
" <td>1.000</td>\n",
478+
" <td>1.000</td>\n",
479+
" <td>0.000</td>\n",
480+
" <td>1.000</td>\n",
481+
" <td>1.000</td>\n",
482+
" <td>1.000</td>\n",
483+
" <td>1.000</td>\n",
484+
" </tr>\n",
485+
" <tr>\n",
486+
" <th>25%</th>\n",
487+
" <td>967.250</td>\n",
488+
" <td>2.000</td>\n",
489+
" <td>2.000</td>\n",
490+
" <td>1.000</td>\n",
491+
" <td>0.000</td>\n",
492+
" <td>3.000</td>\n",
493+
" <td>1.000</td>\n",
494+
" <td>2.000</td>\n",
495+
" <td>0.000</td>\n",
496+
" <td>2.000</td>\n",
497+
" <td>2.000</td>\n",
498+
" <td>2.000</td>\n",
499+
" <td>3.000</td>\n",
500+
" </tr>\n",
501+
" <tr>\n",
502+
" <th>50%</th>\n",
503+
" <td>1933.500</td>\n",
504+
" <td>3.000</td>\n",
505+
" <td>3.000</td>\n",
506+
" <td>1.000</td>\n",
507+
" <td>0.000</td>\n",
508+
" <td>3.000</td>\n",
509+
" <td>1.000</td>\n",
510+
" <td>3.000</td>\n",
511+
" <td>1.000</td>\n",
512+
" <td>3.000</td>\n",
513+
" <td>4.000</td>\n",
514+
" <td>3.000</td>\n",
515+
" <td>4.000</td>\n",
516+
" </tr>\n",
517+
" <tr>\n",
518+
" <th>75%</th>\n",
519+
" <td>2899.750</td>\n",
520+
" <td>4.000</td>\n",
521+
" <td>4.000</td>\n",
522+
" <td>2.000</td>\n",
523+
" <td>2.000</td>\n",
524+
" <td>5.000</td>\n",
525+
" <td>3.000</td>\n",
526+
" <td>4.000</td>\n",
527+
" <td>1.000</td>\n",
528+
" <td>3.000</td>\n",
529+
" <td>5.000</td>\n",
530+
" <td>4.000</td>\n",
531+
" <td>5.000</td>\n",
532+
" </tr>\n",
533+
" <tr>\n",
534+
" <th>max</th>\n",
535+
" <td>3866.000</td>\n",
536+
" <td>6.000</td>\n",
537+
" <td>4.000</td>\n",
538+
" <td>2.000</td>\n",
539+
" <td>8.000</td>\n",
540+
" <td>6.000</td>\n",
541+
" <td>4.000</td>\n",
542+
" <td>4.000</td>\n",
543+
" <td>1.000</td>\n",
544+
" <td>3.000</td>\n",
545+
" <td>5.000</td>\n",
546+
" <td>5.000</td>\n",
547+
" <td>5.000</td>\n",
548+
" </tr>\n",
549+
" </tbody>\n",
550+
"</table>\n",
551+
"</div>"
552+
],
553+
"text/plain": [
554+
" ID AGE EDUC MARRIED KIDS LIFECL OCCAT RISK HHOUSES \n",
555+
"count 3866.000 3866.000 3866.000 3866.000 3866.000 3866.000 3866.000 3866.000 3866.000 \\\n",
556+
"mean 1933.500 3.107 2.906 1.353 0.938 3.697 1.742 3.043 0.717 \n",
557+
"std 1116.162 1.513 1.066 0.478 1.249 1.618 0.934 0.879 0.451 \n",
558+
"min 1.000 1.000 1.000 1.000 0.000 1.000 1.000 1.000 0.000 \n",
559+
"25% 967.250 2.000 2.000 1.000 0.000 3.000 1.000 2.000 0.000 \n",
560+
"50% 1933.500 3.000 3.000 1.000 0.000 3.000 1.000 3.000 1.000 \n",
561+
"75% 2899.750 4.000 4.000 2.000 2.000 5.000 3.000 4.000 1.000 \n",
562+
"max 3866.000 6.000 4.000 2.000 8.000 6.000 4.000 4.000 1.000 \n",
563+
"\n",
564+
" WSAVED SPENDMOR NWCAT INCCL \n",
565+
"count 3866.000 3866.000 3866.000 3866.000 \n",
566+
"mean 2.446 3.561 2.976 3.671 \n",
567+
"std 0.743 1.304 1.463 1.184 \n",
568+
"min 1.000 1.000 1.000 1.000 \n",
569+
"25% 2.000 2.000 2.000 3.000 \n",
570+
"50% 3.000 4.000 3.000 4.000 \n",
571+
"75% 3.000 5.000 4.000 5.000 \n",
572+
"max 3.000 5.000 5.000 5.000 "
573+
]
574+
},
575+
"execution_count": 9,
576+
"metadata": {},
577+
"output_type": "execute_result"
397578
}
398579
],
399580
"source": [
400581
"# describe data\n",
401-
"set_option('precision', 3)\n",
582+
"set_option('display.precision', 3)\n",
402583
"dataset.describe()"
403584
]
404585
},

0 commit comments

Comments
(0)

AltStyle によって変換されたページ (->オリジナル) /