Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells62448
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 MiB
Average record size in memory233.0 B

Variable types

Numeric10
Categorical8
DateTime1
Unsupported5
Text2

Alerts

cl_no is highly imbalanced (52.0%)Imbalance
card_at is highly imbalanced (57.6%)Imbalance
bssh_no has 1034 (10.3%) missing valuesMissing
gugun_cd has 1036 (10.4%) missing valuesMissing
prices has 10000 (100.0%) missing valuesMissing
rm has 9344 (93.4%) missing valuesMissing
bssh_nm has 10000 (100.0%) missing valuesMissing
la has 10000 (100.0%) missing valuesMissing
lo has 10000 (100.0%) missing valuesMissing
adres has 10000 (100.0%) missing valuesMissing
telno has 1034 (10.3%) missing valuesMissing
skey has unique valuesUnique
prices is an unsupported type, check if it needs cleaning or further analysisUnsupported
bssh_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported
la is an unsupported type, check if it needs cleaning or further analysisUnsupported
lo is an unsupported type, check if it needs cleaning or further analysisUnsupported
adres is an unsupported type, check if it needs cleaning or further analysisUnsupported
unitprice has 539 (5.4%) zerosZeros

Reproduction

Analysis started2024-04-17 10:01:11.097851
Analysis finished2024-04-17 10:01:11.621498
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82995.057
Minimum47934
Maximum118526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:11.679526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47934
5-th percentile51633.8
Q165668.75
median82962.5
Q3100439.75
95-th percentile114863.75
Maximum118526
Range70592
Interquartile range (IQR)34771

Descriptive statistics

Standard deviation20233.488
Coefficient of variation (CV)0.24379148
Kurtosis-1.1911535
Mean82995.057
Median Absolute Deviation (MAD)17386
Skewness0.017792339
Sum8.2995057 × 108
Variance4.0939402 × 108
MonotonicityNot monotonic
2024-04-17T19:01:11.804643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
73072 1
 
< 0.1%
55761 1
 
< 0.1%
117511 1
 
< 0.1%
89501 1
 
< 0.1%
55380 1
 
< 0.1%
50038 1
 
< 0.1%
77674 1
 
< 0.1%
116991 1
 
< 0.1%
69743 1
 
< 0.1%
116820 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
47934 1
< 0.1%
47935 1
< 0.1%
47939 1
< 0.1%
47941 1
< 0.1%
47948 1
< 0.1%
47950 1
< 0.1%
47952 1
< 0.1%
47973 1
< 0.1%
47982 1
< 0.1%
47988 1
< 0.1%
ValueCountFrequency (%)
118526 1
< 0.1%
118509 1
< 0.1%
118487 1
< 0.1%
118482 1
< 0.1%
118477 1
< 0.1%
118462 1
< 0.1%
118454 1
< 0.1%
118446 1
< 0.1%
118445 1
< 0.1%
118426 1
< 0.1%

ccode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.5459
Minimum108
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:11.928071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum108
5-th percentile113
Q1125
median135
Q3143
95-th percentile150
Maximum152
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.642132
Coefficient of variation (CV)0.087177011
Kurtosis-0.90051089
Mean133.5459
Median Absolute Deviation (MAD)9
Skewness-0.30698492
Sum1335459
Variance135.53925
MonotonicityNot monotonic
2024-04-17T19:01:12.057274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
143 335
 
3.4%
142 314
 
3.1%
146 311
 
3.1%
134 308
 
3.1%
141 306
 
3.1%
139 303
 
3.0%
137 301
 
3.0%
148 299
 
3.0%
144 298
 
3.0%
125 294
 
2.9%
Other values (35) 6931
69.3%
ValueCountFrequency (%)
108 68
 
0.7%
109 10
 
0.1%
110 103
1.0%
111 4
 
< 0.1%
112 255
2.5%
113 218
2.2%
114 224
2.2%
115 163
1.6%
116 158
1.6%
117 98
 
1.0%
ValueCountFrequency (%)
152 243
2.4%
151 235
2.4%
150 259
2.6%
149 277
2.8%
148 299
3.0%
147 293
2.9%
146 311
3.1%
145 142
1.4%
144 298
3.0%
143 335
3.4%

pcode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.5459
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:12.185345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1123
median133
Q3141
95-th percentile148
Maximum150
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.642132
Coefficient of variation (CV)0.088502435
Kurtosis-0.90051089
Mean131.5459
Median Absolute Deviation (MAD)9
Skewness-0.30698492
Sum1315459
Variance135.53925
MonotonicityNot monotonic
2024-04-17T19:01:12.308232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 335
 
3.4%
140 314
 
3.1%
144 311
 
3.1%
132 308
 
3.1%
139 306
 
3.1%
137 303
 
3.0%
135 301
 
3.0%
146 299
 
3.0%
142 298
 
3.0%
123 294
 
2.9%
Other values (35) 6931
69.3%
ValueCountFrequency (%)
106 68
 
0.7%
107 10
 
0.1%
108 103
1.0%
109 4
 
< 0.1%
110 255
2.5%
111 218
2.2%
112 224
2.2%
113 163
1.6%
114 158
1.6%
115 98
 
1.0%
ValueCountFrequency (%)
150 243
2.4%
149 235
2.4%
148 259
2.6%
147 277
2.8%
146 299
3.0%
145 293
2.9%
144 311
3.1%
143 142
1.4%
142 298
3.0%
141 335
3.4%

bssh_no
Real number (ℝ)

MISSING 

Distinct677
Distinct (%)7.6%
Missing1034
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean2141.7601
Minimum985
Maximum3197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:12.430523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum985
5-th percentile1044
Q11530
median2025
Q32792
95-th percentile3048
Maximum3197
Range2212
Interquartile range (IQR)1262

Descriptive statistics

Standard deviation679.8965
Coefficient of variation (CV)0.31744755
Kurtosis-1.400346
Mean2141.7601
Median Absolute Deviation (MAD)665
Skewness-0.11220414
Sum19203021
Variance462259.24
MonotonicityNot monotonic
2024-04-17T19:01:12.558010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1140 60
 
0.6%
2690 57
 
0.6%
1798 56
 
0.6%
1766 56
 
0.6%
2982 54
 
0.5%
2693 50
 
0.5%
2002 48
 
0.5%
1650 42
 
0.4%
1978 42
 
0.4%
1320 42
 
0.4%
Other values (667) 8459
84.6%
(Missing) 1034
 
10.3%
ValueCountFrequency (%)
985 6
 
0.1%
986 10
 
0.1%
988 16
 
0.2%
991 13
 
0.1%
996 40
0.4%
997 8
 
0.1%
998 11
 
0.1%
999 11
 
0.1%
1004 25
0.2%
1012 11
 
0.1%
ValueCountFrequency (%)
3197 1
 
< 0.1%
3196 1
 
< 0.1%
3195 1
 
< 0.1%
3193 1
 
< 0.1%
3192 2
< 0.1%
3191 1
 
< 0.1%
3187 3
< 0.1%
3186 1
 
< 0.1%
3184 1
 
< 0.1%
3178 1
 
< 0.1%

search_no
Real number (ℝ)

Distinct8958
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean478540.05
Minimum456028
Maximum509102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:12.680359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456028
5-th percentile457822.9
Q1466024.5
median475878.5
Q3491663.25
95-th percentile505101.3
Maximum509102
Range53074
Interquartile range (IQR)25638.75

Descriptive statistics

Standard deviation14914.231
Coefficient of variation (CV)0.031166108
Kurtosis-1.1201808
Mean478540.05
Median Absolute Deviation (MAD)11696.5
Skewness0.33305069
Sum4.7854005 × 109
Variance2.2243428 × 108
MonotonicityNot monotonic
2024-04-17T19:01:12.806083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
478998 6
 
0.1%
457116 6
 
0.1%
470855 5
 
0.1%
464587 5
 
0.1%
466184 5
 
0.1%
505772 5
 
0.1%
466765 4
 
< 0.1%
469633 4
 
< 0.1%
467444 4
 
< 0.1%
457657 4
 
< 0.1%
Other values (8948) 9952
99.5%
ValueCountFrequency (%)
456028 1
< 0.1%
456029 1
< 0.1%
456033 1
< 0.1%
456034 1
< 0.1%
456037 1
< 0.1%
456043 1
< 0.1%
456044 1
< 0.1%
456048 1
< 0.1%
456051 2
< 0.1%
456055 1
< 0.1%
ValueCountFrequency (%)
509102 1
< 0.1%
509090 1
< 0.1%
509084 1
< 0.1%
509080 1
< 0.1%
509079 1
< 0.1%
509078 1
< 0.1%
509077 1
< 0.1%
509069 1
< 0.1%
509050 1
< 0.1%
509044 1
< 0.1%

prices_no
Real number (ℝ)

Distinct8958
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean478540.05
Minimum456028
Maximum509102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:12.928550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456028
5-th percentile457822.9
Q1466024.5
median475878.5
Q3491663.25
95-th percentile505101.3
Maximum509102
Range53074
Interquartile range (IQR)25638.75

Descriptive statistics

Standard deviation14914.231
Coefficient of variation (CV)0.031166108
Kurtosis-1.1201808
Mean478540.05
Median Absolute Deviation (MAD)11696.5
Skewness0.33305069
Sum4.7854005 × 109
Variance2.2243428 × 108
MonotonicityNot monotonic
2024-04-17T19:01:13.063266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
478998 6
 
0.1%
457116 6
 
0.1%
470855 5
 
0.1%
464587 5
 
0.1%
466184 5
 
0.1%
505772 5
 
0.1%
466765 4
 
< 0.1%
469633 4
 
< 0.1%
467444 4
 
< 0.1%
457657 4
 
< 0.1%
Other values (8948) 9952
99.5%
ValueCountFrequency (%)
456028 1
< 0.1%
456029 1
< 0.1%
456033 1
< 0.1%
456034 1
< 0.1%
456037 1
< 0.1%
456043 1
< 0.1%
456044 1
< 0.1%
456048 1
< 0.1%
456051 2
< 0.1%
456055 1
< 0.1%
ValueCountFrequency (%)
509102 1
< 0.1%
509090 1
< 0.1%
509084 1
< 0.1%
509080 1
< 0.1%
509079 1
< 0.1%
509078 1
< 0.1%
509077 1
< 0.1%
509069 1
< 0.1%
509050 1
< 0.1%
509044 1
< 0.1%

prdlst
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.5459
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:13.182193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1123
median133
Q3141
95-th percentile148
Maximum150
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.642132
Coefficient of variation (CV)0.088502435
Kurtosis-0.90051089
Mean131.5459
Median Absolute Deviation (MAD)9
Skewness-0.30698492
Sum1315459
Variance135.53925
MonotonicityNot monotonic
2024-04-17T19:01:13.333681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 335
 
3.4%
140 314
 
3.1%
144 311
 
3.1%
132 308
 
3.1%
139 306
 
3.1%
137 303
 
3.0%
135 301
 
3.0%
146 299
 
3.0%
142 298
 
3.0%
123 294
 
2.9%
Other values (35) 6931
69.3%
ValueCountFrequency (%)
106 68
 
0.7%
107 10
 
0.1%
108 103
1.0%
109 4
 
< 0.1%
110 255
2.5%
111 218
2.2%
112 224
2.2%
113 163
1.6%
114 158
1.6%
115 98
 
1.0%
ValueCountFrequency (%)
150 243
2.4%
149 235
2.4%
148 259
2.6%
147 277
2.8%
146 299
3.0%
145 293
2.9%
144 311
3.1%
143 142
1.4%
142 298
3.0%
141 335
3.4%

cl_no
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
419
8966 
<NA>
1034 

Length

Max length4
Median length3
Mean length3.1034
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row419
2nd row419
3rd row419
4th row419
5th row419

Common Values

ValueCountFrequency (%)
419 8966
89.7%
<NA> 1034
 
10.3%

Length

2024-04-17T19:01:13.449929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:01:13.529307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
419 8966
89.7%
na 1034
 
10.3%

examin_de
Date

Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-06-12 00:00:00
Maximum2020-11-10 00:00:00
2024-04-17T19:01:13.619473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:01:13.737180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

pum_cd
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
454
6088 
466
2226 
465
1105 
455
 
513
467
 
68

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row454
2nd row465
3rd row466
4th row454
5th row454

Common Values

ValueCountFrequency (%)
454 6088
60.9%
466 2226
 
22.3%
465 1105
 
11.1%
455 513
 
5.1%
467 68
 
0.7%

Length

2024-04-17T19:01:13.852856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:01:13.938303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
454 6088
60.9%
466 2226
 
22.3%
465 1105
 
11.1%
455 513
 
5.1%
467 68
 
0.7%

pum_nm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
외식
6088 
서비스
2226 
여가생활
1105 
카페
 
513
기타
 
68

Length

Max length4
Median length2
Mean length2.4436
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row외식
2nd row여가생활
3rd row서비스
4th row외식
5th row외식

Common Values

ValueCountFrequency (%)
외식 6088
60.9%
서비스 2226
 
22.3%
여가생활 1105
 
11.1%
카페 513
 
5.1%
기타 68
 
0.7%

Length

2024-04-17T19:01:14.041092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:01:14.141006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식 6088
60.9%
서비스 2226
 
22.3%
여가생활 1105
 
11.1%
카페 513
 
5.1%
기타 68
 
0.7%

gugun_cd
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)0.8%
Missing1036
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean176.15863
Minimum31
Maximum376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:14.247669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile41
Q190
median176
Q3261
95-th percentile373
Maximum376
Range345
Interquartile range (IQR)171

Descriptive statistics

Standard deviation106.04637
Coefficient of variation (CV)0.60199361
Kurtosis-1.0280049
Mean176.15863
Median Absolute Deviation (MAD)85
Skewness0.39479779
Sum1579086
Variance11245.833
MonotonicityNot monotonic
2024-04-17T19:01:14.368423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
373 713
 
7.1%
189 673
 
6.7%
48 653
 
6.5%
275 648
 
6.5%
216 489
 
4.9%
41 460
 
4.6%
135 353
 
3.5%
57 352
 
3.5%
178 343
 
3.4%
95 327
 
3.3%
Other values (63) 3953
39.5%
(Missing) 1036
 
10.4%
ValueCountFrequency (%)
31 6
 
0.1%
39 12
 
0.1%
40 157
 
1.6%
41 460
4.6%
42 34
 
0.3%
45 10
 
0.1%
48 653
6.5%
53 101
 
1.0%
54 22
 
0.2%
57 352
3.5%
ValueCountFrequency (%)
376 3
 
< 0.1%
373 713
7.1%
372 11
 
0.1%
370 22
 
0.2%
369 73
 
0.7%
365 23
 
0.2%
350 11
 
0.1%
346 55
 
0.5%
345 5
 
0.1%
344 10
 
0.1%

gugun_nm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
1036 
해운대구
845 
동래구
826 
연제구
781 
부산진구
727 
Other values (9)
5785 

Length

Max length4
Median length3
Mean length3.0125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연제구
2nd row해운대구
3rd row남구
4th row남구
5th row사상구

Common Values

ValueCountFrequency (%)
<NA> 1036
10.4%
해운대구 845
 
8.5%
동래구 826
 
8.3%
연제구 781
 
7.8%
부산진구 727
 
7.3%
북구 683
 
6.8%
남구 675
 
6.8%
사상구 673
 
6.7%
금정구 669
 
6.7%
기장군 663
 
6.6%
Other values (4) 2422
24.2%

Length

2024-04-17T19:01:14.512898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1036
10.4%
해운대구 845
 
8.5%
동래구 826
 
8.3%
연제구 781
 
7.8%
부산진구 727
 
7.3%
북구 683
 
6.8%
남구 675
 
6.8%
사상구 673
 
6.7%
금정구 669
 
6.7%
기장군 663
 
6.6%
Other values (4) 2422
24.2%

unit
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.7819
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:14.629947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile200
Maximum350
Range349
Interquartile range (IQR)0

Descriptive statistics

Standard deviation56.585188
Coefficient of variation (CV)2.8604526
Kurtosis6.2393983
Mean19.7819
Median Absolute Deviation (MAD)0
Skewness2.7989594
Sum197819
Variance3201.8835
MonotonicityNot monotonic
2024-04-17T19:01:14.724366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 8969
89.7%
200 761
 
7.6%
130 71
 
0.7%
120 64
 
0.6%
100 49
 
0.5%
150 37
 
0.4%
180 18
 
0.2%
170 8
 
0.1%
350 8
 
0.1%
140 8
 
0.1%
ValueCountFrequency (%)
1 8969
89.7%
100 49
 
0.5%
110 7
 
0.1%
120 64
 
0.6%
130 71
 
0.7%
140 8
 
0.1%
150 37
 
0.4%
170 8
 
0.1%
180 18
 
0.2%
200 761
 
7.6%
ValueCountFrequency (%)
350 8
 
0.1%
200 761
7.6%
180 18
 
0.2%
170 8
 
0.1%
150 37
 
0.4%
140 8
 
0.1%
130 71
 
0.7%
120 64
 
0.6%
110 7
 
0.1%
100 49
 
0.5%

unitprice
Real number (ℝ)

ZEROS 

Distinct206
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12130.929
Minimum0
Maximum229900
Zeros539
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:01:14.842755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14000
median7000
Q312670
95-th percentile40000
Maximum229900
Range229900
Interquartile range (IQR)8670

Descriptive statistics

Standard deviation21871.728
Coefficient of variation (CV)1.8029722
Kurtosis40.426262
Mean12130.929
Median Absolute Deviation (MAD)3800
Skewness5.7902482
Sum1.2130929 × 108
Variance4.783725 × 108
MonotonicityNot monotonic
2024-04-17T19:01:15.264224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000 867
 
8.7%
5000 677
 
6.8%
3000 600
 
6.0%
7000 599
 
6.0%
0 539
 
5.4%
15000 470
 
4.7%
10000 433
 
4.3%
9000 422
 
4.2%
8000 329
 
3.3%
4000 275
 
2.8%
Other values (196) 4789
47.9%
ValueCountFrequency (%)
0 539
5.4%
35 2
 
< 0.1%
200 13
 
0.1%
250 3
 
< 0.1%
300 33
 
0.3%
350 23
 
0.2%
450 11
 
0.1%
500 30
 
0.3%
800 3
 
< 0.1%
1000 66
 
0.7%
ValueCountFrequency (%)
229900 1
 
< 0.1%
217800 4
 
< 0.1%
210000 12
0.1%
205700 5
 
0.1%
200000 21
0.2%
190000 13
0.1%
180000 2
 
< 0.1%
179000 2
 
< 0.1%
173300 1
 
< 0.1%
170400 4
 
< 0.1%

prices
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

rm
Text

MISSING 

Distinct99
Distinct (%)15.1%
Missing9344
Missing (%)93.4%
Memory size156.2 KiB
2024-04-17T19:01:15.480713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length7.4039634
Min length1

Characters and Unicode

Total characters4857
Distinct characters187
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)2.0%

Sample

1st row주말30000
2nd row
3rd row오후7시~오전7시/13000원
4th row재개발지역으로페업
5th row전통전주비빔밥
ValueCountFrequency (%)
재개발지역으로페업 28
 
3.3%
10분 27
 
3.2%
1300 25
 
3.0%
비회원 25
 
3.0%
페업 24
 
2.8%
주말 23
 
2.7%
50000 20
 
2.4%
인상 19
 
2.2%
불고기피자 19
 
2.2%
한방삼계탕 18
 
2.1%
Other values (102) 617
73.0%
2024-04-17T19:01:15.844816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 779
 
16.0%
276
 
5.7%
1 208
 
4.3%
원 166
 
3.4%
2 101
 
2.1%
업 99
 
2.0%
3 91
 
1.9%
/ 87
 
1.8%
페 82
 
1.7%
5 72
 
1.5%
Other values (177) 2896
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2875
59.2%
Decimal Number 1371
28.2%
Space Separator 276
 
5.7%
Other Punctuation 157
 
3.2%
Lowercase Letter 73
 
1.5%
Close Punctuation 37
 
0.8%
Open Punctuation 37
 
0.8%
Math Symbol 17
 
0.4%
Uppercase Letter 14
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 166
 
5.8%
업 99
 
3.4%
페 82
 
2.9%
지 70
 
2.4%
개 67
 
2.3%
로 64
 
2.2%
분 64
 
2.2%
주 57
 
2.0%
으 57
 
2.0%
인 53
 
1.8%
Other values (152) 2096
72.9%
Decimal Number
ValueCountFrequency (%)
0 779
56.8%
1 208
 
15.2%
2 101
 
7.4%
3 91
 
6.6%
5 72
 
5.3%
4 46
 
3.4%
9 43
 
3.1%
7 20
 
1.5%
6 8
 
0.6%
8 3
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 87
55.4%
, 44
28.0%
: 15
 
9.6%
% 5
 
3.2%
. 3
 
1.9%
* 3
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
g 51
69.9%
k 16
 
21.9%
c 3
 
4.1%
m 3
 
4.1%
Space Separator
ValueCountFrequency (%)
276
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2860
58.9%
Common 1895
39.0%
Latin 87
 
1.8%
Han 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 166
 
5.8%
업 99
 
3.5%
페 82
 
2.9%
지 70
 
2.4%
개 67
 
2.3%
로 64
 
2.2%
분 64
 
2.2%
주 57
 
2.0%
으 57
 
2.0%
인 53
 
1.9%
Other values (150) 2081
72.8%
Common
ValueCountFrequency (%)
0 779
41.1%
276
 
14.6%
1 208
 
11.0%
2 101
 
5.3%
3 91
 
4.8%
/ 87
 
4.6%
5 72
 
3.8%
4 46
 
2.4%
, 44
 
2.3%
9 43
 
2.3%
Other values (10) 148
 
7.8%
Latin
ValueCountFrequency (%)
g 51
58.6%
k 16
 
18.4%
R 14
 
16.1%
c 3
 
3.4%
m 3
 
3.4%
Han
ValueCountFrequency (%)
大 9
60.0%
小 6
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2860
58.9%
ASCII 1982
40.8%
CJK 15
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 779
39.3%
276
 
13.9%
1 208
 
10.5%
2 101
 
5.1%
3 91
 
4.6%
/ 87
 
4.4%
5 72
 
3.6%
g 51
 
2.6%
4 46
 
2.3%
, 44
 
2.2%
Other values (15) 227
 
11.5%
Hangul
ValueCountFrequency (%)
원 166
 
5.8%
업 99
 
3.5%
페 82
 
2.9%
지 70
 
2.4%
개 67
 
2.3%
로 64
 
2.2%
분 64
 
2.2%
주 57
 
2.0%
으 57
 
2.0%
인 53
 
1.9%
Other values (150) 2081
72.8%
CJK
ValueCountFrequency (%)
大 9
60.0%
小 6
40.0%

bssh_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

la
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

lo
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

adres
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

telno
Text

MISSING 

Distinct670
Distinct (%)7.5%
Missing1034
Missing (%)10.3%
Memory size156.2 KiB
2024-04-17T19:01:16.068388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.028106
Min length10

Characters and Unicode

Total characters107844
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.2%

Sample

1st row051-853-9298
2nd row051-704-8704
3rd row051-628-0001
4th row051-622-7028
5th row051-326-5775
ValueCountFrequency (%)
051-611-5727 60
 
0.7%
051-727-7644 57
 
0.6%
051-207-1472 56
 
0.6%
051-326-2747 56
 
0.6%
051-612-3808 54
 
0.6%
051-622-2234 50
 
0.6%
051-866-9612 48
 
0.5%
051-865-9339 42
 
0.5%
051-332-0551 42
 
0.5%
051-553-7423 42
 
0.5%
Other values (660) 8459
94.3%
2024-04-17T19:01:16.408121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17542
16.3%
0 16796
15.6%
5 16288
15.1%
1 14224
13.2%
2 8629
8.0%
7 6940
 
6.4%
3 6271
 
5.8%
8 6077
 
5.6%
6 6038
 
5.6%
4 5430
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90302
83.7%
Dash Punctuation 17542
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16796
18.6%
5 16288
18.0%
1 14224
15.8%
2 8629
9.6%
7 6940
7.7%
3 6271
 
6.9%
8 6077
 
6.7%
6 6038
 
6.7%
4 5430
 
6.0%
9 3609
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 17542
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107844
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17542
16.3%
0 16796
15.6%
5 16288
15.1%
1 14224
13.2%
2 8629
8.0%
7 6940
 
6.4%
3 6271
 
5.8%
8 6077
 
5.6%
6 6038
 
5.6%
4 5430
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17542
16.3%
0 16796
15.6%
5 16288
15.1%
1 14224
13.2%
2 8629
8.0%
7 6940
 
6.4%
3 6271
 
5.8%
8 6077
 
5.6%
6 6038
 
5.6%
4 5430
 
5.0%

parkng_at
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
6151 
Y
2815 
704 
<NA>
 
330

Length

Max length4
Median length1
Mean length1.099
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowN
5th rowY

Common Values

ValueCountFrequency (%)
N 6151
61.5%
Y 2815
28.1%
704
 
7.0%
<NA> 330
 
3.3%

Length

2024-04-17T19:01:16.542662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:01:16.646803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6151
66.2%
y 2815
30.3%
na 330
 
3.5%

card_at
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
8473 
 
704
N
 
493
<NA>
 
330

Length

Max length4
Median length1
Mean length1.099
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
Y 8473
84.7%
704
 
7.0%
N 493
 
4.9%
<NA> 330
 
3.3%

Length

2024-04-17T19:01:16.760599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:01:16.854372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 8473
91.1%
n 493
 
5.3%
na 330
 
3.5%

item_name
Categorical

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
돼지갈비(외식)
 
335
삼겹살(외식)
 
314
된장찌개백반
 
311
칼국수
 
308
자장면
 
306
Other values (41)
8426 

Length

Max length8
Median length7
Mean length4.1958
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row치킨
2nd row수영장
3rd row택배
4th row갈비탕
5th row생선초밥

Common Values

ValueCountFrequency (%)
돼지갈비(외식) 335
 
3.4%
삼겹살(외식) 314
 
3.1%
된장찌개백반 311
 
3.1%
칼국수 308
 
3.1%
자장면 306
 
3.1%
돈가스 303
 
3.0%
짬뽕 301
 
3.0%
삼계탕 299
 
3.0%
등심구이 298
 
3.0%
양복세탁료 294
 
2.9%
Other values (36) 6931
69.3%

Length

2024-04-17T19:01:16.956126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이용료 572
 
5.5%
돼지갈비(외식 335
 
3.2%
삼겹살(외식 314
 
3.0%
된장찌개백반 311
 
3.0%
칼국수 308
 
3.0%
자장면 306
 
3.0%
돈가스 303
 
2.9%
짬뽕 301
 
2.9%
삼계탕 299
 
2.9%
등심구이 298
 
2.9%
Other values (36) 6985
67.6%

last_load_dttm
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-02-01 06:17:07
1275 
2021-02-01 06:17:10
1249 
2021-02-01 06:17:13
1042 
2021-02-01 06:17:04
941 
2021-02-01 06:17:05
858 
Other values (7)
4635 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-01 06:17:07
2nd row2021-02-01 06:17:11
3rd row2021-02-01 06:17:06
4th row2021-02-01 06:17:11
5th row2021-02-01 06:17:10

Common Values

ValueCountFrequency (%)
2021-02-01 06:17:07 1275
12.8%
2021-02-01 06:17:10 1249
12.5%
2021-02-01 06:17:13 1042
10.4%
2021-02-01 06:17:04 941
9.4%
2021-02-01 06:17:05 858
8.6%
2021-02-01 06:17:12 830
8.3%
2021-02-01 06:17:08 813
8.1%
2021-02-01 06:17:06 734
7.3%
2021-02-01 06:17:11 719
7.2%
2021-02-01 06:17:09 661
6.6%
Other values (2) 878
8.8%

Length

2024-04-17T19:01:17.064394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-02-01 10000
50.0%
06:17:07 1275
 
6.4%
06:17:10 1249
 
6.2%
06:17:13 1042
 
5.2%
06:17:04 941
 
4.7%
06:17:05 858
 
4.3%
06:17:12 830
 
4.2%
06:17:08 813
 
4.1%
06:17:06 734
 
3.7%
06:17:11 719
 
3.6%
Other values (3) 1539
 
7.7%

Sample

skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
251927307213813619884779074779071364192019-06-25454외식275연제구117000<NA><NA><NA><NA><NA><NA>051-853-9298NY치킨2021-02-01 06:17:07
520409997312011829595034195034191184192020-08-18465여가생활373해운대구12700<NA><NA><NA><NA><NA><NA>051-704-8704YY수영장2021-02-01 06:17:11
205957765512111926474821564821561194192019-09-03466서비스57남구16000<NA><NA><NA><NA><NA><NA>051-628-0001YY택배2021-02-01 06:17:06
508929882514914711515024905024901474192020-08-04454외식57남구112000<NA><NA><NA><NA><NA><NA>051-622-7028NY갈비탕2021-02-01 06:17:11
429215533711411229284643714643711124192018-10-30454외식189사상구120000<NA><NA><NA><NA><NA><NA>051-326-5775YY생선초밥2021-02-01 06:17:10
135558465414614427694887774887771444192019-12-24454외식261수영구17000<NA><NA><NA><NA><NA><NA>051-612-9225NN된장찌개백반2021-02-01 06:17:05
497594847813012828434980644980641284192020-05-26466서비스189사상구125000<NA>주말30000<NA><NA><NA><NA>051-322-1514NY숙박료(여관)2021-02-01 06:17:11
5708910502211511331585054225054221134192020-09-15466서비스261수영구13000<NA><NA><NA><NA><NA><NA>051-625-5000NN주차장 이용료2021-02-01 06:17:12
338646434713613414974723784723781344192019-03-19454외식135부산진구10<NA><NA><NA><NA><NA><NA>070-7843-2768NY피자2021-02-01 06:17:08
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