Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells62655
Missing cells (%)24.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 MiB
Average record size in memory233.0 B

Variable types

Numeric10
Categorical7
DateTime2
Unsupported5
Text2

Alerts

bssh_no has 1106 (11.1%) missing valuesMissing
gugun_cd has 1113 (11.1%) missing valuesMissing
prices has 10000 (100.0%) missing valuesMissing
rm has 9330 (93.3%) 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 1106 (11.1%) 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 434 (4.3%) zerosZeros

Reproduction

Analysis started2024-04-17 09:58:31.820085
Analysis finished2024-04-17 09:58:32.406234
Duration0.59 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%
Mean196903.65
Minimum163988
Maximum229491
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:32.467536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum163988
5-th percentile167298.95
Q1180641.75
median196895.5
Q3213218
95-th percentile226210.1
Maximum229491
Range65503
Interquartile range (IQR)32576.25

Descriptive statistics

Standard deviation18891.603
Coefficient of variation (CV)0.095943389
Kurtosis-1.1925221
Mean196903.65
Median Absolute Deviation (MAD)16288
Skewness-0.0096289158
Sum1.9690365 × 109
Variance3.5689267 × 108
MonotonicityNot monotonic
2024-04-17T18:58:32.608708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
221726 1
 
< 0.1%
176209 1
 
< 0.1%
225246 1
 
< 0.1%
165635 1
 
< 0.1%
203134 1
 
< 0.1%
184760 1
 
< 0.1%
194291 1
 
< 0.1%
213824 1
 
< 0.1%
164776 1
 
< 0.1%
214630 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
163988 1
< 0.1%
164003 1
< 0.1%
164011 1
< 0.1%
164012 1
< 0.1%
164014 1
< 0.1%
164015 1
< 0.1%
164021 1
< 0.1%
164028 1
< 0.1%
164046 1
< 0.1%
164049 1
< 0.1%
ValueCountFrequency (%)
229491 1
< 0.1%
229483 1
< 0.1%
229482 1
< 0.1%
229481 1
< 0.1%
229474 1
< 0.1%
229472 1
< 0.1%
229468 1
< 0.1%
229466 1
< 0.1%
229450 1
< 0.1%
229440 1
< 0.1%

ccode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.5476
Minimum108
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:32.728693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum108
5-th percentile113
Q1125
median134
Q3143
95-th percentile151
Maximum152
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.532607
Coefficient of variation (CV)0.086355782
Kurtosis-0.89265695
Mean133.5476
Median Absolute Deviation (MAD)9
Skewness-0.28308223
Sum1335476
Variance133.00103
MonotonicityNot monotonic
2024-04-17T18:58:32.862622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
143 333
 
3.3%
139 314
 
3.1%
142 306
 
3.1%
125 305
 
3.0%
137 298
 
3.0%
124 294
 
2.9%
136 294
 
2.9%
140 291
 
2.9%
141 291
 
2.9%
134 291
 
2.9%
Other values (35) 6983
69.8%
ValueCountFrequency (%)
108 62
 
0.6%
109 3
 
< 0.1%
110 94
 
0.9%
111 6
 
0.1%
112 241
2.4%
113 202
2.0%
114 198
2.0%
115 184
1.8%
116 165
1.7%
117 108
1.1%
ValueCountFrequency (%)
152 241
2.4%
151 270
2.7%
150 261
2.6%
149 255
2.5%
148 272
2.7%
147 282
2.8%
146 273
2.7%
145 198
2.0%
144 278
2.8%
143 333
3.3%

pcode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.5476
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:33.003554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1123
median132
Q3141
95-th percentile149
Maximum150
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.532607
Coefficient of variation (CV)0.087668703
Kurtosis-0.89265695
Mean131.5476
Median Absolute Deviation (MAD)9
Skewness-0.28308223
Sum1315476
Variance133.00103
MonotonicityNot monotonic
2024-04-17T18:58:33.128770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 333
 
3.3%
137 314
 
3.1%
140 306
 
3.1%
123 305
 
3.0%
135 298
 
3.0%
122 294
 
2.9%
134 294
 
2.9%
138 291
 
2.9%
139 291
 
2.9%
132 291
 
2.9%
Other values (35) 6983
69.8%
ValueCountFrequency (%)
106 62
 
0.6%
107 3
 
< 0.1%
108 94
 
0.9%
109 6
 
0.1%
110 241
2.4%
111 202
2.0%
112 198
2.0%
113 184
1.8%
114 165
1.7%
115 108
1.1%
ValueCountFrequency (%)
150 241
2.4%
149 270
2.7%
148 261
2.6%
147 255
2.5%
146 272
2.7%
145 282
2.8%
144 273
2.7%
143 198
2.0%
142 278
2.8%
141 333
3.3%

bssh_no
Real number (ℝ)

MISSING 

Distinct672
Distinct (%)7.6%
Missing1106
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean2172.0725
Minimum985
Maximum3218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:33.284273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum985
5-th percentile1055
Q11552
median2173
Q32860
95-th percentile3098
Maximum3218
Range2233
Interquartile range (IQR)1308

Descriptive statistics

Standard deviation688.44398
Coefficient of variation (CV)0.31695257
Kurtosis-1.4017368
Mean2172.0725
Median Absolute Deviation (MAD)660
Skewness-0.13592623
Sum19318413
Variance473955.11
MonotonicityNot monotonic
2024-04-17T18:58:33.424485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2982 66
 
0.7%
1798 56
 
0.6%
2693 56
 
0.6%
1140 55
 
0.5%
1766 54
 
0.5%
2690 53
 
0.5%
2002 50
 
0.5%
2392 43
 
0.4%
1981 41
 
0.4%
1055 41
 
0.4%
Other values (662) 8379
83.8%
(Missing) 1106
 
11.1%
ValueCountFrequency (%)
985 12
0.1%
986 14
0.1%
988 18
0.2%
991 7
 
0.1%
996 27
0.3%
997 10
 
0.1%
998 13
0.1%
999 11
0.1%
1004 26
0.3%
1012 2
 
< 0.1%
ValueCountFrequency (%)
3218 1
 
< 0.1%
3212 1
 
< 0.1%
3209 1
 
< 0.1%
3205 3
< 0.1%
3204 2
 
< 0.1%
3203 2
 
< 0.1%
3202 4
< 0.1%
3200 2
 
< 0.1%
3199 5
0.1%
3197 1
 
< 0.1%

search_no
Real number (ℝ)

Distinct9394
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean485676.24
Minimum456029
Maximum517445
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:33.571069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456029
5-th percentile459027.95
Q1470271.25
median485660
Q3500270.25
95-th percentile513078.25
Maximum517445
Range61416
Interquartile range (IQR)29999

Descriptive statistics

Standard deviation17505.646
Coefficient of variation (CV)0.036043859
Kurtosis-1.1986616
Mean485676.24
Median Absolute Deviation (MAD)15110.5
Skewness0.056377432
Sum4.8567624 × 109
Variance3.0644764 × 108
MonotonicityNot monotonic
2024-04-17T18:58:33.702123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
475734 5
 
0.1%
464652 5
 
0.1%
480377 4
 
< 0.1%
458393 4
 
< 0.1%
493161 3
 
< 0.1%
477350 3
 
< 0.1%
488735 3
 
< 0.1%
512889 3
 
< 0.1%
468884 3
 
< 0.1%
463360 3
 
< 0.1%
Other values (9384) 9964
99.6%
ValueCountFrequency (%)
456029 1
< 0.1%
456032 1
< 0.1%
456043 1
< 0.1%
456046 1
< 0.1%
456047 1
< 0.1%
456050 1
< 0.1%
456054 1
< 0.1%
456057 1
< 0.1%
456064 1
< 0.1%
456065 1
< 0.1%
ValueCountFrequency (%)
517445 1
 
< 0.1%
517439 3
< 0.1%
517432 1
 
< 0.1%
517431 1
 
< 0.1%
517428 1
 
< 0.1%
517426 1
 
< 0.1%
517414 1
 
< 0.1%
517407 1
 
< 0.1%
517406 1
 
< 0.1%
517396 1
 
< 0.1%

prices_no
Real number (ℝ)

Distinct9394
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean485676.24
Minimum456029
Maximum517445
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:33.846290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456029
5-th percentile459027.95
Q1470271.25
median485660
Q3500270.25
95-th percentile513078.25
Maximum517445
Range61416
Interquartile range (IQR)29999

Descriptive statistics

Standard deviation17505.646
Coefficient of variation (CV)0.036043859
Kurtosis-1.1986616
Mean485676.24
Median Absolute Deviation (MAD)15110.5
Skewness0.056377432
Sum4.8567624 × 109
Variance3.0644764 × 108
MonotonicityNot monotonic
2024-04-17T18:58:33.967207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
475734 5
 
0.1%
464652 5
 
0.1%
480377 4
 
< 0.1%
458393 4
 
< 0.1%
493161 3
 
< 0.1%
477350 3
 
< 0.1%
488735 3
 
< 0.1%
512889 3
 
< 0.1%
468884 3
 
< 0.1%
463360 3
 
< 0.1%
Other values (9384) 9964
99.6%
ValueCountFrequency (%)
456029 1
< 0.1%
456032 1
< 0.1%
456043 1
< 0.1%
456046 1
< 0.1%
456047 1
< 0.1%
456050 1
< 0.1%
456054 1
< 0.1%
456057 1
< 0.1%
456064 1
< 0.1%
456065 1
< 0.1%
ValueCountFrequency (%)
517445 1
 
< 0.1%
517439 3
< 0.1%
517432 1
 
< 0.1%
517431 1
 
< 0.1%
517428 1
 
< 0.1%
517426 1
 
< 0.1%
517414 1
 
< 0.1%
517407 1
 
< 0.1%
517406 1
 
< 0.1%
517396 1
 
< 0.1%

prdlst
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.5476
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:34.094448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1123
median132
Q3141
95-th percentile149
Maximum150
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.532607
Coefficient of variation (CV)0.087668703
Kurtosis-0.89265695
Mean131.5476
Median Absolute Deviation (MAD)9
Skewness-0.28308223
Sum1315476
Variance133.00103
MonotonicityNot monotonic
2024-04-17T18:58:34.225595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 333
 
3.3%
137 314
 
3.1%
140 306
 
3.1%
123 305
 
3.0%
135 298
 
3.0%
122 294
 
2.9%
134 294
 
2.9%
138 291
 
2.9%
139 291
 
2.9%
132 291
 
2.9%
Other values (35) 6983
69.8%
ValueCountFrequency (%)
106 62
 
0.6%
107 3
 
< 0.1%
108 94
 
0.9%
109 6
 
0.1%
110 241
2.4%
111 202
2.0%
112 198
2.0%
113 184
1.8%
114 165
1.7%
115 108
1.1%
ValueCountFrequency (%)
150 241
2.4%
149 270
2.7%
148 261
2.6%
147 255
2.5%
146 272
2.7%
145 282
2.8%
144 273
2.7%
143 198
2.0%
142 278
2.8%
141 333
3.3%

cl_no
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
419
8894 
<NA>
1106 

Length

Max length4
Median length3
Mean length3.1106
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
419 8894
88.9%
<NA> 1106
 
11.1%

Length

2024-04-17T18:58:34.338057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:58:34.419560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
419 8894
88.9%
na 1106
 
11.1%

examin_de
Date

Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-06-12 00:00:00
Maximum2021-03-23 00:00:00
2024-04-17T18:58:34.526613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:58:34.664392image/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
5981 
466
2286 
465
1126 
455
 
545
467
 
62

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row465
2nd row455
3rd row466
4th row454
5th row454

Common Values

ValueCountFrequency (%)
454 5981
59.8%
466 2286
 
22.9%
465 1126
 
11.3%
455 545
 
5.5%
467 62
 
0.6%

Length

2024-04-17T18:58:34.777567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:58:34.868139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
454 5981
59.8%
466 2286
 
22.9%
465 1126
 
11.3%
455 545
 
5.5%
467 62
 
0.6%

pum_nm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
외식
5981 
서비스
2286 
여가생활
1126 
카페
 
545
기타
 
62

Length

Max length4
Median length2
Mean length2.4538
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외식 5981
59.8%
서비스 2286
 
22.9%
여가생활 1126
 
11.3%
카페 545
 
5.5%
기타 62
 
0.6%

Length

2024-04-17T18:58:34.978824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:58:35.084593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식 5981
59.8%
서비스 2286
 
22.9%
여가생활 1126
 
11.3%
카페 545
 
5.5%
기타 62
 
0.6%

gugun_cd
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)0.8%
Missing1113
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean177.30505
Minimum31
Maximum376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:35.191881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile41
Q190
median178
Q3261
95-th percentile373
Maximum376
Range345
Interquartile range (IQR)171

Descriptive statistics

Standard deviation105.02623
Coefficient of variation (CV)0.59234762
Kurtosis-1.0048027
Mean177.30505
Median Absolute Deviation (MAD)86
Skewness0.38035949
Sum1575710
Variance11030.508
MonotonicityNot monotonic
2024-04-17T18:58:35.337643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189 748
 
7.5%
373 705
 
7.0%
275 629
 
6.3%
48 608
 
6.1%
216 511
 
5.1%
41 416
 
4.2%
135 403
 
4.0%
178 345
 
3.5%
95 337
 
3.4%
57 332
 
3.3%
Other values (62) 3853
38.5%
(Missing) 1113
 
11.1%
ValueCountFrequency (%)
31 12
 
0.1%
39 21
 
0.2%
40 139
 
1.4%
41 416
4.2%
42 38
 
0.4%
45 19
 
0.2%
48 608
6.1%
53 114
 
1.1%
54 36
 
0.4%
57 332
3.3%
ValueCountFrequency (%)
376 6
 
0.1%
373 705
7.0%
372 8
 
0.1%
370 13
 
0.1%
369 65
 
0.7%
365 13
 
0.1%
350 13
 
0.1%
346 48
 
0.5%
344 15
 
0.1%
338 23
 
0.2%

gugun_nm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
1113 
해운대구
810 
연제구
767 
동래구
756 
사상구
748 
Other values (9)
5806 

Length

Max length4
Median length3
Mean length3.0119
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연제구
2nd row동구
3rd row연제구
4th row사상구
5th row사상구

Common Values

ValueCountFrequency (%)
<NA> 1113
11.1%
해운대구 810
 
8.1%
연제구 767
 
7.7%
동래구 756
 
7.6%
사상구 748
 
7.5%
부산진구 748
 
7.5%
북구 721
 
7.2%
사하구 694
 
6.9%
남구 677
 
6.8%
동구 630
 
6.3%
Other values (4) 2336
23.4%

Length

2024-04-17T18:58:35.480978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1113
11.1%
해운대구 810
 
8.1%
연제구 767
 
7.7%
동래구 756
 
7.6%
사상구 748
 
7.5%
부산진구 748
 
7.5%
북구 721
 
7.2%
사하구 694
 
6.9%
남구 677
 
6.8%
동구 630
 
6.3%
Other values (4) 2336
23.4%

unit
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.2118
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:35.601317image/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 deviation55.622162
Coefficient of variation (CV)2.8952083
Kurtosis6.69643
Mean19.2118
Median Absolute Deviation (MAD)0
Skewness2.8656519
Sum192118
Variance3093.8249
MonotonicityNot monotonic
2024-04-17T18:58:35.709151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 8988
89.9%
200 721
 
7.2%
130 86
 
0.9%
120 64
 
0.6%
100 62
 
0.6%
150 25
 
0.2%
180 19
 
0.2%
110 11
 
0.1%
350 9
 
0.1%
170 8
 
0.1%
ValueCountFrequency (%)
1 8988
89.9%
100 62
 
0.6%
110 11
 
0.1%
120 64
 
0.6%
130 86
 
0.9%
140 7
 
0.1%
150 25
 
0.2%
170 8
 
0.1%
180 19
 
0.2%
200 721
 
7.2%
ValueCountFrequency (%)
350 9
 
0.1%
200 721
7.2%
180 19
 
0.2%
170 8
 
0.1%
150 25
 
0.2%
140 7
 
0.1%
130 86
 
0.9%
120 64
 
0.6%
110 11
 
0.1%
100 62
 
0.6%

unitprice
Real number (ℝ)

ZEROS 

Distinct208
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11996.935
Minimum0
Maximum326700
Zeros434
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:58:35.825027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile500
Q14000
median7000
Q312850
95-th percentile40000
Maximum326700
Range326700
Interquartile range (IQR)8850

Descriptive statistics

Standard deviation20680.195
Coefficient of variation (CV)1.7237899
Kurtosis47.05253
Mean11996.935
Median Absolute Deviation (MAD)3500
Skewness6.0955216
Sum1.1996935 × 108
Variance4.2767048 × 108
MonotonicityNot monotonic
2024-04-17T18:58:35.956373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000 931
 
9.3%
7000 682
 
6.8%
5000 635
 
6.3%
3000 586
 
5.9%
15000 472
 
4.7%
10000 449
 
4.5%
0 434
 
4.3%
9000 432
 
4.3%
8000 354
 
3.5%
4000 256
 
2.6%
Other values (198) 4769
47.7%
ValueCountFrequency (%)
0 434
4.3%
35 1
 
< 0.1%
200 13
 
0.1%
250 3
 
< 0.1%
300 19
 
0.2%
350 21
 
0.2%
450 8
 
0.1%
500 18
 
0.2%
800 2
 
< 0.1%
1000 69
 
0.7%
ValueCountFrequency (%)
326700 1
 
< 0.1%
217800 3
 
< 0.1%
210000 15
0.1%
205700 2
 
< 0.1%
200000 11
0.1%
193600 1
 
< 0.1%
190000 11
0.1%
183000 2
 
< 0.1%
180000 2
 
< 0.1%
179000 1
 
< 0.1%

prices
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

rm
Text

MISSING 

Distinct107
Distinct (%)16.0%
Missing9330
Missing (%)93.3%
Memory size156.2 KiB
2024-04-17T18:58:36.236782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length17
Mean length7.5567164
Min length1

Characters and Unicode

Total characters5063
Distinct characters193
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

Unique10 ?
Unique (%)1.5%

Sample

1st row강의료20만원
2nd row프랑스산
3rd row오후7시~오전7시/13000원
4th row
5th row프랑스산
ValueCountFrequency (%)
비회원 26
 
2.9%
1300 26
 
2.9%
주말 24
 
2.7%
주말30000 23
 
2.6%
10분 21
 
2.3%
130g/9000원 19
 
2.1%
50000 19
 
2.1%
아메리카노 18
 
2.0%
인상 17
 
1.9%
곰탕 16
 
1.8%
Other values (110) 692
76.8%
2024-04-17T18:58:36.943595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 816
 
16.1%
300
 
5.9%
1 208
 
4.1%
원 169
 
3.3%
2 111
 
2.2%
3 101
 
2.0%
/ 95
 
1.9%
시 82
 
1.6%
주 82
 
1.6%
업 78
 
1.5%
Other values (183) 3021
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2927
57.8%
Decimal Number 1451
28.7%
Space Separator 300
 
5.9%
Other Punctuation 178
 
3.5%
Lowercase Letter 97
 
1.9%
Open Punctuation 36
 
0.7%
Close Punctuation 36
 
0.7%
Math Symbol 23
 
0.5%
Uppercase Letter 15
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 169
 
5.8%
시 82
 
2.8%
주 82
 
2.8%
업 78
 
2.7%
상 62
 
2.1%
이 62
 
2.1%
분 56
 
1.9%
말 56
 
1.9%
인 52
 
1.8%
자 47
 
1.6%
Other values (158) 2181
74.5%
Decimal Number
ValueCountFrequency (%)
0 816
56.2%
1 208
 
14.3%
2 111
 
7.6%
3 101
 
7.0%
5 77
 
5.3%
4 47
 
3.2%
9 40
 
2.8%
7 30
 
2.1%
6 14
 
1.0%
8 7
 
0.5%
Other Punctuation
ValueCountFrequency (%)
/ 95
53.4%
, 52
29.2%
: 18
 
10.1%
* 6
 
3.4%
. 5
 
2.8%
% 2
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
g 63
64.9%
k 22
 
22.7%
m 6
 
6.2%
c 6
 
6.2%
Space Separator
ValueCountFrequency (%)
300
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2909
57.5%
Common 2024
40.0%
Latin 112
 
2.2%
Han 18
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 169
 
5.8%
시 82
 
2.8%
주 82
 
2.8%
업 78
 
2.7%
상 62
 
2.1%
이 62
 
2.1%
분 56
 
1.9%
말 56
 
1.9%
인 52
 
1.8%
자 47
 
1.6%
Other values (156) 2163
74.4%
Common
ValueCountFrequency (%)
0 816
40.3%
300
 
14.8%
1 208
 
10.3%
2 111
 
5.5%
3 101
 
5.0%
/ 95
 
4.7%
5 77
 
3.8%
, 52
 
2.6%
4 47
 
2.3%
9 40
 
2.0%
Other values (10) 177
 
8.7%
Latin
ValueCountFrequency (%)
g 63
56.2%
k 22
 
19.6%
R 15
 
13.4%
m 6
 
5.4%
c 6
 
5.4%
Han
ValueCountFrequency (%)
大 10
55.6%
小 8
44.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2909
57.5%
ASCII 2136
42.2%
CJK 18
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 816
38.2%
300
 
14.0%
1 208
 
9.7%
2 111
 
5.2%
3 101
 
4.7%
/ 95
 
4.4%
5 77
 
3.6%
g 63
 
2.9%
, 52
 
2.4%
4 47
 
2.2%
Other values (15) 266
 
12.5%
Hangul
ValueCountFrequency (%)
원 169
 
5.8%
시 82
 
2.8%
주 82
 
2.8%
업 78
 
2.7%
상 62
 
2.1%
이 62
 
2.1%
분 56
 
1.9%
말 56
 
1.9%
인 52
 
1.8%
자 47
 
1.6%
Other values (156) 2163
74.4%
CJK
ValueCountFrequency (%)
大 10
55.6%
小 8
44.4%

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 

Distinct659
Distinct (%)7.4%
Missing1106
Missing (%)11.1%
Memory size156.2 KiB
2024-04-17T18:58:37.193400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.0217
Min length10

Characters and Unicode

Total characters106921
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

Unique8 ?
Unique (%)0.1%

Sample

1st row051-851-0134
2nd row051-441-3269
3rd row051-866-7797
4th row051-315-5700
5th row051-326-2747
ValueCountFrequency (%)
051-612-3808 66
 
0.7%
051-559-1592 64
 
0.7%
051-207-1472 56
 
0.6%
051-622-2234 56
 
0.6%
051-611-5727 55
 
0.6%
051-326-2747 54
 
0.6%
051-727-7644 53
 
0.6%
051-866-9612 50
 
0.6%
051-000-0000 45
 
0.5%
051-702-8057 43
 
0.5%
Other values (649) 8352
93.9%
2024-04-17T18:58:37.553761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17412
16.3%
0 16612
15.5%
5 16002
15.0%
1 14117
13.2%
2 8403
7.9%
7 6896
 
6.4%
3 6366
 
6.0%
6 6042
 
5.7%
8 6026
 
5.6%
4 5389
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89509
83.7%
Dash Punctuation 17412
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16612
18.6%
5 16002
17.9%
1 14117
15.8%
2 8403
9.4%
7 6896
7.7%
3 6366
 
7.1%
6 6042
 
6.8%
8 6026
 
6.7%
4 5389
 
6.0%
9 3656
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 17412
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106921
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17412
16.3%
0 16612
15.5%
5 16002
15.0%
1 14117
13.2%
2 8403
7.9%
7 6896
 
6.4%
3 6366
 
6.0%
6 6042
 
5.7%
8 6026
 
5.6%
4 5389
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106921
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17412
16.3%
0 16612
15.5%
5 16002
15.0%
1 14117
13.2%
2 8403
7.9%
7 6896
 
6.4%
3 6366
 
6.0%
6 6042
 
5.7%
8 6026
 
5.6%
4 5389
 
5.0%

parkng_at
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
5937 
Y
2957 
1106 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 5937
59.4%
Y 2957
29.6%
1106
 
11.1%

Length

2024-04-17T18:58:37.674303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:58:37.760118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 5937
66.8%
y 2957
33.2%

card_at
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
8357 
1106 
N
 
537

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 8357
83.6%
1106
 
11.1%
N 537
 
5.4%

Length

2024-04-17T18:58:37.850748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:58:37.932825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 8357
94.0%
n 537
 
6.0%

item_name
Categorical

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
돼지갈비(외식)
 
333
돈가스
 
314
삼겹살(외식)
 
306
양복세탁료
 
305
짬뽕
 
298
Other values (40)
8444 

Length

Max length8
Median length7
Mean length4.2065
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row골프연습장
2nd row커피
3rd row이용료
4th row돼지갈비(외식)
5th row비빔밥

Common Values

ValueCountFrequency (%)
돼지갈비(외식) 333
 
3.3%
돈가스 314
 
3.1%
삼겹살(외식) 306
 
3.1%
양복세탁료 305
 
3.0%
짬뽕 298
 
3.0%
당구장이용료 294
 
2.9%
피자 294
 
2.9%
칼국수 291
 
2.9%
조리라면 291
 
2.9%
자장면 291
 
2.9%
Other values (35) 6983
69.8%

Length

2024-04-17T18:58:38.033292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이용료 701
 
6.7%
돼지갈비(외식 333
 
3.2%
돈가스 314
 
3.0%
삼겹살(외식 306
 
2.9%
양복세탁료 305
 
2.9%
짬뽕 298
 
2.9%
당구장이용료 294
 
2.8%
피자 294
 
2.8%
칼국수 291
 
2.8%
조리라면 291
 
2.8%
Other values (35) 7012
67.2%

last_load_dttm
Date

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-04-01 06:17:03
Maximum2021-04-01 06:17:13
2024-04-17T18:58:38.134771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:58:38.244486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

Sample

skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
778222172611811620105110735110731164192020-12-22465여가생활275연제구1190000<NA>강의료20만원<NA><NA><NA><NA>051-851-0134NY골프연습장2021-04-01 06:17:04
4825918119913213012554792504792501304192019-07-09455카페88동구12500<NA><NA><NA><NA><NA><NA>051-441-3269NY커피2021-04-01 06:17:10
6376416573612912720134666454666451274192018-12-11466서비스275연제구110000<NA><NA><NA><NA><NA><NA>051-866-7797NY이용료2021-04-01 06:17:13
4397818554114314117704812774812771414192019-08-20454외식189사상구2008000<NA>프랑스산<NA><NA><NA><NA>051-315-5700YY돼지갈비(외식)2021-04-01 06:17:10
5992116959615014817664564274564271484192018-06-12454외식189사상구14000<NA><NA><NA><NA><NA><NA>051-326-2747NY비빔밥2021-04-01 06:17:12
76522875312312119725167835167831214192021-03-23465여가생활275연제구115000<NA><NA><NA><NA><NA><NA>051-868-9909NY노래방이용료2021-04-01 06:17:03
4132018813911211014634601034601031104192018-08-21454외식135부산진구13500<NA><NA><NA><NA><NA><NA>051-805-7794NY불고기버거2021-04-01 06:17:10
1145721799211311112735075725075721114192020-10-13466서비스89동구15000<NA><NA><NA><NA><NA><NA>051-468-4052NN의복수선료2021-04-01 06:17:05
3764219185015114917974847814847811494192019-10-15454외식216사하구15000<NA><NA><NA><NA><NA><NA>051-206-6037NY냉면2021-04-01 06:17:09
2539220410613713523884963834963831354192020-04-28454외식275연제구16000<NA><NA><NA><NA><NA><NA>051-863-0661NY짬뽕2021-04-01 06:17:07
skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
691122256314814621685124135124131464192021-01-13454외식312중구116000<NA><NA><NA><NA><NA><NA>051-245-3696NY삼계탕2021-04-01 06:17:04
4925418027411311127344763814763811114192019-05-28466서비스261수영구13000<NA><NA><NA><NA><NA><NA>051-624-4600YY의복수선료2021-04-01 06:17:10
122922826812512317465163015163011234192021-03-09466서비스189사상구17000<NA>신사복상하드라이크리닝<NA><NA><NA><NA>051-322-1513NY양복세탁료2021-04-01 06:17:03
2099120849614214017704618984618981404192018-09-18454외식189사상구15010666<NA><NA><NA><NA><NA><NA>051-315-5700YY삼겹살(외식)2021-04-01 06:17:06
267722685410810624044643984643981064192018-10-30467기타373해운대구186230<NA><NA><NA><NA><NA><NA>051-701-4026YY공동주택관리비2021-04-01 06:17:03
2977619972513213029474924534924531304192020-02-18455카페373해운대구13000<NA><NA><NA><NA><NA><NA>051-704-3231YY커피2021-04-01 06:17:07
1577221374612712518045054425054421254192020-09-15466서비스216사하구16000<NA><NA><NA><NA><NA><NA>051-208-0900NY목욕료2021-04-01 06:17:05
984521960313713527995090475090471354192020-11-10454외식48기장군17000<NA><NA><NA><NA><NA><NA>051-727-9852YY짬뽕2021-04-01 06:17:04
60251169253133131<NA>458393458393131<NA>2018-07-10454외식<NA><NA>10<NA><NA><NA><NA><NA><NA><NA>김밥2021-04-01 06:17:13
21346208181149147<NA>461337461337147<NA>2018-09-04454외식<NA><NA>10<NA><NA><NA><NA><NA><NA><NA>갈비탕2021-04-01 06:17:06