Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells62459
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 (51.5%)Imbalance
card_at is highly imbalanced (51.3%)Imbalance
bssh_no has 1050 (10.5%) missing valuesMissing
gugun_cd has 1057 (10.6%) missing valuesMissing
prices has 10000 (100.0%) missing valuesMissing
rm has 9302 (93.0%) 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 1050 (10.5%) 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 439 (4.4%) zerosZeros

Reproduction

Analysis started2024-04-17 09:57:18.582796
Analysis finished2024-04-17 09:57:19.067897
Duration0.49 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%
Mean195636.21
Minimum163974
Maximum227700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:19.124928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum163974
5-th percentile166978.85
Q1179667.5
median195497.5
Q3211518.25
95-th percentile224549.15
Maximum227700
Range63726
Interquartile range (IQR)31850.75

Descriptive statistics

Standard deviation18445.599
Coefficient of variation (CV)0.0942852
Kurtosis-1.1964674
Mean195636.21
Median Absolute Deviation (MAD)15908.5
Skewness0.017259174
Sum1.9563621 × 109
Variance3.4024013 × 108
MonotonicityNot monotonic
2024-04-17T18:57:19.266525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
213327 1
 
< 0.1%
207030 1
 
< 0.1%
172779 1
 
< 0.1%
225831 1
 
< 0.1%
214629 1
 
< 0.1%
169567 1
 
< 0.1%
183871 1
 
< 0.1%
226101 1
 
< 0.1%
215011 1
 
< 0.1%
197671 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
163974 1
< 0.1%
163979 1
< 0.1%
163984 1
< 0.1%
163987 1
< 0.1%
164007 1
< 0.1%
164021 1
< 0.1%
164032 1
< 0.1%
164043 1
< 0.1%
164049 1
< 0.1%
164052 1
< 0.1%
ValueCountFrequency (%)
227700 1
< 0.1%
227696 1
< 0.1%
227694 1
< 0.1%
227684 1
< 0.1%
227680 1
< 0.1%
227677 1
< 0.1%
227665 1
< 0.1%
227658 1
< 0.1%
227657 1
< 0.1%
227656 1
< 0.1%

ccode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.2792
Minimum108
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:19.406966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum108
5-th percentile113
Q1124
median134
Q3143
95-th percentile151
Maximum152
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.709601
Coefficient of variation (CV)0.087857679
Kurtosis-0.9473362
Mean133.2792
Median Absolute Deviation (MAD)9
Skewness-0.24542778
Sum1332792
Variance137.11476
MonotonicityNot monotonic
2024-04-17T18:57:19.532263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
143 344
 
3.4%
134 307
 
3.1%
141 307
 
3.1%
122 306
 
3.1%
123 297
 
3.0%
149 295
 
2.9%
125 293
 
2.9%
142 290
 
2.9%
137 290
 
2.9%
124 289
 
2.9%
Other values (35) 6982
69.8%
ValueCountFrequency (%)
108 63
 
0.6%
109 10
 
0.1%
110 122
1.2%
111 4
 
< 0.1%
112 212
2.1%
113 242
2.4%
114 180
1.8%
115 209
2.1%
116 178
1.8%
117 113
1.1%
ValueCountFrequency (%)
152 266
2.7%
151 278
2.8%
150 229
2.3%
149 295
2.9%
148 258
2.6%
147 273
2.7%
146 270
2.7%
145 178
1.8%
144 270
2.7%
143 344
3.4%

pcode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.2792
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:19.651398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1122
median132
Q3141
95-th percentile149
Maximum150
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.709601
Coefficient of variation (CV)0.089196165
Kurtosis-0.9473362
Mean131.2792
Median Absolute Deviation (MAD)9
Skewness-0.24542778
Sum1312792
Variance137.11476
MonotonicityNot monotonic
2024-04-17T18:57:19.779803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 344
 
3.4%
132 307
 
3.1%
139 307
 
3.1%
120 306
 
3.1%
121 297
 
3.0%
147 295
 
2.9%
123 293
 
2.9%
140 290
 
2.9%
135 290
 
2.9%
122 289
 
2.9%
Other values (35) 6982
69.8%
ValueCountFrequency (%)
106 63
 
0.6%
107 10
 
0.1%
108 122
1.2%
109 4
 
< 0.1%
110 212
2.1%
111 242
2.4%
112 180
1.8%
113 209
2.1%
114 178
1.8%
115 113
1.1%
ValueCountFrequency (%)
150 266
2.7%
149 278
2.8%
148 229
2.3%
147 295
2.9%
146 258
2.6%
145 273
2.7%
144 270
2.7%
143 178
1.8%
142 270
2.7%
141 344
3.4%

bssh_no
Real number (ℝ)

MISSING 

Distinct669
Distinct (%)7.5%
Missing1050
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean2162.326
Minimum985
Maximum3211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:19.909661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum985
5-th percentile1047
Q11548
median2163
Q32843
95-th percentile3095.1
Maximum3211
Range2226
Interquartile range (IQR)1295

Descriptive statistics

Standard deviation688.33231
Coefficient of variation (CV)0.31832957
Kurtosis-1.4093795
Mean2162.326
Median Absolute Deviation (MAD)654
Skewness-0.10815716
Sum19352818
Variance473801.37
MonotonicityNot monotonic
2024-04-17T18:57:20.028723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2693 66
 
0.7%
2982 64
 
0.6%
2690 57
 
0.6%
1798 54
 
0.5%
1981 49
 
0.5%
1140 48
 
0.5%
1793 47
 
0.5%
2002 43
 
0.4%
1320 42
 
0.4%
1766 41
 
0.4%
Other values (659) 8439
84.4%
(Missing) 1050
 
10.5%
ValueCountFrequency (%)
985 10
 
0.1%
986 13
0.1%
988 18
0.2%
991 14
0.1%
996 30
0.3%
997 9
 
0.1%
998 16
0.2%
999 18
0.2%
1004 16
0.2%
1012 9
 
0.1%
ValueCountFrequency (%)
3211 1
 
< 0.1%
3203 1
 
< 0.1%
3202 4
< 0.1%
3200 2
 
< 0.1%
3199 5
0.1%
3197 2
 
< 0.1%
3196 2
 
< 0.1%
3193 4
< 0.1%
3192 2
 
< 0.1%
3191 3
< 0.1%

search_no
Real number (ℝ)

Distinct9363
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean484523.73
Minimum456028
Maximum514702
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:20.145188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456028
5-th percentile458835.65
Q1469720
median484100
Q3498865.75
95-th percentile511459.35
Maximum514702
Range58674
Interquartile range (IQR)29145.75

Descriptive statistics

Standard deviation16887.89
Coefficient of variation (CV)0.03485462
Kurtosis-1.1991715
Mean484523.73
Median Absolute Deviation (MAD)14516
Skewness0.072106624
Sum4.8452373 × 109
Variance2.8520084 × 108
MonotonicityNot monotonic
2024-04-17T18:57:20.263576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
464637 5
 
0.1%
477479 4
 
< 0.1%
465305 4
 
< 0.1%
513318 3
 
< 0.1%
475734 3
 
< 0.1%
474894 3
 
< 0.1%
464562 3
 
< 0.1%
493661 3
 
< 0.1%
463326 3
 
< 0.1%
457905 3
 
< 0.1%
Other values (9353) 9966
99.7%
ValueCountFrequency (%)
456028 1
< 0.1%
456033 1
< 0.1%
456039 1
< 0.1%
456046 1
< 0.1%
456047 1
< 0.1%
456048 1
< 0.1%
456049 1
< 0.1%
456057 1
< 0.1%
456063 1
< 0.1%
456065 1
< 0.1%
ValueCountFrequency (%)
514702 1
< 0.1%
514700 1
< 0.1%
514694 1
< 0.1%
514691 1
< 0.1%
514690 1
< 0.1%
514687 1
< 0.1%
514683 1
< 0.1%
514680 1
< 0.1%
514678 1
< 0.1%
514673 2
< 0.1%

prices_no
Real number (ℝ)

Distinct9363
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean484523.73
Minimum456028
Maximum514702
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:20.379048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456028
5-th percentile458835.65
Q1469720
median484100
Q3498865.75
95-th percentile511459.35
Maximum514702
Range58674
Interquartile range (IQR)29145.75

Descriptive statistics

Standard deviation16887.89
Coefficient of variation (CV)0.03485462
Kurtosis-1.1991715
Mean484523.73
Median Absolute Deviation (MAD)14516
Skewness0.072106624
Sum4.8452373 × 109
Variance2.8520084 × 108
MonotonicityNot monotonic
2024-04-17T18:57:20.494564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
464637 5
 
0.1%
477479 4
 
< 0.1%
465305 4
 
< 0.1%
513318 3
 
< 0.1%
475734 3
 
< 0.1%
474894 3
 
< 0.1%
464562 3
 
< 0.1%
493661 3
 
< 0.1%
463326 3
 
< 0.1%
457905 3
 
< 0.1%
Other values (9353) 9966
99.7%
ValueCountFrequency (%)
456028 1
< 0.1%
456033 1
< 0.1%
456039 1
< 0.1%
456046 1
< 0.1%
456047 1
< 0.1%
456048 1
< 0.1%
456049 1
< 0.1%
456057 1
< 0.1%
456063 1
< 0.1%
456065 1
< 0.1%
ValueCountFrequency (%)
514702 1
< 0.1%
514700 1
< 0.1%
514694 1
< 0.1%
514691 1
< 0.1%
514690 1
< 0.1%
514687 1
< 0.1%
514683 1
< 0.1%
514680 1
< 0.1%
514678 1
< 0.1%
514673 2
< 0.1%

prdlst
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.2792
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:20.615873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1122
median132
Q3141
95-th percentile149
Maximum150
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.709601
Coefficient of variation (CV)0.089196165
Kurtosis-0.9473362
Mean131.2792
Median Absolute Deviation (MAD)9
Skewness-0.24542778
Sum1312792
Variance137.11476
MonotonicityNot monotonic
2024-04-17T18:57:20.751544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 344
 
3.4%
132 307
 
3.1%
139 307
 
3.1%
120 306
 
3.1%
121 297
 
3.0%
147 295
 
2.9%
123 293
 
2.9%
140 290
 
2.9%
135 290
 
2.9%
122 289
 
2.9%
Other values (35) 6982
69.8%
ValueCountFrequency (%)
106 63
 
0.6%
107 10
 
0.1%
108 122
1.2%
109 4
 
< 0.1%
110 212
2.1%
111 242
2.4%
112 180
1.8%
113 209
2.1%
114 178
1.8%
115 113
1.1%
ValueCountFrequency (%)
150 266
2.7%
149 278
2.8%
148 229
2.3%
147 295
2.9%
146 258
2.6%
145 273
2.7%
144 270
2.7%
143 178
1.8%
142 270
2.7%
141 344
3.4%

cl_no
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
419
8950 
<NA>
1050 

Length

Max length4
Median length3
Mean length3.105
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row419
2nd row<NA>
3rd row419
4th row419
5th row419

Common Values

ValueCountFrequency (%)
419 8950
89.5%
<NA> 1050
 
10.5%

Length

2024-04-17T18:57:20.887156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:20.969707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
419 8950
89.5%
na 1050
 
10.5%

examin_de
Date

Distinct75
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-06-12 00:00:00
Maximum2021-02-23 00:00:00
2024-04-17T18:57:21.072857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:57:21.207003image/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
5848 
466
2383 
465
1205 
455
 
501
467
 
63

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
454 5848
58.5%
466 2383
23.8%
465 1205
 
12.0%
455 501
 
5.0%
467 63
 
0.6%

Length

2024-04-17T18:57:21.342402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:21.439788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
454 5848
58.5%
466 2383
23.8%
465 1205
 
12.0%
455 501
 
5.0%
467 63
 
0.6%

pum_nm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
외식
5848 
서비스
2383 
여가생활
1205 
카페
 
501
기타
 
63

Length

Max length4
Median length2
Mean length2.4793
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외식 5848
58.5%
서비스 2383
23.8%
여가생활 1205
 
12.0%
카페 501
 
5.0%
기타 63
 
0.6%

Length

2024-04-17T18:57:21.833370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:21.935212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식 5848
58.5%
서비스 2383
23.8%
여가생활 1205
 
12.0%
카페 501
 
5.0%
기타 63
 
0.6%

gugun_cd
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)0.8%
Missing1057
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean177.68545
Minimum31
Maximum376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:22.044748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile41
Q192
median176
Q3261
95-th percentile373
Maximum376
Range345
Interquartile range (IQR)169

Descriptive statistics

Standard deviation104.85571
Coefficient of variation (CV)0.59011985
Kurtosis-0.9945797
Mean177.68545
Median Absolute Deviation (MAD)85
Skewness0.38803761
Sum1589041
Variance10994.72
MonotonicityNot monotonic
2024-04-17T18:57:22.185770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189 748
 
7.5%
373 707
 
7.1%
275 604
 
6.0%
48 592
 
5.9%
216 522
 
5.2%
41 416
 
4.2%
135 373
 
3.7%
92 365
 
3.6%
95 349
 
3.5%
57 322
 
3.2%
Other values (62) 3945
39.5%
(Missing) 1057
 
10.6%
ValueCountFrequency (%)
31 10
 
0.1%
39 18
 
0.2%
40 152
 
1.5%
41 416
4.2%
42 34
 
0.3%
45 14
 
0.1%
48 592
5.9%
53 124
 
1.2%
54 28
 
0.3%
57 322
3.2%
ValueCountFrequency (%)
376 7
 
0.1%
373 707
7.1%
372 1
 
< 0.1%
370 20
 
0.2%
369 64
 
0.6%
365 29
 
0.3%
350 12
 
0.1%
346 57
 
0.6%
344 8
 
0.1%
338 44
 
0.4%

gugun_nm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
1057 
해운대구
828 
부산진구
786 
동래구
781 
연제구
750 
Other values (9)
5798 

Length

Max length4
Median length3
Mean length3.0135
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사하구
2nd row<NA>
3rd row동래구
4th row남구
5th row기장군

Common Values

ValueCountFrequency (%)
<NA> 1057
10.6%
해운대구 828
 
8.3%
부산진구 786
 
7.9%
동래구 781
 
7.8%
연제구 750
 
7.5%
사상구 748
 
7.5%
사하구 713
 
7.1%
북구 712
 
7.1%
동구 667
 
6.7%
남구 636
 
6.4%
Other values (4) 2322
23.2%

Length

2024-04-17T18:57:22.324647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1057
10.6%
해운대구 828
 
8.3%
부산진구 786
 
7.9%
동래구 781
 
7.8%
연제구 750
 
7.5%
사상구 748
 
7.5%
사하구 713
 
7.1%
북구 712
 
7.1%
동구 667
 
6.7%
남구 636
 
6.4%
Other values (4) 2322
23.2%

unit
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.4706
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:22.434109image/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 deviation54.389294
Coefficient of variation (CV)2.9446415
Kurtosis6.8120054
Mean18.4706
Median Absolute Deviation (MAD)0
Skewness2.9084801
Sum184706
Variance2958.1954
MonotonicityNot monotonic
2024-04-17T18:57:22.534375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 9026
90.3%
200 701
 
7.0%
130 71
 
0.7%
120 70
 
0.7%
100 59
 
0.6%
150 23
 
0.2%
180 21
 
0.2%
110 12
 
0.1%
140 7
 
0.1%
170 6
 
0.1%
ValueCountFrequency (%)
1 9026
90.3%
100 59
 
0.6%
110 12
 
0.1%
120 70
 
0.7%
130 71
 
0.7%
140 7
 
0.1%
150 23
 
0.2%
170 6
 
0.1%
180 21
 
0.2%
200 701
 
7.0%
ValueCountFrequency (%)
350 4
 
< 0.1%
200 701
7.0%
180 21
 
0.2%
170 6
 
0.1%
150 23
 
0.2%
140 7
 
0.1%
130 71
 
0.7%
120 70
 
0.7%
110 12
 
0.1%
100 59
 
0.6%

unitprice
Real number (ℝ)

ZEROS 

Distinct210
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12461.285
Minimum0
Maximum326700
Zeros439
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:22.662646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile350
Q14000
median7000
Q312800
95-th percentile40000
Maximum326700
Range326700
Interquartile range (IQR)8800

Descriptive statistics

Standard deviation22503.45
Coefficient of variation (CV)1.8058692
Kurtosis41.922551
Mean12461.285
Median Absolute Deviation (MAD)3500
Skewness5.7999007
Sum1.2461285 × 108
Variance5.0640524 × 108
MonotonicityNot monotonic
2024-04-17T18:57:22.797661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000 847
 
8.5%
7000 663
 
6.6%
5000 643
 
6.4%
3000 595
 
5.9%
15000 492
 
4.9%
10000 481
 
4.8%
9000 442
 
4.4%
0 439
 
4.4%
8000 372
 
3.7%
12000 267
 
2.7%
Other values (200) 4759
47.6%
ValueCountFrequency (%)
0 439
4.4%
200 15
 
0.1%
250 6
 
0.1%
300 34
 
0.3%
350 23
 
0.2%
450 12
 
0.1%
500 30
 
0.3%
800 3
 
< 0.1%
1000 75
 
0.8%
1200 194
1.9%
ValueCountFrequency (%)
326700 2
 
< 0.1%
229900 1
 
< 0.1%
217800 6
 
0.1%
210000 7
0.1%
205700 3
 
< 0.1%
200000 15
0.1%
190000 17
0.2%
183000 1
 
< 0.1%
180000 8
0.1%
170400 6
 
0.1%

prices
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

rm
Text

MISSING 

Distinct110
Distinct (%)15.8%
Missing9302
Missing (%)93.0%
Memory size156.2 KiB
2024-04-17T18:57:23.031721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length17
Mean length7.5974212
Min length1

Characters and Unicode

Total characters5303
Distinct characters198
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

Unique15 ?
Unique (%)2.1%

Sample

1st row한방삼계탕
2nd row프랑스산
3rd row맑은곰탕
4th row10분 1400
5th row
ValueCountFrequency (%)
비회원 30
 
3.2%
1300 30
 
3.2%
주말 24
 
2.6%
인상 24
 
2.6%
아메리카노 23
 
2.5%
10분 22
 
2.4%
50000 21
 
2.3%
15~20kg(편의점 21
 
2.3%
재개발지역으로페업 21
 
2.3%
130g/9000원 20
 
2.1%
Other values (113) 695
74.7%
2024-04-17T18:57:23.406338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 834
 
15.7%
312
 
5.9%
1 232
 
4.4%
원 187
 
3.5%
2 126
 
2.4%
3 113
 
2.1%
/ 103
 
1.9%
5 84
 
1.6%
업 72
 
1.4%
g 70
 
1.3%
Other values (188) 3170
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3061
57.7%
Decimal Number 1512
28.5%
Space Separator 312
 
5.9%
Other Punctuation 192
 
3.6%
Lowercase Letter 111
 
2.1%
Close Punctuation 37
 
0.7%
Open Punctuation 37
 
0.7%
Math Symbol 34
 
0.6%
Uppercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 187
 
6.1%
업 72
 
2.4%
시 70
 
2.3%
인 69
 
2.3%
주 68
 
2.2%
분 61
 
2.0%
이 60
 
2.0%
상 59
 
1.9%
리 53
 
1.7%
지 53
 
1.7%
Other values (163) 2309
75.4%
Decimal Number
ValueCountFrequency (%)
0 834
55.2%
1 232
 
15.3%
2 126
 
8.3%
3 113
 
7.5%
5 84
 
5.6%
9 47
 
3.1%
4 37
 
2.4%
7 27
 
1.8%
6 8
 
0.5%
8 4
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 103
53.6%
, 54
28.1%
: 23
 
12.0%
% 4
 
2.1%
. 4
 
2.1%
* 4
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
g 70
63.1%
k 33
29.7%
m 4
 
3.6%
c 4
 
3.6%
Space Separator
ValueCountFrequency (%)
312
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 34
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3038
57.3%
Common 2124
40.1%
Latin 118
 
2.2%
Han 23
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 187
 
6.2%
업 72
 
2.4%
시 70
 
2.3%
인 69
 
2.3%
주 68
 
2.2%
분 61
 
2.0%
이 60
 
2.0%
상 59
 
1.9%
리 53
 
1.7%
지 53
 
1.7%
Other values (161) 2286
75.2%
Common
ValueCountFrequency (%)
0 834
39.3%
312
 
14.7%
1 232
 
10.9%
2 126
 
5.9%
3 113
 
5.3%
/ 103
 
4.8%
5 84
 
4.0%
, 54
 
2.5%
9 47
 
2.2%
) 37
 
1.7%
Other values (10) 182
 
8.6%
Latin
ValueCountFrequency (%)
g 70
59.3%
k 33
28.0%
R 7
 
5.9%
m 4
 
3.4%
c 4
 
3.4%
Han
ValueCountFrequency (%)
大 13
56.5%
小 10
43.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3038
57.3%
ASCII 2242
42.3%
CJK 23
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 834
37.2%
312
 
13.9%
1 232
 
10.3%
2 126
 
5.6%
3 113
 
5.0%
/ 103
 
4.6%
5 84
 
3.7%
g 70
 
3.1%
, 54
 
2.4%
9 47
 
2.1%
Other values (15) 267
 
11.9%
Hangul
ValueCountFrequency (%)
원 187
 
6.2%
업 72
 
2.4%
시 70
 
2.3%
인 69
 
2.3%
주 68
 
2.2%
분 61
 
2.0%
이 60
 
2.0%
상 59
 
1.9%
리 53
 
1.7%
지 53
 
1.7%
Other values (161) 2286
75.2%
CJK
ValueCountFrequency (%)
大 13
56.5%
小 10
43.5%

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 

Distinct654
Distinct (%)7.3%
Missing1050
Missing (%)10.5%
Memory size156.2 KiB
2024-04-17T18:57:23.643964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.027374
Min length10

Characters and Unicode

Total characters107645
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

Unique6 ?
Unique (%)0.1%

Sample

1st row051-293-2549
2nd row051-553-0199
3rd row0516274420
4th row010-0000-0000
5th row051-864-9090
ValueCountFrequency (%)
051-622-2234 66
 
0.7%
051-612-3808 64
 
0.7%
051-000-0000 58
 
0.6%
051-727-7644 57
 
0.6%
051-207-1472 54
 
0.6%
051-559-1592 51
 
0.6%
051-864-9090 49
 
0.5%
051-611-5727 48
 
0.5%
051-202-6514 47
 
0.5%
051-866-9612 43
 
0.5%
Other values (644) 8413
94.0%
2024-04-17T18:57:23.993370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17538
16.3%
0 17039
15.8%
5 15898
14.8%
1 14401
13.4%
2 8421
7.8%
7 6838
 
6.4%
3 6394
 
5.9%
8 6111
 
5.7%
6 5854
 
5.4%
4 5590
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90107
83.7%
Dash Punctuation 17538
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17039
18.9%
5 15898
17.6%
1 14401
16.0%
2 8421
9.3%
7 6838
7.6%
3 6394
 
7.1%
8 6111
 
6.8%
6 5854
 
6.5%
4 5590
 
6.2%
9 3561
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 17538
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107645
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17538
16.3%
0 17039
15.8%
5 15898
14.8%
1 14401
13.4%
2 8421
7.8%
7 6838
 
6.4%
3 6394
 
5.9%
8 6111
 
5.7%
6 5854
 
5.4%
4 5590
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107645
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17538
16.3%
0 17039
15.8%
5 15898
14.8%
1 14401
13.4%
2 8421
7.8%
7 6838
 
6.4%
3 6394
 
5.9%
8 6111
 
5.7%
6 5854
 
5.4%
4 5590
 
5.2%

parkng_at
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
6056 
Y
2894 
1050 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6056
60.6%
Y 2894
28.9%
1050
 
10.5%

Length

2024-04-17T18:57:24.116436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:24.198999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6056
67.7%
y 2894
32.3%

card_at
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
8428 
1050 
N
 
522

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 8428
84.3%
1050
 
10.5%
N 522
 
5.2%

Length

2024-04-17T18:57:24.289301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:24.371342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 8428
94.2%
n 522
 
5.8%

item_name
Categorical

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
돼지갈비(외식)
 
344
자장면
 
307
칼국수
 
307
PC방 이용료
 
306
노래방이용료
 
297
Other values (40)
8439 

Length

Max length8
Median length7
Mean length4.2426
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이용료
2nd row된장찌개백반
3rd row미용료
4th row양복세탁료
5th rowPC방 이용료

Common Values

ValueCountFrequency (%)
돼지갈비(외식) 344
 
3.4%
자장면 307
 
3.1%
칼국수 307
 
3.1%
PC방 이용료 306
 
3.1%
노래방이용료 297
 
3.0%
갈비탕 295
 
2.9%
양복세탁료 293
 
2.9%
삼겹살(외식) 290
 
2.9%
짬뽕 290
 
2.9%
당구장이용료 289
 
2.9%
Other values (35) 6982
69.8%

Length

2024-04-17T18:57:24.471385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이용료 775
 
7.4%
돼지갈비(외식 344
 
3.3%
자장면 307
 
2.9%
칼국수 307
 
2.9%
pc방 306
 
2.9%
노래방이용료 297
 
2.8%
갈비탕 295
 
2.8%
양복세탁료 293
 
2.8%
삼겹살(외식 290
 
2.8%
짬뽕 290
 
2.8%
Other values (35) 7011
66.7%

last_load_dttm
Categorical

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-03-01 06:17:10
1493 
2021-03-01 06:17:07
1312 
2021-03-01 06:17:05
1094 
2021-03-01 06:17:08
917 
2021-03-01 06:17:11
847 
Other values (6)
4337 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-01 06:17:05
2nd row2021-03-01 06:17:12
3rd row2021-03-01 06:17:11
4th row2021-03-01 06:17:10
5th row2021-03-01 06:17:09

Common Values

ValueCountFrequency (%)
2021-03-01 06:17:10 1493
14.9%
2021-03-01 06:17:07 1312
13.1%
2021-03-01 06:17:05 1094
10.9%
2021-03-01 06:17:08 917
9.2%
2021-03-01 06:17:11 847
8.5%
2021-03-01 06:17:12 832
8.3%
2021-03-01 06:17:03 793
7.9%
2021-03-01 06:17:09 772
7.7%
2021-03-01 06:17:04 767
7.7%
2021-03-01 06:17:06 677
6.8%

Length

2024-04-17T18:57:24.588300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-03-01 10000
50.0%
06:17:10 1493
 
7.5%
06:17:07 1312
 
6.6%
06:17:05 1094
 
5.5%
06:17:08 917
 
4.6%
06:17:11 847
 
4.2%
06:17:12 832
 
4.2%
06:17:03 793
 
4.0%
06:17:09 772
 
3.9%
06:17:04 767
 
3.8%
Other values (2) 1173
 
5.9%

Sample

skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
1442621332712912717995027525027521274192020-08-04466서비스216사하구110000<NA><NA><NA><NA><NA><NA>051-293-2549NY이용료2021-03-01 06:17:05
60142167550146144<NA>468263468263144<NA>2019-01-08454외식<NA><NA>10<NA><NA><NA><NA><NA><NA><NA>된장찌개백반2021-03-01 06:17:12
5382917384212812613764726914726911264192019-03-19466서비스104동래구110000<NA><NA><NA><NA><NA><NA>051-553-0199NY미용료2021-03-01 06:17:11
4118418652912512330244821704821701234192019-09-03466서비스57남구17000<NA><NA><NA><NA><NA><NA>0516274420NN양복세탁료2021-03-01 06:17:10
3741719025712212026034597094597091204192018-08-07465여가생활48기장군11200<NA><NA><NA><NA><NA><NA>010-0000-0000NYPC방 이용료2021-03-01 06:17:09
6204916570514214019814666254666251404192018-12-11454외식275연제구20010769<NA><NA><NA><NA><NA><NA>051-864-9090NY삼겹살(외식)2021-03-01 06:17:13
3271919501513813615514878734878731364192019-12-05454외식137부산진구115000<NA><NA><NA><NA><NA><NA>051-808-9981NY치킨2021-03-01 06:17:08
3610919162012212024864846214846211204192019-10-15465여가생활275연제구11200<NA><NA><NA><NA><NA><NA>010-8496-1313NYPC방 이용료2021-03-01 06:17:09
1604121170314013815755034675034671384192020-08-18454외식137부산진구17000<NA><NA><NA><NA><NA><NA>051-817-1282NY조리라면2021-03-01 06:17:05
4218618553011010817554812724812721084192019-08-20466서비스189사상구190000<NA><NA><NA><NA><NA><NA>051-312-8580NY숙박료(호텔)2021-03-01 06:17:10
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5311217457213213016454712914712911304192019-02-19455카페176북구13500<NA><NA><NA><NA><NA><NA>051-332-8686YY커피2021-03-01 06:17:11
4148218625212111926094841994841991194192019-10-01466서비스48기장군17000<NA>15~20kg(편의점)<NA><NA><NA><NA>051-721-2211YY택배2021-03-01 06:17:10
1438521328614814626765027225027221464192020-08-04454외식176북구113000<NA><NA><NA><NA><NA><NA>051-334-5657YY삼계탕2021-03-01 06:17:05
2500220273012912724304972274972271274192020-05-12466서비스48기장군19000<NA><NA><NA><NA><NA><NA>051-728-9297YY이용료2021-03-01 06:17:07
3534819238814113910184854074854071394192019-10-15454외식41금정구15000<NA><NA><NA><NA><NA><NA>051-512-6108NY자장면2021-03-01 06:17:08
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92922679214514331435137925137921434192021-02-09454외식48기장군18000<NA><NA><NA><NA><NA><NA>051-728-3546YY돼지국밥2021-03-01 06:17:03
3839118930313913730154588974588971374192018-07-24454외식226사하구16000<NA><NA><NA><NA><NA><NA>051-992-0007NY돈가스2021-03-01 06:17:09
1753821016413713525184994314994311354192020-06-09454외식40금정구16000<NA><NA><NA><NA><NA><NA>051-512-9044NY짬뽕2021-03-01 06:17:06
1925720844911611415374617664617661144192018-09-18466서비스137부산진구115000<NA><NA><NA><NA><NA><NA>051-816-0031NY사진(반명함판)2021-03-01 06:17:06