Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells62351
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
Categorical7
DateTime2
Unsupported5
Text2

Alerts

cl_no is highly imbalanced (52.7%)Imbalance
card_at is highly imbalanced (50.9%)Imbalance
bssh_no has 1013 (10.1%) missing valuesMissing
gugun_cd has 1019 (10.2%) missing valuesMissing
prices has 10000 (100.0%) missing valuesMissing
rm has 9306 (93.1%) 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 1013 (10.1%) 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 407 (4.1%) zerosZeros

Reproduction

Analysis started2024-04-17 09:57:28.291814
Analysis finished2024-04-17 09:57:28.820489
Duration0.53 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%
Mean197243.11
Minimum163981
Maximum231266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:28.877870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum163981
5-th percentile167229.85
Q1180241.5
median197304
Q3213774
95-th percentile227818.15
Maximum231266
Range67285
Interquartile range (IQR)33532.5

Descriptive statistics

Standard deviation19381.356
Coefficient of variation (CV)0.098261256
Kurtosis-1.1962939
Mean197243.11
Median Absolute Deviation (MAD)16755.5
Skewness0.02039778
Sum1.9724311 × 109
Variance3.7563696 × 108
MonotonicityNot monotonic
2024-04-17T18:57:28.995086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197772 1
 
< 0.1%
213258 1
 
< 0.1%
184104 1
 
< 0.1%
200314 1
 
< 0.1%
217087 1
 
< 0.1%
164878 1
 
< 0.1%
225713 1
 
< 0.1%
218438 1
 
< 0.1%
213604 1
 
< 0.1%
208467 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
163981 1
< 0.1%
163989 1
< 0.1%
163992 1
< 0.1%
164003 1
< 0.1%
164006 1
< 0.1%
164013 1
< 0.1%
164016 1
< 0.1%
164017 1
< 0.1%
164054 1
< 0.1%
164061 1
< 0.1%
ValueCountFrequency (%)
231266 1
< 0.1%
231256 1
< 0.1%
231251 1
< 0.1%
231248 1
< 0.1%
231247 1
< 0.1%
231239 1
< 0.1%
231238 1
< 0.1%
231232 1
< 0.1%
231227 1
< 0.1%
231226 1
< 0.1%

ccode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.0162
Minimum108
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:29.126679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum108
5-th percentile113
Q1124
median134
Q3143
95-th percentile150
Maximum152
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.562055
Coefficient of variation (CV)0.086922154
Kurtosis-0.93404027
Mean133.0162
Median Absolute Deviation (MAD)9
Skewness-0.21179961
Sum1330162
Variance133.68111
MonotonicityNot monotonic
2024-04-17T18:57:29.261800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
143 340
 
3.4%
123 318
 
3.2%
135 313
 
3.1%
125 312
 
3.1%
122 302
 
3.0%
142 298
 
3.0%
133 296
 
3.0%
134 294
 
2.9%
124 293
 
2.9%
130 292
 
2.9%
Other values (35) 6942
69.4%
ValueCountFrequency (%)
108 65
 
0.7%
109 2
 
< 0.1%
110 94
 
0.9%
111 9
 
0.1%
112 252
2.5%
113 204
2.0%
114 196
2.0%
115 206
2.1%
116 185
1.8%
117 116
1.2%
ValueCountFrequency (%)
152 250
2.5%
151 228
2.3%
150 250
2.5%
149 245
2.5%
148 272
2.7%
147 269
2.7%
146 252
2.5%
145 174
1.7%
144 264
2.6%
143 340
3.4%

pcode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.0162
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:29.388267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1122
median132
Q3141
95-th percentile148
Maximum150
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.562055
Coefficient of variation (CV)0.088249045
Kurtosis-0.93404027
Mean131.0162
Median Absolute Deviation (MAD)9
Skewness-0.21179961
Sum1310162
Variance133.68111
MonotonicityNot monotonic
2024-04-17T18:57:29.506317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 340
 
3.4%
121 318
 
3.2%
133 313
 
3.1%
123 312
 
3.1%
120 302
 
3.0%
140 298
 
3.0%
131 296
 
3.0%
132 294
 
2.9%
122 293
 
2.9%
128 292
 
2.9%
Other values (35) 6942
69.4%
ValueCountFrequency (%)
106 65
 
0.7%
107 2
 
< 0.1%
108 94
 
0.9%
109 9
 
0.1%
110 252
2.5%
111 204
2.0%
112 196
2.0%
113 206
2.1%
114 185
1.8%
115 116
1.2%
ValueCountFrequency (%)
150 250
2.5%
149 228
2.3%
148 250
2.5%
147 245
2.5%
146 272
2.7%
145 269
2.7%
144 252
2.5%
143 174
1.7%
142 264
2.6%
141 340
3.4%

bssh_no
Real number (ℝ)

MISSING 

Distinct675
Distinct (%)7.5%
Missing1013
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean2154.2943
Minimum985
Maximum3218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:29.631497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum985
5-th percentile1053
Q11530
median2024
Q32844
95-th percentile3091.4
Maximum3218
Range2233
Interquartile range (IQR)1314

Descriptive statistics

Standard deviation689.35429
Coefficient of variation (CV)0.31999077
Kurtosis-1.417217
Mean2154.2943
Median Absolute Deviation (MAD)667
Skewness-0.088874122
Sum19360643
Variance475209.34
MonotonicityNot monotonic
2024-04-17T18:57:29.747134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2982 67
 
0.7%
2693 58
 
0.6%
2002 54
 
0.5%
1140 51
 
0.5%
1981 49
 
0.5%
1798 48
 
0.5%
1978 43
 
0.4%
2690 42
 
0.4%
1456 42
 
0.4%
1530 42
 
0.4%
Other values (665) 8491
84.9%
(Missing) 1013
 
10.1%
ValueCountFrequency (%)
985 13
0.1%
986 13
0.1%
988 17
0.2%
991 13
0.1%
996 29
0.3%
997 11
 
0.1%
998 9
 
0.1%
999 8
 
0.1%
1004 26
0.3%
1012 12
0.1%
ValueCountFrequency (%)
3218 1
 
< 0.1%
3217 2
< 0.1%
3215 1
 
< 0.1%
3213 1
 
< 0.1%
3211 1
 
< 0.1%
3210 3
< 0.1%
3209 1
 
< 0.1%
3208 2
< 0.1%
3203 1
 
< 0.1%
3202 2
< 0.1%

search_no
Real number (ℝ)

Distinct9404
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean485942.38
Minimum456029
Maximum518796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:29.860343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456029
5-th percentile459173.8
Q1470284.5
median485407.5
Q3500897
95-th percentile514628.2
Maximum518796
Range62767
Interquartile range (IQR)30612.5

Descriptive statistics

Standard deviation17905.144
Coefficient of variation (CV)0.03684623
Kurtosis-1.1849819
Mean485942.38
Median Absolute Deviation (MAD)15269
Skewness0.1009516
Sum4.8594238 × 109
Variance3.2059419 × 108
MonotonicityNot monotonic
2024-04-17T18:57:29.983914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
464637 4
 
< 0.1%
475721 4
 
< 0.1%
467937 4
 
< 0.1%
464481 4
 
< 0.1%
515993 3
 
< 0.1%
513194 3
 
< 0.1%
517096 3
 
< 0.1%
460370 3
 
< 0.1%
476610 3
 
< 0.1%
472448 3
 
< 0.1%
Other values (9394) 9966
99.7%
ValueCountFrequency (%)
456029 2
< 0.1%
456033 1
< 0.1%
456035 1
< 0.1%
456044 1
< 0.1%
456050 1
< 0.1%
456055 1
< 0.1%
456062 1
< 0.1%
456064 1
< 0.1%
456072 1
< 0.1%
456075 1
< 0.1%
ValueCountFrequency (%)
518796 1
< 0.1%
518786 1
< 0.1%
518783 1
< 0.1%
518780 1
< 0.1%
518772 1
< 0.1%
518766 1
< 0.1%
518754 1
< 0.1%
518751 1
< 0.1%
518745 1
< 0.1%
518739 1
< 0.1%

prices_no
Real number (ℝ)

Distinct9404
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean485942.38
Minimum456029
Maximum518796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:30.126536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456029
5-th percentile459173.8
Q1470284.5
median485407.5
Q3500897
95-th percentile514628.2
Maximum518796
Range62767
Interquartile range (IQR)30612.5

Descriptive statistics

Standard deviation17905.144
Coefficient of variation (CV)0.03684623
Kurtosis-1.1849819
Mean485942.38
Median Absolute Deviation (MAD)15269
Skewness0.1009516
Sum4.8594238 × 109
Variance3.2059419 × 108
MonotonicityNot monotonic
2024-04-17T18:57:30.260314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
464637 4
 
< 0.1%
475721 4
 
< 0.1%
467937 4
 
< 0.1%
464481 4
 
< 0.1%
515993 3
 
< 0.1%
513194 3
 
< 0.1%
517096 3
 
< 0.1%
460370 3
 
< 0.1%
476610 3
 
< 0.1%
472448 3
 
< 0.1%
Other values (9394) 9966
99.7%
ValueCountFrequency (%)
456029 2
< 0.1%
456033 1
< 0.1%
456035 1
< 0.1%
456044 1
< 0.1%
456050 1
< 0.1%
456055 1
< 0.1%
456062 1
< 0.1%
456064 1
< 0.1%
456072 1
< 0.1%
456075 1
< 0.1%
ValueCountFrequency (%)
518796 1
< 0.1%
518786 1
< 0.1%
518783 1
< 0.1%
518780 1
< 0.1%
518772 1
< 0.1%
518766 1
< 0.1%
518754 1
< 0.1%
518751 1
< 0.1%
518745 1
< 0.1%
518739 1
< 0.1%

prdlst
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.0162
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:30.397073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1122
median132
Q3141
95-th percentile148
Maximum150
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.562055
Coefficient of variation (CV)0.088249045
Kurtosis-0.93404027
Mean131.0162
Median Absolute Deviation (MAD)9
Skewness-0.21179961
Sum1310162
Variance133.68111
MonotonicityNot monotonic
2024-04-17T18:57:30.829149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 340
 
3.4%
121 318
 
3.2%
133 313
 
3.1%
123 312
 
3.1%
120 302
 
3.0%
140 298
 
3.0%
131 296
 
3.0%
132 294
 
2.9%
122 293
 
2.9%
128 292
 
2.9%
Other values (35) 6942
69.4%
ValueCountFrequency (%)
106 65
 
0.7%
107 2
 
< 0.1%
108 94
 
0.9%
109 9
 
0.1%
110 252
2.5%
111 204
2.0%
112 196
2.0%
113 206
2.1%
114 185
1.8%
115 116
1.2%
ValueCountFrequency (%)
150 250
2.5%
149 228
2.3%
148 250
2.5%
147 245
2.5%
146 272
2.7%
145 269
2.7%
144 252
2.5%
143 174
1.7%
142 264
2.6%
141 340
3.4%

cl_no
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
419
8987 
<NA>
1013 

Length

Max length4
Median length3
Mean length3.1013
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
419 8987
89.9%
<NA> 1013
 
10.1%

Length

2024-04-17T18:57:30.933203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:31.026973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
419 8987
89.9%
na 1013
 
10.1%

examin_de
Date

Distinct79
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-06-12 00:00:00
Maximum2021-04-20 00:00:00
2024-04-17T18:57:31.138425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:57:31.265265image/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
5778 
466
2400 
465
1229 
455
 
528
467
 
65

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
454 5778
57.8%
466 2400
24.0%
465 1229
 
12.3%
455 528
 
5.3%
467 65
 
0.7%

Length

2024-04-17T18:57:31.375571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:31.473259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
454 5778
57.8%
466 2400
24.0%
465 1229
 
12.3%
455 528
 
5.3%
467 65
 
0.7%

pum_nm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
외식
5778 
서비스
2400 
여가생활
1229 
카페
 
528
기타
 
65

Length

Max length4
Median length2
Mean length2.4858
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외식 5778
57.8%
서비스 2400
24.0%
여가생활 1229
 
12.3%
카페 528
 
5.3%
기타 65
 
0.7%

Length

2024-04-17T18:57:31.583015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:31.694225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식 5778
57.8%
서비스 2400
24.0%
여가생활 1229
 
12.3%
카페 528
 
5.3%
기타 65
 
0.7%

gugun_cd
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)0.8%
Missing1019
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean177.17426
Minimum31
Maximum376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:31.811644image/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 deviation104.15077
Coefficient of variation (CV)0.5878437
Kurtosis-0.98678292
Mean177.17426
Median Absolute Deviation (MAD)85
Skewness0.3791641
Sum1591202
Variance10847.383
MonotonicityNot monotonic
2024-04-17T18:57:31.928981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189 723
 
7.2%
373 691
 
6.9%
275 657
 
6.6%
48 615
 
6.2%
216 536
 
5.4%
135 418
 
4.2%
41 407
 
4.1%
92 343
 
3.4%
95 340
 
3.4%
57 320
 
3.2%
Other values (63) 3931
39.3%
(Missing) 1019
 
10.2%
ValueCountFrequency (%)
31 13
 
0.1%
39 20
 
0.2%
40 155
 
1.6%
41 407
4.1%
42 35
 
0.4%
45 7
 
0.1%
48 615
6.2%
53 115
 
1.1%
54 29
 
0.3%
57 320
3.2%
ValueCountFrequency (%)
376 5
 
0.1%
373 691
6.9%
372 12
 
0.1%
370 18
 
0.2%
369 65
 
0.7%
365 12
 
0.1%
350 12
 
0.1%
346 39
 
0.4%
344 14
 
0.1%
338 30
 
0.3%

gugun_nm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
1019 
연제구
819 
해운대구
803 
부산진구
801 
동래구
791 
Other values (9)
5767 

Length

Max length4
Median length3
Mean length3.0142
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북구
2nd row기장군
3rd row동래구
4th row사상구
5th row사상구

Common Values

ValueCountFrequency (%)
<NA> 1019
10.2%
연제구 819
 
8.2%
해운대구 803
 
8.0%
부산진구 801
 
8.0%
동래구 791
 
7.9%
사상구 723
 
7.2%
북구 722
 
7.2%
사하구 714
 
7.1%
남구 650
 
6.5%
동구 632
 
6.3%
Other values (4) 2326
23.3%

Length

2024-04-17T18:57:32.054848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1019
10.2%
연제구 819
 
8.2%
해운대구 803
 
8.0%
부산진구 801
 
8.0%
동래구 791
 
7.9%
사상구 723
 
7.2%
북구 722
 
7.2%
사하구 714
 
7.1%
남구 650
 
6.5%
동구 632
 
6.3%
Other values (4) 2326
23.3%

unit
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.6884
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:32.155396image/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 deviation54.732391
Coefficient of variation (CV)2.9286826
Kurtosis6.8090162
Mean18.6884
Median Absolute Deviation (MAD)0
Skewness2.8973474
Sum186884
Variance2995.6347
MonotonicityNot monotonic
2024-04-17T18:57:32.263182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 9014
90.1%
200 697
 
7.0%
130 85
 
0.9%
120 63
 
0.6%
100 58
 
0.6%
150 29
 
0.3%
180 23
 
0.2%
110 11
 
0.1%
170 10
 
0.1%
350 6
 
0.1%
ValueCountFrequency (%)
1 9014
90.1%
100 58
 
0.6%
110 11
 
0.1%
120 63
 
0.6%
130 85
 
0.9%
140 4
 
< 0.1%
150 29
 
0.3%
170 10
 
0.1%
180 23
 
0.2%
200 697
 
7.0%
ValueCountFrequency (%)
350 6
 
0.1%
200 697
7.0%
180 23
 
0.2%
170 10
 
0.1%
150 29
 
0.3%
140 4
 
< 0.1%
130 85
 
0.9%
120 63
 
0.6%
110 11
 
0.1%
100 58
 
0.6%

unitprice
Real number (ℝ)

ZEROS 

Distinct216
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12498.056
Minimum0
Maximum326700
Zeros407
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T18:57:32.374145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile500
Q14000
median7000
Q313000
95-th percentile40000
Maximum326700
Range326700
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation22265.995
Coefficient of variation (CV)1.7815567
Kurtosis42.747003
Mean12498.056
Median Absolute Deviation (MAD)3666
Skewness5.8956627
Sum1.2498056 × 108
Variance4.9577453 × 108
MonotonicityNot monotonic
2024-04-17T18:57:32.496921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000 860
 
8.6%
7000 646
 
6.5%
3000 571
 
5.7%
5000 567
 
5.7%
10000 504
 
5.0%
15000 458
 
4.6%
9000 418
 
4.2%
0 407
 
4.1%
8000 303
 
3.0%
12000 267
 
2.7%
Other values (206) 4999
50.0%
ValueCountFrequency (%)
0 407
4.1%
35 1
 
< 0.1%
200 16
 
0.2%
250 7
 
0.1%
300 35
 
0.4%
350 12
 
0.1%
450 13
 
0.1%
500 28
 
0.3%
800 3
 
< 0.1%
1000 78
 
0.8%
ValueCountFrequency (%)
326700 1
 
< 0.1%
254100 1
 
< 0.1%
229900 2
 
< 0.1%
217800 6
 
0.1%
210000 11
0.1%
205700 2
 
< 0.1%
200000 19
0.2%
190000 11
0.1%
187550 1
 
< 0.1%
183000 2
 
< 0.1%

prices
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

rm
Text

MISSING 

Distinct115
Distinct (%)16.6%
Missing9306
Missing (%)93.1%
Memory size156.2 KiB
2024-04-17T18:57:32.762875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length19
Mean length7.6988473
Min length1

Characters and Unicode

Total characters5343
Distinct characters202
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

Unique18 ?
Unique (%)2.6%

Sample

1st row10분 1400원 (중)
2nd row大 : 22,000원 小:12,900
3rd row노래연습장
4th row페업
5th row녹차
ValueCountFrequency (%)
비회원 32
 
3.3%
10분 32
 
3.3%
1300 32
 
3.3%
주말 28
 
2.9%
50000 27
 
2.8%
주말30000 25
 
2.6%
아메리카노 19
 
2.0%
인상 18
 
1.9%
페업 18
 
1.9%
1400원 18
 
1.9%
Other values (121) 720
74.3%
2024-04-17T18:57:33.150623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 908
 
17.0%
366
 
6.9%
1 223
 
4.2%
원 190
 
3.6%
2 120
 
2.2%
3 120
 
2.2%
/ 105
 
2.0%
업 83
 
1.6%
주 83
 
1.6%
5 82
 
1.5%
Other values (192) 3063
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2986
55.9%
Decimal Number 1596
29.9%
Space Separator 366
 
6.9%
Other Punctuation 206
 
3.9%
Lowercase Letter 93
 
1.7%
Close Punctuation 35
 
0.7%
Open Punctuation 35
 
0.7%
Math Symbol 15
 
0.3%
Uppercase Letter 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 190
 
6.4%
업 83
 
2.8%
주 83
 
2.8%
분 70
 
2.3%
말 67
 
2.2%
상 66
 
2.2%
이 64
 
2.1%
시 61
 
2.0%
인 61
 
2.0%
회 49
 
1.6%
Other values (167) 2192
73.4%
Decimal Number
ValueCountFrequency (%)
0 908
56.9%
1 223
 
14.0%
2 120
 
7.5%
3 120
 
7.5%
5 82
 
5.1%
4 54
 
3.4%
9 48
 
3.0%
7 20
 
1.3%
8 12
 
0.8%
6 9
 
0.6%
Other Punctuation
ValueCountFrequency (%)
/ 105
51.0%
, 67
32.5%
: 21
 
10.2%
* 9
 
4.4%
% 3
 
1.5%
. 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
g 53
57.0%
k 22
23.7%
c 9
 
9.7%
m 9
 
9.7%
Space Separator
ValueCountFrequency (%)
366
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2965
55.5%
Common 2253
42.2%
Latin 104
 
1.9%
Han 21
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 190
 
6.4%
업 83
 
2.8%
주 83
 
2.8%
분 70
 
2.4%
말 67
 
2.3%
상 66
 
2.2%
이 64
 
2.2%
시 61
 
2.1%
인 61
 
2.1%
회 49
 
1.7%
Other values (165) 2171
73.2%
Common
ValueCountFrequency (%)
0 908
40.3%
366
16.2%
1 223
 
9.9%
2 120
 
5.3%
3 120
 
5.3%
/ 105
 
4.7%
5 82
 
3.6%
, 67
 
3.0%
4 54
 
2.4%
9 48
 
2.1%
Other values (10) 160
 
7.1%
Latin
ValueCountFrequency (%)
g 53
51.0%
k 22
21.2%
R 11
 
10.6%
c 9
 
8.7%
m 9
 
8.7%
Han
ValueCountFrequency (%)
大 11
52.4%
小 10
47.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2965
55.5%
ASCII 2357
44.1%
CJK 21
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 908
38.5%
366
15.5%
1 223
 
9.5%
2 120
 
5.1%
3 120
 
5.1%
/ 105
 
4.5%
5 82
 
3.5%
, 67
 
2.8%
4 54
 
2.3%
g 53
 
2.2%
Other values (15) 259
 
11.0%
Hangul
ValueCountFrequency (%)
원 190
 
6.4%
업 83
 
2.8%
주 83
 
2.8%
분 70
 
2.4%
말 67
 
2.3%
상 66
 
2.2%
이 64
 
2.2%
시 61
 
2.1%
인 61
 
2.1%
회 49
 
1.7%
Other values (165) 2171
73.2%
CJK
ValueCountFrequency (%)
大 11
52.4%
小 10
47.6%

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 

Distinct661
Distinct (%)7.4%
Missing1013
Missing (%)10.1%
Memory size156.2 KiB
2024-04-17T18:57:33.375876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.026038
Min length10

Characters and Unicode

Total characters108078
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

Unique13 ?
Unique (%)0.1%

Sample

1st row051-341-3005
2nd row051-727-0905
3rd row051-553-5000
4th row051-322-2456
5th row051-313-3759
ValueCountFrequency (%)
051-612-3808 67
 
0.7%
051-622-2234 58
 
0.6%
051-866-9612 54
 
0.6%
051-000-0000 54
 
0.6%
051-559-1592 51
 
0.6%
051-611-5727 51
 
0.6%
051-864-9090 49
 
0.5%
051-207-1472 48
 
0.5%
051-865-9339 43
 
0.5%
051-727-7644 42
 
0.5%
Other values (651) 8470
94.2%
2024-04-17T18:57:33.705934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17594
16.3%
0 17066
15.8%
5 16126
14.9%
1 14314
13.2%
2 8357
7.7%
7 6868
 
6.4%
3 6432
 
6.0%
8 6229
 
5.8%
6 5963
 
5.5%
4 5448
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90484
83.7%
Dash Punctuation 17594
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17066
18.9%
5 16126
17.8%
1 14314
15.8%
2 8357
9.2%
7 6868
7.6%
3 6432
 
7.1%
8 6229
 
6.9%
6 5963
 
6.6%
4 5448
 
6.0%
9 3681
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 17594
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108078
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17594
16.3%
0 17066
15.8%
5 16126
14.9%
1 14314
13.2%
2 8357
7.7%
7 6868
 
6.4%
3 6432
 
6.0%
8 6229
 
5.8%
6 5963
 
5.5%
4 5448
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108078
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17594
16.3%
0 17066
15.8%
5 16126
14.9%
1 14314
13.2%
2 8357
7.7%
7 6868
 
6.4%
3 6432
 
6.0%
8 6229
 
5.8%
6 5963
 
5.5%
4 5448
 
5.0%

parkng_at
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
6131 
Y
2856 
1013 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6131
61.3%
Y 2856
28.6%
1013
 
10.1%

Length

2024-04-17T18:57:33.827404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:33.918915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6131
68.2%
y 2856
31.8%

card_at
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
8422 
1013 
N
 
565

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 8422
84.2%
1013
 
10.1%
N 565
 
5.7%

Length

2024-04-17T18:57:34.005808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:57:34.083462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 8422
93.7%
n 565
 
6.3%

item_name
Categorical

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
돼지갈비(외식)
 
340
노래방이용료
 
318
탕수육
 
313
양복세탁료
 
312
PC방 이용료
 
302
Other values (40)
8415 

Length

Max length8
Median length6
Mean length4.264
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row택배
2nd row당구장이용료
3rd row치킨
4th row김치찌개백반
5th row탕수육

Common Values

ValueCountFrequency (%)
돼지갈비(외식) 340
 
3.4%
노래방이용료 318
 
3.2%
탕수육 313
 
3.1%
양복세탁료 312
 
3.1%
PC방 이용료 302
 
3.0%
삼겹살(외식) 298
 
3.0%
김밥 296
 
3.0%
칼국수 294
 
2.9%
당구장이용료 293
 
2.9%
숙박료(여관) 292
 
2.9%
Other values (35) 6942
69.4%

Length

2024-04-17T18:57:34.187397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이용료 774
 
7.4%
돼지갈비(외식 340
 
3.2%
노래방이용료 318
 
3.0%
탕수육 313
 
3.0%
양복세탁료 312
 
3.0%
pc방 302
 
2.9%
삼겹살(외식 298
 
2.8%
김밥 296
 
2.8%
칼국수 294
 
2.8%
당구장이용료 293
 
2.8%
Other values (35) 6968
66.3%

last_load_dttm
Date

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-05-01 06:17:03
Maximum2021-05-01 06:17:13
2024-04-17T18:57:34.291242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:57:34.390853image/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
3350019777212111930944927224927221194192020-02-18466서비스178북구18000<NA><NA><NA><NA><NA><NA>051-341-3005YY택배2021-05-01 06:17:08
3907619217712412224194852534852531224192019-10-15465여가생활48기장군18400<NA>10분 1400원 (중)<NA><NA><NA><NA>051-727-0905YY당구장이용료2021-05-01 06:17:09
5431117691713813613694732824732821364192019-04-02454외식97동래구116000<NA><NA><NA><NA><NA><NA>051-553-5000NY치킨2021-05-01 06:17:11
4598518529214714528614808004808001454192019-08-06454외식189사상구16000<NA><NA><NA><NA><NA><NA>051-322-2456NN김치찌개백반2021-05-01 06:17:10
4570518558613513330234813134813131334192019-08-20454외식189사상구112900<NA>大 : 22,000원 小:12,900<NA><NA><NA><NA>051-313-3759NY탕수육2021-05-01 06:17:10
5656517466014414224984713854713851424192019-02-19454외식41금정구20050000<NA><NA><NA><NA><NA><NA>051-517-4300YY등심구이2021-05-01 06:17:12
78782233651261249865132285132281244192021-01-26466서비스39금정구17000<NA><NA><NA><NA><NA><NA>051-582-9850NY찜질방이용료2021-05-01 06:17:04
1178521948213112930315089515089511294192020-11-10455카페261수영구13000<NA><NA><NA><NA><NA><NA>051-611-7412NN국산차2021-05-01 06:17:05
1817321313614113915305026105026101394192020-08-04454외식137부산진구15000<NA><NA><NA><NA><NA><NA>051-816-1649NY자장면2021-05-01 06:17:06
2966120164315114917984940544940541494192020-03-17454외식216사하구15000<NA><NA><NA><NA><NA><NA>051-207-1472NY냉면2021-05-01 06:17:07
skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
770622357714714529824644814644811454192018-10-30454외식259수영구16000<NA><NA><NA><NA><NA><NA>051-612-3808NN김치찌개백반2021-05-01 06:17:04
2758120365911211016214959444959441104192020-04-14454외식176북구13900<NA><NA><NA><NA><NA><NA>051-337-8686NY불고기버거2021-05-01 06:17:07
5621317506913913713724717374717371374192019-03-05454외식104동래구16000<NA><NA><NA><NA><NA><NA>051-555-9349NY돈가스2021-05-01 06:17:12
2757620365413713516164959404959401354192020-04-14454외식176북구16000<NA><NA><NA><NA><NA><NA>051-332-6613NY짬뽕2021-05-01 06:17:07
2332920790515215017794611534611531504192018-09-04454외식216사하구110000<NA><NA><NA><NA><NA><NA>051-207-4656NY곰탕2021-05-01 06:17:07
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