Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells7105
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 MiB
Average record size in memory231.0 B

Variable types

Numeric15
DateTime2
Categorical5
Text4

Alerts

parkng_at is highly imbalanced (94.5%)Imbalance
card_at is highly imbalanced (97.0%)Imbalance
rm has 6855 (68.5%) missing valuesMissing
skey has unique valuesUnique
unitprice has 145 (1.5%) zerosZeros
prices has 145 (1.5%) zerosZeros

Reproduction

Analysis started2024-04-21 09:18:35.839160
Analysis finished2024-04-21 09:18:37.193996
Duration1.35 second
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%
Mean22613.827
Minimum1567
Maximum43621
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:37.328296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1567
5-th percentile3697.9
Q112102.5
median22592.5
Q333187.75
95-th percentile41489.15
Maximum43621
Range42054
Interquartile range (IQR)21085.25

Descriptive statistics

Standard deviation12150.367
Coefficient of variation (CV)0.53729813
Kurtosis-1.205511
Mean22613.827
Median Absolute Deviation (MAD)10546.5
Skewness-0.00046281192
Sum2.2613827 × 108
Variance1.4763141 × 108
MonotonicityNot monotonic
2024-04-21T18:18:37.569401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25417 1
 
< 0.1%
7756 1
 
< 0.1%
42008 1
 
< 0.1%
9975 1
 
< 0.1%
21612 1
 
< 0.1%
39295 1
 
< 0.1%
30289 1
 
< 0.1%
42284 1
 
< 0.1%
4632 1
 
< 0.1%
12605 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1567 1
< 0.1%
1569 1
< 0.1%
1570 1
< 0.1%
1572 1
< 0.1%
1576 1
< 0.1%
1581 1
< 0.1%
1586 1
< 0.1%
1588 1
< 0.1%
1589 1
< 0.1%
1595 1
< 0.1%
ValueCountFrequency (%)
43621 1
< 0.1%
43619 1
< 0.1%
43611 1
< 0.1%
43608 1
< 0.1%
43607 1
< 0.1%
43603 1
< 0.1%
43600 1
< 0.1%
43591 1
< 0.1%
43586 1
< 0.1%
43577 1
< 0.1%

ccode
Real number (ℝ)

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.7069
Minimum77
Maximum159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:37.793055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum77
5-th percentile78
Q183
median90
Q3100
95-th percentile156
Maximum159
Range82
Interquartile range (IQR)17

Descriptive statistics

Standard deviation19.282146
Coefficient of variation (CV)0.20359812
Kurtosis4.9257402
Mean94.7069
Median Absolute Deviation (MAD)8
Skewness2.2806129
Sum947069
Variance371.80117
MonotonicityNot monotonic
2024-04-21T18:18:38.008626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
78 424
 
4.2%
79 421
 
4.2%
80 412
 
4.1%
83 409
 
4.1%
82 407
 
4.1%
106 405
 
4.0%
87 399
 
4.0%
77 394
 
3.9%
81 394
 
3.9%
90 393
 
3.9%
Other values (22) 5942
59.4%
ValueCountFrequency (%)
77 394
3.9%
78 424
4.2%
79 421
4.2%
80 412
4.1%
81 394
3.9%
82 407
4.1%
83 409
4.1%
84 384
3.8%
85 266
2.7%
86 265
2.6%
ValueCountFrequency (%)
159 81
 
0.8%
158 79
 
0.8%
157 278
2.8%
156 279
2.8%
106 405
4.0%
105 260
2.6%
104 256
2.6%
103 245
2.5%
101 374
3.7%
100 278
2.8%

pcode
Real number (ℝ)

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.6352
Minimum76
Maximum157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:38.229343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum76
5-th percentile77
Q182
median89
Q399
95-th percentile154
Maximum157
Range81
Interquartile range (IQR)17

Descriptive statistics

Standard deviation19.051027
Coefficient of variation (CV)0.20346009
Kurtosis4.8381838
Mean93.6352
Median Absolute Deviation (MAD)8
Skewness2.2572696
Sum936352
Variance362.94162
MonotonicityNot monotonic
2024-04-21T18:18:38.666523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
77 424
 
4.2%
78 421
 
4.2%
79 412
 
4.1%
82 409
 
4.1%
81 407
 
4.1%
105 405
 
4.0%
86 399
 
4.0%
76 394
 
3.9%
80 394
 
3.9%
89 393
 
3.9%
Other values (22) 5942
59.4%
ValueCountFrequency (%)
76 394
3.9%
77 424
4.2%
78 421
4.2%
79 412
4.1%
80 394
3.9%
81 407
4.1%
82 409
4.1%
83 384
3.8%
84 266
2.7%
85 265
2.6%
ValueCountFrequency (%)
157 81
 
0.8%
156 79
 
0.8%
155 278
2.8%
154 279
2.8%
105 405
4.0%
104 260
2.6%
103 256
2.6%
102 245
2.5%
100 374
3.7%
99 278
2.8%

bssh_no
Real number (ℝ)

Distinct53
Distinct (%)0.5%
Missing31
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean382.18899
Minimum14
Maximum3028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:38.918342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile19
Q129
median39
Q358
95-th percentile2625
Maximum3028
Range3014
Interquartile range (IQR)29

Descriptive statistics

Standard deviation886.22252
Coefficient of variation (CV)2.3188071
Kurtosis2.9708605
Mean382.18899
Median Absolute Deviation (MAD)11
Skewness2.2136525
Sum3810042
Variance785390.36
MonotonicityNot monotonic
2024-04-21T18:18:39.162406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 354
 
3.5%
2524 345
 
3.5%
38 343
 
3.4%
28 342
 
3.4%
41 338
 
3.4%
2625 329
 
3.3%
22 326
 
3.3%
32 324
 
3.2%
31 320
 
3.2%
42 314
 
3.1%
Other values (43) 6634
66.3%
ValueCountFrequency (%)
14 64
 
0.6%
15 65
 
0.7%
17 76
 
0.8%
19 296
3.0%
20 282
2.8%
22 326
3.3%
23 300
3.0%
25 308
3.1%
26 291
2.9%
28 342
3.4%
ValueCountFrequency (%)
3028 270
2.7%
2814 1
 
< 0.1%
2625 329
3.3%
2562 299
3.0%
2524 345
3.5%
2349 65
 
0.7%
87 74
 
0.7%
85 77
 
0.8%
80 83
 
0.8%
79 81
 
0.8%

search_no
Real number (ℝ)

Distinct1473
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean473022.97
Minimum464693
Maximum481965
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:39.407606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum464693
5-th percentile465539
Q1469021
median472935
Q3476996
95-th percentile480231
Maximum481965
Range17272
Interquartile range (IQR)7975

Descriptive statistics

Standard deviation4902.215
Coefficient of variation (CV)0.010363588
Kurtosis-1.1690431
Mean473022.97
Median Absolute Deviation (MAD)4048
Skewness-0.023757469
Sum4.7302297 × 109
Variance24031712
MonotonicityNot monotonic
2024-04-21T18:18:39.658665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
476984 32
 
0.3%
476981 26
 
0.3%
478649 25
 
0.2%
477045 24
 
0.2%
480233 24
 
0.2%
478642 24
 
0.2%
480232 24
 
0.2%
467297 23
 
0.2%
476983 23
 
0.2%
480222 23
 
0.2%
Other values (1463) 9752
97.5%
ValueCountFrequency (%)
464693 4
 
< 0.1%
464694 11
0.1%
464695 7
0.1%
464696 7
0.1%
464697 8
0.1%
464698 10
0.1%
464699 10
0.1%
464700 5
0.1%
464701 10
0.1%
464702 5
0.1%
ValueCountFrequency (%)
481965 2
 
< 0.1%
481963 4
< 0.1%
481962 3
 
< 0.1%
481956 4
< 0.1%
481955 2
 
< 0.1%
481954 3
 
< 0.1%
481949 7
0.1%
481945 5
0.1%
481935 7
0.1%
481934 9
0.1%

prices_no
Real number (ℝ)

Distinct1473
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean473022.97
Minimum464693
Maximum481965
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:39.913912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum464693
5-th percentile465539
Q1469021
median472935
Q3476996
95-th percentile480231
Maximum481965
Range17272
Interquartile range (IQR)7975

Descriptive statistics

Standard deviation4902.215
Coefficient of variation (CV)0.010363588
Kurtosis-1.1690431
Mean473022.97
Median Absolute Deviation (MAD)4048
Skewness-0.023757469
Sum4.7302297 × 109
Variance24031712
MonotonicityNot monotonic
2024-04-21T18:18:40.178487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
476984 32
 
0.3%
476981 26
 
0.3%
478649 25
 
0.2%
477045 24
 
0.2%
480233 24
 
0.2%
478642 24
 
0.2%
480232 24
 
0.2%
467297 23
 
0.2%
476983 23
 
0.2%
480222 23
 
0.2%
Other values (1463) 9752
97.5%
ValueCountFrequency (%)
464693 4
 
< 0.1%
464694 11
0.1%
464695 7
0.1%
464696 7
0.1%
464697 8
0.1%
464698 10
0.1%
464699 10
0.1%
464700 5
0.1%
464701 10
0.1%
464702 5
0.1%
ValueCountFrequency (%)
481965 2
 
< 0.1%
481963 4
< 0.1%
481962 3
 
< 0.1%
481956 4
< 0.1%
481955 2
 
< 0.1%
481954 3
 
< 0.1%
481949 7
0.1%
481945 5
0.1%
481935 7
0.1%
481934 9
0.1%

prdlst
Real number (ℝ)

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.6352
Minimum76
Maximum157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:40.420535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum76
5-th percentile77
Q182
median89
Q399
95-th percentile154
Maximum157
Range81
Interquartile range (IQR)17

Descriptive statistics

Standard deviation19.051027
Coefficient of variation (CV)0.20346009
Kurtosis4.8381838
Mean93.6352
Median Absolute Deviation (MAD)8
Skewness2.2572696
Sum936352
Variance362.94162
MonotonicityNot monotonic
2024-04-21T18:18:40.662387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
77 424
 
4.2%
78 421
 
4.2%
79 412
 
4.1%
82 409
 
4.1%
81 407
 
4.1%
105 405
 
4.0%
86 399
 
4.0%
76 394
 
3.9%
80 394
 
3.9%
89 393
 
3.9%
Other values (22) 5942
59.4%
ValueCountFrequency (%)
76 394
3.9%
77 424
4.2%
78 421
4.2%
79 412
4.1%
80 394
3.9%
81 407
4.1%
82 409
4.1%
83 384
3.8%
84 266
2.7%
85 265
2.6%
ValueCountFrequency (%)
157 81
 
0.8%
156 79
 
0.8%
155 278
2.8%
154 279
2.8%
105 405
4.0%
104 260
2.6%
103 256
2.6%
102 245
2.5%
100 374
3.7%
99 278
2.8%

cl_no
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing31
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean409.11496
Minimum405
Maximum419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:40.870241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum405
5-th percentile405
Q1406
median407
Q3411
95-th percentile417
Maximum419
Range14
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.4224894
Coefficient of variation (CV)0.010809894
Kurtosis-0.69973753
Mean409.11496
Median Absolute Deviation (MAD)1
Skewness0.96841623
Sum4078467
Variance19.558413
MonotonicityNot monotonic
2024-04-21T18:18:41.052010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
406 2484
24.8%
417 1908
19.1%
407 1901
19.0%
405 1550
15.5%
411 643
 
6.4%
408 600
 
6.0%
410 589
 
5.9%
416 293
 
2.9%
419 1
 
< 0.1%
(Missing) 31
 
0.3%
ValueCountFrequency (%)
405 1550
15.5%
406 2484
24.8%
407 1901
19.0%
408 600
 
6.0%
410 589
 
5.9%
411 643
 
6.4%
416 293
 
2.9%
417 1908
19.1%
419 1
 
< 0.1%
ValueCountFrequency (%)
419 1
 
< 0.1%
417 1908
19.1%
416 293
 
2.9%
411 643
 
6.4%
410 589
 
5.9%
408 600
 
6.0%
407 1901
19.0%
406 2484
24.8%
405 1550
15.5%

examin_de
Date

Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-11-01 00:00:00
Maximum2019-08-28 00:00:00
2024-04-21T18:18:41.279819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:18:41.531523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

pum_cd
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean459.5536
Minimum456
Maximum464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:41.729437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456
5-th percentile456
Q1456
median459
Q3463
95-th percentile464
Maximum464
Range8
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.1291702
Coefficient of variation (CV)0.0068091518
Kurtosis-1.5093287
Mean459.5536
Median Absolute Deviation (MAD)3
Skewness0.20170261
Sum4595536
Variance9.7917062
MonotonicityNot monotonic
2024-04-21T18:18:41.928935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
456 3256
32.6%
464 1988
19.9%
461 1822
18.2%
458 1560
15.6%
463 820
 
8.2%
459 554
 
5.5%
ValueCountFrequency (%)
456 3256
32.6%
458 1560
15.6%
459 554
 
5.5%
461 1822
18.2%
463 820
 
8.2%
464 1988
19.9%
ValueCountFrequency (%)
464 1988
19.9%
463 820
 
8.2%
461 1822
18.2%
459 554
 
5.5%
458 1560
15.6%
456 3256
32.6%

pum_nm
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
농산물
3256 
식료품
1988 
주류및음료,차
1822 
축산물
1560 
세제
820 

Length

Max length7
Median length3
Mean length3.6468
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식료품
2nd row주류및음료,차
3rd row수산물
4th row농산물
5th row주류및음료,차

Common Values

ValueCountFrequency (%)
농산물 3256
32.6%
식료품 1988
19.9%
주류및음료,차 1822
18.2%
축산물 1560
15.6%
세제 820
 
8.2%
수산물 554
 
5.5%

Length

2024-04-21T18:18:42.152378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:18:42.340246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농산물 3256
32.6%
식료품 1988
19.9%
주류및음료,차 1822
18.2%
축산물 1560
15.6%
세제 820
 
8.2%
수산물 554
 
5.5%

gugun_cd
Real number (ℝ)

Distinct47
Distinct (%)0.5%
Missing31
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean187.8068
Minimum21
Maximum374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:42.558724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile31
Q195
median188
Q3262
95-th percentile365
Maximum374
Range353
Interquartile range (IQR)167

Descriptive statistics

Standard deviation103.56378
Coefficient of variation (CV)0.55143785
Kurtosis-0.98603699
Mean187.8068
Median Absolute Deviation (MAD)84
Skewness0.17681979
Sum1872246
Variance10725.456
MonotonicityNot monotonic
2024-04-21T18:18:42.802608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
189 596
 
6.0%
374 395
 
4.0%
111 376
 
3.8%
227 363
 
3.6%
273 354
 
3.5%
174 345
 
3.5%
360 343
 
3.4%
145 342
 
3.4%
223 338
 
3.4%
365 329
 
3.3%
Other values (37) 6188
61.9%
ValueCountFrequency (%)
21 283
2.8%
27 67
 
0.7%
31 300
3.0%
33 63
 
0.6%
48 297
3.0%
52 308
3.1%
53 94
 
0.9%
64 307
3.1%
66 79
 
0.8%
80 71
 
0.7%
ValueCountFrequency (%)
374 395
4.0%
369 70
 
0.7%
365 329
3.3%
360 343
3.4%
333 71
 
0.7%
316 298
3.0%
314 76
 
0.8%
293 320
3.2%
275 77
 
0.8%
273 354
3.5%

gugun_nm
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
해운대구
1137 
부산진구
813 
북구
797 
남구
788 
사하구
772 
Other values (12)
5693 

Length

Max length4
Median length3
Mean length2.9095
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해운대구
2nd row동구
3rd row기장군
4th row부산진구
5th row동래구

Common Values

ValueCountFrequency (%)
해운대구 1137
11.4%
부산진구 813
 
8.1%
북구 797
 
8.0%
남구 788
 
7.9%
사하구 772
 
7.7%
동래구 759
 
7.6%
사상구 725
 
7.2%
수영구 716
 
7.2%
금정구 713
 
7.1%
연제구 505
 
5.1%
Other values (7) 2275
22.8%

Length

2024-04-21T18:18:43.059136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
해운대구 1137
11.4%
부산진구 813
 
8.1%
북구 797
 
8.0%
남구 788
 
7.9%
사하구 772
 
7.7%
동래구 759
 
7.6%
사상구 725
 
7.2%
수영구 716
 
7.2%
금정구 713
 
7.1%
연제구 505
 
5.1%
Other values (7) 2275
22.8%

unit
Real number (ℝ)

Distinct241
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean694.02037
Minimum0
Maximum9000
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:43.331346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median400
Q31000
95-th percentile2400
Maximum9000
Range9000
Interquartile range (IQR)997

Descriptive statistics

Standard deviation1036.3916
Coefficient of variation (CV)1.4933158
Kurtosis12.164778
Mean694.02037
Median Absolute Deviation (MAD)398
Skewness3.0258208
Sum6940203.7
Variance1074107.6
MonotonicityNot monotonic
2024-04-21T18:18:43.568980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500.0 1186
 
11.9%
100.0 794
 
7.9%
1.0 792
 
7.9%
1000.0 740
 
7.4%
2000.0 622
 
6.2%
600.0 525
 
5.2%
1.8 493
 
4.9%
20.0 405
 
4.0%
320.0 278
 
2.8%
360.0 270
 
2.7%
Other values (231) 3895
39.0%
ValueCountFrequency (%)
0.0 6
 
0.1%
0.1 22
 
0.2%
0.8 18
 
0.2%
0.9 252
 
2.5%
1.0 792
7.9%
1.05 10
 
0.1%
1.1 12
 
0.1%
1.2 20
 
0.2%
1.4 144
 
1.4%
1.5 232
 
2.3%
ValueCountFrequency (%)
9000.0 5
 
0.1%
8000.0 1
 
< 0.1%
6000.0 166
1.7%
5000.0 9
 
0.1%
4500.0 5
 
0.1%
3800.0 1
 
< 0.1%
3744.0 6
 
0.1%
3700.0 6
 
0.1%
3600.0 1
 
< 0.1%
3500.0 6
 
0.1%

unitprice
Real number (ℝ)

ZEROS 

Distinct1621
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9539.7161
Minimum0
Maximum70000
Zeros145
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:43.803000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile796
Q12000
median3980
Q38950
95-th percentile47142
Maximum70000
Range70000
Interquartile range (IQR)6950

Descriptive statistics

Standard deviation13484.397
Coefficient of variation (CV)1.4135009
Kurtosis4.457207
Mean9539.7161
Median Absolute Deviation (MAD)2570
Skewness2.2981755
Sum95397161
Variance1.8182897 × 108
MonotonicityNot monotonic
2024-04-21T18:18:44.051919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1190 201
 
2.0%
676 191
 
1.9%
2500 190
 
1.9%
2000 184
 
1.8%
796 152
 
1.5%
0 145
 
1.5%
3500 143
 
1.4%
1410 129
 
1.3%
7250 129
 
1.3%
3000 117
 
1.2%
Other values (1611) 8419
84.2%
ValueCountFrequency (%)
0 145
1.5%
279 1
 
< 0.1%
303 1
 
< 0.1%
390 1
 
< 0.1%
468 1
 
< 0.1%
531 1
 
< 0.1%
541 1
 
< 0.1%
590 2
 
< 0.1%
596 1
 
< 0.1%
666 2
 
< 0.1%
ValueCountFrequency (%)
70000 2
 
< 0.1%
65000 4
 
< 0.1%
63000 4
 
< 0.1%
60800 1
 
< 0.1%
60500 10
0.1%
60000 23
0.2%
59900 21
0.2%
59800 1
 
< 0.1%
59500 1
 
< 0.1%
59000 17
0.2%

prices
Real number (ℝ)

ZEROS 

Distinct1099
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7987.0742
Minimum0
Maximum70000
Zeros145
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:44.310784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile800
Q12000
median3500
Q37980
95-th percentile40000
Maximum70000
Range70000
Interquartile range (IQR)5980

Descriptive statistics

Standard deviation11879.797
Coefficient of variation (CV)1.4873778
Kurtosis8.5077137
Mean7987.0742
Median Absolute Deviation (MAD)2100
Skewness2.9611147
Sum79870742
Variance1.4112957 × 108
MonotonicityNot monotonic
2024-04-21T18:18:44.775562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2500 225
 
2.2%
1190 205
 
2.1%
2000 197
 
2.0%
3000 175
 
1.8%
5000 173
 
1.7%
0 145
 
1.5%
3500 145
 
1.5%
1500 129
 
1.3%
1410 129
 
1.3%
7250 129
 
1.3%
Other values (1089) 8348
83.5%
ValueCountFrequency (%)
0 145
1.5%
145 1
 
< 0.1%
187 1
 
< 0.1%
192 1
 
< 0.1%
199 1
 
< 0.1%
200 2
 
< 0.1%
220 1
 
< 0.1%
224 2
 
< 0.1%
225 2
 
< 0.1%
237 2
 
< 0.1%
ValueCountFrequency (%)
70000 2
 
< 0.1%
65000 4
 
< 0.1%
63000 3
 
< 0.1%
60800 1
 
< 0.1%
60500 10
0.1%
60000 23
0.2%
59900 21
0.2%
59800 1
 
< 0.1%
59500 1
 
< 0.1%
59000 12
0.1%

rm
Text

MISSING 

Distinct994
Distinct (%)31.6%
Missing6855
Missing (%)68.5%
Memory size156.2 KiB
2024-04-21T18:18:45.597979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length7.1863275
Min length1

Characters and Unicode

Total characters22601
Distinct characters361
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique562 ?
Unique (%)17.9%

Sample

1st row시원소주
2nd row 품절
3rd row흙대파
4th rowLG테그업4Kg(2kg*2) 2/26~3/4
5th row전통청결미
ValueCountFrequency (%)
행사 174
 
4.6%
없음 51
 
1.4%
1등급 46
 
1.2%
이맛쌀 42
 
1.1%
하우스밀감 41
 
1.1%
샘표501 39
 
1.0%
품절 39
 
1.0%
햇양파 37
 
1.0%
하우스 35
 
0.9%
1+1 33
 
0.9%
Other values (926) 3233
85.8%
2024-04-21T18:18:46.676389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1618
 
7.2%
1457
 
6.4%
1 1109
 
4.9%
/ 812
 
3.6%
2 617
 
2.7%
3 539
 
2.4%
사 447
 
2.0%
g 434
 
1.9%
5 417
 
1.8%
9 416
 
1.8%
Other values (351) 14735
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12720
56.3%
Decimal Number 5743
25.4%
Space Separator 1457
 
6.4%
Other Punctuation 1233
 
5.5%
Lowercase Letter 644
 
2.8%
Math Symbol 281
 
1.2%
Uppercase Letter 273
 
1.2%
Close Punctuation 106
 
0.5%
Open Punctuation 103
 
0.5%
Dash Punctuation 41
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 447
 
3.5%
행 353
 
2.8%
기 235
 
1.8%
원 233
 
1.8%
고 221
 
1.7%
생 210
 
1.7%
이 203
 
1.6%
지 198
 
1.6%
쌀 195
 
1.5%
등 194
 
1.5%
Other values (303) 10231
80.4%
Lowercase Letter
ValueCountFrequency (%)
g 434
67.4%
k 76
 
11.8%
m 47
 
7.3%
l 42
 
6.5%
p 11
 
1.7%
x 8
 
1.2%
a 6
 
0.9%
s 4
 
0.6%
e 4
 
0.6%
u 3
 
0.5%
Other values (5) 9
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
L 83
30.4%
G 42
15.4%
K 39
14.3%
P 24
 
8.8%
M 22
 
8.1%
C 21
 
7.7%
R 18
 
6.6%
T 16
 
5.9%
A 6
 
2.2%
N 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 1618
28.2%
1 1109
19.3%
2 617
 
10.7%
3 539
 
9.4%
5 417
 
7.3%
9 416
 
7.2%
4 345
 
6.0%
8 272
 
4.7%
7 213
 
3.7%
6 197
 
3.4%
Other Punctuation
ValueCountFrequency (%)
/ 812
65.9%
. 180
 
14.6%
* 137
 
11.1%
, 78
 
6.3%
% 23
 
1.9%
& 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 183
65.1%
+ 98
34.9%
Space Separator
ValueCountFrequency (%)
1457
100.0%
Close Punctuation
ValueCountFrequency (%)
) 106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12713
56.2%
Common 8964
39.7%
Latin 917
 
4.1%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 447
 
3.5%
행 353
 
2.8%
기 235
 
1.8%
원 233
 
1.8%
고 221
 
1.7%
생 210
 
1.7%
이 203
 
1.6%
지 198
 
1.6%
쌀 195
 
1.5%
등 194
 
1.5%
Other values (302) 10224
80.4%
Latin
ValueCountFrequency (%)
g 434
47.3%
L 83
 
9.1%
k 76
 
8.3%
m 47
 
5.1%
G 42
 
4.6%
l 42
 
4.6%
K 39
 
4.3%
P 24
 
2.6%
M 22
 
2.4%
C 21
 
2.3%
Other values (16) 87
 
9.5%
Common
ValueCountFrequency (%)
0 1618
18.0%
1457
16.3%
1 1109
12.4%
/ 812
9.1%
2 617
 
6.9%
3 539
 
6.0%
5 417
 
4.7%
9 416
 
4.6%
4 345
 
3.8%
8 272
 
3.0%
Other values (12) 1362
15.2%
Han
ValueCountFrequency (%)
入 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12706
56.2%
ASCII 9881
43.7%
CJK 7
 
< 0.1%
Compat Jamo 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1618
16.4%
1457
14.7%
1 1109
11.2%
/ 812
 
8.2%
2 617
 
6.2%
3 539
 
5.5%
g 434
 
4.4%
5 417
 
4.2%
9 416
 
4.2%
4 345
 
3.5%
Other values (38) 2117
21.4%
Hangul
ValueCountFrequency (%)
사 447
 
3.5%
행 353
 
2.8%
기 235
 
1.8%
원 233
 
1.8%
고 221
 
1.7%
생 210
 
1.7%
이 203
 
1.6%
지 198
 
1.6%
쌀 195
 
1.5%
등 194
 
1.5%
Other values (301) 10217
80.4%
CJK
ValueCountFrequency (%)
入 7
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 7
100.0%

bssh_nm
Text

Distinct54
Distinct (%)0.5%
Missing31
Missing (%)0.3%
Memory size156.2 KiB
2024-04-21T18:18:47.343225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.0891764
Min length4

Characters and Unicode

Total characters90610
Distinct characters108
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row삼성홈플러스(센텀시티점)
2nd row탑마트(초량점)
3rd row삼성홈플러스(정관점)
4th row개금골목시장
5th row롯데마트(동래점)
ValueCountFrequency (%)
이마트(연제점 354
 
3.2%
농협하나로클럽마트 345
 
3.2%
탑마트(반여점 343
 
3.1%
삼성홈플러스(서면점 342
 
3.1%
롯데마트(사하점 338
 
3.1%
삼성홈플러스(센텀시티점 329
 
3.0%
롯데수퍼(명지점 326
 
3.0%
이마트(해운대점 324
 
3.0%
삼성홈플러스(영도점 320
 
2.9%
삼성홈플러스(서부산점 314
 
2.9%
Other values (49) 7603
69.5%
2024-04-21T18:18:48.243789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 7544
 
8.3%
( 7146
 
7.9%
) 7146
 
7.9%
트 4957
 
5.5%
마 4957
 
5.5%
스 3317
 
3.7%
러 2754
 
3.0%
플 2754
 
3.0%
홈 2484
 
2.7%
삼 2214
 
2.4%
Other values (98) 45337
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75275
83.1%
Open Punctuation 7146
 
7.9%
Close Punctuation 7146
 
7.9%
Space Separator 969
 
1.1%
Decimal Number 74
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 7544
 
10.0%
트 4957
 
6.6%
마 4957
 
6.6%
스 3317
 
4.4%
러 2754
 
3.7%
플 2754
 
3.7%
홈 2484
 
3.3%
삼 2214
 
2.9%
성 2214
 
2.9%
시 2163
 
2.9%
Other values (94) 39917
53.0%
Open Punctuation
ValueCountFrequency (%)
( 7146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7146
100.0%
Space Separator
ValueCountFrequency (%)
969
100.0%
Decimal Number
ValueCountFrequency (%)
1 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75275
83.1%
Common 15335
 
16.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 7544
 
10.0%
트 4957
 
6.6%
마 4957
 
6.6%
스 3317
 
4.4%
러 2754
 
3.7%
플 2754
 
3.7%
홈 2484
 
3.3%
삼 2214
 
2.9%
성 2214
 
2.9%
시 2163
 
2.9%
Other values (94) 39917
53.0%
Common
ValueCountFrequency (%)
( 7146
46.6%
) 7146
46.6%
969
 
6.3%
1 74
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75275
83.1%
ASCII 15335
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 7544
 
10.0%
트 4957
 
6.6%
마 4957
 
6.6%
스 3317
 
4.4%
러 2754
 
3.7%
플 2754
 
3.7%
홈 2484
 
3.3%
삼 2214
 
2.9%
성 2214
 
2.9%
시 2163
 
2.9%
Other values (94) 39917
53.0%
ASCII
ValueCountFrequency (%)
( 7146
46.6%
) 7146
46.6%
969
 
6.3%
1 74
 
0.5%

la
Real number (ℝ)

Distinct52
Distinct (%)0.5%
Missing32
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean35.16411
Minimum35.08484
Maximum35.323099
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:48.482531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.08484
5-th percentile35.085472
Q135.11677
median35.16423
Q335.205868
95-th percentile35.250107
Maximum35.323099
Range0.2382593
Interquartile range (IQR)0.089098

Descriptive statistics

Standard deviation0.056436952
Coefficient of variation (CV)0.0016049589
Kurtosis0.050642684
Mean35.16411
Median Absolute Deviation (MAD)0.042625
Skewness0.59143214
Sum350515.85
Variance0.0031851296
MonotonicityNot monotonic
2024-04-21T18:18:48.736788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17615 354
 
3.5%
35.250025 345
 
3.5%
35.205868 343
 
3.4%
35.149452 342
 
3.4%
35.08484 338
 
3.4%
35.1709359 329
 
3.3%
35.085472 326
 
3.3%
35.165993 324
 
3.2%
35.095905 320
 
3.2%
35.16483 314
 
3.1%
Other values (42) 6633
66.3%
ValueCountFrequency (%)
35.08484 338
3.4%
35.085472 326
3.3%
35.092663 298
3.0%
35.0931597 65
 
0.7%
35.095905 320
3.2%
35.0970155 76
 
0.8%
35.097233 298
3.0%
35.098934 293
2.9%
35.0996462 76
 
0.8%
35.099649 59
 
0.6%
ValueCountFrequency (%)
35.3230993 296
3.0%
35.250107 283
2.8%
35.250025 345
3.5%
35.2392 300
3.0%
35.234905 288
2.9%
35.2222318 70
 
0.7%
35.2159352 63
 
0.6%
35.2146331 81
 
0.8%
35.2119516 67
 
0.7%
35.211483 306
3.1%

lo
Real number (ℝ)

Distinct52
Distinct (%)0.5%
Missing32
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean129.05622
Minimum128.89784
Maximum129.17634
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T18:18:48.983546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.89784
5-th percentile128.97157
Q1129.01125
median129.06401
Q3129.0915
95-th percentile129.16739
Maximum129.17634
Range0.2784985
Interquartile range (IQR)0.0802545

Descriptive statistics

Standard deviation0.062522774
Coefficient of variation (CV)0.00048446153
Kurtosis0.0082190341
Mean129.05622
Median Absolute Deviation (MAD)0.03952
Skewness-0.27200886
Sum1286432.4
Variance0.0039090972
MonotonicityNot monotonic
2024-04-21T18:18:49.227718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.08133 354
 
3.5%
129.0112455 345
 
3.5%
129.12317 343
 
3.4%
129.06401 342
 
3.4%
128.97157 338
 
3.4%
129.1337096 329
 
3.3%
128.89784 326
 
3.3%
129.16739 324
 
3.2%
129.04424 320
 
3.2%
128.97812 314
 
3.1%
Other values (42) 6633
66.3%
ValueCountFrequency (%)
128.89784 326
3.3%
128.9019892 65
 
0.7%
128.97157 338
3.4%
128.97812 314
3.1%
128.97891 282
2.8%
128.9813855 64
 
0.6%
128.9822804 65
 
0.7%
128.9893459 76
 
0.8%
128.99406 293
2.9%
129.0016813 83
 
0.8%
ValueCountFrequency (%)
129.1763385 296
3.0%
129.1744835 70
 
0.7%
129.16739 324
3.2%
129.1623293 71
 
0.7%
129.1337096 329
3.3%
129.12317 343
3.4%
129.116693 71
 
0.7%
129.113611 270
2.7%
129.1114753 79
 
0.8%
129.1111015 299
3.0%

adres
Text

Distinct53
Distinct (%)0.5%
Missing31
Missing (%)0.3%
Memory size156.2 KiB
2024-04-21T18:18:50.346293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length21.530745
Min length14

Characters and Unicode

Total characters214640
Distinct characters114
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row부산광역시 해운대구 우동 해운대구 센텀동로6
2nd row부산광역시 동구 초량동 393-1
3rd row부산광역시 기장군 정관면 매학리 712-1
4th row부산광역시 부산진구 개금동 가야대로 482번길 40
5th row부산광역시 동래구 온천동 502-3
ValueCountFrequency (%)
부산광역시 9969
 
22.2%
해운대구 1466
 
3.3%
부산진구 813
 
1.8%
북구 797
 
1.8%
남구 788
 
1.8%
사하구 772
 
1.7%
동래구 759
 
1.7%
사상구 725
 
1.6%
수영구 716
 
1.6%
금정구 713
 
1.6%
Other values (152) 27361
61.0%
2024-04-21T18:18:51.694947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34910
16.3%
동 12140
 
5.7%
부 11733
 
5.5%
산 11363
 
5.3%
구 10937
 
5.1%
광 10239
 
4.8%
시 10199
 
4.8%
1 10153
 
4.7%
역 9969
 
4.6%
2 7093
 
3.3%
Other values (104) 85904
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 127513
59.4%
Decimal Number 43856
 
20.4%
Space Separator 34910
 
16.3%
Dash Punctuation 5335
 
2.5%
Open Punctuation 1378
 
0.6%
Close Punctuation 1378
 
0.6%
Other Punctuation 270
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12140
 
9.5%
부 11733
 
9.2%
산 11363
 
8.9%
구 10937
 
8.6%
광 10239
 
8.0%
시 10199
 
8.0%
역 9969
 
7.8%
로 2621
 
2.1%
남 2194
 
1.7%
대 2010
 
1.6%
Other values (89) 44108
34.6%
Decimal Number
ValueCountFrequency (%)
1 10153
23.2%
2 7093
16.2%
3 5786
13.2%
5 3926
 
9.0%
6 3330
 
7.6%
8 3240
 
7.4%
7 3089
 
7.0%
4 2725
 
6.2%
9 2429
 
5.5%
0 2085
 
4.8%
Space Separator
ValueCountFrequency (%)
34910
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5335
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1378
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1378
100.0%
Other Punctuation
ValueCountFrequency (%)
, 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 127513
59.4%
Common 87127
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12140
 
9.5%
부 11733
 
9.2%
산 11363
 
8.9%
구 10937
 
8.6%
광 10239
 
8.0%
시 10199
 
8.0%
역 9969
 
7.8%
로 2621
 
2.1%
남 2194
 
1.7%
대 2010
 
1.6%
Other values (89) 44108
34.6%
Common
ValueCountFrequency (%)
34910
40.1%
1 10153
 
11.7%
2 7093
 
8.1%
3 5786
 
6.6%
- 5335
 
6.1%
5 3926
 
4.5%
6 3330
 
3.8%
8 3240
 
3.7%
7 3089
 
3.5%
4 2725
 
3.1%
Other values (5) 7540
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 127513
59.4%
ASCII 87127
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34910
40.1%
1 10153
 
11.7%
2 7093
 
8.1%
3 5786
 
6.6%
- 5335
 
6.1%
5 3926
 
4.5%
6 3330
 
3.8%
8 3240
 
3.7%
7 3089
 
3.5%
4 2725
 
3.1%
Other values (5) 7540
 
8.7%
Hangul
ValueCountFrequency (%)
동 12140
 
9.5%
부 11733
 
9.2%
산 11363
 
8.9%
구 10937
 
8.6%
광 10239
 
8.0%
시 10199
 
8.0%
역 9969
 
7.8%
로 2621
 
2.1%
남 2194
 
1.7%
대 2010
 
1.6%
Other values (89) 44108
34.6%

telno
Text

Distinct53
Distinct (%)0.5%
Missing31
Missing (%)0.3%
Memory size156.2 KiB
2024-04-21T18:18:52.354270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.015047
Min length12

Characters and Unicode

Total characters119778
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row051-709-8000
2nd row051-466-2112
3rd row051-519-8200
4th row051-892-2606
5th row051-668-2500
ValueCountFrequency (%)
051-860-1052 354
 
3.6%
051-330-9000 345
 
3.5%
051-525-0422 343
 
3.4%
051-605-1000 342
 
3.4%
051-603-2500 338
 
3.4%
051-709-8000 329
 
3.3%
051-292-5602 326
 
3.3%
051-608-1234 324
 
3.3%
051-418-2000 320
 
3.2%
051-319-9157 314
 
3.1%
Other values (43) 6634
66.5%
2024-04-21T18:18:53.205073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28757
24.0%
- 19938
16.6%
1 16754
14.0%
5 15912
13.3%
2 10072
 
8.4%
6 6633
 
5.5%
3 4859
 
4.1%
9 4402
 
3.7%
4 4234
 
3.5%
8 4122
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99840
83.4%
Dash Punctuation 19938
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28757
28.8%
1 16754
16.8%
5 15912
15.9%
2 10072
 
10.1%
6 6633
 
6.6%
3 4859
 
4.9%
9 4402
 
4.4%
4 4234
 
4.2%
8 4122
 
4.1%
7 4095
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 19938
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119778
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28757
24.0%
- 19938
16.6%
1 16754
14.0%
5 15912
13.3%
2 10072
 
8.4%
6 6633
 
5.5%
3 4859
 
4.1%
9 4402
 
3.7%
4 4234
 
3.5%
8 4122
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119778
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28757
24.0%
- 19938
16.6%
1 16754
14.0%
5 15912
13.3%
2 10072
 
8.4%
6 6633
 
5.5%
3 4859
 
4.1%
9 4402
 
3.7%
4 4234
 
3.5%
8 4122
 
3.4%

parkng_at
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
9903 
N
 
66
 
31

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 9903
99.0%
N 66
 
0.7%
31
 
0.3%

Length

2024-04-21T18:18:53.423601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:18:53.586230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 9903
99.3%
n 66
 
0.7%

card_at
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
9969 
 
31

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 9969
99.7%
31
 
0.3%

Length

2024-04-21T18:18:53.755638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:18:53.916063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 9969
100.0%

item_name
Categorical

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
밀감
 
424
배
 
421
사과
 
412
무
 
409
대파
 
407
Other values (27)
7927 

Length

Max length5
Median length4
Mean length2.4497
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row간장
2nd row소주
3rd row고등어
4th row배
5th row커피크림

Common Values

ValueCountFrequency (%)
밀감 424
 
4.2%
배 421
 
4.2%
사과 412
 
4.1%
무 409
 
4.1%
대파 407
 
4.1%
쌀 405
 
4.0%
닭고기 399
 
4.0%
고등어 394
 
3.9%
양파 394
 
3.9%
달걀 393
 
3.9%
Other values (22) 5942
59.4%

Length

2024-04-21T18:18:54.102278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
밀감 424
 
4.2%
배 421
 
4.2%
사과 412
 
4.1%
무 409
 
4.1%
대파 407
 
4.1%
쌀 405
 
4.0%
닭고기 399
 
4.0%
고등어 394
 
3.9%
양파 394
 
3.9%
달걀 393
 
3.9%
Other values (22) 5942
59.4%

last_load_dttm
Date

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-06 11:35:32
Maximum2021-01-06 11:35:39
2024-04-21T18:18:54.290961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:18:54.470187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

Sample

skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
238572541799982625475251475251984062019-05-02464식료품365해운대구1.7630011900<NA>삼성홈플러스(센텀시티점)35.170936129.13371부산광역시 해운대구 우동 해운대구 센텀동로6051-709-8000YY간장2021-01-06 11:35:36
1558717148929126471447471447914102019-02-28461주류및음료,차92동구360.011901190시원소주탑마트(초량점)35.11677129.0395부산광역시 동구 초량동 393-1051-466-2112YY소주2021-01-06 11:35:34
1290614467777619469921469921764062019-02-07459수산물48기장군500.027432743품절삼성홈플러스(정관점)35.323099129.176339부산광역시 기장군 정관면 매학리 712-1051-519-8200YY고등어2021-01-06 11:35:34
3776939330797866480177480177784172019-07-31456농산물120부산진구600.0400004000<NA>개금골목시장35.151289129.024543부산광역시 부산진구 개금동 가야대로 482번길 40051-892-2606YY배2021-01-06 11:35:38
1691918480979629471400471400964072019-02-21461주류및음료,차111동래구500.025502550<NA>롯데마트(동래점)35.211483129.0776부산광역시 동래구 온천동 502-3051-668-2500YY커피크림2021-01-06 11:35:35
272642882510610525244753604753601054112019-05-09456농산물174북구20.06050060500<NA>농협하나로클럽마트35.250025129.011246부산광역시 북구 금곡동 북구금곡동1874-3051-330-9000YY쌀2021-01-06 11:35:36
1075712317828126469821469821814102019-01-24456농산물92동구869.028652490흙대파탑마트(초량점)35.11677129.0395부산광역시 동구 초량동 393-1051-466-2112YY대파2021-01-06 11:35:34
14102971797875464837464837784172018-11-07456농산물227서구6000.01600016000<NA>새벽해안시장35.09316129.024782부산광역시 서구 남부민1동 해안새벽시장길 68051-242-7273YY배2021-01-06 11:35:32
1734418905878635472939472939864102019-03-28458축산물227서구1.049524952<NA>탑마트(서구)35.092663129.02449부산광역시 서구 남부민1동 685051-244-1221YY닭고기2021-01-06 11:35:35
1559117152969526471447471447954102019-02-28463세제92동구4.066008800LG테그업4Kg(2kg*2) 2/26~3/4탑마트(초량점)35.11677129.0395부산광역시 동구 초량동 393-1051-466-2112YY가루비누2021-01-06 11:35:34
skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
2319724757908928473716473716894062019-04-11458축산물145부산진구600.026902690<NA>삼성홈플러스(서면점)35.149452129.06401부산광역시 부산진구 전포동 892-20051-605-1000YY달걀2021-01-06 11:35:36
1783519396868545473602473602854082019-04-04463세제95동래구1.435003500<NA>메가마트(동래점)35.204113129.08112부산광역시 동래구 명륜동 506-3051-550-2000YY부엌용세제2021-01-06 11:35:35
55077067898865466404466404884172018-12-05458축산물135부산진구500.05500055000<NA>부전시장35.160843129.057283부산광역시 부산진구 부전1동 중앙대로 767051-818-1091YY쇠고기2021-01-06 11:35:32
3091632477828138477043477043814072019-06-07456농산물360해운대구1000.0126612661380/1090g탑마트(반여점)35.205868129.12317(48038) 부산광역시 해운대구 선수촌로 119 (반여동)051-525-0422YY대파2021-01-06 11:35:37
364943805510410326254793724793721034062019-07-18464식료품365해운대구5.06763380<NA>삼성홈플러스(센텀시티점)35.170936129.13371부산광역시 해운대구 우동 해운대구 센텀동로6051-709-8000YY라면2021-01-06 11:35:38
2997931540787745476276476276774082019-05-23456농산물95동래구1500.01326619900하우스밀감메가마트(동래점)35.204113129.08112부산광역시 동래구 명륜동 506-3051-550-2000YY밀감2021-01-06 11:35:37
1687218433101100304713464713461004162019-02-21464식료품209사하구380.044103990<NA>뉴코아아울렛킴스클럽(괴정점)35.098934128.99406부산광역시 사하구 괴정3동 961-1051-209-5061YY두부2021-01-06 11:35:34
32744343051009931477032477032994062019-06-07464식료품293영도구320.072907290<NA>삼성홈플러스(영도점)35.095905129.04424부산광역시 영도구 봉래동2가 151-1051-418-2000YY참기름2021-01-06 11:35:37
4241885106105284646934646931054062018-11-01456농산물145부산진구20.05490054900좋은쌀삼성홈플러스(서면점)35.149452129.06401부산광역시 부산진구 전포동 892-20051-605-1000YY쌀2021-01-06 11:35:32
3237933940929135476982476982914102019-05-30461주류및음료,차227서구360.011901190<NA>탑마트(서구)35.092663129.02449부산광역시 서구 남부민1동 685051-244-1221YY소주2021-01-06 11:35:37