Overview

Dataset statistics

Number of variables51
Number of observations1797
Missing cells16044
Missing cells (%)17.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory774.0 KiB
Average record size in memory441.1 B

Variable types

Numeric14
Categorical22
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2022-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123185

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
업태구분명 is highly imbalanced (63.0%)Imbalance
위생업태명 is highly imbalanced (63.0%)Imbalance
사용끝지하층 is highly imbalanced (52.2%)Imbalance
조건부허가시작일자 is highly imbalanced (99.3%)Imbalance
조건부허가종료일자 is highly imbalanced (99.3%)Imbalance
여성종사자수 is highly imbalanced (79.1%)Imbalance
남성종사자수 is highly imbalanced (76.8%)Imbalance
다중이용업소여부 is highly imbalanced (85.5%)Imbalance
인허가취소일자 has 1797 (100.0%) missing valuesMissing
폐업일자 has 769 (42.8%) missing valuesMissing
휴업시작일자 has 1797 (100.0%) missing valuesMissing
휴업종료일자 has 1797 (100.0%) missing valuesMissing
재개업일자 has 1797 (100.0%) missing valuesMissing
소재지전화 has 107 (6.0%) missing valuesMissing
도로명전체주소 has 603 (33.6%) missing valuesMissing
도로명우편번호 has 656 (36.5%) missing valuesMissing
좌표정보(x) has 97 (5.4%) missing valuesMissing
좌표정보(y) has 97 (5.4%) missing valuesMissing
건물지상층수 has 411 (22.9%) missing valuesMissing
건물지하층수 has 643 (35.8%) missing valuesMissing
사용시작지상층 has 597 (33.2%) missing valuesMissing
사용끝지상층 has 687 (38.2%) missing valuesMissing
욕실수 has 580 (32.3%) missing valuesMissing
조건부허가신고사유 has 1796 (99.9%) missing valuesMissing
Unnamed: 50 has 1797 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 50 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 359 (20.0%) zerosZeros
건물지하층수 has 555 (30.9%) zerosZeros
사용시작지상층 has 368 (20.5%) zerosZeros
사용끝지상층 has 251 (14.0%) zerosZeros
욕실수 has 633 (35.2%) zerosZeros

Reproduction

Analysis started2024-04-17 21:46:17.661289
Analysis finished2024-04-17 21:46:19.210252
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1797
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean899
Minimum1
Maximum1797
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:19.265737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile90.8
Q1450
median899
Q31348
95-th percentile1707.2
Maximum1797
Range1796
Interquartile range (IQR)898

Descriptive statistics

Standard deviation518.89353
Coefficient of variation (CV)0.57718969
Kurtosis-1.2
Mean899
Median Absolute Deviation (MAD)449
Skewness0
Sum1615503
Variance269250.5
MonotonicityStrictly increasing
2024-04-18T06:46:19.392889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1125 1
 
0.1%
1207 1
 
0.1%
1206 1
 
0.1%
1205 1
 
0.1%
1204 1
 
0.1%
1203 1
 
0.1%
1202 1
 
0.1%
1201 1
 
0.1%
1200 1
 
0.1%
Other values (1787) 1787
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1797 1
0.1%
1796 1
0.1%
1795 1
0.1%
1794 1
0.1%
1793 1
0.1%
1792 1
0.1%
1791 1
0.1%
1790 1
0.1%
1789 1
0.1%
1788 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
목욕장업
1797 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목욕장업 1797
100.0%

Length

2024-04-18T06:46:19.508270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:19.605721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 1797
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
11_44_01_P
1797 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_44_01_P
2nd row11_44_01_P
3rd row11_44_01_P
4th row11_44_01_P
5th row11_44_01_P

Common Values

ValueCountFrequency (%)
11_44_01_P 1797
100.0%

Length

2024-04-18T06:46:19.698807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:19.805357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 1797
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3323105.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:19.891572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation40032.511
Coefficient of variation (CV)0.012046718
Kurtosis-0.91623812
Mean3323105.2
Median Absolute Deviation (MAD)30000
Skewness0.1239273
Sum5.97162 × 109
Variance1.602602 × 109
MonotonicityNot monotonic
2024-04-18T06:46:20.029508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 222
12.4%
3340000 174
9.7%
3330000 159
8.8%
3300000 147
 
8.2%
3310000 147
 
8.2%
3370000 130
 
7.2%
3320000 125
 
7.0%
3350000 113
 
6.3%
3380000 112
 
6.2%
3270000 94
 
5.2%
Other values (6) 374
20.8%
ValueCountFrequency (%)
3250000 62
 
3.5%
3260000 73
 
4.1%
3270000 94
5.2%
3280000 72
 
4.0%
3290000 222
12.4%
3300000 147
8.2%
3310000 147
8.2%
3320000 125
7.0%
3330000 159
8.8%
3340000 174
9.7%
ValueCountFrequency (%)
3400000 45
 
2.5%
3390000 93
5.2%
3380000 112
6.2%
3370000 130
7.2%
3360000 29
 
1.6%
3350000 113
6.3%
3340000 174
9.7%
3330000 159
8.8%
3320000 125
7.0%
3310000 147
8.2%

관리번호
Text

UNIQUE 

Distinct1797
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:46:20.203780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters39534
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

Unique1797 ?
Unique (%)100.0%

Sample

1st row3250000-202-2005-00001
2nd row3250000-202-1984-00152
3rd row3250000-202-1988-00159
4th row3250000-202-1960-00144
5th row3250000-202-1960-00146
ValueCountFrequency (%)
3250000-202-2005-00001 1
 
0.1%
3280000-202-1973-00012 1
 
0.1%
3310000-202-2005-00001 1
 
0.1%
3310000-202-1996-00631 1
 
0.1%
3310000-202-1987-01102 1
 
0.1%
3310000-202-1986-00968 1
 
0.1%
3310000-202-1971-00158 1
 
0.1%
3310000-202-1978-00688 1
 
0.1%
3310000-202-1976-01097 1
 
0.1%
3310000-202-1998-00049 1
 
0.1%
Other values (1787) 1787
99.4%
2024-04-18T06:46:20.503228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15255
38.6%
2 5606
 
14.2%
- 5391
 
13.6%
3 3899
 
9.9%
1 2708
 
6.8%
9 2498
 
6.3%
8 1135
 
2.9%
4 935
 
2.4%
7 832
 
2.1%
5 683
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34143
86.4%
Dash Punctuation 5391
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15255
44.7%
2 5606
 
16.4%
3 3899
 
11.4%
1 2708
 
7.9%
9 2498
 
7.3%
8 1135
 
3.3%
4 935
 
2.7%
7 832
 
2.4%
5 683
 
2.0%
6 592
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 5391
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39534
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15255
38.6%
2 5606
 
14.2%
- 5391
 
13.6%
3 3899
 
9.9%
1 2708
 
6.8%
9 2498
 
6.3%
8 1135
 
2.9%
4 935
 
2.4%
7 832
 
2.1%
5 683
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39534
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15255
38.6%
2 5606
 
14.2%
- 5391
 
13.6%
3 3899
 
9.9%
1 2708
 
6.8%
9 2498
 
6.3%
8 1135
 
2.9%
4 935
 
2.4%
7 832
 
2.1%
5 683
 
1.7%

인허가일자
Real number (ℝ)

Distinct1529
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19909790
Minimum19540131
Maximum20220105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:20.635355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19540131
5-th percentile19700421
Q119830304
median19901023
Q320010418
95-th percentile20110110
Maximum20220105
Range679974
Interquartile range (IQR)180114

Descriptive statistics

Standard deviation123994.54
Coefficient of variation (CV)0.0062278177
Kurtosis-0.36013264
Mean19909790
Median Absolute Deviation (MAD)80910
Skewness-0.035987221
Sum3.5777892 × 1010
Variance1.5374646 × 1010
MonotonicityNot monotonic
2024-04-18T06:46:20.760684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19630110 15
 
0.8%
20001130 9
 
0.5%
19830304 5
 
0.3%
20000420 5
 
0.3%
19820928 5
 
0.3%
20030115 5
 
0.3%
19880314 4
 
0.2%
19880923 4
 
0.2%
19861217 4
 
0.2%
19840908 4
 
0.2%
Other values (1519) 1737
96.7%
ValueCountFrequency (%)
19540131 1
 
0.1%
19601210 3
 
0.2%
19630108 1
 
0.1%
19630109 3
 
0.2%
19630110 15
0.8%
19630610 4
 
0.2%
19631001 1
 
0.1%
19640211 1
 
0.1%
19640915 1
 
0.1%
19641015 1
 
0.1%
ValueCountFrequency (%)
20220105 1
0.1%
20211115 1
0.1%
20211112 1
0.1%
20210914 1
0.1%
20210525 1
0.1%
20210401 1
0.1%
20210316 1
0.1%
20201013 1
0.1%
20200924 1
0.1%
20200921 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1797
Missing (%)100.0%
Memory size15.9 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
3
1028 
1
769 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 1028
57.2%
1 769
42.8%

Length

2024-04-18T06:46:20.885205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:20.974333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1028
57.2%
1 769
42.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
폐업
1028 
영업/정상
769 

Length

Max length5
Median length2
Mean length3.2838063
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 1028
57.2%
영업/정상 769
42.8%

Length

2024-04-18T06:46:21.072565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:21.167756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1028
57.2%
영업/정상 769
42.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2
1028 
1
769 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 1028
57.2%
1 769
42.8%

Length

2024-04-18T06:46:21.257046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:21.359859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1028
57.2%
1 769
42.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
폐업
1028 
영업
769 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1028
57.2%
영업 769
42.8%

Length

2024-04-18T06:46:21.460176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:21.564268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1028
57.2%
영업 769
42.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct863
Distinct (%)83.9%
Missing769
Missing (%)42.8%
Infinite0
Infinite (%)0.0%
Mean20102282
Minimum19901019
Maximum20211231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:21.675633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19901019
5-th percentile20000255
Q120051092
median20101119
Q320150720
95-th percentile20201224
Maximum20211231
Range310212
Interquartile range (IQR)99628.75

Descriptive statistics

Standard deviation63151.71
Coefficient of variation (CV)0.0031415195
Kurtosis-0.61435054
Mean20102282
Median Absolute Deviation (MAD)49850
Skewness-0.15951805
Sum2.0665146 × 1010
Variance3.9881385 × 109
MonotonicityNot monotonic
2024-04-18T06:46:21.798535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050121 12
 
0.7%
20051017 7
 
0.4%
20001130 7
 
0.4%
20170310 5
 
0.3%
20030401 5
 
0.3%
20120621 4
 
0.2%
20141030 4
 
0.2%
20190226 4
 
0.2%
20030122 4
 
0.2%
19981231 3
 
0.2%
Other values (853) 973
54.1%
(Missing) 769
42.8%
ValueCountFrequency (%)
19901019 1
0.1%
19921202 1
0.1%
19930607 1
0.1%
19930726 1
0.1%
19930924 1
0.1%
19931228 1
0.1%
19950309 1
0.1%
19950624 1
0.1%
19950709 1
0.1%
19950728 1
0.1%
ValueCountFrequency (%)
20211231 2
0.1%
20211221 1
0.1%
20211217 1
0.1%
20211202 1
0.1%
20211201 1
0.1%
20211129 1
0.1%
20211124 1
0.1%
20211115 1
0.1%
20211111 1
0.1%
20211103 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1797
Missing (%)100.0%
Memory size15.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1797
Missing (%)100.0%
Memory size15.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1797
Missing (%)100.0%
Memory size15.9 KiB

소재지전화
Text

MISSING 

Distinct1608
Distinct (%)95.1%
Missing107
Missing (%)6.0%
Memory size14.2 KiB
2024-04-18T06:46:22.048389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.909467
Min length3

Characters and Unicode

Total characters18437
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

Unique1570 ?
Unique (%)92.9%

Sample

1st row051 4692777
2nd row051 4633803
3rd row051 2472425
4th row051 2449501
5th row051 2443396
ValueCountFrequency (%)
051 1636
45.5%
808 8
 
0.2%
893 7
 
0.2%
070 5
 
0.1%
261 5
 
0.1%
891 5
 
0.1%
816 5
 
0.1%
897 5
 
0.1%
802 5
 
0.1%
727 4
 
0.1%
Other values (1765) 1907
53.1%
2024-04-18T06:46:22.407408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3044
16.5%
0 2836
15.4%
1 2762
15.0%
1911
10.4%
2 1442
7.8%
3 1299
7.0%
6 1229
6.7%
4 1108
 
6.0%
7 1070
 
5.8%
8 1033
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16526
89.6%
Space Separator 1911
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3044
18.4%
0 2836
17.2%
1 2762
16.7%
2 1442
8.7%
3 1299
7.9%
6 1229
7.4%
4 1108
 
6.7%
7 1070
 
6.5%
8 1033
 
6.3%
9 703
 
4.3%
Space Separator
ValueCountFrequency (%)
1911
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18437
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3044
16.5%
0 2836
15.4%
1 2762
15.0%
1911
10.4%
2 1442
7.8%
3 1299
7.0%
6 1229
6.7%
4 1108
 
6.0%
7 1070
 
5.8%
8 1033
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18437
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3044
16.5%
0 2836
15.4%
1 2762
15.0%
1911
10.4%
2 1442
7.8%
3 1299
7.0%
6 1229
6.7%
4 1108
 
6.0%
7 1070
 
5.8%
8 1033
 
5.6%
Distinct1578
Distinct (%)88.3%
Missing9
Missing (%)0.5%
Memory size14.2 KiB
2024-04-18T06:46:22.670562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.9709172
Min length3

Characters and Unicode

Total characters10676
Distinct characters12
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

Unique1494 ?
Unique (%)83.6%

Sample

1st row462.00
2nd row405.00
3rd row338.97
4th row1,416.48
5th row517.00
ValueCountFrequency (%)
00 116
 
6.5%
330.00 5
 
0.3%
348.00 3
 
0.2%
252.17 3
 
0.2%
93.73 3
 
0.2%
798.24 3
 
0.2%
506.24 3
 
0.2%
427.44 3
 
0.2%
478.00 3
 
0.2%
426.00 3
 
0.2%
Other values (1568) 1643
91.9%
2024-04-18T06:46:23.052593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1788
16.7%
0 1422
13.3%
2 1049
9.8%
3 996
9.3%
4 926
8.7%
1 899
8.4%
6 699
 
6.5%
8 699
 
6.5%
5 692
 
6.5%
7 679
 
6.4%
Other values (2) 827
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8730
81.8%
Other Punctuation 1946
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1422
16.3%
2 1049
12.0%
3 996
11.4%
4 926
10.6%
1 899
10.3%
6 699
8.0%
8 699
8.0%
5 692
7.9%
7 679
7.8%
9 669
7.7%
Other Punctuation
ValueCountFrequency (%)
. 1788
91.9%
, 158
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
Common 10676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1788
16.7%
0 1422
13.3%
2 1049
9.8%
3 996
9.3%
4 926
8.7%
1 899
8.4%
6 699
 
6.5%
8 699
 
6.5%
5 692
 
6.5%
7 679
 
6.4%
Other values (2) 827
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1788
16.7%
0 1422
13.3%
2 1049
9.8%
3 996
9.3%
4 926
8.7%
1 899
8.4%
6 699
 
6.5%
8 699
 
6.5%
5 692
 
6.5%
7 679
 
6.4%
Other values (2) 827
7.7%

소재지우편번호
Real number (ℝ)

Distinct631
Distinct (%)35.2%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean610444.58
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:23.178803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601811
Q1606806.75
median611803
Q3614822
95-th percentile617833.45
Maximum619953
Range19942
Interquartile range (IQR)8015.25

Descriptive statistics

Standard deviation5186.2049
Coefficient of variation (CV)0.0084957833
Kurtosis-0.92841612
Mean610444.58
Median Absolute Deviation (MAD)3962.5
Skewness-0.21932413
Sum1.0939167 × 109
Variance26896721
MonotonicityNot monotonic
2024-04-18T06:46:23.300351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604851 15
 
0.8%
612846 12
 
0.7%
612847 12
 
0.7%
608808 11
 
0.6%
608828 10
 
0.6%
614822 10
 
0.6%
613832 9
 
0.5%
607826 9
 
0.5%
613805 9
 
0.5%
607833 9
 
0.5%
Other values (621) 1686
93.8%
ValueCountFrequency (%)
600011 1
 
0.1%
600012 1
 
0.1%
600017 1
 
0.1%
600021 1
 
0.1%
600022 4
0.2%
600023 1
 
0.1%
600025 1
 
0.1%
600032 1
 
0.1%
600042 1
 
0.1%
600044 1
 
0.1%
ValueCountFrequency (%)
619953 2
 
0.1%
619952 3
0.2%
619951 4
0.2%
619913 1
 
0.1%
619912 2
 
0.1%
619911 2
 
0.1%
619906 3
0.2%
619905 5
0.3%
619904 3
0.2%
619903 7
0.4%
Distinct1735
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:46:23.600518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length23.295492
Min length16

Characters and Unicode

Total characters41862
Distinct characters276
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1681 ?
Unique (%)93.5%

Sample

1st row부산광역시 중구 중앙동4가 79-1 마린센터(지하1층)
2nd row부산광역시 중구 영주동 292-10
3rd row부산광역시 중구 신창동2가 21-2
4th row부산광역시 중구 부평동3가 22-1 외 2필지
5th row부산광역시 중구 부평동4가 28-3
ValueCountFrequency (%)
부산광역시 1797
 
22.4%
t통b반 334
 
4.2%
부산진구 222
 
2.8%
사하구 174
 
2.2%
해운대구 159
 
2.0%
남구 147
 
1.8%
동래구 147
 
1.8%
연제구 130
 
1.6%
북구 125
 
1.6%
금정구 113
 
1.4%
Other values (2176) 4672
58.3%
2024-04-18T06:46:24.085262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6224
 
14.9%
2148
 
5.1%
2139
 
5.1%
2079
 
5.0%
1 1891
 
4.5%
1867
 
4.5%
1819
 
4.3%
1809
 
4.3%
1801
 
4.3%
- 1672
 
4.0%
Other values (266) 18413
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24307
58.1%
Decimal Number 8732
 
20.9%
Space Separator 6224
 
14.9%
Dash Punctuation 1672
 
4.0%
Uppercase Letter 683
 
1.6%
Other Punctuation 114
 
0.3%
Open Punctuation 61
 
0.1%
Close Punctuation 61
 
0.1%
Math Symbol 7
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2148
 
8.8%
2139
 
8.8%
2079
 
8.6%
1867
 
7.7%
1819
 
7.5%
1809
 
7.4%
1801
 
7.4%
1375
 
5.7%
1306
 
5.4%
385
 
1.6%
Other values (240) 7579
31.2%
Decimal Number
ValueCountFrequency (%)
1 1891
21.7%
2 1127
12.9%
3 984
11.3%
4 879
10.1%
5 778
8.9%
6 675
 
7.7%
7 644
 
7.4%
8 608
 
7.0%
0 607
 
7.0%
9 539
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 342
50.1%
T 334
48.9%
W 2
 
0.3%
A 2
 
0.3%
L 1
 
0.1%
I 1
 
0.1%
G 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 112
98.2%
. 1
 
0.9%
@ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
6224
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1672
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24307
58.1%
Common 16871
40.3%
Latin 684
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2148
 
8.8%
2139
 
8.8%
2079
 
8.6%
1867
 
7.7%
1819
 
7.5%
1809
 
7.4%
1801
 
7.4%
1375
 
5.7%
1306
 
5.4%
385
 
1.6%
Other values (240) 7579
31.2%
Common
ValueCountFrequency (%)
6224
36.9%
1 1891
 
11.2%
- 1672
 
9.9%
2 1127
 
6.7%
3 984
 
5.8%
4 879
 
5.2%
5 778
 
4.6%
6 675
 
4.0%
7 644
 
3.8%
8 608
 
3.6%
Other values (8) 1389
 
8.2%
Latin
ValueCountFrequency (%)
B 342
50.0%
T 334
48.8%
W 2
 
0.3%
A 2
 
0.3%
L 1
 
0.1%
I 1
 
0.1%
G 1
 
0.1%
1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24307
58.1%
ASCII 17554
41.9%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6224
35.5%
1 1891
 
10.8%
- 1672
 
9.5%
2 1127
 
6.4%
3 984
 
5.6%
4 879
 
5.0%
5 778
 
4.4%
6 675
 
3.8%
7 644
 
3.7%
8 608
 
3.5%
Other values (15) 2072
 
11.8%
Hangul
ValueCountFrequency (%)
2148
 
8.8%
2139
 
8.8%
2079
 
8.6%
1867
 
7.7%
1819
 
7.5%
1809
 
7.4%
1801
 
7.4%
1375
 
5.7%
1306
 
5.4%
385
 
1.6%
Other values (240) 7579
31.2%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1181
Distinct (%)98.9%
Missing603
Missing (%)33.6%
Memory size14.2 KiB
2024-04-18T06:46:24.417016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length27.554439
Min length20

Characters and Unicode

Total characters32900
Distinct characters336
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1168 ?
Unique (%)97.8%

Sample

1st row부산광역시 중구 충장대로9번길 52, 지하1층 (중앙동4가, 마린센터)
2nd row부산광역시 중구 영주로 20 (영주동)
3rd row부산광역시 중구 광복로43번길 12 (신창동2가)
4th row부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)
5th row부산광역시 중구 흑교로21번길 21 (부평동4가)
ValueCountFrequency (%)
부산광역시 1194
 
19.1%
부산진구 154
 
2.5%
사하구 103
 
1.6%
남구 103
 
1.6%
해운대구 103
 
1.6%
동래구 96
 
1.5%
연제구 84
 
1.3%
북구 77
 
1.2%
금정구 75
 
1.2%
사상구 71
 
1.1%
Other values (1727) 4204
67.1%
2024-04-18T06:46:24.901069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5071
 
15.4%
1514
 
4.6%
1448
 
4.4%
1447
 
4.4%
1261
 
3.8%
1250
 
3.8%
1224
 
3.7%
1199
 
3.6%
( 1180
 
3.6%
) 1180
 
3.6%
Other values (326) 16126
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19812
60.2%
Decimal Number 5076
 
15.4%
Space Separator 5071
 
15.4%
Open Punctuation 1181
 
3.6%
Close Punctuation 1181
 
3.6%
Other Punctuation 351
 
1.1%
Dash Punctuation 200
 
0.6%
Uppercase Letter 14
 
< 0.1%
Math Symbol 13
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1514
 
7.6%
1448
 
7.3%
1447
 
7.3%
1261
 
6.4%
1250
 
6.3%
1224
 
6.2%
1199
 
6.1%
1138
 
5.7%
710
 
3.6%
669
 
3.4%
Other values (298) 7952
40.1%
Decimal Number
ValueCountFrequency (%)
1 1149
22.6%
2 720
14.2%
3 628
12.4%
5 447
 
8.8%
4 436
 
8.6%
6 388
 
7.6%
0 380
 
7.5%
7 353
 
7.0%
9 290
 
5.7%
8 285
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 6
42.9%
A 4
28.6%
W 2
 
14.3%
I 1
 
7.1%
G 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 346
98.6%
. 3
 
0.9%
* 1
 
0.3%
@ 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 1180
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1180
99.9%
] 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 12
92.3%
1
 
7.7%
Space Separator
ValueCountFrequency (%)
5071
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19812
60.2%
Common 13073
39.7%
Latin 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1514
 
7.6%
1448
 
7.3%
1447
 
7.3%
1261
 
6.4%
1250
 
6.3%
1224
 
6.2%
1199
 
6.1%
1138
 
5.7%
710
 
3.6%
669
 
3.4%
Other values (298) 7952
40.1%
Common
ValueCountFrequency (%)
5071
38.8%
( 1180
 
9.0%
) 1180
 
9.0%
1 1149
 
8.8%
2 720
 
5.5%
3 628
 
4.8%
5 447
 
3.4%
4 436
 
3.3%
6 388
 
3.0%
0 380
 
2.9%
Other values (12) 1494
 
11.4%
Latin
ValueCountFrequency (%)
B 6
40.0%
A 4
26.7%
W 2
 
13.3%
1
 
6.7%
I 1
 
6.7%
G 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19812
60.2%
ASCII 13086
39.8%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5071
38.8%
( 1180
 
9.0%
) 1180
 
9.0%
1 1149
 
8.8%
2 720
 
5.5%
3 628
 
4.8%
5 447
 
3.4%
4 436
 
3.3%
6 388
 
3.0%
0 380
 
2.9%
Other values (16) 1507
 
11.5%
Hangul
ValueCountFrequency (%)
1514
 
7.6%
1448
 
7.3%
1447
 
7.3%
1261
 
6.4%
1250
 
6.3%
1224
 
6.2%
1199
 
6.1%
1138
 
5.7%
710
 
3.6%
669
 
3.4%
Other values (298) 7952
40.1%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct877
Distinct (%)76.9%
Missing656
Missing (%)36.5%
Infinite0
Infinite (%)0.0%
Mean47879.616
Minimum46002
Maximum49523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:25.018573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46249
Q147142
median47878
Q348719
95-th percentile49396
Maximum49523
Range3521
Interquartile range (IQR)1577

Descriptive statistics

Standard deviation983.19155
Coefficient of variation (CV)0.020534658
Kurtosis-1.0472654
Mean47879.616
Median Absolute Deviation (MAD)756
Skewness-0.077956339
Sum54630642
Variance966665.62
MonotonicityNot monotonic
2024-04-18T06:46:25.139581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47709 8
 
0.4%
48099 8
 
0.4%
47248 6
 
0.3%
46327 5
 
0.3%
46308 4
 
0.2%
47142 4
 
0.2%
48095 4
 
0.2%
47712 4
 
0.2%
48052 4
 
0.2%
48053 4
 
0.2%
Other values (867) 1090
60.7%
(Missing) 656
36.5%
ValueCountFrequency (%)
46002 1
0.1%
46008 1
0.1%
46015 1
0.1%
46017 1
0.1%
46020 1
0.1%
46032 1
0.1%
46033 1
0.1%
46036 2
0.1%
46037 2
0.1%
46040 1
0.1%
ValueCountFrequency (%)
49523 1
0.1%
49522 1
0.1%
49521 1
0.1%
49518 2
0.1%
49515 2
0.1%
49511 2
0.1%
49506 1
0.1%
49505 1
0.1%
49504 1
0.1%
49503 2
0.1%
Distinct1129
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:46:25.411523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length3
Mean length4.1240957
Min length2

Characters and Unicode

Total characters7411
Distinct characters380
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

Unique890 ?
Unique (%)49.5%

Sample

1st row마린목욕탕
2nd row거북탕
3rd row녹수탕
4th row금강스파
5th row부천탕
ValueCountFrequency (%)
사우나 25
 
1.3%
청수탕 21
 
1.1%
현대탕 20
 
1.0%
옥천탕 19
 
1.0%
천수탕 15
 
0.8%
산수탕 15
 
0.8%
목욕탕 15
 
0.8%
장수탕 14
 
0.7%
제일탕 13
 
0.7%
약수탕 13
 
0.7%
Other values (1184) 1783
91.3%
2024-04-18T06:46:25.798179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1356
 
18.3%
299
 
4.0%
220
 
3.0%
180
 
2.4%
179
 
2.4%
167
 
2.3%
158
 
2.1%
156
 
2.1%
121
 
1.6%
117
 
1.6%
Other values (370) 4458
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7138
96.3%
Space Separator 156
 
2.1%
Close Punctuation 37
 
0.5%
Open Punctuation 34
 
0.5%
Decimal Number 20
 
0.3%
Uppercase Letter 15
 
0.2%
Lowercase Letter 7
 
0.1%
Dash Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1356
 
19.0%
299
 
4.2%
220
 
3.1%
180
 
2.5%
179
 
2.5%
167
 
2.3%
158
 
2.2%
121
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (348) 4228
59.2%
Uppercase Letter
ValueCountFrequency (%)
G 4
26.7%
L 2
13.3%
W 2
13.3%
O 2
13.3%
S 1
 
6.7%
F 1
 
6.7%
J 1
 
6.7%
M 1
 
6.7%
B 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
n 2
28.6%
u 1
14.3%
d 1
14.3%
r 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 11
55.0%
4 9
45.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7137
96.3%
Common 251
 
3.4%
Latin 22
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1356
 
19.0%
299
 
4.2%
220
 
3.1%
180
 
2.5%
179
 
2.5%
167
 
2.3%
158
 
2.2%
121
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (347) 4227
59.2%
Latin
ValueCountFrequency (%)
G 4
18.2%
L 2
9.1%
W 2
9.1%
O 2
9.1%
o 2
9.1%
n 2
9.1%
S 1
 
4.5%
F 1
 
4.5%
u 1
 
4.5%
d 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
156
62.2%
) 37
 
14.7%
( 34
 
13.5%
2 11
 
4.4%
4 9
 
3.6%
- 2
 
0.8%
. 1
 
0.4%
, 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7137
96.3%
ASCII 273
 
3.7%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1356
 
19.0%
299
 
4.2%
220
 
3.1%
180
 
2.5%
179
 
2.5%
167
 
2.3%
158
 
2.2%
121
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (347) 4227
59.2%
ASCII
ValueCountFrequency (%)
156
57.1%
) 37
 
13.6%
( 34
 
12.5%
2 11
 
4.0%
4 9
 
3.3%
G 4
 
1.5%
- 2
 
0.7%
L 2
 
0.7%
W 2
 
0.7%
O 2
 
0.7%
Other values (12) 14
 
5.1%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1522
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0130975 × 1013
Minimum1.999021 × 1013
Maximum2.0220126 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:25.928870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.999021 × 1013
5-th percentile2.0020424 × 1013
Q12.0050415 × 1013
median2.0150429 × 1013
Q32.0200905 × 1013
95-th percentile2.0211022 × 1013
Maximum2.0220126 × 1013
Range2.2991615 × 1011
Interquartile range (IQR)1.5049 × 1011

Descriptive statistics

Standard deviation7.280967 × 1010
Coefficient of variation (CV)0.0036167979
Kurtosis-1.4060145
Mean2.0130975 × 1013
Median Absolute Deviation (MAD)5.9778941 × 1010
Skewness-0.39479725
Sum3.6175363 × 1016
Variance5.3012481 × 1021
MonotonicityNot monotonic
2024-04-18T06:46:26.043544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020418000000 27
 
1.5%
20030409000000 25
 
1.4%
20040318000000 13
 
0.7%
20050415000000 12
 
0.7%
20030303000000 12
 
0.7%
20031217000000 10
 
0.6%
20041208000000 9
 
0.5%
20030722000000 8
 
0.4%
20040324000000 8
 
0.4%
20070410000000 7
 
0.4%
Other values (1512) 1666
92.7%
ValueCountFrequency (%)
19990210000000 2
 
0.1%
19990212000000 1
 
0.1%
19990302000000 7
0.4%
19990310000000 6
0.3%
19990315000000 1
 
0.1%
19990325000000 2
 
0.1%
19990420000000 2
 
0.1%
19990421000000 7
0.4%
19990422000000 1
 
0.1%
19990427000000 1
 
0.1%
ValueCountFrequency (%)
20220126154749 1
0.1%
20220126151626 1
0.1%
20220126143742 1
0.1%
20220125171531 1
0.1%
20220124094934 1
0.1%
20220120134948 1
0.1%
20220119161713 1
0.1%
20220119152813 1
0.1%
20220117150331 1
0.1%
20220117115550 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
I
1096 
U
701 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1096
61.0%
U 701
39.0%

Length

2024-04-18T06:46:26.155943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:26.254939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1096
61.0%
u 701
39.0%
Distinct307
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
Minimum2018-08-31 23:59:59
Maximum2022-01-28 02:40:00
2024-04-18T06:46:26.346660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:46:26.462248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
공동탕업
1519 
목욕장업 기타
155 
공동탕업+찜질시설서비스영업
 
79
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7289928
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업
2nd row공동탕업
3rd row공동탕업
4th row공동탕업+찜질시설서비스영업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 1519
84.5%
목욕장업 기타 155
 
8.6%
공동탕업+찜질시설서비스영업 79
 
4.4%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:46:26.575278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:26.663201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1519
77.8%
목욕장업 155
 
7.9%
기타 155
 
7.9%
공동탕업+찜질시설서비스영업 79
 
4.0%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1539
Distinct (%)90.5%
Missing97
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean387812.11
Minimum366820.79
Maximum407878.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:26.764030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366820.79
5-th percentile379643.78
Q1384073.03
median388169.96
Q3391128.8
95-th percentile396842.4
Maximum407878.31
Range41057.525
Interquartile range (IQR)7055.772

Descriptive statistics

Standard deviation5293.2824
Coefficient of variation (CV)0.01364909
Kurtosis0.71756893
Mean387812.11
Median Absolute Deviation (MAD)3549.1996
Skewness0.26312037
Sum6.5928059 × 108
Variance28018839
MonotonicityNot monotonic
2024-04-18T06:46:26.885011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
391834.082986499 4
 
0.2%
386026.75739607 4
 
0.2%
379381.589505082 3
 
0.2%
388552.359453092 3
 
0.2%
389322.400841052 3
 
0.2%
386428.823034759 3
 
0.2%
384030.39531508 3
 
0.2%
392823.81074453 3
 
0.2%
379618.460093644 3
 
0.2%
379052.480675244 3
 
0.2%
Other values (1529) 1668
92.8%
(Missing) 97
 
5.4%
ValueCountFrequency (%)
366820.787750249 1
0.1%
370674.351397752 1
0.1%
370718.68095386 1
0.1%
372902.66679319 1
0.1%
373056.59115396 1
0.1%
373088.087508096 2
0.1%
373178.636648911 1
0.1%
373368.868121279 1
0.1%
373512.89135141 1
0.1%
374901.846816548 2
0.1%
ValueCountFrequency (%)
407878.31227469 1
0.1%
407739.046710947 1
0.1%
407413.951209968 1
0.1%
407195.438344935 1
0.1%
406982.053033795 1
0.1%
405347.024248643 1
0.1%
405172.859381319 1
0.1%
404771.782281376 1
0.1%
404674.710704763 1
0.1%
403845.595330569 1
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct1539
Distinct (%)90.5%
Missing97
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean186629.55
Minimum173914.72
Maximum207205.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:27.011103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173914.72
5-th percentile177917.54
Q1182312.64
median186787.38
Q3190629.4
95-th percentile195582.75
Maximum207205.17
Range33290.452
Interquartile range (IQR)8316.7627

Descriptive statistics

Standard deviation5632.1531
Coefficient of variation (CV)0.03017825
Kurtosis0.039126272
Mean186629.55
Median Absolute Deviation (MAD)4116.8895
Skewness0.24671914
Sum3.1727023 × 108
Variance31721148
MonotonicityNot monotonic
2024-04-18T06:46:27.120890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189185.417047275 4
 
0.2%
181580.381775088 4
 
0.2%
180485.975246308 3
 
0.2%
184430.486759907 3
 
0.2%
193209.131530013 3
 
0.2%
189577.746954425 3
 
0.2%
181514.179291296 3
 
0.2%
187864.933254648 3
 
0.2%
174097.616386311 3
 
0.2%
181034.181864204 3
 
0.2%
Other values (1529) 1668
92.8%
(Missing) 97
 
5.4%
ValueCountFrequency (%)
173914.718015169 1
 
0.1%
174068.494334685 1
 
0.1%
174097.616386311 3
0.2%
174213.492106852 1
 
0.1%
174596.132939092 1
 
0.1%
174644.872274897 1
 
0.1%
174676.412428464 1
 
0.1%
174765.307900471 1
 
0.1%
174811.513941031 1
 
0.1%
174885.756922702 2
0.1%
ValueCountFrequency (%)
207205.169925653 1
0.1%
207141.911104602 1
0.1%
206164.575140106 1
0.1%
205671.36729929 1
0.1%
205652.426376355 1
0.1%
205455.066408843 1
0.1%
205405.879376804 1
0.1%
205366.770002161 1
0.1%
205061.202821882 1
0.1%
204747.884437376 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
공동탕업
1519 
목욕장업 기타
155 
공동탕업+찜질시설서비스영업
 
79
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7289928
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업
2nd row공동탕업
3rd row공동탕업
4th row공동탕업+찜질시설서비스영업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 1519
84.5%
목욕장업 기타 155
 
8.6%
공동탕업+찜질시설서비스영업 79
 
4.4%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:46:27.240151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:27.328523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1519
77.8%
목욕장업 155
 
7.9%
기타 155
 
7.9%
공동탕업+찜질시설서비스영업 79
 
4.0%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)2.4%
Missing411
Missing (%)22.9%
Infinite0
Infinite (%)0.0%
Mean3.7308802
Minimum0
Maximum42
Zeros359
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:27.424046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q35
95-th percentile10
Maximum42
Range42
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.4365253
Coefficient of variation (CV)1.1891364
Kurtosis16.286997
Mean3.7308802
Median Absolute Deviation (MAD)2
Skewness3.3076597
Sum5171
Variance19.682757
MonotonicityNot monotonic
2024-04-18T06:46:27.986073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 359
20.0%
3 298
16.6%
4 207
11.5%
2 133
 
7.4%
5 132
 
7.3%
6 51
 
2.8%
7 48
 
2.7%
8 29
 
1.6%
1 25
 
1.4%
9 20
 
1.1%
Other values (23) 84
 
4.7%
(Missing) 411
22.9%
ValueCountFrequency (%)
0 359
20.0%
1 25
 
1.4%
2 133
 
7.4%
3 298
16.6%
4 207
11.5%
5 132
 
7.3%
6 51
 
2.8%
7 48
 
2.7%
8 29
 
1.6%
9 20
 
1.1%
ValueCountFrequency (%)
42 1
 
0.1%
37 1
 
0.1%
34 1
 
0.1%
33 1
 
0.1%
32 1
 
0.1%
30 1
 
0.1%
29 1
 
0.1%
28 3
0.2%
27 1
 
0.1%
25 2
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.7%
Missing643
Missing (%)35.8%
Infinite0
Infinite (%)0.0%
Mean0.75649913
Minimum0
Maximum7
Zeros555
Zeros (%)30.9%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:28.069102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0414548
Coefficient of variation (CV)1.3766768
Kurtosis7.9953373
Mean0.75649913
Median Absolute Deviation (MAD)1
Skewness2.423707
Sum873
Variance1.0846281
MonotonicityNot monotonic
2024-04-18T06:46:28.182698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 555
30.9%
1 457
25.4%
2 78
 
4.3%
3 28
 
1.6%
4 16
 
0.9%
6 10
 
0.6%
5 9
 
0.5%
7 1
 
0.1%
(Missing) 643
35.8%
ValueCountFrequency (%)
0 555
30.9%
1 457
25.4%
2 78
 
4.3%
3 28
 
1.6%
4 16
 
0.9%
5 9
 
0.5%
6 10
 
0.6%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
6 10
 
0.6%
5 9
 
0.5%
4 16
 
0.9%
3 28
 
1.6%
2 78
 
4.3%
1 457
25.4%
0 555
30.9%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.8%
Missing597
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean1.3508333
Minimum0
Maximum10
Zeros368
Zeros (%)20.5%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:28.294918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3997793
Coefficient of variation (CV)1.0362339
Kurtosis5.7016112
Mean1.3508333
Median Absolute Deviation (MAD)1
Skewness1.822878
Sum1621
Variance1.9593821
MonotonicityNot monotonic
2024-04-18T06:46:28.393960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 372
20.7%
0 368
20.5%
2 300
16.7%
3 76
 
4.2%
4 42
 
2.3%
5 21
 
1.2%
6 12
 
0.7%
8 4
 
0.2%
10 3
 
0.2%
7 2
 
0.1%
(Missing) 597
33.2%
ValueCountFrequency (%)
0 368
20.5%
1 372
20.7%
2 300
16.7%
3 76
 
4.2%
4 42
 
2.3%
5 21
 
1.2%
6 12
 
0.7%
7 2
 
0.1%
8 4
 
0.2%
10 3
 
0.2%
ValueCountFrequency (%)
10 3
 
0.2%
8 4
 
0.2%
7 2
 
0.1%
6 12
 
0.7%
5 21
 
1.2%
4 42
 
2.3%
3 76
 
4.2%
2 300
16.7%
1 372
20.7%
0 368
20.5%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.1%
Missing687
Missing (%)38.2%
Infinite0
Infinite (%)0.0%
Mean2.1405405
Minimum0
Maximum11
Zeros251
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:28.489107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7349314
Coefficient of variation (CV)0.8105109
Kurtosis2.4828704
Mean2.1405405
Median Absolute Deviation (MAD)1
Skewness1.101129
Sum2376
Variance3.0099871
MonotonicityNot monotonic
2024-04-18T06:46:28.577049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 381
21.2%
0 251
 
14.0%
3 210
 
11.7%
1 93
 
5.2%
4 82
 
4.6%
5 48
 
2.7%
6 20
 
1.1%
7 11
 
0.6%
9 5
 
0.3%
8 5
 
0.3%
Other values (2) 4
 
0.2%
(Missing) 687
38.2%
ValueCountFrequency (%)
0 251
14.0%
1 93
 
5.2%
2 381
21.2%
3 210
11.7%
4 82
 
4.6%
5 48
 
2.7%
6 20
 
1.1%
7 11
 
0.6%
8 5
 
0.3%
9 5
 
0.3%
ValueCountFrequency (%)
11 1
 
0.1%
10 3
 
0.2%
9 5
 
0.3%
8 5
 
0.3%
7 11
 
0.6%
6 20
 
1.1%
5 48
 
2.7%
4 82
 
4.6%
3 210
11.7%
2 381
21.2%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
895 
0
810 
1
 
80
2
 
9
3
 
3

Length

Max length4
Median length1
Mean length2.4941569
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
<NA> 895
49.8%
0 810
45.1%
1 80
 
4.5%
2 9
 
0.5%
3 3
 
0.2%

Length

2024-04-18T06:46:28.696054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:28.787801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 895
49.8%
0 810
45.1%
1 80
 
4.5%
2 9
 
0.5%
3 3
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1102 
0
602 
1
 
68
2
 
21
3
 
3

Length

Max length4
Median length4
Mean length2.8397329
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1102
61.3%
0 602
33.5%
1 68
 
3.8%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

Length

2024-04-18T06:46:28.885064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:28.975469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1102
61.3%
0 602
33.5%
1 68
 
3.8%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
0
908 
<NA>
889 

Length

Max length4
Median length1
Mean length2.4841402
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 908
50.5%
<NA> 889
49.5%

Length

2024-04-18T06:46:29.072717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:29.157101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 908
50.5%
na 889
49.5%

양실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
0
908 
<NA>
889 

Length

Max length4
Median length1
Mean length2.4841402
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 908
50.5%
<NA> 889
49.5%

Length

2024-04-18T06:46:29.255053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:29.338896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 908
50.5%
na 889
49.5%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)1.4%
Missing580
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean1.3105998
Minimum0
Maximum26
Zeros633
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size15.9 KiB
2024-04-18T06:46:29.416812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4.2
Maximum26
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1430336
Coefficient of variation (CV)1.6351548
Kurtosis31.888068
Mean1.3105998
Median Absolute Deviation (MAD)0
Skewness4.3671316
Sum1595
Variance4.5925931
MonotonicityNot monotonic
2024-04-18T06:46:29.506557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 633
35.2%
2 474
26.4%
6 28
 
1.6%
4 25
 
1.4%
1 19
 
1.1%
8 13
 
0.7%
10 6
 
0.3%
3 5
 
0.3%
5 3
 
0.2%
12 2
 
0.1%
Other values (7) 9
 
0.5%
(Missing) 580
32.3%
ValueCountFrequency (%)
0 633
35.2%
1 19
 
1.1%
2 474
26.4%
3 5
 
0.3%
4 25
 
1.4%
5 3
 
0.2%
6 28
 
1.6%
8 13
 
0.7%
9 2
 
0.1%
10 6
 
0.3%
ValueCountFrequency (%)
26 1
 
0.1%
22 1
 
0.1%
18 2
 
0.1%
15 1
 
0.1%
14 1
 
0.1%
12 2
 
0.1%
11 1
 
0.1%
10 6
0.3%
9 2
 
0.1%
8 13
0.7%
Distinct2
Distinct (%)0.1%
Missing2
Missing (%)0.1%
Memory size3.6 KiB
False
1340 
True
455 
(Missing)
 
2
ValueCountFrequency (%)
False 1340
74.6%
True 455
 
25.3%
(Missing) 2
 
0.1%
2024-04-18T06:46:29.590011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
0
907 
<NA>
889 
2
 
1

Length

Max length4
Median length1
Mean length2.4841402
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 907
50.5%
<NA> 889
49.5%
2 1
 
0.1%

Length

2024-04-18T06:46:29.680093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:29.784458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 907
50.5%
na 889
49.5%
2 1
 
0.1%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1796
Missing (%)99.9%
Memory size14.2 KiB
2024-04-18T06:46:29.929797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters36
Distinct characters28
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 (%)100.0%

Sample

1st row건축과-16824(2019.4.15),가설건축물 존치기간연장 신고
ValueCountFrequency (%)
건축과-16824(2019.4.15),가설건축물 1
33.3%
존치기간연장 1
33.3%
신고 1
33.3%
2024-04-18T06:46:30.191249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
 
8.3%
2
 
5.6%
2 2
 
5.6%
4 2
 
5.6%
. 2
 
5.6%
2
 
5.6%
2
 
5.6%
1
 
2.8%
1
 
2.8%
1
 
2.8%
Other values (18) 18
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
44.4%
Decimal Number 12
33.3%
Other Punctuation 3
 
8.3%
Space Separator 2
 
5.6%
Close Punctuation 1
 
2.8%
Open Punctuation 1
 
2.8%
Dash Punctuation 1
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%
Decimal Number
ValueCountFrequency (%)
1 3
25.0%
2 2
16.7%
4 2
16.7%
5 1
 
8.3%
9 1
 
8.3%
0 1
 
8.3%
8 1
 
8.3%
6 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
55.6%
Hangul 16
44.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
15.0%
2 2
10.0%
4 2
10.0%
. 2
10.0%
2
10.0%
) 1
 
5.0%
, 1
 
5.0%
5 1
 
5.0%
9 1
 
5.0%
0 1
 
5.0%
Other values (4) 4
20.0%
Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
55.6%
Hangul 16
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
15.0%
2 2
10.0%
4 2
10.0%
. 2
10.0%
2
10.0%
) 1
 
5.0%
, 1
 
5.0%
5 1
 
5.0%
9 1
 
5.0%
0 1
 
5.0%
Other values (4) 4
20.0%
Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1796 
20190501
 
1

Length

Max length8
Median length4
Mean length4.0022259
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1796
99.9%
20190501 1
 
0.1%

Length

2024-04-18T06:46:30.368572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:30.522502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1796
99.9%
20190501 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1796 
20210421
 
1

Length

Max length8
Median length4
Mean length4.0022259
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1796
99.9%
20210421 1
 
0.1%

Length

2024-04-18T06:46:30.633189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:30.737063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1796
99.9%
20210421 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1397 
자가
273 
임대
 
127

Length

Max length4
Median length4
Mean length3.5548136
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1397
77.7%
자가 273
 
15.2%
임대 127
 
7.1%

Length

2024-04-18T06:46:30.841475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:30.934010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1397
77.7%
자가 273
 
15.2%
임대 127
 
7.1%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1099 
0
698 

Length

Max length4
Median length4
Mean length2.8347245
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1099
61.2%
0 698
38.8%

Length

2024-04-18T06:46:31.043084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:31.143631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1099
61.2%
0 698
38.8%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1589 
0
203 
2
 
2
1
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.6527546
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1589
88.4%
0 203
 
11.3%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:46:31.243170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:31.341048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1589
88.4%
0 203
 
11.3%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1589 
0
203 
1
 
3
4
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.6527546
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1589
88.4%
0 203
 
11.3%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:46:31.449519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:31.554149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1589
88.4%
0 203
 
11.3%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1124 
0
673 

Length

Max length4
Median length4
Mean length2.8764608
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1124
62.5%
0 673
37.5%

Length

2024-04-18T06:46:31.658292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:31.746050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1124
62.5%
0 673
37.5%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1125 
0
672 

Length

Max length4
Median length4
Mean length2.8781302
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1125
62.6%
0 672
37.4%

Length

2024-04-18T06:46:31.833532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:46:31.923018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1125
62.6%
0 672
37.4%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
False
1760 
True
 
37
ValueCountFrequency (%)
False 1760
97.9%
True 37
 
2.1%
2024-04-18T06:46:32.010776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1797
Missing (%)100.0%
Memory size15.9 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
01목욕장업11_44_01_P32500003250000-202-2005-0000120050228<NA>1영업/정상1영업<NA><NA><NA><NA>051 4692777462.00600816부산광역시 중구 중앙동4가 79-1 마린센터(지하1층)부산광역시 중구 충장대로9번길 52, 지하1층 (중앙동4가, 마린센터)48936마린목욕탕20201204174358U2020-12-06 02:40:00.0공동탕업385825.756708180869.292985공동탕업1930011001N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
12목욕장업11_44_01_P32500003250000-202-1984-0015219840217<NA>1영업/정상1영업<NA><NA><NA><NA>051 4633803405.00600110부산광역시 중구 영주동 292-10부산광역시 중구 영주로 20 (영주동)48916거북탕20201204173920U2020-12-06 02:40:00.0공동탕업385168.082468180838.190458공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
23목욕장업11_44_01_P32500003250000-202-1988-0015919880913<NA>1영업/정상1영업<NA><NA><NA><NA>051 2472425338.97600062부산광역시 중구 신창동2가 21-2부산광역시 중구 광복로43번길 12 (신창동2가)48947녹수탕20201204174055U2020-12-06 02:40:00.0공동탕업385015.385179808.355521공동탕업412400000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
34목욕장업11_44_01_P32500003250000-202-1960-0014419601210<NA>1영업/정상1영업<NA><NA><NA><NA>051 24495011,416.48600808부산광역시 중구 부평동3가 22-1 외 2필지부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)48976금강스파20211018162024U2021-10-20 02:40:00.0공동탕업+찜질시설서비스영업384542.121202179994.202104공동탕업+찜질시설서비스영업515511000N0<NA><NA><NA><NA>00000Y<NA>
45목욕장업11_44_01_P32500003250000-202-1960-0014619601210<NA>1영업/정상1영업<NA><NA><NA><NA>051 2443396517.00600074부산광역시 중구 부평동4가 28-3부산광역시 중구 흑교로21번길 21 (부평동4가)48974부천탕20210114133518U2021-01-16 02:40:00.0공동탕업384380.762746179907.143964공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
56목욕장업11_44_01_P32500003250000-202-1982-0015119821112<NA>1영업/정상1영업<NA><NA><NA><NA>051 469 3202232.00600811부산광역시 중구 영주동 636-2부산광역시 중구 중구로188번길 21 (영주동)48922청호탕20200814133434U2020-08-16 02:40:00.0공동탕업385598.846694180987.169146공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
67목욕장업11_44_01_P32500003250000-202-1969-0000119691201<NA>1영업/정상1영업<NA><NA><NA><NA>051 2451969233.00600806부산광역시 중구 부평동2가 68-6부산광역시 중구 중구로33번길 44 (부평동2가)48977청수탕20210118094352U2021-01-20 02:40:00.0공동탕업384626.918928179878.92302공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
78목욕장업11_44_01_P32500003250000-202-1970-0000419701228<NA>1영업/정상1영업<NA><NA><NA><NA>051 4698444156.00600110부산광역시 중구 영주동 277-16부산광역시 중구 동영로 77-1 (영주동)48915영주탕20201204173703U2020-12-06 02:40:00.0공동탕업385201.615276181101.034719공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
89목욕장업11_44_01_P32500003250000-202-1960-0014719601210<NA>1영업/정상1영업<NA><NA><NA><NA>051 231 4848337.00600012부산광역시 중구 중앙동2가 21-1 , 6, 8부산광역시 중구 대청로138번길 15-1 (중앙동2가, 21-1, 6, 8)48956신수탕20200827153644U2020-08-29 02:40:00.0공동탕업385508.413955179934.600251공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
910목욕장업11_44_01_P32500003250000-202-1990-0016419900905<NA>1영업/정상1영업<NA><NA><NA><NA>051 2486681526.00600023부산광역시 중구 동광동3가 9-1부산광역시 중구 대청로134번길 10 (동광동3가)48955득일탕20201204174232U2020-12-06 02:40:00.0공동탕업385446.727545180003.559095공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
17871788목욕장업11_44_01_P34000003400000-202-1984-0033619840305<NA>3폐업2폐업20200710<NA><NA><NA>051 7215512722.19619912부산광역시 기장군 일광면 삼성리 33-6부산광역시 기장군 일광면 삼성3길 55-146044명성탕20200710154125U2020-07-12 02:40:00.0공동탕업403211.411148198587.35393공동탕업301300004Y0<NA><NA><NA>자가0<NA><NA>00N<NA>
17881789목욕장업11_44_01_P34000003400000-202-1998-0008819980819<NA>3폐업2폐업20090724<NA><NA><NA>051 7210905550.19619904부산광역시 기장군 기장읍 대변리 423번지<NA><NA>대변항해수탕20031219000000I2018-08-31 23:59:59.0공동탕업402750.992777194137.607656공동탕업3<NA>33<NA><NA><NA><NA>2Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
17891790목욕장업11_44_01_P34000003400000-202-2009-0000120091027<NA>3폐업2폐업20190718<NA><NA><NA>051 723 20931,500.00619903부산광역시 기장군 기장읍 대라리 57번지부산광역시 기장군 기장읍 차성동로 6346066석천탕20190718173053U2019-07-20 02:40:00.0공동탕업401671.55937196027.51628공동탕업004400006N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
17901791목욕장업11_44_01_P34000003400000-202-1984-0033719840922<NA>3폐업2폐업20041124<NA><NA><NA>051 7214512.00619913부산광역시 기장군 일광면 이천리 908번지<NA><NA>일광탕20020621000000I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
17911792목욕장업11_44_01_P34000003400000-202-1991-0008419911126<NA>3폐업2폐업20090817<NA><NA><NA>051 7220680322.38619905부산광역시 기장군 기장읍 동부리 152-8번지 6B 8-1L<NA><NA>제일탕20031219000000I2018-08-31 23:59:59.0공동탕업401672.154925196524.792797공동탕업3<NA>12<NA><NA><NA><NA>2Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N<NA>
17921793목욕장업11_44_01_P34000003400000-202-1994-0040719940916<NA>3폐업2폐업20061107<NA><NA><NA>051 7273302395.22619911부산광역시 기장군 일광면 칠암리 158-5번지<NA><NA>풍년탕20031219000000I2018-08-31 23:59:59.0공동탕업405347.024249202354.011586공동탕업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
17931794목욕장업11_44_01_P34000003400000-202-1994-0040819941125<NA>3폐업2폐업20090731<NA><NA><NA>051 7211997183.56619872부산광역시 기장군 철마면 장전리 366번지<NA><NA>철마목욕탕20030820000000I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
17941795목욕장업11_44_01_P34000003400000-202-1992-0008419920210<NA>3폐업2폐업20070829<NA><NA><NA>051 7221054609.82619906부산광역시 기장군 기장읍 청강리 226-7번지<NA><NA>보광탕20070814161709I2018-08-31 23:59:59.0공동탕업401913.079586195119.258755공동탕업4<NA>12<NA><NA><NA><NA>4Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N<NA>
17951796목욕장업11_44_01_P34000003400000-202-2000-0009120000330<NA>3폐업2폐업20161129<NA><NA><NA>051 7222537384.00619901부산광역시 기장군 기장읍 교리 352-8번지부산광역시 기장군 기장읍 차성동로 164-1546055교리탕20161130114519I2018-08-31 23:59:59.0공동탕업401804.176817197042.683118공동탕업3<NA>12<NA><NA><NA><NA>4Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
17961797목욕장업11_44_01_P34000003400000-202-2003-0000220031029<NA>3폐업2폐업20121220<NA><NA><NA>051 7243994348.16619905부산광역시 기장군 기장읍 서부리 422번지부산광역시 기장군 기장읍 반송로 154546058에쿠스목욕장20040531000000I2018-08-31 23:59:59.0공동탕업401037.499134196702.5529공동탕업52<NA><NA>11<NA><NA>2N<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N<NA>