Overview

Dataset statistics

Number of variables45
Number of observations1808
Missing cells16105
Missing cells (%)19.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory678.1 KiB
Average record size in memory384.1 B

Variable types

Numeric11
Categorical16
Text7
DateTime4
Unsupported5
Boolean2

Dataset

Description2023-09-01
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 (62.9%)Imbalance
위생업태명 is highly imbalanced (62.9%)Imbalance
사용끝지하층 is highly imbalanced (51.2%)Imbalance
조건부허가시작일자 is highly imbalanced (99.3%)Imbalance
조건부허가종료일자 is highly imbalanced (99.3%)Imbalance
여성종사자수 is highly imbalanced (72.3%)Imbalance
남성종사자수 is highly imbalanced (69.3%)Imbalance
다중이용업소여부 is highly imbalanced (83.5%)Imbalance
인허가취소일자 has 1808 (100.0%) missing valuesMissing
폐업일자 has 721 (39.9%) missing valuesMissing
휴업시작일자 has 1808 (100.0%) missing valuesMissing
휴업종료일자 has 1808 (100.0%) missing valuesMissing
재개업일자 has 1808 (100.0%) missing valuesMissing
소재지전화 has 158 (8.7%) missing valuesMissing
도로명전체주소 has 603 (33.4%) missing valuesMissing
도로명우편번호 has 661 (36.6%) missing valuesMissing
좌표정보(x) has 131 (7.2%) missing valuesMissing
좌표정보(y) has 131 (7.2%) missing valuesMissing
건물지상층수 has 401 (22.2%) missing valuesMissing
건물지하층수 has 624 (34.5%) missing valuesMissing
사용시작지상층 has 577 (31.9%) missing valuesMissing
사용끝지상층 has 666 (36.8%) missing valuesMissing
욕실수 has 567 (31.4%) missing valuesMissing
조건부허가신고사유 has 1807 (99.9%) missing valuesMissing
Unnamed: 44 has 1808 (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: 44 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 116 (6.4%) zerosZeros
건물지상층수 has 377 (20.9%) zerosZeros
건물지하층수 has 581 (32.1%) zerosZeros
사용시작지상층 has 392 (21.7%) zerosZeros
사용끝지상층 has 276 (15.3%) zerosZeros
욕실수 has 648 (35.8%) zerosZeros

Reproduction

Analysis started2024-04-17 21:47:05.534670
Analysis finished2024-04-17 21:47:06.506600
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1808
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean904.5
Minimum1
Maximum1808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:06.562363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile91.35
Q1452.75
median904.5
Q31356.25
95-th percentile1717.65
Maximum1808
Range1807
Interquartile range (IQR)903.5

Descriptive statistics

Standard deviation522.06896
Coefficient of variation (CV)0.57719067
Kurtosis-1.2
Mean904.5
Median Absolute Deviation (MAD)452
Skewness0
Sum1635336
Variance272556
MonotonicityStrictly increasing
2024-04-18T06:47:06.694762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1189 1
 
0.1%
1215 1
 
0.1%
1214 1
 
0.1%
1213 1
 
0.1%
1212 1
 
0.1%
1211 1
 
0.1%
1210 1
 
0.1%
1209 1
 
0.1%
1208 1
 
0.1%
Other values (1798) 1798
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 (%)
1808 1
0.1%
1807 1
0.1%
1806 1
0.1%
1805 1
0.1%
1804 1
0.1%
1803 1
0.1%
1802 1
0.1%
1801 1
0.1%
1800 1
0.1%
1799 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
목욕장업
1808 

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 1808
100.0%

Length

2024-04-18T06:47:06.828943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:06.921185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 1808
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
11_44_01_P
1808 

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 1808
100.0%

Length

2024-04-18T06:47:07.012627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:07.093172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 1808
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3323091.8
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:07.163289image/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 deviation40102.365
Coefficient of variation (CV)0.012067787
Kurtosis-0.91742239
Mean3323091.8
Median Absolute Deviation (MAD)30000
Skewness0.12286803
Sum6.00815 × 109
Variance1.6081996 × 109
MonotonicityNot monotonic
2024-04-18T06:47:07.256646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 223
12.3%
3340000 174
9.6%
3330000 160
8.8%
3310000 148
 
8.2%
3300000 147
 
8.1%
3370000 130
 
7.2%
3320000 126
 
7.0%
3350000 113
 
6.2%
3380000 112
 
6.2%
3270000 94
 
5.2%
Other values (6) 381
21.1%
ValueCountFrequency (%)
3250000 63
 
3.5%
3260000 75
 
4.1%
3270000 94
5.2%
3280000 72
 
4.0%
3290000 223
12.3%
3300000 147
8.1%
3310000 148
8.2%
3320000 126
7.0%
3330000 160
8.8%
3340000 174
9.6%
ValueCountFrequency (%)
3400000 46
 
2.5%
3390000 94
5.2%
3380000 112
6.2%
3370000 130
7.2%
3360000 31
 
1.7%
3350000 113
6.2%
3340000 174
9.6%
3330000 160
8.8%
3320000 126
7.0%
3310000 148
8.2%

관리번호
Text

UNIQUE 

Distinct1808
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:47:07.417733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters39776
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

Unique1808 ?
Unique (%)100.0%

Sample

1st row3250000-202-2022-00001
2nd row3250000-202-2005-00001
3rd row3250000-202-1984-00152
4th row3250000-202-1988-00159
5th row3250000-202-1960-00144
ValueCountFrequency (%)
3250000-202-2022-00001 1
 
0.1%
3310000-202-1970-00767 1
 
0.1%
3310000-202-1990-00971 1
 
0.1%
3310000-202-2007-00001 1
 
0.1%
3310000-202-1984-01041 1
 
0.1%
3310000-202-1982-00342 1
 
0.1%
3310000-202-1992-00725 1
 
0.1%
3310000-202-1982-01099 1
 
0.1%
3310000-202-1963-01039 1
 
0.1%
3310000-202-1981-00159 1
 
0.1%
Other values (1798) 1798
99.4%
2024-04-18T06:47:07.747901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15366
38.6%
2 5660
 
14.2%
- 5424
 
13.6%
3 3924
 
9.9%
1 2719
 
6.8%
9 2500
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34352
86.4%
Dash Punctuation 5424
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15366
44.7%
2 5660
 
16.5%
3 3924
 
11.4%
1 2719
 
7.9%
9 2500
 
7.3%
8 1135
 
3.3%
4 936
 
2.7%
7 832
 
2.4%
5 684
 
2.0%
6 596
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 5424
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39776
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15366
38.6%
2 5660
 
14.2%
- 5424
 
13.6%
3 3924
 
9.9%
1 2719
 
6.8%
9 2500
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39776
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15366
38.6%
2 5660
 
14.2%
- 5424
 
13.6%
3 3924
 
9.9%
1 2719
 
6.8%
9 2500
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%
Distinct1540
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
Minimum1954-01-31 00:00:00
Maximum2023-07-20 00:00:00
2024-04-18T06:47:07.872691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:47:08.007809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1808
Missing (%)100.0%
Memory size16.0 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
3
1087 
1
721 

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 1087
60.1%
1 721
39.9%

Length

2024-04-18T06:47:08.124545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:08.204178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1087
60.1%
1 721
39.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
폐업
1087 
영업/정상
721 

Length

Max length5
Median length2
Mean length3.1963496
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 1087
60.1%
영업/정상 721
39.9%

Length

2024-04-18T06:47:08.295558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:08.389393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1087
60.1%
영업/정상 721
39.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2
1087 
1
721 

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 1087
60.1%
1 721
39.9%

Length

2024-04-18T06:47:08.479758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:08.562254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1087
60.1%
1 721
39.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
폐업
1087 
영업
721 

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 1087
60.1%
영업 721
39.9%

Length

2024-04-18T06:47:08.646274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:08.742312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1087
60.1%
영업 721
39.9%

폐업일자
Date

MISSING 

Distinct917
Distinct (%)84.4%
Missing721
Missing (%)39.9%
Memory size14.3 KiB
Minimum1990-10-19 00:00:00
Maximum2023-07-26 00:00:00
2024-04-18T06:47:08.836110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:47:08.941455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1808
Missing (%)100.0%
Memory size16.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1808
Missing (%)100.0%
Memory size16.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1808
Missing (%)100.0%
Memory size16.0 KiB

소재지전화
Text

MISSING 

Distinct1612
Distinct (%)97.7%
Missing158
Missing (%)8.7%
Memory size14.3 KiB
2024-04-18T06:47:09.147134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.127879
Min length7

Characters and Unicode

Total characters18361
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

Unique1575 ?
Unique (%)95.5%

Sample

1st row051 462 7616
2nd row051 4692777
3rd row051 4633803
4th row051 2472425
5th row051 2449501
ValueCountFrequency (%)
051 1595
44.8%
808 8
 
0.2%
893 7
 
0.2%
261 5
 
0.1%
891 5
 
0.1%
816 5
 
0.1%
802 5
 
0.1%
070 5
 
0.1%
897 5
 
0.1%
342 4
 
0.1%
Other values (1774) 1917
53.8%
2024-04-18T06:47:09.479789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3007
16.4%
0 2801
15.3%
1 2725
14.8%
1920
10.5%
2 1445
7.9%
3 1304
7.1%
6 1230
6.7%
4 1113
 
6.1%
7 1076
 
5.9%
8 1034
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16441
89.5%
Space Separator 1920
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3007
18.3%
0 2801
17.0%
1 2725
16.6%
2 1445
8.8%
3 1304
7.9%
6 1230
7.5%
4 1113
 
6.8%
7 1076
 
6.5%
8 1034
 
6.3%
9 706
 
4.3%
Space Separator
ValueCountFrequency (%)
1920
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18361
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3007
16.4%
0 2801
15.3%
1 2725
14.8%
1920
10.5%
2 1445
7.9%
3 1304
7.1%
6 1230
6.7%
4 1113
 
6.1%
7 1076
 
5.9%
8 1034
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3007
16.4%
0 2801
15.3%
1 2725
14.8%
1920
10.5%
2 1445
7.9%
3 1304
7.1%
6 1230
6.7%
4 1113
 
6.1%
7 1076
 
5.9%
8 1034
 
5.6%

소재지면적
Real number (ℝ)

ZEROS 

Distinct1588
Distinct (%)88.3%
Missing9
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean498.57367
Minimum0
Maximum8878.3
Zeros116
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:09.602664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1237.42
median348
Q3538
95-th percentile1381.296
Maximum8878.3
Range8878.3
Interquartile range (IQR)300.58

Descriptive statistics

Standard deviation613.45881
Coefficient of variation (CV)1.2304276
Kurtosis50.791637
Mean498.57367
Median Absolute Deviation (MAD)137.34
Skewness5.735288
Sum896934.04
Variance376331.71
MonotonicityNot monotonic
2024-04-18T06:47:09.720498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 116
 
6.4%
330.0 5
 
0.3%
478.0 3
 
0.2%
363.3 3
 
0.2%
427.44 3
 
0.2%
798.24 3
 
0.2%
506.24 3
 
0.2%
252.17 3
 
0.2%
348.0 3
 
0.2%
93.73 3
 
0.2%
Other values (1578) 1654
91.5%
(Missing) 9
 
0.5%
ValueCountFrequency (%)
0.0 116
6.4%
16.65 1
 
0.1%
38.67 1
 
0.1%
60.9 1
 
0.1%
60.99 1
 
0.1%
66.0 1
 
0.1%
66.7 1
 
0.1%
72.39 1
 
0.1%
74.24 1
 
0.1%
80.99 1
 
0.1%
ValueCountFrequency (%)
8878.3 1
0.1%
7380.0 1
0.1%
7095.85 1
0.1%
6261.31 1
0.1%
6160.67 1
0.1%
4941.04 1
0.1%
4669.74 1
0.1%
4518.62 1
0.1%
4351.55 1
0.1%
3776.66 1
0.1%
Distinct631
Distinct (%)35.0%
Missing7
Missing (%)0.4%
Memory size14.3 KiB
2024-04-18T06:47:10.023885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters12607
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

Unique196 ?
Unique (%)10.9%

Sample

1st row600-800
2nd row600-816
3rd row600-110
4th row600-062
5th row600-808
ValueCountFrequency (%)
604-851 15
 
0.8%
612-846 12
 
0.7%
612-847 12
 
0.7%
608-828 11
 
0.6%
608-808 11
 
0.6%
614-822 10
 
0.6%
613-805 9
 
0.5%
607-833 9
 
0.5%
607-826 9
 
0.5%
613-832 9
 
0.5%
Other values (621) 1694
94.1%
2024-04-18T06:47:10.467068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2208
17.5%
8 1952
15.5%
- 1801
14.3%
0 1755
13.9%
1 1726
13.7%
2 840
 
6.7%
4 730
 
5.8%
3 572
 
4.5%
7 441
 
3.5%
9 320
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10806
85.7%
Dash Punctuation 1801
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2208
20.4%
8 1952
18.1%
0 1755
16.2%
1 1726
16.0%
2 840
 
7.8%
4 730
 
6.8%
3 572
 
5.3%
7 441
 
4.1%
9 320
 
3.0%
5 262
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1801
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12607
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2208
17.5%
8 1952
15.5%
- 1801
14.3%
0 1755
13.9%
1 1726
13.7%
2 840
 
6.7%
4 730
 
5.8%
3 572
 
4.5%
7 441
 
3.5%
9 320
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12607
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2208
17.5%
8 1952
15.5%
- 1801
14.3%
0 1755
13.9%
1 1726
13.7%
2 840
 
6.7%
4 730
 
5.8%
3 572
 
4.5%
7 441
 
3.5%
9 320
 
2.5%
Distinct1752
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:47:10.774431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length23.143252
Min length16

Characters and Unicode

Total characters41843
Distinct characters278
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

Unique1702 ?
Unique (%)94.1%

Sample

1st row부산광역시 중구 대청동4가 24-1
2nd row부산광역시 중구 중앙동4가 79-1 마린센터(지하1층)
3rd row부산광역시 중구 영주동 292-10
4th row부산광역시 중구 신창동2가 21-2
5th row부산광역시 중구 부평동3가 22-1 외 2필지
ValueCountFrequency (%)
부산광역시 1808
 
22.4%
t통b반 334
 
4.1%
부산진구 223
 
2.8%
사하구 174
 
2.2%
해운대구 160
 
2.0%
남구 148
 
1.8%
동래구 147
 
1.8%
연제구 130
 
1.6%
북구 126
 
1.6%
금정구 113
 
1.4%
Other values (2205) 4704
58.3%
2024-04-18T06:47:11.237334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6260
 
15.0%
2160
 
5.2%
2151
 
5.1%
2090
 
5.0%
1 1904
 
4.6%
1879
 
4.5%
1830
 
4.4%
1821
 
4.4%
1812
 
4.3%
- 1680
 
4.0%
Other values (268) 18256
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24190
57.8%
Decimal Number 8786
 
21.0%
Space Separator 6260
 
15.0%
Dash Punctuation 1680
 
4.0%
Uppercase Letter 683
 
1.6%
Other Punctuation 114
 
0.3%
Close Punctuation 61
 
0.1%
Open Punctuation 61
 
0.1%
Math Symbol 7
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2160
 
8.9%
2151
 
8.9%
2090
 
8.6%
1879
 
7.8%
1830
 
7.6%
1821
 
7.5%
1812
 
7.5%
1254
 
5.2%
1184
 
4.9%
385
 
1.6%
Other values (242) 7624
31.5%
Decimal Number
ValueCountFrequency (%)
1 1904
21.7%
2 1138
13.0%
3 995
11.3%
4 881
10.0%
5 780
8.9%
6 678
 
7.7%
7 649
 
7.4%
0 612
 
7.0%
8 609
 
6.9%
9 540
 
6.1%
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 (%)
6260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1680
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24190
57.8%
Common 16969
40.6%
Latin 684
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2160
 
8.9%
2151
 
8.9%
2090
 
8.6%
1879
 
7.8%
1830
 
7.6%
1821
 
7.5%
1812
 
7.5%
1254
 
5.2%
1184
 
4.9%
385
 
1.6%
Other values (242) 7624
31.5%
Common
ValueCountFrequency (%)
6260
36.9%
1 1904
 
11.2%
- 1680
 
9.9%
2 1138
 
6.7%
3 995
 
5.9%
4 881
 
5.2%
5 780
 
4.6%
6 678
 
4.0%
7 649
 
3.8%
0 612
 
3.6%
Other values (8) 1392
 
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 24190
57.8%
ASCII 17652
42.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6260
35.5%
1 1904
 
10.8%
- 1680
 
9.5%
2 1138
 
6.4%
3 995
 
5.6%
4 881
 
5.0%
5 780
 
4.4%
6 678
 
3.8%
7 649
 
3.7%
0 612
 
3.5%
Other values (15) 2075
 
11.8%
Hangul
ValueCountFrequency (%)
2160
 
8.9%
2151
 
8.9%
2090
 
8.6%
1879
 
7.8%
1830
 
7.6%
1821
 
7.5%
1812
 
7.5%
1254
 
5.2%
1184
 
4.9%
385
 
1.6%
Other values (242) 7624
31.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1192
Distinct (%)98.9%
Missing603
Missing (%)33.4%
Memory size14.3 KiB
2024-04-18T06:47:11.571107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length27.624066
Min length20

Characters and Unicode

Total characters33287
Distinct characters337
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

Unique1179 ?
Unique (%)97.8%

Sample

1st row부산광역시 중구 대청북길 44, 1-3층 (대청동4가)
2nd row부산광역시 중구 충장대로9번길 52, 지하1층 (중앙동4가, 마린센터)
3rd row부산광역시 중구 영주로 20 (영주동)
4th row부산광역시 중구 광복로43번길 12 (신창동2가)
5th row부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)
ValueCountFrequency (%)
부산광역시 1205
 
19.0%
부산진구 155
 
2.4%
남구 104
 
1.6%
해운대구 104
 
1.6%
사하구 103
 
1.6%
동래구 96
 
1.5%
연제구 84
 
1.3%
북구 78
 
1.2%
금정구 75
 
1.2%
사상구 72
 
1.1%
Other values (1741) 4265
67.3%
2024-04-18T06:47:12.087076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5137
 
15.4%
1528
 
4.6%
1460
 
4.4%
1460
 
4.4%
1273
 
3.8%
1264
 
3.8%
1236
 
3.7%
1210
 
3.6%
) 1190
 
3.6%
( 1190
 
3.6%
Other values (327) 16339
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20027
60.2%
Decimal Number 5141
 
15.4%
Space Separator 5137
 
15.4%
Close Punctuation 1191
 
3.6%
Open Punctuation 1191
 
3.6%
Other Punctuation 367
 
1.1%
Dash Punctuation 204
 
0.6%
Uppercase Letter 15
 
< 0.1%
Math Symbol 13
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1528
 
7.6%
1460
 
7.3%
1460
 
7.3%
1273
 
6.4%
1264
 
6.3%
1236
 
6.2%
1210
 
6.0%
1147
 
5.7%
714
 
3.6%
671
 
3.4%
Other values (299) 8064
40.3%
Decimal Number
ValueCountFrequency (%)
1 1162
22.6%
2 724
14.1%
3 642
12.5%
5 454
 
8.8%
4 445
 
8.7%
6 393
 
7.6%
0 387
 
7.5%
7 356
 
6.9%
9 292
 
5.7%
8 286
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 7
46.7%
A 4
26.7%
W 2
 
13.3%
I 1
 
6.7%
G 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 362
98.6%
. 3
 
0.8%
@ 1
 
0.3%
* 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1190
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1190
99.9%
[ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 12
92.3%
1
 
7.7%
Space Separator
ValueCountFrequency (%)
5137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20027
60.2%
Common 13244
39.8%
Latin 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1528
 
7.6%
1460
 
7.3%
1460
 
7.3%
1273
 
6.4%
1264
 
6.3%
1236
 
6.2%
1210
 
6.0%
1147
 
5.7%
714
 
3.6%
671
 
3.4%
Other values (299) 8064
40.3%
Common
ValueCountFrequency (%)
5137
38.8%
) 1190
 
9.0%
( 1190
 
9.0%
1 1162
 
8.8%
2 724
 
5.5%
3 642
 
4.8%
5 454
 
3.4%
4 445
 
3.4%
6 393
 
3.0%
0 387
 
2.9%
Other values (12) 1520
 
11.5%
Latin
ValueCountFrequency (%)
B 7
43.8%
A 4
25.0%
W 2
 
12.5%
I 1
 
6.2%
G 1
 
6.2%
1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20027
60.2%
ASCII 13258
39.8%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5137
38.7%
) 1190
 
9.0%
( 1190
 
9.0%
1 1162
 
8.8%
2 724
 
5.5%
3 642
 
4.8%
5 454
 
3.4%
4 445
 
3.4%
6 393
 
3.0%
0 387
 
2.9%
Other values (16) 1534
 
11.6%
Hangul
ValueCountFrequency (%)
1528
 
7.6%
1460
 
7.3%
1460
 
7.3%
1273
 
6.4%
1264
 
6.3%
1236
 
6.2%
1210
 
6.0%
1147
 
5.7%
714
 
3.6%
671
 
3.4%
Other values (299) 8064
40.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct877
Distinct (%)76.5%
Missing661
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean47881.063
Minimum46002
Maximum49523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:12.247151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46249
Q147141
median47878
Q348721.5
95-th percentile49395.4
Maximum49523
Range3521
Interquartile range (IQR)1580.5

Descriptive statistics

Standard deviation984.48887
Coefficient of variation (CV)0.020561132
Kurtosis-1.0538911
Mean47881.063
Median Absolute Deviation (MAD)761
Skewness-0.079862726
Sum54919579
Variance969218.34
MonotonicityNot monotonic
2024-04-18T06:47:12.411316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48099 9
 
0.5%
47709 8
 
0.4%
47248 6
 
0.3%
46327 5
 
0.3%
48095 4
 
0.2%
48053 4
 
0.2%
46308 4
 
0.2%
47712 4
 
0.2%
47142 4
 
0.2%
48052 4
 
0.2%
Other values (867) 1095
60.6%
(Missing) 661
36.6%
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%
Distinct1141
Distinct (%)63.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:47:12.712907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length3
Mean length4.1847345
Min length2

Characters and Unicode

Total characters7566
Distinct characters400
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

Unique902 ?
Unique (%)49.9%

Sample

1st row대청행복탕
2nd row마린목욕탕
3rd row거북탕
4th row녹수탕
5th row금강스파
ValueCountFrequency (%)
사우나 27
 
1.4%
청수탕 21
 
1.1%
현대탕 19
 
1.0%
옥천탕 19
 
1.0%
천수탕 16
 
0.8%
목욕탕 15
 
0.8%
산수탕 15
 
0.8%
장수탕 14
 
0.7%
제일탕 13
 
0.7%
약수탕 13
 
0.7%
Other values (1206) 1806
91.3%
2024-04-18T06:47:13.653606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1357
 
17.9%
300
 
4.0%
222
 
2.9%
182
 
2.4%
179
 
2.4%
170
 
2.2%
170
 
2.2%
160
 
2.1%
122
 
1.6%
118
 
1.6%
Other values (390) 4586
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7251
95.8%
Space Separator 170
 
2.2%
Close Punctuation 40
 
0.5%
Open Punctuation 37
 
0.5%
Uppercase Letter 27
 
0.4%
Decimal Number 19
 
0.3%
Lowercase Letter 17
 
0.2%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1357
 
18.7%
300
 
4.1%
222
 
3.1%
182
 
2.5%
179
 
2.5%
170
 
2.3%
160
 
2.2%
122
 
1.7%
118
 
1.6%
116
 
1.6%
Other values (357) 4325
59.6%
Uppercase Letter
ValueCountFrequency (%)
G 4
14.8%
S 3
11.1%
O 3
11.1%
L 3
11.1%
W 3
11.1%
B 2
7.4%
C 2
7.4%
F 1
 
3.7%
J 1
 
3.7%
M 1
 
3.7%
Other values (4) 4
14.8%
Lowercase Letter
ValueCountFrequency (%)
n 3
17.6%
l 3
17.6%
o 2
11.8%
u 2
11.8%
s 2
11.8%
e 2
11.8%
r 1
 
5.9%
b 1
 
5.9%
d 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 10
52.6%
4 8
42.1%
1 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 1
33.3%
, 1
33.3%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
170
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7250
95.8%
Common 271
 
3.6%
Latin 44
 
0.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1357
 
18.7%
300
 
4.1%
222
 
3.1%
182
 
2.5%
179
 
2.5%
170
 
2.3%
160
 
2.2%
122
 
1.7%
118
 
1.6%
116
 
1.6%
Other values (356) 4324
59.6%
Latin
ValueCountFrequency (%)
G 4
 
9.1%
S 3
 
6.8%
O 3
 
6.8%
L 3
 
6.8%
n 3
 
6.8%
l 3
 
6.8%
W 3
 
6.8%
B 2
 
4.5%
o 2
 
4.5%
u 2
 
4.5%
Other values (13) 16
36.4%
Common
ValueCountFrequency (%)
170
62.7%
) 40
 
14.8%
( 37
 
13.7%
2 10
 
3.7%
4 8
 
3.0%
- 2
 
0.7%
. 1
 
0.4%
1 1
 
0.4%
, 1
 
0.4%
& 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7250
95.8%
ASCII 315
 
4.2%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1357
 
18.7%
300
 
4.1%
222
 
3.1%
182
 
2.5%
179
 
2.5%
170
 
2.3%
160
 
2.2%
122
 
1.7%
118
 
1.6%
116
 
1.6%
Other values (356) 4324
59.6%
ASCII
ValueCountFrequency (%)
170
54.0%
) 40
 
12.7%
( 37
 
11.7%
2 10
 
3.2%
4 8
 
2.5%
G 4
 
1.3%
S 3
 
1.0%
O 3
 
1.0%
L 3
 
1.0%
n 3
 
1.0%
Other values (23) 34
 
10.8%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct1533
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
Minimum1999-02-10 00:00:00
Maximum2023-07-31 15:02:14
2024-04-18T06:47:13.785570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:47:13.951531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
I
1045 
U
763 

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 1045
57.8%
U 763
42.2%

Length

2024-04-18T06:47:14.098137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:14.201303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1045
57.8%
u 763
42.2%
Distinct394
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-08-02 02:40:00
2024-04-18T06:47:14.334351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:47:14.469839image/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 size14.3 KiB
공동탕업
1526 
목욕장업 기타
160 
공동탕업+찜질시설서비스영업
 
78
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.727323
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1526
84.4%
목욕장업 기타 160
 
8.8%
공동탕업+찜질시설서비스영업 78
 
4.3%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:47:14.628938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:14.753786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1526
77.5%
목욕장업 160
 
8.1%
기타 160
 
8.1%
공동탕업+찜질시설서비스영업 78
 
4.0%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1512
Distinct (%)90.2%
Missing131
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean387813.38
Minimum366820.79
Maximum407878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:14.873432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366820.79
5-th percentile379624.14
Q1384030.4
median388130.05
Q3391162.17
95-th percentile397021.17
Maximum407878
Range41057.216
Interquartile range (IQR)7131.7699

Descriptive statistics

Standard deviation5337.1273
Coefficient of variation (CV)0.013762102
Kurtosis0.66386322
Mean387813.38
Median Absolute Deviation (MAD)3605.0155
Skewness0.27612535
Sum6.5036303 × 108
Variance28484928
MonotonicityNot monotonic
2024-04-18T06:47:14.983857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
386026.75739607 4
 
0.2%
391834.082986499 4
 
0.2%
389415.20340442 3
 
0.2%
389680.677797295 3
 
0.2%
392683.749989177 3
 
0.2%
388552.977112094 3
 
0.2%
383091.957810087 3
 
0.2%
379618.460093644 3
 
0.2%
391103.422349355 3
 
0.2%
386428.823034759 3
 
0.2%
Other values (1502) 1645
91.0%
(Missing) 131
 
7.2%
ValueCountFrequency (%)
366820.787750492 1
0.1%
370718.68095413 1
0.1%
372902.666793487 1
0.1%
373056.591154247 1
0.1%
373088.08750839 2
0.1%
373178.636649203 1
0.1%
373368.868121567 1
0.1%
373512.891351707 2
0.1%
374901.846816856 2
0.1%
375279.393220432 1
0.1%
ValueCountFrequency (%)
407878.004041358 1
0.1%
407739.061113608 1
0.1%
407413.973711585 1
0.1%
407195.384771566 1
0.1%
406981.949996683 1
0.1%
405347.006280193 1
0.1%
405172.859382016 1
0.1%
404770.45246328 1
0.1%
404674.707509308 1
0.1%
403841.725234449 1
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct1512
Distinct (%)90.2%
Missing131
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean186594.86
Minimum173914.72
Maximum207205.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:15.097007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173914.72
5-th percentile177833.59
Q1182123.56
median186772.17
Q3190600.22
95-th percentile195664.77
Maximum207205.27
Range33290.55
Interquartile range (IQR)8476.6546

Descriptive statistics

Standard deviation5653.8993
Coefficient of variation (CV)0.030300402
Kurtosis0.047807897
Mean186594.86
Median Absolute Deviation (MAD)4137.1875
Skewness0.25942826
Sum3.1291958 × 108
Variance31966577
MonotonicityNot monotonic
2024-04-18T06:47:15.233860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
181580.381775088 4
 
0.2%
189185.417047275 4
 
0.2%
193131.590860807 3
 
0.2%
182339.017460953 3
 
0.2%
185760.578634347 3
 
0.2%
184433.515092005 3
 
0.2%
179227.873327685 3
 
0.2%
174097.616386311 3
 
0.2%
182446.170472991 3
 
0.2%
189577.746954425 3
 
0.2%
Other values (1502) 1645
91.0%
(Missing) 131
 
7.2%
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%
174676.412428457 1
 
0.1%
174765.307900471 1
 
0.1%
174811.513941025 1
 
0.1%
174885.756922702 2
0.1%
ValueCountFrequency (%)
207205.267789628 1
0.1%
207141.913579437 1
0.1%
206164.575140106 1
0.1%
205671.36699064 1
0.1%
205652.48759924 1
0.1%
205455.065758112 1
0.1%
205405.417865169 1
0.1%
205366.743408054 1
0.1%
205061.201316499 1
0.1%
204747.884437376 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
공동탕업
1526 
목욕장업 기타
160 
공동탕업+찜질시설서비스영업
 
78
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.727323
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1526
84.4%
목욕장업 기타 160
 
8.8%
공동탕업+찜질시설서비스영업 78
 
4.3%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:47:15.357920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:15.453134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1526
77.5%
목욕장업 160
 
8.1%
기타 160
 
8.1%
공동탕업+찜질시설서비스영업 78
 
4.0%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)2.3%
Missing401
Missing (%)22.2%
Infinite0
Infinite (%)0.0%
Mean3.7057569
Minimum0
Maximum42
Zeros377
Zeros (%)20.9%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:15.559333image/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 deviation4.4746944
Coefficient of variation (CV)1.2074981
Kurtosis16.060945
Mean3.7057569
Median Absolute Deviation (MAD)2
Skewness3.3016419
Sum5214
Variance20.02289
MonotonicityNot monotonic
2024-04-18T06:47:15.682532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 377
20.9%
3 298
16.5%
4 208
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) 86
 
4.8%
(Missing) 401
22.2%
ValueCountFrequency (%)
0 377
20.9%
1 25
 
1.4%
2 133
 
7.4%
3 298
16.5%
4 208
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 4
0.2%
27 1
 
0.1%
25 2
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.7%
Missing624
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean0.74746622
Minimum0
Maximum7
Zeros581
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:15.785969image/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 deviation1.049692
Coefficient of variation (CV)1.4043337
Kurtosis8.0792197
Mean0.74746622
Median Absolute Deviation (MAD)1
Skewness2.4551304
Sum885
Variance1.1018533
MonotonicityNot monotonic
2024-04-18T06:47:15.900521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 581
32.1%
1 459
25.4%
2 78
 
4.3%
3 28
 
1.5%
4 17
 
0.9%
6 11
 
0.6%
5 9
 
0.5%
7 1
 
0.1%
(Missing) 624
34.5%
ValueCountFrequency (%)
0 581
32.1%
1 459
25.4%
2 78
 
4.3%
3 28
 
1.5%
4 17
 
0.9%
5 9
 
0.5%
6 11
 
0.6%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
6 11
 
0.6%
5 9
 
0.5%
4 17
 
0.9%
3 28
 
1.5%
2 78
 
4.3%
1 459
25.4%
0 581
32.1%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.8%
Missing577
Missing (%)31.9%
Infinite0
Infinite (%)0.0%
Mean1.3354996
Minimum0
Maximum10
Zeros392
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:15.994601image/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 deviation1.4120384
Coefficient of variation (CV)1.057311
Kurtosis5.5152816
Mean1.3354996
Median Absolute Deviation (MAD)1
Skewness1.8199506
Sum1644
Variance1.9938526
MonotonicityNot monotonic
2024-04-18T06:47:16.083166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 392
21.7%
1 375
20.7%
2 300
16.6%
3 77
 
4.3%
4 42
 
2.3%
5 22
 
1.2%
6 14
 
0.8%
8 4
 
0.2%
10 3
 
0.2%
7 2
 
0.1%
(Missing) 577
31.9%
ValueCountFrequency (%)
0 392
21.7%
1 375
20.7%
2 300
16.6%
3 77
 
4.3%
4 42
 
2.3%
5 22
 
1.2%
6 14
 
0.8%
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 14
 
0.8%
5 22
 
1.2%
4 42
 
2.3%
3 77
 
4.3%
2 300
16.6%
1 375
20.7%
0 392
21.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.1%
Missing666
Missing (%)36.8%
Infinite0
Infinite (%)0.0%
Mean2.1068301
Minimum0
Maximum11
Zeros276
Zeros (%)15.3%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:16.172144image/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 deviation1.7581578
Coefficient of variation (CV)0.83450384
Kurtosis2.4157192
Mean2.1068301
Median Absolute Deviation (MAD)1
Skewness1.1124609
Sum2406
Variance3.091119
MonotonicityNot monotonic
2024-04-18T06:47:16.274405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 382
21.1%
0 276
15.3%
3 211
 
11.7%
1 94
 
5.2%
4 83
 
4.6%
5 49
 
2.7%
6 21
 
1.2%
7 11
 
0.6%
9 6
 
0.3%
8 5
 
0.3%
Other values (2) 4
 
0.2%
(Missing) 666
36.8%
ValueCountFrequency (%)
0 276
15.3%
1 94
 
5.2%
2 382
21.1%
3 211
11.7%
4 83
 
4.6%
5 49
 
2.7%
6 21
 
1.2%
7 11
 
0.6%
8 5
 
0.3%
9 6
 
0.3%
ValueCountFrequency (%)
11 1
 
0.1%
10 3
 
0.2%
9 6
 
0.3%
8 5
 
0.3%
7 11
 
0.6%
6 21
 
1.2%
5 49
 
2.7%
4 83
 
4.6%
3 211
11.7%
2 382
21.1%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
0
868 
<NA>
847 
1
 
81
2
 
9
3
 
3

Length

Max length4
Median length1
Mean length2.4054204
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 868
48.0%
<NA> 847
46.8%
1 81
 
4.5%
2 9
 
0.5%
3 3
 
0.2%

Length

2024-04-18T06:47:16.400383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:16.493849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 868
48.0%
na 847
46.8%
1 81
 
4.5%
2 9
 
0.5%
3 3
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1048 
0
666 
1
 
69
2
 
21
3
 
3

Length

Max length4
Median length4
Mean length2.7389381
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1048
58.0%
0 666
36.8%
1 69
 
3.8%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

Length

2024-04-18T06:47:16.587744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:16.699497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1048
58.0%
0 666
36.8%
1 69
 
3.8%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)1.4%
Missing567
Missing (%)31.4%
Infinite0
Infinite (%)0.0%
Mean1.3126511
Minimum0
Maximum26
Zeros648
Zeros (%)35.8%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:47:16.789192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum26
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1456429
Coefficient of variation (CV)1.6345874
Kurtosis31.144166
Mean1.3126511
Median Absolute Deviation (MAD)0
Skewness4.3042991
Sum1629
Variance4.6037834
MonotonicityNot monotonic
2024-04-18T06:47:16.900819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 648
35.8%
2 479
26.5%
6 30
 
1.7%
4 26
 
1.4%
1 19
 
1.1%
8 14
 
0.8%
10 6
 
0.3%
3 5
 
0.3%
5 3
 
0.2%
18 2
 
0.1%
Other values (7) 9
 
0.5%
(Missing) 567
31.4%
ValueCountFrequency (%)
0 648
35.8%
1 19
 
1.1%
2 479
26.5%
3 5
 
0.3%
4 26
 
1.4%
5 3
 
0.2%
6 30
 
1.7%
8 14
 
0.8%
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 14
0.8%
Distinct2
Distinct (%)0.1%
Missing2
Missing (%)0.1%
Memory size3.7 KiB
False
1347 
True
459 
(Missing)
 
2
ValueCountFrequency (%)
False 1347
74.5%
True 459
 
25.4%
(Missing) 2
 
0.1%
2024-04-18T06:47:16.996697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1807
Missing (%)99.9%
Memory size14.3 KiB
2024-04-18T06:47:17.126510image/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%
2024-04-18T06:47:17.364910image/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 size14.3 KiB
<NA>
1807 
20190501
 
1

Length

Max length8
Median length4
Mean length4.0022124
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> 1807
99.9%
20190501 1
 
0.1%

Length

2024-04-18T06:47:17.475851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:17.563658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1807
99.9%
20190501 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1807 
20210421
 
1

Length

Max length8
Median length4
Mean length4.0022124
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> 1807
99.9%
20210421 1
 
0.1%

Length

2024-04-18T06:47:17.653439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:17.741651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1807
99.9%
20210421 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1406 
자가
274 
임대
 
128

Length

Max length4
Median length4
Mean length3.5553097
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1406
77.8%
자가 274
 
15.2%
임대 128
 
7.1%

Length

2024-04-18T06:47:17.832768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:17.928298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1406
77.8%
자가 274
 
15.2%
임대 128
 
7.1%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1475 
0
328 
2
 
2
1
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.4474558
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1475
81.6%
0 328
 
18.1%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:47:18.040703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:18.148810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1475
81.6%
0 328
 
18.1%
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 size14.3 KiB
<NA>
1475 
0
328 
1
 
3
4
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.4474558
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1475
81.6%
0 328
 
18.1%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:47:18.261578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:47:18.363322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1475
81.6%
0 328
 
18.1%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
False
1764 
True
 
44
ValueCountFrequency (%)
False 1764
97.6%
True 44
 
2.4%
2024-04-18T06:47:18.456183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 44
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1808
Missing (%)100.0%
Memory size16.0 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수다중이용업소여부Unnamed: 44
01목욕장업11_44_01_P32500003250000-202-2022-000012022-03-28<NA>1영업/정상1영업<NA><NA><NA><NA>051 462 7616354.91600-800부산광역시 중구 대청동4가 24-1부산광역시 중구 대청북길 44, 1-3층 (대청동4가)48971대청행복탕2023-05-19 14:45:43U2023-05-21 02:40:00공동탕업385153.11515180500.97525공동탕업4113002Y<NA><NA><NA>임대00N<NA>
12목욕장업11_44_01_P32500003250000-202-2005-000012005-02-28<NA>1영업/정상1영업<NA><NA><NA><NA>051 4692777462.0600-816부산광역시 중구 중앙동4가 79-1 마린센터(지하1층)부산광역시 중구 충장대로9번길 52, 지하1층 (중앙동4가, 마린센터)48936마린목욕탕2020-12-04 17:43:58U2020-12-06 02:40:00공동탕업385825.756708180869.292985공동탕업19300111N<NA><NA><NA><NA><NA><NA>N<NA>
23목욕장업11_44_01_P32500003250000-202-1984-001521984-02-17<NA>1영업/정상1영업<NA><NA><NA><NA>051 4633803405.0600-110부산광역시 중구 영주동 292-10부산광역시 중구 영주로 20 (영주동)48916거북탕2020-12-04 17:39:20U2020-12-06 02:40:00공동탕업385168.082468180838.190458공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
34목욕장업11_44_01_P32500003250000-202-1988-001591988-09-13<NA>1영업/정상1영업<NA><NA><NA><NA>051 2472425338.97600-062부산광역시 중구 신창동2가 21-2부산광역시 중구 광복로43번길 12 (신창동2가)48947녹수탕2020-12-04 17:40:55U2020-12-06 02:40:00공동탕업385015.385179808.355521공동탕업4124000N<NA><NA><NA>임대<NA><NA>N<NA>
45목욕장업11_44_01_P32500003250000-202-1960-001441960-12-10<NA>1영업/정상1영업<NA><NA><NA><NA>051 24495011416.48600-808부산광역시 중구 부평동3가 22-1 외 2필지부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)48976금강스파2021-10-18 16:20:24U2021-10-20 02:40:00공동탕업+찜질시설서비스영업384542.121202179994.202104공동탕업+찜질시설서비스영업5155110N<NA><NA><NA><NA>00Y<NA>
56목욕장업11_44_01_P32500003250000-202-1960-001461960-12-10<NA>1영업/정상1영업<NA><NA><NA><NA>051 2443396517.0600-074부산광역시 중구 부평동4가 28-3부산광역시 중구 흑교로21번길 21 (부평동4가)48974부천탕2021-01-14 13:35:18U2021-01-16 02:40:00공동탕업384380.762746179907.143964공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
67목욕장업11_44_01_P32500003250000-202-1982-001511982-11-12<NA>1영업/정상1영업<NA><NA><NA><NA>051 469 3202232.0600-811부산광역시 중구 영주동 636-2부산광역시 중구 중구로188번길 21 (영주동)48922청호탕2020-08-14 13:34:34U2020-08-16 02:40:00공동탕업385598.846694180987.169146공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
78목욕장업11_44_01_P32500003250000-202-1969-000011969-12-01<NA>1영업/정상1영업<NA><NA><NA><NA>051 2451969233.0600-806부산광역시 중구 부평동2가 68-6부산광역시 중구 중구로33번길 44 (부평동2가)48977청수탕2021-01-18 09:43:52U2021-01-20 02:40:00공동탕업384626.918928179878.92302공동탕업<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N<NA>
89목욕장업11_44_01_P32500003250000-202-1970-000041970-12-28<NA>1영업/정상1영업<NA><NA><NA><NA>051 4698444156.0600-110부산광역시 중구 영주동 277-16부산광역시 중구 동영로 77-1 (영주동)48915영주탕2020-12-04 17:37:03U2020-12-06 02:40:00공동탕업385201.615276181101.034719공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
910목욕장업11_44_01_P32500003250000-202-1960-001471960-12-10<NA>1영업/정상1영업<NA><NA><NA><NA>051 231 4848337.0600-012부산광역시 중구 중앙동2가 21-1 , 6, 8부산광역시 중구 대청로138번길 15-1 (중앙동2가, 21-1, 6, 8)48956신수탕2022-03-18 10:54:44U2022-03-20 02:40:00공동탕업385508.413955179934.600251공동탕업0000000N<NA><NA><NA><NA>00N<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수다중이용업소여부Unnamed: 44
17981799목욕장업11_44_01_P34000003400000-202-1998-000881998-08-19<NA>3폐업2폐업2009-07-24<NA><NA><NA>051 7210905550.19619-904부산광역시 기장군 기장읍 대변리 423번지<NA><NA>대변항해수탕2003-12-19 00:00:00I2018-08-31 23:59:59공동탕업402751.009587194137.606353공동탕업3<NA>33<NA><NA>2Y<NA><NA><NA>임대<NA><NA>N<NA>
17991800목욕장업11_44_01_P34000003400000-202-1987-002841987-04-25<NA>3폐업2폐업2023-07-17<NA><NA><NA>051 7272155112.3619-951부산광역시 기장군 장안읍 월내리 21-2부산광역시 기장군 장안읍 월내해안4길 846037월천탕2023-07-17 11:22:09U2023-07-19 02:40:00공동탕업407195.384772205455.065758공동탕업0000000N<NA><NA><NA><NA>00N<NA>
18001801목욕장업11_44_01_P34000003400000-202-2009-000012009-10-27<NA>3폐업2폐업2019-07-18<NA><NA><NA>051 723 20931500.0619-903부산광역시 기장군 기장읍 대라리 57번지부산광역시 기장군 기장읍 차성동로 6346066석천탕2019-07-18 17:30:53U2019-07-20 02:40:00공동탕업401671.555424196027.510818공동탕업0044006N<NA><NA><NA><NA><NA><NA>N<NA>
18011802목욕장업11_44_01_P34000003400000-202-1984-003371984-09-22<NA>3폐업2폐업2004-11-24<NA><NA><NA>051 72145120.0619-913부산광역시 기장군 일광면 이천리 908번지<NA><NA>일광탕2002-06-21 00:00:00I2018-08-31 23:59:59공동탕업<NA><NA>공동탕업000<NA>0<NA>0N<NA><NA><NA><NA><NA><NA>N<NA>
18021803목욕장업11_44_01_P34000003400000-202-1991-000841991-11-26<NA>3폐업2폐업2009-08-17<NA><NA><NA>051 7220680322.38619-905부산광역시 기장군 기장읍 동부리 152-8번지 6B 8-1L<NA><NA>제일탕2003-12-19 00:00:00I2018-08-31 23:59:59공동탕업401672.155429196524.791525공동탕업3<NA>12<NA><NA>2Y<NA><NA><NA>자가<NA><NA>N<NA>
18031804목욕장업11_44_01_P34000003400000-202-1994-004071994-09-16<NA>3폐업2폐업2006-11-07<NA><NA><NA>051 7273302395.22619-911부산광역시 기장군 일광면 칠암리 158-5번지<NA><NA>풍년탕2003-12-19 00:00:00I2018-08-31 23:59:59공동탕업405347.00628202354.026519공동탕업1<NA>11<NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N<NA>
18041805목욕장업11_44_01_P34000003400000-202-1994-004081994-11-25<NA>3폐업2폐업2009-07-31<NA><NA><NA>051 7211997183.56619-872부산광역시 기장군 철마면 장전리 366번지<NA><NA>철마목욕탕2003-08-20 00:00:00I2018-08-31 23:59:59공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N<NA>
18051806목욕장업11_44_01_P34000003400000-202-1992-000841992-02-10<NA>3폐업2폐업2007-08-29<NA><NA><NA>051 7221054609.82619-906부산광역시 기장군 기장읍 청강리 226-7번지<NA><NA>보광탕2007-08-14 16:17:09I2018-08-31 23:59:59공동탕업401913.048724195119.251102공동탕업4<NA>12<NA><NA>4Y<NA><NA><NA>자가<NA><NA>N<NA>
18061807목욕장업11_44_01_P34000003400000-202-2000-000912000-03-30<NA>3폐업2폐업2016-11-29<NA><NA><NA>051 7222537384.0619-901부산광역시 기장군 기장읍 교리 352-8번지부산광역시 기장군 기장읍 차성동로 164-1546055교리탕2016-11-30 11:45:19I2018-08-31 23:59:59공동탕업401804.177755197042.680998공동탕업3<NA>12<NA><NA>4Y<NA><NA><NA>임대<NA><NA>N<NA>
18071808목욕장업11_44_01_P34000003400000-202-2003-000022003-10-29<NA>3폐업2폐업2012-12-20<NA><NA><NA>051 7243994348.16619-905부산광역시 기장군 기장읍 서부리 422번지부산광역시 기장군 기장읍 반송로 154546058에쿠스목욕장2004-05-31 00:00:00I2018-08-31 23:59:59공동탕업401037.499103196702.552856공동탕업52<NA><NA>112N<NA><NA><NA>자가<NA><NA>N<NA>