Overview

Dataset statistics

Number of variables51
Number of observations1810
Missing cells16388
Missing cells (%)17.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory779.6 KiB
Average record size in memory441.1 B

Variable types

Numeric14
Categorical22
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2021-06-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123185

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
업태구분명 is highly imbalanced (63.5%)Imbalance
위생업태명 is highly imbalanced (63.5%)Imbalance
사용끝지하층 is highly imbalanced (54.2%)Imbalance
조건부허가시작일자 is highly imbalanced (99.3%)Imbalance
조건부허가종료일자 is highly imbalanced (99.3%)Imbalance
여성종사자수 is highly imbalanced (92.5%)Imbalance
남성종사자수 is highly imbalanced (91.7%)Imbalance
다중이용업소여부 is highly imbalanced (86.9%)Imbalance
인허가취소일자 has 1810 (100.0%) missing valuesMissing
폐업일자 has 801 (44.3%) missing valuesMissing
휴업시작일자 has 1810 (100.0%) missing valuesMissing
휴업종료일자 has 1810 (100.0%) missing valuesMissing
재개업일자 has 1810 (100.0%) missing valuesMissing
소재지전화 has 118 (6.5%) missing valuesMissing
도로명전체주소 has 618 (34.1%) missing valuesMissing
도로명우편번호 has 669 (37.0%) missing valuesMissing
좌표정보(x) has 103 (5.7%) missing valuesMissing
좌표정보(y) has 103 (5.7%) missing valuesMissing
건물지상층수 has 433 (23.9%) missing valuesMissing
건물지하층수 has 672 (37.1%) missing valuesMissing
사용시작지상층 has 624 (34.5%) missing valuesMissing
사용끝지상층 has 762 (42.1%) missing valuesMissing
욕실수 has 610 (33.7%) missing valuesMissing
조건부허가신고사유 has 1809 (99.9%) missing valuesMissing
Unnamed: 50 has 1810 (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 352 (19.4%) zerosZeros
건물지하층수 has 540 (29.8%) zerosZeros
사용시작지상층 has 358 (19.8%) zerosZeros
사용끝지상층 has 192 (10.6%) zerosZeros
욕실수 has 620 (34.3%) zerosZeros

Reproduction

Analysis started2024-04-17 21:45:28.346168
Analysis finished2024-04-17 21:45:29.288382
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1810
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean905.5
Minimum1
Maximum1810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:29.361027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile91.45
Q1453.25
median905.5
Q31357.75
95-th percentile1719.55
Maximum1810
Range1809
Interquartile range (IQR)904.5

Descriptive statistics

Standard deviation522.64631
Coefficient of variation (CV)0.57719085
Kurtosis-1.2
Mean905.5
Median Absolute Deviation (MAD)452.5
Skewness0
Sum1638955
Variance273159.17
MonotonicityStrictly increasing
2024-04-18T06:45:29.498333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1190 1
 
0.1%
1216 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%
Other values (1800) 1800
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 (%)
1810 1
0.1%
1809 1
0.1%
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%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
목욕장업
1810 

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 1810
100.0%

Length

2024-04-18T06:45:29.619997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:29.697362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 1810
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
11_44_01_P
1810 

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 1810
100.0%

Length

2024-04-18T06:45:29.774561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:29.855806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 1810
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3322939.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:29.939387image/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 deviation39925.049
Coefficient of variation (CV)0.01201498
Kurtosis-0.90898057
Mean3322939.2
Median Absolute Deviation (MAD)30000
Skewness0.13702446
Sum6.01452 × 109
Variance1.5940096 × 109
MonotonicityNot monotonic
2024-04-18T06:45:30.038567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 222
12.3%
3340000 173
9.6%
3300000 164
9.1%
3330000 159
8.8%
3310000 146
 
8.1%
3370000 130
 
7.2%
3320000 123
 
6.8%
3350000 114
 
6.3%
3380000 112
 
6.2%
3270000 94
 
5.2%
Other values (6) 373
20.6%
ValueCountFrequency (%)
3250000 62
 
3.4%
3260000 72
 
4.0%
3270000 94
5.2%
3280000 72
 
4.0%
3290000 222
12.3%
3300000 164
9.1%
3310000 146
8.1%
3320000 123
6.8%
3330000 159
8.8%
3340000 173
9.6%
ValueCountFrequency (%)
3400000 45
 
2.5%
3390000 93
5.1%
3380000 112
6.2%
3370000 130
7.2%
3360000 29
 
1.6%
3350000 114
6.3%
3340000 173
9.6%
3330000 159
8.8%
3320000 123
6.8%
3310000 146
8.1%

관리번호
Text

UNIQUE 

Distinct1810
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:45:30.227575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters39820
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

Unique1810 ?
Unique (%)100.0%

Sample

1st row3400000-202-2003-00002
2nd row3400000-202-2000-00091
3rd row3400000-202-1992-00084
4th row3400000-202-1994-00408
5th row3400000-202-1994-00407
ValueCountFrequency (%)
3400000-202-2003-00002 1
 
0.1%
3330000-202-2012-00005 1
 
0.1%
3350000-202-2002-00002 1
 
0.1%
3350000-202-1984-00939 1
 
0.1%
3350000-202-1982-00974 1
 
0.1%
3350000-202-2000-01017 1
 
0.1%
3350000-202-1985-00977 1
 
0.1%
3350000-202-1990-00995 1
 
0.1%
3350000-202-1987-00979 1
 
0.1%
3350000-202-1986-00958 1
 
0.1%
Other values (1800) 1800
99.4%
2024-04-18T06:45:30.521069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15338
38.5%
2 5631
 
14.1%
- 5430
 
13.6%
3 3927
 
9.9%
1 2740
 
6.9%
9 2539
 
6.4%
8 1141
 
2.9%
4 946
 
2.4%
7 837
 
2.1%
5 693
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34390
86.4%
Dash Punctuation 5430
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15338
44.6%
2 5631
 
16.4%
3 3927
 
11.4%
1 2740
 
8.0%
9 2539
 
7.4%
8 1141
 
3.3%
4 946
 
2.8%
7 837
 
2.4%
5 693
 
2.0%
6 598
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 5430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39820
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15338
38.5%
2 5631
 
14.1%
- 5430
 
13.6%
3 3927
 
9.9%
1 2740
 
6.9%
9 2539
 
6.4%
8 1141
 
2.9%
4 946
 
2.4%
7 837
 
2.1%
5 693
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15338
38.5%
2 5631
 
14.1%
- 5430
 
13.6%
3 3927
 
9.9%
1 2740
 
6.9%
9 2539
 
6.4%
8 1141
 
2.9%
4 946
 
2.4%
7 837
 
2.1%
5 693
 
1.7%

인허가일자
Real number (ℝ)

Distinct1525
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19909356
Minimum19540131
Maximum20210401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:30.639732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19540131
5-th percentile19700461
Q119830355
median19901116
Q320010280
95-th percentile20100905
Maximum20210401
Range670270
Interquartile range (IQR)179925

Descriptive statistics

Standard deviation122611.71
Coefficient of variation (CV)0.0061584973
Kurtosis-0.36266901
Mean19909356
Median Absolute Deviation (MAD)80807.5
Skewness-0.067230095
Sum3.6035934 × 1010
Variance1.5033632 × 1010
MonotonicityNot monotonic
2024-04-18T06:45:30.766999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19630110 15
 
0.8%
20001130 9
 
0.5%
19921202 8
 
0.4%
19960710 6
 
0.3%
19971227 6
 
0.3%
20000420 5
 
0.3%
20030115 5
 
0.3%
19830304 5
 
0.3%
19820928 5
 
0.3%
19861217 4
 
0.2%
Other values (1515) 1742
96.2%
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 (%)
20210401 1
0.1%
20210316 1
0.1%
20201013 1
0.1%
20200924 1
0.1%
20200921 1
0.1%
20200908 1
0.1%
20200827 1
0.1%
20200708 1
0.1%
20200703 1
0.1%
20200624 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1810
Missing (%)100.0%
Memory size16.0 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
3
1009 
1
801 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 1009
55.7%
1 801
44.3%

Length

2024-04-18T06:45:30.889244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:30.974364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1009
55.7%
1 801
44.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
폐업
1009 
영업/정상
801 

Length

Max length5
Median length2
Mean length3.3276243
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1009
55.7%
영업/정상 801
44.3%

Length

2024-04-18T06:45:31.110965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:31.214401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1009
55.7%
영업/정상 801
44.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2
1009 
1
801 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 1009
55.7%
1 801
44.3%

Length

2024-04-18T06:45:31.307804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:31.390541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1009
55.7%
1 801
44.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
폐업
1009 
영업
801 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1009
55.7%
영업 801
44.3%

Length

2024-04-18T06:45:31.498527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:31.584108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1009
55.7%
영업 801
44.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct846
Distinct (%)83.8%
Missing801
Missing (%)44.3%
Infinite0
Infinite (%)0.0%
Mean20094964
Minimum19860612
Maximum20210422
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:31.689489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19860612
5-th percentile19990367
Q120050901
median20100114
Q320150316
95-th percentile20191075
Maximum20210422
Range349810
Interquartile range (IQR)99415

Descriptive statistics

Standard deviation64970.415
Coefficient of variation (CV)0.0032331691
Kurtosis0.062803004
Mean20094964
Median Absolute Deviation (MAD)49413
Skewness-0.44761569
Sum2.0275818 × 1010
Variance4.2211548 × 109
MonotonicityNot monotonic
2024-04-18T06:45:31.810260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050121 12
 
0.7%
20001130 7
 
0.4%
20051017 7
 
0.4%
20170310 5
 
0.3%
20030401 5
 
0.3%
20141030 4
 
0.2%
20190226 4
 
0.2%
20120621 4
 
0.2%
20030122 4
 
0.2%
20150601 3
 
0.2%
Other values (836) 954
52.7%
(Missing) 801
44.3%
ValueCountFrequency (%)
19860612 1
0.1%
19870602 1
0.1%
19871229 1
0.1%
19890607 1
0.1%
19891016 1
0.1%
19900228 1
0.1%
19900705 1
0.1%
19901019 2
0.1%
19911220 1
0.1%
19920305 1
0.1%
ValueCountFrequency (%)
20210422 1
 
0.1%
20210415 1
 
0.1%
20210407 1
 
0.1%
20210329 1
 
0.1%
20210325 1
 
0.1%
20210322 3
0.2%
20210218 1
 
0.1%
20210215 1
 
0.1%
20210208 1
 
0.1%
20210119 1
 
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1810
Missing (%)100.0%
Memory size16.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1810
Missing (%)100.0%
Memory size16.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1810
Missing (%)100.0%
Memory size16.0 KiB

소재지전화
Text

MISSING 

Distinct1608
Distinct (%)95.0%
Missing118
Missing (%)6.5%
Memory size14.3 KiB
2024-04-18T06:45:32.051785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.903664
Min length3

Characters and Unicode

Total characters18449
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

Unique1569 ?
Unique (%)92.7%

Sample

1st row051 7243994
2nd row051 7222537
3rd row051 7221054
4th row051 7211997
5th row051 7273302
ValueCountFrequency (%)
051 1638
45.6%
893 7
 
0.2%
808 7
 
0.2%
070 6
 
0.2%
816 5
 
0.1%
897 5
 
0.1%
891 5
 
0.1%
802 5
 
0.1%
261 5
 
0.1%
727 4
 
0.1%
Other values (1762) 1905
53.0%
2024-04-18T06:45:32.432683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3048
16.5%
0 2839
15.4%
1 2763
15.0%
1909
10.3%
2 1450
7.9%
3 1297
7.0%
6 1226
6.6%
4 1108
 
6.0%
7 1074
 
5.8%
8 1036
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16540
89.7%
Space Separator 1909
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3048
18.4%
0 2839
17.2%
1 2763
16.7%
2 1450
8.8%
3 1297
7.8%
6 1226
7.4%
4 1108
 
6.7%
7 1074
 
6.5%
8 1036
 
6.3%
9 699
 
4.2%
Space Separator
ValueCountFrequency (%)
1909
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18449
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3048
16.5%
0 2839
15.4%
1 2763
15.0%
1909
10.3%
2 1450
7.9%
3 1297
7.0%
6 1226
6.6%
4 1108
 
6.0%
7 1074
 
5.8%
8 1036
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18449
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3048
16.5%
0 2839
15.4%
1 2763
15.0%
1909
10.3%
2 1450
7.9%
3 1297
7.0%
6 1226
6.6%
4 1108
 
6.0%
7 1074
 
5.8%
8 1036
 
5.6%
Distinct1591
Distinct (%)88.3%
Missing9
Missing (%)0.5%
Memory size14.3 KiB
2024-04-18T06:45:32.701091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.9700167
Min length3

Characters and Unicode

Total characters10752
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

Unique1508 ?
Unique (%)83.7%

Sample

1st row348.16
2nd row384.00
3rd row609.82
4th row183.56
5th row395.22
ValueCountFrequency (%)
00 117
 
6.5%
330.00 5
 
0.3%
93.73 3
 
0.2%
284.00 3
 
0.2%
506.24 3
 
0.2%
348.00 3
 
0.2%
426.00 3
 
0.2%
427.44 3
 
0.2%
478.00 3
 
0.2%
798.24 3
 
0.2%
Other values (1581) 1655
91.9%
2024-04-18T06:45:33.090291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1801
16.8%
0 1438
13.4%
2 1062
9.9%
3 1008
9.4%
4 934
8.7%
1 903
8.4%
8 704
 
6.5%
6 699
 
6.5%
5 694
 
6.5%
7 676
 
6.3%
Other values (2) 833
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8792
81.8%
Other Punctuation 1960
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1438
16.4%
2 1062
12.1%
3 1008
11.5%
4 934
10.6%
1 903
10.3%
8 704
8.0%
6 699
8.0%
5 694
7.9%
7 676
7.7%
9 674
7.7%
Other Punctuation
ValueCountFrequency (%)
. 1801
91.9%
, 159
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
Common 10752
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1801
16.8%
0 1438
13.4%
2 1062
9.9%
3 1008
9.4%
4 934
8.7%
1 903
8.4%
8 704
 
6.5%
6 699
 
6.5%
5 694
 
6.5%
7 676
 
6.3%
Other values (2) 833
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1801
16.8%
0 1438
13.4%
2 1062
9.9%
3 1008
9.4%
4 934
8.7%
1 903
8.4%
8 704
 
6.5%
6 699
 
6.5%
5 694
 
6.5%
7 676
 
6.3%
Other values (2) 833
7.7%

소재지우편번호
Real number (ℝ)

Distinct630
Distinct (%)34.9%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean610420.3
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:33.221296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601811
Q1606809
median611800
Q3614820
95-th percentile617833.8
Maximum619953
Range19942
Interquartile range (IQR)8011

Descriptive statistics

Standard deviation5164.6754
Coefficient of variation (CV)0.0084608513
Kurtosis-0.91812306
Mean610420.3
Median Absolute Deviation (MAD)3963
Skewness-0.20722323
Sum1.1018086 × 109
Variance26673872
MonotonicityNot monotonic
2024-04-18T06:45:33.348193image/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 10
 
0.6%
608828 10
 
0.6%
614822 10
 
0.6%
607833 10
 
0.6%
607826 9
 
0.5%
613805 9
 
0.5%
613832 9
 
0.5%
Other values (620) 1699
93.9%
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%
Distinct1734
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:45:34.158840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length23.378453
Min length16

Characters and Unicode

Total characters42315
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

Unique1669 ?
Unique (%)92.2%

Sample

1st row부산광역시 기장군 기장읍 서부리 422번지
2nd row부산광역시 기장군 기장읍 교리 352-8번지
3rd row부산광역시 기장군 기장읍 청강리 226-7번지
4th row부산광역시 기장군 철마면 장전리 366번지
5th row부산광역시 기장군 일광면 칠암리 158-5번지
ValueCountFrequency (%)
부산광역시 1810
 
22.4%
t통b반 334
 
4.1%
부산진구 222
 
2.8%
사하구 173
 
2.1%
동래구 164
 
2.0%
해운대구 159
 
2.0%
남구 146
 
1.8%
연제구 130
 
1.6%
북구 123
 
1.5%
금정구 114
 
1.4%
Other values (2169) 4692
58.2%
2024-04-18T06:45:34.628769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6258
 
14.8%
2161
 
5.1%
2152
 
5.1%
2108
 
5.0%
1 1906
 
4.5%
1880
 
4.4%
1831
 
4.3%
1822
 
4.3%
1814
 
4.3%
- 1682
 
4.0%
Other values (266) 18701
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24664
58.3%
Decimal Number 8784
 
20.8%
Space Separator 6258
 
14.8%
Dash Punctuation 1682
 
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 (%)
2161
 
8.8%
2152
 
8.7%
2108
 
8.5%
1880
 
7.6%
1831
 
7.4%
1822
 
7.4%
1814
 
7.4%
1492
 
6.0%
1424
 
5.8%
385
 
1.6%
Other values (240) 7595
30.8%
Decimal Number
ValueCountFrequency (%)
1 1906
21.7%
2 1133
12.9%
3 986
11.2%
4 892
10.2%
5 782
8.9%
6 679
 
7.7%
7 644
 
7.3%
8 611
 
7.0%
0 610
 
6.9%
9 541
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 342
50.1%
T 334
48.9%
A 2
 
0.3%
W 2
 
0.3%
I 1
 
0.1%
G 1
 
0.1%
L 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 112
98.2%
@ 1
 
0.9%
. 1
 
0.9%
Space Separator
ValueCountFrequency (%)
6258
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1682
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 24664
58.3%
Common 16967
40.1%
Latin 684
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2161
 
8.8%
2152
 
8.7%
2108
 
8.5%
1880
 
7.6%
1831
 
7.4%
1822
 
7.4%
1814
 
7.4%
1492
 
6.0%
1424
 
5.8%
385
 
1.6%
Other values (240) 7595
30.8%
Common
ValueCountFrequency (%)
6258
36.9%
1 1906
 
11.2%
- 1682
 
9.9%
2 1133
 
6.7%
3 986
 
5.8%
4 892
 
5.3%
5 782
 
4.6%
6 679
 
4.0%
7 644
 
3.8%
8 611
 
3.6%
Other values (8) 1394
 
8.2%
Latin
ValueCountFrequency (%)
B 342
50.0%
T 334
48.8%
A 2
 
0.3%
W 2
 
0.3%
1
 
0.1%
I 1
 
0.1%
G 1
 
0.1%
L 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24664
58.3%
ASCII 17650
41.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6258
35.5%
1 1906
 
10.8%
- 1682
 
9.5%
2 1133
 
6.4%
3 986
 
5.6%
4 892
 
5.1%
5 782
 
4.4%
6 679
 
3.8%
7 644
 
3.6%
8 611
 
3.5%
Other values (15) 2077
 
11.8%
Hangul
ValueCountFrequency (%)
2161
 
8.8%
2152
 
8.7%
2108
 
8.5%
1880
 
7.6%
1831
 
7.4%
1822
 
7.4%
1814
 
7.4%
1492
 
6.0%
1424
 
5.8%
385
 
1.6%
Other values (240) 7595
30.8%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1178
Distinct (%)98.8%
Missing618
Missing (%)34.1%
Memory size14.3 KiB
2024-04-18T06:45:34.956486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length27.503356
Min length20

Characters and Unicode

Total characters32784
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

Unique1166 ?
Unique (%)97.8%

Sample

1st row부산광역시 기장군 기장읍 반송로 1545
2nd row부산광역시 기장군 기장읍 차성동로 164-15
3rd row부산광역시 기장군 기장읍 차성동로 63
4th row부산광역시 기장군 일광면 삼성3길 55-1
5th row부산광역시 기장군 장안읍 길천길 1-2
ValueCountFrequency (%)
부산광역시 1192
 
19.1%
부산진구 154
 
2.5%
해운대구 103
 
1.6%
남구 102
 
1.6%
사하구 102
 
1.6%
동래구 99
 
1.6%
연제구 84
 
1.3%
금정구 75
 
1.2%
북구 75
 
1.2%
사상구 71
 
1.1%
Other values (1719) 4186
67.1%
2024-04-18T06:45:35.428614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5052
 
15.4%
1514
 
4.6%
1446
 
4.4%
1445
 
4.4%
1259
 
3.8%
1248
 
3.8%
1221
 
3.7%
1197
 
3.7%
) 1178
 
3.6%
( 1178
 
3.6%
Other values (326) 16046
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19751
60.2%
Decimal Number 5055
 
15.4%
Space Separator 5052
 
15.4%
Close Punctuation 1179
 
3.6%
Open Punctuation 1179
 
3.6%
Other Punctuation 342
 
1.0%
Dash Punctuation 199
 
0.6%
Uppercase Letter 14
 
< 0.1%
Math Symbol 12
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1514
 
7.7%
1446
 
7.3%
1445
 
7.3%
1259
 
6.4%
1248
 
6.3%
1221
 
6.2%
1197
 
6.1%
1136
 
5.8%
709
 
3.6%
668
 
3.4%
Other values (298) 7908
40.0%
Decimal Number
ValueCountFrequency (%)
1 1142
22.6%
2 719
14.2%
3 622
12.3%
5 443
 
8.8%
4 433
 
8.6%
6 390
 
7.7%
0 380
 
7.5%
7 353
 
7.0%
9 289
 
5.7%
8 284
 
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 (%)
, 337
98.5%
. 3
 
0.9%
@ 1
 
0.3%
* 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1178
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1178
99.9%
[ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 11
91.7%
1
 
8.3%
Space Separator
ValueCountFrequency (%)
5052
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19751
60.2%
Common 13018
39.7%
Latin 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1514
 
7.7%
1446
 
7.3%
1445
 
7.3%
1259
 
6.4%
1248
 
6.3%
1221
 
6.2%
1197
 
6.1%
1136
 
5.8%
709
 
3.6%
668
 
3.4%
Other values (298) 7908
40.0%
Common
ValueCountFrequency (%)
5052
38.8%
) 1178
 
9.0%
( 1178
 
9.0%
1 1142
 
8.8%
2 719
 
5.5%
3 622
 
4.8%
5 443
 
3.4%
4 433
 
3.3%
6 390
 
3.0%
0 380
 
2.9%
Other values (12) 1481
 
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 19751
60.2%
ASCII 13031
39.7%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5052
38.8%
) 1178
 
9.0%
( 1178
 
9.0%
1 1142
 
8.8%
2 719
 
5.5%
3 622
 
4.8%
5 443
 
3.4%
4 433
 
3.3%
6 390
 
3.0%
0 380
 
2.9%
Other values (16) 1494
 
11.5%
Hangul
ValueCountFrequency (%)
1514
 
7.7%
1446
 
7.3%
1445
 
7.3%
1259
 
6.4%
1248
 
6.3%
1221
 
6.2%
1197
 
6.1%
1136
 
5.8%
709
 
3.6%
668
 
3.4%
Other values (298) 7908
40.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct878
Distinct (%)77.0%
Missing669
Missing (%)37.0%
Infinite0
Infinite (%)0.0%
Mean47879.602
Minimum46002
Maximum49523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:35.560448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46249
Q147142
median47872
Q348715
95-th percentile49394
Maximum49523
Range3521
Interquartile range (IQR)1573

Descriptive statistics

Standard deviation979.85099
Coefficient of variation (CV)0.020464894
Kurtosis-1.0352859
Mean47879.602
Median Absolute Deviation (MAD)745
Skewness-0.080030317
Sum54630626
Variance960107.96
MonotonicityNot monotonic
2024-04-18T06:45:35.714683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48099 8
 
0.4%
47709 8
 
0.4%
47248 6
 
0.3%
46327 5
 
0.3%
47814 4
 
0.2%
46308 4
 
0.2%
48095 4
 
0.2%
48052 4
 
0.2%
47142 4
 
0.2%
47712 4
 
0.2%
Other values (868) 1090
60.2%
(Missing) 669
37.0%
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%
Distinct1136
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:45:36.079260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length3
Mean length4.1187845
Min length2

Characters and Unicode

Total characters7455
Distinct characters381
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

Unique894 ?
Unique (%)49.4%

Sample

1st row에쿠스목욕장
2nd row교리탕
3rd row보광탕
4th row철마목욕탕
5th row풍년탕
ValueCountFrequency (%)
사우나 23
 
1.2%
청수탕 21
 
1.1%
현대탕 21
 
1.1%
옥천탕 19
 
1.0%
산수탕 15
 
0.8%
천수탕 15
 
0.8%
목욕탕 15
 
0.8%
장수탕 14
 
0.7%
평화탕 13
 
0.7%
정수탕 13
 
0.7%
Other values (1191) 1792
91.4%
2024-04-18T06:45:36.530552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1369
 
18.4%
301
 
4.0%
223
 
3.0%
182
 
2.4%
180
 
2.4%
168
 
2.3%
158
 
2.1%
151
 
2.0%
122
 
1.6%
117
 
1.6%
Other values (371) 4484
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7187
96.4%
Space Separator 151
 
2.0%
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 (%)
1369
 
19.0%
301
 
4.2%
223
 
3.1%
182
 
2.5%
180
 
2.5%
168
 
2.3%
158
 
2.2%
122
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (349) 4254
59.2%
Uppercase Letter
ValueCountFrequency (%)
G 4
26.7%
O 2
13.3%
W 2
13.3%
L 2
13.3%
B 1
 
6.7%
J 1
 
6.7%
M 1
 
6.7%
S 1
 
6.7%
F 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
n 2
28.6%
d 1
14.3%
u 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 (%)
151
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 7186
96.4%
Common 246
 
3.3%
Latin 22
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1369
 
19.1%
301
 
4.2%
223
 
3.1%
182
 
2.5%
180
 
2.5%
168
 
2.3%
158
 
2.2%
122
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (348) 4253
59.2%
Latin
ValueCountFrequency (%)
G 4
18.2%
o 2
9.1%
n 2
9.1%
O 2
9.1%
W 2
9.1%
L 2
9.1%
B 1
 
4.5%
d 1
 
4.5%
u 1
 
4.5%
r 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
151
61.4%
) 37
 
15.0%
( 34
 
13.8%
2 11
 
4.5%
4 9
 
3.7%
- 2
 
0.8%
, 1
 
0.4%
. 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7186
96.4%
ASCII 268
 
3.6%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1369
 
19.1%
301
 
4.2%
223
 
3.1%
182
 
2.5%
180
 
2.5%
168
 
2.3%
158
 
2.2%
122
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (348) 4253
59.2%
ASCII
ValueCountFrequency (%)
151
56.3%
) 37
 
13.8%
( 34
 
12.7%
2 11
 
4.1%
4 9
 
3.4%
G 4
 
1.5%
o 2
 
0.7%
n 2
 
0.7%
O 2
 
0.7%
- 2
 
0.7%
Other values (12) 14
 
5.2%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1515
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0126393 × 1013
Minimum1.999021 × 1013
Maximum2.021043 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:36.685186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.999021 × 1013
5-th percentile2.0020422 × 1013
Q12.0050211 × 1013
median2.014086 × 1013
Q32.0200112 × 1013
95-th percentile2.0210208 × 1013
Maximum2.021043 × 1013
Range2.2022013 × 1011
Interquartile range (IQR)1.4990136 × 1011

Descriptive statistics

Standard deviation7.1078426 × 1010
Coefficient of variation (CV)0.0035316029
Kurtosis-1.4261397
Mean2.0126393 × 1013
Median Absolute Deviation (MAD)6.0062524 × 1010
Skewness-0.36086121
Sum3.6428771 × 1016
Variance5.0521426 × 1021
MonotonicityNot monotonic
2024-04-18T06:45:36.821414image/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 12
 
0.7%
20020422000000 10
 
0.6%
20041208000000 9
 
0.5%
20040324000000 8
 
0.4%
20030722000000 8
 
0.4%
Other values (1505) 1674
92.5%
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 (%)
20210430134659 1
0.1%
20210430130309 1
0.1%
20210429160658 1
0.1%
20210429141717 1
0.1%
20210429105709 1
0.1%
20210429102230 1
0.1%
20210427160054 1
0.1%
20210426163616 1
0.1%
20210422100722 1
0.1%
20210419192707 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
I
1175 
U
635 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1175
64.9%
U 635
35.1%

Length

2024-04-18T06:45:36.944368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:37.044079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1175
64.9%
u 635
35.1%
Distinct249
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-02 02:40:00
2024-04-18T06:45:37.148345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:45:37.272032image/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
1535 
목욕장업 기타
155 
공동탕업+찜질시설서비스영업
 
76
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7071823
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1535
84.8%
목욕장업 기타 155
 
8.6%
공동탕업+찜질시설서비스영업 76
 
4.2%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:45:37.398427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:37.490653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1535
78.1%
목욕장업 155
 
7.9%
기타 155
 
7.9%
공동탕업+찜질시설서비스영업 76
 
3.9%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1540
Distinct (%)90.2%
Missing103
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean387834.22
Minimum366820.79
Maximum407878.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:37.588018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366820.79
5-th percentile379644.67
Q1384183.07
median388186.05
Q3391122.4
95-th percentile396841.07
Maximum407878.31
Range41057.525
Interquartile range (IQR)6939.3304

Descriptive statistics

Standard deviation5279.2398
Coefficient of variation (CV)0.013612104
Kurtosis0.7355075
Mean387834.22
Median Absolute Deviation (MAD)3518.6278
Skewness0.25406415
Sum6.6203302 × 108
Variance27870373
MonotonicityNot monotonic
2024-04-18T06:45:37.710148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
389322.400841052 4
 
0.2%
389655.360752282 4
 
0.2%
386026.75739607 4
 
0.2%
391834.082986499 4
 
0.2%
383091.957810087 3
 
0.2%
387887.847333871 3
 
0.2%
378594.286473542 3
 
0.2%
379381.589505082 3
 
0.2%
386428.823034759 3
 
0.2%
391103.422349355 3
 
0.2%
Other values (1530) 1673
92.4%
(Missing) 103
 
5.7%
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 

Distinct1540
Distinct (%)90.2%
Missing103
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean186669.95
Minimum173914.72
Maximum207205.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:37.825392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173914.72
5-th percentile177923.58
Q1182345.44
median186863.29
Q3190709.95
95-th percentile195571.84
Maximum207205.17
Range33290.452
Interquartile range (IQR)8364.515

Descriptive statistics

Standard deviation5628.5743
Coefficient of variation (CV)0.030152547
Kurtosis0.02689192
Mean186669.95
Median Absolute Deviation (MAD)4091.8147
Skewness0.23169017
Sum3.186456 × 108
Variance31680849
MonotonicityNot monotonic
2024-04-18T06:45:37.937515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193209.131530013 4
 
0.2%
191344.913457427 4
 
0.2%
181580.381775088 4
 
0.2%
189185.417047275 4
 
0.2%
179227.873327685 3
 
0.2%
187966.542955171 3
 
0.2%
180709.776059033 3
 
0.2%
180485.975246308 3
 
0.2%
189577.746954425 3
 
0.2%
182446.170472991 3
 
0.2%
Other values (1530) 1673
92.4%
(Missing) 103
 
5.7%
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 size14.3 KiB
공동탕업
1535 
목욕장업 기타
155 
공동탕업+찜질시설서비스영업
 
76
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7071823
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1535
84.8%
목욕장업 기타 155
 
8.6%
공동탕업+찜질시설서비스영업 76
 
4.2%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:45:38.054122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:38.149937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1535
78.1%
목욕장업 155
 
7.9%
기타 155
 
7.9%
공동탕업+찜질시설서비스영업 76
 
3.9%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)2.4%
Missing433
Missing (%)23.9%
Infinite0
Infinite (%)0.0%
Mean3.7487291
Minimum0
Maximum42
Zeros352
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:38.262025image/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 deviation4.4428755
Coefficient of variation (CV)1.1851685
Kurtosis16.246982
Mean3.7487291
Median Absolute Deviation (MAD)2
Skewness3.3060001
Sum5162
Variance19.739143
MonotonicityNot monotonic
2024-04-18T06:45:38.364674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 352
19.4%
3 298
16.5%
4 206
11.4%
2 133
 
7.3%
5 131
 
7.2%
6 51
 
2.8%
7 48
 
2.7%
8 29
 
1.6%
1 25
 
1.4%
9 20
 
1.1%
Other values (23) 84
 
4.6%
(Missing) 433
23.9%
ValueCountFrequency (%)
0 352
19.4%
1 25
 
1.4%
2 133
 
7.3%
3 298
16.5%
4 206
11.4%
5 131
 
7.2%
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%
Missing672
Missing (%)37.1%
Infinite0
Infinite (%)0.0%
Mean0.76537786
Minimum0
Maximum7
Zeros540
Zeros (%)29.8%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:38.469268image/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 deviation1.0444627
Coefficient of variation (CV)1.3646366
Kurtosis7.934637
Mean0.76537786
Median Absolute Deviation (MAD)1
Skewness2.4146872
Sum871
Variance1.0909023
MonotonicityNot monotonic
2024-04-18T06:45:38.563490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 540
29.8%
1 457
25.2%
2 77
 
4.3%
3 28
 
1.5%
4 16
 
0.9%
6 10
 
0.6%
5 9
 
0.5%
7 1
 
0.1%
(Missing) 672
37.1%
ValueCountFrequency (%)
0 540
29.8%
1 457
25.2%
2 77
 
4.3%
3 28
 
1.5%
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
 
1.5%
2 77
 
4.3%
1 457
25.2%
0 540
29.8%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.8%
Missing624
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean1.3650927
Minimum0
Maximum10
Zeros358
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:38.653690image/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 deviation1.405509
Coefficient of variation (CV)1.029607
Kurtosis5.6448604
Mean1.3650927
Median Absolute Deviation (MAD)1
Skewness1.8161357
Sum1619
Variance1.9754556
MonotonicityNot monotonic
2024-04-18T06:45:38.750293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 368
20.3%
0 358
19.8%
2 299
16.5%
3 77
 
4.3%
4 42
 
2.3%
5 20
 
1.1%
6 13
 
0.7%
8 4
 
0.2%
10 3
 
0.2%
7 2
 
0.1%
(Missing) 624
34.5%
ValueCountFrequency (%)
0 358
19.8%
1 368
20.3%
2 299
16.5%
3 77
 
4.3%
4 42
 
2.3%
5 20
 
1.1%
6 13
 
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 13
 
0.7%
5 20
 
1.1%
4 42
 
2.3%
3 77
 
4.3%
2 299
16.5%
1 368
20.3%
0 358
19.8%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.1%
Missing762
Missing (%)42.1%
Infinite0
Infinite (%)0.0%
Mean2.2633588
Minimum0
Maximum11
Zeros192
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:38.849465image/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 deviation1.7104971
Coefficient of variation (CV)0.75573397
Kurtosis2.6797966
Mean2.2633588
Median Absolute Deviation (MAD)1
Skewness1.1225323
Sum2372
Variance2.9258004
MonotonicityNot monotonic
2024-04-18T06:45:38.936794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 381
21.0%
3 207
 
11.4%
0 192
 
10.6%
1 92
 
5.1%
4 82
 
4.5%
5 48
 
2.7%
6 21
 
1.2%
7 11
 
0.6%
8 5
 
0.3%
9 5
 
0.3%
Other values (2) 4
 
0.2%
(Missing) 762
42.1%
ValueCountFrequency (%)
0 192
10.6%
1 92
 
5.1%
2 381
21.0%
3 207
11.4%
4 82
 
4.5%
5 48
 
2.7%
6 21
 
1.2%
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 21
 
1.2%
5 48
 
2.7%
4 82
 
4.5%
3 207
11.4%
2 381
21.0%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
942 
0
776 
1
 
80
2
 
9
3
 
3

Length

Max length4
Median length4
Mean length2.561326
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 942
52.0%
0 776
42.9%
1 80
 
4.4%
2 9
 
0.5%
3 3
 
0.2%

Length

2024-04-18T06:45:39.041020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:39.136442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 942
52.0%
0 776
42.9%
1 80
 
4.4%
2 9
 
0.5%
3 3
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1198 
0
520 
1
 
67
2
 
21
3
 
3

Length

Max length4
Median length4
Mean length2.9856354
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1198
66.2%
0 520
28.7%
1 67
 
3.7%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

Length

2024-04-18T06:45:39.243567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:39.346305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1198
66.2%
0 520
28.7%
1 67
 
3.7%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
936 
0
874 

Length

Max length4
Median length4
Mean length2.5513812
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 936
51.7%
0 874
48.3%

Length

2024-04-18T06:45:39.457242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:39.563476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 936
51.7%
0 874
48.3%

양실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
936 
0
874 

Length

Max length4
Median length4
Mean length2.5513812
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 936
51.7%
0 874
48.3%

Length

2024-04-18T06:45:39.671662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:39.775698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 936
51.7%
0 874
48.3%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)1.4%
Missing610
Missing (%)33.7%
Infinite0
Infinite (%)0.0%
Mean1.3233333
Minimum0
Maximum26
Zeros620
Zeros (%)34.3%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:45:39.891074image/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 deviation2.1535212
Coefficient of variation (CV)1.627346
Kurtosis31.595833
Mean1.3233333
Median Absolute Deviation (MAD)0
Skewness4.3493591
Sum1588
Variance4.6376536
MonotonicityNot monotonic
2024-04-18T06:45:40.000052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 620
34.3%
2 471
26.0%
6 28
 
1.5%
4 25
 
1.4%
1 18
 
1.0%
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) 610
33.7%
ValueCountFrequency (%)
0 620
34.3%
1 18
 
1.0%
2 471
26.0%
3 5
 
0.3%
4 25
 
1.4%
5 3
 
0.2%
6 28
 
1.5%
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 size3.7 KiB
False
1358 
True
450 
(Missing)
 
2
ValueCountFrequency (%)
False 1358
75.0%
True 450
 
24.9%
(Missing) 2
 
0.1%
2024-04-18T06:45:40.089786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
936 
0
873 
2
 
1

Length

Max length4
Median length4
Mean length2.5513812
Min length1

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> 936
51.7%
0 873
48.2%
2 1
 
0.1%

Length

2024-04-18T06:45:40.177262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:40.265502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 936
51.7%
0 873
48.2%
2 1
 
0.1%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1809
Missing (%)99.9%
Memory size14.3 KiB
2024-04-18T06:45:40.396871image/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%
2024-04-18T06:45:40.651769image/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>
1809 
20190501
 
1

Length

Max length8
Median length4
Mean length4.0022099
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> 1809
99.9%
20190501 1
 
0.1%

Length

2024-04-18T06:45:40.767345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:40.856423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1809
99.9%
20190501 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1809 
20210421
 
1

Length

Max length8
Median length4
Mean length4.0022099
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> 1809
99.9%
20210421 1
 
0.1%

Length

2024-04-18T06:45:40.957461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:41.053130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1809
99.9%
20210421 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1411 
자가
272 
임대
 
127

Length

Max length4
Median length4
Mean length3.559116
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1411
78.0%
자가 272
 
15.0%
임대 127
 
7.0%

Length

2024-04-18T06:45:41.154576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:41.248595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1411
78.0%
자가 272
 
15.0%
임대 127
 
7.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1196 
0
614 

Length

Max length4
Median length4
Mean length2.9823204
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1196
66.1%
0 614
33.9%

Length

2024-04-18T06:45:41.341111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:41.428924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1196
66.1%
0 614
33.9%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1762 
0
 
43
2
 
2
5
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.920442
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1762
97.3%
0 43
 
2.4%
2 2
 
0.1%
5 1
 
0.1%
3 1
 
0.1%
1 1
 
0.1%

Length

2024-04-18T06:45:41.526952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:41.644397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1762
97.3%
0 43
 
2.4%
2 2
 
0.1%
5 1
 
0.1%
3 1
 
0.1%
1 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1762 
0
 
43
1
 
3
5
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.920442
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1762
97.3%
0 43
 
2.4%
1 3
 
0.2%
5 1
 
0.1%
4 1
 
0.1%

Length

2024-04-18T06:45:41.751987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:41.873749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1762
97.3%
0 43
 
2.4%
1 3
 
0.2%
5 1
 
0.1%
4 1
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1223 
0
587 

Length

Max length4
Median length4
Mean length3.0270718
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1223
67.6%
0 587
32.4%

Length

2024-04-18T06:45:42.003583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:42.094720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1223
67.6%
0 587
32.4%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1224 
0
586 

Length

Max length4
Median length4
Mean length3.0287293
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1224
67.6%
0 586
32.4%

Length

2024-04-18T06:45:42.189680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:45:42.279204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1224
67.6%
0 586
32.4%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
False
1777 
True
 
33
ValueCountFrequency (%)
False 1777
98.2%
True 33
 
1.8%
2024-04-18T06:45:42.365042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1810
Missing (%)100.0%
Memory size16.0 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
01목욕장업11_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>
12목욕장업11_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>
23목욕장업11_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>
34목욕장업11_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>
45목욕장업11_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>
56목욕장업11_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>
67목욕장업11_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>
78목욕장업11_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>
89목욕장업11_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>
910목욕장업11_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>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
18001801목욕장업11_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>
18011802목욕장업11_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>
18021803목욕장업11_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>
18031804목욕장업11_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>
18041805목욕장업11_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>
18051806목욕장업11_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>
18061807목욕장업11_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)48976금강스파20200716105230U2020-07-18 02:40:00.0공동탕업+찜질시설서비스영업384542.121202179994.202104공동탕업+찜질시설서비스영업515511000N0<NA><NA><NA><NA>0<NA><NA>00Y<NA>
18071808목욕장업11_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>
18081809목욕장업11_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>
18091810목욕장업11_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>