Overview

Dataset statistics

Number of variables38
Number of observations885
Missing cells8083
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory283.6 KiB
Average record size in memory328.1 B

Variable types

Numeric11
Categorical14
Text5
Unsupported7
DateTime1

Dataset

Description2021-06-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123167

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
문화체육업종명 has constant value ""Constant
상세영업상태명 is highly imbalanced (52.9%)Imbalance
휴업시작일자 is highly imbalanced (98.4%)Imbalance
휴업종료일자 is highly imbalanced (98.4%)Imbalance
공사립구분명 is highly imbalanced (98.7%)Imbalance
보험가입여부코드 is highly imbalanced (63.8%)Imbalance
지도자수 is highly imbalanced (82.1%)Imbalance
건축물동수 is highly imbalanced (69.5%)Imbalance
회원모집총인원 is highly imbalanced (98.1%)Imbalance
인허가취소일자 has 885 (100.0%) missing valuesMissing
폐업일자 has 547 (61.8%) missing valuesMissing
재개업일자 has 885 (100.0%) missing valuesMissing
소재지전화 has 173 (19.5%) missing valuesMissing
소재지면적 has 885 (100.0%) missing valuesMissing
소재지우편번호 has 282 (31.9%) missing valuesMissing
소재지전체주소 has 15 (1.7%) missing valuesMissing
도로명전체주소 has 20 (2.3%) missing valuesMissing
도로명우편번호 has 307 (34.7%) missing valuesMissing
업태구분명 has 885 (100.0%) missing valuesMissing
좌표정보(x) has 9 (1.0%) missing valuesMissing
좌표정보(y) has 9 (1.0%) missing valuesMissing
건축물연면적 has 526 (59.4%) missing valuesMissing
세부업종명 has 885 (100.0%) missing valuesMissing
법인명 has 885 (100.0%) missing valuesMissing
Unnamed: 37 has 885 (100.0%) missing valuesMissing
번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
세부업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법인명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 37 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물연면적 has 9 (1.0%) zerosZeros

Reproduction

Analysis started2024-04-16 23:03:09.891559
Analysis finished2024-04-16 23:03:10.916741
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct885
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean443
Minimum1
Maximum885
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:10.976592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45.2
Q1222
median443
Q3664
95-th percentile840.8
Maximum885
Range884
Interquartile range (IQR)442

Descriptive statistics

Standard deviation255.62179
Coefficient of variation (CV)0.57702436
Kurtosis-1.2
Mean443
Median Absolute Deviation (MAD)221
Skewness0
Sum392055
Variance65342.5
MonotonicityStrictly increasing
2024-04-17T08:03:11.079903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
596 1
 
0.1%
585 1
 
0.1%
586 1
 
0.1%
587 1
 
0.1%
588 1
 
0.1%
589 1
 
0.1%
590 1
 
0.1%
591 1
 
0.1%
592 1
 
0.1%
Other values (875) 875
98.9%
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 (%)
885 1
0.1%
884 1
0.1%
883 1
0.1%
882 1
0.1%
881 1
0.1%
880 1
0.1%
879 1
0.1%
878 1
0.1%
877 1
0.1%
876 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
골프연습장업
885 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
골프연습장업 885
100.0%

Length

2024-04-17T08:03:11.173329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:11.244302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골프연습장업 885
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
10_31_01_P
885 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10_31_01_P
2nd row10_31_01_P
3rd row10_31_01_P
4th row10_31_01_P
5th row10_31_01_P

Common Values

ValueCountFrequency (%)
10_31_01_P 885
100.0%

Length

2024-04-17T08:03:11.316999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:11.388584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10_31_01_p 885
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3335604.5
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:11.472086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3262000
Q13300000
median3340000
Q33370000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation39416.008
Coefficient of variation (CV)0.011816751
Kurtosis-0.70372185
Mean3335604.5
Median Absolute Deviation (MAD)30000
Skewness-0.2236103
Sum2.95201 × 109
Variance1.5536217 × 109
MonotonicityNot monotonic
2024-04-17T08:03:11.567403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 125
14.1%
3340000 82
9.3%
3290000 70
 
7.9%
3300000 68
 
7.7%
3350000 67
 
7.6%
3370000 65
 
7.3%
3390000 63
 
7.1%
3380000 60
 
6.8%
3360000 54
 
6.1%
3400000 52
 
5.9%
Other values (6) 179
20.2%
ValueCountFrequency (%)
3250000 30
 
3.4%
3260000 15
 
1.7%
3270000 21
 
2.4%
3280000 18
 
2.0%
3290000 70
7.9%
3300000 68
7.7%
3310000 44
 
5.0%
3320000 51
5.8%
3330000 125
14.1%
3340000 82
9.3%
ValueCountFrequency (%)
3400000 52
5.9%
3390000 63
7.1%
3380000 60
6.8%
3370000 65
7.3%
3360000 54
6.1%
3350000 67
7.6%
3340000 82
9.3%
3330000 125
14.1%
3320000 51
5.8%
3310000 44
 
5.0%

관리번호
Text

Distinct179
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-04-17T08:03:11.736522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters17700
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)5.9%

Sample

1st rowCDFH3301052004000003
2nd rowCDFH3301052005000001
3rd rowCDFH3301051992000001
4th rowCDFH3301051996000001
5th rowCDFH3301051997000002
ValueCountFrequency (%)
cdfh3301052009000001 16
 
1.8%
cdfh3301052010000001 15
 
1.7%
cdfh3301052015000001 15
 
1.7%
cdfh3301052007000001 14
 
1.6%
cdfh3301052011000001 14
 
1.6%
cdfh3301052008000002 14
 
1.6%
cdfh3301052010000002 14
 
1.6%
cdfh3301052009000002 14
 
1.6%
cdfh3301052004000001 13
 
1.5%
cdfh3301052012000001 13
 
1.5%
Other values (169) 743
84.0%
2024-04-17T08:03:11.995961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7494
42.3%
3 1965
 
11.1%
1 1796
 
10.1%
2 1081
 
6.1%
5 1013
 
5.7%
C 885
 
5.0%
D 885
 
5.0%
F 885
 
5.0%
H 885
 
5.0%
9 268
 
1.5%
Other values (4) 543
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14160
80.0%
Uppercase Letter 3540
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7494
52.9%
3 1965
 
13.9%
1 1796
 
12.7%
2 1081
 
7.6%
5 1013
 
7.2%
9 268
 
1.9%
4 160
 
1.1%
8 149
 
1.1%
7 123
 
0.9%
6 111
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 885
25.0%
D 885
25.0%
F 885
25.0%
H 885
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14160
80.0%
Latin 3540
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7494
52.9%
3 1965
 
13.9%
1 1796
 
12.7%
2 1081
 
7.6%
5 1013
 
7.2%
9 268
 
1.9%
4 160
 
1.1%
8 149
 
1.1%
7 123
 
0.9%
6 111
 
0.8%
Latin
ValueCountFrequency (%)
C 885
25.0%
D 885
25.0%
F 885
25.0%
H 885
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7494
42.3%
3 1965
 
11.1%
1 1796
 
10.1%
2 1081
 
6.1%
5 1013
 
5.7%
C 885
 
5.0%
D 885
 
5.0%
F 885
 
5.0%
H 885
 
5.0%
9 268
 
1.5%
Other values (4) 543
 
3.1%

인허가일자
Real number (ℝ)

Distinct777
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20095628
Minimum19891201
Maximum20210324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:12.115653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19891201
5-th percentile19980340
Q120070420
median20100126
Q320140324
95-th percentile20190428
Maximum20210324
Range319123
Interquartile range (IQR)69904

Descriptive statistics

Standard deviation60488.399
Coefficient of variation (CV)0.0030100277
Kurtosis0.63411185
Mean20095628
Median Absolute Deviation (MAD)30798
Skewness-0.60795587
Sum1.7784631 × 1010
Variance3.6588464 × 109
MonotonicityNot monotonic
2024-04-17T08:03:12.226255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030203 9
 
1.0%
20161222 4
 
0.5%
20090513 3
 
0.3%
20080311 3
 
0.3%
20200109 3
 
0.3%
20100218 3
 
0.3%
20100813 3
 
0.3%
20100726 3
 
0.3%
20091106 3
 
0.3%
20100105 3
 
0.3%
Other values (767) 848
95.8%
ValueCountFrequency (%)
19891201 1
0.1%
19891208 1
0.1%
19891222 1
0.1%
19900103 1
0.1%
19900104 1
0.1%
19910531 1
0.1%
19910920 1
0.1%
19911221 1
0.1%
19920319 1
0.1%
19921112 1
0.1%
ValueCountFrequency (%)
20210324 1
0.1%
20210224 1
0.1%
20210129 2
0.2%
20201119 1
0.1%
20200915 1
0.1%
20200730 1
0.1%
20200707 1
0.1%
20200706 1
0.1%
20200603 1
0.1%
20200508 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing885
Missing (%)100.0%
Memory size7.9 KiB

영업상태구분코드
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
1
537 
3
302 
4
 
44
2
 
2

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 (%)
1 537
60.7%
3 302
34.1%
4 44
 
5.0%
2 2
 
0.2%

Length

2024-04-17T08:03:12.344979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:12.426373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 537
60.7%
3 302
34.1%
4 44
 
5.0%
2 2
 
0.2%

영업상태명
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
영업/정상
537 
폐업
302 
취소/말소/만료/정지/중지
 
44
휴업
 
2

Length

Max length14
Median length5
Mean length4.4169492
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 537
60.7%
폐업 302
34.1%
취소/말소/만료/정지/중지 44
 
5.0%
휴업 2
 
0.2%

Length

2024-04-17T08:03:12.534924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:12.618008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 537
60.7%
폐업 302
34.1%
취소/말소/만료/정지/중지 44
 
5.0%
휴업 2
 
0.2%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.650847
Minimum2
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:12.710011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median13
Q313
95-th percentile13
Maximum35
Range33
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.2641742
Coefficient of variation (CV)0.68202781
Kurtosis3.649913
Mean10.650847
Median Absolute Deviation (MAD)0
Skewness1.471898
Sum9426
Variance52.768226
MonotonicityNot monotonic
2024-04-17T08:03:12.794039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
13 537
60.7%
3 302
34.1%
35 42
 
4.7%
2 2
 
0.2%
32 1
 
0.1%
33 1
 
0.1%
ValueCountFrequency (%)
2 2
 
0.2%
3 302
34.1%
13 537
60.7%
32 1
 
0.1%
33 1
 
0.1%
35 42
 
4.7%
ValueCountFrequency (%)
35 42
 
4.7%
33 1
 
0.1%
32 1
 
0.1%
13 537
60.7%
3 302
34.1%
2 2
 
0.2%

상세영업상태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
영업중
537 
폐업
302 
직권말소
 
42
휴업
 
2
신고취소
 
1

Length

Max length4
Median length3
Mean length2.7062147
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 537
60.7%
폐업 302
34.1%
직권말소 42
 
4.7%
휴업 2
 
0.2%
신고취소 1
 
0.1%
지정취소 1
 
0.1%

Length

2024-04-17T08:03:12.895701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:12.991500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 537
60.7%
폐업 302
34.1%
직권말소 42
 
4.7%
휴업 2
 
0.2%
신고취소 1
 
0.1%
지정취소 1
 
0.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct290
Distinct (%)85.8%
Missing547
Missing (%)61.8%
Infinite0
Infinite (%)0.0%
Mean20142668
Minimum19991027
Maximum20210413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:13.103431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19991027
5-th percentile20051014
Q120110316
median20150709
Q320181204
95-th percentile20200641
Maximum20210413
Range219386
Interquartile range (IQR)70888

Descriptive statistics

Standard deviation47108.738
Coefficient of variation (CV)0.0023387537
Kurtosis-0.26528727
Mean20142668
Median Absolute Deviation (MAD)34992.5
Skewness-0.66090726
Sum6.8082217 × 109
Variance2.2192332 × 109
MonotonicityNot monotonic
2024-04-17T08:03:13.217291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20181204 11
 
1.2%
20190409 4
 
0.5%
20190416 3
 
0.3%
20170426 3
 
0.3%
20171213 3
 
0.3%
20130319 2
 
0.2%
20170308 2
 
0.2%
20181228 2
 
0.2%
20130620 2
 
0.2%
20140127 2
 
0.2%
Other values (280) 304
34.4%
(Missing) 547
61.8%
ValueCountFrequency (%)
19991027 1
0.1%
20010425 1
0.1%
20020727 1
0.1%
20021212 1
0.1%
20030625 1
0.1%
20030906 1
0.1%
20031017 1
0.1%
20031031 1
0.1%
20031231 1
0.1%
20040227 1
0.1%
ValueCountFrequency (%)
20210413 1
0.1%
20210309 1
0.1%
20210226 1
0.1%
20210223 1
0.1%
20210208 1
0.1%
20210126 1
0.1%
20210119 1
0.1%
20201216 1
0.1%
20201211 1
0.1%
20201125 1
0.1%

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
883 
20180808
 
1
20090701
 
1

Length

Max length8
Median length4
Mean length4.0090395
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 883
99.8%
20180808 1
 
0.1%
20090701 1
 
0.1%

Length

2024-04-17T08:03:13.322633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:13.410052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 883
99.8%
20180808 1
 
0.1%
20090701 1
 
0.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
883 
20190630
 
1
20110630
 
1

Length

Max length8
Median length4
Mean length4.0090395
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 883
99.8%
20190630 1
 
0.1%
20110630 1
 
0.1%

Length

2024-04-17T08:03:13.499862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:13.587532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 883
99.8%
20190630 1
 
0.1%
20110630 1
 
0.1%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing885
Missing (%)100.0%
Memory size7.9 KiB

소재지전화
Text

MISSING 

Distinct688
Distinct (%)96.6%
Missing173
Missing (%)19.5%
Memory size7.0 KiB
2024-04-17T08:03:13.797189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length10.108146
Min length5

Characters and Unicode

Total characters7197
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique664 ?
Unique (%)93.3%

Sample

1st row255-0707
2nd row466-4655
3rd row464-4171
4th row051-466-0969
5th row051-245-0155
ValueCountFrequency (%)
204-1160 2
 
0.3%
723-0794 2
 
0.3%
051 2
 
0.3%
756-5005 2
 
0.3%
051-508-9991 2
 
0.3%
529-1745 2
 
0.3%
051-202-0099 2
 
0.3%
266-8500 2
 
0.3%
724-7800 2
 
0.3%
051-720-9001 2
 
0.3%
Other values (681) 696
97.2%
2024-04-17T08:03:14.126158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1129
15.7%
- 1054
14.6%
5 953
13.2%
1 877
12.2%
7 625
8.7%
2 593
8.2%
3 485
6.7%
6 392
 
5.4%
4 380
 
5.3%
8 376
 
5.2%
Other values (5) 333
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6115
85.0%
Dash Punctuation 1054
 
14.6%
Close Punctuation 14
 
0.2%
Math Symbol 7
 
0.1%
Space Separator 4
 
0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1129
18.5%
5 953
15.6%
1 877
14.3%
7 625
10.2%
2 593
9.7%
3 485
7.9%
6 392
 
6.4%
4 380
 
6.2%
8 376
 
6.1%
9 305
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 1054
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7197
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1129
15.7%
- 1054
14.6%
5 953
13.2%
1 877
12.2%
7 625
8.7%
2 593
8.2%
3 485
6.7%
6 392
 
5.4%
4 380
 
5.3%
8 376
 
5.2%
Other values (5) 333
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1129
15.7%
- 1054
14.6%
5 953
13.2%
1 877
12.2%
7 625
8.7%
2 593
8.2%
3 485
6.7%
6 392
 
5.4%
4 380
 
5.3%
8 376
 
5.2%
Other values (5) 333
 
4.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing885
Missing (%)100.0%
Memory size7.9 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct312
Distinct (%)51.7%
Missing282
Missing (%)31.9%
Infinite0
Infinite (%)0.0%
Mean611283.12
Minimum600013
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:14.245507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600013
5-th percentile601837.2
Q1607824
median612020
Q3614801.5
95-th percentile619904.8
Maximum619963
Range19950
Interquartile range (IQR)6977.5

Descriptive statistics

Standard deviation5138.3977
Coefficient of variation (CV)0.008405921
Kurtosis-0.74806065
Mean611283.12
Median Absolute Deviation (MAD)4187
Skewness-0.22914925
Sum3.6860372 × 108
Variance26403130
MonotonicityNot monotonic
2024-04-17T08:03:14.352597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
616852 13
 
1.5%
619905 10
 
1.1%
619963 9
 
1.0%
611803 8
 
0.9%
604868 7
 
0.8%
612846 6
 
0.7%
613827 6
 
0.7%
613815 6
 
0.7%
611812 6
 
0.7%
612851 6
 
0.7%
Other values (302) 526
59.4%
(Missing) 282
31.9%
ValueCountFrequency (%)
600013 1
0.1%
600021 1
0.1%
600031 1
0.1%
600042 2
0.2%
600044 1
0.1%
600046 1
0.1%
600051 1
0.1%
600082 1
0.1%
600092 1
0.1%
600100 2
0.2%
ValueCountFrequency (%)
619963 9
1.0%
619962 1
 
0.1%
619961 4
 
0.5%
619952 1
 
0.1%
619951 1
 
0.1%
619913 1
 
0.1%
619912 3
 
0.3%
619906 1
 
0.1%
619905 10
1.1%
619903 1
 
0.1%

소재지전체주소
Text

MISSING 

Distinct827
Distinct (%)95.1%
Missing15
Missing (%)1.7%
Memory size7.0 KiB
2024-04-17T08:03:14.623015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length44
Mean length25.705747
Min length13

Characters and Unicode

Total characters22364
Distinct characters341
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique792 ?
Unique (%)91.0%

Sample

1st row부산광역시 중구 광복동1가 7번지
2nd row부산광역시 중구 중앙동4가 76-23번지
3rd row부산광역시 중구 중앙동4가 89-12번지
4th row부산광역시 중구 중앙동3가 9-5번지
5th row부산광역시 중구 대청동2가 34-1번지
ValueCountFrequency (%)
부산광역시 870
 
20.2%
해운대구 125
 
2.9%
사하구 79
 
1.8%
부산진구 70
 
1.6%
동래구 68
 
1.6%
금정구 67
 
1.6%
연제구 62
 
1.4%
사상구 61
 
1.4%
수영구 60
 
1.4%
북구 51
 
1.2%
Other values (1326) 2794
64.9%
2024-04-17T08:03:15.009939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3438
 
15.4%
1 1048
 
4.7%
산 1015
 
4.5%
부 1013
 
4.5%
동 977
 
4.4%
광 907
 
4.1%
시 890
 
4.0%
역 870
 
3.9%
구 849
 
3.8%
지 844
 
3.8%
Other values (331) 10513
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13290
59.4%
Decimal Number 4669
 
20.9%
Space Separator 3438
 
15.4%
Dash Punctuation 749
 
3.3%
Uppercase Letter 85
 
0.4%
Other Punctuation 78
 
0.3%
Open Punctuation 23
 
0.1%
Close Punctuation 22
 
0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 1015
 
7.6%
부 1013
 
7.6%
동 977
 
7.4%
광 907
 
6.8%
시 890
 
6.7%
역 870
 
6.5%
구 849
 
6.4%
지 844
 
6.4%
번 734
 
5.5%
층 250
 
1.9%
Other values (291) 4941
37.2%
Uppercase Letter
ValueCountFrequency (%)
B 30
35.3%
S 10
 
11.8%
C 7
 
8.2%
A 5
 
5.9%
K 5
 
5.9%
I 4
 
4.7%
D 3
 
3.5%
E 3
 
3.5%
Z 2
 
2.4%
W 2
 
2.4%
Other values (12) 14
16.5%
Decimal Number
ValueCountFrequency (%)
1 1048
22.4%
2 644
13.8%
3 538
11.5%
4 422
9.0%
0 410
 
8.8%
5 402
 
8.6%
7 343
 
7.3%
6 326
 
7.0%
8 275
 
5.9%
9 261
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 74
94.9%
/ 3
 
3.8%
& 1
 
1.3%
Space Separator
ValueCountFrequency (%)
3438
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 749
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13290
59.4%
Common 8989
40.2%
Latin 85
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 1015
 
7.6%
부 1013
 
7.6%
동 977
 
7.4%
광 907
 
6.8%
시 890
 
6.7%
역 870
 
6.5%
구 849
 
6.4%
지 844
 
6.4%
번 734
 
5.5%
층 250
 
1.9%
Other values (291) 4941
37.2%
Latin
ValueCountFrequency (%)
B 30
35.3%
S 10
 
11.8%
C 7
 
8.2%
A 5
 
5.9%
K 5
 
5.9%
I 4
 
4.7%
D 3
 
3.5%
E 3
 
3.5%
Z 2
 
2.4%
W 2
 
2.4%
Other values (12) 14
16.5%
Common
ValueCountFrequency (%)
3438
38.2%
1 1048
 
11.7%
- 749
 
8.3%
2 644
 
7.2%
3 538
 
6.0%
4 422
 
4.7%
0 410
 
4.6%
5 402
 
4.5%
7 343
 
3.8%
6 326
 
3.6%
Other values (8) 669
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13290
59.4%
ASCII 9074
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3438
37.9%
1 1048
 
11.5%
- 749
 
8.3%
2 644
 
7.1%
3 538
 
5.9%
4 422
 
4.7%
0 410
 
4.5%
5 402
 
4.4%
7 343
 
3.8%
6 326
 
3.6%
Other values (30) 754
 
8.3%
Hangul
ValueCountFrequency (%)
산 1015
 
7.6%
부 1013
 
7.6%
동 977
 
7.4%
광 907
 
6.8%
시 890
 
6.7%
역 870
 
6.5%
구 849
 
6.4%
지 844
 
6.4%
번 734
 
5.5%
층 250
 
1.9%
Other values (291) 4941
37.2%

도로명전체주소
Text

MISSING 

Distinct837
Distinct (%)96.8%
Missing20
Missing (%)2.3%
Memory size7.0 KiB
2024-04-17T08:03:15.300006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length50
Mean length31.408092
Min length19

Characters and Unicode

Total characters27168
Distinct characters382
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique813 ?
Unique (%)94.0%

Sample

1st row부산광역시 중구 광복로85번길 5-10 (광복동1가)
2nd row부산광역시 중구 중앙대로 148 (중앙동4가)
3rd row부산광역시 중구 충장대로5번길 5 (중앙동4가)
4th row부산광역시 중구 해관로 49 (중앙동3가)
5th row부산광역시 중구 광복중앙로 28-1 (대청동2가)
ValueCountFrequency (%)
부산광역시 865
 
16.9%
해운대구 123
 
2.4%
사하구 81
 
1.6%
부산진구 70
 
1.4%
금정구 66
 
1.3%
동래구 63
 
1.2%
연제구 63
 
1.2%
사상구 62
 
1.2%
수영구 58
 
1.1%
강서구 54
 
1.1%
Other values (1437) 3611
70.6%
2024-04-17T08:03:15.706239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4433
 
16.3%
동 1058
 
3.9%
산 1045
 
3.8%
부 1012
 
3.7%
광 936
 
3.4%
시 935
 
3.4%
역 865
 
3.2%
로 856
 
3.2%
구 850
 
3.1%
1 843
 
3.1%
Other values (372) 14335
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15966
58.8%
Space Separator 4433
 
16.3%
Decimal Number 4137
 
15.2%
Open Punctuation 834
 
3.1%
Close Punctuation 832
 
3.1%
Other Punctuation 780
 
2.9%
Dash Punctuation 85
 
0.3%
Uppercase Letter 81
 
0.3%
Math Symbol 17
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1058
 
6.6%
산 1045
 
6.5%
부 1012
 
6.3%
광 936
 
5.9%
시 935
 
5.9%
역 865
 
5.4%
로 856
 
5.4%
구 850
 
5.3%
대 506
 
3.2%
층 355
 
2.2%
Other values (332) 7548
47.3%
Uppercase Letter
ValueCountFrequency (%)
B 41
50.6%
S 8
 
9.9%
C 6
 
7.4%
K 5
 
6.2%
A 4
 
4.9%
I 3
 
3.7%
F 2
 
2.5%
Y 2
 
2.5%
L 1
 
1.2%
N 1
 
1.2%
Other values (8) 8
 
9.9%
Decimal Number
ValueCountFrequency (%)
1 843
20.4%
2 656
15.9%
3 474
11.5%
0 430
10.4%
4 413
10.0%
5 315
 
7.6%
6 287
 
6.9%
7 278
 
6.7%
9 225
 
5.4%
8 216
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 776
99.5%
& 2
 
0.3%
* 1
 
0.1%
/ 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 833
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 831
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4433
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15966
58.8%
Common 11118
40.9%
Latin 84
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1058
 
6.6%
산 1045
 
6.5%
부 1012
 
6.3%
광 936
 
5.9%
시 935
 
5.9%
역 865
 
5.4%
로 856
 
5.4%
구 850
 
5.3%
대 506
 
3.2%
층 355
 
2.2%
Other values (332) 7548
47.3%
Common
ValueCountFrequency (%)
4433
39.9%
1 843
 
7.6%
( 833
 
7.5%
) 831
 
7.5%
, 776
 
7.0%
2 656
 
5.9%
3 474
 
4.3%
0 430
 
3.9%
4 413
 
3.7%
5 315
 
2.8%
Other values (11) 1114
 
10.0%
Latin
ValueCountFrequency (%)
B 41
48.8%
S 8
 
9.5%
C 6
 
7.1%
K 5
 
6.0%
A 4
 
4.8%
I 3
 
3.6%
b 3
 
3.6%
F 2
 
2.4%
Y 2
 
2.4%
L 1
 
1.2%
Other values (9) 9
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15966
58.8%
ASCII 11202
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4433
39.6%
1 843
 
7.5%
( 833
 
7.4%
) 831
 
7.4%
, 776
 
6.9%
2 656
 
5.9%
3 474
 
4.2%
0 430
 
3.8%
4 413
 
3.7%
5 315
 
2.8%
Other values (30) 1198
 
10.7%
Hangul
ValueCountFrequency (%)
동 1058
 
6.6%
산 1045
 
6.5%
부 1012
 
6.3%
광 936
 
5.9%
시 935
 
5.9%
역 865
 
5.4%
로 856
 
5.4%
구 850
 
5.3%
대 506
 
3.2%
층 355
 
2.2%
Other values (332) 7548
47.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct402
Distinct (%)69.6%
Missing307
Missing (%)34.7%
Infinite0
Infinite (%)0.0%
Mean102247.42
Minimum46004
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:15.816238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46004
5-th percentile46054.55
Q146754
median47562.5
Q348531
95-th percentile612022.5
Maximum619963
Range573959
Interquartile range (IQR)1777

Descriptive statistics

Standard deviation167225.42
Coefficient of variation (CV)1.6354977
Kurtosis5.490379
Mean102247.42
Median Absolute Deviation (MAD)858
Skewness2.7330766
Sum59099007
Variance2.796434 × 1010
MonotonicityNot monotonic
2024-04-17T08:03:15.917875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46726 19
 
2.1%
46015 8
 
0.9%
46765 6
 
0.7%
46059 4
 
0.5%
46027 4
 
0.5%
46230 4
 
0.5%
46759 4
 
0.5%
46762 4
 
0.5%
47502 4
 
0.5%
46764 4
 
0.5%
Other values (392) 517
58.4%
(Missing) 307
34.7%
ValueCountFrequency (%)
46004 1
 
0.1%
46006 1
 
0.1%
46008 2
 
0.2%
46015 8
0.9%
46017 1
 
0.1%
46018 1
 
0.1%
46021 1
 
0.1%
46027 4
0.5%
46029 2
 
0.2%
46032 1
 
0.1%
ValueCountFrequency (%)
619963 2
0.2%
619952 1
0.1%
619905 2
0.2%
619903 1
0.1%
619901 1
0.1%
619871 1
0.1%
618814 1
0.1%
618290 1
0.1%
617846 2
0.2%
617829 1
0.1%

사업장명
Text

Distinct839
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-04-17T08:03:16.136801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length8.3740113
Min length2

Characters and Unicode

Total characters7411
Distinct characters431
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique798 ?
Unique (%)90.2%

Sample

1st row(주)이지알앤에스 실내골프연습장
2nd row리드 실내골프연습장
3rd row대원골프연습장
4th row중앙골프클럽
5th row광복실내골프연습장
ValueCountFrequency (%)
골프 54
 
4.4%
스크린골프 43
 
3.5%
스크린 36
 
2.9%
골프연습장 35
 
2.8%
골프아카데미 19
 
1.5%
골프존 14
 
1.1%
아카데미 12
 
1.0%
스크린골프연습장 10
 
0.8%
골프클럽 8
 
0.7%
실내골프연습장 5
 
0.4%
Other values (903) 993
80.8%
2024-04-17T08:03:16.459400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
프 802
 
10.8%
골 796
 
10.7%
스 524
 
7.1%
린 392
 
5.3%
크 381
 
5.1%
344
 
4.6%
장 273
 
3.7%
연 253
 
3.4%
습 242
 
3.3%
아 108
 
1.5%
Other values (421) 3296
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6531
88.1%
Space Separator 344
 
4.6%
Uppercase Letter 301
 
4.1%
Close Punctuation 57
 
0.8%
Open Punctuation 56
 
0.8%
Decimal Number 46
 
0.6%
Lowercase Letter 46
 
0.6%
Other Punctuation 26
 
0.4%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
프 802
 
12.3%
골 796
 
12.2%
스 524
 
8.0%
린 392
 
6.0%
크 381
 
5.8%
장 273
 
4.2%
연 253
 
3.9%
습 242
 
3.7%
아 108
 
1.7%
카 101
 
1.5%
Other values (358) 2659
40.7%
Uppercase Letter
ValueCountFrequency (%)
G 42
14.0%
S 28
 
9.3%
J 24
 
8.0%
K 22
 
7.3%
O 20
 
6.6%
P 18
 
6.0%
A 18
 
6.0%
M 15
 
5.0%
B 14
 
4.7%
R 12
 
4.0%
Other values (14) 88
29.2%
Lowercase Letter
ValueCountFrequency (%)
n 8
17.4%
o 6
13.0%
e 4
8.7%
s 4
8.7%
l 4
8.7%
i 3
 
6.5%
a 2
 
4.3%
y 2
 
4.3%
f 2
 
4.3%
r 2
 
4.3%
Other values (7) 9
19.6%
Decimal Number
ValueCountFrequency (%)
2 13
28.3%
5 6
13.0%
1 6
13.0%
7 6
13.0%
4 5
 
10.9%
0 4
 
8.7%
3 2
 
4.3%
6 2
 
4.3%
9 1
 
2.2%
8 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
& 13
50.0%
. 7
26.9%
' 2
 
7.7%
· 2
 
7.7%
＆ 1
 
3.8%
/ 1
 
3.8%
Space Separator
ValueCountFrequency (%)
344
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6531
88.1%
Common 532
 
7.2%
Latin 348
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
프 802
 
12.3%
골 796
 
12.2%
스 524
 
8.0%
린 392
 
6.0%
크 381
 
5.8%
장 273
 
4.2%
연 253
 
3.9%
습 242
 
3.7%
아 108
 
1.7%
카 101
 
1.5%
Other values (358) 2659
40.7%
Latin
ValueCountFrequency (%)
G 42
 
12.1%
S 28
 
8.0%
J 24
 
6.9%
K 22
 
6.3%
O 20
 
5.7%
P 18
 
5.2%
A 18
 
5.2%
M 15
 
4.3%
B 14
 
4.0%
R 12
 
3.4%
Other values (32) 135
38.8%
Common
ValueCountFrequency (%)
344
64.7%
) 57
 
10.7%
( 56
 
10.5%
2 13
 
2.4%
& 13
 
2.4%
. 7
 
1.3%
5 6
 
1.1%
1 6
 
1.1%
7 6
 
1.1%
4 5
 
0.9%
Other values (11) 19
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6531
88.1%
ASCII 876
 
11.8%
None 3
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
프 802
 
12.3%
골 796
 
12.2%
스 524
 
8.0%
린 392
 
6.0%
크 381
 
5.8%
장 273
 
4.2%
연 253
 
3.9%
습 242
 
3.7%
아 108
 
1.7%
카 101
 
1.5%
Other values (358) 2659
40.7%
ASCII
ValueCountFrequency (%)
344
39.3%
) 57
 
6.5%
( 56
 
6.4%
G 42
 
4.8%
S 28
 
3.2%
J 24
 
2.7%
K 22
 
2.5%
O 20
 
2.3%
P 18
 
2.1%
A 18
 
2.1%
Other values (50) 247
28.2%
None
ValueCountFrequency (%)
· 2
66.7%
＆ 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct885
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0165501 × 1013
Minimum2.0021227 × 1013
Maximum2.0210429 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:16.573216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0021227 × 1013
5-th percentile2.0090434 × 1013
Q12.0140529 × 1013
median2.0180712 × 1013
Q32.0200324 × 1013
95-th percentile2.0210223 × 1013
Maximum2.0210429 × 1013
Range1.8920199 × 1011
Interquartile range (IQR)5.9795 × 1010

Descriptive statistics

Standard deviation4.0392913 × 1010
Coefficient of variation (CV)0.0020030701
Kurtosis0.99006385
Mean2.0165501 × 1013
Median Absolute Deviation (MAD)2.0004939 × 1010
Skewness-1.1975978
Sum1.7846469 × 1016
Variance1.6315874 × 1021
MonotonicityNot monotonic
2024-04-17T08:03:16.692042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150608132227 1
 
0.1%
20121004095513 1
 
0.1%
20210428114550 1
 
0.1%
20140109174849 1
 
0.1%
20130404153416 1
 
0.1%
20110112164237 1
 
0.1%
20181018134005 1
 
0.1%
20131010091106 1
 
0.1%
20121217165649 1
 
0.1%
20130502112912 1
 
0.1%
Other values (875) 875
98.9%
ValueCountFrequency (%)
20021227103144 1
0.1%
20030109171150 1
0.1%
20030110141132 1
0.1%
20030203110210 1
0.1%
20030203110340 1
0.1%
20030203110518 1
0.1%
20030226104604 1
0.1%
20030331101637 1
0.1%
20030430175817 1
0.1%
20031017172247 1
0.1%
ValueCountFrequency (%)
20210429095044 1
0.1%
20210428114550 1
0.1%
20210423101644 1
0.1%
20210420113513 1
0.1%
20210420103457 1
0.1%
20210420090617 1
0.1%
20210419175841 1
0.1%
20210415154441 1
0.1%
20210408130837 1
0.1%
20210408120755 1
0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
I
483 
U
402 

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 483
54.6%
U 402
45.4%

Length

2024-04-17T08:03:16.791571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:17.115907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 483
54.6%
u 402
45.4%

데이터갱신일자
Date

Distinct237
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-01 02:40:00
2024-04-17T08:03:17.202332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T08:03:17.305983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing885
Missing (%)100.0%
Memory size7.9 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct723
Distinct (%)82.5%
Missing9
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean388021.24
Minimum366778.84
Maximum407507.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:17.416878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366778.84
5-th percentile375164.61
Q1383001.74
median388772.69
Q3392403.09
95-th percentile398323.2
Maximum407507.94
Range40729.102
Interquartile range (IQR)9401.3494

Descriptive statistics

Standard deviation6852.0388
Coefficient of variation (CV)0.017658927
Kurtosis-0.14591574
Mean388021.24
Median Absolute Deviation (MAD)4277.2836
Skewness-0.21074912
Sum3.3990661 × 108
Variance46950435
MonotonicityNot monotonic
2024-04-17T08:03:17.533820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
380751.85794394 4
 
0.5%
390057.531834683 4
 
0.5%
380540.836768886 4
 
0.5%
388772.690659798 4
 
0.5%
387686.194940483 3
 
0.3%
382952.600977025 3
 
0.3%
388281.182003521 3
 
0.3%
403054.577045169 3
 
0.3%
398024.244821605 3
 
0.3%
398218.09176136 3
 
0.3%
Other values (713) 842
95.1%
(Missing) 9
 
1.0%
ValueCountFrequency (%)
366778.837130241 1
0.1%
369062.766773096 1
0.1%
369082.163399585 1
0.1%
369100.736478994 1
0.1%
370993.074784655 1
0.1%
371070.269343027 1
0.1%
371173.79944234 2
0.2%
371178.823833358 1
0.1%
371343.929617089 1
0.1%
371362.0 1
0.1%
ValueCountFrequency (%)
407507.938658253 1
 
0.1%
404652.929281822 1
 
0.1%
403863.06017145 1
 
0.1%
403130.0 1
 
0.1%
403109.0 1
 
0.1%
403071.0 1
 
0.1%
403054.577045169 3
0.3%
401878.440381112 1
 
0.1%
401684.661779178 1
 
0.1%
401683.483048634 1
 
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct723
Distinct (%)82.5%
Missing9
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean187340.56
Minimum173968.57
Maximum207005.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:17.644094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173968.57
5-th percentile177553.83
Q1183238.52
median187339.53
Q3190755.05
95-th percentile197962.61
Maximum207005.49
Range33036.914
Interquartile range (IQR)7516.5293

Descriptive statistics

Standard deviation6489.627
Coefficient of variation (CV)0.034640802
Kurtosis0.17330714
Mean187340.56
Median Absolute Deviation (MAD)3653.406
Skewness0.35648693
Sum1.6411033 × 108
Variance42115259
MonotonicityNot monotonic
2024-04-17T08:03:17.753679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185656.488485036 4
 
0.5%
196950.450593302 4
 
0.5%
175274.144961403 4
 
0.5%
189846.311489648 4
 
0.5%
189911.430545728 3
 
0.3%
196461.739281708 3
 
0.3%
183760.229166657 3
 
0.3%
201007.435331934 3
 
0.3%
204621.655738547 3
 
0.3%
203994.563890741 3
 
0.3%
Other values (713) 842
95.1%
(Missing) 9
 
1.0%
ValueCountFrequency (%)
173968.574615591 1
0.1%
174009.639875441 1
0.1%
174035.700224564 1
0.1%
174068.494334685 1
0.1%
174209.665999624 2
0.2%
174289.976688419 2
0.2%
174403.0 1
0.1%
174676.412428464 1
0.1%
174978.46447201 1
0.1%
175237.529203319 1
0.1%
ValueCountFrequency (%)
207005.48875144 1
0.1%
206047.415761754 1
0.1%
206042.801652498 1
0.1%
205722.852692375 1
0.1%
205555.974594837 1
0.1%
205277.845892938 1
0.1%
204874.624668269 1
0.1%
204794.968858 1
0.1%
204769.0 1
0.1%
204712.0 1
0.1%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
골프연습장업
885 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
골프연습장업 885
100.0%

Length

2024-04-17T08:03:17.864789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:17.937989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골프연습장업 885
100.0%

공사립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
사립
884 
공립
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
사립 884
99.9%
공립 1
 
0.1%

Length

2024-04-17T08:03:18.014265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:18.100453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 884
99.9%
공립 1
 
0.1%

보험가입여부코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
759 
0
88 
Y
 
37
1
 
1

Length

Max length4
Median length4
Mean length3.5728814
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 759
85.8%
0 88
 
9.9%
Y 37
 
4.2%
1 1
 
0.1%

Length

2024-04-17T08:03:18.185024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:18.275113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 759
85.8%
0 88
 
9.9%
y 37
 
4.2%
1 1
 
0.1%

지도자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
827 
1
 
44
2
 
11
3
 
2
0
 
1

Length

Max length4
Median length4
Mean length3.8033898
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> 827
93.4%
1 44
 
5.0%
2 11
 
1.2%
3 2
 
0.2%
0 1
 
0.1%

Length

2024-04-17T08:03:18.386271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:18.495497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 827
93.4%
1 44
 
5.0%
2 11
 
1.2%
3 2
 
0.2%
0 1
 
0.1%

건축물동수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
732 
1
135 
0
 
7
2
 
7
5
 
3

Length

Max length4
Median length4
Mean length3.4813559
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> 732
82.7%
1 135
 
15.3%
0 7
 
0.8%
2 7
 
0.8%
5 3
 
0.3%
4 1
 
0.1%

Length

2024-04-17T08:03:18.597997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:18.698512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 732
82.7%
1 135
 
15.3%
0 7
 
0.8%
2 7
 
0.8%
5 3
 
0.3%
4 1
 
0.1%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct337
Distinct (%)93.9%
Missing526
Missing (%)59.4%
Infinite0
Infinite (%)0.0%
Mean5594.2729
Minimum0
Maximum143479.19
Zeros9
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-04-17T08:03:18.796436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile171.811
Q1622.225
median1967.27
Q34508.58
95-th percentile22759.34
Maximum143479.19
Range143479.19
Interquartile range (IQR)3886.355

Descriptive statistics

Standard deviation14115.498
Coefficient of variation (CV)2.523205
Kurtosis52.95997
Mean5594.2729
Median Absolute Deviation (MAD)1573.94
Skewness6.6285994
Sum2008344
Variance1.9924727 × 108
MonotonicityNot monotonic
2024-04-17T08:03:18.909767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9
 
1.0%
2470.42 3
 
0.3%
2434.08 3
 
0.3%
2671.21 2
 
0.2%
1301.44 2
 
0.2%
3772.26 2
 
0.2%
2096.03 2
 
0.2%
4274.22 2
 
0.2%
5718.42 2
 
0.2%
31854.3 2
 
0.2%
Other values (327) 330
37.3%
(Missing) 526
59.4%
ValueCountFrequency (%)
0.0 9
1.0%
0.1 1
 
0.1%
36.32 1
 
0.1%
96.99 1
 
0.1%
128.8 1
 
0.1%
138.29 1
 
0.1%
140.0 1
 
0.1%
145.2 1
 
0.1%
147.45 1
 
0.1%
159.67 1
 
0.1%
ValueCountFrequency (%)
143479.19 1
0.1%
129000.0 1
0.1%
116942.0 1
0.1%
64681.13 1
0.1%
55054.37 1
0.1%
54329.0 1
0.1%
52382.0 1
0.1%
43141.69 1
0.1%
40596.23 1
0.1%
35212.21 1
0.1%

회원모집총인원
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
882 
300
 
1
70
 
1
400
 
1

Length

Max length4
Median length4
Mean length3.9954802
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 882
99.7%
300 1
 
0.1%
70 1
 
0.1%
400 1
 
0.1%

Length

2024-04-17T08:03:19.019194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:03:19.110013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 882
99.7%
300 1
 
0.1%
70 1
 
0.1%
400 1
 
0.1%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing885
Missing (%)100.0%
Memory size7.9 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing885
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 37
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing885
Missing (%)100.0%
Memory size7.9 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명Unnamed: 37
01골프연습장업10_31_01_P3250000CDFH330105200400000320040811<NA>3폐업3폐업20150608<NA><NA><NA>255-0707<NA>600031부산광역시 중구 광복동1가 7번지부산광역시 중구 광복로85번길 5-10 (광복동1가)<NA>(주)이지알앤에스 실내골프연습장20150608132227I2018-08-31 23:59:59.0<NA>385386.063275179669.736313골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
12골프연습장업10_31_01_P3250000CDFH330105200500000120050328<NA>3폐업3폐업20070605<NA><NA><NA>466-4655<NA>600816부산광역시 중구 중앙동4가 76-23번지부산광역시 중구 중앙대로 148 (중앙동4가)<NA>리드 실내골프연습장20070605140559I2018-08-31 23:59:59.0<NA>385735.140512180956.485998골프연습장업사립0<NA><NA><NA><NA><NA><NA><NA>
23골프연습장업10_31_01_P3250000CDFH330105199200000119921123<NA>3폐업3폐업20130103<NA><NA><NA>464-4171<NA>600814부산광역시 중구 중앙동4가 89-12번지부산광역시 중구 충장대로5번길 5 (중앙동4가)<NA>대원골프연습장20130103111523I2018-08-31 23:59:59.0<NA>385635.996084180419.418144골프연습장업사립<NA><NA><NA>145.2<NA><NA><NA><NA>
34골프연습장업10_31_01_P3250000CDFH330105199600000119960502<NA>3폐업3폐업20100112<NA><NA><NA>051-466-0969<NA>600013부산광역시 중구 중앙동3가 9-5번지부산광역시 중구 해관로 49 (중앙동3가)<NA>중앙골프클럽20100112151009I2018-08-31 23:59:59.0<NA>385514.650537180140.244867골프연습장업사립0<NA><NA>214.0<NA><NA><NA><NA>
45골프연습장업10_31_01_P3250000CDFH330105199700000219971211<NA>3폐업3폐업20020727<NA><NA><NA>051-245-0155<NA>600092부산광역시 중구 대청동2가 34-1번지부산광역시 중구 광복중앙로 28-1 (대청동2가)<NA>광복실내골프연습장20040727102048I2018-08-31 23:59:59.0<NA>385126.032162179976.116994골프연습장업사립0<NA><NA><NA><NA><NA><NA><NA>
56골프연습장업10_31_01_P3250000CDFH330105200300000120030305<NA>3폐업3폐업20040228<NA><NA><NA>051-463-1100<NA>600100부산광역시 중구 대창동2가 36-5번지부산광역시 중구 중앙대로 133 (대창동2가)<NA>포시즌 골프연습장20040709121811I2018-08-31 23:59:59.0<NA>385634.524592180842.542511골프연습장업사립0<NA><NA><NA><NA><NA><NA><NA>
67골프연습장업10_31_01_P3250000CDFH330105201400000320140508<NA>3폐업3폐업20191029<NA><NA><NA>051-246-0717<NA>600042부산광역시 중구 남포동2가 25-10번지부산광역시 중구 구덕로34번길 4 (남포동2가)48954광복스크린20191029175001U2019-10-31 02:40:00.0<NA>385243.158544179580.295176골프연습장업사립<NA><NA><NA>8245.54<NA><NA><NA><NA>
78골프연습장업10_31_01_P3250000CDFH330105201500000120150102<NA>3폐업3폐업20191213<NA><NA><NA>1899-6569<NA>600051부산광역시 중구 창선동1가 12-1번지부산광역시 중구 광복로39번길 6 (창선동1가)48947제임스짐(JAMESGYM)20191213112332U2019-12-15 02:40:00.0<NA>384993.660073179733.755299골프연습장업사립<NA>3<NA>16057.0<NA><NA><NA><NA>
89골프연습장업10_31_01_P3250000CDFH330105200700000220070508<NA>3폐업3폐업20100108<NA><NA><NA>463-4700<NA>600100부산광역시 중구 대창동1가 23-13번지부산광역시 중구 중앙대로 129 (대창동1가)<NA>스카이 골프20100108105017I2018-08-31 23:59:59.0<NA>385629.342278180803.857906골프연습장업사립0<NA><NA><NA><NA><NA><NA><NA>
910골프연습장업10_31_01_P3250000CDFH330105200900000120090429<NA>3폐업3폐업20130114<NA><NA><NA>247-2323<NA>600044부산광역시 중구 남포동4가 37-1번지부산광역시 중구 자갈치해안로 52 (남포동4가)<NA>비치골프클럽20130114093207I2018-08-31 23:59:59.0<NA>385139.215952179403.007902골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명Unnamed: 37
875876골프연습장업10_31_01_P3330000CDFH330105200400000220040330<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA>051-704-8799<NA>612843부산광역시 해운대구 좌동 1443-6번지 한창프라자 3층부산광역시 해운대구 좌동순환로 307-1 (좌동,한창프라자 3층)<NA>Lee골프클리닉20181204132351U2019-05-10 02:40:00.0<NA>398835.47776187666.142752골프연습장업사립<NA><NA><NA>320.87<NA><NA><NA><NA>
876877골프연습장업10_31_01_P3330000CDFH330105200500000220050129<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA>051-742-3456<NA>612846부산광역시 해운대구 중동 940-3번지부산광역시 해운대구 달맞이길62번길 3 (중동)<NA>해운대골프아카데미20181204110423U2018-12-06 02:40:00.0<NA>397783.088647186778.584045골프연습장업사립<NA><NA><NA>270.39<NA><NA><NA><NA>
877878골프연습장업10_31_01_P3330000CDFH330105200700000520070516<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA>051-702-5577<NA>612862부산광역시 해운대구 좌동 1429-1번지 501호부산광역시 해운대구 좌동로 152, 501호 (좌동)<NA>알바트로스 클럽20181204132204U2018-12-06 02:40:00.0<NA>398628.50347188364.542637골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
878879골프연습장업10_31_01_P3330000CDFH330105200800000320080125<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA>051-744-0911<NA>612824부산광역시 해운대구 우동 1434번지부산광역시 해운대구 마린시티3로 1 (우동)<NA>썬프라자골프연습장20181204110538U2018-12-06 02:40:00.0<NA>395615.201854186406.750871골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
879880골프연습장업10_31_01_P3330000CDFH330105201200000320120418<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA>703-7222<NA>612836부산광역시 해운대구 좌동 1459-6번지 자생메디컬타워 B101호부산광역시 해운대구 해운대로 793, B101호 (좌동, 자생메디컬타워)48102(주)나눔FNC20181204132622U2019-05-10 02:40:00.0<NA>398107.089978187767.70283골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
880881골프연습장업10_31_01_P3330000CDFH330105200800000820080311<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA>051-783-1800<NA>612833부산광역시 해운대구 재송동 1129-1번지부산광역시 해운대구 재반로112번길 14 (재송동)<NA>장산스크린골프20181204132040U2018-12-06 02:40:00.0<NA>393747.234162189760.397963골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
881882골프연습장업10_31_01_P3330000CDFH330105201000000720100726<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA><NA><NA>612874부산광역시 해운대구 우동 1507번지 트럼프월드센텀2 상가401호부산광역시 해운대구 센텀3로 32 (우동,트럼프월드센텀2 상가401호)<NA>액티브짐20181204131034U2018-12-06 02:40:00.0<NA>394340.42655187360.76946골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
882883골프연습장업10_31_01_P3330000CDFH330105200900000420090429<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA><NA><NA>612849부산광역시 해운대구 중동 1489-4번지부산광역시 해운대구 달맞이길 193 (중동)48115오션뷰 스크린 골프연습장20181204105833U2018-12-06 02:40:00.0<NA>398794.494655186552.868898골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
883884골프연습장업10_31_01_P3330000CDFH330105200900001520091208<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA><NA><NA>612020부산광역시 해운대구 우동 1484번지부산광역시 해운대구 센텀동로 26 (우동)<NA>스마일휘트니스센터20181204131145U2018-12-06 02:40:00.0<NA>394205.564135187948.534671골프연습장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
884885골프연습장업10_31_01_P3330000CDFH330105200400000120040309<NA>4취소/말소/만료/정지/중지35직권말소20181204<NA><NA><NA>051-703-7701<NA>612842부산광역시 해운대구 좌동 1483-2번지 노블시티5층부산광역시 해운대구 세실로27번길 15 (좌동,노블시티5층)<NA>PGA실내골프연습장20181204115658U2018-12-06 02:40:00.0<NA>398385.316332187615.739745골프연습장업사립<NA><NA><NA>376.6<NA><NA><NA><NA>