Overview

Dataset statistics

Number of variables39
Number of observations1188
Missing cells11036
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory394.6 KiB
Average record size in memory340.1 B

Variable types

Numeric14
Categorical12
Text5
Unsupported7
DateTime1

Dataset

Description2022-04-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123010

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
시력표수 is highly imbalanced (63.9%)Imbalance
표본렌즈수 is highly imbalanced (58.1%)Imbalance
정점굴절계기수 is highly imbalanced (51.1%)Imbalance
조제용연마기수 is highly imbalanced (54.1%)Imbalance
렌즈절단기수 is highly imbalanced (55.9%)Imbalance
인허가취소일자 has 1188 (100.0%) missing valuesMissing
폐업일자 has 782 (65.8%) missing valuesMissing
휴업시작일자 has 1188 (100.0%) missing valuesMissing
휴업종료일자 has 1188 (100.0%) missing valuesMissing
재개업일자 has 1188 (100.0%) missing valuesMissing
소재지전화 has 181 (15.2%) missing valuesMissing
소재지면적 has 1188 (100.0%) missing valuesMissing
소재지우편번호 has 513 (43.2%) missing valuesMissing
소재지전체주소 has 104 (8.8%) missing valuesMissing
도로명전체주소 has 82 (6.9%) missing valuesMissing
도로명우편번호 has 256 (21.5%) missing valuesMissing
업태구분명 has 1188 (100.0%) missing valuesMissing
좌표정보(x) has 80 (6.7%) missing valuesMissing
좌표정보(y) has 80 (6.7%) missing valuesMissing
측정의자수 has 44 (3.7%) missing valuesMissing
가열기수 has 48 (4.0%) missing valuesMissing
안경세척기수 has 47 (4.0%) missing valuesMissing
총면적 has 498 (41.9%) missing valuesMissing
Unnamed: 38 has 1188 (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
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
Unnamed: 38 is an unsupported type, check if it needs cleaning or further analysisUnsupported
측정의자수 has 209 (17.6%) zerosZeros
동공거리측정기수 has 174 (14.6%) zerosZeros
가열기수 has 210 (17.7%) zerosZeros
안경세척기수 has 209 (17.6%) zerosZeros
총면적 has 79 (6.6%) zerosZeros

Reproduction

Analysis started2024-04-21 10:34:13.207752
Analysis finished2024-04-21 10:34:14.589573
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1188
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean594.5
Minimum1
Maximum1188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:14.783022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile60.35
Q1297.75
median594.5
Q3891.25
95-th percentile1128.65
Maximum1188
Range1187
Interquartile range (IQR)593.5

Descriptive statistics

Standard deviation343.09037
Coefficient of variation (CV)0.57710743
Kurtosis-1.2
Mean594.5
Median Absolute Deviation (MAD)297
Skewness0
Sum706266
Variance117711
MonotonicityStrictly increasing
2024-04-21T19:34:15.221738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
800 1
 
0.1%
798 1
 
0.1%
797 1
 
0.1%
796 1
 
0.1%
795 1
 
0.1%
794 1
 
0.1%
793 1
 
0.1%
792 1
 
0.1%
791 1
 
0.1%
Other values (1178) 1178
99.2%
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 (%)
1188 1
0.1%
1187 1
0.1%
1186 1
0.1%
1185 1
0.1%
1184 1
0.1%
1183 1
0.1%
1182 1
0.1%
1181 1
0.1%
1180 1
0.1%
1179 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
안경업
1188 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안경업 1188
100.0%

Length

2024-04-21T19:34:15.639150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:15.932000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안경업 1188
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
01_02_01_P
1188 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01_02_01_P
2nd row01_02_01_P
3rd row01_02_01_P
4th row01_02_01_P
5th row01_02_01_P

Common Values

ValueCountFrequency (%)
01_02_01_P 1188
100.0%

Length

2024-04-21T19:34:16.232911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:16.390152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_02_01_p 1188
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325033.7
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:16.540894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation39851.226
Coefficient of variation (CV)0.01198521
Kurtosis-0.74230071
Mean3325033.7
Median Absolute Deviation (MAD)30000
Skewness-0.050247516
Sum3.95014 × 109
Variance1.5881202 × 109
MonotonicityIncreasing
2024-04-21T19:34:16.745854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 177
14.9%
3290000 148
12.5%
3310000 115
9.7%
3330000 102
8.6%
3340000 93
7.8%
3300000 90
7.6%
3250000 80
6.7%
3390000 68
 
5.7%
3320000 65
 
5.5%
3370000 65
 
5.5%
Other values (6) 185
15.6%
ValueCountFrequency (%)
3250000 80
6.7%
3260000 23
 
1.9%
3270000 29
 
2.4%
3280000 27
 
2.3%
3290000 148
12.5%
3300000 90
7.6%
3310000 115
9.7%
3320000 65
5.5%
3330000 102
8.6%
3340000 93
7.8%
ValueCountFrequency (%)
3400000 35
 
2.9%
3390000 68
 
5.7%
3380000 52
 
4.4%
3370000 65
 
5.5%
3360000 19
 
1.6%
3350000 177
14.9%
3340000 93
7.8%
3330000 102
8.6%
3320000 65
 
5.5%
3310000 115
9.7%

관리번호
Text

UNIQUE 

Distinct1188
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2024-04-21T19:34:17.386924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters29700
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

Unique1188 ?
Unique (%)100.0%

Sample

1st rowPHMB220183250021082200001
2nd rowPHMB220103250021082200001
3rd rowPHMB219933250021082200001
4th rowPHMB220103250021082200006
5th rowPHMB220143250021082200001
ValueCountFrequency (%)
phmb220183250021082200001 1
 
0.1%
phmb219933350024082200001 1
 
0.1%
phmb219923350024082200002 1
 
0.1%
phmb219783350024082200001 1
 
0.1%
phmb219863350024082200004 1
 
0.1%
phmb219863350024082200003 1
 
0.1%
phmb219883350024082200002 1
 
0.1%
phmb219853350024082200002 1
 
0.1%
phmb220083350024082200001 1
 
0.1%
phmb220073350024082200002 1
 
0.1%
Other values (1178) 1178
99.2%
2024-04-21T19:34:18.231208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9710
32.7%
2 6384
21.5%
3 2601
 
8.8%
1 1629
 
5.5%
8 1522
 
5.1%
P 1188
 
4.0%
H 1188
 
4.0%
M 1188
 
4.0%
B 1188
 
4.0%
4 1057
 
3.6%
Other values (4) 2045
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24948
84.0%
Uppercase Letter 4752
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9710
38.9%
2 6384
25.6%
3 2601
 
10.4%
1 1629
 
6.5%
8 1522
 
6.1%
4 1057
 
4.2%
9 978
 
3.9%
5 595
 
2.4%
7 255
 
1.0%
6 217
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P 1188
25.0%
H 1188
25.0%
M 1188
25.0%
B 1188
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24948
84.0%
Latin 4752
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9710
38.9%
2 6384
25.6%
3 2601
 
10.4%
1 1629
 
6.5%
8 1522
 
6.1%
4 1057
 
4.2%
9 978
 
3.9%
5 595
 
2.4%
7 255
 
1.0%
6 217
 
0.9%
Latin
ValueCountFrequency (%)
P 1188
25.0%
H 1188
25.0%
M 1188
25.0%
B 1188
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9710
32.7%
2 6384
21.5%
3 2601
 
8.8%
1 1629
 
5.5%
8 1522
 
5.1%
P 1188
 
4.0%
H 1188
 
4.0%
M 1188
 
4.0%
B 1188
 
4.0%
4 1057
 
3.6%
Other values (4) 2045
 
6.9%

인허가일자
Real number (ℝ)

Distinct1089
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20042740
Minimum19710518
Maximum20220228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:18.484134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19710518
5-th percentile19850616
Q119960422
median20060414
Q320133445
95-th percentile20200913
Maximum20220228
Range509710
Interquartile range (IQR)173022.5

Descriptive statistics

Standard deviation111011.29
Coefficient of variation (CV)0.0055387282
Kurtosis-0.76148951
Mean20042740
Median Absolute Deviation (MAD)80805.5
Skewness-0.39846
Sum2.3810775 × 1010
Variance1.2323506 × 1010
MonotonicityNot monotonic
2024-04-21T19:34:18.752491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19910628 12
 
1.0%
19901119 5
 
0.4%
20000908 3
 
0.3%
20150731 3
 
0.3%
20210823 2
 
0.2%
20210104 2
 
0.2%
19910724 2
 
0.2%
20140416 2
 
0.2%
20020326 2
 
0.2%
20001004 2
 
0.2%
Other values (1079) 1153
97.1%
ValueCountFrequency (%)
19710518 1
0.1%
19750813 1
0.1%
19751230 1
0.1%
19770602 1
0.1%
19780306 1
0.1%
19780419 1
0.1%
19780711 1
0.1%
19780812 1
0.1%
19780825 1
0.1%
19781027 1
0.1%
ValueCountFrequency (%)
20220228 1
0.1%
20220223 1
0.1%
20220203 1
0.1%
20220120 1
0.1%
20220114 1
0.1%
20211227 1
0.1%
20211216 1
0.1%
20211206 1
0.1%
20211130 2
0.2%
20211123 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1188
Missing (%)100.0%
Memory size10.6 KiB
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
1
762 
3
418 
4
 
8

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 (%)
1 762
64.1%
3 418
35.2%
4 8
 
0.7%

Length

2024-04-21T19:34:18.988995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:19.156261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 762
64.1%
3 418
35.2%
4 8
 
0.7%

영업상태명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
영업/정상
762 
폐업
418 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length4.0050505
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 762
64.1%
폐업 418
35.2%
취소/말소/만료/정지/중지 8
 
0.7%

Length

2024-04-21T19:34:19.347753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:19.524381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 762
64.1%
폐업 418
35.2%
취소/말소/만료/정지/중지 8
 
0.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
13
762 
3
418 
24
 
8

Length

Max length2
Median length2
Mean length1.6481481
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 762
64.1%
3 418
35.2%
24 8
 
0.7%

Length

2024-04-21T19:34:19.709460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:19.878074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 762
64.1%
3 418
35.2%
24 8
 
0.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
영업중
762 
폐업
418 
직권폐업
 
8

Length

Max length4
Median length3
Mean length2.6548822
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 762
64.1%
폐업 418
35.2%
직권폐업 8
 
0.7%

Length

2024-04-21T19:34:20.076350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:20.261712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 762
64.1%
폐업 418
35.2%
직권폐업 8
 
0.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct377
Distinct (%)92.9%
Missing782
Missing (%)65.8%
Infinite0
Infinite (%)0.0%
Mean20104857
Minimum19851128
Maximum20220218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:20.465211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19851128
5-th percentile19923367
Q120081038
median20120457
Q320177886
95-th percentile20210528
Maximum20220218
Range369090
Interquartile range (IQR)96848

Descriptive statistics

Standard deviation87374.882
Coefficient of variation (CV)0.0043459588
Kurtosis-0.23176611
Mean20104857
Median Absolute Deviation (MAD)50471
Skewness-0.86780799
Sum8.162572 × 109
Variance7.6343699 × 109
MonotonicityNot monotonic
2024-04-21T19:34:20.729905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110303 3
 
0.3%
20110211 2
 
0.2%
20140602 2
 
0.2%
20180115 2
 
0.2%
20111130 2
 
0.2%
20100803 2
 
0.2%
20091028 2
 
0.2%
20110131 2
 
0.2%
19951109 2
 
0.2%
20110216 2
 
0.2%
Other values (367) 385
32.4%
(Missing) 782
65.8%
ValueCountFrequency (%)
19851128 1
0.1%
19900226 1
0.1%
19900507 1
0.1%
19900514 1
0.1%
19900927 1
0.1%
19901128 1
0.1%
19910122 1
0.1%
19910314 1
0.1%
19910406 2
0.2%
19910531 2
0.2%
ValueCountFrequency (%)
20220218 1
0.1%
20211230 1
0.1%
20211130 1
0.1%
20211126 1
0.1%
20211105 1
0.1%
20211022 1
0.1%
20211021 1
0.1%
20211014 1
0.1%
20210825 1
0.1%
20210820 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1188
Missing (%)100.0%
Memory size10.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1188
Missing (%)100.0%
Memory size10.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1188
Missing (%)100.0%
Memory size10.6 KiB

소재지전화
Text

MISSING 

Distinct951
Distinct (%)94.4%
Missing181
Missing (%)15.2%
Memory size9.4 KiB
2024-04-21T19:34:21.513453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.294935
Min length7

Characters and Unicode

Total characters11374
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique903 ?
Unique (%)89.7%

Sample

1st row2531216
2nd row070-4116-2770
3rd row051-253-1216
4th row051-246-0006
5th row051-245-1999
ValueCountFrequency (%)
051-808-7088 4
 
0.4%
261-6700 3
 
0.3%
051-337-7111 3
 
0.3%
051-816-4500 3
 
0.3%
051-625-8471 3
 
0.3%
051-623-7778 3
 
0.3%
051-647-5766 3
 
0.3%
051-302-2495 2
 
0.2%
051-257-7090 2
 
0.2%
051-625-8086 2
 
0.2%
Other values (941) 979
97.2%
2024-04-21T19:34:22.521857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1770
15.6%
0 1728
15.2%
5 1587
14.0%
1 1575
13.8%
2 858
7.5%
8 705
 
6.2%
6 699
 
6.1%
7 695
 
6.1%
3 692
 
6.1%
4 630
 
5.5%
Other values (4) 435
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9561
84.1%
Dash Punctuation 1770
 
15.6%
Close Punctuation 39
 
0.3%
Math Symbol 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1728
18.1%
5 1587
16.6%
1 1575
16.5%
2 858
9.0%
8 705
7.4%
6 699
7.3%
7 695
7.3%
3 692
7.2%
4 630
 
6.6%
9 392
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 1770
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11374
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1770
15.6%
0 1728
15.2%
5 1587
14.0%
1 1575
13.8%
2 858
7.5%
8 705
 
6.2%
6 699
 
6.1%
7 695
 
6.1%
3 692
 
6.1%
4 630
 
5.5%
Other values (4) 435
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1770
15.6%
0 1728
15.2%
5 1587
14.0%
1 1575
13.8%
2 858
7.5%
8 705
 
6.2%
6 699
 
6.1%
7 695
 
6.1%
3 692
 
6.1%
4 630
 
5.5%
Other values (4) 435
 
3.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1188
Missing (%)100.0%
Memory size10.6 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct340
Distinct (%)50.4%
Missing513
Missing (%)43.2%
Infinite0
Infinite (%)0.0%
Mean608141.65
Minimum48272
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:22.758192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48272
5-th percentile601812
Q1607832
median609839
Q3614041.5
95-th percentile617296.7
Maximum619963
Range571691
Interquartile range (IQR)6209.5

Descriptive statistics

Standard deviation37696.382
Coefficient of variation (CV)0.061986188
Kurtosis214.98154
Mean608141.65
Median Absolute Deviation (MAD)3968
Skewness-14.596712
Sum4.1049561 × 108
Variance1.4210172 × 109
MonotonicityNot monotonic
2024-04-21T19:34:22.994760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
609839 33
 
2.8%
614845 8
 
0.7%
609834 8
 
0.7%
616852 7
 
0.6%
608805 7
 
0.6%
609800 7
 
0.6%
614030 7
 
0.6%
611089 7
 
0.6%
609822 7
 
0.6%
611082 6
 
0.5%
Other values (330) 578
48.7%
(Missing) 513
43.2%
ValueCountFrequency (%)
48272 1
 
0.1%
48296 1
 
0.1%
49247 1
 
0.1%
600016 1
 
0.1%
600017 1
 
0.1%
600031 2
0.2%
600032 3
0.3%
600042 1
 
0.1%
600045 1
 
0.1%
600052 1
 
0.1%
ValueCountFrequency (%)
619963 6
0.5%
619961 1
 
0.1%
619912 2
 
0.2%
619905 5
0.4%
619903 4
0.3%
618814 2
 
0.2%
618807 1
 
0.1%
617846 2
 
0.2%
617833 1
 
0.1%
617830 1
 
0.1%

소재지전체주소
Text

MISSING 

Distinct1031
Distinct (%)95.1%
Missing104
Missing (%)8.8%
Memory size9.4 KiB
2024-04-21T19:34:24.194773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length24.133764
Min length3

Characters and Unicode

Total characters26161
Distinct characters313
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

Unique983 ?
Unique (%)90.7%

Sample

1st row부산광역시 중구 창선동2가 24번지 4호
2nd row부산광역시 중구 남포동2가 24번지 8호
3rd row부산광역시 중구 창선동2가 24번지 4호
4th row부산광역시 중구 남포동4가 2번지 5호
5th row부산광역시 중구 남포동6가 85
ValueCountFrequency (%)
부산광역시 1055
 
19.3%
금정구 170
 
3.1%
부산진구 143
 
2.6%
1호 121
 
2.2%
남구 106
 
1.9%
사하구 86
 
1.6%
동래구 81
 
1.5%
중구 76
 
1.4%
해운대구 72
 
1.3%
1층 68
 
1.2%
Other values (1403) 3499
63.9%
2024-04-21T19:34:25.841073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4408
 
16.8%
1 1395
 
5.3%
1362
 
5.2%
1300
 
5.0%
1206
 
4.6%
1101
 
4.2%
1088
 
4.2%
1086
 
4.2%
1060
 
4.1%
2 916
 
3.5%
Other values (303) 11239
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15572
59.5%
Decimal Number 5714
 
21.8%
Space Separator 4408
 
16.8%
Dash Punctuation 295
 
1.1%
Uppercase Letter 64
 
0.2%
Other Punctuation 44
 
0.2%
Close Punctuation 30
 
0.1%
Open Punctuation 30
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1362
 
8.7%
1300
 
8.3%
1206
 
7.7%
1101
 
7.1%
1088
 
7.0%
1086
 
7.0%
1060
 
6.8%
826
 
5.3%
788
 
5.1%
773
 
5.0%
Other values (269) 4982
32.0%
Uppercase Letter
ValueCountFrequency (%)
S 11
17.2%
K 10
15.6%
B 7
10.9%
E 6
9.4%
A 6
9.4%
H 5
7.8%
C 5
7.8%
U 4
 
6.2%
Y 4
 
6.2%
G 2
 
3.1%
Other values (3) 4
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 1395
24.4%
2 916
16.0%
3 640
11.2%
4 547
 
9.6%
5 474
 
8.3%
0 393
 
6.9%
6 365
 
6.4%
7 352
 
6.2%
8 321
 
5.6%
9 311
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 36
81.8%
. 5
 
11.4%
@ 2
 
4.5%
/ 1
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
4408
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 295
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15572
59.5%
Common 10523
40.2%
Latin 66
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1362
 
8.7%
1300
 
8.3%
1206
 
7.7%
1101
 
7.1%
1088
 
7.0%
1086
 
7.0%
1060
 
6.8%
826
 
5.3%
788
 
5.1%
773
 
5.0%
Other values (269) 4982
32.0%
Common
ValueCountFrequency (%)
4408
41.9%
1 1395
 
13.3%
2 916
 
8.7%
3 640
 
6.1%
4 547
 
5.2%
5 474
 
4.5%
0 393
 
3.7%
6 365
 
3.5%
7 352
 
3.3%
8 321
 
3.1%
Other values (9) 712
 
6.8%
Latin
ValueCountFrequency (%)
S 11
16.7%
K 10
15.2%
B 7
10.6%
E 6
9.1%
A 6
9.1%
H 5
7.6%
C 5
7.6%
U 4
 
6.1%
Y 4
 
6.1%
G 2
 
3.0%
Other values (5) 6
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15572
59.5%
ASCII 10589
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4408
41.6%
1 1395
 
13.2%
2 916
 
8.7%
3 640
 
6.0%
4 547
 
5.2%
5 474
 
4.5%
0 393
 
3.7%
6 365
 
3.4%
7 352
 
3.3%
8 321
 
3.0%
Other values (24) 778
 
7.3%
Hangul
ValueCountFrequency (%)
1362
 
8.7%
1300
 
8.3%
1206
 
7.7%
1101
 
7.1%
1088
 
7.0%
1086
 
7.0%
1060
 
6.8%
826
 
5.3%
788
 
5.1%
773
 
5.0%
Other values (269) 4982
32.0%

도로명전체주소
Text

MISSING 

Distinct1031
Distinct (%)93.2%
Missing82
Missing (%)6.9%
Memory size9.4 KiB
2024-04-21T19:34:27.158386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length49
Mean length28.146474
Min length20

Characters and Unicode

Total characters31130
Distinct characters358
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

Unique970 ?
Unique (%)87.7%

Sample

1st row부산광역시 중구 국제시장2길 6-1 (창선동2가)
2nd row부산광역시 중구 구덕로34번길 3-1 (남포동2가)
3rd row부산광역시 중구 국제시장2길 6-1 (창선동2가)
4th row부산광역시 중구 구덕로 38-1, 1,2층 (남포동4가)
5th row부산광역시 중구 광복로 43 (창선동1가)
ValueCountFrequency (%)
부산광역시 1107
 
17.7%
1층 177
 
2.8%
금정구 155
 
2.5%
부산진구 142
 
2.3%
해운대구 101
 
1.6%
남구 92
 
1.5%
사하구 89
 
1.4%
동래구 89
 
1.4%
중구 76
 
1.2%
부전동 71
 
1.1%
Other values (1359) 4152
66.4%
2024-04-21T19:34:28.718424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5149
 
16.5%
1410
 
4.5%
1398
 
4.5%
1353
 
4.3%
1193
 
3.8%
1188
 
3.8%
1143
 
3.7%
1111
 
3.6%
1 1097
 
3.5%
) 1092
 
3.5%
Other values (348) 14996
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18616
59.8%
Space Separator 5149
 
16.5%
Decimal Number 4382
 
14.1%
Close Punctuation 1092
 
3.5%
Open Punctuation 1092
 
3.5%
Other Punctuation 552
 
1.8%
Dash Punctuation 163
 
0.5%
Uppercase Letter 72
 
0.2%
Math Symbol 7
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1410
 
7.6%
1398
 
7.5%
1353
 
7.3%
1193
 
6.4%
1188
 
6.4%
1143
 
6.1%
1111
 
6.0%
1089
 
5.8%
586
 
3.1%
280
 
1.5%
Other values (313) 7865
42.2%
Uppercase Letter
ValueCountFrequency (%)
S 14
19.4%
K 12
16.7%
B 11
15.3%
A 5
 
6.9%
H 5
 
6.9%
C 5
 
6.9%
E 4
 
5.6%
Y 4
 
5.6%
U 4
 
5.6%
G 4
 
5.6%
Other values (4) 4
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 1097
25.0%
2 673
15.4%
3 408
 
9.3%
0 389
 
8.9%
4 375
 
8.6%
5 323
 
7.4%
7 316
 
7.2%
6 302
 
6.9%
9 258
 
5.9%
8 241
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
b 1
20.0%
h 1
20.0%
k 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 548
99.3%
. 4
 
0.7%
Space Separator
ValueCountFrequency (%)
5149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1092
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1092
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 163
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18616
59.8%
Common 12437
40.0%
Latin 77
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1410
 
7.6%
1398
 
7.5%
1353
 
7.3%
1193
 
6.4%
1188
 
6.4%
1143
 
6.1%
1111
 
6.0%
1089
 
5.8%
586
 
3.1%
280
 
1.5%
Other values (313) 7865
42.2%
Latin
ValueCountFrequency (%)
S 14
18.2%
K 12
15.6%
B 11
14.3%
A 5
 
6.5%
H 5
 
6.5%
C 5
 
6.5%
E 4
 
5.2%
Y 4
 
5.2%
U 4
 
5.2%
G 4
 
5.2%
Other values (8) 9
11.7%
Common
ValueCountFrequency (%)
5149
41.4%
1 1097
 
8.8%
) 1092
 
8.8%
( 1092
 
8.8%
2 673
 
5.4%
, 548
 
4.4%
3 408
 
3.3%
0 389
 
3.1%
4 375
 
3.0%
5 323
 
2.6%
Other values (7) 1291
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18616
59.8%
ASCII 12514
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5149
41.1%
1 1097
 
8.8%
) 1092
 
8.7%
( 1092
 
8.7%
2 673
 
5.4%
, 548
 
4.4%
3 408
 
3.3%
0 389
 
3.1%
4 375
 
3.0%
5 323
 
2.6%
Other values (25) 1368
 
10.9%
Hangul
ValueCountFrequency (%)
1410
 
7.6%
1398
 
7.5%
1353
 
7.3%
1193
 
6.4%
1188
 
6.4%
1143
 
6.1%
1111
 
6.0%
1089
 
5.8%
586
 
3.1%
280
 
1.5%
Other values (313) 7865
42.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct539
Distinct (%)57.8%
Missing256
Missing (%)21.5%
Infinite0
Infinite (%)0.0%
Mean82936.735
Minimum46004
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:28.963447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46004
5-th percentile46243
Q147130.75
median47862.5
Q348945
95-th percentile608796.75
Maximum619963
Range573959
Interquartile range (IQR)1814.25

Descriptive statistics

Standard deviation136452.28
Coefficient of variation (CV)1.6452574
Kurtosis11.205726
Mean82936.735
Median Absolute Deviation (MAD)869.5
Skewness3.630341
Sum77297037
Variance1.8619224 × 1010
MonotonicityNot monotonic
2024-04-21T19:34:29.221044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48946 21
 
1.8%
48953 13
 
1.1%
46291 11
 
0.9%
48945 10
 
0.8%
47295 9
 
0.8%
47296 8
 
0.7%
47254 7
 
0.6%
46576 7
 
0.6%
47289 7
 
0.6%
48095 7
 
0.6%
Other values (529) 832
70.0%
(Missing) 256
 
21.5%
ValueCountFrequency (%)
46004 1
 
0.1%
46008 2
 
0.2%
46010 1
 
0.1%
46015 5
0.4%
46017 1
 
0.1%
46029 1
 
0.1%
46048 3
0.3%
46055 1
 
0.1%
46056 2
 
0.2%
46061 2
 
0.2%
ValueCountFrequency (%)
619963 1
0.1%
619961 1
0.1%
619912 1
0.1%
619905 1
0.1%
619903 2
0.2%
618803 1
0.1%
617823 1
0.1%
617818 1
0.1%
617816 1
0.1%
617800 1
0.1%
Distinct940
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2024-04-21T19:34:29.983743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.8181818
Min length2

Characters and Unicode

Total characters8100
Distinct characters415
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique823 ?
Unique (%)69.3%

Sample

1st row국전안경
2nd row아이샵(eye#)안경
3rd row국전안경
4th row눈사랑안경남포
5th row갤러리안경원
ValueCountFrequency (%)
안경원 67
 
4.5%
안경 44
 
2.9%
갤러리안경 30
 
2.0%
안경나라 22
 
1.5%
눈사랑안경 18
 
1.2%
초이스안경 13
 
0.9%
갤러리안경원 13
 
0.9%
오렌즈 12
 
0.8%
세컨페이스 11
 
0.7%
으뜸50안경 11
 
0.7%
Other values (938) 1252
83.9%
2024-04-21T19:34:30.960494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1078
 
13.3%
1076
 
13.3%
404
 
5.0%
305
 
3.8%
281
 
3.5%
270
 
3.3%
215
 
2.7%
188
 
2.3%
127
 
1.6%
0 97
 
1.2%
Other values (405) 4059
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7298
90.1%
Space Separator 305
 
3.8%
Decimal Number 196
 
2.4%
Uppercase Letter 87
 
1.1%
Lowercase Letter 70
 
0.9%
Open Punctuation 58
 
0.7%
Close Punctuation 58
 
0.7%
Other Punctuation 22
 
0.3%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1078
 
14.8%
1076
 
14.7%
404
 
5.5%
281
 
3.9%
270
 
3.7%
215
 
2.9%
188
 
2.6%
127
 
1.7%
88
 
1.2%
81
 
1.1%
Other values (347) 3490
47.8%
Uppercase Letter
ValueCountFrequency (%)
O 13
14.9%
S 8
 
9.2%
E 8
 
9.2%
L 6
 
6.9%
K 5
 
5.7%
G 5
 
5.7%
C 4
 
4.6%
N 4
 
4.6%
I 4
 
4.6%
M 4
 
4.6%
Other values (12) 26
29.9%
Lowercase Letter
ValueCountFrequency (%)
e 10
14.3%
c 7
10.0%
a 7
10.0%
n 7
10.0%
o 6
8.6%
i 6
8.6%
t 5
7.1%
l 5
7.1%
p 3
 
4.3%
s 3
 
4.3%
Other values (8) 11
15.7%
Decimal Number
ValueCountFrequency (%)
0 97
49.5%
1 44
22.4%
8 23
 
11.7%
5 23
 
11.7%
2 5
 
2.6%
3 3
 
1.5%
6 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 13
59.1%
· 4
 
18.2%
& 3
 
13.6%
# 2
 
9.1%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
305
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7298
90.1%
Common 644
 
8.0%
Latin 157
 
1.9%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1078
 
14.8%
1076
 
14.7%
404
 
5.5%
281
 
3.9%
270
 
3.7%
215
 
2.9%
188
 
2.6%
127
 
1.7%
88
 
1.2%
81
 
1.1%
Other values (347) 3490
47.8%
Latin
ValueCountFrequency (%)
O 13
 
8.3%
e 10
 
6.4%
S 8
 
5.1%
E 8
 
5.1%
c 7
 
4.5%
a 7
 
4.5%
n 7
 
4.5%
o 6
 
3.8%
i 6
 
3.8%
L 6
 
3.8%
Other values (30) 79
50.3%
Common
ValueCountFrequency (%)
305
47.4%
0 97
 
15.1%
( 58
 
9.0%
) 58
 
9.0%
1 44
 
6.8%
8 23
 
3.6%
5 23
 
3.6%
. 13
 
2.0%
2 5
 
0.8%
· 4
 
0.6%
Other values (7) 14
 
2.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7297
90.1%
ASCII 796
 
9.8%
None 5
 
0.1%
CJK 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1078
 
14.8%
1076
 
14.7%
404
 
5.5%
281
 
3.9%
270
 
3.7%
215
 
2.9%
188
 
2.6%
127
 
1.7%
88
 
1.2%
81
 
1.1%
Other values (346) 3489
47.8%
ASCII
ValueCountFrequency (%)
305
38.3%
0 97
 
12.2%
( 58
 
7.3%
) 58
 
7.3%
1 44
 
5.5%
8 23
 
2.9%
5 23
 
2.9%
. 13
 
1.6%
O 13
 
1.6%
e 10
 
1.3%
Other values (45) 152
19.1%
None
ValueCountFrequency (%)
· 4
80.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1162
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0151193 × 1013
Minimum2.008112 × 1013
Maximum2.0220228 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:31.199858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.008112 × 1013
5-th percentile2.0090209 × 1013
Q12.0120487 × 1013
median2.0150724 × 1013
Q32.0190149 × 1013
95-th percentile2.0210826 × 1013
Maximum2.0220228 × 1013
Range1.3910801 × 1011
Interquartile range (IQR)6.9661245 × 1010

Descriptive statistics

Standard deviation4.0307048 × 1010
Coefficient of variation (CV)0.0020002314
Kurtosis-1.1662283
Mean2.0151193 × 1013
Median Absolute Deviation (MAD)3.0497987 × 1010
Skewness-0.026291638
Sum2.3939617 × 1016
Variance1.6246581 × 1021
MonotonicityNot monotonic
2024-04-21T19:34:31.459420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20081201183150 18
 
1.5%
20081215160833 6
 
0.5%
20081215160832 4
 
0.3%
20081201183151 2
 
0.2%
20090209151721 1
 
0.1%
20090209151337 1
 
0.1%
20090209151001 1
 
0.1%
20090209150705 1
 
0.1%
20090209150435 1
 
0.1%
20090209150211 1
 
0.1%
Other values (1152) 1152
97.0%
ValueCountFrequency (%)
20081120141639 1
 
0.1%
20081126140756 1
 
0.1%
20081126141153 1
 
0.1%
20081201183150 18
1.5%
20081201183151 2
 
0.2%
20081206110426 1
 
0.1%
20081215160831 1
 
0.1%
20081215160832 4
 
0.3%
20081215160833 6
 
0.5%
20081226155323 1
 
0.1%
ValueCountFrequency (%)
20220228155227 1
0.1%
20220225171330 1
0.1%
20220225160744 1
0.1%
20220224164003 1
0.1%
20220224133930 1
0.1%
20220224103829 1
0.1%
20220223192727 1
0.1%
20220223134912 1
0.1%
20220223134505 1
0.1%
20220218154413 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
I
931 
U
257 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 931
78.4%
U 257
 
21.6%

Length

2024-04-21T19:34:31.706107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:31.870108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 931
78.4%
u 257
 
21.6%
Distinct296
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
Minimum2018-08-31 23:59:59
Maximum2022-03-02 00:22:36
2024-04-21T19:34:32.065244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:34:32.307668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1188
Missing (%)100.0%
Memory size10.6 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct946
Distinct (%)85.4%
Missing80
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean388079.6
Minimum367108.19
Maximum403236.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:32.550061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367108.19
5-th percentile379691.51
Q1384878.5
median388523.55
Q3391233.26
95-th percentile397398.14
Maximum403236.19
Range36128.006
Interquartile range (IQR)6354.7648

Descriptive statistics

Standard deviation5260.5426
Coefficient of variation (CV)0.013555319
Kurtosis0.44714108
Mean388079.6
Median Absolute Deviation (MAD)3188.6684
Skewness-0.030989062
Sum4.2999219 × 108
Variance27673309
MonotonicityNot monotonic
2024-04-21T19:34:32.808721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387618.822819234 8
 
0.7%
387271.299492377 7
 
0.6%
389314.662085919 5
 
0.4%
398237.363461482 5
 
0.4%
389816.233000769 5
 
0.4%
389097.800933845 5
 
0.4%
387920.292112964 5
 
0.4%
385590.814676765 4
 
0.3%
395388.715069604 4
 
0.3%
393952.264486105 4
 
0.3%
Other values (936) 1056
88.9%
(Missing) 80
 
6.7%
ValueCountFrequency (%)
367108.187126995 1
0.1%
371179.51398421 1
0.1%
371180.37604943 1
0.1%
373495.79454295 1
0.1%
373508.720158398 1
0.1%
373510.894532737 1
0.1%
373561.0 1
0.1%
373576.028819056 1
0.1%
373735.179018815 1
0.1%
374816.0 1
0.1%
ValueCountFrequency (%)
403236.192851 1
 
0.1%
402168.434114938 3
0.3%
401739.342184973 1
 
0.1%
401727.549967414 1
 
0.1%
401723.705169194 1
 
0.1%
401721.440535713 1
 
0.1%
401712.115666 1
 
0.1%
401709.206084507 1
 
0.1%
401700.977668733 1
 
0.1%
401687.081587248 1
 
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct947
Distinct (%)85.5%
Missing80
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean187319.18
Minimum174016.55
Maximum206377.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:33.060794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174016.55
5-th percentile178715.13
Q1183542.35
median187069.33
Q3191765.61
95-th percentile196235.82
Maximum206377.97
Range32361.42
Interquartile range (IQR)8223.2564

Descriptive statistics

Standard deviation5841.3136
Coefficient of variation (CV)0.031183745
Kurtosis-0.15387719
Mean187319.18
Median Absolute Deviation (MAD)4353.1956
Skewness0.18954385
Sum2.0754965 × 108
Variance34120944
MonotonicityNot monotonic
2024-04-21T19:34:33.306576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186273.478853367 8
 
0.7%
186099.137533193 7
 
0.6%
194669.898821687 5
 
0.4%
187720.511056894 5
 
0.4%
193329.605871168 5
 
0.4%
192260.811648263 5
 
0.4%
186157.316240551 5
 
0.4%
179553.867031936 4
 
0.3%
186268.853282623 4
 
0.3%
187602.933160728 4
 
0.3%
Other values (937) 1056
88.9%
(Missing) 80
 
6.7%
ValueCountFrequency (%)
174016.551235181 1
 
0.1%
174289.976688419 2
0.2%
174820.944129501 1
 
0.1%
174883.742734168 2
0.2%
174910.857552639 1
 
0.1%
174915.765704636 1
 
0.1%
174922.72397246 1
 
0.1%
175057.154813024 1
 
0.1%
175314.286676535 1
 
0.1%
175382.738615908 3
0.3%
ValueCountFrequency (%)
206377.970967 1
0.1%
206209.450536273 1
0.1%
205965.90747 1
0.1%
205730.304383 1
0.1%
205464.225232 1
0.1%
205376.57603 1
0.1%
205312.201457 1
0.1%
205109.080405 1
0.1%
205056.269216 1
0.1%
205035.508686 1
0.1%

시력표수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
1
974 
0
172 
2
 
35
<NA>
 
5
3
 
2

Length

Max length4
Median length1
Mean length1.0126263
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 974
82.0%
0 172
 
14.5%
2 35
 
2.9%
<NA> 5
 
0.4%
3 2
 
0.2%

Length

2024-04-21T19:34:33.553165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:33.739683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 974
82.0%
0 172
 
14.5%
2 35
 
2.9%
na 5
 
0.4%
3 2
 
0.2%

표본렌즈수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
1
904 
0
208 
<NA>
 
36
2
 
33
3
 
6

Length

Max length4
Median length1
Mean length1.0925926
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 904
76.1%
0 208
 
17.5%
<NA> 36
 
3.0%
2 33
 
2.8%
3 6
 
0.5%
266 1
 
0.1%

Length

2024-04-21T19:34:33.943661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:34.138087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 904
76.1%
0 208
 
17.5%
na 36
 
3.0%
2 33
 
2.8%
3 6
 
0.5%
266 1
 
0.1%

측정의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing44
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean0.88199301
Minimum0
Maximum11
Zeros209
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:34.313885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.58791344
Coefficient of variation (CV)0.66657382
Kurtosis80.370309
Mean0.88199301
Median Absolute Deviation (MAD)0
Skewness4.9717112
Sum1009
Variance0.34564222
MonotonicityNot monotonic
2024-04-21T19:34:34.648304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 883
74.3%
0 209
 
17.6%
2 43
 
3.6%
3 4
 
0.3%
4 3
 
0.3%
5 1
 
0.1%
11 1
 
0.1%
(Missing) 44
 
3.7%
ValueCountFrequency (%)
0 209
 
17.6%
1 883
74.3%
2 43
 
3.6%
3 4
 
0.3%
4 3
 
0.3%
5 1
 
0.1%
11 1
 
0.1%
ValueCountFrequency (%)
11 1
 
0.1%
5 1
 
0.1%
4 3
 
0.3%
3 4
 
0.3%
2 43
 
3.6%
1 883
74.3%
0 209
 
17.6%

동공거리측정기수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.6%
Missing5
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.92476754
Minimum0
Maximum10
Zeros174
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:34.988098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.59489105
Coefficient of variation (CV)0.64328712
Kurtosis56.384114
Mean0.92476754
Median Absolute Deviation (MAD)0
Skewness4.6127198
Sum1094
Variance0.35389536
MonotonicityNot monotonic
2024-04-21T19:34:35.334563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 961
80.9%
0 174
 
14.6%
2 31
 
2.6%
3 8
 
0.7%
5 5
 
0.4%
4 3
 
0.3%
10 1
 
0.1%
(Missing) 5
 
0.4%
ValueCountFrequency (%)
0 174
 
14.6%
1 961
80.9%
2 31
 
2.6%
3 8
 
0.7%
4 3
 
0.3%
5 5
 
0.4%
10 1
 
0.1%
ValueCountFrequency (%)
10 1
 
0.1%
5 5
 
0.4%
4 3
 
0.3%
3 8
 
0.7%
2 31
 
2.6%
1 961
80.9%
0 174
 
14.6%

정점굴절계기수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
1
868 
0
172 
2
104 
3
 
30
4
 
7

Length

Max length4
Median length1
Mean length1.0176768
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row4
5th row1

Common Values

ValueCountFrequency (%)
1 868
73.1%
0 172
 
14.5%
2 104
 
8.8%
3 30
 
2.5%
4 7
 
0.6%
<NA> 7
 
0.6%

Length

2024-04-21T19:34:35.734903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:36.079150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 868
73.1%
0 172
 
14.5%
2 104
 
8.8%
3 30
 
2.5%
4 7
 
0.6%
na 7
 
0.6%

조제용연마기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
1
901 
0
211 
<NA>
 
48
2
 
27
3
 
1

Length

Max length4
Median length1
Mean length1.1212121
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 901
75.8%
0 211
 
17.8%
<NA> 48
 
4.0%
2 27
 
2.3%
3 1
 
0.1%

Length

2024-04-21T19:34:36.470674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:36.803295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 901
75.8%
0 211
 
17.8%
na 48
 
4.0%
2 27
 
2.3%
3 1
 
0.1%

렌즈절단기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
1
910 
0
212 
<NA>
 
46
2
 
19
3
 
1

Length

Max length4
Median length1
Mean length1.1161616
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 910
76.6%
0 212
 
17.8%
<NA> 46
 
3.9%
2 19
 
1.6%
3 1
 
0.1%

Length

2024-04-21T19:34:37.189374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:37.528596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 910
76.6%
0 212
 
17.8%
na 46
 
3.9%
2 19
 
1.6%
3 1
 
0.1%

가열기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing48
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean0.92982456
Minimum0
Maximum5
Zeros210
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:37.840085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.57941417
Coefficient of variation (CV)0.62314354
Kurtosis5.547294
Mean0.92982456
Median Absolute Deviation (MAD)0
Skewness0.89928673
Sum1060
Variance0.33572078
MonotonicityNot monotonic
2024-04-21T19:34:38.178921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 817
68.8%
0 210
 
17.7%
2 101
 
8.5%
3 9
 
0.8%
5 2
 
0.2%
4 1
 
0.1%
(Missing) 48
 
4.0%
ValueCountFrequency (%)
0 210
 
17.7%
1 817
68.8%
2 101
 
8.5%
3 9
 
0.8%
4 1
 
0.1%
5 2
 
0.2%
ValueCountFrequency (%)
5 2
 
0.2%
4 1
 
0.1%
3 9
 
0.8%
2 101
 
8.5%
1 817
68.8%
0 210
 
17.7%

안경세척기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing47
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean0.96319018
Minimum0
Maximum5
Zeros209
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:38.507251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.61875227
Coefficient of variation (CV)0.64239886
Kurtosis3.4898033
Mean0.96319018
Median Absolute Deviation (MAD)0
Skewness0.84669224
Sum1099
Variance0.38285438
MonotonicityNot monotonic
2024-04-21T19:34:38.847003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 791
66.6%
0 209
 
17.6%
2 119
 
10.0%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
(Missing) 47
 
4.0%
ValueCountFrequency (%)
0 209
 
17.6%
1 791
66.6%
2 119
 
10.0%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 2
 
0.2%
3 19
 
1.6%
2 119
 
10.0%
1 791
66.6%
0 209
 
17.6%

총면적
Real number (ℝ)

MISSING  ZEROS 

Distinct511
Distinct (%)74.1%
Missing498
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean76.252449
Minimum0
Maximum723.02
Zeros79
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-04-21T19:34:39.215565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133
median58.5
Q399
95-th percentile213.55
Maximum723.02
Range723.02
Interquartile range (IQR)66

Descriptive statistics

Standard deviation73.027556
Coefficient of variation (CV)0.95770767
Kurtosis17.326572
Mean76.252449
Median Absolute Deviation (MAD)31.5
Skewness2.9381535
Sum52614.19
Variance5333.0239
MonotonicityNot monotonic
2024-04-21T19:34:39.858272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 79
 
6.6%
33.0 10
 
0.8%
49.5 5
 
0.4%
66.0 5
 
0.4%
60.0 5
 
0.4%
46.2 4
 
0.3%
56.0 4
 
0.3%
57.6 4
 
0.3%
114.0 3
 
0.3%
105.6 3
 
0.3%
Other values (501) 568
47.8%
(Missing) 498
41.9%
ValueCountFrequency (%)
0.0 79
6.6%
1.0 1
 
0.1%
2.0 1
 
0.1%
5.56 1
 
0.1%
5.6 1
 
0.1%
7.5 1
 
0.1%
8.5 1
 
0.1%
10.23 1
 
0.1%
11.22 1
 
0.1%
11.5 1
 
0.1%
ValueCountFrequency (%)
723.02 1
0.1%
700.0 1
0.1%
361.38 1
0.1%
336.9 1
0.1%
334.0 1
0.1%
329.12 1
0.1%
320.0 1
0.1%
310.68 1
0.1%
304.5 1
0.1%
304.12 1
0.1%

Unnamed: 38
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1188
Missing (%)100.0%
Memory size10.6 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
01안경업01_02_01_P3250000PHMB22018325002108220000120180814<NA>3폐업3폐업20210726<NA><NA><NA>2531216<NA><NA>부산광역시 중구 창선동2가 24번지 4호부산광역시 중구 국제시장2길 6-1 (창선동2가)48946국전안경20210726152758U2021-07-28 02:40:00.0<NA>384903.524108179742.03163311111111193.22<NA>
12안경업01_02_01_P3250000PHMB22010325002108220000120100312<NA>3폐업3폐업20120406<NA><NA><NA>070-4116-2770<NA>600042부산광역시 중구 남포동2가 24번지 8호부산광역시 중구 구덕로34번길 3-1 (남포동2가)<NA>아이샵(eye#)안경20121026092051I2018-08-31 23:59:59.0<NA>385208.616221179585.320651111111111134.98<NA>
23안경업01_02_01_P3250000PHMB21993325002108220000119930327<NA>3폐업3폐업20180814<NA><NA><NA>051-253-1216<NA>600819부산광역시 중구 창선동2가 24번지 4호부산광역시 중구 국제시장2길 6-1 (창선동2가)48946국전안경20180814102702I2018-08-31 23:59:59.0<NA>384903.524108179742.031633111111111<NA><NA>
34안경업01_02_01_P3250000PHMB22010325002108220000620101227<NA>3폐업3폐업20190416<NA><NA><NA><NA><NA><NA>부산광역시 중구 남포동4가 2번지 5호부산광역시 중구 구덕로 38-1, 1,2층 (남포동4가)48953눈사랑안경남포20190416151924U2019-04-18 02:40:00.0<NA>385186.028117179577.535415111141144188.2<NA>
45안경업01_02_01_P3250000PHMB22014325002108220000120140102<NA>3폐업3폐업20161012<NA><NA><NA>051-246-0006<NA><NA><NA>부산광역시 중구 광복로 43 (창선동1가)48947갤러리안경원20161012162524I2018-08-31 23:59:59.0<NA>385016.604749179699.072538111111111197.49<NA>
56안경업01_02_01_P3250000PHMB22004325002108220000120040312<NA>3폐업3폐업20090320<NA><NA><NA>051-245-1999<NA><NA>부산광역시 중구 남포동6가 85<NA><NA>남포프라자안경20120320135800I2018-08-31 23:59:59.0<NA><NA><NA>111111111<NA><NA>
67안경업01_02_01_P3250000PHMB22005325002108220000120051122<NA>3폐업3폐업20180416<NA><NA><NA>051-245-7344<NA><NA>부산광역시 중구 부평동1가 23-27부산광역시 중구 중구로33번길 12 (부평동1가)48978마루안경20180424153521I2018-08-31 23:59:59.0<NA>384777.232329179870.976762111111111<NA><NA>
78안경업01_02_01_P3250000PHMB22006325002108220000120061228<NA>3폐업3폐업20210623<NA><NA><NA>051-246-1341<NA><NA>부산광역시 중구 창선동2가 45-17부산광역시 중구 중구로 14 (창선동2가)48953080안경20210623114002U2021-06-25 02:40:00.0<NA>384843.682071179657.801434111111111<NA><NA>
89안경업01_02_01_P3250000PHMB22010325002108220000520101109<NA>3폐업3폐업20180531<NA><NA><NA>242-4623<NA>600063부산광역시 중구 신창동3가 16번지 7호부산광역시 중구 광복로35번길 16 (신창동3가)48946스마일안경20180605150519I2018-08-31 23:59:59.0<NA>384931.528183179828.54383611111111149.0<NA>
910안경업01_02_01_P3250000PHMB21987325002108220000119870722<NA>3폐업3폐업20121022<NA><NA><NA>051-245-9976<NA><NA>부산광역시 중구 신창동3가 32-2<NA><NA>금장안경20121026092249I2018-08-31 23:59:59.0<NA><NA><NA>111111111<NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
11781179안경업01_02_01_P3400000PHMB22014340001308220000120140324<NA>1영업/정상13영업중<NA><NA><NA><NA>728-8880<NA>619963부산광역시 기장군 정관면 용수리 1328번지 1호부산광역시 기장군 정관면 정관로 501 (삼영프라자 1층)46015파프리카안경점20160628144728I2018-08-31 23:59:59.0<NA>397407.420855205376.5760311213112290.0<NA>
11791180안경업01_02_01_P3400000PHMB22014340001308220000420141111<NA>1영업/정상13영업중<NA><NA><NA><NA>051-727-6819<NA><NA><NA>부산광역시 기장군 정관면 정관로 56046017안경만들기20190329153555U2019-03-31 02:40:00.0<NA>397797.997977204915.6281111212111195.7<NA>
11801181안경업01_02_01_P3400000PHMB22014340001308220000520141222<NA>1영업/정상13영업중<NA><NA><NA><NA>051-901-2520<NA><NA><NA>부산광역시 기장군 기장읍 기장해안로 147 (롯데몰동부산점스펙터내)46083스펙트롯데동부산점안경원20141222181646I2018-08-31 23:59:59.0<NA>401669.0190270.011411112236.96<NA>
11811182안경업01_02_01_P3400000PHMB22020340001308220000120200221<NA>1영업/정상13영업중<NA><NA><NA><NA>0517215051<NA><NA>부산광역시 기장군 기장읍 동부리 280번지 11호 빠리바게트부산광역시 기장군 기장읍 차성동로 64, 2층46065으뜸50안경콘택트 기장점20200221163210I2020-02-23 00:23:23.0<NA>401709.206085196053.96927411<NA>1<NA><NA><NA><NA><NA>100.42<NA>
11821183안경업01_02_01_P3400000PHMB22014340001308220000320140827<NA>1영업/정상13영업중<NA><NA><NA><NA>728-7229<NA><NA><NA>부산광역시 기장군 정관면 정관로 389 (롯데타워 103호)46008우리동네 안경원20190628145312U2019-06-30 02:40:00.0<NA>396910.307285206377.97096711122111272.6<NA>
11831184안경업01_02_01_P3400000PHMB22021340001308220000220210728<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7585-0909<NA><NA>부산광역시 기장군 정관읍 매학리 713-1 정관타워부산광역시 기장군 정관읍 정관로 561, 3층 303호46015으뜸플러스안경 부산정관점20210729105316I2021-07-31 00:22:51.0<NA>397748.735322204683.186892100110000202.97<NA>
11841185안경업01_02_01_P3400000PHMB22021340001308220000320210906<NA>1영업/정상13영업중<NA><NA><NA><NA>051-722-2233<NA><NA>부산광역시 기장군 일광면 삼성리 830부산광역시 기장군 일광면 해빛6로 107-3, 1층 105,106호46048바라본안경20210906142236I2021-09-08 00:22:50.0<NA><NA><NA>10011000063.5<NA>
11851186안경업01_02_01_P3400000PHMB22021340001308220000120210601<NA>1영업/정상13영업중<NA><NA><NA><NA>051-722-3180<NA><NA>부산광역시 기장군 기장읍 교리 342-1부산광역시 기장군 기장읍 차성로 430, 1층 110호46056기장성모안경20211116145430U2021-11-18 02:40:00.0<NA>401700.977669197225.42833320011000062.73<NA>
11861187안경업01_02_01_P3400000PHMB22020340001308220000220110728<NA>1영업/정상13영업중<NA><NA><NA><NA>051-545-1518<NA><NA>부산광역시 기장군 기장읍 교리 340-1 꼬마돈까스부산광역시 기장군 기장읍 차성로 424, 1층46056갤러리안경20200914132924I2020-09-16 00:23:12.0<NA>401654.858313197228.25087111111112256.6<NA>
11871188안경업01_02_01_P3400000PHMB22018340001308220000120181122<NA>1영업/정상13영업중<NA><NA><NA><NA>051-724-6900<NA><NA>부산광역시 기장군 기장읍 동부리 362번지 1호부산광역시 기장군 기장읍 차성동로 10446063다비치안경 기장시장점20190502162748U2019-05-04 02:40:00.0<NA>401723.705169196436.866389222221122213.0<NA>