Overview

Dataset statistics

Number of variables35
Number of observations91
Missing cells752
Missing cells (%)23.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 KiB
Average record size in memory303.5 B

Variable types

Categorical15
Text6
DateTime4
Unsupported6
Numeric4

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),시력표수,표본렌즈수,측정의자수,동공거리측정기수,정점굴절계기수,조제용연마기수,렌즈절단기수,가열기수,안경세척기수,총면적
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-16399/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 91 (100.0%) missing valuesMissing
폐업일자 has 44 (48.4%) missing valuesMissing
휴업시작일자 has 91 (100.0%) missing valuesMissing
휴업종료일자 has 91 (100.0%) missing valuesMissing
재개업일자 has 91 (100.0%) missing valuesMissing
전화번호 has 18 (19.8%) missing valuesMissing
소재지면적 has 91 (100.0%) missing valuesMissing
소재지우편번호 has 38 (41.8%) missing valuesMissing
지번주소 has 2 (2.2%) missing valuesMissing
도로명주소 has 11 (12.1%) missing valuesMissing
도로명우편번호 has 18 (19.8%) missing valuesMissing
업태구분명 has 91 (100.0%) missing valuesMissing
좌표정보(X) has 15 (16.5%) missing valuesMissing
좌표정보(Y) has 15 (16.5%) missing valuesMissing
총면적 has 45 (49.5%) missing valuesMissing
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

Reproduction

Analysis started2024-05-11 06:23:49.934783
Analysis finished2024-05-11 06:23:50.864298
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
3170000
91 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 91
100.0%

Length

2024-05-11T15:23:50.982531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:51.170456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 91
100.0%

관리번호
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-05-11T15:23:51.515687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2275
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

Unique91 ?
Unique (%)100.0%

Sample

1st rowPHMB219913170035082200001
2nd rowPHMB219913170035082200002
3rd rowPHMB219913170035082200003
4th rowPHMB219913170035082200004
5th rowPHMB219913170035082200005
ValueCountFrequency (%)
phmb219913170035082200001 1
 
1.1%
phmb220113170035082200004 1
 
1.1%
phmb220163170035082200002 1
 
1.1%
phmb220163170035082200001 1
 
1.1%
phmb220153170035082200001 1
 
1.1%
phmb220143170035082200007 1
 
1.1%
phmb220143170035082200006 1
 
1.1%
phmb220143170035082200005 1
 
1.1%
phmb220143170035082200004 1
 
1.1%
phmb220143170035082200003 1
 
1.1%
Other values (81) 81
89.0%
2024-05-11T15:23:52.196635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 736
32.4%
2 395
17.4%
3 209
 
9.2%
1 196
 
8.6%
7 103
 
4.5%
5 101
 
4.4%
8 97
 
4.3%
P 91
 
4.0%
H 91
 
4.0%
M 91
 
4.0%
Other values (4) 165
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1911
84.0%
Uppercase Letter 364
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 736
38.5%
2 395
20.7%
3 209
 
10.9%
1 196
 
10.3%
7 103
 
5.4%
5 101
 
5.3%
8 97
 
5.1%
9 48
 
2.5%
4 17
 
0.9%
6 9
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
P 91
25.0%
H 91
25.0%
M 91
25.0%
B 91
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1911
84.0%
Latin 364
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 736
38.5%
2 395
20.7%
3 209
 
10.9%
1 196
 
10.3%
7 103
 
5.4%
5 101
 
5.3%
8 97
 
5.1%
9 48
 
2.5%
4 17
 
0.9%
6 9
 
0.5%
Latin
ValueCountFrequency (%)
P 91
25.0%
H 91
25.0%
M 91
25.0%
B 91
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 736
32.4%
2 395
17.4%
3 209
 
9.2%
1 196
 
8.6%
7 103
 
4.5%
5 101
 
4.4%
8 97
 
4.3%
P 91
 
4.0%
H 91
 
4.0%
M 91
 
4.0%
Other values (4) 165
 
7.3%

인허가일자
Date

Distinct89
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size860.0 B
Minimum1980-07-03 00:00:00
Maximum2023-08-01 00:00:00
2024-05-11T15:23:52.464432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:52.760164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
3
47 
1
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 47
51.6%
1 44
48.4%

Length

2024-05-11T15:23:53.055775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:53.225187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 47
51.6%
1 44
48.4%

영업상태명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
폐업
47 
영업/정상
44 

Length

Max length5
Median length2
Mean length3.4505495
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 47
51.6%
영업/정상 44
48.4%

Length

2024-05-11T15:23:53.434366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:53.632760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 47
51.6%
영업/정상 44
48.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
3
47 
13
44 

Length

Max length2
Median length1
Mean length1.4835165
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 47
51.6%
13 44
48.4%

Length

2024-05-11T15:23:53.811430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:54.017681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 47
51.6%
13 44
48.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
폐업
47 
영업중
44 

Length

Max length3
Median length2
Mean length2.4835165
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 47
51.6%
영업중 44
48.4%

Length

2024-05-11T15:23:54.229319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:54.454858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 47
51.6%
영업중 44
48.4%

폐업일자
Date

MISSING 

Distinct46
Distinct (%)97.9%
Missing44
Missing (%)48.4%
Memory size860.0 B
Minimum2009-04-06 00:00:00
Maximum2024-03-24 00:00:00
2024-05-11T15:23:54.645343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:54.875208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

전화번호
Text

MISSING 

Distinct67
Distinct (%)91.8%
Missing18
Missing (%)19.8%
Memory size860.0 B
2024-05-11T15:23:55.680912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.8356164
Min length8

Characters and Unicode

Total characters645
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)84.9%

Sample

1st row857-7966
2nd row803-2193
3rd row805-7755
4th row808-0551
5th row856-3039
ValueCountFrequency (%)
892-3003 3
 
4.1%
893-8384 2
 
2.7%
866-8824 2
 
2.7%
838-6606 2
 
2.7%
894-6090 2
 
2.7%
2136-9718 1
 
1.4%
02-838-0077 1
 
1.4%
3289-9009 1
 
1.4%
868-5679 1
 
1.4%
02-802-2255 1
 
1.4%
Other values (57) 57
78.1%
2024-05-11T15:23:56.357878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 101
15.7%
8 93
14.4%
- 88
13.6%
2 63
9.8%
6 54
8.4%
9 53
8.2%
3 49
7.6%
5 48
7.4%
4 35
 
5.4%
1 31
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 557
86.4%
Dash Punctuation 88
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 101
18.1%
8 93
16.7%
2 63
11.3%
6 54
9.7%
9 53
9.5%
3 49
8.8%
5 48
8.6%
4 35
 
6.3%
1 31
 
5.6%
7 30
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 645
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 101
15.7%
8 93
14.4%
- 88
13.6%
2 63
9.8%
6 54
8.4%
9 53
8.2%
3 49
7.6%
5 48
7.4%
4 35
 
5.4%
1 31
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 645
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 101
15.7%
8 93
14.4%
- 88
13.6%
2 63
9.8%
6 54
8.4%
9 53
8.2%
3 49
7.6%
5 48
7.4%
4 35
 
5.4%
1 31
 
4.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

소재지우편번호
Text

MISSING 

Distinct29
Distinct (%)54.7%
Missing38
Missing (%)41.8%
Memory size860.0 B
2024-05-11T15:23:56.665749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0377358
Min length6

Characters and Unicode

Total characters320
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)24.5%

Sample

1st row153801
2nd row153863
3rd row153816
4th row153832
5th row153808
ValueCountFrequency (%)
153856 4
 
7.5%
153806 3
 
5.7%
153786 3
 
5.7%
153864 3
 
5.7%
153813 3
 
5.7%
153023 3
 
5.7%
153801 3
 
5.7%
153857 2
 
3.8%
153841 2
 
3.8%
153858 2
 
3.8%
Other values (19) 25
47.2%
2024-05-11T15:23:57.156583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 69
21.6%
3 69
21.6%
1 68
21.2%
8 51
15.9%
6 19
 
5.9%
0 16
 
5.0%
7 8
 
2.5%
4 8
 
2.5%
2 7
 
2.2%
9 3
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 318
99.4%
Dash Punctuation 2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 69
21.7%
3 69
21.7%
1 68
21.4%
8 51
16.0%
6 19
 
6.0%
0 16
 
5.0%
7 8
 
2.5%
4 8
 
2.5%
2 7
 
2.2%
9 3
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 320
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 69
21.6%
3 69
21.6%
1 68
21.2%
8 51
15.9%
6 19
 
5.9%
0 16
 
5.0%
7 8
 
2.5%
4 8
 
2.5%
2 7
 
2.2%
9 3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 69
21.6%
3 69
21.6%
1 68
21.2%
8 51
15.9%
6 19
 
5.9%
0 16
 
5.0%
7 8
 
2.5%
4 8
 
2.5%
2 7
 
2.2%
9 3
 
0.9%

지번주소
Text

MISSING 

Distinct80
Distinct (%)89.9%
Missing2
Missing (%)2.2%
Memory size860.0 B
2024-05-11T15:23:57.742552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length23.662921
Min length9

Characters and Unicode

Total characters2106
Distinct characters105
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)82.0%

Sample

1st row서울특별시 금천구 가산동 145번지 20호
2nd row서울특별시 금천구 시흥동 985번지 8호
3rd row독산2동 378-242
4th row서울특별시 금천구 독산동 1044번지 10호
5th row독산4동 179-12
ValueCountFrequency (%)
서울특별시 73
 
17.0%
금천구 73
 
17.0%
가산동 24
 
5.6%
독산동 20
 
4.7%
시흥동 18
 
4.2%
60번지 9
 
2.1%
3호 6
 
1.4%
시흥5동 6
 
1.4%
1층 5
 
1.2%
시흥1동 5
 
1.2%
Other values (142) 190
44.3%
2024-05-11T15:23:58.538184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
343
 
16.3%
시 109
 
5.2%
동 92
 
4.4%
1 90
 
4.3%
금 77
 
3.7%
천 77
 
3.7%
울 76
 
3.6%
구 73
 
3.5%
서 73
 
3.5%
특 73
 
3.5%
Other values (95) 1023
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1236
58.7%
Decimal Number 476
 
22.6%
Space Separator 343
 
16.3%
Dash Punctuation 29
 
1.4%
Close Punctuation 7
 
0.3%
Open Punctuation 7
 
0.3%
Uppercase Letter 6
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 109
 
8.8%
동 92
 
7.4%
금 77
 
6.2%
천 77
 
6.2%
울 76
 
6.1%
구 73
 
5.9%
서 73
 
5.9%
특 73
 
5.9%
별 73
 
5.9%
호 63
 
5.1%
Other values (77) 450
36.4%
Decimal Number
ValueCountFrequency (%)
1 90
18.9%
9 55
11.6%
3 52
10.9%
2 52
10.9%
0 48
10.1%
8 46
9.7%
5 38
8.0%
4 34
 
7.1%
7 33
 
6.9%
6 28
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
66.7%
C 1
 
16.7%
A 1
 
16.7%
Space Separator
ValueCountFrequency (%)
343
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1236
58.7%
Common 864
41.0%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 109
 
8.8%
동 92
 
7.4%
금 77
 
6.2%
천 77
 
6.2%
울 76
 
6.1%
구 73
 
5.9%
서 73
 
5.9%
특 73
 
5.9%
별 73
 
5.9%
호 63
 
5.1%
Other values (77) 450
36.4%
Common
ValueCountFrequency (%)
343
39.7%
1 90
 
10.4%
9 55
 
6.4%
3 52
 
6.0%
2 52
 
6.0%
0 48
 
5.6%
8 46
 
5.3%
5 38
 
4.4%
4 34
 
3.9%
7 33
 
3.8%
Other values (5) 73
 
8.4%
Latin
ValueCountFrequency (%)
B 4
66.7%
C 1
 
16.7%
A 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1236
58.7%
ASCII 870
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
343
39.4%
1 90
 
10.3%
9 55
 
6.3%
3 52
 
6.0%
2 52
 
6.0%
0 48
 
5.5%
8 46
 
5.3%
5 38
 
4.4%
4 34
 
3.9%
7 33
 
3.8%
Other values (8) 79
 
9.1%
Hangul
ValueCountFrequency (%)
시 109
 
8.8%
동 92
 
7.4%
금 77
 
6.2%
천 77
 
6.2%
울 76
 
6.1%
구 73
 
5.9%
서 73
 
5.9%
특 73
 
5.9%
별 73
 
5.9%
호 63
 
5.1%
Other values (77) 450
36.4%

도로명주소
Text

MISSING 

Distinct77
Distinct (%)96.2%
Missing11
Missing (%)12.1%
Memory size860.0 B
2024-05-11T15:23:59.095023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length32.7125
Min length21

Characters and Unicode

Total characters2617
Distinct characters132
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

Unique74 ?
Unique (%)92.5%

Sample

1st row서울특별시 금천구 가산로 128 (가산동)
2nd row서울특별시 금천구 시흥대로 149, 105호 (시흥동, 신라상가)
3rd row서울특별시 금천구 독산로 171 (독산동)
4th row서울특별시 금천구 시흥대로58길 6 (시흥동)
5th row서울특별시 금천구 은행나무로 51 (시흥동)
ValueCountFrequency (%)
서울특별시 80
 
15.9%
금천구 80
 
15.9%
시흥동 28
 
5.6%
독산동 24
 
4.8%
가산동 23
 
4.6%
시흥대로 21
 
4.2%
1층 20
 
4.0%
독산로 11
 
2.2%
금하로 10
 
2.0%
가산디지털1로 6
 
1.2%
Other values (142) 200
39.8%
2024-05-11T15:23:59.968086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
423
 
16.2%
시 145
 
5.5%
1 123
 
4.7%
금 96
 
3.7%
울 86
 
3.3%
천 85
 
3.2%
( 84
 
3.2%
) 84
 
3.2%
동 83
 
3.2%
서 81
 
3.1%
Other values (122) 1327
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1538
58.8%
Space Separator 423
 
16.2%
Decimal Number 386
 
14.7%
Open Punctuation 84
 
3.2%
Close Punctuation 84
 
3.2%
Other Punctuation 80
 
3.1%
Uppercase Letter 12
 
0.5%
Dash Punctuation 7
 
0.3%
Math Symbol 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 145
 
9.4%
금 96
 
6.2%
울 86
 
5.6%
천 85
 
5.5%
동 83
 
5.4%
서 81
 
5.3%
구 80
 
5.2%
별 80
 
5.2%
특 80
 
5.2%
로 79
 
5.1%
Other values (101) 643
41.8%
Decimal Number
ValueCountFrequency (%)
1 123
31.9%
2 42
 
10.9%
3 38
 
9.8%
0 35
 
9.1%
5 30
 
7.8%
6 30
 
7.8%
9 28
 
7.3%
8 21
 
5.4%
7 20
 
5.2%
4 19
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 7
58.3%
J 2
 
16.7%
S 2
 
16.7%
A 1
 
8.3%
Space Separator
ValueCountFrequency (%)
423
100.0%
Open Punctuation
ValueCountFrequency (%)
( 84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84
100.0%
Other Punctuation
ValueCountFrequency (%)
, 80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1538
58.8%
Common 1066
40.7%
Latin 13
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 145
 
9.4%
금 96
 
6.2%
울 86
 
5.6%
천 85
 
5.5%
동 83
 
5.4%
서 81
 
5.3%
구 80
 
5.2%
별 80
 
5.2%
특 80
 
5.2%
로 79
 
5.1%
Other values (101) 643
41.8%
Common
ValueCountFrequency (%)
423
39.7%
1 123
 
11.5%
( 84
 
7.9%
) 84
 
7.9%
, 80
 
7.5%
2 42
 
3.9%
3 38
 
3.6%
0 35
 
3.3%
5 30
 
2.8%
6 30
 
2.8%
Other values (6) 97
 
9.1%
Latin
ValueCountFrequency (%)
B 7
53.8%
J 2
 
15.4%
S 2
 
15.4%
w 1
 
7.7%
A 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1538
58.8%
ASCII 1079
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
423
39.2%
1 123
 
11.4%
( 84
 
7.8%
) 84
 
7.8%
, 80
 
7.4%
2 42
 
3.9%
3 38
 
3.5%
0 35
 
3.2%
5 30
 
2.8%
6 30
 
2.8%
Other values (11) 110
 
10.2%
Hangul
ValueCountFrequency (%)
시 145
 
9.4%
금 96
 
6.2%
울 86
 
5.6%
천 85
 
5.5%
동 83
 
5.4%
서 81
 
5.3%
구 80
 
5.2%
별 80
 
5.2%
특 80
 
5.2%
로 79
 
5.1%
Other values (101) 643
41.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)58.9%
Missing18
Missing (%)19.8%
Infinite0
Infinite (%)0.0%
Mean16528.041
Minimum8503
Maximum153832
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T15:24:00.206794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8503
5-th percentile8506.6
Q18514
median8573
Q38627
95-th percentile66693.2
Maximum153832
Range145329
Interquartile range (IQR)113

Descriptive statistics

Standard deviation33280.337
Coefficient of variation (CV)2.0135682
Kurtosis14.353418
Mean16528.041
Median Absolute Deviation (MAD)55
Skewness3.9950892
Sum1206547
Variance1.1075809 × 109
MonotonicityNot monotonic
2024-05-11T15:24:00.438633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
8511 7
 
7.7%
8608 4
 
4.4%
8514 4
 
4.4%
8573 4
 
4.4%
8632 4
 
4.4%
8617 3
 
3.3%
8626 3
 
3.3%
8507 3
 
3.3%
8627 2
 
2.2%
8510 2
 
2.2%
Other values (33) 37
40.7%
(Missing) 18
19.8%
ValueCountFrequency (%)
8503 2
 
2.2%
8504 1
 
1.1%
8506 1
 
1.1%
8507 3
3.3%
8510 2
 
2.2%
8511 7
7.7%
8513 1
 
1.1%
8514 4
4.4%
8523 1
 
1.1%
8524 1
 
1.1%
ValueCountFrequency (%)
153832 1
 
1.1%
153813 1
 
1.1%
153806 1
 
1.1%
153755 1
 
1.1%
8652 2
2.2%
8645 1
 
1.1%
8642 1
 
1.1%
8638 1
 
1.1%
8636 1
 
1.1%
8632 4
4.4%

사업장명
Text

Distinct81
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-05-11T15:24:00.901155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.1208791
Min length2

Characters and Unicode

Total characters739
Distinct characters166
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)81.3%

Sample

1st row수도안경원
2nd row밝은눈안경원
3rd row정옥안경원
4th row한독안경원
5th row안경산책
ValueCountFrequency (%)
안경 5
 
4.1%
착한안경 4
 
3.3%
안경랜드 3
 
2.5%
콘택트 3
 
2.5%
안경콘택트 3
 
2.5%
안경마당 2
 
1.6%
글라스 2
 
1.6%
시흥점 2
 
1.6%
1001안경 2
 
1.6%
트루아이 2
 
1.6%
Other values (89) 94
77.0%
2024-05-11T15:24:01.621618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 81
 
11.0%
경 81
 
11.0%
31
 
4.2%
원 28
 
3.8%
점 25
 
3.4%
트 22
 
3.0%
아 16
 
2.2%
택 15
 
2.0%
콘 15
 
2.0%
산 13
 
1.8%
Other values (156) 412
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 634
85.8%
Space Separator 31
 
4.2%
Decimal Number 26
 
3.5%
Open Punctuation 13
 
1.8%
Close Punctuation 13
 
1.8%
Uppercase Letter 13
 
1.8%
Lowercase Letter 7
 
0.9%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 81
 
12.8%
경 81
 
12.8%
원 28
 
4.4%
점 25
 
3.9%
트 22
 
3.5%
아 16
 
2.5%
택 15
 
2.4%
콘 15
 
2.4%
산 13
 
2.1%
이 13
 
2.1%
Other values (129) 325
51.3%
Uppercase Letter
ValueCountFrequency (%)
O 3
23.1%
E 2
15.4%
N 2
15.4%
L 1
 
7.7%
A 1
 
7.7%
C 1
 
7.7%
Y 1
 
7.7%
G 1
 
7.7%
J 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
0 11
42.3%
1 10
38.5%
5 1
 
3.8%
7 1
 
3.8%
2 1
 
3.8%
9 1
 
3.8%
3 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
s 2
28.6%
l 1
14.3%
a 1
14.3%
e 1
14.3%
d 1
14.3%
o 1
14.3%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 634
85.8%
Common 85
 
11.5%
Latin 20
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 81
 
12.8%
경 81
 
12.8%
원 28
 
4.4%
점 25
 
3.9%
트 22
 
3.5%
아 16
 
2.5%
택 15
 
2.4%
콘 15
 
2.4%
산 13
 
2.1%
이 13
 
2.1%
Other values (129) 325
51.3%
Latin
ValueCountFrequency (%)
O 3
15.0%
E 2
 
10.0%
N 2
 
10.0%
s 2
 
10.0%
L 1
 
5.0%
A 1
 
5.0%
C 1
 
5.0%
Y 1
 
5.0%
G 1
 
5.0%
l 1
 
5.0%
Other values (5) 5
25.0%
Common
ValueCountFrequency (%)
31
36.5%
( 13
15.3%
) 13
15.3%
0 11
 
12.9%
1 10
 
11.8%
5 1
 
1.2%
& 1
 
1.2%
, 1
 
1.2%
7 1
 
1.2%
2 1
 
1.2%
Other values (2) 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 634
85.8%
ASCII 105
 
14.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 81
 
12.8%
경 81
 
12.8%
원 28
 
4.4%
점 25
 
3.9%
트 22
 
3.5%
아 16
 
2.5%
택 15
 
2.4%
콘 15
 
2.4%
산 13
 
2.1%
이 13
 
2.1%
Other values (129) 325
51.3%
ASCII
ValueCountFrequency (%)
31
29.5%
( 13
12.4%
) 13
12.4%
0 11
 
10.5%
1 10
 
9.5%
O 3
 
2.9%
E 2
 
1.9%
N 2
 
1.9%
s 2
 
1.9%
L 1
 
1.0%
Other values (17) 17
16.2%

최종수정일자
Date

Distinct90
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size860.0 B
Minimum2008-12-15 17:27:28
Maximum2024-03-22 09:53:23
2024-05-11T15:24:01.856414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:02.126694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
I
55 
U
36 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 55
60.4%
U 36
39.6%

Length

2024-05-11T15:24:02.395835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:02.564372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 55
60.4%
u 36
39.6%

데이터갱신일자
Date

Distinct47
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Memory size860.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:04:00
2024-05-11T15:24:02.748055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:02.990417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing91
Missing (%)100.0%
Memory size951.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)77.6%
Missing15
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean190826.52
Minimum189055.14
Maximum192361.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T15:24:03.273940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189055.14
5-th percentile189538.02
Q1190119.46
median191139.09
Q3191337.84
95-th percentile191823.03
Maximum192361.46
Range3306.3225
Interquartile range (IQR)1218.3773

Descriptive statistics

Standard deviation769.73086
Coefficient of variation (CV)0.0040336682
Kurtosis-0.79542669
Mean190826.52
Median Absolute Deviation (MAD)352.4264
Skewness-0.50533543
Sum14502815
Variance592485.59
MonotonicityNot monotonic
2024-05-11T15:24:03.562497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190119.463375612 4
 
4.4%
191823.026849977 3
 
3.3%
189538.020935968 3
 
3.3%
190809.507840375 2
 
2.2%
190860.825733675 2
 
2.2%
189662.959175776 2
 
2.2%
189878.584063836 2
 
2.2%
191281.882201185 2
 
2.2%
190704.904312713 2
 
2.2%
189722.178532426 2
 
2.2%
Other values (49) 52
57.1%
(Missing) 15
 
16.5%
ValueCountFrequency (%)
189055.138252216 1
 
1.1%
189378.332493727 1
 
1.1%
189467.124186925 1
 
1.1%
189538.020935968 3
3.3%
189662.959175776 2
2.2%
189685.516219475 1
 
1.1%
189722.178532426 2
2.2%
189759.713050655 1
 
1.1%
189790.323886715 1
 
1.1%
189844.09058809 1
 
1.1%
ValueCountFrequency (%)
192361.460767692 1
 
1.1%
191948.466942039 1
 
1.1%
191901.802729439 1
 
1.1%
191823.026849977 3
3.3%
191793.549910441 1
 
1.1%
191747.816778024 1
 
1.1%
191606.939761049 2
2.2%
191506.396738317 1
 
1.1%
191501.366737525 1
 
1.1%
191481.675294989 1
 
1.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)77.6%
Missing15
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean440344.92
Minimum437689.38
Maximum442139.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T15:24:03.858076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437689.38
5-th percentile438480.51
Q1439042.38
median440587.05
Q3441716.68
95-th percentile442020.02
Maximum442139.51
Range4450.13
Interquartile range (IQR)2674.2998

Descriptive statistics

Standard deviation1374.2203
Coefficient of variation (CV)0.0031207815
Kurtosis-1.4930116
Mean440344.92
Median Absolute Deviation (MAD)1364.9626
Skewness-0.18700856
Sum33466214
Variance1888481.3
MonotonicityNot monotonic
2024-05-11T15:24:04.119400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441716.684586176 4
 
4.4%
438834.378061101 3
 
3.3%
441982.427934953 3
 
3.3%
440728.382273075 2
 
2.2%
441368.003228725 2
 
2.2%
442139.514492212 2
 
2.2%
441837.131132949 2
 
2.2%
438816.408043458 2
 
2.2%
440940.384414334 2
 
2.2%
441920.972770099 2
 
2.2%
Other values (49) 52
57.1%
(Missing) 15
 
16.5%
ValueCountFrequency (%)
437689.38449215 1
1.1%
437777.824339474 1
1.1%
437914.06299827 1
1.1%
438365.613175801 1
1.1%
438518.811960006 1
1.1%
438636.970338125 1
1.1%
438728.805383163 1
1.1%
438749.684135648 1
1.1%
438781.498511524 1
1.1%
438816.408043458 2
2.2%
ValueCountFrequency (%)
442139.514492212 2
2.2%
442066.99866487 1
 
1.1%
442026.468974479 1
 
1.1%
442017.86745811 1
 
1.1%
441982.427934953 3
3.3%
441958.334400683 1
 
1.1%
441945.691459493 1
 
1.1%
441920.972770099 2
2.2%
441902.681311108 1
 
1.1%
441837.131132949 2
2.2%

시력표수
Categorical

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
47 
0
25 
<NA>
16 
2
 
3

Length

Max length4
Median length1
Mean length1.5274725
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 47
51.6%
0 25
27.5%
<NA> 16
 
17.6%
2 3
 
3.3%

Length

2024-05-11T15:24:04.383991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:04.569318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 47
51.6%
0 25
27.5%
na 16
 
17.6%
2 3
 
3.3%

표본렌즈수
Categorical

Distinct5
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
41 
0
29 
<NA>
18 
3
 
2
2
 
1

Length

Max length4
Median length1
Mean length1.5934066
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 41
45.1%
0 29
31.9%
<NA> 18
19.8%
3 2
 
2.2%
2 1
 
1.1%

Length

2024-05-11T15:24:04.722316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:04.891906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
45.1%
0 29
31.9%
na 18
19.8%
3 2
 
2.2%
2 1
 
1.1%

측정의자수
Categorical

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
41 
0
29 
<NA>
18 
2
 
3

Length

Max length4
Median length1
Mean length1.5934066
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 41
45.1%
0 29
31.9%
<NA> 18
19.8%
2 3
 
3.3%

Length

2024-05-11T15:24:05.078007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:05.242703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
45.1%
0 29
31.9%
na 18
19.8%
2 3
 
3.3%

동공거리측정기수
Categorical

Distinct6
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
41 
0
26 
<NA>
16 
5
 
3
2
 
3

Length

Max length4
Median length1
Mean length1.5274725
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 41
45.1%
0 26
28.6%
<NA> 16
 
17.6%
5 3
 
3.3%
2 3
 
3.3%
3 2
 
2.2%

Length

2024-05-11T15:24:05.447037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:05.663341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
45.1%
0 26
28.6%
na 16
 
17.6%
5 3
 
3.3%
2 3
 
3.3%
3 2
 
2.2%

정점굴절계기수
Categorical

Distinct5
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
36 
0
25 
<NA>
16 
2
11 
3
 
3

Length

Max length4
Median length1
Mean length1.5274725
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 36
39.6%
0 25
27.5%
<NA> 16
17.6%
2 11
 
12.1%
3 3
 
3.3%

Length

2024-05-11T15:24:05.869514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:06.058030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 36
39.6%
0 25
27.5%
na 16
17.6%
2 11
 
12.1%
3 3
 
3.3%

조제용연마기수
Categorical

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
39 
0
30 
<NA>
19 
2
 
3

Length

Max length4
Median length1
Mean length1.6263736
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 39
42.9%
0 30
33.0%
<NA> 19
20.9%
2 3
 
3.3%

Length

2024-05-11T15:24:06.265572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:06.448306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 39
42.9%
0 30
33.0%
na 19
20.9%
2 3
 
3.3%

렌즈절단기수
Categorical

Distinct5
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
40 
0
30 
<NA>
19 
3
 
1
2
 
1

Length

Max length4
Median length1
Mean length1.6263736
Min length1

Unique

Unique2 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 40
44.0%
0 30
33.0%
<NA> 19
20.9%
3 1
 
1.1%
2 1
 
1.1%

Length

2024-05-11T15:24:06.657791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:06.894947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 40
44.0%
0 30
33.0%
na 19
20.9%
3 1
 
1.1%
2 1
 
1.1%

가열기수
Categorical

Distinct5
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
31 
0
30 
<NA>
19 
2
9 
3
 
2

Length

Max length4
Median length1
Mean length1.6263736
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 31
34.1%
0 30
33.0%
<NA> 19
20.9%
2 9
 
9.9%
3 2
 
2.2%

Length

2024-05-11T15:24:07.075998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:07.283590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 31
34.1%
0 30
33.0%
na 19
20.9%
2 9
 
9.9%
3 2
 
2.2%

안경세척기수
Categorical

Distinct5
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size860.0 B
0
29 
1
28 
<NA>
19 
2
10 
3
5 

Length

Max length4
Median length1
Mean length1.6263736
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 29
31.9%
1 28
30.8%
<NA> 19
20.9%
2 10
 
11.0%
3 5
 
5.5%

Length

2024-05-11T15:24:07.537888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:24:07.745607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 29
31.9%
1 28
30.8%
na 19
20.9%
2 10
 
11.0%
3 5
 
5.5%

총면적
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)97.8%
Missing45
Missing (%)49.5%
Infinite0
Infinite (%)0.0%
Mean66.282826
Minimum11.24
Maximum344.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-05-11T15:24:08.331495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11.24
5-th percentile22.0125
Q129.665
median46.775
Q372.45
95-th percentile206.675
Maximum344.86
Range333.62
Interquartile range (IQR)42.785

Descriptive statistics

Standard deviation65.334363
Coefficient of variation (CV)0.98569067
Kurtosis8.9374548
Mean66.282826
Median Absolute Deviation (MAD)20.745
Skewness2.8601171
Sum3049.01
Variance4268.579
MonotonicityNot monotonic
2024-05-11T15:24:08.529585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
26.26 2
 
2.2%
38.3 1
 
1.1%
31.3 1
 
1.1%
23.49 1
 
1.1%
83.54 1
 
1.1%
42.25 1
 
1.1%
25.8 1
 
1.1%
44.55 1
 
1.1%
38.28 1
 
1.1%
344.86 1
 
1.1%
Other values (35) 35
38.5%
(Missing) 45
49.5%
ValueCountFrequency (%)
11.24 1
1.1%
20.0 1
1.1%
22.0 1
1.1%
22.05 1
1.1%
22.08 1
1.1%
22.86 1
1.1%
23.49 1
1.1%
24.6 1
1.1%
25.8 1
1.1%
26.26 2
2.2%
ValueCountFrequency (%)
344.86 1
1.1%
274.0 1
1.1%
231.9 1
1.1%
131.0 1
1.1%
105.99 1
1.1%
105.0 1
1.1%
104.4 1
1.1%
104.0 1
1.1%
83.54 1
1.1%
78.65 1
1.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적
03170000PHMB21991317003508220000119910525<NA>1영업/정상13영업중<NA><NA><NA><NA>857-7966<NA>153801서울특별시 금천구 가산동 145번지 20호서울특별시 금천구 가산로 128 (가산동)8528수도안경원2021-01-21 16:54:36U2021-01-23 02:40:00.0<NA>190406.485225441652.977781000000000<NA>
13170000PHMB21991317003508220000219910612<NA>3폐업3폐업20181228<NA><NA><NA>803-2193<NA>153863서울특별시 금천구 시흥동 985번지 8호서울특별시 금천구 시흥대로 149, 105호 (시흥동, 신라상가)8638밝은눈안경원2019-05-23 14:59:42U2019-05-25 02:40:00.0<NA>191341.238749438365.61317611111111133.06
23170000PHMB21991317003508220000319910627<NA>3폐업3폐업20090701<NA><NA><NA>805-7755<NA>153816독산2동 378-242<NA><NA>정옥안경원2009-07-01 14:57:41I2018-08-31 23:59:59.0<NA><NA><NA>000000000<NA>
33170000PHMB21991317003508220000419910711<NA>3폐업3폐업20140103<NA><NA><NA>808-0551<NA>153832서울특별시 금천구 독산동 1044번지 10호서울특별시 금천구 독산로 171 (독산동)153832한독안경원2014-01-03 14:10:32I2018-08-31 23:59:59.0<NA>191430.251337440046.437705000000000<NA>
43170000PHMB21991317003508220000519910827<NA>3폐업3폐업20100120<NA><NA><NA>856-3039<NA>153808독산4동 179-12<NA><NA>안경산책2010-01-20 16:20:17I2018-08-31 23:59:59.0<NA><NA><NA>000000000<NA>
53170000PHMB21991317003508220000619910827<NA>3폐업3폐업20160722<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로58길 6 (시흥동)8628글라스 갤러리2016-07-25 10:02:17I2018-08-31 23:59:59.0<NA>191224.257274439053.64859911111111262.0
63170000PHMB2199131700350822000071991-08-31<NA>3폐업3폐업2024-03-24<NA><NA><NA>803-0431<NA><NA>서울특별시 금천구 시흥동 909번지 24호서울특별시 금천구 은행나무로 51 (시흥동)8642한독안경원2024-03-22 09:53:23U2023-12-02 22:04:00.0<NA>191793.54991438781.498512<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73170000PHMB21992317003508220000119920106<NA>1영업/정상13영업중<NA><NA><NA><NA>802-3116<NA>153857서울특별시 금천구 시흥동 856번지 25호서울특별시 금천구 독산로 135 (시흥동)8622안경산책2008-12-15 17:27:28I2018-08-31 23:59:59.0<NA>191506.396738439695.13606000000000<NA>
83170000PHMB21992317003508220000219920527<NA>1영업/정상13영업중<NA><NA><NA><NA>802-9922<NA>153864서울특별시 금천구 시흥동 999번지 47호서울특별시 금천구 시흥대로 235 (시흥동)8614박철웅안경원2008-12-15 17:27:28I2018-08-31 23:59:59.0<NA>191092.203634439187.456372000000000<NA>
93170000PHMB21993317003508220000119930623<NA>1영업/정상13영업중<NA><NA><NA><NA>863-2144<NA>153808서울특별시 금천구 독산동 192번지 2호서울특별시 금천구 독산로 258 (독산동)8557형제안경원2019-06-04 16:02:21U2019-06-06 02:40:00.0<NA>191332.240203440842.336063000000000<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적
813170000PHMB22021317003508220000120210401<NA>1영업/정상13영업중<NA><NA><NA><NA>02-853-5567<NA><NA>서울특별시 금천구 독산동 950-2 영남빌딩서울특별시 금천구 남부순환로 1384, 영남빌딩 1층 (독산동)8547남대문 안경2021-04-06 09:03:01I2021-04-08 00:22:58.0<NA>191481.675295441945.6914592<NA><NA>23<NA><NA><NA><NA>72.0
823170000PHMB2202131700350822000022021-05-14<NA>3폐업3폐업2022-12-07<NA><NA><NA>02-2085-0608<NA><NA>서울특별시 금천구 가산동 60-48서울특별시 금천구 디지털로9길 41, 108호 (가산동)8511아이킵안경2023-06-27 11:28:50U2022-12-05 22:09:00.0<NA>189844.090588441902.681311<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
833170000PHMB22021317003508220000320210820<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 1155 금천롯데캐슬골드파크3차 310동 B15호서울특별시 금천구 시흥대로 291, 310동 B15호 (독산동, 금천롯데캐슬골드파크3차)8608안경진정성 금천롯데캐슬점2021-08-22 09:02:26I2021-08-24 00:22:50.0<NA><NA><NA>10011000049.76
843170000PHMB22021317003508220000420211028<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 371-41 가산 에스케이 브이원 센터서울특별시 금천구 가산디지털1로 171, 가산 에스케이 브이원 센터 1층 110호 (가산동)8503뷰맵2021-10-28 16:17:39I2021-10-30 00:22:45.0<NA>189378.332494442066.99866510011000049.0
853170000PHMB22021317003508220000520211112<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 60-8 현대시티아울렛 가산점서울특별시 금천구 디지털로10길 9, 현대시티아울렛 가산점 지하1층 (가산동)8514ALO현대아울렛가산점2021-11-12 11:57:54I2021-11-14 00:22:45.0<NA>190119.463376441716.68458610011000071.6
863170000PHMB22022317003508220000119800703<NA>1영업/정상13영업중<NA><NA><NA><NA>2643-9084<NA><NA>서울특별시 금천구 독산동 1156 금천롯데캐슬골드파크4차 109호서울특별시 금천구 시흥대로 315, 금천롯데캐슬골드파크4차 109호 (독산동)8608캐슬안경2022-08-16 15:13:27U2021-12-07 23:08:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
873170000PHMB22022317003508220000220221124<NA>1영업/정상13영업중<NA><NA><NA><NA>02-807-3094<NA><NA>서울특별시 금천구 독산동 1037-4서울특별시 금천구 독산로 215, 101-103호 (독산동)86171001안경 위드렌즈(독산점)2022-11-24 13:39:20I2021-10-31 22:06:00.0<NA>191226.671549440428.265743<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
883170000PHMB2202331700350822000012023-03-28<NA>1영업/정상13영업중<NA><NA><NA><NA>02-863-9556<NA><NA>서울특별시 금천구 독산동 988-8서울특별시 금천구 시흥대로138길 33(독산동)8544독산안경박사2023-03-29 09:06:37I2022-12-02 21:01:00.0<NA>191125.756585441182.799013<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
893170000PHMB2202331700350822000022020-11-23<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 879-97서울특별시 금천구 금하로 645, 1층 (시흥동)8626안경집2023-07-27 16:09:10I2022-12-06 22:09:00.0<NA>191334.975382439133.203931<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
903170000PHMB2202331700350822000032023-08-01<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 371-50 에이스하이엔드타워3차 B104호서울특별시 금천구 가산디지털1로 145, 에이스하이엔드타워3차 B104호 (가산동)8506오투스안경원2023-08-01 15:54:35I2022-12-08 00:03:00.0<NA>189467.124187441780.005399<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>