Overview

Dataset statistics

Number of variables35
Number of observations213
Missing cells1556
Missing cells (%)20.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory62.9 KiB
Average record size in memory302.6 B

Variable types

Categorical16
Text5
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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-16395/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
표본렌즈수 is highly imbalanced (54.5%)Imbalance
동공거리측정기수 is highly imbalanced (52.8%)Imbalance
인허가취소일자 has 213 (100.0%) missing valuesMissing
폐업일자 has 114 (53.5%) missing valuesMissing
휴업시작일자 has 213 (100.0%) missing valuesMissing
휴업종료일자 has 213 (100.0%) missing valuesMissing
재개업일자 has 213 (100.0%) missing valuesMissing
전화번호 has 11 (5.2%) missing valuesMissing
소재지면적 has 213 (100.0%) missing valuesMissing
지번주소 has 14 (6.6%) missing valuesMissing
도로명주소 has 18 (8.5%) missing valuesMissing
도로명우편번호 has 23 (10.8%) missing valuesMissing
업태구분명 has 213 (100.0%) missing valuesMissing
좌표정보(X) has 19 (8.9%) missing valuesMissing
좌표정보(Y) has 19 (8.9%) missing valuesMissing
총면적 has 60 (28.2%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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 started2024-04-06 13:15:49.691867
Analysis finished2024-04-06 13:15:50.440484
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3130000
213 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 213
100.0%

Length

2024-04-06T22:15:50.508212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:50.628781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 213
100.0%

관리번호
Text

UNIQUE 

Distinct213
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-06T22:15:50.854843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters5325
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

Unique213 ?
Unique (%)100.0%

Sample

1st rowPHMB219763130033082200001
2nd rowPHMB219783130033082200001
3rd rowPHMB219813130033082200001
4th rowPHMB219823130033082200001
5th rowPHMB219833130033082200001
ValueCountFrequency (%)
phmb219763130033082200001 1
 
0.5%
phmb220133130033082200005 1
 
0.5%
phmb220153130033082200007 1
 
0.5%
phmb220153130033082200008 1
 
0.5%
phmb220153130033082200009 1
 
0.5%
phmb220153130033082200010 1
 
0.5%
phmb220153130033082200011 1
 
0.5%
phmb220163130033082200001 1
 
0.5%
phmb220163130033082200002 1
 
0.5%
phmb220163130033082200003 1
 
0.5%
Other values (203) 203
95.3%
2024-04-06T22:15:51.242156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1732
32.5%
2 914
17.2%
3 897
16.8%
1 435
 
8.2%
8 258
 
4.8%
P 213
 
4.0%
H 213
 
4.0%
M 213
 
4.0%
B 213
 
4.0%
9 66
 
1.2%
Other values (4) 171
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4473
84.0%
Uppercase Letter 852
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1732
38.7%
2 914
20.4%
3 897
20.1%
1 435
 
9.7%
8 258
 
5.8%
9 66
 
1.5%
4 53
 
1.2%
7 42
 
0.9%
5 41
 
0.9%
6 35
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
P 213
25.0%
H 213
25.0%
M 213
25.0%
B 213
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4473
84.0%
Latin 852
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1732
38.7%
2 914
20.4%
3 897
20.1%
1 435
 
9.7%
8 258
 
5.8%
9 66
 
1.5%
4 53
 
1.2%
7 42
 
0.9%
5 41
 
0.9%
6 35
 
0.8%
Latin
ValueCountFrequency (%)
P 213
25.0%
H 213
25.0%
M 213
25.0%
B 213
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1732
32.5%
2 914
17.2%
3 897
16.8%
1 435
 
8.2%
8 258
 
4.8%
P 213
 
4.0%
H 213
 
4.0%
M 213
 
4.0%
B 213
 
4.0%
9 66
 
1.2%
Other values (4) 171
 
3.2%

인허가일자
Date

Distinct208
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1976-09-24 00:00:00
Maximum2024-03-22 00:00:00
2024-04-06T22:15:51.403461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:15:51.562541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
115 
3
98 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 115
54.0%
3 98
46.0%

Length

2024-04-06T22:15:51.757661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:51.884254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 115
54.0%
3 98
46.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
영업/정상
115 
폐업
98 

Length

Max length5
Median length5
Mean length3.6197183
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 115
54.0%
폐업 98
46.0%

Length

2024-04-06T22:15:52.028589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:52.162497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 115
54.0%
폐업 98
46.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
13
115 
3
98 

Length

Max length2
Median length2
Mean length1.5399061
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 115
54.0%
3 98
46.0%

Length

2024-04-06T22:15:52.328588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:52.439120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 115
54.0%
3 98
46.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
영업중
115 
폐업
98 

Length

Max length3
Median length3
Mean length2.5399061
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 115
54.0%
폐업 98
46.0%

Length

2024-04-06T22:15:52.565992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:52.688301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 115
54.0%
폐업 98
46.0%

폐업일자
Date

MISSING 

Distinct96
Distinct (%)97.0%
Missing114
Missing (%)53.5%
Memory size1.8 KiB
Minimum2009-01-15 00:00:00
Maximum2024-03-20 00:00:00
2024-04-06T22:15:52.801912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:15:52.964103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

전화번호
Text

MISSING 

Distinct195
Distinct (%)96.5%
Missing11
Missing (%)5.2%
Memory size1.8 KiB
2024-04-06T22:15:53.240926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10
Min length8

Characters and Unicode

Total characters2020
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

Unique189 ?
Unique (%)93.6%

Sample

1st row713-0761
2nd row363-1575
3rd row334-0821
4th row714-6103
5th row02-313-7517
ValueCountFrequency (%)
02-333-8199 3
 
1.5%
02-333-3453 2
 
1.0%
3143-5055 2
 
1.0%
333-8199 2
 
1.0%
393-1141 2
 
1.0%
376-2002 2
 
1.0%
713-0761 1
 
0.5%
02-711-7973 1
 
0.5%
313-5251 1
 
0.5%
02-334-0034 1
 
0.5%
Other values (185) 185
91.6%
2024-04-06T22:15:53.787292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 316
15.6%
3 312
15.4%
0 306
15.1%
2 251
12.4%
1 159
7.9%
7 152
7.5%
4 111
 
5.5%
5 110
 
5.4%
6 106
 
5.2%
9 101
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1704
84.4%
Dash Punctuation 316
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 312
18.3%
0 306
18.0%
2 251
14.7%
1 159
9.3%
7 152
8.9%
4 111
 
6.5%
5 110
 
6.5%
6 106
 
6.2%
9 101
 
5.9%
8 96
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 316
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2020
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 316
15.6%
3 312
15.4%
0 306
15.1%
2 251
12.4%
1 159
7.9%
7 152
7.5%
4 111
 
5.5%
5 110
 
5.4%
6 106
 
5.2%
9 101
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 316
15.6%
3 312
15.4%
0 306
15.1%
2 251
12.4%
1 159
7.9%
7 152
7.5%
4 111
 
5.5%
5 110
 
5.4%
6 106
 
5.2%
9 101
 
5.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

소재지우편번호
Categorical

Distinct45
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
91 
121210
15 
121270
 
9
121200
 
8
121100
 
7
Other values (40)
83 

Length

Max length7
Median length6
Mean length5.1596244
Min length4

Unique

Unique21 ?
Unique (%)9.9%

Sample

1st row121040
2nd row121010
3rd row121230
4th row121090
5th row121010

Common Values

ValueCountFrequency (%)
<NA> 91
42.7%
121210 15
 
7.0%
121270 9
 
4.2%
121200 8
 
3.8%
121100 7
 
3.3%
121010 7
 
3.3%
121020 6
 
2.8%
121220 5
 
2.3%
121829 5
 
2.3%
121827 4
 
1.9%
Other values (35) 56
26.3%

Length

2024-04-06T22:15:53.952883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 91
42.7%
121210 15
 
7.0%
121270 9
 
4.2%
121200 8
 
3.8%
121100 7
 
3.3%
121010 7
 
3.3%
121020 6
 
2.8%
121220 5
 
2.3%
121829 5
 
2.3%
121230 4
 
1.9%
Other values (35) 56
26.3%

지번주소
Text

MISSING 

Distinct192
Distinct (%)96.5%
Missing14
Missing (%)6.6%
Memory size1.8 KiB
2024-04-06T22:15:54.241821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length25.58794
Min length15

Characters and Unicode

Total characters5092
Distinct characters207
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)93.5%

Sample

1st row서울특별시 마포구 도화2동 250-13
2nd row서울특별시 마포구 아현2동282-17
3rd row서울특별시 마포구 망원1동338-1
4th row서울특별시 마포구 염리동159-1
5th row서울특별시 마포구 아현2동347-1
ValueCountFrequency (%)
서울특별시 198
19.6%
마포구 197
19.5%
1층 48
 
4.8%
서교동 37
 
3.7%
동교동 18
 
1.8%
합정동 16
 
1.6%
1호 15
 
1.5%
상암동 15
 
1.5%
상수동 10
 
1.0%
2층 8
 
0.8%
Other values (310) 448
44.4%
2024-04-06T22:15:54.851595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
820
 
16.1%
1 271
 
5.3%
서 247
 
4.9%
동 228
 
4.5%
마 207
 
4.1%
포 206
 
4.0%
시 201
 
3.9%
구 199
 
3.9%
울 198
 
3.9%
별 198
 
3.9%
Other values (197) 2317
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3065
60.2%
Decimal Number 1066
 
20.9%
Space Separator 820
 
16.1%
Dash Punctuation 71
 
1.4%
Uppercase Letter 52
 
1.0%
Other Punctuation 6
 
0.1%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%
Letter Number 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 247
 
8.1%
동 228
 
7.4%
마 207
 
6.8%
포 206
 
6.7%
시 201
 
6.6%
구 199
 
6.5%
울 198
 
6.5%
별 198
 
6.5%
특 198
 
6.5%
지 127
 
4.1%
Other values (165) 1056
34.5%
Uppercase Letter
ValueCountFrequency (%)
G 10
19.2%
T 7
13.5%
K 6
11.5%
B 6
11.5%
I 6
11.5%
L 5
9.6%
C 2
 
3.8%
A 2
 
3.8%
F 2
 
3.8%
Y 1
 
1.9%
Other values (5) 5
9.6%
Decimal Number
ValueCountFrequency (%)
1 271
25.4%
3 150
14.1%
2 141
13.2%
4 118
11.1%
5 88
 
8.3%
0 80
 
7.5%
6 65
 
6.1%
7 62
 
5.8%
8 60
 
5.6%
9 31
 
2.9%
Space Separator
ValueCountFrequency (%)
820
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3065
60.2%
Common 1974
38.8%
Latin 53
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 247
 
8.1%
동 228
 
7.4%
마 207
 
6.8%
포 206
 
6.7%
시 201
 
6.6%
구 199
 
6.5%
울 198
 
6.5%
별 198
 
6.5%
특 198
 
6.5%
지 127
 
4.1%
Other values (165) 1056
34.5%
Common
ValueCountFrequency (%)
820
41.5%
1 271
 
13.7%
3 150
 
7.6%
2 141
 
7.1%
4 118
 
6.0%
5 88
 
4.5%
0 80
 
4.1%
- 71
 
3.6%
6 65
 
3.3%
7 62
 
3.1%
Other values (6) 108
 
5.5%
Latin
ValueCountFrequency (%)
G 10
18.9%
T 7
13.2%
K 6
11.3%
B 6
11.3%
I 6
11.3%
L 5
9.4%
C 2
 
3.8%
A 2
 
3.8%
F 2
 
3.8%
Ⅱ 1
 
1.9%
Other values (6) 6
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3065
60.2%
ASCII 2026
39.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
820
40.5%
1 271
 
13.4%
3 150
 
7.4%
2 141
 
7.0%
4 118
 
5.8%
5 88
 
4.3%
0 80
 
3.9%
- 71
 
3.5%
6 65
 
3.2%
7 62
 
3.1%
Other values (21) 160
 
7.9%
Hangul
ValueCountFrequency (%)
서 247
 
8.1%
동 228
 
7.4%
마 207
 
6.8%
포 206
 
6.7%
시 201
 
6.6%
구 199
 
6.5%
울 198
 
6.5%
별 198
 
6.5%
특 198
 
6.5%
지 127
 
4.1%
Other values (165) 1056
34.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct191
Distinct (%)97.9%
Missing18
Missing (%)8.5%
Memory size1.8 KiB
2024-04-06T22:15:55.196820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length47
Mean length32.010256
Min length22

Characters and Unicode

Total characters6242
Distinct characters234
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)96.4%

Sample

1st row서울특별시 마포구 도화길 6-12 (도화동)
2nd row서울특별시 마포구 굴레방로 7 (아현동)
3rd row서울특별시 마포구 포은로 68 (망원동)
4th row서울특별시 마포구 백범로 138-1 (염리동)
5th row서울특별시 마포구 신촌로 236-1 (아현동)
ValueCountFrequency (%)
서울특별시 195
 
15.6%
마포구 195
 
15.6%
1층 64
 
5.1%
서교동 45
 
3.6%
동교동 23
 
1.8%
양화로 20
 
1.6%
합정동 18
 
1.4%
월드컵북로 18
 
1.4%
2층 17
 
1.4%
망원동 16
 
1.3%
Other values (319) 638
51.1%
2024-04-06T22:15:55.703930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1054
 
16.9%
1 288
 
4.6%
서 247
 
4.0%
동 240
 
3.8%
마 237
 
3.8%
포 224
 
3.6%
울 213
 
3.4%
시 200
 
3.2%
, 200
 
3.2%
) 197
 
3.2%
Other values (224) 3142
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3627
58.1%
Space Separator 1054
 
16.9%
Decimal Number 873
 
14.0%
Other Punctuation 200
 
3.2%
Close Punctuation 197
 
3.2%
Open Punctuation 197
 
3.2%
Uppercase Letter 53
 
0.8%
Dash Punctuation 27
 
0.4%
Lowercase Letter 12
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 247
 
6.8%
동 240
 
6.6%
마 237
 
6.5%
포 224
 
6.2%
울 213
 
5.9%
시 200
 
5.5%
구 196
 
5.4%
별 195
 
5.4%
특 195
 
5.4%
로 190
 
5.2%
Other values (180) 1490
41.1%
Uppercase Letter
ValueCountFrequency (%)
B 10
18.9%
L 6
11.3%
G 6
11.3%
C 4
 
7.5%
R 3
 
5.7%
T 3
 
5.7%
D 3
 
5.7%
E 2
 
3.8%
A 2
 
3.8%
W 2
 
3.8%
Other values (9) 12
22.6%
Decimal Number
ValueCountFrequency (%)
1 288
33.0%
2 136
15.6%
3 88
 
10.1%
0 77
 
8.8%
4 59
 
6.8%
5 55
 
6.3%
6 54
 
6.2%
9 41
 
4.7%
7 39
 
4.5%
8 36
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
25.0%
i 2
16.7%
n 2
16.7%
r 1
 
8.3%
t 1
 
8.3%
g 1
 
8.3%
s 1
 
8.3%
u 1
 
8.3%
Space Separator
ValueCountFrequency (%)
1054
100.0%
Other Punctuation
ValueCountFrequency (%)
, 200
100.0%
Close Punctuation
ValueCountFrequency (%)
) 197
100.0%
Open Punctuation
ValueCountFrequency (%)
( 197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3627
58.1%
Common 2549
40.8%
Latin 66
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 247
 
6.8%
동 240
 
6.6%
마 237
 
6.5%
포 224
 
6.2%
울 213
 
5.9%
시 200
 
5.5%
구 196
 
5.4%
별 195
 
5.4%
특 195
 
5.4%
로 190
 
5.2%
Other values (180) 1490
41.1%
Latin
ValueCountFrequency (%)
B 10
15.2%
L 6
 
9.1%
G 6
 
9.1%
C 4
 
6.1%
R 3
 
4.5%
T 3
 
4.5%
D 3
 
4.5%
e 3
 
4.5%
E 2
 
3.0%
i 2
 
3.0%
Other values (18) 24
36.4%
Common
ValueCountFrequency (%)
1054
41.3%
1 288
 
11.3%
, 200
 
7.8%
) 197
 
7.7%
( 197
 
7.7%
2 136
 
5.3%
3 88
 
3.5%
0 77
 
3.0%
4 59
 
2.3%
5 55
 
2.2%
Other values (6) 198
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3627
58.1%
ASCII 2614
41.9%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1054
40.3%
1 288
 
11.0%
, 200
 
7.7%
) 197
 
7.5%
( 197
 
7.5%
2 136
 
5.2%
3 88
 
3.4%
0 77
 
2.9%
4 59
 
2.3%
5 55
 
2.1%
Other values (33) 263
 
10.1%
Hangul
ValueCountFrequency (%)
서 247
 
6.8%
동 240
 
6.6%
마 237
 
6.5%
포 224
 
6.2%
울 213
 
5.9%
시 200
 
5.5%
구 196
 
5.4%
별 195
 
5.4%
특 195
 
5.4%
로 190
 
5.2%
Other values (180) 1490
41.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct109
Distinct (%)57.4%
Missing23
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean14581.279
Minimum3907
Maximum121887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-06T22:15:55.878450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3907
5-th percentile3925
Q14023
median4051
Q34116
95-th percentile121818.1
Maximum121887
Range117980
Interquartile range (IQR)93

Descriptive statistics

Standard deviation33678.617
Coefficient of variation (CV)2.3097163
Kurtosis6.4754148
Mean14581.279
Median Absolute Deviation (MAD)50
Skewness2.8995267
Sum2770443
Variance1.1342492 × 109
MonotonicityNot monotonic
2024-04-06T22:15:56.023639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4049 11
 
5.2%
4055 8
 
3.8%
4050 7
 
3.3%
4040 6
 
2.8%
3925 6
 
2.8%
4053 5
 
2.3%
4051 5
 
2.3%
4012 3
 
1.4%
4047 3
 
1.4%
3964 3
 
1.4%
Other values (99) 133
62.4%
(Missing) 23
 
10.8%
ValueCountFrequency (%)
3907 1
 
0.5%
3908 1
 
0.5%
3918 1
 
0.5%
3924 2
 
0.9%
3925 6
2.8%
3927 1
 
0.5%
3932 2
 
0.9%
3938 1
 
0.5%
3940 1
 
0.5%
3946 2
 
0.9%
ValueCountFrequency (%)
121887 1
0.5%
121885 2
0.9%
121873 1
0.5%
121861 1
0.5%
121838 2
0.9%
121837 1
0.5%
121819 2
0.9%
121817 2
0.9%
121807 1
0.5%
121803 1
0.5%

사업장명
Text

Distinct208
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-06T22:15:56.257773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length17
Mean length8.0328638
Min length2

Characters and Unicode

Total characters1711
Distinct characters283
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203 ?
Unique (%)95.3%

Sample

1st row아이닥터안경
2nd row동명사안경점
3rd row서독안경원
4th row아이글라스안경
5th row세란안경원
ValueCountFrequency (%)
홍대점 7
 
2.6%
안경원 5
 
1.8%
안경 4
 
1.5%
합정점 3
 
1.1%
인키안경원 3
 
1.1%
eye 3
 
1.1%
글라스스토리 3
 
1.1%
으뜸50안경 3
 
1.1%
탑안경원 2
 
0.7%
안경콘택트 2
 
0.7%
Other values (227) 239
87.2%
2024-04-06T22:15:56.637075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 143
 
8.4%
경 140
 
8.2%
점 71
 
4.1%
62
 
3.6%
원 60
 
3.5%
이 57
 
3.3%
스 47
 
2.7%
아 46
 
2.7%
즈 33
 
1.9%
대 32
 
1.9%
Other values (273) 1020
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1452
84.9%
Uppercase Letter 84
 
4.9%
Space Separator 62
 
3.6%
Lowercase Letter 33
 
1.9%
Open Punctuation 28
 
1.6%
Close Punctuation 28
 
1.6%
Decimal Number 22
 
1.3%
Currency Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 143
 
9.8%
경 140
 
9.6%
점 71
 
4.9%
원 60
 
4.1%
이 57
 
3.9%
스 47
 
3.2%
아 46
 
3.2%
즈 33
 
2.3%
대 32
 
2.2%
트 31
 
2.1%
Other values (223) 792
54.5%
Uppercase Letter
ValueCountFrequency (%)
E 10
11.9%
M 7
 
8.3%
C 6
 
7.1%
Y 6
 
7.1%
F 6
 
7.1%
L 6
 
7.1%
I 6
 
7.1%
A 6
 
7.1%
N 4
 
4.8%
O 3
 
3.6%
Other values (14) 24
28.6%
Lowercase Letter
ValueCountFrequency (%)
o 7
21.2%
e 5
15.2%
y 3
9.1%
a 2
 
6.1%
c 2
 
6.1%
r 2
 
6.1%
p 2
 
6.1%
b 2
 
6.1%
d 2
 
6.1%
u 1
 
3.0%
Other values (5) 5
15.2%
Decimal Number
ValueCountFrequency (%)
0 9
40.9%
5 8
36.4%
1 2
 
9.1%
2 1
 
4.5%
9 1
 
4.5%
7 1
 
4.5%
Space Separator
ValueCountFrequency (%)
62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Currency Symbol
ValueCountFrequency (%)
￦ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1452
84.9%
Common 142
 
8.3%
Latin 117
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 143
 
9.8%
경 140
 
9.6%
점 71
 
4.9%
원 60
 
4.1%
이 57
 
3.9%
스 47
 
3.2%
아 46
 
3.2%
즈 33
 
2.3%
대 32
 
2.2%
트 31
 
2.1%
Other values (223) 792
54.5%
Latin
ValueCountFrequency (%)
E 10
 
8.5%
M 7
 
6.0%
o 7
 
6.0%
C 6
 
5.1%
Y 6
 
5.1%
F 6
 
5.1%
L 6
 
5.1%
I 6
 
5.1%
A 6
 
5.1%
e 5
 
4.3%
Other values (29) 52
44.4%
Common
ValueCountFrequency (%)
62
43.7%
( 28
19.7%
) 28
19.7%
0 9
 
6.3%
5 8
 
5.6%
1 2
 
1.4%
2 1
 
0.7%
￦ 1
 
0.7%
9 1
 
0.7%
7 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1452
84.9%
ASCII 258
 
15.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 143
 
9.8%
경 140
 
9.6%
점 71
 
4.9%
원 60
 
4.1%
이 57
 
3.9%
스 47
 
3.2%
아 46
 
3.2%
즈 33
 
2.3%
대 32
 
2.2%
트 31
 
2.1%
Other values (223) 792
54.5%
ASCII
ValueCountFrequency (%)
62
24.0%
( 28
 
10.9%
) 28
 
10.9%
E 10
 
3.9%
0 9
 
3.5%
5 8
 
3.1%
M 7
 
2.7%
o 7
 
2.7%
C 6
 
2.3%
Y 6
 
2.3%
Other values (39) 87
33.7%
None
ValueCountFrequency (%)
￦ 1
100.0%

최종수정일자
Date

UNIQUE 

Distinct213
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2009-04-06 14:05:56
Maximum2024-03-25 13:39:08
2024-04-06T22:15:56.806449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:15:56.968499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
I
121 
U
92 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 121
56.8%
U 92
43.2%

Length

2024-04-06T22:15:57.099381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:57.528135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 121
56.8%
u 92
43.2%

데이터갱신일자
Date

Distinct88
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:07:00
2024-04-06T22:15:57.637022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:15:57.788147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing213
Missing (%)100.0%
Memory size2.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct167
Distinct (%)86.1%
Missing19
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean193237.9
Minimum189315.37
Maximum203582.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-06T22:15:57.952849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189315.37
5-th percentile190262.93
Q1192302.51
median193112.37
Q3194164.94
95-th percentile195891.02
Maximum203582.6
Range14267.225
Interquartile range (IQR)1862.4265

Descriptive statistics

Standard deviation1716.9712
Coefficient of variation (CV)0.0088852716
Kurtosis5.8435659
Mean193237.9
Median Absolute Deviation (MAD)904.86079
Skewness1.081684
Sum37488152
Variance2947990.1
MonotonicityNot monotonic
2024-04-06T22:15:58.097059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192207.507628577 4
 
1.9%
193090.782177835 3
 
1.4%
192902.636839946 3
 
1.4%
193166.430144679 3
 
1.4%
192928.722248904 3
 
1.4%
190125.564768858 3
 
1.4%
192907.801267495 2
 
0.9%
191010.381048042 2
 
0.9%
196057.949965838 2
 
0.9%
193194.919383183 2
 
0.9%
Other values (157) 167
78.4%
(Missing) 19
 
8.9%
ValueCountFrequency (%)
189315.370584751 1
 
0.5%
189683.413598 1
 
0.5%
190086.625449279 1
 
0.5%
190111.0 1
 
0.5%
190125.564768858 3
1.4%
190193.738328 1
 
0.5%
190250.875091908 2
0.9%
190269.417315 1
 
0.5%
190282.759163473 1
 
0.5%
190312.037649 1
 
0.5%
ValueCountFrequency (%)
203582.595678321 1
0.5%
196485.605930116 1
0.5%
196338.449433848 1
0.5%
196057.949965838 2
0.9%
196002.238594738 1
0.5%
195998.895889935 1
0.5%
195978.784376311 1
0.5%
195978.443676521 1
0.5%
195967.719264 1
0.5%
195849.727721903 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct167
Distinct (%)86.1%
Missing19
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean450102.97
Minimum412876.82
Maximum453647.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-06T22:15:58.266089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum412876.82
5-th percentile448871.76
Q1449620.48
median450231.49
Q3450514.06
95-th percentile453090.15
Maximum453647.35
Range40770.53
Interquartile range (IQR)893.58639

Descriptive statistics

Standard deviation2878.8063
Coefficient of variation (CV)0.0063958837
Kurtosis146.5145
Mean450102.97
Median Absolute Deviation (MAD)414.22293
Skewness-11.225782
Sum87319976
Variance8287525.4
MonotonicityNot monotonic
2024-04-06T22:15:58.417988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449593.157466657 4
 
1.9%
449520.194492732 3
 
1.4%
449559.001671018 3
 
1.4%
450425.852790862 3
 
1.4%
449730.225257157 3
 
1.4%
453090.149821248 3
 
1.4%
450383.115207223 2
 
0.9%
451972.154018501 2
 
0.9%
449897.213071289 2
 
0.9%
450887.063662706 2
 
0.9%
Other values (157) 167
78.4%
(Missing) 19
 
8.9%
ValueCountFrequency (%)
412876.819130805 1
0.5%
448606.519628513 1
0.5%
448616.6144333 1
0.5%
448644.311298762 2
0.9%
448652.176751796 1
0.5%
448688.192562795 1
0.5%
448787.973520895 1
0.5%
448813.415128501 1
0.5%
448837.0 1
0.5%
448890.481663742 1
0.5%
ValueCountFrequency (%)
453647.349314742 1
 
0.5%
453407.67377 1
 
0.5%
453400.897594 1
 
0.5%
453326.849506 1
 
0.5%
453248.0 1
 
0.5%
453247.163288 1
 
0.5%
453231.427685063 1
 
0.5%
453213.198487908 1
 
0.5%
453090.149821248 3
1.4%
453017.867202928 2
0.9%

시력표수
Categorical

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
158 
<NA>
50 
2
 
5

Length

Max length4
Median length1
Mean length1.7042254
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 158
74.2%
<NA> 50
 
23.5%
2 5
 
2.3%

Length

2024-04-06T22:15:58.582510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:58.692946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 158
74.2%
na 50
 
23.5%
2 5
 
2.3%

표본렌즈수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
145 
<NA>
58 
2
 
5
0
 
3
4
 
1

Length

Max length4
Median length1
Mean length1.8169014
Min length1

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
1 145
68.1%
<NA> 58
 
27.2%
2 5
 
2.3%
0 3
 
1.4%
4 1
 
0.5%
6 1
 
0.5%

Length

2024-04-06T22:15:58.824927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:58.962085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 145
68.1%
na 58
 
27.2%
2 5
 
2.3%
0 3
 
1.4%
4 1
 
0.5%
6 1
 
0.5%

측정의자수
Categorical

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
146 
<NA>
56 
2
 
8
0
 
3

Length

Max length4
Median length1
Mean length1.7887324
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 146
68.5%
<NA> 56
 
26.3%
2 8
 
3.8%
0 3
 
1.4%

Length

2024-04-06T22:15:59.089670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:59.206198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 146
68.5%
na 56
 
26.3%
2 8
 
3.8%
0 3
 
1.4%

동공거리측정기수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
157 
<NA>
52 
2
 
3
4
 
1

Length

Max length4
Median length1
Mean length1.7323944
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
1 157
73.7%
<NA> 52
 
24.4%
2 3
 
1.4%
4 1
 
0.5%

Length

2024-04-06T22:15:59.335118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:59.446626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 157
73.7%
na 52
 
24.4%
2 3
 
1.4%
4 1
 
0.5%

정점굴절계기수
Categorical

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
145 
<NA>
51 
2
 
13
3
 
4

Length

Max length4
Median length1
Mean length1.7183099
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 145
68.1%
<NA> 51
 
23.9%
2 13
 
6.1%
3 4
 
1.9%

Length

2024-04-06T22:15:59.552460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:59.668245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 145
68.1%
na 51
 
23.9%
2 13
 
6.1%
3 4
 
1.9%

조제용연마기수
Categorical

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
145 
<NA>
60 
2
 
5
0
 
3

Length

Max length4
Median length1
Mean length1.8450704
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 145
68.1%
<NA> 60
28.2%
2 5
 
2.3%
0 3
 
1.4%

Length

2024-04-06T22:15:59.790410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:15:59.935334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 145
68.1%
na 60
28.2%
2 5
 
2.3%
0 3
 
1.4%

렌즈절단기수
Categorical

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
147 
<NA>
61 
0
 
3
2
 
2

Length

Max length4
Median length1
Mean length1.8591549
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 147
69.0%
<NA> 61
28.6%
0 3
 
1.4%
2 2
 
0.9%

Length

2024-04-06T22:16:00.083412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:16:00.234757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 147
69.0%
na 61
28.6%
0 3
 
1.4%
2 2
 
0.9%

가열기수
Categorical

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
128 
<NA>
62 
2
18 
0
 
3
3
 
2

Length

Max length4
Median length1
Mean length1.8732394
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 128
60.1%
<NA> 62
29.1%
2 18
 
8.5%
0 3
 
1.4%
3 2
 
0.9%

Length

2024-04-06T22:16:00.401440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:16:00.552056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 128
60.1%
na 62
29.1%
2 18
 
8.5%
0 3
 
1.4%
3 2
 
0.9%

안경세척기수
Categorical

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
130 
<NA>
60 
2
18 
0
 
3
3
 
2

Length

Max length4
Median length1
Mean length1.8450704
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 130
61.0%
<NA> 60
28.2%
2 18
 
8.5%
0 3
 
1.4%
3 2
 
0.9%

Length

2024-04-06T22:16:00.692499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:16:00.821467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 130
61.0%
na 60
28.2%
2 18
 
8.5%
0 3
 
1.4%
3 2
 
0.9%

총면적
Real number (ℝ)

MISSING 

Distinct140
Distinct (%)91.5%
Missing60
Missing (%)28.2%
Infinite0
Infinite (%)0.0%
Mean56.876144
Minimum1
Maximum353.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-06T22:16:00.957830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.936
Q130.03
median40
Q362.96
95-th percentile146.114
Maximum353.98
Range352.98
Interquartile range (IQR)32.93

Descriptive statistics

Standard deviation50.156602
Coefficient of variation (CV)0.88185659
Kurtosis15.283158
Mean56.876144
Median Absolute Deviation (MAD)15.43
Skewness3.3168374
Sum8702.05
Variance2515.6847
MonotonicityNot monotonic
2024-04-06T22:16:01.124364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62.29 4
 
1.9%
25.0 3
 
1.4%
1.0 3
 
1.4%
25.2 2
 
0.9%
33.0 2
 
0.9%
35.1 2
 
0.9%
12.0 2
 
0.9%
26.4 2
 
0.9%
49.5 2
 
0.9%
36.8 1
 
0.5%
Other values (130) 130
61.0%
(Missing) 60
28.2%
ValueCountFrequency (%)
1.0 3
1.4%
12.0 2
0.9%
16.5 1
 
0.5%
17.08 1
 
0.5%
17.6 1
 
0.5%
18.16 1
 
0.5%
18.86 1
 
0.5%
18.9 1
 
0.5%
19.47 1
 
0.5%
19.63 1
 
0.5%
ValueCountFrequency (%)
353.98 1
0.5%
352.05 1
0.5%
210.58 1
0.5%
176.0 1
0.5%
171.08 1
0.5%
169.97 1
0.5%
157.86 1
0.5%
155.99 1
0.5%
139.53 1
0.5%
133.69 1
0.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적
03130000PHMB21976313003308220000119760924<NA>1영업/정상13영업중<NA><NA><NA><NA>713-0761<NA>121040서울특별시 마포구 도화2동 250-13서울특별시 마포구 도화길 6-12 (도화동)4173아이닥터안경2015-10-19 15:10:47I2018-08-31 23:59:59.0<NA>195245.581802448606.519629111111111<NA>
13130000PHMB21978313003308220000119780929<NA>3폐업3폐업20221229<NA><NA><NA>363-1575<NA>121010서울특별시 마포구 아현2동282-17서울특별시 마포구 굴레방로 7 (아현동)4117동명사안경점2022-12-29 11:01:55U2021-11-01 21:01:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23130000PHMB21981313003308220000119811118<NA>1영업/정상13영업중<NA><NA><NA><NA>334-0821<NA>121230서울특별시 마포구 망원1동338-1서울특별시 마포구 포은로 68 (망원동)4018서독안경원2014-01-12 20:20:51I2018-08-31 23:59:59.0<NA>191651.829438450113.43954711111111133.3
33130000PHMB21982313003308220000119821210<NA>1영업/정상13영업중<NA><NA><NA><NA>714-6103<NA>121090서울특별시 마포구 염리동159-1서울특별시 마포구 백범로 138-1 (염리동)4149아이글라스안경2014-01-12 20:19:46I2018-08-31 23:59:59.0<NA>195175.541722449286.37477711111111131.4
43130000PHMB21983313003308220000119830906<NA>3폐업3폐업20220914<NA><NA><NA>02-313-7517<NA>121010서울특별시 마포구 아현2동347-1서울특별시 마포구 신촌로 236-1 (아현동)4114세란안경원2022-09-14 15:40:24U2021-12-08 23:06:00.0<NA>195682.783952450515.145612<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53130000PHMB21984313003308220000119840924<NA>3폐업3폐업20131101<NA><NA><NA>719-2216<NA>121020서울특별시 마포구 공덕2동256-30서울특별시 마포구 만리재로 23 (공덕동)121803프랑스안경원2014-01-10 16:21:16I2018-08-31 23:59:59.0<NA>195849.727722449175.307569111111111<NA>
63130000PHMB21985313003308220000119850524<NA>3폐업3폐업20110530<NA><NA><NA>337-6793<NA>121220서울특별시 마포구 합정동384-19<NA><NA>보안당열린안경2011-05-30 11:38:11I2018-08-31 23:59:59.0<NA><NA><NA>111111111<NA>
73130000PHMB21986313003308220000119860411<NA>3폐업3폐업20160114<NA><NA><NA>712-1112<NA>121020서울특별시 마포구 공덕2동255-16서울특별시 마포구 마포대로 110 (공덕동)4213마포안경원2016-01-15 09:11:33I2018-08-31 23:59:59.0<NA>195670.963021449139.73295511111111124.1
83130000PHMB21986313003308220000219860906<NA>3폐업3폐업20100530<NA><NA><NA>313-0005<NA>121010서울특별시 마포구 아현1동618-3<NA><NA>태양안경원2010-06-24 17:51:27I2018-08-31 23:59:59.0<NA><NA><NA>11111111125.0
93130000PHMB21988313003308220000119880521<NA>3폐업3폐업20160426<NA><NA><NA>701-1255<NA>121070서울특별시 마포구 용강동40-4서울특별시 마포구 토정로 317 (용강동)4166Good안경콘택트2016-04-26 17:46:21I2018-08-31 23:59:59.0<NA>194989.174999448616.61443311111111133.25
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적
2033130000PHMB2202331300330822000022023-04-20<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3141-1007<NA><NA>서울특별시 마포구 동교동 179-28서울특별시 마포구 신촌로4길 3, 1층 (동교동)4056안보이면 안경원가975 잘보여요2023-05-18 15:42:30U2022-12-04 22:00:00.0<NA>193634.936433450603.6975<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2043130000PHMB2202331300330822000032023-05-03<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 연남동 358-1서울특별시 마포구 동교로 225, 2층 (연남동)3989안경상회 연남점2023-05-18 15:38:07U2022-12-04 22:00:00.0<NA>193194.919383450887.063663<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2053130000PHMB2202331300330822000042020-02-18<NA>1영업/정상13영업중<NA><NA><NA><NA>02-363-4953<NA><NA>서울특별시 마포구 아현동 744-3서울특별시 마포구 마포대로24길 17-1, 1층 102호 (아현동)4203정석안경원2023-05-11 11:15:26I2022-12-04 23:03:00.0<NA>196338.449434450195.278136<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2063130000PHMB2202331300330822000052023-06-28<NA>1영업/정상13영업중<NA><NA><NA><NA>070-4187-0707<NA><NA>서울특별시 마포구 연남동 223-45서울특별시 마포구 성미산로31길 11, 1층 (연남동)3980츄렌즈 플래그십 스토어 연남2023-07-20 10:03:06U2022-12-06 22:02:00.0<NA>193337.524937451360.563107<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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