Overview

Dataset statistics

Number of variables29
Number of observations68
Missing cells666
Missing cells (%)33.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.4 KiB
Average record size in memory246.9 B

Variable types

Categorical8
Text9
DateTime3
Unsupported6
Numeric3

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),비상시설위치,시설구분명,시설명_건물명,해제일자
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-20029/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (73.9%)Imbalance
영업상태명 is highly imbalanced (73.9%)Imbalance
상세영업상태코드 is highly imbalanced (73.9%)Imbalance
상세영업상태명 is highly imbalanced (73.9%)Imbalance
데이터갱신구분 is highly imbalanced (88.9%)Imbalance
시설구분명 is highly imbalanced (72.7%)Imbalance
해제일자 is highly imbalanced (88.9%)Imbalance
인허가취소일자 has 65 (95.6%) missing valuesMissing
폐업일자 has 65 (95.6%) missing valuesMissing
휴업시작일자 has 68 (100.0%) missing valuesMissing
휴업종료일자 has 68 (100.0%) missing valuesMissing
재개업일자 has 68 (100.0%) missing valuesMissing
전화번호 has 68 (100.0%) missing valuesMissing
소재지우편번호 has 68 (100.0%) missing valuesMissing
업태구분명 has 68 (100.0%) missing valuesMissing
좌표정보(X) has 1 (1.5%) missing valuesMissing
좌표정보(Y) has 1 (1.5%) missing valuesMissing
비상시설위치 has 63 (92.6%) missing valuesMissing
시설명_건물명 has 63 (92.6%) missing valuesMissing
관리번호 has unique valuesUnique
소재지면적 has unique valuesUnique
도로명주소 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 has unique valuesUnique
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
전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 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 05:43:27.070117
Analysis finished2024-05-11 05:43:27.730722
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
3020000
68 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 68
100.0%

Length

2024-05-11T14:43:27.801901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:27.919964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 68
100.0%

관리번호
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T14:43:28.112868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1224
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row3020000-S201800002
2nd row3020000-S200100067
3rd row3020000-S200100069
4th row3020000-S200100070
5th row3020000-S200100078
ValueCountFrequency (%)
3020000-s201800002 1
 
1.5%
3020000-s200100053 1
 
1.5%
3020000-s200100030 1
 
1.5%
3020000-s200100033 1
 
1.5%
3020000-s200100050 1
 
1.5%
3020000-s200100051 1
 
1.5%
3020000-s200100052 1
 
1.5%
3020000-s200100067 1
 
1.5%
3020000-s201800004 1
 
1.5%
3020000-s201100002 1
 
1.5%
Other values (58) 58
85.3%
2024-05-11T14:43:28.533004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 709
57.9%
2 151
 
12.3%
3 81
 
6.6%
1 69
 
5.6%
- 68
 
5.6%
S 68
 
5.6%
6 18
 
1.5%
8 16
 
1.3%
5 13
 
1.1%
9 11
 
0.9%
Other values (2) 20
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1088
88.9%
Dash Punctuation 68
 
5.6%
Uppercase Letter 68
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 709
65.2%
2 151
 
13.9%
3 81
 
7.4%
1 69
 
6.3%
6 18
 
1.7%
8 16
 
1.5%
5 13
 
1.2%
9 11
 
1.0%
7 11
 
1.0%
4 9
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1156
94.4%
Latin 68
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 709
61.3%
2 151
 
13.1%
3 81
 
7.0%
1 69
 
6.0%
- 68
 
5.9%
6 18
 
1.6%
8 16
 
1.4%
5 13
 
1.1%
9 11
 
1.0%
7 11
 
1.0%
Latin
ValueCountFrequency (%)
S 68
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1224
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 709
57.9%
2 151
 
12.3%
3 81
 
6.6%
1 69
 
5.6%
- 68
 
5.6%
S 68
 
5.6%
6 18
 
1.5%
8 16
 
1.3%
5 13
 
1.1%
9 11
 
0.9%
Other values (2) 20
 
1.6%

인허가일자
Date

Distinct13
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2001-12-10 00:00:00
Maximum2018-09-07 00:00:00
2024-05-11T14:43:28.685717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:43:28.849338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

인허가취소일자
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing65
Missing (%)95.6%
Memory size676.0 B
2024-05-11T14:43:29.002494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length8.3333333
Min length5

Characters and Unicode

Total characters25
Distinct characters8
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

Unique3 ?
Unique (%)100.0%

Sample

1st row2023-09-09
2nd row2023-12-11
3rd row42613
ValueCountFrequency (%)
2023-09-09 1
33.3%
2023-12-11 1
33.3%
42613 1
33.3%
2024-05-11T14:43:29.294345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
24.0%
0 4
16.0%
- 4
16.0%
1 4
16.0%
3 3
12.0%
9 2
 
8.0%
4 1
 
4.0%
6 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
84.0%
Dash Punctuation 4
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
28.6%
0 4
19.0%
1 4
19.0%
3 3
14.3%
9 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
24.0%
0 4
16.0%
- 4
16.0%
1 4
16.0%
3 3
12.0%
9 2
 
8.0%
4 1
 
4.0%
6 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
24.0%
0 4
16.0%
- 4
16.0%
1 4
16.0%
3 3
12.0%
9 2
 
8.0%
4 1
 
4.0%
6 1
 
4.0%

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
1
65 
4
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 65
95.6%
4 3
 
4.4%

Length

2024-05-11T14:43:29.461609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:29.603867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 65
95.6%
4 3
 
4.4%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
영업/정상
65 
취소/말소/만료/정지/중지
 
3

Length

Max length14
Median length5
Mean length5.3970588
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 65
95.6%
취소/말소/만료/정지/중지 3
 
4.4%

Length

2024-05-11T14:43:29.716843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:29.844337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 65
95.6%
취소/말소/만료/정지/중지 3
 
4.4%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
18
65 
19
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row18
2nd row18
3rd row18
4th row18
5th row18

Common Values

ValueCountFrequency (%)
18 65
95.6%
19 3
 
4.4%

Length

2024-05-11T14:43:30.035042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:30.161171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 65
95.6%
19 3
 
4.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
사용중
65 
사용중지
 
3

Length

Max length4
Median length3
Mean length3.0441176
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 65
95.6%
사용중지 3
 
4.4%

Length

2024-05-11T14:43:30.296850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:30.454589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 65
95.6%
사용중지 3
 
4.4%

폐업일자
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing65
Missing (%)95.6%
Memory size676.0 B
2024-05-11T14:43:30.588203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length8.3333333
Min length5

Characters and Unicode

Total characters25
Distinct characters8
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

Unique3 ?
Unique (%)100.0%

Sample

1st row2023-09-09
2nd row2023-12-11
3rd row42613
ValueCountFrequency (%)
2023-09-09 1
33.3%
2023-12-11 1
33.3%
42613 1
33.3%
2024-05-11T14:43:30.862405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
24.0%
0 4
16.0%
- 4
16.0%
1 4
16.0%
3 3
12.0%
9 2
 
8.0%
4 1
 
4.0%
6 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
84.0%
Dash Punctuation 4
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
28.6%
0 4
19.0%
1 4
19.0%
3 3
14.3%
9 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
24.0%
0 4
16.0%
- 4
16.0%
1 4
16.0%
3 3
12.0%
9 2
 
8.0%
4 1
 
4.0%
6 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
24.0%
0 4
16.0%
- 4
16.0%
1 4
16.0%
3 3
12.0%
9 2
 
8.0%
4 1
 
4.0%
6 1
 
4.0%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

소재지면적
Real number (ℝ)

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10899.675
Minimum183
Maximum62439.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T14:43:31.028367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183
5-th percentile322.05
Q11317.5
median6552
Q315420.5
95-th percentile39123.85
Maximum62439.5
Range62256.5
Interquartile range (IQR)14103

Descriptive statistics

Standard deviation13487.818
Coefficient of variation (CV)1.2374514
Kurtosis3.8963932
Mean10899.675
Median Absolute Deviation (MAD)5677.5
Skewness1.9178943
Sum741177.89
Variance1.8192124 × 108
MonotonicityNot monotonic
2024-05-11T14:43:31.196846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1380.14 1
 
1.5%
188.0 1
 
1.5%
1800.0 1
 
1.5%
1320.0 1
 
1.5%
235.33 1
 
1.5%
2056.0 1
 
1.5%
2294.0 1
 
1.5%
25572.0 1
 
1.5%
1198.0 1
 
1.5%
21054.0 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
183.0 1
1.5%
188.0 1
1.5%
235.33 1
1.5%
300.0 1
1.5%
363.0 1
1.5%
456.0 1
1.5%
483.0 1
1.5%
573.0 1
1.5%
613.0 1
1.5%
679.69 1
1.5%
ValueCountFrequency (%)
62439.5 1
1.5%
56771.0 1
1.5%
39860.0 1
1.5%
39190.0 1
1.5%
39001.0 1
1.5%
33452.0 1
1.5%
28590.0 1
1.5%
26549.0 1
1.5%
25572.0 1
1.5%
24693.0 1
1.5%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

지번주소
Text

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T14:43:31.477468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length24.867647
Min length17

Characters and Unicode

Total characters1691
Distinct characters138
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

Unique66 ?
Unique (%)97.1%

Sample

1st row서울특별시 용산구 후암동 435번지 2호
2nd row서울특별시 용산구 한남동 747-7 하얏트호텔
3rd row서울특별시 용산구 한남동 736-1 제일기획
4th row서울특별시 용산구 한남동 726-494 6호선 한강진역
5th row서울특별시 용산구 보광동 448번지
ValueCountFrequency (%)
서울특별시 68
19.9%
용산구 68
19.9%
이태원동 6
 
1.8%
이촌동 6
 
1.8%
갈월동 6
 
1.8%
한남동 6
 
1.8%
주민센터 5
 
1.5%
후암동 4
 
1.2%
효창동 4
 
1.2%
4호선 4
 
1.2%
Other values (141) 165
48.2%
2024-05-11T14:43:31.990772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
274
 
16.2%
용 89
 
5.3%
산 89
 
5.3%
서 74
 
4.4%
동 71
 
4.2%
구 70
 
4.1%
울 70
 
4.1%
시 70
 
4.1%
별 68
 
4.0%
특 68
 
4.0%
Other values (128) 748
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1115
65.9%
Space Separator 274
 
16.2%
Decimal Number 266
 
15.7%
Dash Punctuation 30
 
1.8%
Other Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 89
 
8.0%
산 89
 
8.0%
서 74
 
6.6%
동 71
 
6.4%
구 70
 
6.3%
울 70
 
6.3%
시 70
 
6.3%
별 68
 
6.1%
특 68
 
6.1%
지 27
 
2.4%
Other values (111) 419
37.6%
Decimal Number
ValueCountFrequency (%)
1 52
19.5%
2 45
16.9%
4 30
11.3%
3 27
10.2%
5 22
8.3%
8 19
 
7.1%
9 18
 
6.8%
0 18
 
6.8%
6 18
 
6.8%
7 17
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
274
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1115
65.9%
Common 574
33.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 89
 
8.0%
산 89
 
8.0%
서 74
 
6.6%
동 71
 
6.4%
구 70
 
6.3%
울 70
 
6.3%
시 70
 
6.3%
별 68
 
6.1%
특 68
 
6.1%
지 27
 
2.4%
Other values (111) 419
37.6%
Common
ValueCountFrequency (%)
274
47.7%
1 52
 
9.1%
2 45
 
7.8%
4 30
 
5.2%
- 30
 
5.2%
3 27
 
4.7%
5 22
 
3.8%
8 19
 
3.3%
9 18
 
3.1%
0 18
 
3.1%
Other values (5) 39
 
6.8%
Latin
ValueCountFrequency (%)
L 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1115
65.9%
ASCII 576
34.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
274
47.6%
1 52
 
9.0%
2 45
 
7.8%
4 30
 
5.2%
- 30
 
5.2%
3 27
 
4.7%
5 22
 
3.8%
8 19
 
3.3%
9 18
 
3.1%
0 18
 
3.1%
Other values (7) 41
 
7.1%
Hangul
ValueCountFrequency (%)
용 89
 
8.0%
산 89
 
8.0%
서 74
 
6.6%
동 71
 
6.4%
구 70
 
6.3%
울 70
 
6.3%
시 70
 
6.3%
별 68
 
6.1%
특 68
 
6.1%
지 27
 
2.4%
Other values (111) 419
37.6%

도로명주소
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T14:43:32.410442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length43
Mean length38.617647
Min length23

Characters and Unicode

Total characters2626
Distinct characters188
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row서울특별시 용산구 소월로2나길 18 (후암동)
2nd row서울특별시 용산구 소월로 322, 하얏트호텔 지하 1~2층 (한남동)
3rd row서울특별시 용산구 이태원로 222, 제일기획 (한남동)
4th row서울특별시 용산구 이태원로 지하287, 6호선 한강진역 지하 4층 (한남동)
5th row서울특별시 용산구 장문로 104 (보광동, 신동아아파트)
ValueCountFrequency (%)
서울특별시 68
 
14.1%
용산구 68
 
14.1%
지하 12
 
2.5%
지하1~2층 10
 
2.1%
한강대로 9
 
1.9%
주민센터 9
 
1.9%
갈월동 6
 
1.2%
이촌동 6
 
1.2%
한남동 6
 
1.2%
지하1~3층 6
 
1.2%
Other values (208) 283
58.6%
2024-05-11T14:43:32.940633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
418
 
15.9%
산 94
 
3.6%
용 93
 
3.5%
서 86
 
3.3%
, 81
 
3.1%
동 78
 
3.0%
로 76
 
2.9%
1 75
 
2.9%
울 72
 
2.7%
시 70
 
2.7%
Other values (178) 1483
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1644
62.6%
Space Separator 418
 
15.9%
Decimal Number 304
 
11.6%
Other Punctuation 82
 
3.1%
Open Punctuation 69
 
2.6%
Close Punctuation 69
 
2.6%
Math Symbol 33
 
1.3%
Uppercase Letter 5
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 94
 
5.7%
용 93
 
5.7%
서 86
 
5.2%
동 78
 
4.7%
로 76
 
4.6%
울 72
 
4.4%
시 70
 
4.3%
구 70
 
4.3%
별 68
 
4.1%
특 68
 
4.1%
Other values (156) 869
52.9%
Decimal Number
ValueCountFrequency (%)
1 75
24.7%
2 62
20.4%
3 30
 
9.9%
5 25
 
8.2%
6 22
 
7.2%
4 21
 
6.9%
0 19
 
6.2%
8 17
 
5.6%
7 17
 
5.6%
9 16
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
20.0%
S 1
20.0%
N 1
20.0%
T 1
20.0%
Y 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 81
98.8%
! 1
 
1.2%
Space Separator
ValueCountFrequency (%)
418
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Math Symbol
ValueCountFrequency (%)
~ 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1644
62.6%
Common 977
37.2%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 94
 
5.7%
용 93
 
5.7%
서 86
 
5.2%
동 78
 
4.7%
로 76
 
4.6%
울 72
 
4.4%
시 70
 
4.3%
구 70
 
4.3%
별 68
 
4.1%
특 68
 
4.1%
Other values (156) 869
52.9%
Common
ValueCountFrequency (%)
418
42.8%
, 81
 
8.3%
1 75
 
7.7%
( 69
 
7.1%
) 69
 
7.1%
2 62
 
6.3%
~ 33
 
3.4%
3 30
 
3.1%
5 25
 
2.6%
6 22
 
2.3%
Other values (7) 93
 
9.5%
Latin
ValueCountFrequency (%)
L 1
20.0%
S 1
20.0%
N 1
20.0%
T 1
20.0%
Y 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1644
62.6%
ASCII 982
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
418
42.6%
, 81
 
8.2%
1 75
 
7.6%
( 69
 
7.0%
) 69
 
7.0%
2 62
 
6.3%
~ 33
 
3.4%
3 30
 
3.1%
5 25
 
2.5%
6 22
 
2.2%
Other values (12) 98
 
10.0%
Hangul
ValueCountFrequency (%)
산 94
 
5.7%
용 93
 
5.7%
서 86
 
5.2%
동 78
 
4.7%
로 76
 
4.6%
울 72
 
4.4%
시 70
 
4.3%
구 70
 
4.3%
별 68
 
4.1%
특 68
 
4.1%
Other values (156) 869
52.9%

도로명우편번호
Text

Distinct54
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T14:43:33.224450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9705882
Min length4

Characters and Unicode

Total characters338
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

Unique42 ?
Unique (%)61.8%

Sample

1st row04326
2nd row04347
3rd row04404
4th row04347
5th row04416
ValueCountFrequency (%)
04374 3
 
4.4%
04385 3
 
4.4%
04320 2
 
2.9%
04386 2
 
2.9%
04422 2
 
2.9%
04355 2
 
2.9%
04323 2
 
2.9%
04347 2
 
2.9%
04322 2
 
2.9%
04353 2
 
2.9%
Other values (44) 46
67.6%
2024-05-11T14:43:33.715180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 90
26.6%
0 80
23.7%
3 70
20.7%
5 20
 
5.9%
2 20
 
5.9%
8 14
 
4.1%
9 12
 
3.6%
1 11
 
3.3%
7 10
 
3.0%
6 10
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 337
99.7%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 90
26.7%
0 80
23.7%
3 70
20.8%
5 20
 
5.9%
2 20
 
5.9%
8 14
 
4.2%
9 12
 
3.6%
1 11
 
3.3%
7 10
 
3.0%
6 10
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 338
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 90
26.6%
0 80
23.7%
3 70
20.7%
5 20
 
5.9%
2 20
 
5.9%
8 14
 
4.1%
9 12
 
3.6%
1 11
 
3.3%
7 10
 
3.0%
6 10
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 90
26.6%
0 80
23.7%
3 70
20.7%
5 20
 
5.9%
2 20
 
5.9%
8 14
 
4.1%
9 12
 
3.6%
1 11
 
3.3%
7 10
 
3.0%
6 10
 
3.0%

사업장명
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T14:43:34.025378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20.5
Mean length15.558824
Min length7

Characters and Unicode

Total characters1058
Distinct characters169
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row혜심원(지하1층)
2nd row하얏트호텔(지하1~2층)
3rd row제일기획빌딩(지하3~4층)
4th row지하철 한강진역(지하1~4층)
5th row보광동신동아아파트 지하1층
ValueCountFrequency (%)
이촌동 4
 
3.9%
지하주차장 4
 
3.9%
지하철 3
 
2.9%
지하1층 3
 
2.9%
지하1~2층 2
 
1.9%
1~2층 2
 
1.9%
1층 2
 
1.9%
혜심원(지하1층 1
 
1.0%
주민센터 1
 
1.0%
북한강아파트 1
 
1.0%
Other values (80) 80
77.7%
2024-05-11T14:43:34.525675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 78
 
7.4%
하 75
 
7.1%
층 69
 
6.5%
( 63
 
6.0%
) 63
 
6.0%
1 61
 
5.8%
~ 49
 
4.6%
2 35
 
3.3%
35
 
3.3%
동 23
 
2.2%
Other values (159) 507
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 717
67.8%
Decimal Number 124
 
11.7%
Open Punctuation 63
 
6.0%
Close Punctuation 63
 
6.0%
Math Symbol 49
 
4.6%
Space Separator 35
 
3.3%
Uppercase Letter 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 78
 
10.9%
하 75
 
10.5%
층 69
 
9.6%
동 23
 
3.2%
파 21
 
2.9%
이 18
 
2.5%
아 18
 
2.5%
주 16
 
2.2%
트 16
 
2.2%
센 14
 
2.0%
Other values (143) 369
51.5%
Decimal Number
ValueCountFrequency (%)
1 61
49.2%
2 35
28.2%
3 13
 
10.5%
4 9
 
7.3%
5 5
 
4.0%
9 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
L 2
28.6%
S 1
14.3%
N 1
14.3%
T 1
14.3%
Y 1
14.3%
G 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Math Symbol
ValueCountFrequency (%)
~ 49
100.0%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 717
67.8%
Common 334
31.6%
Latin 7
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 78
 
10.9%
하 75
 
10.5%
층 69
 
9.6%
동 23
 
3.2%
파 21
 
2.9%
이 18
 
2.5%
아 18
 
2.5%
주 16
 
2.2%
트 16
 
2.2%
센 14
 
2.0%
Other values (143) 369
51.5%
Common
ValueCountFrequency (%)
( 63
18.9%
) 63
18.9%
1 61
18.3%
~ 49
14.7%
2 35
10.5%
35
10.5%
3 13
 
3.9%
4 9
 
2.7%
5 5
 
1.5%
9 1
 
0.3%
Latin
ValueCountFrequency (%)
L 2
28.6%
S 1
14.3%
N 1
14.3%
T 1
14.3%
Y 1
14.3%
G 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 717
67.8%
ASCII 341
32.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 78
 
10.9%
하 75
 
10.5%
층 69
 
9.6%
동 23
 
3.2%
파 21
 
2.9%
이 18
 
2.5%
아 18
 
2.5%
주 16
 
2.2%
트 16
 
2.2%
센 14
 
2.0%
Other values (143) 369
51.5%
ASCII
ValueCountFrequency (%)
( 63
18.5%
) 63
18.5%
1 61
17.9%
~ 49
14.4%
2 35
10.3%
35
10.3%
3 13
 
3.8%
4 9
 
2.6%
5 5
 
1.5%
L 2
 
0.6%
Other values (6) 6
 
1.8%

최종수정일자
Date

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2016-08-31 14:56:43
Maximum2024-01-31 09:38:27
2024-05-11T14:43:34.776795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:43:34.951941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
U
67 
I
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
U 67
98.5%
I 1
 
1.5%

Length

2024-05-11T14:43:35.132889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:35.289186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 67
98.5%
i 1
 
1.5%

데이터갱신일자
Date

Distinct14
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 00:02:00
2024-05-11T14:43:35.453308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:43:35.664167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)98.5%
Missing1
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean197851.2
Minimum195266.36
Maximum200939.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T14:43:35.844023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195266.36
5-th percentile195852.45
Q1196796.77
median197563.07
Q3199141.53
95-th percentile200093.67
Maximum200939.3
Range5672.9369
Interquartile range (IQR)2344.7567

Descriptive statistics

Standard deviation1436.7001
Coefficient of variation (CV)0.0072615179
Kurtosis-0.96675329
Mean197851.2
Median Absolute Deviation (MAD)1218.4132
Skewness0.21681903
Sum13256031
Variance2064107
MonotonicityNot monotonic
2024-05-11T14:43:36.023799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196324.188598829 2
 
2.9%
197940.501959902 1
 
1.5%
199387.896366941 1
 
1.5%
200939.299261016 1
 
1.5%
197999.390069553 1
 
1.5%
200310.979917902 1
 
1.5%
198781.48296152 1
 
1.5%
199457.430158682 1
 
1.5%
195647.721598266 1
 
1.5%
199471.30974998 1
 
1.5%
Other values (56) 56
82.4%
ValueCountFrequency (%)
195266.362355276 1
1.5%
195563.535062555 1
1.5%
195647.721598266 1
1.5%
195846.05238755 1
1.5%
195867.376009283 1
1.5%
195925.434808411 1
1.5%
195946.156031124 1
1.5%
195981.203408641 1
1.5%
196126.855627043 1
1.5%
196179.662725826 1
1.5%
ValueCountFrequency (%)
200939.299261016 1
1.5%
200310.979917902 1
1.5%
200270.393683814 1
1.5%
200093.947721943 1
1.5%
200093.016718644 1
1.5%
200006.188629725 1
1.5%
199939.720762017 1
1.5%
199827.290294906 1
1.5%
199737.097413554 1
1.5%
199624.32911584 1
1.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)98.5%
Missing1
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean448153.11
Minimum446413.23
Maximum450168.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T14:43:36.261983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446413.23
5-th percentile446582.01
Q1447172.33
median448094.93
Q3448790.46
95-th percentile449961.34
Maximum450168.32
Range3755.0936
Interquartile range (IQR)1618.1264

Descriptive statistics

Standard deviation1051.0783
Coefficient of variation (CV)0.0023453554
Kurtosis-0.88739547
Mean448153.11
Median Absolute Deviation (MAD)826.0221
Skewness0.18757276
Sum30026258
Variance1104765.7
MonotonicityNot monotonic
2024-05-11T14:43:36.500285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448224.758666308 2
 
2.9%
450125.719031797 1
 
1.5%
448055.04886957 1
 
1.5%
448094.925577541 1
 
1.5%
449602.714791691 1
 
1.5%
447939.994985364 1
 
1.5%
448410.640240428 1
 
1.5%
448033.219644757 1
 
1.5%
448011.81160846 1
 
1.5%
447522.747030786 1
 
1.5%
Other values (56) 56
82.4%
ValueCountFrequency (%)
446413.230030876 1
1.5%
446472.907414567 1
1.5%
446503.162895472 1
1.5%
446559.136495499 1
1.5%
446635.383950146 1
1.5%
446735.872721729 1
1.5%
446755.881350777 1
1.5%
446788.454136977 1
1.5%
446893.484429691 1
1.5%
446894.749807934 1
1.5%
ValueCountFrequency (%)
450168.3235982 1
1.5%
450125.719031797 1
1.5%
450094.236418678 1
1.5%
449972.993855472 1
1.5%
449934.157783456 1
1.5%
449895.759589421 1
1.5%
449711.539621321 1
1.5%
449602.714791691 1
1.5%
449487.391169308 1
1.5%
449370.243999548 1
1.5%

비상시설위치
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing63
Missing (%)92.6%
Memory size676.0 B
2024-05-11T14:43:36.694652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length21.8
Min length18

Characters and Unicode

Total characters109
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row서울특별시 용산구 보광동 238번지 2호
2nd row서울특별시 용산구 보광동 151번지
3rd row서울특별시 용산구 문배동 24-21 용산아크로타워
4th row서울특별시 용산구 보광동 217번지 32호
5th row서울특별시 용산구 용문동 90번지
ValueCountFrequency (%)
서울특별시 5
21.7%
용산구 5
21.7%
보광동 3
13.0%
238번지 1
 
4.3%
2호 1
 
4.3%
151번지 1
 
4.3%
문배동 1
 
4.3%
24-21 1
 
4.3%
용산아크로타워 1
 
4.3%
217번지 1
 
4.3%
Other values (3) 3
13.0%
2024-05-11T14:43:37.117430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
16.5%
용 7
 
6.4%
산 6
 
5.5%
2 6
 
5.5%
서 5
 
4.6%
특 5
 
4.6%
별 5
 
4.6%
시 5
 
4.6%
구 5
 
4.6%
울 5
 
4.6%
Other values (22) 42
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72
66.1%
Space Separator 18
 
16.5%
Decimal Number 18
 
16.5%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 7
 
9.7%
산 6
 
8.3%
서 5
 
6.9%
특 5
 
6.9%
별 5
 
6.9%
시 5
 
6.9%
구 5
 
6.9%
울 5
 
6.9%
동 5
 
6.9%
번 4
 
5.6%
Other values (11) 20
27.8%
Decimal Number
ValueCountFrequency (%)
2 6
33.3%
1 4
22.2%
3 2
 
11.1%
8 1
 
5.6%
9 1
 
5.6%
7 1
 
5.6%
4 1
 
5.6%
5 1
 
5.6%
0 1
 
5.6%
Space Separator
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72
66.1%
Common 37
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 7
 
9.7%
산 6
 
8.3%
서 5
 
6.9%
특 5
 
6.9%
별 5
 
6.9%
시 5
 
6.9%
구 5
 
6.9%
울 5
 
6.9%
동 5
 
6.9%
번 4
 
5.6%
Other values (11) 20
27.8%
Common
ValueCountFrequency (%)
18
48.6%
2 6
 
16.2%
1 4
 
10.8%
3 2
 
5.4%
8 1
 
2.7%
9 1
 
2.7%
7 1
 
2.7%
- 1
 
2.7%
4 1
 
2.7%
5 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72
66.1%
ASCII 37
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
48.6%
2 6
 
16.2%
1 4
 
10.8%
3 2
 
5.4%
8 1
 
2.7%
9 1
 
2.7%
7 1
 
2.7%
- 1
 
2.7%
4 1
 
2.7%
5 1
 
2.7%
Hangul
ValueCountFrequency (%)
용 7
 
9.7%
산 6
 
8.3%
서 5
 
6.9%
특 5
 
6.9%
별 5
 
6.9%
시 5
 
6.9%
구 5
 
6.9%
울 5
 
6.9%
동 5
 
6.9%
번 4
 
5.6%
Other values (11) 20
27.8%

시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
63 
공공용시설
 
4
공공시설
 
1

Length

Max length5
Median length4
Mean length4.0588235
Min length4

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 63
92.6%
공공용시설 4
 
5.9%
공공시설 1
 
1.5%

Length

2024-05-11T14:43:37.357883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:37.510859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 63
92.6%
공공용시설 4
 
5.9%
공공시설 1
 
1.5%

시설명_건물명
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing63
Missing (%)92.6%
Memory size676.0 B
2024-05-11T14:43:37.744707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length13.8
Min length7

Characters and Unicode

Total characters69
Distinct characters48
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row한국폴리텍대학 서울정수캠퍼스 본관동 지하1층
2nd row리버빌아파트 지하1층
3rd row아크로타워(지하1~3층)
4th row보광동주민센터 지하1~2층
5th row브라운스톤용산
ValueCountFrequency (%)
지하1층 2
20.0%
한국폴리텍대학 1
10.0%
서울정수캠퍼스 1
10.0%
본관동 1
10.0%
리버빌아파트 1
10.0%
아크로타워(지하1~3층 1
10.0%
보광동주민센터 1
10.0%
지하1~2층 1
10.0%
브라운스톤용산 1
10.0%
2024-05-11T14:43:38.505371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
7.2%
층 4
 
5.8%
1 4
 
5.8%
하 4
 
5.8%
지 4
 
5.8%
아 2
 
2.9%
동 2
 
2.9%
~ 2
 
2.9%
스 2
 
2.9%
리 2
 
2.9%
Other values (38) 38
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54
78.3%
Decimal Number 6
 
8.7%
Space Separator 5
 
7.2%
Math Symbol 2
 
2.9%
Open Punctuation 1
 
1.4%
Close Punctuation 1
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 4
 
7.4%
하 4
 
7.4%
지 4
 
7.4%
아 2
 
3.7%
동 2
 
3.7%
스 2
 
3.7%
리 2
 
3.7%
운 1
 
1.9%
워 1
 
1.9%
용 1
 
1.9%
Other values (31) 31
57.4%
Decimal Number
ValueCountFrequency (%)
1 4
66.7%
2 1
 
16.7%
3 1
 
16.7%
Space Separator
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54
78.3%
Common 15
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 4
 
7.4%
하 4
 
7.4%
지 4
 
7.4%
아 2
 
3.7%
동 2
 
3.7%
스 2
 
3.7%
리 2
 
3.7%
운 1
 
1.9%
워 1
 
1.9%
용 1
 
1.9%
Other values (31) 31
57.4%
Common
ValueCountFrequency (%)
5
33.3%
1 4
26.7%
~ 2
 
13.3%
2 1
 
6.7%
( 1
 
6.7%
3 1
 
6.7%
) 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54
78.3%
ASCII 15
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
33.3%
1 4
26.7%
~ 2
 
13.3%
2 1
 
6.7%
( 1
 
6.7%
3 1
 
6.7%
) 1
 
6.7%
Hangul
ValueCountFrequency (%)
층 4
 
7.4%
하 4
 
7.4%
지 4
 
7.4%
아 2
 
3.7%
동 2
 
3.7%
스 2
 
3.7%
리 2
 
3.7%
운 1
 
1.9%
워 1
 
1.9%
용 1
 
1.9%
Other values (31) 31
57.4%

해제일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
67 
20160831
 
1

Length

Max length8
Median length4
Mean length4.0588235
Min length4

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 67
98.5%
20160831 1
 
1.5%

Length

2024-05-11T14:43:38.793229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:38.977734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 67
98.5%
20160831 1
 
1.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
030200003020000-S2018000022018-09-07<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1380.14<NA>서울특별시 용산구 후암동 435번지 2호서울특별시 용산구 소월로2나길 18 (후암동)04326혜심원(지하1층)2023-07-17 13:40:11U2022-12-06 23:09:00.0<NA>197940.50196450125.719032<NA><NA><NA><NA>
130200003020000-S2001000672001-12-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3223.0<NA>서울특별시 용산구 한남동 747-7 하얏트호텔서울특별시 용산구 소월로 322, 하얏트호텔 지하 1~2층 (한남동)04347하얏트호텔(지하1~2층)2023-07-17 15:17:33U2022-12-06 23:09:00.0<NA>199737.097414448587.753315<NA><NA><NA><NA>
230200003020000-S2001000692001-12-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1023.0<NA>서울특별시 용산구 한남동 736-1 제일기획서울특별시 용산구 이태원로 222, 제일기획 (한남동)04404제일기획빌딩(지하3~4층)2023-07-17 15:18:17U2022-12-06 23:09:00.0<NA>199827.290295448078.558293<NA><NA><NA><NA>
330200003020000-S2001000702001-12-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>10794.0<NA>서울특별시 용산구 한남동 726-494 6호선 한강진역서울특별시 용산구 이태원로 지하287, 6호선 한강진역 지하 4층 (한남동)04347지하철 한강진역(지하1~4층)2023-07-17 15:01:23U2022-12-06 23:09:00.0<NA>200093.016719448727.898865<NA><NA><NA><NA>
430200003020000-S2001000782001-12-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1980.0<NA>서울특별시 용산구 보광동 448번지서울특별시 용산구 장문로 104 (보광동, 신동아아파트)04416보광동신동아아파트 지하1층2023-07-17 15:06:30U2022-12-06 23:09:00.0<NA>200093.947722447069.04703<NA><NA><NA><NA>
530200003020000-S2001000092001-12-102023-09-094취소/말소/만료/정지/중지19사용중지2023-09-09<NA><NA><NA><NA>613.0<NA>서울특별시 용산구 갈월동 2-5서울특별시 용산구 한강대로 350, 지하1층 (갈월동)04334갑을빌딩(지하1층)2023-09-09 16:08:59U2022-12-08 23:01:00.0<NA>197484.456801449711.539621<NA><NA><NA><NA>
630200003020000-S2018000052018-09-07<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1902.23<NA>서울특별시 용산구 용산동2가 11-13 용산2가동 주민센터, 용산치안센터서울특별시 용산구 신흥로 90, 용산2가동 주민센터, 용산치안센터 지하1~3층 (용산동2가)04339용산2가동 주민센터(지하1~3층)2023-07-17 14:00:30U2022-12-06 23:09:00.0<NA>198647.329571449298.28042<NA><NA><NA><NA>
730200003020000-S2018000032018-09-07<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>8848.0<NA>서울특별시 용산구 용문동 90번지서울특별시 용산구 효창원로 88 (용문동, 브라운스톤용산)04363브라운스톤 용산(지하1~2층)2023-07-17 14:38:59U2022-12-06 23:09:00.0<NA>196324.188599448224.758666<NA><NA><NA><NA>
830200003020000-S2011000022011-05-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>39190.0<NA>서울특별시 용산구 한강로1가 50-1 용산파크자이서울특별시 용산구 한강대로 205, 지하1~5층 (한강로1가, 용산파크자이)04322용산파크자이(지하1~5층)2023-11-20 17:17:43U2022-10-31 22:02:00.0<NA>197514.145786448264.322315<NA><NA><NA><NA>
930200003020000-S2013000012013-12-06<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>39001.0<NA>서울특별시 용산구 동자동 45 센트레빌아스테리움서울서울특별시 용산구 한강대로 372, 지하2~9층 (동자동, 센트레빌아스테리움서울)04323센트레빌아스테리움서울(지하2~9층)2023-07-17 14:20:40U2022-12-06 23:09:00.0<NA>197563.069806449934.157783<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
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6530200003020000-S2013000022013-12-06426134취소/말소/만료/정지/중지19사용중지42613<NA><NA><NA><NA>183.0<NA>서울특별시 용산구 용문동 90번지서울특별시 용산구 효창원로 88 (용문동)140-080브라운스톤용산2016-08-31 14:56:43I2018-08-31 23:59:59.0<NA>196324.188599448224.758666서울특별시 용산구 용문동 90번지공공시설브라운스톤용산20160831
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