Overview

Dataset statistics

Number of variables29
Number of observations84
Missing cells820
Missing cells (%)33.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.2 KiB
Average record size in memory246.6 B

Variable types

Categorical9
Text9
DateTime2
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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-20028/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (54.6%)Imbalance
영업상태명 is highly imbalanced (54.6%)Imbalance
상세영업상태코드 is highly imbalanced (54.6%)Imbalance
상세영업상태명 is highly imbalanced (54.6%)Imbalance
데이터갱신구분 is highly imbalanced (67.4%)Imbalance
시설구분명 is highly imbalanced (65.6%)Imbalance
해제일자 is highly imbalanced (77.0%)Imbalance
인허가취소일자 has 76 (90.5%) missing valuesMissing
폐업일자 has 76 (90.5%) missing valuesMissing
휴업시작일자 has 84 (100.0%) missing valuesMissing
휴업종료일자 has 84 (100.0%) missing valuesMissing
재개업일자 has 84 (100.0%) missing valuesMissing
전화번호 has 84 (100.0%) missing valuesMissing
소재지우편번호 has 84 (100.0%) missing valuesMissing
도로명우편번호 has 4 (4.8%) missing valuesMissing
업태구분명 has 84 (100.0%) missing valuesMissing
좌표정보(X) has 4 (4.8%) missing valuesMissing
좌표정보(Y) has 4 (4.8%) missing valuesMissing
비상시설위치 has 76 (90.5%) missing valuesMissing
시설명_건물명 has 76 (90.5%) missing valuesMissing
관리번호 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 09:28:09.079033
Analysis finished2024-05-11 09:28:10.438790
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
3010000
84 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 84
100.0%

Length

2024-05-11T09:28:10.763206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:28:11.207719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 84
100.0%

관리번호
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-05-11T09:28:11.894965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1512
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

Unique84 ?
Unique (%)100.0%

Sample

1st row3010000-S199900005
2nd row3010000-S201200002
3rd row3010000-S201200004
4th row3010000-S201100004
5th row3010000-S200000003
ValueCountFrequency (%)
3010000-s199900005 1
 
1.2%
3010000-s198800004 1
 
1.2%
3010000-s199200001 1
 
1.2%
3010000-s200500020 1
 
1.2%
3010000-s199500001 1
 
1.2%
3010000-s199700008 1
 
1.2%
3010000-s200700001 1
 
1.2%
3010000-s198700008 1
 
1.2%
3010000-s198700006 1
 
1.2%
3010000-s198700009 1
 
1.2%
Other values (74) 74
88.1%
2024-05-11T09:28:13.019248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 824
54.5%
1 176
 
11.6%
3 98
 
6.5%
- 84
 
5.6%
S 84
 
5.6%
9 73
 
4.8%
2 70
 
4.6%
8 44
 
2.9%
5 20
 
1.3%
7 20
 
1.3%
Other values (2) 19
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1344
88.9%
Dash Punctuation 84
 
5.6%
Uppercase Letter 84
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 824
61.3%
1 176
 
13.1%
3 98
 
7.3%
9 73
 
5.4%
2 70
 
5.2%
8 44
 
3.3%
5 20
 
1.5%
7 20
 
1.5%
6 10
 
0.7%
4 9
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1428
94.4%
Latin 84
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 824
57.7%
1 176
 
12.3%
3 98
 
6.9%
- 84
 
5.9%
9 73
 
5.1%
2 70
 
4.9%
8 44
 
3.1%
5 20
 
1.4%
7 20
 
1.4%
6 10
 
0.7%
Latin
ValueCountFrequency (%)
S 84
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1512
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 824
54.5%
1 176
 
11.6%
3 98
 
6.5%
- 84
 
5.6%
S 84
 
5.6%
9 73
 
4.8%
2 70
 
4.6%
8 44
 
2.9%
5 20
 
1.3%
7 20
 
1.3%
Other values (2) 19
 
1.3%

인허가일자
Date

Distinct43
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum1980-12-31 00:00:00
Maximum2018-09-07 00:00:00
2024-05-11T09:28:13.658372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:28:14.209370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)

인허가취소일자
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing76
Missing (%)90.5%
Memory size804.0 B
2024-05-11T09:28:14.553642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length6.25
Min length5

Characters and Unicode

Total characters50
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

Unique4 ?
Unique (%)50.0%

Sample

1st row2024-02-26
2nd row41817
3rd row41817
4th row41817
5th row41817
ValueCountFrequency (%)
41817 4
50.0%
2024-02-26 1
 
12.5%
45093 1
 
12.5%
43278 1
 
12.5%
2024-01-03 1
 
12.5%
2024-05-11T09:28:15.403042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
18.0%
4 8
16.0%
2 7
14.0%
0 6
12.0%
8 5
10.0%
7 5
10.0%
- 4
8.0%
3 3
 
6.0%
6 1
 
2.0%
5 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46
92.0%
Dash Punctuation 4
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
19.6%
4 8
17.4%
2 7
15.2%
0 6
13.0%
8 5
10.9%
7 5
10.9%
3 3
 
6.5%
6 1
 
2.2%
5 1
 
2.2%
9 1
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9
18.0%
4 8
16.0%
2 7
14.0%
0 6
12.0%
8 5
10.0%
7 5
10.0%
- 4
8.0%
3 3
 
6.0%
6 1
 
2.0%
5 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
18.0%
4 8
16.0%
2 7
14.0%
0 6
12.0%
8 5
10.0%
7 5
10.0%
- 4
8.0%
3 3
 
6.0%
6 1
 
2.0%
5 1
 
2.0%

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
1
76 
4
8 

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 76
90.5%
4 8
 
9.5%

Length

2024-05-11T09:28:15.765120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:28:16.220623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 76
90.5%
4 8
 
9.5%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
영업/정상
76 
취소/말소/만료/정지/중지
8 

Length

Max length14
Median length5
Mean length5.8571429
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 76
90.5%
취소/말소/만료/정지/중지 8
 
9.5%

Length

2024-05-11T09:28:16.716848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:28:17.159252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 76
90.5%
취소/말소/만료/정지/중지 8
 
9.5%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
18
76 
19
8 

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 76
90.5%
19 8
 
9.5%

Length

2024-05-11T09:28:18.071486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:28:18.444987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 76
90.5%
19 8
 
9.5%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
사용중
76 
사용중지
8 

Length

Max length4
Median length3
Mean length3.0952381
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 76
90.5%
사용중지 8
 
9.5%

Length

2024-05-11T09:28:18.947418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:28:19.307371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 76
90.5%
사용중지 8
 
9.5%

폐업일자
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing76
Missing (%)90.5%
Memory size804.0 B
2024-05-11T09:28:19.767782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length6.25
Min length5

Characters and Unicode

Total characters50
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

Unique4 ?
Unique (%)50.0%

Sample

1st row2024-02-26
2nd row41817
3rd row41817
4th row41817
5th row41817
ValueCountFrequency (%)
41817 4
50.0%
2024-02-26 1
 
12.5%
45093 1
 
12.5%
43278 1
 
12.5%
2024-01-03 1
 
12.5%
2024-05-11T09:28:20.973269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
18.0%
4 8
16.0%
2 7
14.0%
0 6
12.0%
8 5
10.0%
7 5
10.0%
- 4
8.0%
3 3
 
6.0%
6 1
 
2.0%
5 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46
92.0%
Dash Punctuation 4
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
19.6%
4 8
17.4%
2 7
15.2%
0 6
13.0%
8 5
10.9%
7 5
10.9%
3 3
 
6.5%
6 1
 
2.2%
5 1
 
2.2%
9 1
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9
18.0%
4 8
16.0%
2 7
14.0%
0 6
12.0%
8 5
10.0%
7 5
10.0%
- 4
8.0%
3 3
 
6.0%
6 1
 
2.0%
5 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
18.0%
4 8
16.0%
2 7
14.0%
0 6
12.0%
8 5
10.0%
7 5
10.0%
- 4
8.0%
3 3
 
6.0%
6 1
 
2.0%
5 1
 
2.0%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

소재지면적
Real number (ℝ)

Distinct80
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7879.5952
Minimum44
Maximum71343
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-05-11T09:28:21.557818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile438.6
Q11492.25
median3800.5
Q38822.5
95-th percentile32494.5
Maximum71343
Range71299
Interquartile range (IQR)7330.25

Descriptive statistics

Standard deviation11657.948
Coefficient of variation (CV)1.479511
Kurtosis11.881754
Mean7879.5952
Median Absolute Deviation (MAD)2895
Skewness3.1219988
Sum661886
Variance1.3590775 × 108
MonotonicityNot monotonic
2024-05-11T09:28:22.347986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14430 3
 
3.6%
1758 2
 
2.4%
2821 2
 
2.4%
7678 1
 
1.2%
907 1
 
1.2%
620 1
 
1.2%
884 1
 
1.2%
1507 1
 
1.2%
15474 1
 
1.2%
4171 1
 
1.2%
Other values (70) 70
83.3%
ValueCountFrequency (%)
44 1
1.2%
287 1
1.2%
356 1
1.2%
403 1
1.2%
438 1
1.2%
442 1
1.2%
448 1
1.2%
476 1
1.2%
495 1
1.2%
620 1
1.2%
ValueCountFrequency (%)
71343 1
1.2%
47064 1
1.2%
39896 1
1.2%
39570 1
1.2%
33660 1
1.2%
25890 1
1.2%
24454 1
1.2%
19215 1
1.2%
17916 1
1.2%
16529 1
1.2%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

지번주소
Text

Distinct74
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-05-11T09:28:23.333149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length21.607143
Min length14

Characters and Unicode

Total characters1815
Distinct characters78
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)78.6%

Sample

1st row서울특별시 중구 충무로1가 52번지 41호
2nd row서울특별시 중구 신당동 844번지
3rd row서울특별시 중구 회현동1가 115번지
4th row서울특별시 중구 신당동 844번지
5th row서울특별시 중구 남대문로2가 9번지 9호
ValueCountFrequency (%)
서울특별시 84
21.3%
중구 84
21.3%
신당동 19
 
4.8%
1호 12
 
3.0%
3호 5
 
1.3%
41호 4
 
1.0%
844번지 4
 
1.0%
서소문동 4
 
1.0%
남창동 3
 
0.8%
을지로1가 3
 
0.8%
Other values (129) 173
43.8%
2024-05-11T09:28:24.733748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
311
17.1%
지 92
 
5.1%
서 89
 
4.9%
구 87
 
4.8%
중 86
 
4.7%
울 85
 
4.7%
특 84
 
4.6%
별 84
 
4.6%
시 84
 
4.6%
1 79
 
4.4%
Other values (68) 734
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1160
63.9%
Decimal Number 331
 
18.2%
Space Separator 311
 
17.1%
Dash Punctuation 11
 
0.6%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 92
 
7.9%
서 89
 
7.7%
구 87
 
7.5%
중 86
 
7.4%
울 85
 
7.3%
특 84
 
7.2%
별 84
 
7.2%
시 84
 
7.2%
번 72
 
6.2%
동 49
 
4.2%
Other values (55) 348
30.0%
Decimal Number
ValueCountFrequency (%)
1 79
23.9%
2 51
15.4%
4 44
13.3%
3 36
10.9%
5 30
 
9.1%
9 21
 
6.3%
6 21
 
6.3%
0 20
 
6.0%
8 16
 
4.8%
7 13
 
3.9%
Space Separator
ValueCountFrequency (%)
311
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1160
63.9%
Common 655
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 92
 
7.9%
서 89
 
7.7%
구 87
 
7.5%
중 86
 
7.4%
울 85
 
7.3%
특 84
 
7.2%
별 84
 
7.2%
시 84
 
7.2%
번 72
 
6.2%
동 49
 
4.2%
Other values (55) 348
30.0%
Common
ValueCountFrequency (%)
311
47.5%
1 79
 
12.1%
2 51
 
7.8%
4 44
 
6.7%
3 36
 
5.5%
5 30
 
4.6%
9 21
 
3.2%
6 21
 
3.2%
0 20
 
3.1%
8 16
 
2.4%
Other values (3) 26
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1160
63.9%
ASCII 655
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
311
47.5%
1 79
 
12.1%
2 51
 
7.8%
4 44
 
6.7%
3 36
 
5.5%
5 30
 
4.6%
9 21
 
3.2%
6 21
 
3.2%
0 20
 
3.1%
8 16
 
2.4%
Other values (3) 26
 
4.0%
Hangul
ValueCountFrequency (%)
지 92
 
7.9%
서 89
 
7.7%
구 87
 
7.5%
중 86
 
7.4%
울 85
 
7.3%
특 84
 
7.2%
별 84
 
7.2%
시 84
 
7.2%
번 72
 
6.2%
동 49
 
4.2%
Other values (55) 348
30.0%

도로명주소
Text

Distinct79
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-05-11T09:28:25.644296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length33
Min length19

Characters and Unicode

Total characters2772
Distinct characters191
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

Unique75 ?
Unique (%)89.3%

Sample

1st row서울특별시 중구 소공로 지하 58 (충무로1가, 회현지하쇼핑센터)
2nd row서울특별시 중구 다산로 32 (신당동, 남산타운)
3rd row서울특별시 중구 퇴계로12길 78 (회현동1가, 중구회현체육센터)
4th row서울특별시 중구 다산로 32 (신당동, 남산타운)
5th row서울특별시 중구 남대문로 지하 72 (남대문로2가, 명동지하쇼핑센터)
ValueCountFrequency (%)
서울특별시 84
 
15.4%
중구 84
 
15.4%
지하 25
 
4.6%
신당동 20
 
3.7%
을지로 11
 
2.0%
세종대로 9
 
1.6%
다산로 7
 
1.3%
퇴계로 7
 
1.3%
소공로 6
 
1.1%
2호선 6
 
1.1%
Other values (215) 288
52.7%
2024-05-11T09:28:27.006860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
463
 
16.7%
로 129
 
4.7%
서 101
 
3.6%
구 98
 
3.5%
울 94
 
3.4%
시 90
 
3.2%
중 90
 
3.2%
특 84
 
3.0%
별 84
 
3.0%
) 84
 
3.0%
Other values (181) 1455
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1756
63.3%
Space Separator 463
 
16.7%
Decimal Number 301
 
10.9%
Close Punctuation 84
 
3.0%
Open Punctuation 84
 
3.0%
Other Punctuation 79
 
2.8%
Dash Punctuation 2
 
0.1%
Lowercase Letter 2
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 129
 
7.3%
서 101
 
5.8%
구 98
 
5.6%
울 94
 
5.4%
시 90
 
5.1%
중 90
 
5.1%
특 84
 
4.8%
별 84
 
4.8%
지 79
 
4.5%
동 62
 
3.5%
Other values (163) 845
48.1%
Decimal Number
ValueCountFrequency (%)
1 66
21.9%
2 55
18.3%
3 36
12.0%
4 30
10.0%
6 26
 
8.6%
0 22
 
7.3%
5 21
 
7.0%
8 19
 
6.3%
7 15
 
5.0%
9 11
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
p 1
50.0%
Space Separator
ValueCountFrequency (%)
463
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 84
100.0%
Other Punctuation
ValueCountFrequency (%)
, 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1756
63.3%
Common 1013
36.5%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 129
 
7.3%
서 101
 
5.8%
구 98
 
5.6%
울 94
 
5.4%
시 90
 
5.1%
중 90
 
5.1%
특 84
 
4.8%
별 84
 
4.8%
지 79
 
4.5%
동 62
 
3.5%
Other values (163) 845
48.1%
Common
ValueCountFrequency (%)
463
45.7%
) 84
 
8.3%
( 84
 
8.3%
, 79
 
7.8%
1 66
 
6.5%
2 55
 
5.4%
3 36
 
3.6%
4 30
 
3.0%
6 26
 
2.6%
0 22
 
2.2%
Other values (5) 68
 
6.7%
Latin
ValueCountFrequency (%)
a 1
33.3%
M 1
33.3%
p 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1756
63.3%
ASCII 1016
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
463
45.6%
) 84
 
8.3%
( 84
 
8.3%
, 79
 
7.8%
1 66
 
6.5%
2 55
 
5.4%
3 36
 
3.5%
4 30
 
3.0%
6 26
 
2.6%
0 22
 
2.2%
Other values (8) 71
 
7.0%
Hangul
ValueCountFrequency (%)
로 129
 
7.3%
서 101
 
5.8%
구 98
 
5.6%
울 94
 
5.4%
시 90
 
5.1%
중 90
 
5.1%
특 84
 
4.8%
별 84
 
4.8%
지 79
 
4.5%
동 62
 
3.5%
Other values (163) 845
48.1%

도로명우편번호
Text

MISSING 

Distinct62
Distinct (%)77.5%
Missing4
Missing (%)4.8%
Memory size804.0 B
2024-05-11T09:28:27.687152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9875
Min length4

Characters and Unicode

Total characters399
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

Unique49 ?
Unique (%)61.3%

Sample

1st row04535
2nd row04595
3rd row04633
4th row04595
5th row4535
ValueCountFrequency (%)
04595 4
 
5.0%
04533 4
 
5.0%
04527 3
 
3.8%
04515 2
 
2.5%
04501 2
 
2.5%
04542 2
 
2.5%
04585 2
 
2.5%
04550 2
 
2.5%
04625 2
 
2.5%
04513 2
 
2.5%
Other values (52) 55
68.8%
2024-05-11T09:28:28.959490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 90
22.6%
0 89
22.3%
4 87
21.8%
3 24
 
6.0%
2 24
 
6.0%
6 22
 
5.5%
1 20
 
5.0%
9 17
 
4.3%
8 15
 
3.8%
7 10
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 398
99.7%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 90
22.6%
0 89
22.4%
4 87
21.9%
3 24
 
6.0%
2 24
 
6.0%
6 22
 
5.5%
1 20
 
5.0%
9 17
 
4.3%
8 15
 
3.8%
7 10
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 399
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 90
22.6%
0 89
22.3%
4 87
21.8%
3 24
 
6.0%
2 24
 
6.0%
6 22
 
5.5%
1 20
 
5.0%
9 17
 
4.3%
8 15
 
3.8%
7 10
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 399
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 90
22.6%
0 89
22.3%
4 87
21.8%
3 24
 
6.0%
2 24
 
6.0%
6 22
 
5.5%
1 20
 
5.0%
9 17
 
4.3%
8 15
 
3.8%
7 10
 
2.5%

사업장명
Text

Distinct83
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-05-11T09:28:29.823210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length12.154762
Min length4

Characters and Unicode

Total characters1021
Distinct characters171
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

Unique82 ?
Unique (%)97.6%

Sample

1st row회현지하쇼핑센터
2nd row남산타운문화체육센터 지하1층
3rd row중구회현체육센터 지하1층
4th row남산타운아파트1 (분양동)지하1층
5th row명동지하쇼핑센터
ValueCountFrequency (%)
지하주차장 7
 
5.3%
지하1층 6
 
4.5%
지하1~2층 5
 
3.8%
지하2~3층 4
 
3.0%
지하1~3층 4
 
3.0%
지하3층 3
 
2.3%
지하1~4층 2
 
1.5%
1층 2
 
1.5%
지하1~5층 2
 
1.5%
부영빌딩 2
 
1.5%
Other values (94) 95
72.0%
2024-05-11T09:28:31.270740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 93
 
9.1%
하 84
 
8.2%
48
 
4.7%
층 37
 
3.6%
장 30
 
2.9%
1 27
 
2.6%
역 26
 
2.5%
~ 23
 
2.3%
3 21
 
2.1%
2 20
 
2.0%
Other values (161) 612
59.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 857
83.9%
Decimal Number 84
 
8.2%
Space Separator 48
 
4.7%
Math Symbol 23
 
2.3%
Close Punctuation 3
 
0.3%
Open Punctuation 3
 
0.3%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 93
 
10.9%
하 84
 
9.8%
층 37
 
4.3%
장 30
 
3.5%
역 26
 
3.0%
철 20
 
2.3%
승 20
 
2.3%
강 20
 
2.3%
호 18
 
2.1%
선 17
 
2.0%
Other values (147) 492
57.4%
Decimal Number
ValueCountFrequency (%)
1 27
32.1%
3 21
25.0%
2 20
23.8%
4 8
 
9.5%
6 4
 
4.8%
5 3
 
3.6%
7 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
E 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 857
83.9%
Common 161
 
15.8%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 93
 
10.9%
하 84
 
9.8%
층 37
 
4.3%
장 30
 
3.5%
역 26
 
3.0%
철 20
 
2.3%
승 20
 
2.3%
강 20
 
2.3%
호 18
 
2.1%
선 17
 
2.0%
Other values (147) 492
57.4%
Common
ValueCountFrequency (%)
48
29.8%
1 27
16.8%
~ 23
14.3%
3 21
13.0%
2 20
12.4%
4 8
 
5.0%
6 4
 
2.5%
) 3
 
1.9%
5 3
 
1.9%
( 3
 
1.9%
Latin
ValueCountFrequency (%)
B 1
33.3%
E 1
33.3%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 857
83.9%
ASCII 164
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 93
 
10.9%
하 84
 
9.8%
층 37
 
4.3%
장 30
 
3.5%
역 26
 
3.0%
철 20
 
2.3%
승 20
 
2.3%
강 20
 
2.3%
호 18
 
2.1%
선 17
 
2.0%
Other values (147) 492
57.4%
ASCII
ValueCountFrequency (%)
48
29.3%
1 27
16.5%
~ 23
14.0%
3 21
12.8%
2 20
12.2%
4 8
 
4.9%
6 4
 
2.4%
) 3
 
1.8%
5 3
 
1.8%
( 3
 
1.8%
Other values (4) 4
 
2.4%

최종수정일자
Date

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum2014-06-27 17:33:05
Maximum2024-02-26 15:41:12
2024-05-11T09:28:31.829553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:28:32.398046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
U
79 
I
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 79
94.0%
I 5
 
6.0%

Length

2024-05-11T09:28:32.856006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:28:33.459060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 79
94.0%
i 5
 
6.0%

데이터갱신일자
Categorical

Distinct12
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-11-30 22:04:00.0
52 
2023-11-30 22:00:00.0
12 
2023-11-30 21:01:00.0
6 
2018-08-31 23:59:59.0
 
5
2023-12-02 00:02:00.0
 
2
Other values (7)
7 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique7 ?
Unique (%)8.3%

Sample

1st row2023-11-30 22:00:00.0
2nd row2023-11-30 22:07:00.0
3rd row2023-11-30 22:04:00.0
4th row2023-11-30 22:04:00.0
5th row2023-04-05 02:40:00.0

Common Values

ValueCountFrequency (%)
2023-11-30 22:04:00.0 52
61.9%
2023-11-30 22:00:00.0 12
 
14.3%
2023-11-30 21:01:00.0 6
 
7.1%
2018-08-31 23:59:59.0 5
 
6.0%
2023-12-02 00:02:00.0 2
 
2.4%
2023-11-30 22:07:00.0 1
 
1.2%
2023-04-05 02:40:00.0 1
 
1.2%
2023-01-19 02:40:00.0 1
 
1.2%
2023-11-30 22:06:00.0 1
 
1.2%
2023-12-01 22:08:00.0 1
 
1.2%
Other values (2) 2
 
2.4%

Length

2024-05-11T09:28:33.835201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-11-30 72
42.9%
22:04:00.0 52
31.0%
22:00:00.0 12
 
7.1%
21:01:00.0 6
 
3.6%
2018-08-31 5
 
3.0%
23:59:59.0 5
 
3.0%
02:40:00.0 3
 
1.8%
2023-12-01 2
 
1.2%
2023-12-02 2
 
1.2%
00:02:00.0 2
 
1.2%
Other values (7) 7
 
4.2%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct71
Distinct (%)88.8%
Missing4
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean199207.94
Minimum196814.92
Maximum201944.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-05-11T09:28:34.476703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196814.92
5-th percentile197272.52
Q1197939.94
median198930.27
Q3200702.71
95-th percentile201656.23
Maximum201944.61
Range5129.6947
Interquartile range (IQR)2762.7699

Descriptive statistics

Standard deviation1512.6713
Coefficient of variation (CV)0.007593429
Kurtosis-1.3083473
Mean199207.94
Median Absolute Deviation (MAD)1189.5995
Skewness0.32678725
Sum15936635
Variance2288174.6
MonotonicityNot monotonic
2024-05-11T09:28:35.235831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200750.455125653 3
 
3.6%
199429.381307184 2
 
2.4%
197505.769854333 2
 
2.4%
199067.076000716 2
 
2.4%
197831.032460836 2
 
2.4%
198294.579463422 2
 
2.4%
198354.121882082 2
 
2.4%
197614.608800998 2
 
2.4%
201823.908977364 1
 
1.2%
197620.648923884 1
 
1.2%
Other values (61) 61
72.6%
(Missing) 4
 
4.8%
ValueCountFrequency (%)
196814.916728854 1
1.2%
197032.923485936 1
1.2%
197034.02843741 1
1.2%
197143.10408516 1
1.2%
197279.328436862 1
1.2%
197403.590119982 1
1.2%
197505.769854333 2
2.4%
197566.025174596 1
1.2%
197614.608800998 2
2.4%
197620.648923884 1
1.2%
ValueCountFrequency (%)
201944.611391747 1
1.2%
201852.931048042 1
1.2%
201823.908977364 1
1.2%
201703.261478668 1
1.2%
201653.75549585 1
1.2%
201634.148959452 1
1.2%
201511.590138084 1
1.2%
201457.329270788 1
1.2%
201421.025827064 1
1.2%
201363.777556422 1
1.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct71
Distinct (%)88.8%
Missing4
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean451035.05
Minimum449547.1
Maximum452076.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-05-11T09:28:35.773305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449547.1
5-th percentile449770.58
Q1450770.53
median451108.8
Q3451522.79
95-th percentile451766.45
Maximum452076.82
Range2529.715
Interquartile range (IQR)752.25726

Descriptive statistics

Standard deviation574.11045
Coefficient of variation (CV)0.0012728732
Kurtosis0.25919804
Mean451035.05
Median Absolute Deviation (MAD)383.77465
Skewness-0.79144832
Sum36082804
Variance329602.81
MonotonicityNot monotonic
2024-05-11T09:28:36.220431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449638.824308081 3
 
3.6%
450992.469281547 2
 
2.4%
450514.71337214 2
 
2.4%
451547.450342157 2
 
2.4%
450960.381231325 2
 
2.4%
450952.394190021 2
 
2.4%
451309.736293852 2
 
2.4%
451032.860087325 2
 
2.4%
452076.818664092 1
 
1.2%
450919.874344114 1
 
1.2%
Other values (61) 61
72.6%
(Missing) 4
 
4.8%
ValueCountFrequency (%)
449547.103651161 1
 
1.2%
449638.824308081 3
3.6%
449777.515840267 1
 
1.2%
449952.509481192 1
 
1.2%
450241.960631774 1
 
1.2%
450277.009027586 1
 
1.2%
450277.600241968 1
 
1.2%
450305.644873169 1
 
1.2%
450309.162582147 1
 
1.2%
450368.066302876 1
 
1.2%
ValueCountFrequency (%)
452076.818664092 1
1.2%
451865.344390849 1
1.2%
451808.563758166 1
1.2%
451785.827095837 1
1.2%
451765.426505347 1
1.2%
451729.447902786 1
1.2%
451694.035675644 1
1.2%
451675.09180947 1
1.2%
451662.510762256 1
1.2%
451612.700077323 1
1.2%

비상시설위치
Text

MISSING 

Distinct7
Distinct (%)87.5%
Missing76
Missing (%)90.5%
Memory size804.0 B
2024-05-11T09:28:36.718220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length22.125
Min length18

Characters and Unicode

Total characters177
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)75.0%

Sample

1st row서울특별시 중구 남대문로2가 9번지 9호
2nd row서울특별시 중구 서소문동 120번지 23호
3rd row서울특별시 중구 회현동1가 115번지
4th row서울특별시 중구 충무로1가 52번지 41호
5th row서울특별시 중구 신당동 850번지
ValueCountFrequency (%)
서울특별시 8
21.1%
중구 8
21.1%
충무로1가 2
 
5.3%
52번지 2
 
5.3%
41호 2
 
5.3%
신당동 1
 
2.6%
17번지 1
 
2.6%
남대문로4가 1
 
2.6%
10호 1
 
2.6%
149번지 1
 
2.6%
Other values (11) 11
28.9%
2024-05-11T09:28:37.678184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
16.9%
1 12
 
6.8%
서 9
 
5.1%
지 9
 
5.1%
번 8
 
4.5%
특 8
 
4.5%
별 8
 
4.5%
시 8
 
4.5%
중 8
 
4.5%
구 8
 
4.5%
Other values (24) 69
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
62.7%
Decimal Number 36
 
20.3%
Space Separator 30
 
16.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 9
 
8.1%
지 9
 
8.1%
번 8
 
7.2%
특 8
 
7.2%
별 8
 
7.2%
시 8
 
7.2%
중 8
 
7.2%
구 8
 
7.2%
울 8
 
7.2%
호 6
 
5.4%
Other values (14) 31
27.9%
Decimal Number
ValueCountFrequency (%)
1 12
33.3%
2 7
19.4%
4 4
 
11.1%
5 4
 
11.1%
9 3
 
8.3%
0 3
 
8.3%
3 1
 
2.8%
8 1
 
2.8%
7 1
 
2.8%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
62.7%
Common 66
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 9
 
8.1%
지 9
 
8.1%
번 8
 
7.2%
특 8
 
7.2%
별 8
 
7.2%
시 8
 
7.2%
중 8
 
7.2%
구 8
 
7.2%
울 8
 
7.2%
호 6
 
5.4%
Other values (14) 31
27.9%
Common
ValueCountFrequency (%)
30
45.5%
1 12
 
18.2%
2 7
 
10.6%
4 4
 
6.1%
5 4
 
6.1%
9 3
 
4.5%
0 3
 
4.5%
3 1
 
1.5%
8 1
 
1.5%
7 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
62.7%
ASCII 66
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
45.5%
1 12
 
18.2%
2 7
 
10.6%
4 4
 
6.1%
5 4
 
6.1%
9 3
 
4.5%
0 3
 
4.5%
3 1
 
1.5%
8 1
 
1.5%
7 1
 
1.5%
Hangul
ValueCountFrequency (%)
서 9
 
8.1%
지 9
 
8.1%
번 8
 
7.2%
특 8
 
7.2%
별 8
 
7.2%
시 8
 
7.2%
중 8
 
7.2%
구 8
 
7.2%
울 8
 
7.2%
호 6
 
5.4%
Other values (14) 31
27.9%

시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
<NA>
76 
공공시설
 
5
공공용시설
 
3

Length

Max length5
Median length4
Mean length4.0357143
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 76
90.5%
공공시설 5
 
6.0%
공공용시설 3
 
3.6%

Length

2024-05-11T09:28:38.103794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:28:38.414357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 76
90.5%
공공시설 5
 
6.0%
공공용시설 3
 
3.6%

시설명_건물명
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing76
Missing (%)90.5%
Memory size804.0 B
2024-05-11T09:28:38.780323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length8.5
Mean length8.25
Min length4

Characters and Unicode

Total characters66
Distinct characters41
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row명동지하쇼핑센터
2nd row부영빌딩 지하3층
3rd row중구회현체육센타(나동 지하주차장)
4th row충무지하상가
5th row동화동주민센터
ValueCountFrequency (%)
명동지하쇼핑센터 1
10.0%
부영빌딩 1
10.0%
지하3층 1
10.0%
중구회현체육센타(나동 1
10.0%
지하주차장 1
10.0%
충무지하상가 1
10.0%
동화동주민센터 1
10.0%
을지로지하보도 1
10.0%
회현지하도상가 1
10.0%
흥국생명 1
10.0%
2024-05-11T09:28:39.907721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 7
 
10.6%
하 6
 
9.1%
동 4
 
6.1%
센 3
 
4.5%
명 2
 
3.0%
가 2
 
3.0%
현 2
 
3.0%
회 2
 
3.0%
상 2
 
3.0%
2
 
3.0%
Other values (31) 34
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
92.4%
Space Separator 2
 
3.0%
Close Punctuation 1
 
1.5%
Open Punctuation 1
 
1.5%
Decimal Number 1
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 7
 
11.5%
하 6
 
9.8%
동 4
 
6.6%
센 3
 
4.9%
명 2
 
3.3%
가 2
 
3.3%
현 2
 
3.3%
회 2
 
3.3%
상 2
 
3.3%
도 2
 
3.3%
Other values (27) 29
47.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61
92.4%
Common 5
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 7
 
11.5%
하 6
 
9.8%
동 4
 
6.6%
센 3
 
4.9%
명 2
 
3.3%
가 2
 
3.3%
현 2
 
3.3%
회 2
 
3.3%
상 2
 
3.3%
도 2
 
3.3%
Other values (27) 29
47.5%
Common
ValueCountFrequency (%)
2
40.0%
) 1
20.0%
( 1
20.0%
3 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61
92.4%
ASCII 5
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 7
 
11.5%
하 6
 
9.8%
동 4
 
6.6%
센 3
 
4.9%
명 2
 
3.3%
가 2
 
3.3%
현 2
 
3.3%
회 2
 
3.3%
상 2
 
3.3%
도 2
 
3.3%
Other values (27) 29
47.5%
ASCII
ValueCountFrequency (%)
2
40.0%
) 1
20.0%
( 1
20.0%
3 1
20.0%

해제일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
<NA>
78 
20140627
 
4
20230616
 
1
20180627
 
1

Length

Max length8
Median length4
Mean length4.2857143
Min length4

Unique

Unique2 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
92.9%
20140627 4
 
4.8%
20230616 1
 
1.2%
20180627 1
 
1.2%

Length

2024-05-11T09:28:40.441443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:28:40.826281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
92.9%
20140627 4
 
4.8%
20230616 1
 
1.2%
20180627 1
 
1.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
030100003010000-S1999000051999-05-25<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>7678<NA>서울특별시 중구 충무로1가 52번지 41호서울특별시 중구 소공로 지하 58 (충무로1가, 회현지하쇼핑센터)04535회현지하쇼핑센터2024-01-18 11:08:43U2023-11-30 22:00:00.0<NA>198294.579463450952.39419<NA><NA><NA><NA>
130100003010000-S2012000022012-06-29<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>438<NA>서울특별시 중구 신당동 844번지서울특별시 중구 다산로 32 (신당동, 남산타운)04595남산타운문화체육센터 지하1층2024-01-25 16:49:39U2023-11-30 22:07:00.0<NA>200750.455126449638.824308<NA><NA><NA><NA>
230100003010000-S2012000042012-06-29<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1056<NA>서울특별시 중구 회현동1가 115번지서울특별시 중구 퇴계로12길 78 (회현동1가, 중구회현체육센터)04633중구회현체육센터 지하1층2024-01-22 10:01:05U2023-11-30 22:04:00.0<NA>198302.921921450437.595573<NA><NA><NA><NA>
330100003010000-S2011000042011-04-06<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>71343<NA>서울특별시 중구 신당동 844번지서울특별시 중구 다산로 32 (신당동, 남산타운)04595남산타운아파트1 (분양동)지하1층2024-01-22 10:14:09U2023-11-30 22:04:00.0<NA>200750.455126449638.824308<NA><NA><NA><NA>
430100003010000-S2000000032000-04-03<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1758<NA>서울특별시 중구 남대문로2가 9번지 9호서울특별시 중구 남대문로 지하 72 (남대문로2가, 명동지하쇼핑센터)4535명동지하쇼핑센터2023-04-03 14:12:58U2023-04-05 02:40:00.0<NA>198354.121882451309.736294서울특별시 중구 남대문로2가 9번지 9호공공용시설명동지하쇼핑센터<NA>
530100003010000-S1990000051990-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2821<NA>서울특별시 중구 서소문동 120번지 23호서울특별시 중구 세종대로9길 42 (서소문동, 부영빌딩)4513부영빌딩 지하3층2023-01-17 08:38:40U2023-01-19 02:40:00.0<NA>197614.608801451032.860087서울특별시 중구 서소문동 120번지 23호공공용시설부영빌딩 지하3층<NA>
630100003010000-S2002000052002-12-26<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>10785<NA>서울특별시 중구 신당동 369번지 2호서울특별시 중구 다산로 지하 115 (신당동, 약수역 6호선)045986호선약수역지하철승강장2024-01-22 10:13:21U2023-11-30 22:04:00.0<NA>200857.799865450277.009028<NA><NA><NA><NA>
730100003010000-S2018000012018-09-07<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>8800<NA>서울특별시 중구 충무로3가 49번지서울특별시 중구 충무로 13 (충무로3가, 엘크루메트로시티)04554엘크루메트로시티 지하2~6층2024-01-22 17:08:52U2023-11-30 22:04:00.0<NA>199279.677406451120.517701<NA><NA><NA><NA>
830100003010000-S2016000012016-03-31<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>39896<NA>서울특별시 중구 황학동 2545번지서울특별시 중구 청계천로 400 (황학동, 롯데캐슬베네치아)04572베네치아메가몰 지하3~4층2024-01-29 15:12:59U2023-11-30 21:01:00.0<NA>201823.908977452076.818664<NA><NA><NA><NA>
930100003010000-S2005000021999-02-20<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>10701<NA>서울특별시 중구 필동2가 16-2 충무로역 3,4호선서울특별시 중구 퇴계로 지하214, 충무로역 3,4호선 (필동2가)046254호선충무로역지하철승강장2024-01-29 14:16:40U2023-11-30 21:01:00.0<NA>199429.381307450992.469282<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
7430100003010000-S1990000211990-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2821<NA>서울특별시 중구 서소문동 120-23 부영빌딩서울특별시 중구 세종대로9길 42, 부영빌딩 (서소문동)04513부영빌딩 지하3층2024-01-22 09:44:11U2023-11-30 22:04:00.0<NA>197614.608801451032.860087<NA><NA><NA><NA>
7530100003010000-S1987000121987-12-31<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>8890<NA>서울특별시 중구 장충동2가 199번지 3호서울특별시 중구 동호로 지하 256 (장충동2가, 동대입구역 3호선)046173호선동대입구역지하철승강장2024-01-22 10:04:29U2023-11-30 22:04:00.0<NA>200382.10665450770.846479<NA><NA><NA><NA>
7630100003010000-S1987000131987-10-31<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6225<NA>서울특별시 중구 신당동 361번지 4호서울특별시 중구 동호로 191 (신당동, 선일빌딩)04598선일빌딩3호선약수역지하철승강장2024-01-22 10:35:49U2023-11-30 22:04:00.0<NA>200820.038485450309.162582<NA><NA><NA><NA>
7730100003010000-S1985000011987-07-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1128<NA>서울특별시 중구 신당동 369-44 약수역 3호선서울특별시 중구 다산로 지하122, 약수역 3호선 (신당동)045973호선약수역지하철승강장2024-01-22 10:12:47U2023-11-30 22:04:00.0<NA>200901.523441450241.960632<NA><NA><NA><NA>
7830100003010000-S1985000021985-10-21<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>495<NA>서울특별시 중구 봉래동2가 123번지서울특별시 중구 통일로 21 (봉래동2가, 서울역앞우체국)04509서울역우체국앞지하보도2024-01-22 09:57:48U2023-11-30 22:04:00.0<NA>197403.59012450590.945275<NA><NA><NA><NA>
7930100003010000-S1985000031985-07-24<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1650<NA>서울특별시 중구 남대문로5가 120번지서울특별시 중구 소월로 10 (남대문로5가, 단암빌딩)04527단암타워빌딩 지하1~2층2024-01-22 10:00:06U2023-11-30 22:04:00.0<NA>197761.352668450694.317527<NA><NA><NA><NA>
8030100003010000-S2005000121980-12-31<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1448<NA>서울특별시 중구 예관동 120번지 1호서울특별시 중구 창경궁로 17 (예관동, 중구청)04558중구청 지하1~3층2024-01-22 10:38:29U2023-11-30 22:04:00.0<NA>199732.248739451272.806325<NA><NA><NA><NA>
8130100003010000-S1980000031980-12-31<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>5179<NA>서울특별시 중구 장충동2가 201번지서울특별시 중구 장충단로 60 (장충동2가, 반얀트리 클럽 앤 스파 서울)04605반얀트리클럽앤스파서울 지하1~2층2024-01-22 10:05:14U2023-11-30 22:04:00.0<NA>199977.759937449777.51584<NA><NA><NA><NA>
8230100003010000-S2008000092008-12-09<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1945<NA>서울특별시 중구 신당동 846번지서울특별시 중구 다산로42나길 46 (신당동, 신당동 파라다이스 아파트)04585신당동파라다이스아파트 지하주차장 1층2024-01-31 15:14:00U2023-12-02 00:02:00.0<NA>201457.329271451124.073491<NA><NA><NA><NA>
8330100003010000-S2008000112008-12-09<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>33660<NA>서울특별시 중구 신당동 843번지서울특별시 중구 청구로1길 23 (신당동, 삼성아파트)04588신당삼성아파트 지하주차장2024-01-31 13:15:09U2023-12-02 00:02:00.0<NA>201511.590138450655.06251<NA><NA><NA><NA>