Overview

Dataset statistics

Number of variables29
Number of observations97
Missing cells724
Missing cells (%)25.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.3 KiB
Average record size in memory246.4 B

Variable types

Categorical12
Text7
Unsupported6
Numeric3
DateTime1

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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-20046/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (73.8%)Imbalance
영업상태코드 is highly imbalanced (55.4%)Imbalance
영업상태명 is highly imbalanced (55.4%)Imbalance
상세영업상태코드 is highly imbalanced (55.4%)Imbalance
상세영업상태명 is highly imbalanced (55.4%)Imbalance
폐업일자 is highly imbalanced (73.8%)Imbalance
데이터갱신구분 is highly imbalanced (70.7%)Imbalance
해제일자 is highly imbalanced (82.2%)Imbalance
휴업시작일자 has 97 (100.0%) missing valuesMissing
휴업종료일자 has 97 (100.0%) missing valuesMissing
재개업일자 has 97 (100.0%) missing valuesMissing
전화번호 has 97 (100.0%) missing valuesMissing
소재지우편번호 has 97 (100.0%) missing valuesMissing
도로명우편번호 has 2 (2.1%) missing valuesMissing
업태구분명 has 97 (100.0%) missing valuesMissing
좌표정보(X) has 2 (2.1%) missing valuesMissing
좌표정보(Y) has 2 (2.1%) missing valuesMissing
비상시설위치 has 68 (70.1%) missing valuesMissing
시설명_건물명 has 68 (70.1%) 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 06:42:37.601316
Analysis finished2024-05-11 06:42:38.933097
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
3190000
97 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 97
100.0%

Length

2024-05-11T06:42:39.127460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:42:39.597229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 97
100.0%

관리번호
Text

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2024-05-11T06:42:40.102808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1746
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

Unique97 ?
Unique (%)100.0%

Sample

1st row3190000-S202200006
2nd row3190000-S200300134
3rd row3190000-S200300103
4th row3190000-S200300104
5th row3190000-S200700005
ValueCountFrequency (%)
3190000-s202200006 1
 
1.0%
3190000-s200700008 1
 
1.0%
3190000-s200600004 1
 
1.0%
3190000-s200600003 1
 
1.0%
3190000-s200700011 1
 
1.0%
3190000-s200300110 1
 
1.0%
3190000-s200900008 1
 
1.0%
3190000-s200300069 1
 
1.0%
3190000-s200300086 1
 
1.0%
3190000-s200300135 1
 
1.0%
Other values (87) 87
89.7%
2024-05-11T06:42:41.111031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 899
51.5%
3 161
 
9.2%
1 156
 
8.9%
9 128
 
7.3%
2 123
 
7.0%
- 97
 
5.6%
S 97
 
5.6%
6 20
 
1.1%
7 19
 
1.1%
4 17
 
1.0%
Other values (2) 29
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1552
88.9%
Dash Punctuation 97
 
5.6%
Uppercase Letter 97
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 899
57.9%
3 161
 
10.4%
1 156
 
10.1%
9 128
 
8.2%
2 123
 
7.9%
6 20
 
1.3%
7 19
 
1.2%
4 17
 
1.1%
8 15
 
1.0%
5 14
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1649
94.4%
Latin 97
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 899
54.5%
3 161
 
9.8%
1 156
 
9.5%
9 128
 
7.8%
2 123
 
7.5%
- 97
 
5.9%
6 20
 
1.2%
7 19
 
1.2%
4 17
 
1.0%
8 15
 
0.9%
Latin
ValueCountFrequency (%)
S 97
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 899
51.5%
3 161
 
9.2%
1 156
 
8.9%
9 128
 
7.3%
2 123
 
7.0%
- 97
 
5.6%
S 97
 
5.6%
6 20
 
1.1%
7 19
 
1.1%
4 17
 
1.0%
Other values (2) 29
 
1.7%

인허가일자
Categorical

Distinct37
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
2003-02-17
19 
2003-02-14
10 
2003-02-19
9 
2007-07-23
6 
2006-03-31
5 
Other values (32)
48 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique22 ?
Unique (%)22.7%

Sample

1st row2022-12-23
2nd row2003-09-15
3rd row2003-02-19
4th row2003-02-19
5th row2007-07-23

Common Values

ValueCountFrequency (%)
2003-02-17 19
19.6%
2003-02-14 10
 
10.3%
2003-02-19 9
 
9.3%
2007-07-23 6
 
6.2%
2006-03-31 5
 
5.2%
2009-08-27 4
 
4.1%
2009-12-10 4
 
4.1%
2022-08-05 3
 
3.1%
2003-02-11 3
 
3.1%
2011-11-16 2
 
2.1%
Other values (27) 32
33.0%

Length

2024-05-11T06:42:41.651963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2003-02-17 19
19.6%
2003-02-14 10
 
10.3%
2003-02-19 9
 
9.3%
2007-07-23 6
 
6.2%
2006-03-31 5
 
5.2%
2009-08-27 4
 
4.1%
2009-12-10 4
 
4.1%
2022-08-05 3
 
3.1%
2003-02-11 3
 
3.1%
2011-01-18 2
 
2.1%
Other values (27) 32
33.0%

인허가취소일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size908.0 B
<NA>
88 
2023-12-07
 
4
42615
 
3
2023-08-01
 
1
41831
 
1

Length

Max length10
Median length4
Mean length4.3505155
Min length4

Unique

Unique2 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 88
90.7%
2023-12-07 4
 
4.1%
42615 3
 
3.1%
2023-08-01 1
 
1.0%
41831 1
 
1.0%

Length

2024-05-11T06:42:42.156023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:42:42.713068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
90.7%
2023-12-07 4
 
4.1%
42615 3
 
3.1%
2023-08-01 1
 
1.0%
41831 1
 
1.0%

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
88 
4
9 

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 88
90.7%
4 9
 
9.3%

Length

2024-05-11T06:42:43.133654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:42:43.455198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 88
90.7%
4 9
 
9.3%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
영업/정상
88 
취소/말소/만료/정지/중지
9 

Length

Max length14
Median length5
Mean length5.8350515
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 88
90.7%
취소/말소/만료/정지/중지 9
 
9.3%

Length

2024-05-11T06:42:43.864817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:42:44.274879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 88
90.7%
취소/말소/만료/정지/중지 9
 
9.3%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
18
88 
19
9 

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 88
90.7%
19 9
 
9.3%

Length

2024-05-11T06:42:44.615560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:42:44.916817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 88
90.7%
19 9
 
9.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
사용중
88 
사용중지
9 

Length

Max length4
Median length3
Mean length3.0927835
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 88
90.7%
사용중지 9
 
9.3%

Length

2024-05-11T06:42:45.263809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:42:45.633335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 88
90.7%
사용중지 9
 
9.3%

폐업일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size908.0 B
<NA>
88 
2023-12-07
 
4
42615
 
3
2023-08-01
 
1
41831
 
1

Length

Max length10
Median length4
Mean length4.3505155
Min length4

Unique

Unique2 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 88
90.7%
2023-12-07 4
 
4.1%
42615 3
 
3.1%
2023-08-01 1
 
1.0%
41831 1
 
1.0%

Length

2024-05-11T06:42:46.012934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:42:46.344689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
90.7%
2023-12-07 4
 
4.1%
42615 3
 
3.1%
2023-08-01 1
 
1.0%
41831 1
 
1.0%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing97
Missing (%)100.0%
Memory size1005.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing97
Missing (%)100.0%
Memory size1005.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing97
Missing (%)100.0%
Memory size1005.0 B

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing97
Missing (%)100.0%
Memory size1005.0 B

소재지면적
Real number (ℝ)

Distinct95
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10174.054
Minimum320
Maximum53600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2024-05-11T06:42:46.782960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum320
5-th percentile580.8
Q12383.29
median6272
Q312292
95-th percentile37435.6
Maximum53600
Range53280
Interquartile range (IQR)9908.71

Descriptive statistics

Standard deviation11439.088
Coefficient of variation (CV)1.1243391
Kurtosis3.3744108
Mean10174.054
Median Absolute Deviation (MAD)4207
Skewness1.8913643
Sum986883.28
Variance1.3085272 × 108
MonotonicityNot monotonic
2024-05-11T06:42:47.209896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1184.0 2
 
2.1%
2640.0 2
 
2.1%
320.0 1
 
1.0%
10296.0 1
 
1.0%
43495.0 1
 
1.0%
4364.0 1
 
1.0%
20921.0 1
 
1.0%
8754.0 1
 
1.0%
6363.0 1
 
1.0%
13859.0 1
 
1.0%
Other values (85) 85
87.6%
ValueCountFrequency (%)
320.0 1
1.0%
378.0 1
1.0%
470.0 1
1.0%
486.0 1
1.0%
572.0 1
1.0%
583.0 1
1.0%
723.0 1
1.0%
803.0 1
1.0%
963.0 1
1.0%
1031.0 1
1.0%
ValueCountFrequency (%)
53600.0 1
1.0%
46484.0 1
1.0%
44480.0 1
1.0%
43495.0 1
1.0%
39278.0 1
1.0%
36975.0 1
1.0%
29145.55 1
1.0%
29117.0 1
1.0%
28490.0 1
1.0%
26297.0 1
1.0%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing97
Missing (%)100.0%
Memory size1005.0 B

지번주소
Text

Distinct90
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size908.0 B
2024-05-11T06:42:47.829409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length21.453608
Min length17

Characters and Unicode

Total characters2081
Distinct characters72
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

Unique85 ?
Unique (%)87.6%

Sample

1st row서울특별시 동작구 사당동 1160 사당 롯데캐슬 골든포레 108동
2nd row서울특별시 동작구 사당동 1143번지
3rd row서울특별시 동작구 사당동 1139번지
4th row서울특별시 동작구 사당동 1138번지
5th row서울특별시 동작구 사당동 1145 사당해그린 아파트
ValueCountFrequency (%)
서울특별시 97
21.8%
동작구 97
21.8%
사당동 25
 
5.6%
흑석동 17
 
3.8%
상도동 15
 
3.4%
노량진동 14
 
3.2%
신대방동 10
 
2.3%
1호 10
 
2.3%
본동 7
 
1.6%
대방동 5
 
1.1%
Other values (120) 147
33.1%
2024-05-11T06:42:48.932090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
347
16.7%
동 198
 
9.5%
작 100
 
4.8%
서 97
 
4.7%
울 97
 
4.7%
특 97
 
4.7%
별 97
 
4.7%
시 97
 
4.7%
구 97
 
4.7%
지 90
 
4.3%
Other values (62) 764
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1381
66.4%
Decimal Number 353
 
17.0%
Space Separator 347
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 198
14.3%
작 100
 
7.2%
서 97
 
7.0%
울 97
 
7.0%
특 97
 
7.0%
별 97
 
7.0%
시 97
 
7.0%
구 97
 
7.0%
지 90
 
6.5%
번 88
 
6.4%
Other values (51) 323
23.4%
Decimal Number
ValueCountFrequency (%)
1 78
22.1%
3 55
15.6%
2 47
13.3%
4 46
13.0%
5 33
9.3%
0 25
 
7.1%
7 19
 
5.4%
9 18
 
5.1%
8 17
 
4.8%
6 15
 
4.2%
Space Separator
ValueCountFrequency (%)
347
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1381
66.4%
Common 700
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 198
14.3%
작 100
 
7.2%
서 97
 
7.0%
울 97
 
7.0%
특 97
 
7.0%
별 97
 
7.0%
시 97
 
7.0%
구 97
 
7.0%
지 90
 
6.5%
번 88
 
6.4%
Other values (51) 323
23.4%
Common
ValueCountFrequency (%)
347
49.6%
1 78
 
11.1%
3 55
 
7.9%
2 47
 
6.7%
4 46
 
6.6%
5 33
 
4.7%
0 25
 
3.6%
7 19
 
2.7%
9 18
 
2.6%
8 17
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1381
66.4%
ASCII 700
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
347
49.6%
1 78
 
11.1%
3 55
 
7.9%
2 47
 
6.7%
4 46
 
6.6%
5 33
 
4.7%
0 25
 
3.6%
7 19
 
2.7%
9 18
 
2.6%
8 17
 
2.4%
Hangul
ValueCountFrequency (%)
동 198
14.3%
작 100
 
7.2%
서 97
 
7.0%
울 97
 
7.0%
특 97
 
7.0%
별 97
 
7.0%
시 97
 
7.0%
구 97
 
7.0%
지 90
 
6.5%
번 88
 
6.4%
Other values (51) 323
23.4%

도로명주소
Text

Distinct94
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size908.0 B
2024-05-11T06:42:49.459049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39
Mean length34.164948
Min length23

Characters and Unicode

Total characters3314
Distinct characters213
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

Unique92 ?
Unique (%)94.8%

Sample

1st row서울특별시 동작구 사당로 90, 108동 (사당동, 사당 롯데캐슬 골든포레)
2nd row서울특별시 동작구 사당로2가길 173 (사당동, 남해오네뜨아파트)
3rd row서울특별시 동작구 사당로2가길 102 (사당동, 사당자이아파트)
4th row서울특별시 동작구 사당로2가길 188 (사당동, 삼호그린아파트)
5th row서울특별시 동작구 사당로2길 40 (사당동, 사당해그린 아파트)
ValueCountFrequency (%)
서울특별시 97
 
16.1%
동작구 97
 
16.1%
사당동 25
 
4.1%
상도동 16
 
2.6%
지하 14
 
2.3%
노량진동 14
 
2.3%
흑석동 13
 
2.2%
신대방동 10
 
1.7%
본동 7
 
1.2%
노량진로 7
 
1.2%
Other values (215) 304
50.3%
2024-05-11T06:42:50.517159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
507
 
15.3%
동 225
 
6.8%
작 115
 
3.5%
서 105
 
3.2%
) 103
 
3.1%
( 103
 
3.1%
구 101
 
3.0%
울 100
 
3.0%
시 100
 
3.0%
특 99
 
3.0%
Other values (203) 1756
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2166
65.4%
Space Separator 507
 
15.3%
Decimal Number 326
 
9.8%
Close Punctuation 103
 
3.1%
Open Punctuation 103
 
3.1%
Other Punctuation 92
 
2.8%
Lowercase Letter 8
 
0.2%
Uppercase Letter 6
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 225
 
10.4%
작 115
 
5.3%
서 105
 
4.8%
구 101
 
4.7%
울 100
 
4.6%
시 100
 
4.6%
특 99
 
4.6%
별 99
 
4.6%
로 95
 
4.4%
사 51
 
2.4%
Other values (174) 1076
49.7%
Decimal Number
ValueCountFrequency (%)
1 66
20.2%
2 59
18.1%
3 29
8.9%
9 28
8.6%
0 27
8.3%
7 24
 
7.4%
5 24
 
7.4%
4 24
 
7.4%
8 23
 
7.1%
6 22
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
j 1
12.5%
s 1
12.5%
a 1
12.5%
g 1
12.5%
n 1
12.5%
o 1
12.5%
k 1
12.5%
t 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
33.3%
V 1
16.7%
P 1
16.7%
A 1
16.7%
D 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 91
98.9%
. 1
 
1.1%
Space Separator
ValueCountFrequency (%)
507
100.0%
Close Punctuation
ValueCountFrequency (%)
) 103
100.0%
Open Punctuation
ValueCountFrequency (%)
( 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2166
65.4%
Common 1134
34.2%
Latin 14
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 225
 
10.4%
작 115
 
5.3%
서 105
 
4.8%
구 101
 
4.7%
울 100
 
4.6%
시 100
 
4.6%
특 99
 
4.6%
별 99
 
4.6%
로 95
 
4.4%
사 51
 
2.4%
Other values (174) 1076
49.7%
Common
ValueCountFrequency (%)
507
44.7%
) 103
 
9.1%
( 103
 
9.1%
, 91
 
8.0%
1 66
 
5.8%
2 59
 
5.2%
3 29
 
2.6%
9 28
 
2.5%
0 27
 
2.4%
7 24
 
2.1%
Other values (6) 97
 
8.6%
Latin
ValueCountFrequency (%)
T 2
14.3%
V 1
 
7.1%
P 1
 
7.1%
A 1
 
7.1%
j 1
 
7.1%
s 1
 
7.1%
a 1
 
7.1%
g 1
 
7.1%
n 1
 
7.1%
o 1
 
7.1%
Other values (3) 3
21.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2166
65.4%
ASCII 1148
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
507
44.2%
) 103
 
9.0%
( 103
 
9.0%
, 91
 
7.9%
1 66
 
5.7%
2 59
 
5.1%
3 29
 
2.5%
9 28
 
2.4%
0 27
 
2.4%
7 24
 
2.1%
Other values (19) 111
 
9.7%
Hangul
ValueCountFrequency (%)
동 225
 
10.4%
작 115
 
5.3%
서 105
 
4.8%
구 101
 
4.7%
울 100
 
4.6%
시 100
 
4.6%
특 99
 
4.6%
별 99
 
4.6%
로 95
 
4.4%
사 51
 
2.4%
Other values (174) 1076
49.7%

도로명우편번호
Text

MISSING 

Distinct73
Distinct (%)76.8%
Missing2
Missing (%)2.1%
Memory size908.0 B
2024-05-11T06:42:51.083797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.8421053
Min length4

Characters and Unicode

Total characters460
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

Unique59 ?
Unique (%)62.1%

Sample

1st row07075
2nd row07030
3rd row07028
4th row07031
5th row07029
ValueCountFrequency (%)
07071 5
 
5.3%
06928 4
 
4.2%
06981 3
 
3.2%
06974 3
 
3.2%
06906 3
 
3.2%
06973 2
 
2.1%
06963 2
 
2.1%
06916 2
 
2.1%
06925 2
 
2.1%
6992 2
 
2.1%
Other values (63) 67
70.5%
2024-05-11T06:42:52.337389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 134
29.1%
6 76
16.5%
9 69
15.0%
7 59
12.8%
1 28
 
6.1%
2 24
 
5.2%
8 19
 
4.1%
3 19
 
4.1%
4 14
 
3.0%
5 14
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 456
99.1%
Dash Punctuation 4
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 134
29.4%
6 76
16.7%
9 69
15.1%
7 59
12.9%
1 28
 
6.1%
2 24
 
5.3%
8 19
 
4.2%
3 19
 
4.2%
4 14
 
3.1%
5 14
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 460
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 134
29.1%
6 76
16.5%
9 69
15.0%
7 59
12.8%
1 28
 
6.1%
2 24
 
5.2%
8 19
 
4.1%
3 19
 
4.1%
4 14
 
3.0%
5 14
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 134
29.1%
6 76
16.5%
9 69
15.0%
7 59
12.8%
1 28
 
6.1%
2 24
 
5.2%
8 19
 
4.1%
3 19
 
4.1%
4 14
 
3.0%
5 14
 
3.0%

사업장명
Text

Distinct96
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2024-05-11T06:42:53.057616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length17.371134
Min length7

Characters and Unicode

Total characters1685
Distinct characters197
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

Unique95 ?
Unique (%)97.9%

Sample

1st row사당롯데캐슬골든포레 108동 지하3층주차장
2nd row남해오네뜨아파트 지하주차장 1층
3rd row사당자이아파트 2주차장 지하2층
4th row삼호그린아파트 상가주차장 지하1층
5th row사당해그린 아파트 지하주차장 1층
ValueCountFrequency (%)
지하주차장 68
24.5%
1층 22
 
7.9%
1~2층 15
 
5.4%
1~3층 13
 
4.7%
지하1층 9
 
3.2%
지하1~3층 6
 
2.2%
지하1~2층 6
 
2.2%
1~4층 3
 
1.1%
101동 3
 
1.1%
삼성래미안아파트 2
 
0.7%
Other values (125) 131
47.1%
2024-05-11T06:42:54.492986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
181
 
10.7%
지 104
 
6.2%
하 99
 
5.9%
1 90
 
5.3%
층 87
 
5.2%
차 76
 
4.5%
장 76
 
4.5%
주 75
 
4.5%
아 54
 
3.2%
~ 50
 
3.0%
Other values (187) 793
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1213
72.0%
Decimal Number 197
 
11.7%
Space Separator 181
 
10.7%
Math Symbol 50
 
3.0%
Open Punctuation 17
 
1.0%
Close Punctuation 17
 
1.0%
Other Punctuation 5
 
0.3%
Uppercase Letter 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 104
 
8.6%
하 99
 
8.2%
층 87
 
7.2%
차 76
 
6.3%
장 76
 
6.3%
주 75
 
6.2%
아 54
 
4.5%
트 50
 
4.1%
파 47
 
3.9%
동 25
 
2.1%
Other values (168) 520
42.9%
Decimal Number
ValueCountFrequency (%)
1 90
45.7%
2 37
18.8%
3 29
 
14.7%
0 12
 
6.1%
4 9
 
4.6%
7 7
 
3.6%
9 6
 
3.0%
5 4
 
2.0%
6 2
 
1.0%
8 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
P 2
40.0%
C 2
40.0%
K 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
@ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
181
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1213
72.0%
Common 467
 
27.7%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 104
 
8.6%
하 99
 
8.2%
층 87
 
7.2%
차 76
 
6.3%
장 76
 
6.3%
주 75
 
6.2%
아 54
 
4.5%
트 50
 
4.1%
파 47
 
3.9%
동 25
 
2.1%
Other values (168) 520
42.9%
Common
ValueCountFrequency (%)
181
38.8%
1 90
19.3%
~ 50
 
10.7%
2 37
 
7.9%
3 29
 
6.2%
( 17
 
3.6%
) 17
 
3.6%
0 12
 
2.6%
4 9
 
1.9%
7 7
 
1.5%
Other values (6) 18
 
3.9%
Latin
ValueCountFrequency (%)
P 2
40.0%
C 2
40.0%
K 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1213
72.0%
ASCII 472
 
28.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
181
38.3%
1 90
19.1%
~ 50
 
10.6%
2 37
 
7.8%
3 29
 
6.1%
( 17
 
3.6%
) 17
 
3.6%
0 12
 
2.5%
4 9
 
1.9%
7 7
 
1.5%
Other values (9) 23
 
4.9%
Hangul
ValueCountFrequency (%)
지 104
 
8.6%
하 99
 
8.2%
층 87
 
7.2%
차 76
 
6.3%
장 76
 
6.3%
주 75
 
6.2%
아 54
 
4.5%
트 50
 
4.1%
파 47
 
3.9%
동 25
 
2.1%
Other values (168) 520
42.9%

최종수정일자
Date

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
Minimum2014-07-11 17:52:57
Maximum2024-02-14 10:56:27
2024-05-11T06:42:55.188850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:42:55.781948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
U
92 
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 92
94.8%
I 5
 
5.2%

Length

2024-05-11T06:42:56.357229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:42:56.680607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 92
94.8%
i 5
 
5.2%

데이터갱신일자
Categorical

Distinct20
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size908.0 B
2022-12-24 02:40:00.0
18 
2022-10-30 22:05:00.0
13 
2022-11-01 00:05:00.0
13 
2023-11-30 22:00:00.0
11 
2022-11-01 00:03:00.0
6 
Other values (15)
36 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique6 ?
Unique (%)6.2%

Sample

1st row2022-12-06 22:02:00.0
2nd row2022-12-06 22:02:00.0
3rd row2022-12-06 22:02:00.0
4th row2022-12-06 22:02:00.0
5th row2023-12-02 00:01:00.0

Common Values

ValueCountFrequency (%)
2022-12-24 02:40:00.0 18
18.6%
2022-10-30 22:05:00.0 13
13.4%
2022-11-01 00:05:00.0 13
13.4%
2023-11-30 22:00:00.0 11
11.3%
2022-11-01 00:03:00.0 6
 
6.2%
2023-11-30 22:01:00.0 5
 
5.2%
2022-12-06 22:02:00.0 4
 
4.1%
2023-12-02 00:01:00.0 4
 
4.1%
2022-11-02 00:09:00.0 4
 
4.1%
2018-08-31 23:59:59.0 4
 
4.1%
Other values (10) 15
15.5%

Length

2024-05-11T06:42:57.305731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02:40:00.0 24
12.4%
2023-11-30 20
 
10.3%
2022-11-01 19
 
9.8%
2022-12-24 18
 
9.3%
00:05:00.0 14
 
7.2%
2022-10-30 13
 
6.7%
22:05:00.0 13
 
6.7%
22:00:00.0 11
 
5.7%
00:03:00.0 7
 
3.6%
22:01:00.0 5
 
2.6%
Other values (19) 50
25.8%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing97
Missing (%)100.0%
Memory size1005.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct89
Distinct (%)93.7%
Missing2
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean195734.99
Minimum191691.68
Maximum198363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2024-05-11T06:42:57.840657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191691.68
5-th percentile193173.76
Q1194634.45
median195669.68
Q3197044.89
95-th percentile198119.61
Maximum198363
Range6671.3179
Interquartile range (IQR)2410.436

Descriptive statistics

Standard deviation1621.1199
Coefficient of variation (CV)0.0082822182
Kurtosis-0.69119838
Mean195734.99
Median Absolute Deviation (MAD)1193.3062
Skewness-0.28070972
Sum18594824
Variance2628029.8
MonotonicityNot monotonic
2024-05-11T06:42:58.349915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196122.678608319 3
 
3.1%
197802.436613024 3
 
3.1%
195489.423430508 3
 
3.1%
197884.419059004 1
 
1.0%
195516.598950438 1
 
1.0%
195909.193793374 1
 
1.0%
194728.636441065 1
 
1.0%
194017.823630013 1
 
1.0%
193140.052317678 1
 
1.0%
197521.920612639 1
 
1.0%
Other values (79) 79
81.4%
(Missing) 2
 
2.1%
ValueCountFrequency (%)
191691.678396263 1
1.0%
191831.580904689 1
1.0%
193131.960291844 1
1.0%
193140.052317678 1
1.0%
193167.049947274 1
1.0%
193176.63667583 1
1.0%
193204.782207917 1
1.0%
193232.027896757 1
1.0%
193235.493966882 1
1.0%
193251.639163512 1
1.0%
ValueCountFrequency (%)
198362.996258131 1
 
1.0%
198305.619512013 1
 
1.0%
198289.039514074 1
 
1.0%
198264.117304529 1
 
1.0%
198160.522867056 1
 
1.0%
198102.075352016 1
 
1.0%
198083.195564553 1
 
1.0%
197952.634729818 1
 
1.0%
197884.419059004 1
 
1.0%
197802.436613024 3
3.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct89
Distinct (%)93.7%
Missing2
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean444096.22
Minimum441563.24
Maximum445868.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2024-05-11T06:42:58.898824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441563.24
5-th percentile441965.57
Q1443172.08
median444346.32
Q3445056.14
95-th percentile445644.22
Maximum445868.08
Range4304.8412
Interquartile range (IQR)1884.0642

Descriptive statistics

Standard deviation1162.7463
Coefficient of variation (CV)0.0026182306
Kurtosis-0.93370164
Mean444096.22
Median Absolute Deviation (MAD)963.31038
Skewness-0.37338833
Sum42189141
Variance1351979
MonotonicityNot monotonic
2024-05-11T06:42:59.510285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444705.530165147 3
 
3.1%
443049.214038897 3
 
3.1%
444995.675592494 3
 
3.1%
443202.796249226 1
 
1.0%
445311.807070983 1
 
1.0%
445290.169030964 1
 
1.0%
444904.631279295 1
 
1.0%
445610.919894144 1
 
1.0%
443178.674686446 1
 
1.0%
441563.235294712 1
 
1.0%
Other values (79) 79
81.4%
(Missing) 2
 
2.1%
ValueCountFrequency (%)
441563.235294712 1
1.0%
441636.298345044 1
1.0%
441761.298589927 1
1.0%
441803.965560199 1
1.0%
441864.405844378 1
1.0%
442008.926216025 1
1.0%
442123.305986878 1
1.0%
442211.512440311 1
1.0%
442505.243729118 1
1.0%
442553.172261019 1
1.0%
ValueCountFrequency (%)
445868.076456773 1
1.0%
445764.166038984 1
1.0%
445708.372377286 1
1.0%
445664.797007601 1
1.0%
445658.842192651 1
1.0%
445637.957918936 1
1.0%
445637.87823237 1
1.0%
445611.486175435 1
1.0%
445610.919894144 1
1.0%
445564.835806877 1
1.0%

비상시설위치
Text

MISSING 

Distinct27
Distinct (%)93.1%
Missing68
Missing (%)70.1%
Memory size908.0 B
2024-05-11T06:43:00.085902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length23
Mean length20.793103
Min length19

Characters and Unicode

Total characters603
Distinct characters42
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

Unique25 ?
Unique (%)86.2%

Sample

1st row서울특별시 동작구 사당동 105번지
2nd row서울특별시 동작구 사당동 1134번지
3rd row서울특별시 동작구 상도동 414번지
4th row서울특별시 동작구 동작동 105번지
5th row서울특별시 동작구 사당동 169번지 32호
ValueCountFrequency (%)
서울특별시 29
23.0%
동작구 29
23.0%
사당동 12
 
9.5%
상도동 11
 
8.7%
105번지 3
 
2.4%
신대방동 3
 
2.4%
흑석동 2
 
1.6%
힐스테이트 2
 
1.6%
상도 2
 
1.6%
414번지 2
 
1.6%
Other values (31) 31
24.6%
2024-05-11T06:43:01.202776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
16.1%
동 59
 
9.8%
1 30
 
5.0%
작 30
 
5.0%
울 29
 
4.8%
구 29
 
4.8%
서 29
 
4.8%
시 29
 
4.8%
별 29
 
4.8%
특 29
 
4.8%
Other values (32) 213
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 404
67.0%
Decimal Number 102
 
16.9%
Space Separator 97
 
16.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 59
14.6%
작 30
 
7.4%
울 29
 
7.2%
구 29
 
7.2%
서 29
 
7.2%
시 29
 
7.2%
별 29
 
7.2%
특 29
 
7.2%
지 28
 
6.9%
번 27
 
6.7%
Other values (22) 86
21.3%
Decimal Number
ValueCountFrequency (%)
1 30
29.4%
4 16
15.7%
3 15
14.7%
5 14
13.7%
2 10
 
9.8%
0 7
 
6.9%
7 5
 
4.9%
9 4
 
3.9%
6 1
 
1.0%
Space Separator
ValueCountFrequency (%)
97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 404
67.0%
Common 199
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 59
14.6%
작 30
 
7.4%
울 29
 
7.2%
구 29
 
7.2%
서 29
 
7.2%
시 29
 
7.2%
별 29
 
7.2%
특 29
 
7.2%
지 28
 
6.9%
번 27
 
6.7%
Other values (22) 86
21.3%
Common
ValueCountFrequency (%)
97
48.7%
1 30
 
15.1%
4 16
 
8.0%
3 15
 
7.5%
5 14
 
7.0%
2 10
 
5.0%
0 7
 
3.5%
7 5
 
2.5%
9 4
 
2.0%
6 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 404
67.0%
ASCII 199
33.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
48.7%
1 30
 
15.1%
4 16
 
8.0%
3 15
 
7.5%
5 14
 
7.0%
2 10
 
5.0%
0 7
 
3.5%
7 5
 
2.5%
9 4
 
2.0%
6 1
 
0.5%
Hangul
ValueCountFrequency (%)
동 59
14.6%
작 30
 
7.4%
울 29
 
7.2%
구 29
 
7.2%
서 29
 
7.2%
시 29
 
7.2%
별 29
 
7.2%
특 29
 
7.2%
지 28
 
6.9%
번 27
 
6.7%
Other values (22) 86
21.3%

시설구분명
Categorical

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
<NA>
68 
공공용시설
25 
공공시설
 
4

Length

Max length5
Median length4
Mean length4.257732
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 68
70.1%
공공용시설 25
 
25.8%
공공시설 4
 
4.1%

Length

2024-05-11T06:43:01.758738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:43:02.186472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
70.1%
공공용시설 25
 
25.8%
공공시설 4
 
4.1%

시설명_건물명
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing68
Missing (%)70.1%
Memory size908.0 B
2024-05-11T06:43:02.726817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length17.206897
Min length8

Characters and Unicode

Total characters499
Distinct characters99
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

Unique29 ?
Unique (%)100.0%

Sample

1st row사당우성아파트2단지 지하주차장 1층
2nd row경남아너스빌 지하주차장 1~2층
3rd row상도건영아파트 101동 지하주차장 1층
4th row사당극동아파트 지하주차장 1층
5th row현대아파트 지하주차장 1층
ValueCountFrequency (%)
지하주차장 21
25.3%
1층 8
 
9.6%
1~3층 6
 
7.2%
1~2층 5
 
6.0%
지하1층 3
 
3.6%
힐스테이트 2
 
2.4%
상도 2
 
2.4%
은혜교회 1
 
1.2%
센트럴파크 1
 
1.2%
p1 1
 
1.2%
Other values (33) 33
39.8%
2024-05-11T06:43:03.904703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
 
10.8%
1 31
 
6.2%
지 30
 
6.0%
하 26
 
5.2%
아 25
 
5.0%
차 25
 
5.0%
주 24
 
4.8%
층 24
 
4.8%
트 24
 
4.8%
장 24
 
4.8%
Other values (89) 212
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 361
72.3%
Decimal Number 58
 
11.6%
Space Separator 54
 
10.8%
Math Symbol 13
 
2.6%
Uppercase Letter 5
 
1.0%
Close Punctuation 3
 
0.6%
Open Punctuation 3
 
0.6%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 30
 
8.3%
하 26
 
7.2%
아 25
 
6.9%
차 25
 
6.9%
주 24
 
6.6%
층 24
 
6.6%
트 24
 
6.6%
장 24
 
6.6%
파 22
 
6.1%
동 8
 
2.2%
Other values (72) 129
35.7%
Decimal Number
ValueCountFrequency (%)
1 31
53.4%
3 9
 
15.5%
2 9
 
15.5%
0 5
 
8.6%
4 1
 
1.7%
6 1
 
1.7%
5 1
 
1.7%
9 1
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
P 2
40.0%
C 2
40.0%
K 1
20.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
54
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 361
72.3%
Common 133
 
26.7%
Latin 5
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 30
 
8.3%
하 26
 
7.2%
아 25
 
6.9%
차 25
 
6.9%
주 24
 
6.6%
층 24
 
6.6%
트 24
 
6.6%
장 24
 
6.6%
파 22
 
6.1%
동 8
 
2.2%
Other values (72) 129
35.7%
Common
ValueCountFrequency (%)
54
40.6%
1 31
23.3%
~ 13
 
9.8%
3 9
 
6.8%
2 9
 
6.8%
0 5
 
3.8%
) 3
 
2.3%
( 3
 
2.3%
4 1
 
0.8%
6 1
 
0.8%
Other values (4) 4
 
3.0%
Latin
ValueCountFrequency (%)
P 2
40.0%
C 2
40.0%
K 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 361
72.3%
ASCII 138
 
27.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
39.1%
1 31
22.5%
~ 13
 
9.4%
3 9
 
6.5%
2 9
 
6.5%
0 5
 
3.6%
) 3
 
2.2%
( 3
 
2.2%
P 2
 
1.4%
C 2
 
1.4%
Other values (7) 7
 
5.1%
Hangul
ValueCountFrequency (%)
지 30
 
8.3%
하 26
 
7.2%
아 25
 
6.9%
차 25
 
6.9%
주 24
 
6.6%
층 24
 
6.6%
트 24
 
6.6%
장 24
 
6.6%
파 22
 
6.1%
동 8
 
2.2%
Other values (72) 129
35.7%

해제일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
<NA>
93 
20160902
 
3
20140711
 
1

Length

Max length8
Median length4
Mean length4.1649485
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 93
95.9%
20160902 3
 
3.1%
20140711 1
 
1.0%

Length

2024-05-11T06:43:04.429816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:43:05.037876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 93
95.9%
20160902 3
 
3.1%
20140711 1
 
1.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
031900003190000-S2022000062022-12-23<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2383.29<NA>서울특별시 동작구 사당동 1160 사당 롯데캐슬 골든포레 108동서울특별시 동작구 사당로 90, 108동 (사당동, 사당 롯데캐슬 골든포레)07075사당롯데캐슬골든포레 108동 지하3층주차장2023-07-20 14:20:23U2022-12-06 22:02:00.0<NA>196594.019078443280.825807<NA><NA><NA><NA>
131900003190000-S2003001342003-09-15<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4944.0<NA>서울특별시 동작구 사당동 1143번지서울특별시 동작구 사당로2가길 173 (사당동, 남해오네뜨아파트)07030남해오네뜨아파트 지하주차장 1층2023-07-20 14:26:03U2022-12-06 22:02:00.0<NA>196881.933802442765.323757<NA><NA><NA><NA>
231900003190000-S2003001032003-02-19<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>13777.0<NA>서울특별시 동작구 사당동 1139번지서울특별시 동작구 사당로2가길 102 (사당동, 사당자이아파트)07028사당자이아파트 2주차장 지하2층2023-07-20 14:23:01U2022-12-06 22:02:00.0<NA>196608.871745442945.068602<NA><NA><NA><NA>
331900003190000-S2003001042003-02-19<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>7647.0<NA>서울특별시 동작구 사당동 1138번지서울특별시 동작구 사당로2가길 188 (사당동, 삼호그린아파트)07031삼호그린아파트 상가주차장 지하1층2023-07-20 14:25:10U2022-12-06 22:02:00.0<NA>196862.986014442650.854854<NA><NA><NA><NA>
431900003190000-S2007000052007-07-23<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2983.0<NA>서울특별시 동작구 사당동 1145 사당해그린 아파트서울특별시 동작구 사당로2길 40 (사당동, 사당해그린 아파트)07029사당해그린 아파트 지하주차장 1층2024-01-30 16:27:18U2023-12-02 00:01:00.0<NA>196688.746154443297.718472<NA><NA><NA><NA>
531900003190000-S2008000022008-12-24<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4824.0<NA>서울특별시 동작구 사당동 1141번지서울특별시 동작구 사당로20길 119 (사당동, 르메이에르)07024르메이에르아파트 지하주차장 1층2024-01-19 10:36:50U2023-11-30 22:01:00.0<NA>197604.031352441803.96556<NA><NA><NA><NA>
631900003190000-S2008000012008-12-05<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>5235.0<NA>서울특별시 동작구 사당동 1037번지 9호서울특별시 동작구 사당로26길 130-6 (사당동, 삼성아파트)07016삼성아파트 지하주차장 1층2024-01-19 10:36:25U2023-11-30 22:01:00.0<NA>197952.63473441761.29859<NA><NA><NA><NA>
731900003190000-S2003000852003-02-17<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6497.0<NA>서울특별시 동작구 사당동 105번지서울특별시 동작구 동작대로29길 91 (사당동, 사당우성아파트)6999사당우성아파트2단지 지하주차장 1층2022-12-22 14:08:03U2022-12-24 02:40:00.0<NA>197802.436613443049.214039서울특별시 동작구 사당동 105번지공공용시설사당우성아파트2단지 지하주차장 1층<NA>
831900003190000-S2003000922003-02-19<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>7550.0<NA>서울특별시 동작구 사당동 1134번지서울특별시 동작구 사당로9가길 82 (사당동, 경남아너스빌 아파트)6988경남아너스빌 지하주차장 1~2층2022-12-22 14:09:41U2022-12-24 02:40:00.0<NA>197083.024969442894.978971서울특별시 동작구 사당동 1134번지공공용시설경남아너스빌 지하주차장 1~2층<NA>
931900003190000-S2003000232003-02-14<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>10801.0<NA>서울특별시 동작구 상도동 414번지서울특별시 동작구 만양로 26 (상도동, 건영아파트)6918상도건영아파트 101동 지하주차장 1층2023-06-15 20:59:55U2023-06-17 02:40:00.0<NA>195489.423431444995.675592서울특별시 동작구 상도동 414번지공공용시설상도건영아파트 101동 지하주차장 1층<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
8731900003190000-S1999000051999-09-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>5620.0<NA>서울특별시 동작구 신대방동 425번지서울특별시 동작구 보라매로5길 20 (신대방동, 서울특별시보라매병원)07061시립보라매병원 사랑관 지하주차장 1층2023-11-01 14:51:33U2022-11-01 00:03:00.0<NA>193235.493967443510.420778<NA><NA><NA><NA>
8831900003190000-S2003000022003-02-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1322.0<NA>서울특별시 동작구 노량진동 128번지 2호서울특별시 동작구 노량진로 186 (노량진동)06913고려직업전문학교 지하주차장 1층2023-11-03 10:57:38U2022-11-01 00:05:00.0<NA>195159.843318445611.486175<NA><NA><NA><NA>
8931900003190000-S2003000082003-02-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>8034.0<NA>서울특별시 동작구 상도동 414번지서울특별시 동작구 만양로 26 (상도동, 건영아파트)06918상도건영아파트 지하주차장 1~3층2023-11-03 10:58:19U2022-11-01 00:05:00.0<NA>195489.423431444995.675592<NA><NA><NA><NA>
9031900003190000-S2009000032009-08-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>15955.0<NA>서울특별시 동작구 동작동 326번지서울특별시 동작구 현충로 지하 220 (동작동, 9호선 동작역)06984동작역(9호선) 지하1~3층2024-01-17 11:06:59U2023-11-30 22:00:00.0<NA>198083.195565444447.275763<NA><NA><NA><NA>
9131900003190000-S2009000022009-08-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>9020.0<NA>서울특별시 동작구 본동 475번지 1호서울특별시 동작구 노량진로 지하 238 (본동, 9호선 노들역)06906노들역(9호선) 지하1~2층2024-01-17 11:11:01U2023-11-30 22:00:00.0<NA>195931.30456445764.166039<NA><NA><NA><NA>
9231900003190000-S2009000012009-08-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>8912.0<NA>서울특별시 동작구 노량진동 60번지 11호서울특별시 동작구 노량진로 지하 130 (노량진동, 9호선 노량진역)06922노량진역(9호선) 지하1~2층2024-01-17 11:10:35U2023-11-30 22:00:00.0<NA>194705.650962445708.372377<NA><NA><NA><NA>
9331900003190000-S2003000242003-02-14<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>9100.0<NA>서울특별시 동작구 상도동 26번지 20호서울특별시 동작구 상도로 지하 188 (상도동, 장승배기역)06963장승배기역(7호선) 지하1~3층2024-01-17 11:04:48U2023-11-30 22:00:00.0<NA>194719.816573444724.494334<NA><NA><NA><NA>
9431900003190000-S2003000222003-02-14<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>9240.0<NA>서울특별시 동작구 상도1동 702번지 1호서울특별시 동작구 상도로 지하 272 (상도1동, 상도역(중대입구역)7호선)07032상도역(7호선) 지하2~4층2024-01-17 11:04:26U2023-11-30 22:00:00.0<NA>195269.263442444590.563172<NA><NA><NA><NA>
9531900003190000-S2003000482003-02-14<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>9355.0<NA>서울특별시 동작구 상도동 514번지서울특별시 동작구 상도로 지하 378 (상도동, 7호선 숭실대입구역)07040숭실대입구역(7호선) 지하1~6층2024-01-17 11:05:59U2023-11-30 22:00:00.0<NA>195867.131208443736.609105<NA><NA><NA><NA>
9631900003190000-S2003000332003-02-14<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>8727.0<NA>서울특별시 동작구 대방동 406번지 10호서울특별시 동작구 상도로 지하 76 (대방동, 7호선 신대방삼거리역)07041신대방삼거리역(7호선) 지하1~3층2024-01-17 11:05:32U2023-11-30 22:00:00.0<NA>193537.613234444162.946885<NA><NA><NA><NA>