Overview

Dataset statistics

Number of variables29
Number of observations152
Missing cells1382
Missing cells (%)31.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.6 KiB
Average record size in memory246.9 B

Variable types

Categorical10
Text8
Unsupported6
Numeric4
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-20048/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가일자 is highly imbalanced (51.5%)Imbalance
영업상태코드 is highly imbalanced (73.1%)Imbalance
영업상태명 is highly imbalanced (73.1%)Imbalance
상세영업상태코드 is highly imbalanced (73.1%)Imbalance
상세영업상태명 is highly imbalanced (73.1%)Imbalance
데이터갱신구분 is highly imbalanced (79.1%)Imbalance
해제일자 is highly imbalanced (82.4%)Imbalance
인허가취소일자 has 145 (95.4%) missing valuesMissing
폐업일자 has 145 (95.4%) missing valuesMissing
휴업시작일자 has 152 (100.0%) missing valuesMissing
휴업종료일자 has 152 (100.0%) missing valuesMissing
재개업일자 has 152 (100.0%) missing valuesMissing
전화번호 has 152 (100.0%) missing valuesMissing
소재지우편번호 has 152 (100.0%) missing valuesMissing
업태구분명 has 152 (100.0%) missing valuesMissing
비상시설위치 has 90 (59.2%) missing valuesMissing
시설명_건물명 has 90 (59.2%) 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 started2024-04-29 20:05:45.175694
Analysis finished2024-04-29 20:05:45.997351
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3210000
152 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 152
100.0%

Length

2024-04-30T05:05:46.061561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:05:46.142308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 152
100.0%

관리번호
Text

UNIQUE 

Distinct152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T05:05:46.308301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters2736
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

Unique152 ?
Unique (%)100.0%

Sample

1st row3210000-S202300002
2nd row3210000-S201700013
3rd row3210000-S200800122
4th row3210000-S200800048
5th row3210000-S201700015
ValueCountFrequency (%)
3210000-s202300002 1
 
0.7%
3210000-s200800066 1
 
0.7%
3210000-s200800177 1
 
0.7%
3210000-s201600003 1
 
0.7%
3210000-s200800044 1
 
0.7%
3210000-s200800092 1
 
0.7%
3210000-s200800084 1
 
0.7%
3210000-s201300004 1
 
0.7%
3210000-s200800061 1
 
0.7%
3210000-s200800079 1
 
0.7%
Other values (142) 142
93.4%
2024-04-30T05:05:46.597370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1334
48.8%
2 341
 
12.5%
1 284
 
10.4%
3 189
 
6.9%
- 152
 
5.6%
S 152
 
5.6%
8 124
 
4.5%
6 41
 
1.5%
4 32
 
1.2%
5 31
 
1.1%
Other values (2) 56
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2432
88.9%
Dash Punctuation 152
 
5.6%
Uppercase Letter 152
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1334
54.9%
2 341
 
14.0%
1 284
 
11.7%
3 189
 
7.8%
8 124
 
5.1%
6 41
 
1.7%
4 32
 
1.3%
5 31
 
1.3%
7 30
 
1.2%
9 26
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 152
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2584
94.4%
Latin 152
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1334
51.6%
2 341
 
13.2%
1 284
 
11.0%
3 189
 
7.3%
- 152
 
5.9%
8 124
 
4.8%
6 41
 
1.6%
4 32
 
1.2%
5 31
 
1.2%
7 30
 
1.2%
Latin
ValueCountFrequency (%)
S 152
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1334
48.8%
2 341
 
12.5%
1 284
 
10.4%
3 189
 
6.9%
- 152
 
5.6%
S 152
 
5.6%
8 124
 
4.5%
6 41
 
1.5%
4 32
 
1.2%
5 31
 
1.1%
Other values (2) 56
 
2.0%

인허가일자
Categorical

IMBALANCE 

Distinct22
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2008-09-01
103 
2016-12-30
12 
2019-12-02
 
5
2015-11-25
 
4
2017-04-03
 
3
Other values (17)
25 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique10 ?
Unique (%)6.6%

Sample

1st row2023-12-15
2nd row2017-05-02
3rd row2008-09-01
4th row2008-09-01
5th row2017-01-02

Common Values

ValueCountFrequency (%)
2008-09-01 103
67.8%
2016-12-30 12
 
7.9%
2019-12-02 5
 
3.3%
2015-11-25 4
 
2.6%
2017-04-03 3
 
2.0%
2009-12-01 3
 
2.0%
2011-01-01 2
 
1.3%
2017-05-02 2
 
1.3%
2008-09-30 2
 
1.3%
2013-01-02 2
 
1.3%
Other values (12) 14
 
9.2%

Length

2024-04-30T05:05:46.727638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2008-09-01 103
67.8%
2016-12-30 12
 
7.9%
2019-12-02 5
 
3.3%
2015-11-25 4
 
2.6%
2017-04-03 3
 
2.0%
2009-12-01 3
 
2.0%
2013-01-02 2
 
1.3%
2016-01-21 2
 
1.3%
2009-08-27 2
 
1.3%
2008-09-30 2
 
1.3%
Other values (12) 14
 
9.2%

인허가취소일자
Text

MISSING 

Distinct4
Distinct (%)57.1%
Missing145
Missing (%)95.4%
Memory size1.3 KiB
2024-04-30T05:05:46.833014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length7.1428571
Min length5

Characters and Unicode

Total characters50
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 (%)42.9%

Sample

1st row2023-12-12
2nd row2023-12-01
3rd row2023-08-14
4th row42734
5th row42734
ValueCountFrequency (%)
42734 4
57.1%
2023-12-12 1
 
14.3%
2023-12-01 1
 
14.3%
2023-08-14 1
 
14.3%
2024-04-30T05:05:47.049719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
26.0%
4 9
18.0%
3 7
14.0%
- 6
12.0%
0 5
 
10.0%
1 5
 
10.0%
7 4
 
8.0%
8 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
88.0%
Dash Punctuation 6
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
29.5%
4 9
20.5%
3 7
15.9%
0 5
 
11.4%
1 5
 
11.4%
7 4
 
9.1%
8 1
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
26.0%
4 9
18.0%
3 7
14.0%
- 6
12.0%
0 5
 
10.0%
1 5
 
10.0%
7 4
 
8.0%
8 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
26.0%
4 9
18.0%
3 7
14.0%
- 6
12.0%
0 5
 
10.0%
1 5
 
10.0%
7 4
 
8.0%
8 1
 
2.0%

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1
145 
4
 
7

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 (%)
1 145
95.4%
4 7
 
4.6%

Length

2024-04-30T05:05:47.164338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:05:47.245612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 145
95.4%
4 7
 
4.6%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업/정상
145 
취소/말소/만료/정지/중지
 
7

Length

Max length14
Median length5
Mean length5.4144737
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 145
95.4%
취소/말소/만료/정지/중지 7
 
4.6%

Length

2024-04-30T05:05:47.333212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:05:47.426943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 145
95.4%
취소/말소/만료/정지/중지 7
 
4.6%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
18
145 
19
 
7

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 (%)
18 145
95.4%
19 7
 
4.6%

Length

2024-04-30T05:05:47.506704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:05:47.590234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 145
95.4%
19 7
 
4.6%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
사용중
145 
사용중지
 
7

Length

Max length4
Median length3
Mean length3.0460526
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 145
95.4%
사용중지 7
 
4.6%

Length

2024-04-30T05:05:47.678568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:05:47.762693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 145
95.4%
사용중지 7
 
4.6%

폐업일자
Text

MISSING 

Distinct4
Distinct (%)57.1%
Missing145
Missing (%)95.4%
Memory size1.3 KiB
2024-04-30T05:05:47.856887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length7.1428571
Min length5

Characters and Unicode

Total characters50
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 (%)42.9%

Sample

1st row2023-12-12
2nd row2023-12-01
3rd row2023-08-14
4th row42734
5th row42734
ValueCountFrequency (%)
42734 4
57.1%
2023-12-12 1
 
14.3%
2023-12-01 1
 
14.3%
2023-08-14 1
 
14.3%
2024-04-30T05:05:48.120308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
26.0%
4 9
18.0%
3 7
14.0%
- 6
12.0%
0 5
 
10.0%
1 5
 
10.0%
7 4
 
8.0%
8 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
88.0%
Dash Punctuation 6
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
29.5%
4 9
20.5%
3 7
15.9%
0 5
 
11.4%
1 5
 
11.4%
7 4
 
9.1%
8 1
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
26.0%
4 9
18.0%
3 7
14.0%
- 6
12.0%
0 5
 
10.0%
1 5
 
10.0%
7 4
 
8.0%
8 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
26.0%
4 9
18.0%
3 7
14.0%
- 6
12.0%
0 5
 
10.0%
1 5
 
10.0%
7 4
 
8.0%
8 1
 
2.0%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

소재지면적
Real number (ℝ)

Distinct135
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8332.6971
Minimum280
Maximum84737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T05:05:48.239603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum280
5-th percentile646.5
Q12444.5
median4918.5
Q37126
95-th percentile32953.35
Maximum84737
Range84457
Interquartile range (IQR)4681.5

Descriptive statistics

Standard deviation12647.119
Coefficient of variation (CV)1.5177702
Kurtosis14.198008
Mean8332.6971
Median Absolute Deviation (MAD)2422.5
Skewness3.5650828
Sum1266570
Variance1.5994963 × 108
MonotonicityNot monotonic
2024-04-30T05:05:48.373678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5500.0 7
 
4.6%
4500.0 5
 
3.3%
1553.0 2
 
1.3%
55000.0 2
 
1.3%
1800.0 2
 
1.3%
2400.0 2
 
1.3%
5560.0 2
 
1.3%
2239.0 2
 
1.3%
2146.0 2
 
1.3%
14430.0 1
 
0.7%
Other values (125) 125
82.2%
ValueCountFrequency (%)
280.0 1
0.7%
295.0 1
0.7%
331.8 1
0.7%
334.0 1
0.7%
495.0 1
0.7%
500.0 1
0.7%
530.0 1
0.7%
619.0 1
0.7%
669.0 1
0.7%
829.0 1
0.7%
ValueCountFrequency (%)
84737.0 1
0.7%
64966.0 1
0.7%
56021.26 1
0.7%
55000.0 2
1.3%
49803.0 1
0.7%
37847.0 1
0.7%
34649.0 1
0.7%
31566.0 1
0.7%
28803.0 1
0.7%
28716.0 1
0.7%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

지번주소
Text

Distinct146
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T05:05:48.628396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length21.644737
Min length18

Characters and Unicode

Total characters3290
Distinct characters74
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

Unique140 ?
Unique (%)92.1%

Sample

1st row서울특별시 서초구 우면동 753 서초호반써밋
2nd row서울특별시 서초구 잠원동 76번지
3rd row서울특별시 서초구 반포동 520번지 3호
4th row서울특별시 서초구 반포동 1141번지
5th row서울특별시 서초구 방배동 2909번지
ValueCountFrequency (%)
서울특별시 152
21.2%
서초구 145
20.3%
방배동 36
 
5.0%
서초동 36
 
5.0%
반포동 25
 
3.5%
잠원동 20
 
2.8%
1호 19
 
2.7%
2호 10
 
1.4%
양재동 10
 
1.4%
우면동 8
 
1.1%
Other values (179) 255
35.6%
2024-04-30T05:05:49.021841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
564
17.1%
서 337
 
10.2%
초 183
 
5.6%
동 154
 
4.7%
시 152
 
4.6%
별 152
 
4.6%
특 152
 
4.6%
구 152
 
4.6%
울 152
 
4.6%
지 148
 
4.5%
Other values (64) 1144
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2111
64.2%
Decimal Number 611
 
18.6%
Space Separator 564
 
17.1%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 337
16.0%
초 183
8.7%
동 154
7.3%
시 152
 
7.2%
별 152
 
7.2%
특 152
 
7.2%
구 152
 
7.2%
울 152
 
7.2%
지 148
 
7.0%
번 146
 
6.9%
Other values (52) 383
18.1%
Decimal Number
ValueCountFrequency (%)
1 128
20.9%
3 71
11.6%
2 65
10.6%
7 63
10.3%
4 61
10.0%
6 56
9.2%
0 52
8.5%
8 46
 
7.5%
5 41
 
6.7%
9 28
 
4.6%
Space Separator
ValueCountFrequency (%)
564
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2111
64.2%
Common 1179
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 337
16.0%
초 183
8.7%
동 154
7.3%
시 152
 
7.2%
별 152
 
7.2%
특 152
 
7.2%
구 152
 
7.2%
울 152
 
7.2%
지 148
 
7.0%
번 146
 
6.9%
Other values (52) 383
18.1%
Common
ValueCountFrequency (%)
564
47.8%
1 128
 
10.9%
3 71
 
6.0%
2 65
 
5.5%
7 63
 
5.3%
4 61
 
5.2%
6 56
 
4.7%
0 52
 
4.4%
8 46
 
3.9%
5 41
 
3.5%
Other values (2) 32
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2111
64.2%
ASCII 1179
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
564
47.8%
1 128
 
10.9%
3 71
 
6.0%
2 65
 
5.5%
7 63
 
5.3%
4 61
 
5.2%
6 56
 
4.7%
0 52
 
4.4%
8 46
 
3.9%
5 41
 
3.5%
Other values (2) 32
 
2.7%
Hangul
ValueCountFrequency (%)
서 337
16.0%
초 183
8.7%
동 154
7.3%
시 152
 
7.2%
별 152
 
7.2%
특 152
 
7.2%
구 152
 
7.2%
울 152
 
7.2%
지 148
 
7.0%
번 146
 
6.9%
Other values (52) 383
18.1%

도로명주소
Text

Distinct148
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T05:05:49.231345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length34.315789
Min length25

Characters and Unicode

Total characters5216
Distinct characters261
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

Unique144 ?
Unique (%)94.7%

Sample

1st row서울특별시 서초구 양재대로2길 109 (우면동, 서초호반써밋)
2nd row서울특별시 서초구 반포대로 316 (잠원동, 씨티21)
3rd row서울특별시 서초구 반포대로 217 (반포동, 조달청빌딩)
4th row서울특별시 서초구 신반포로 23 (반포동, 엘루체)
5th row서울특별시 서초구 과천대로 지하 816 (방배동, 남태령역)
ValueCountFrequency (%)
서울특별시 152
 
16.2%
서초구 145
 
15.4%
서초동 37
 
3.9%
방배동 35
 
3.7%
반포동 25
 
2.7%
지하 22
 
2.3%
잠원동 20
 
2.1%
신반포로 11
 
1.2%
양재동 10
 
1.1%
잠원로 9
 
1.0%
Other values (357) 473
50.4%
2024-04-30T05:05:49.547320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
787
 
15.1%
서 391
 
7.5%
초 228
 
4.4%
동 177
 
3.4%
구 162
 
3.1%
) 159
 
3.0%
( 159
 
3.0%
울 156
 
3.0%
시 155
 
3.0%
, 153
 
2.9%
Other values (251) 2689
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3395
65.1%
Space Separator 787
 
15.1%
Decimal Number 527
 
10.1%
Close Punctuation 159
 
3.0%
Open Punctuation 159
 
3.0%
Other Punctuation 155
 
3.0%
Dash Punctuation 18
 
0.3%
Uppercase Letter 16
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 391
 
11.5%
초 228
 
6.7%
동 177
 
5.2%
구 162
 
4.8%
울 156
 
4.6%
시 155
 
4.6%
로 153
 
4.5%
특 152
 
4.5%
별 152
 
4.5%
방 78
 
2.3%
Other values (225) 1591
46.9%
Decimal Number
ValueCountFrequency (%)
1 112
21.3%
2 74
14.0%
3 70
13.3%
4 48
9.1%
7 46
8.7%
8 40
 
7.6%
5 40
 
7.6%
6 38
 
7.2%
0 36
 
6.8%
9 23
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
R 3
18.8%
S 2
12.5%
E 2
12.5%
W 2
12.5%
D 2
12.5%
K 1
 
6.2%
A 1
 
6.2%
O 1
 
6.2%
T 1
 
6.2%
J 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 153
98.7%
& 2
 
1.3%
Space Separator
ValueCountFrequency (%)
787
100.0%
Close Punctuation
ValueCountFrequency (%)
) 159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3395
65.1%
Common 1805
34.6%
Latin 16
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 391
 
11.5%
초 228
 
6.7%
동 177
 
5.2%
구 162
 
4.8%
울 156
 
4.6%
시 155
 
4.6%
로 153
 
4.5%
특 152
 
4.5%
별 152
 
4.5%
방 78
 
2.3%
Other values (225) 1591
46.9%
Common
ValueCountFrequency (%)
787
43.6%
) 159
 
8.8%
( 159
 
8.8%
, 153
 
8.5%
1 112
 
6.2%
2 74
 
4.1%
3 70
 
3.9%
4 48
 
2.7%
7 46
 
2.5%
8 40
 
2.2%
Other values (6) 157
 
8.7%
Latin
ValueCountFrequency (%)
R 3
18.8%
S 2
12.5%
E 2
12.5%
W 2
12.5%
D 2
12.5%
K 1
 
6.2%
A 1
 
6.2%
O 1
 
6.2%
T 1
 
6.2%
J 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3395
65.1%
ASCII 1821
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
787
43.2%
) 159
 
8.7%
( 159
 
8.7%
, 153
 
8.4%
1 112
 
6.2%
2 74
 
4.1%
3 70
 
3.8%
4 48
 
2.6%
7 46
 
2.5%
8 40
 
2.2%
Other values (16) 173
 
9.5%
Hangul
ValueCountFrequency (%)
서 391
 
11.5%
초 228
 
6.7%
동 177
 
5.2%
구 162
 
4.8%
울 156
 
4.6%
시 155
 
4.6%
로 153
 
4.5%
특 152
 
4.5%
별 152
 
4.5%
방 78
 
2.3%
Other values (225) 1591
46.9%

도로명우편번호
Real number (ℝ)

Distinct104
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6626.7303
Minimum6038
Maximum7025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T05:05:49.690008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6038
5-th percentile6503.55
Q16545
median6613.5
Q36725.25
95-th percentile6798.9
Maximum7025
Range987
Interquartile range (IQR)180.25

Descriptive statistics

Standard deviation138.61309
Coefficient of variation (CV)0.020917268
Kurtosis3.9589923
Mean6626.7303
Median Absolute Deviation (MAD)93
Skewness-0.99086764
Sum1007263
Variance19213.589
MonotonicityNot monotonic
2024-04-30T05:05:49.828564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6762 4
 
2.6%
6511 4
 
2.6%
6545 4
 
2.6%
6802 4
 
2.6%
6568 3
 
2.0%
6544 3
 
2.0%
6504 3
 
2.0%
6510 3
 
2.0%
6635 3
 
2.0%
6578 3
 
2.0%
Other values (94) 118
77.6%
ValueCountFrequency (%)
6038 1
 
0.7%
6110 1
 
0.7%
6123 1
 
0.7%
6232 2
1.3%
6501 1
 
0.7%
6502 1
 
0.7%
6503 1
 
0.7%
6504 3
2.0%
6509 1
 
0.7%
6510 3
2.0%
ValueCountFrequency (%)
7025 1
 
0.7%
7013 1
 
0.7%
6802 4
2.6%
6800 2
1.3%
6798 1
 
0.7%
6797 1
 
0.7%
6796 1
 
0.7%
6792 2
1.3%
6785 1
 
0.7%
6780 2
1.3%

사업장명
Text

Distinct151
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T05:05:50.042617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length17.078947
Min length4

Characters and Unicode

Total characters2596
Distinct characters236
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)98.7%

Sample

1st row서초호반써밋아파트 지하1~2층
2nd row씨티21 지하1~2층 주차장
3rd row조달청 지하 1층
4th row엘루체컨벤션 지하2~4층
5th row남태령역 4호선 지하1~지하3층
ValueCountFrequency (%)
주차장 85
 
18.2%
지하1~2층 53
 
11.3%
지하 35
 
7.5%
지하1층 25
 
5.4%
1~2층 16
 
3.4%
지하1~3층 14
 
3.0%
1~3층 7
 
1.5%
1층 7
 
1.5%
방배 6
 
1.3%
3호선 5
 
1.1%
Other values (184) 214
45.8%
2024-04-30T05:05:50.383303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
316
 
12.2%
지 162
 
6.2%
하 153
 
5.9%
층 148
 
5.7%
1 139
 
5.4%
~ 112
 
4.3%
차 103
 
4.0%
주 100
 
3.9%
2 95
 
3.7%
장 90
 
3.5%
Other values (226) 1178
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1852
71.3%
Space Separator 316
 
12.2%
Decimal Number 305
 
11.7%
Math Symbol 112
 
4.3%
Uppercase Letter 7
 
0.3%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 162
 
8.7%
하 153
 
8.3%
층 148
 
8.0%
차 103
 
5.6%
주 100
 
5.4%
장 90
 
4.9%
아 79
 
4.3%
트 73
 
3.9%
파 70
 
3.8%
서 36
 
1.9%
Other values (207) 838
45.2%
Decimal Number
ValueCountFrequency (%)
1 139
45.6%
2 95
31.1%
3 39
 
12.8%
4 12
 
3.9%
7 6
 
2.0%
5 6
 
2.0%
9 4
 
1.3%
6 3
 
1.0%
8 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
T 1
14.3%
J 1
14.3%
W 1
14.3%
S 1
14.3%
E 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
@ 2
50.0%
Space Separator
ValueCountFrequency (%)
316
100.0%
Math Symbol
ValueCountFrequency (%)
~ 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1852
71.3%
Common 737
 
28.4%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 162
 
8.7%
하 153
 
8.3%
층 148
 
8.0%
차 103
 
5.6%
주 100
 
5.4%
장 90
 
4.9%
아 79
 
4.3%
트 73
 
3.9%
파 70
 
3.8%
서 36
 
1.9%
Other values (207) 838
45.2%
Common
ValueCountFrequency (%)
316
42.9%
1 139
18.9%
~ 112
 
15.2%
2 95
 
12.9%
3 39
 
5.3%
4 12
 
1.6%
7 6
 
0.8%
5 6
 
0.8%
9 4
 
0.5%
6 3
 
0.4%
Other values (3) 5
 
0.7%
Latin
ValueCountFrequency (%)
A 2
28.6%
T 1
14.3%
J 1
14.3%
W 1
14.3%
S 1
14.3%
E 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1852
71.3%
ASCII 744
28.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
316
42.5%
1 139
18.7%
~ 112
 
15.1%
2 95
 
12.8%
3 39
 
5.2%
4 12
 
1.6%
7 6
 
0.8%
5 6
 
0.8%
9 4
 
0.5%
6 3
 
0.4%
Other values (9) 12
 
1.6%
Hangul
ValueCountFrequency (%)
지 162
 
8.7%
하 153
 
8.3%
층 148
 
8.0%
차 103
 
5.6%
주 100
 
5.4%
장 90
 
4.9%
아 79
 
4.3%
트 73
 
3.9%
파 70
 
3.8%
서 36
 
1.9%
Other values (207) 838
45.2%

최종수정일자
Date

UNIQUE 

Distinct152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2017-01-17 09:59:45
Maximum2024-03-04 18:08:37
2024-04-30T05:05:50.511290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:05:50.639504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
U
147 
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 147
96.7%
I 5
 
3.3%

Length

2024-04-30T05:05:50.747884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:05:50.828816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 147
96.7%
i 5
 
3.3%

데이터갱신일자
Categorical

Distinct26
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-01 00:07:00.0
61 
2023-07-08 02:40:00.0
28 
2023-11-30 23:00:00.0
8 
2023-02-04 02:40:00.0
8 
2022-12-06 22:09:00.0
7 
Other values (21)
40 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique14 ?
Unique (%)9.2%

Sample

1st row2023-12-01 00:07:00.0
2nd row2023-12-01 00:07:00.0
3rd row2022-12-08 22:02:00.0
4th row2023-12-01 00:08:00.0
5th row2023-12-01 22:03:00.0

Common Values

ValueCountFrequency (%)
2023-12-01 00:07:00.0 61
40.1%
2023-07-08 02:40:00.0 28
18.4%
2023-11-30 23:00:00.0 8
 
5.3%
2023-02-04 02:40:00.0 8
 
5.3%
2022-12-06 22:09:00.0 7
 
4.6%
2023-03-30 02:40:00.0 6
 
3.9%
2023-05-26 08:48:36.0 5
 
3.3%
2023-02-03 02:40:00.0 5
 
3.3%
2018-08-31 23:59:59.0 4
 
2.6%
2023-11-30 22:04:00.0 2
 
1.3%
Other values (16) 18
 
11.8%

Length

2024-04-30T05:05:50.915414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-12-01 65
21.4%
00:07:00.0 61
20.1%
02:40:00.0 52
17.1%
2023-07-08 29
9.5%
2023-11-30 10
 
3.3%
23:00:00.0 8
 
2.6%
2023-02-04 8
 
2.6%
2022-12-06 7
 
2.3%
22:09:00.0 7
 
2.3%
2023-03-30 6
 
2.0%
Other values (27) 51
16.8%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

좌표정보(X)
Real number (ℝ)

Distinct144
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201020.78
Minimum197839.68
Maximum208072.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T05:05:51.031562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum197839.68
5-th percentile198485.26
Q1199663.4
median200846.88
Q3202089.56
95-th percentile204279.13
Maximum208072.63
Range10232.947
Interquartile range (IQR)2426.1553

Descriptive statistics

Standard deviation1811.8264
Coefficient of variation (CV)0.0090131297
Kurtosis0.81401736
Mean201020.78
Median Absolute Deviation (MAD)1196.1861
Skewness0.71998692
Sum30555159
Variance3282714.9
MonotonicityNot monotonic
2024-04-30T05:05:51.365215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200576.608647619 2
 
1.3%
200008.448105672 2
 
1.3%
200538.827495706 2
 
1.3%
199651.963765033 2
 
1.3%
200628.43767533 2
 
1.3%
200394.225955905 2
 
1.3%
202422.251739571 2
 
1.3%
200361.368180707 2
 
1.3%
201552.711589927 1
 
0.7%
201383.30193718 1
 
0.7%
Other values (134) 134
88.2%
ValueCountFrequency (%)
197839.678764919 1
0.7%
198264.117304529 1
0.7%
198359.032400861 1
0.7%
198399.608674928 1
0.7%
198409.59135773 1
0.7%
198432.354182494 1
0.7%
198469.14427566 1
0.7%
198478.53754999 1
0.7%
198490.751641835 1
0.7%
198506.458385404 1
0.7%
ValueCountFrequency (%)
208072.625904312 1
0.7%
205570.093214399 1
0.7%
205329.561120927 1
0.7%
205081.919519016 1
0.7%
204984.537386457 1
0.7%
204964.487244211 1
0.7%
204853.673349105 1
0.7%
204764.540443577 1
0.7%
203881.968015816 1
0.7%
203849.852632304 1
0.7%

좌표정보(Y)
Real number (ℝ)

Distinct144
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean443041.71
Minimum438483.39
Maximum446439.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T05:05:51.483263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438483.39
5-th percentile439609.38
Q1442108.53
median443162.04
Q3444425.56
95-th percentile445611.57
Maximum446439.13
Range7955.7473
Interquartile range (IQR)2317.0285

Descriptive statistics

Standard deviation1827.1022
Coefficient of variation (CV)0.004123996
Kurtosis-0.18177266
Mean443041.71
Median Absolute Deviation (MAD)1186.9678
Skewness-0.49221322
Sum67342340
Variance3338302.6
MonotonicityNot monotonic
2024-04-30T05:05:51.617869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445241.8984183 2
 
1.3%
444099.363020068 2
 
1.3%
445335.667245506 2
 
1.3%
444612.778032093 2
 
1.3%
445580.594039349 2
 
1.3%
444207.694481581 2
 
1.3%
443872.484453417 2
 
1.3%
444737.116217031 2
 
1.3%
444738.474405663 1
 
0.7%
446439.134713956 1
 
0.7%
Other values (134) 134
88.2%
ValueCountFrequency (%)
438483.387454937 1
0.7%
438491.712309438 1
0.7%
438572.422815938 1
0.7%
438648.715942165 1
0.7%
438840.103774693 1
0.7%
438907.277212806 1
0.7%
439241.118196373 1
0.7%
439363.863225029 1
0.7%
439810.25559883 1
0.7%
440215.751657504 1
0.7%
ValueCountFrequency (%)
446439.134713956 1
0.7%
446382.381669803 1
0.7%
446331.380046658 1
0.7%
446247.719636035 1
0.7%
445821.126176834 1
0.7%
445786.44928266 1
0.7%
445706.12537466 1
0.7%
445649.426044828 1
0.7%
445580.594039349 2
1.3%
445522.194176774 1
0.7%

비상시설위치
Text

MISSING 

Distinct60
Distinct (%)96.8%
Missing90
Missing (%)59.2%
Memory size1.3 KiB
2024-04-30T05:05:51.857255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length21.612903
Min length18

Characters and Unicode

Total characters1340
Distinct characters53
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

Unique58 ?
Unique (%)93.5%

Sample

1st row서울특별시 서초구 반포동 128-1 신반포역
2nd row서울특별시 서초구 반포동 16번지 6호
3rd row서울특별시 서초구 내곡동 143번지
4th row서울특별시 서초구 신원동 285번지
5th row서울특별시 서초구 신원동 374번지
ValueCountFrequency (%)
서울특별시 62
20.9%
서초구 60
20.3%
방배동 24
 
8.1%
반포동 16
 
5.4%
1호 10
 
3.4%
서초동 6
 
2.0%
3호 5
 
1.7%
신원동 5
 
1.7%
70번지 4
 
1.4%
내곡동 3
 
1.0%
Other values (87) 101
34.1%
2024-04-30T05:05:52.221130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
234
17.5%
서 130
 
9.7%
초 66
 
4.9%
동 63
 
4.7%
특 62
 
4.6%
별 62
 
4.6%
시 62
 
4.6%
구 62
 
4.6%
울 62
 
4.6%
번 59
 
4.4%
Other values (43) 478
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 863
64.4%
Decimal Number 241
 
18.0%
Space Separator 234
 
17.5%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 130
15.1%
초 66
 
7.6%
동 63
 
7.3%
특 62
 
7.2%
별 62
 
7.2%
시 62
 
7.2%
구 62
 
7.2%
울 62
 
7.2%
번 59
 
6.8%
지 59
 
6.8%
Other values (31) 176
20.4%
Decimal Number
ValueCountFrequency (%)
1 46
19.1%
3 26
10.8%
0 25
10.4%
8 25
10.4%
7 24
10.0%
2 24
10.0%
6 22
9.1%
4 19
7.9%
5 15
 
6.2%
9 15
 
6.2%
Space Separator
ValueCountFrequency (%)
234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 863
64.4%
Common 477
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 130
15.1%
초 66
 
7.6%
동 63
 
7.3%
특 62
 
7.2%
별 62
 
7.2%
시 62
 
7.2%
구 62
 
7.2%
울 62
 
7.2%
번 59
 
6.8%
지 59
 
6.8%
Other values (31) 176
20.4%
Common
ValueCountFrequency (%)
234
49.1%
1 46
 
9.6%
3 26
 
5.5%
0 25
 
5.2%
8 25
 
5.2%
7 24
 
5.0%
2 24
 
5.0%
6 22
 
4.6%
4 19
 
4.0%
5 15
 
3.1%
Other values (2) 17
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 863
64.4%
ASCII 477
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234
49.1%
1 46
 
9.6%
3 26
 
5.5%
0 25
 
5.2%
8 25
 
5.2%
7 24
 
5.0%
2 24
 
5.0%
6 22
 
4.6%
4 19
 
4.0%
5 15
 
3.1%
Other values (2) 17
 
3.6%
Hangul
ValueCountFrequency (%)
서 130
15.1%
초 66
 
7.6%
동 63
 
7.3%
특 62
 
7.2%
별 62
 
7.2%
시 62
 
7.2%
구 62
 
7.2%
울 62
 
7.2%
번 59
 
6.8%
지 59
 
6.8%
Other values (31) 176
20.4%

시설구분명
Categorical

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
90 
공공용시설
58 
공공시설
 
4

Length

Max length5
Median length4
Mean length4.3815789
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> 90
59.2%
공공용시설 58
38.2%
공공시설 4
 
2.6%

Length

2024-04-30T05:05:52.342607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:05:52.429190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 90
59.2%
공공용시설 58
38.2%
공공시설 4
 
2.6%

시설명_건물명
Text

MISSING 

Distinct61
Distinct (%)98.4%
Missing90
Missing (%)59.2%
Memory size1.3 KiB
2024-04-30T05:05:52.594808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21.5
Mean length17.322581
Min length4

Characters and Unicode

Total characters1074
Distinct characters152
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

Unique60 ?
Unique (%)96.8%

Sample

1st row신반포역 9호선 지하1~2층
2nd row반포힐스테이트아파트 지하1~2층 주차장
3rd row서초포레스타 2단지아파트 지하1~2층 주차장
4th row서초포레스타 6단지아파트 지하1층 주차장
5th row서초포레스타 5단지아파트 지하1~2층 주차장
ValueCountFrequency (%)
주차장 33
17.6%
지하1~2층 22
 
11.8%
지하 16
 
8.6%
지하1층 9
 
4.8%
1~2층 7
 
3.7%
방배 5
 
2.7%
1~3층 5
 
2.7%
서초포레스타 4
 
2.1%
지하1~3층 3
 
1.6%
지하1~4층 3
 
1.6%
Other values (76) 80
42.8%
2024-04-30T05:05:52.913083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
125
 
11.6%
지 66
 
6.1%
하 61
 
5.7%
층 58
 
5.4%
1 55
 
5.1%
~ 48
 
4.5%
차 42
 
3.9%
아 39
 
3.6%
2 38
 
3.5%
주 37
 
3.4%
Other values (142) 505
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 773
72.0%
Space Separator 125
 
11.6%
Decimal Number 124
 
11.5%
Math Symbol 48
 
4.5%
Other Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 66
 
8.5%
하 61
 
7.9%
층 58
 
7.5%
차 42
 
5.4%
아 39
 
5.0%
주 37
 
4.8%
트 37
 
4.8%
파 36
 
4.7%
장 35
 
4.5%
방 18
 
2.3%
Other values (129) 344
44.5%
Decimal Number
ValueCountFrequency (%)
1 55
44.4%
2 38
30.6%
3 12
 
9.7%
4 7
 
5.6%
7 4
 
3.2%
5 4
 
3.2%
9 2
 
1.6%
8 1
 
0.8%
6 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
@ 2
50.0%
Space Separator
ValueCountFrequency (%)
125
100.0%
Math Symbol
ValueCountFrequency (%)
~ 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 773
72.0%
Common 301
 
28.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 66
 
8.5%
하 61
 
7.9%
층 58
 
7.5%
차 42
 
5.4%
아 39
 
5.0%
주 37
 
4.8%
트 37
 
4.8%
파 36
 
4.7%
장 35
 
4.5%
방 18
 
2.3%
Other values (129) 344
44.5%
Common
ValueCountFrequency (%)
125
41.5%
1 55
18.3%
~ 48
 
15.9%
2 38
 
12.6%
3 12
 
4.0%
4 7
 
2.3%
7 4
 
1.3%
5 4
 
1.3%
, 2
 
0.7%
@ 2
 
0.7%
Other values (3) 4
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 773
72.0%
ASCII 301
 
28.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
125
41.5%
1 55
18.3%
~ 48
 
15.9%
2 38
 
12.6%
3 12
 
4.0%
4 7
 
2.3%
7 4
 
1.3%
5 4
 
1.3%
, 2
 
0.7%
@ 2
 
0.7%
Other values (3) 4
 
1.3%
Hangul
ValueCountFrequency (%)
지 66
 
8.5%
하 61
 
7.9%
층 58
 
7.5%
차 42
 
5.4%
아 39
 
5.0%
주 37
 
4.8%
트 37
 
4.8%
파 36
 
4.7%
장 35
 
4.5%
방 18
 
2.3%
Other values (129) 344
44.5%

해제일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
148 
20161230
 
4

Length

Max length8
Median length4
Mean length4.1052632
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> 148
97.4%
20161230 4
 
2.6%

Length

2024-04-30T05:05:53.035189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:05:53.126501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 148
97.4%
20161230 4
 
2.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
032100003210000-S2023000022023-12-15<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>34649.0<NA>서울특별시 서초구 우면동 753 서초호반써밋서울특별시 서초구 양재대로2길 109 (우면동, 서초호반써밋)6767서초호반써밋아파트 지하1~2층2024-01-05 16:40:53U2023-12-01 00:07:00.0<NA>201102.694119439363.863225<NA><NA><NA><NA>
132100003210000-S2017000132017-05-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2970.0<NA>서울특별시 서초구 잠원동 76번지서울특별시 서초구 반포대로 316 (잠원동, 씨티21)6509씨티21 지하1~2층 주차장2024-01-05 15:02:33U2023-12-01 00:07:00.0<NA>199988.339466445001.037013<NA><NA><NA><NA>
232100003210000-S2008001222008-09-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1300.0<NA>서울특별시 서초구 반포동 520번지 3호서울특별시 서초구 반포대로 217 (반포동, 조달청빌딩)6578조달청 지하 1층2023-09-20 13:21:19U2022-12-08 22:02:00.0<NA>200194.426588444128.805256<NA><NA><NA><NA>
332100003210000-S2008000482008-09-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1600.0<NA>서울특별시 서초구 반포동 1141번지서울특별시 서초구 신반포로 23 (반포동, 엘루체)6502엘루체컨벤션 지하2~4층2024-01-06 18:03:49U2023-12-01 00:08:00.0<NA>198791.788015444392.672549<NA><NA><NA><NA>
432100003210000-S2017000152017-01-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3709.6<NA>서울특별시 서초구 방배동 2909번지서울특별시 서초구 과천대로 지하 816 (방배동, 남태령역)6761남태령역 4호선 지하1~지하3층2024-02-21 13:51:19U2023-12-01 22:03:00.0<NA>198981.625784440245.26424<NA><NA><NA><NA>
532100003210000-S2016000112016-12-30<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2771.0<NA>서울특별시 서초구 잠원동 157번지서울특별시 서초구 신반포로33길 15 (잠원동, 동아아파트)6521동아아파트 지하1~3층 주차장2024-01-05 15:00:34U2023-12-01 00:07:00.0<NA>200828.122824445167.786946<NA><NA><NA><NA>
632100003210000-S2016000052016-12-30<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2239.0<NA>서울특별시 서초구 잠원동 70번지 1호서울특별시 서초구 잠원로 69 (잠원동, 킴스클럽)6511킴스클럽 지하3층 주차장2024-01-05 14:58:27U2023-12-01 00:07:00.0<NA>200538.827496445335.667246<NA><NA><NA><NA>
732100003210000-S2008000462008-09-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>5863.0<NA>서울특별시 서초구 잠원동 58번지서울특별시 서초구 나루터로 46 (잠원동, 금호베스트빌아파트)6523금호베스트빌 지하1~2층2024-01-08 17:04:06U2023-11-30 23:00:00.0<NA>201180.951711445821.126177<NA><NA><NA><NA>
832100003210000-S2008001802008-09-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>5500.0<NA>서울특별시 서초구 반포동 128-1 신반포역서울특별시 서초구 신반포로 지하105, 신반포역 (반포동)6504신반포역 9호선 지하1~2층2023-07-06 14:03:23I2023-07-08 00:19:04.0<NA>199651.963765444612.778032서울특별시 서초구 반포동 128-1 신반포역공공용시설신반포역 9호선 지하1~2층<NA>
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
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14332100003210000-S2008001072008-09-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>331.8<NA>서울특별시 서초구 방배동 446번지 2호서울특별시 서초구 방배천로2길 12 (방배동)6693사조빌딩 지하2층 주차장2024-01-05 15:20:08U2023-12-01 00:07:00.0<NA>198478.53755441630.724842<NA><NA><NA><NA>
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14832100003210000-S2008000112008-09-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3526.0<NA>서울특별시 서초구 서초동 1347번지 20호서울특별시 서초구 효령로74길 56 (서초동, 서초벽산블루밍아파트)6726서초벽산블루밍아파트 지하1~2층 주차장2024-01-05 15:36:28U2023-12-01 00:07:00.0<NA>202232.727557442624.511401<NA><NA><NA><NA>
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