Overview

Dataset statistics

Number of variables29
Number of observations128
Missing cells1141
Missing cells (%)30.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.8 KiB
Average record size in memory246.0 B

Variable types

Categorical7
Text7
DateTime5
Unsupported6
Numeric4

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),비상시설위치,시설구분명,시설명_건물명,해제일자
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20016/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
데이터갱신구분 is highly imbalanced (57.7%)Imbalance
시설구분명 is highly imbalanced (54.9%)Imbalance
인허가취소일자 has 46 (35.9%) missing valuesMissing
폐업일자 has 46 (35.9%) missing valuesMissing
휴업시작일자 has 128 (100.0%) missing valuesMissing
휴업종료일자 has 128 (100.0%) missing valuesMissing
재개업일자 has 128 (100.0%) missing valuesMissing
전화번호 has 128 (100.0%) missing valuesMissing
소재지우편번호 has 128 (100.0%) missing valuesMissing
도로명주소 has 56 (43.8%) missing valuesMissing
도로명우편번호 has 56 (43.8%) missing valuesMissing
업태구분명 has 128 (100.0%) missing valuesMissing
좌표정보(X) has 57 (44.5%) missing valuesMissing
좌표정보(Y) has 57 (44.5%) missing valuesMissing
비상시설위치 has 3 (2.3%) missing valuesMissing
시설명_건물명 has 3 (2.3%) missing valuesMissing
해제일자 has 49 (38.3%) missing valuesMissing
관리번호 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 00:39:52.906484
Analysis finished2024-05-11 00:39:54.051236
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3140000
128 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 128
100.0%

Length

2024-05-11T00:39:54.256579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:39:54.991993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 128
100.0%

관리번호
Text

UNIQUE 

Distinct128
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T00:39:55.422579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters2304
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

Unique128 ?
Unique (%)100.0%

Sample

1st row3140000-E200200002
2nd row3140000-E200200003
3rd row3140000-E200200004
4th row3140000-E200200005
5th row3140000-E200200006
ValueCountFrequency (%)
3140000-e200200002 1
 
0.8%
3140000-e200200003 1
 
0.8%
3140000-e201100001 1
 
0.8%
3140000-e201000003 1
 
0.8%
3140000-e201000002 1
 
0.8%
3140000-e200800001 1
 
0.8%
3140000-e200700020 1
 
0.8%
3140000-e200700018 1
 
0.8%
3140000-e200700016 1
 
0.8%
3140000-e200700015 1
 
0.8%
Other values (118) 118
92.2%
2024-05-11T00:39:56.772676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1183
51.3%
2 227
 
9.9%
1 212
 
9.2%
3 164
 
7.1%
4 154
 
6.7%
- 128
 
5.6%
E 128
 
5.6%
7 40
 
1.7%
5 26
 
1.1%
6 21
 
0.9%
Other values (2) 21
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2048
88.9%
Dash Punctuation 128
 
5.6%
Uppercase Letter 128
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1183
57.8%
2 227
 
11.1%
1 212
 
10.4%
3 164
 
8.0%
4 154
 
7.5%
7 40
 
2.0%
5 26
 
1.3%
6 21
 
1.0%
8 13
 
0.6%
9 8
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2176
94.4%
Latin 128
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1183
54.4%
2 227
 
10.4%
1 212
 
9.7%
3 164
 
7.5%
4 154
 
7.1%
- 128
 
5.9%
7 40
 
1.8%
5 26
 
1.2%
6 21
 
1.0%
8 13
 
0.6%
Latin
ValueCountFrequency (%)
E 128
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1183
51.3%
2 227
 
9.9%
1 212
 
9.2%
3 164
 
7.1%
4 154
 
6.7%
- 128
 
5.6%
E 128
 
5.6%
7 40
 
1.7%
5 26
 
1.1%
6 21
 
0.9%
Other values (2) 21
 
0.9%

인허가일자
Date

Distinct22
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2002-11-01 00:00:00
Maximum2020-11-09 00:00:00
2024-05-11T00:39:57.413537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:39:57.932547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

인허가취소일자
Date

MISSING 

Distinct25
Distinct (%)30.5%
Missing46
Missing (%)35.9%
Memory size1.1 KiB
Minimum2003-09-30 00:00:00
Maximum2023-05-19 00:00:00
2024-05-11T00:39:58.401390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:39:58.984668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

영업상태코드
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
4
82 
1
46 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row4

Common Values

ValueCountFrequency (%)
4 82
64.1%
1 46
35.9%

Length

2024-05-11T00:39:59.678549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:40:00.073699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 82
64.1%
1 46
35.9%

영업상태명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
취소/말소/만료/정지/중지
82 
영업/정상
46 

Length

Max length14
Median length14
Mean length10.765625
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row취소/말소/만료/정지/중지

Common Values

ValueCountFrequency (%)
취소/말소/만료/정지/중지 82
64.1%
영업/정상 46
35.9%

Length

2024-05-11T00:40:00.450453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:40:00.937044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취소/말소/만료/정지/중지 82
64.1%
영업/정상 46
35.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
19
82 
18
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row18
2nd row18
3rd row18
4th row18
5th row19

Common Values

ValueCountFrequency (%)
19 82
64.1%
18 46
35.9%

Length

2024-05-11T00:40:01.383234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:40:01.722320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
19 82
64.1%
18 46
35.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
사용중지
82 
사용중
46 

Length

Max length4
Median length4
Mean length3.640625
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중지 82
64.1%
사용중 46
35.9%

Length

2024-05-11T00:40:02.092461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:40:02.555806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중지 82
64.1%
사용중 46
35.9%

폐업일자
Date

MISSING 

Distinct25
Distinct (%)30.5%
Missing46
Missing (%)35.9%
Memory size1.1 KiB
Minimum2003-09-30 00:00:00
Maximum2023-05-19 00:00:00
2024-05-11T00:40:03.037563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:40:03.536971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing128
Missing (%)100.0%
Memory size1.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing128
Missing (%)100.0%
Memory size1.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing128
Missing (%)100.0%
Memory size1.3 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing128
Missing (%)100.0%
Memory size1.3 KiB

소재지면적
Real number (ℝ)

Distinct57
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean247.87187
Minimum30
Maximum8184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T00:40:04.120815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile30
Q153.25
median80
Q3100
95-th percentile1085.2
Maximum8184
Range8154
Interquartile range (IQR)46.75

Descriptive statistics

Standard deviation769.7189
Coefficient of variation (CV)3.1053095
Kurtosis90.429989
Mean247.87187
Median Absolute Deviation (MAD)26
Skewness8.9071009
Sum31727.6
Variance592467.18
MonotonicityNot monotonic
2024-05-11T00:40:04.720875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 13
 
10.2%
50.0 12
 
9.4%
60.0 11
 
8.6%
100.0 10
 
7.8%
80.0 9
 
7.0%
90.0 8
 
6.2%
40.0 4
 
3.1%
86.0 3
 
2.3%
88.0 2
 
1.6%
300.0 2
 
1.6%
Other values (47) 54
42.2%
ValueCountFrequency (%)
30.0 13
10.2%
35.0 1
 
0.8%
40.0 4
 
3.1%
50.0 12
9.4%
51.0 2
 
1.6%
54.0 2
 
1.6%
55.0 1
 
0.8%
56.0 1
 
0.8%
60.0 11
8.6%
65.0 2
 
1.6%
ValueCountFrequency (%)
8184.0 1
0.8%
1640.0 1
0.8%
1370.0 1
0.8%
1201.0 1
0.8%
1182.0 1
0.8%
1100.0 1
0.8%
1095.0 1
0.8%
1067.0 1
0.8%
957.0 1
0.8%
870.0 1
0.8%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing128
Missing (%)100.0%
Memory size1.3 KiB

지번주소
Text

Distinct127
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T00:40:05.825191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length17.765625
Min length7

Characters and Unicode

Total characters2274
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

Unique126 ?
Unique (%)98.4%

Sample

1st row서울특별시 양천구 목동 735번지
2nd row서울특별시 양천구 신월동 425번지 2호
3rd row서울특별시 양천구 목동 906번지
4th row서울특별시 양천구 신월동 591번지 1호
5th row신월6동 591-5
ValueCountFrequency (%)
서울특별시 83
 
16.5%
양천구 83
 
16.5%
신정동 29
 
5.8%
목동 28
 
5.6%
신월동 26
 
5.2%
1호 16
 
3.2%
호 9
 
1.8%
신월6동 7
 
1.4%
2호 7
 
1.4%
신월7동 6
 
1.2%
Other values (161) 208
41.4%
2024-05-11T00:40:07.357534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
403
 
17.7%
동 128
 
5.6%
1 127
 
5.6%
신 88
 
3.9%
서 85
 
3.7%
양 85
 
3.7%
천 85
 
3.7%
특 84
 
3.7%
별 84
 
3.7%
시 84
 
3.7%
Other values (31) 1021
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1264
55.6%
Decimal Number 567
24.9%
Space Separator 403
 
17.7%
Dash Punctuation 39
 
1.7%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 128
 
10.1%
신 88
 
7.0%
서 85
 
6.7%
양 85
 
6.7%
천 85
 
6.7%
특 84
 
6.6%
별 84
 
6.6%
시 84
 
6.6%
울 84
 
6.6%
구 83
 
6.6%
Other values (18) 374
29.6%
Decimal Number
ValueCountFrequency (%)
1 127
22.4%
2 62
10.9%
5 60
10.6%
3 56
9.9%
9 53
9.3%
4 46
 
8.1%
0 45
 
7.9%
7 41
 
7.2%
8 40
 
7.1%
6 37
 
6.5%
Space Separator
ValueCountFrequency (%)
403
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1264
55.6%
Common 1010
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 128
 
10.1%
신 88
 
7.0%
서 85
 
6.7%
양 85
 
6.7%
천 85
 
6.7%
특 84
 
6.6%
별 84
 
6.6%
시 84
 
6.6%
울 84
 
6.6%
구 83
 
6.6%
Other values (18) 374
29.6%
Common
ValueCountFrequency (%)
403
39.9%
1 127
 
12.6%
2 62
 
6.1%
5 60
 
5.9%
3 56
 
5.5%
9 53
 
5.2%
4 46
 
4.6%
0 45
 
4.5%
7 41
 
4.1%
8 40
 
4.0%
Other values (3) 77
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1264
55.6%
ASCII 1010
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
403
39.9%
1 127
 
12.6%
2 62
 
6.1%
5 60
 
5.9%
3 56
 
5.5%
9 53
 
5.2%
4 46
 
4.6%
0 45
 
4.5%
7 41
 
4.1%
8 40
 
4.0%
Other values (3) 77
 
7.6%
Hangul
ValueCountFrequency (%)
동 128
 
10.1%
신 88
 
7.0%
서 85
 
6.7%
양 85
 
6.7%
천 85
 
6.7%
특 84
 
6.6%
별 84
 
6.6%
시 84
 
6.6%
울 84
 
6.6%
구 83
 
6.6%
Other values (18) 374
29.6%

도로명주소
Text

MISSING 

Distinct71
Distinct (%)98.6%
Missing56
Missing (%)43.8%
Memory size1.1 KiB
2024-05-11T00:40:08.291136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length26.444444
Min length21

Characters and Unicode

Total characters1904
Distinct characters119
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)97.2%

Sample

1st row서울특별시 양천구 목동중앙남로 27 (목동)
2nd row서울특별시 양천구 오목로5길 34 (신월동)
3rd row서울특별시 양천구 목동동로 363 (목동)
4th row서울특별시 양천구 중앙로29길 55 (신월동)
5th row서울특별시 양천구 목동중앙로 143 (목동)
ValueCountFrequency (%)
서울특별시 72
18.8%
양천구 72
18.8%
신월동 26
 
6.8%
신정동 25
 
6.5%
목동 21
 
5.5%
신정로 4
 
1.0%
남부순환로 4
 
1.0%
목동로 4
 
1.0%
등촌로 4
 
1.0%
13 3
 
0.8%
Other values (121) 147
38.5%
2024-05-11T00:40:09.608202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
 
16.3%
동 100
 
5.3%
양 80
 
4.2%
서 79
 
4.1%
천 77
 
4.0%
특 73
 
3.8%
별 73
 
3.8%
시 73
 
3.8%
울 73
 
3.8%
로 72
 
3.8%
Other values (109) 894
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1210
63.6%
Space Separator 310
 
16.3%
Decimal Number 216
 
11.3%
Close Punctuation 72
 
3.8%
Open Punctuation 72
 
3.8%
Other Punctuation 21
 
1.1%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 100
 
8.3%
양 80
 
6.6%
서 79
 
6.5%
천 77
 
6.4%
특 73
 
6.0%
별 73
 
6.0%
시 73
 
6.0%
울 73
 
6.0%
로 72
 
6.0%
구 72
 
6.0%
Other values (94) 438
36.2%
Decimal Number
ValueCountFrequency (%)
1 40
18.5%
3 36
16.7%
2 31
14.4%
7 24
11.1%
6 20
9.3%
5 20
9.3%
0 18
8.3%
4 14
 
6.5%
9 8
 
3.7%
8 5
 
2.3%
Space Separator
ValueCountFrequency (%)
310
100.0%
Close Punctuation
ValueCountFrequency (%)
) 72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 72
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1210
63.6%
Common 694
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 100
 
8.3%
양 80
 
6.6%
서 79
 
6.5%
천 77
 
6.4%
특 73
 
6.0%
별 73
 
6.0%
시 73
 
6.0%
울 73
 
6.0%
로 72
 
6.0%
구 72
 
6.0%
Other values (94) 438
36.2%
Common
ValueCountFrequency (%)
310
44.7%
) 72
 
10.4%
( 72
 
10.4%
1 40
 
5.8%
3 36
 
5.2%
2 31
 
4.5%
7 24
 
3.5%
, 21
 
3.0%
6 20
 
2.9%
5 20
 
2.9%
Other values (5) 48
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1210
63.6%
ASCII 694
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
44.7%
) 72
 
10.4%
( 72
 
10.4%
1 40
 
5.8%
3 36
 
5.2%
2 31
 
4.5%
7 24
 
3.5%
, 21
 
3.0%
6 20
 
2.9%
5 20
 
2.9%
Other values (5) 48
 
6.9%
Hangul
ValueCountFrequency (%)
동 100
 
8.3%
양 80
 
6.6%
서 79
 
6.5%
천 77
 
6.4%
특 73
 
6.0%
별 73
 
6.0%
시 73
 
6.0%
울 73
 
6.0%
로 72
 
6.0%
구 72
 
6.0%
Other values (94) 438
36.2%

도로명우편번호
Text

MISSING 

Distinct58
Distinct (%)80.6%
Missing56
Missing (%)43.8%
Memory size1.1 KiB
2024-05-11T00:40:10.308634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5694444
Min length5

Characters and Unicode

Total characters401
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

Unique47 ?
Unique (%)65.3%

Sample

1st row158815
2nd row158832
3rd row158877
4th row158788
5th row158779
ValueCountFrequency (%)
158832 3
 
4.2%
158070 3
 
4.2%
07900 3
 
4.2%
158050 2
 
2.8%
158819 2
 
2.8%
158818 2
 
2.8%
07904 2
 
2.8%
07946 2
 
2.8%
08108 2
 
2.8%
07905 2
 
2.8%
Other values (48) 49
68.1%
2024-05-11T00:40:11.376897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 95
23.7%
0 76
19.0%
1 61
15.2%
5 58
14.5%
7 39
9.7%
9 23
 
5.7%
3 16
 
4.0%
4 13
 
3.2%
6 10
 
2.5%
2 9
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 95
23.8%
0 76
19.0%
1 61
15.2%
5 58
14.5%
7 39
9.8%
9 23
 
5.8%
3 16
 
4.0%
4 13
 
3.2%
6 10
 
2.5%
2 9
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 401
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 95
23.7%
0 76
19.0%
1 61
15.2%
5 58
14.5%
7 39
9.7%
9 23
 
5.7%
3 16
 
4.0%
4 13
 
3.2%
6 10
 
2.5%
2 9
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 401
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 95
23.7%
0 76
19.0%
1 61
15.2%
5 58
14.5%
7 39
9.7%
9 23
 
5.7%
3 16
 
4.0%
4 13
 
3.2%
6 10
 
2.5%
2 9
 
2.2%

사업장명
Text

Distinct125
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T00:40:12.376153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length7.171875
Min length2

Characters and Unicode

Total characters918
Distinct characters222
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

Unique122 ?
Unique (%)95.3%

Sample

1st row강서고등학교
2nd row신월4동주민센터
3rd row파리공원
4th row신안약수아파트
5th row신안약수아파트
ValueCountFrequency (%)
신트리공원 2
 
1.5%
사우나 2
 
1.5%
양천고등학교 2
 
1.5%
신안약수아파트 2
 
1.5%
백화점 1
 
0.7%
수명산롯데캐슬아파트 1
 
0.7%
강서고등학교 1
 
0.7%
진명여고 1
 
0.7%
얼음막걸리 1
 
0.7%
목동11단지아파트 1
 
0.7%
Other values (120) 120
89.6%
2024-05-11T00:40:13.744373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 45
 
4.9%
( 45
 
4.9%
신 22
 
2.4%
수 20
 
2.2%
원 18
 
2.0%
동 18
 
2.0%
주 17
 
1.9%
교 17
 
1.9%
트 17
 
1.9%
아 17
 
1.9%
Other values (212) 682
74.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 799
87.0%
Close Punctuation 45
 
4.9%
Open Punctuation 45
 
4.9%
Decimal Number 19
 
2.1%
Space Separator 6
 
0.7%
Dash Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 22
 
2.8%
수 20
 
2.5%
원 18
 
2.3%
동 18
 
2.3%
주 17
 
2.1%
교 17
 
2.1%
트 17
 
2.1%
아 17
 
2.1%
파 16
 
2.0%
성 13
 
1.6%
Other values (197) 624
78.1%
Decimal Number
ValueCountFrequency (%)
4 4
21.1%
1 3
15.8%
6 3
15.8%
2 3
15.8%
0 2
10.5%
9 1
 
5.3%
7 1
 
5.3%
5 1
 
5.3%
3 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 799
87.0%
Common 117
 
12.7%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 22
 
2.8%
수 20
 
2.5%
원 18
 
2.3%
동 18
 
2.3%
주 17
 
2.1%
교 17
 
2.1%
트 17
 
2.1%
아 17
 
2.1%
파 16
 
2.0%
성 13
 
1.6%
Other values (197) 624
78.1%
Common
ValueCountFrequency (%)
) 45
38.5%
( 45
38.5%
6
 
5.1%
4 4
 
3.4%
1 3
 
2.6%
6 3
 
2.6%
2 3
 
2.6%
0 2
 
1.7%
- 2
 
1.7%
9 1
 
0.9%
Other values (3) 3
 
2.6%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 799
87.0%
ASCII 119
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 45
37.8%
( 45
37.8%
6
 
5.0%
4 4
 
3.4%
1 3
 
2.5%
6 3
 
2.5%
2 3
 
2.5%
0 2
 
1.7%
- 2
 
1.7%
9 1
 
0.8%
Other values (5) 5
 
4.2%
Hangul
ValueCountFrequency (%)
신 22
 
2.8%
수 20
 
2.5%
원 18
 
2.3%
동 18
 
2.3%
주 17
 
2.1%
교 17
 
2.1%
트 17
 
2.1%
아 17
 
2.1%
파 16
 
2.0%
성 13
 
1.6%
Other values (197) 624
78.1%

최종수정일자
Date

Distinct86
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2006-05-26 00:00:00
Maximum2023-05-22 09:44:14
2024-05-11T00:40:14.528136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:40:15.383386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
I
117 
U
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 117
91.4%
U 11
 
8.6%

Length

2024-05-11T00:40:15.923247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:40:16.320294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 117
91.4%
u 11
 
8.6%

데이터갱신일자
Date

Distinct12
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-08-31 23:59:59
Maximum2022-12-04 22:04:00
2024-05-11T00:40:16.655491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:40:17.062010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing128
Missing (%)100.0%
Memory size1.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)97.2%
Missing57
Missing (%)44.5%
Infinite0
Infinite (%)0.0%
Mean186820.67
Minimum184560.69
Maximum189878.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T00:40:17.470024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184560.69
5-th percentile184652
Q1185503.29
median187169.07
Q3187951.41
95-th percentile189072.96
Maximum189878.41
Range5317.72
Interquartile range (IQR)2448.1175

Descriptive statistics

Standard deviation1500.5601
Coefficient of variation (CV)0.0080320883
Kurtosis-1.2743896
Mean186820.67
Median Absolute Deviation (MAD)1323.3738
Skewness0.0015595233
Sum13264267
Variance2251680.6
MonotonicityNot monotonic
2024-05-11T00:40:17.925463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186289.438816703 3
 
2.3%
187169.070737345 1
 
0.8%
187243.924813489 1
 
0.8%
185528.525780849 1
 
0.8%
188669.485919056 1
 
0.8%
187879.054915494 1
 
0.8%
187531.38903074 1
 
0.8%
185478.063988449 1
 
0.8%
185725.129416389 1
 
0.8%
188269.576442399 1
 
0.8%
Other values (59) 59
46.1%
(Missing) 57
44.5%
ValueCountFrequency (%)
184560.687279761 1
0.8%
184607.492337403 1
0.8%
184626.053521926 1
0.8%
184645.579724418 1
0.8%
184658.429344271 1
0.8%
184660.89830575 1
0.8%
184676.704972197 1
0.8%
184727.430998613 1
0.8%
184737.734597798 1
0.8%
184773.961624315 1
0.8%
ValueCountFrequency (%)
189878.40729119 1
0.8%
189371.998478153 1
0.8%
189151.208015925 1
0.8%
189084.868866885 1
0.8%
189061.053426304 1
0.8%
188927.879344286 1
0.8%
188884.075622342 1
0.8%
188669.485919056 1
0.8%
188656.783840714 1
0.8%
188542.093729668 1
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)97.2%
Missing57
Missing (%)44.5%
Infinite0
Infinite (%)0.0%
Mean447190.27
Minimum444992.01
Maximum449783.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T00:40:18.352208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444992.01
5-th percentile445147.7
Q1446229.24
median447186.89
Q3448307.58
95-th percentile449278.31
Maximum449783.45
Range4791.4413
Interquartile range (IQR)2078.3438

Descriptive statistics

Standard deviation1360.8057
Coefficient of variation (CV)0.0030430127
Kurtosis-1.0320163
Mean447190.27
Median Absolute Deviation (MAD)1111.1034
Skewness0.020086475
Sum31750510
Variance1851792.2
MonotonicityNot monotonic
2024-05-11T00:40:18.817777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445182.294506346 3
 
2.3%
446311.114167671 1
 
0.8%
445830.274522885 1
 
0.8%
447030.427539885 1
 
0.8%
449398.438608253 1
 
0.8%
447370.031967944 1
 
0.8%
447310.609246804 1
 
0.8%
446309.072252909 1
 
0.8%
446772.73663492 1
 
0.8%
448253.548056054 1
 
0.8%
Other values (59) 59
46.1%
(Missing) 57
44.5%
ValueCountFrequency (%)
444992.010588191 1
 
0.8%
445018.996790344 1
 
0.8%
445064.011138948 1
 
0.8%
445113.109971419 1
 
0.8%
445182.294506346 3
2.3%
445209.687205241 1
 
0.8%
445229.76179636 1
 
0.8%
445249.033483384 1
 
0.8%
445264.23483344 1
 
0.8%
445532.444934761 1
 
0.8%
ValueCountFrequency (%)
449783.451870726 1
0.8%
449749.281558664 1
0.8%
449683.219205227 1
0.8%
449398.438608253 1
0.8%
449158.187080718 1
0.8%
449027.329508592 1
0.8%
449017.825528364 1
0.8%
448902.294659584 1
0.8%
448798.213455584 1
0.8%
448790.067971689 1
0.8%

비상시설위치
Text

MISSING 

Distinct124
Distinct (%)99.2%
Missing3
Missing (%)2.3%
Memory size1.1 KiB
2024-05-11T00:40:19.457634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length17.64
Min length7

Characters and Unicode

Total characters2205
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

Unique123 ?
Unique (%)98.4%

Sample

1st row서울특별시 양천구 목동 735번지
2nd row서울특별시 양천구 신월동 425번지 2호
3rd row서울특별시 양천구 목동 906번지
4th row서울특별시 양천구 신월동 591번지 1호
5th row신월6동 591-5
ValueCountFrequency (%)
서울특별시 80
 
16.4%
양천구 80
 
16.4%
목동 28
 
5.7%
신정동 26
 
5.3%
신월동 26
 
5.3%
1호 16
 
3.3%
호 9
 
1.8%
신월6동 7
 
1.4%
2호 7
 
1.4%
신월7동 6
 
1.2%
Other values (157) 202
41.5%
2024-05-11T00:40:20.480802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
391
 
17.7%
동 125
 
5.7%
1 125
 
5.7%
신 85
 
3.9%
서 82
 
3.7%
양 82
 
3.7%
천 82
 
3.7%
특 81
 
3.7%
별 81
 
3.7%
시 81
 
3.7%
Other values (31) 990
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1222
55.4%
Decimal Number 552
25.0%
Space Separator 391
 
17.7%
Dash Punctuation 39
 
1.8%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 125
 
10.2%
신 85
 
7.0%
서 82
 
6.7%
양 82
 
6.7%
천 82
 
6.7%
특 81
 
6.6%
별 81
 
6.6%
시 81
 
6.6%
울 81
 
6.6%
구 80
 
6.5%
Other values (18) 362
29.6%
Decimal Number
ValueCountFrequency (%)
1 125
22.6%
5 60
10.9%
2 60
10.9%
3 54
9.8%
9 52
9.4%
4 44
 
8.0%
0 43
 
7.8%
7 40
 
7.2%
6 37
 
6.7%
8 37
 
6.7%
Space Separator
ValueCountFrequency (%)
391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1222
55.4%
Common 983
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 125
 
10.2%
신 85
 
7.0%
서 82
 
6.7%
양 82
 
6.7%
천 82
 
6.7%
특 81
 
6.6%
별 81
 
6.6%
시 81
 
6.6%
울 81
 
6.6%
구 80
 
6.5%
Other values (18) 362
29.6%
Common
ValueCountFrequency (%)
391
39.8%
1 125
 
12.7%
5 60
 
6.1%
2 60
 
6.1%
3 54
 
5.5%
9 52
 
5.3%
4 44
 
4.5%
0 43
 
4.4%
7 40
 
4.1%
- 39
 
4.0%
Other values (3) 75
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1222
55.4%
ASCII 983
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
391
39.8%
1 125
 
12.7%
5 60
 
6.1%
2 60
 
6.1%
3 54
 
5.5%
9 52
 
5.3%
4 44
 
4.5%
0 43
 
4.4%
7 40
 
4.1%
- 39
 
4.0%
Other values (3) 75
 
7.6%
Hangul
ValueCountFrequency (%)
동 125
 
10.2%
신 85
 
7.0%
서 82
 
6.7%
양 82
 
6.7%
천 82
 
6.7%
특 81
 
6.6%
별 81
 
6.6%
시 81
 
6.6%
울 81
 
6.6%
구 80
 
6.5%
Other values (18) 362
29.6%

시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
민간시설
103 
자치단체자체시설
 
10
공공시설
 
10
<NA>
 
3
정부지원시설
 
2

Length

Max length8
Median length4
Mean length4.34375
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정부지원시설
2nd row자치단체자체시설
3rd row자치단체자체시설
4th row자치단체자체시설
5th row자치단체자체시설

Common Values

ValueCountFrequency (%)
민간시설 103
80.5%
자치단체자체시설 10
 
7.8%
공공시설 10
 
7.8%
<NA> 3
 
2.3%
정부지원시설 2
 
1.6%

Length

2024-05-11T00:40:20.927852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:40:21.321043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간시설 103
80.5%
자치단체자체시설 10
 
7.8%
공공시설 10
 
7.8%
na 3
 
2.3%
정부지원시설 2
 
1.6%

시설명_건물명
Text

MISSING 

Distinct122
Distinct (%)97.6%
Missing3
Missing (%)2.3%
Memory size1.1 KiB
2024-05-11T00:40:21.804605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length7.104
Min length2

Characters and Unicode

Total characters888
Distinct characters218
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

Unique119 ?
Unique (%)95.2%

Sample

1st row강서고등학교
2nd row신월4동주민센터
3rd row파리공원
4th row신안약수아파트
5th row신안약수아파트
ValueCountFrequency (%)
신안약수아파트 2
 
1.5%
사우나 2
 
1.5%
양천고등학교 2
 
1.5%
신트리공원 2
 
1.5%
프라자 1
 
0.8%
신월5동복합청사 1
 
0.8%
진명여고 1
 
0.8%
신월바다주차장 1
 
0.8%
얼음막걸리 1
 
0.8%
목동11단지아파트 1
 
0.8%
Other values (117) 117
89.3%
2024-05-11T00:40:22.869661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 42
 
4.7%
) 42
 
4.7%
신 22
 
2.5%
수 20
 
2.3%
동 18
 
2.0%
원 17
 
1.9%
트 17
 
1.9%
아 17
 
1.9%
교 17
 
1.9%
파 16
 
1.8%
Other values (208) 660
74.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 777
87.5%
Open Punctuation 42
 
4.7%
Close Punctuation 42
 
4.7%
Decimal Number 17
 
1.9%
Space Separator 6
 
0.7%
Dash Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 22
 
2.8%
수 20
 
2.6%
동 18
 
2.3%
원 17
 
2.2%
트 17
 
2.2%
아 17
 
2.2%
교 17
 
2.2%
파 16
 
2.1%
주 16
 
2.1%
목 13
 
1.7%
Other values (193) 604
77.7%
Decimal Number
ValueCountFrequency (%)
6 3
17.6%
1 3
17.6%
4 3
17.6%
0 2
11.8%
2 2
11.8%
9 1
 
5.9%
5 1
 
5.9%
7 1
 
5.9%
3 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 777
87.5%
Common 109
 
12.3%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 22
 
2.8%
수 20
 
2.6%
동 18
 
2.3%
원 17
 
2.2%
트 17
 
2.2%
아 17
 
2.2%
교 17
 
2.2%
파 16
 
2.1%
주 16
 
2.1%
목 13
 
1.7%
Other values (193) 604
77.7%
Common
ValueCountFrequency (%)
( 42
38.5%
) 42
38.5%
6
 
5.5%
6 3
 
2.8%
1 3
 
2.8%
4 3
 
2.8%
0 2
 
1.8%
2 2
 
1.8%
- 2
 
1.8%
9 1
 
0.9%
Other values (3) 3
 
2.8%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 777
87.5%
ASCII 111
 
12.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 42
37.8%
) 42
37.8%
6
 
5.4%
6 3
 
2.7%
1 3
 
2.7%
4 3
 
2.7%
0 2
 
1.8%
2 2
 
1.8%
- 2
 
1.8%
9 1
 
0.9%
Other values (5) 5
 
4.5%
Hangul
ValueCountFrequency (%)
신 22
 
2.8%
수 20
 
2.6%
동 18
 
2.3%
원 17
 
2.2%
트 17
 
2.2%
아 17
 
2.2%
교 17
 
2.2%
파 16
 
2.1%
주 16
 
2.1%
목 13
 
1.7%
Other values (193) 604
77.7%

해제일자
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)29.1%
Missing49
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean20082747
Minimum20030930
Maximum20210914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T00:40:23.301500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030930
5-th percentile20030930
Q120030930
median20060202
Q320141226
95-th percentile20180219
Maximum20210914
Range179984
Interquartile range (IQR)110296

Descriptive statistics

Standard deviation56940.296
Coefficient of variation (CV)0.0028352842
Kurtosis-1.1752993
Mean20082747
Median Absolute Deviation (MAD)29272
Skewness0.6036477
Sum1.586537 × 109
Variance3.2421973 × 109
MonotonicityNot monotonic
2024-05-11T00:40:23.992443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20030930 34
26.6%
20151224 8
 
6.2%
20060202 8
 
6.2%
20141226 4
 
3.1%
20070630 4
 
3.1%
20120925 2
 
1.6%
20110131 2
 
1.6%
20181221 2
 
1.6%
20060502 1
 
0.8%
20210914 1
 
0.8%
Other values (13) 13
 
10.2%
(Missing) 49
38.3%
ValueCountFrequency (%)
20030930 34
26.6%
20060202 8
 
6.2%
20060502 1
 
0.8%
20070630 4
 
3.1%
20071126 1
 
0.8%
20081208 1
 
0.8%
20100618 1
 
0.8%
20110131 2
 
1.6%
20120917 1
 
0.8%
20120925 2
 
1.6%
ValueCountFrequency (%)
20210914 1
 
0.8%
20200730 1
 
0.8%
20181221 2
 
1.6%
20180108 1
 
0.8%
20171123 1
 
0.8%
20171010 1
 
0.8%
20170407 1
 
0.8%
20161226 1
 
0.8%
20151224 8
6.2%
20150114 1
 
0.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
031400003140000-E20020000220021101<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>500.0<NA>서울특별시 양천구 목동 735번지서울특별시 양천구 목동중앙남로 27 (목동)158815강서고등학교2021-04-29 19:36:23U2021-05-01 02:40:00.0<NA>188116.996243448247.895331서울특별시 양천구 목동 735번지정부지원시설강서고등학교<NA>
131400003140000-E20020000320021101<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>300.0<NA>서울특별시 양천구 신월동 425번지 2호서울특별시 양천구 오목로5길 34 (신월동)158832신월4동주민센터2017-04-07 09:59:03I2018-08-31 23:59:59.0<NA>185794.829757446952.705424서울특별시 양천구 신월동 425번지 2호자치단체자체시설신월4동주민센터<NA>
231400003140000-E20020000420021101<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>200.0<NA>서울특별시 양천구 목동 906번지서울특별시 양천구 목동동로 363 (목동)158877파리공원2017-04-04 11:40:25I2018-08-31 23:59:59.0<NA>189061.053426448066.844626서울특별시 양천구 목동 906번지자치단체자체시설파리공원<NA>
331400003140000-E20020000520021101<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>51.0<NA>서울특별시 양천구 신월동 591번지 1호서울특별시 양천구 중앙로29길 55 (신월동)158788신안약수아파트2017-04-07 10:00:28I2018-08-31 23:59:59.0<NA>186443.256012446043.758277서울특별시 양천구 신월동 591번지 1호자치단체자체시설신안약수아파트<NA>
431400003140000-E20020000620021101200602024취소/말소/만료/정지/중지19사용중지20060202<NA><NA><NA><NA>51.0<NA>신월6동 591-5<NA><NA>신안약수아파트2006-05-26 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA>신월6동 591-5자치단체자체시설신안약수아파트20060202
531400003140000-E20020000720021101201308144취소/말소/만료/정지/중지19사용중지20130814<NA><NA><NA><NA>100.0<NA>신월3동 37<NA><NA>독수리아파트2013-10-21 14:33:47I2018-08-31 23:59:59.0<NA><NA><NA>신월3동 37자치단체자체시설독수리아파트20130814
631400003140000-E20020000820021101200309304취소/말소/만료/정지/중지19사용중지20030930<NA><NA><NA><NA>100.0<NA>신정3동 743-2<NA><NA>신정시영아파트2006-05-26 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA>신정3동 743-2자치단체자체시설신정시영아파트20030930
731400003140000-E20020000920021101200602024취소/말소/만료/정지/중지19사용중지20060202<NA><NA><NA><NA>250.0<NA>목1동 917-9<NA><NA>구희경2006-05-26 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA>목1동 917-9민간시설구희경20060202
831400003140000-E20020001020021101200706304취소/말소/만료/정지/중지19사용중지20070630<NA><NA><NA><NA>100.0<NA>목1동 408-115<NA><NA>이종표2007-11-22 17:12:33I2018-08-31 23:59:59.0<NA><NA><NA>목1동 408-115민간시설이종표20070630
931400003140000-E20020001120021101200602024취소/말소/만료/정지/중지19사용중지20060202<NA><NA><NA><NA>360.0<NA>목1동 924<NA><NA>유재우2006-05-26 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA>목1동 924민간시설유재우20060202
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
11831400003140000-E20170001020170828<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>68.0<NA>서울특별시 양천구 신정동 813번지 17호서울특별시 양천구 신정로 146 (신정동)08110신정동충전소2017-08-30 13:06:06I2018-08-31 23:59:59.0<NA>185701.457005444992.010588서울특별시 양천구 신정동 813번지 17호민간시설신정동충전소<NA>
11931400003140000-E20170001120170828<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>67.0<NA>서울특별시 양천구 신월동 53번지 1호서울특별시 양천구 남부순환로 311 (신월동, 신흥가스충전소)07904(주)신흥충전소2017-08-30 13:09:41I2018-08-31 23:59:59.0<NA>184607.492337448542.663712서울특별시 양천구 신월동 53번지 1호민간시설(주)신흥충전소<NA>
12031400003140000-E20170001220170828<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>65.0<NA>서울특별시 양천구 신정동 162번지 15호서울특별시 양천구 안양천로 669 (신정동, 복지신정충전소)08103복지신정충전소2017-08-30 13:12:03I2018-08-31 23:59:59.0<NA>188542.09373445018.99679서울특별시 양천구 신정동 162번지 15호민간시설복지신정충전소<NA>
12131400003140000-E20170001320170828201711234취소/말소/만료/정지/중지19사용중지20171123<NA><NA><NA><NA>90.0<NA>서울특별시 양천구 목동 946번지 1호서울특별시 양천구 목동중앙본로 73 (목동, 목동문화체육센터)07953목동문화체육센터2017-11-23 17:44:16I2018-08-31 23:59:59.0<NA>188279.662566449017.825528서울특별시 양천구 목동 946번지 1호민간시설목동문화체육센터20171123
12231400003140000-E20170001420170828<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>77.0<NA>서울특별시 양천구 목동 613번지 2호서울특별시 양천구 등촌로 220 (목동)07946등촌사우나2017-08-30 13:15:40I2018-08-31 23:59:59.0<NA>187916.254333449683.219205서울특별시 양천구 목동 613번지 2호민간시설등촌사우나<NA>
12331400003140000-E20170001520180108<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>150.0<NA>서울특별시 양천구 신정동 산 109번지 1호 양천고등학교서울특별시 양천구 신정로14길 13, 양천고등학교 (신정동)08108양천고등학교2021-04-29 19:36:50U2021-05-01 02:40:00.0<NA>186289.438817445182.294506서울특별시 양천구 신정동 산 109번지 1호 양천고등학교자치단체자체시설양천고등학교<NA>
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