Overview

Dataset statistics

Number of variables29
Number of observations199
Missing cells1741
Missing cells (%)30.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.7 KiB
Average record size in memory245.7 B

Variable types

Categorical10
Text7
DateTime2
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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-20037/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (66.3%)Imbalance
폐업일자 is highly imbalanced (66.3%)Imbalance
데이터갱신구분 is highly imbalanced (59.6%)Imbalance
시설구분명 is highly imbalanced (55.0%)Imbalance
휴업시작일자 has 199 (100.0%) missing valuesMissing
휴업종료일자 has 199 (100.0%) missing valuesMissing
재개업일자 has 199 (100.0%) missing valuesMissing
전화번호 has 199 (100.0%) missing valuesMissing
소재지우편번호 has 199 (100.0%) missing valuesMissing
도로명우편번호 has 8 (4.0%) missing valuesMissing
업태구분명 has 199 (100.0%) missing valuesMissing
좌표정보(X) has 7 (3.5%) missing valuesMissing
좌표정보(Y) has 7 (3.5%) missing valuesMissing
비상시설위치 has 171 (85.9%) missing valuesMissing
시설명_건물명 has 171 (85.9%) missing valuesMissing
해제일자 has 183 (92.0%) 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 06:46:57.118551
Analysis finished2024-05-11 06:46:57.957247
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3100000
199 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 199
100.0%

Length

2024-05-11T15:46:58.054267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:58.216797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 199
100.0%

관리번호
Text

UNIQUE 

Distinct199
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T15:46:58.497241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters3582
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

Unique199 ?
Unique (%)100.0%

Sample

1st row3100000-S201700003
2nd row3100000-S200700009
3rd row3100000-S201200065
4th row3100000-S198800001
5th row3100000-S201100002
ValueCountFrequency (%)
3100000-s201700003 1
 
0.5%
3100000-s200800010 1
 
0.5%
3100000-s201200037 1
 
0.5%
3100000-s201200038 1
 
0.5%
3100000-s199400009 1
 
0.5%
3100000-s201200035 1
 
0.5%
3100000-s201200036 1
 
0.5%
3100000-s201200067 1
 
0.5%
3100000-s201200069 1
 
0.5%
3100000-s201200070 1
 
0.5%
Other values (189) 189
95.0%
2024-05-11T15:46:59.048041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1914
53.4%
1 437
 
12.2%
3 250
 
7.0%
2 200
 
5.6%
- 199
 
5.6%
S 199
 
5.6%
9 181
 
5.1%
8 78
 
2.2%
7 36
 
1.0%
4 35
 
1.0%
Other values (2) 53
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3184
88.9%
Dash Punctuation 199
 
5.6%
Uppercase Letter 199
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1914
60.1%
1 437
 
13.7%
3 250
 
7.9%
2 200
 
6.3%
9 181
 
5.7%
8 78
 
2.4%
7 36
 
1.1%
4 35
 
1.1%
6 30
 
0.9%
5 23
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 199
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3383
94.4%
Latin 199
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1914
56.6%
1 437
 
12.9%
3 250
 
7.4%
2 200
 
5.9%
- 199
 
5.9%
9 181
 
5.4%
8 78
 
2.3%
7 36
 
1.1%
4 35
 
1.0%
6 30
 
0.9%
Latin
ValueCountFrequency (%)
S 199
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1914
53.4%
1 437
 
12.2%
3 250
 
7.0%
2 200
 
5.6%
- 199
 
5.6%
S 199
 
5.6%
9 181
 
5.1%
8 78
 
2.2%
7 36
 
1.0%
4 35
 
1.0%
Other values (2) 53
 
1.5%

인허가일자
Date

Distinct116
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1979-05-01 00:00:00
Maximum2023-07-12 00:00:00
2024-05-11T15:46:59.290196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:59.528754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct19
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
161 
2023-12-26
 
7
42766
 
5
2023-12-28
 
4
42178
 
3
Other values (14)
19 

Length

Max length10
Median length4
Mean length4.7437186
Min length4

Unique

Unique10 ?
Unique (%)5.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row2023-07-17
5th row2023-09-11

Common Values

ValueCountFrequency (%)
<NA> 161
80.9%
2023-12-26 7
 
3.5%
42766 5
 
2.5%
2023-12-28 4
 
2.0%
42178 3
 
1.5%
2023-12-11 3
 
1.5%
42878 2
 
1.0%
2023-09-11 2
 
1.0%
2023-08-17 2
 
1.0%
2023-08-18 1
 
0.5%
Other values (9) 9
 
4.5%

Length

2024-05-11T15:46:59.768467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 161
80.9%
2023-12-26 7
 
3.5%
42766 5
 
2.5%
2023-12-28 4
 
2.0%
42178 3
 
1.5%
2023-12-11 3
 
1.5%
42878 2
 
1.0%
2023-09-11 2
 
1.0%
2023-08-17 2
 
1.0%
41785 1
 
0.5%
Other values (9) 9
 
4.5%

영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1
161 
4
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 161
80.9%
4 38
 
19.1%

Length

2024-05-11T15:46:59.938125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:00.109589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 161
80.9%
4 38
 
19.1%

영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
영업/정상
161 
취소/말소/만료/정지/중지
38 

Length

Max length14
Median length5
Mean length6.718593
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 161
80.9%
취소/말소/만료/정지/중지 38
 
19.1%

Length

2024-05-11T15:47:00.255005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:00.411664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 161
80.9%
취소/말소/만료/정지/중지 38
 
19.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
18
161 
19
38 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
18 161
80.9%
19 38
 
19.1%

Length

2024-05-11T15:47:00.571149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:00.700966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 161
80.9%
19 38
 
19.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
사용중
161 
사용중지
38 

Length

Max length4
Median length3
Mean length3.1909548
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 161
80.9%
사용중지 38
 
19.1%

Length

2024-05-11T15:47:00.864741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:01.053269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 161
80.9%
사용중지 38
 
19.1%

폐업일자
Categorical

IMBALANCE 

Distinct19
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
161 
2023-12-26
 
7
42766
 
5
2023-12-28
 
4
42178
 
3
Other values (14)
19 

Length

Max length10
Median length4
Mean length4.7437186
Min length4

Unique

Unique10 ?
Unique (%)5.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row2023-07-17
5th row2023-09-11

Common Values

ValueCountFrequency (%)
<NA> 161
80.9%
2023-12-26 7
 
3.5%
42766 5
 
2.5%
2023-12-28 4
 
2.0%
42178 3
 
1.5%
2023-12-11 3
 
1.5%
42878 2
 
1.0%
2023-09-11 2
 
1.0%
2023-08-17 2
 
1.0%
2023-08-18 1
 
0.5%
Other values (9) 9
 
4.5%

Length

2024-05-11T15:47:01.286233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 161
80.9%
2023-12-26 7
 
3.5%
42766 5
 
2.5%
2023-12-28 4
 
2.0%
42178 3
 
1.5%
2023-12-11 3
 
1.5%
42878 2
 
1.0%
2023-09-11 2
 
1.0%
2023-08-17 2
 
1.0%
41785 1
 
0.5%
Other values (9) 9
 
4.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

소재지면적
Real number (ℝ)

Distinct131
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4212.6583
Minimum62.88
Maximum60464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T15:47:01.527417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62.88
5-th percentile250
Q1536
median964
Q34189.235
95-th percentile18137.1
Maximum60464
Range60401.12
Interquartile range (IQR)3653.235

Descriptive statistics

Standard deviation7880.9788
Coefficient of variation (CV)1.8707852
Kurtosis18.306475
Mean4212.6583
Median Absolute Deviation (MAD)564
Skewness3.7415571
Sum838319
Variance62109827
MonotonicityNot monotonic
2024-05-11T15:47:01.735953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
600.0 10
 
5.0%
1200.0 9
 
4.5%
14000.0 5
 
2.5%
300.0 5
 
2.5%
500.0 5
 
2.5%
7456.95 4
 
2.0%
850.0 4
 
2.0%
2500.0 4
 
2.0%
700.0 4
 
2.0%
4500.0 4
 
2.0%
Other values (121) 145
72.9%
ValueCountFrequency (%)
62.88 1
0.5%
80.4 1
0.5%
107.0 1
0.5%
150.0 1
0.5%
152.73 1
0.5%
171.21 1
0.5%
180.0 2
1.0%
236.0 1
0.5%
250.0 2
1.0%
251.0 1
0.5%
ValueCountFrequency (%)
60464.0 1
0.5%
46695.0 1
0.5%
35000.0 1
0.5%
32000.0 1
0.5%
26676.0 1
0.5%
25000.0 1
0.5%
24667.88 1
0.5%
23500.0 1
0.5%
21000.0 1
0.5%
19371.0 1
0.5%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

지번주소
Text

Distinct160
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T15:47:02.164515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length21.130653
Min length17

Characters and Unicode

Total characters4205
Distinct characters112
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

Unique137 ?
Unique (%)68.8%

Sample

1st row서울특별시 노원구 월계동 447번지 1호
2nd row서울특별시 노원구 상계동 771 서울시립뇌성마비복지관
3rd row서울특별시 노원구 월계동 941번지
4th row서울특별시 노원구 하계동 271번지 3호
5th row서울특별시 노원구 중계동 508번지
ValueCountFrequency (%)
서울특별시 199
22.2%
노원구 199
22.2%
상계동 72
 
8.0%
중계동 53
 
5.9%
월계동 40
 
4.5%
1호 19
 
2.1%
하계동 18
 
2.0%
공릉동 16
 
1.8%
2호 13
 
1.5%
3호 7
 
0.8%
Other values (184) 260
29.0%
2024-05-11T15:47:03.201469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
697
16.6%
원 207
 
4.9%
노 204
 
4.9%
울 203
 
4.8%
서 202
 
4.8%
시 202
 
4.8%
구 201
 
4.8%
특 200
 
4.8%
별 200
 
4.8%
동 200
 
4.8%
Other values (102) 1689
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2779
66.1%
Decimal Number 711
 
16.9%
Space Separator 697
 
16.6%
Dash Punctuation 14
 
0.3%
Other Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 207
 
7.4%
노 204
 
7.3%
울 203
 
7.3%
서 202
 
7.3%
시 202
 
7.3%
구 201
 
7.2%
특 200
 
7.2%
별 200
 
7.2%
동 200
 
7.2%
계 190
 
6.8%
Other values (86) 770
27.7%
Decimal Number
ValueCountFrequency (%)
1 125
17.6%
5 95
13.4%
2 91
12.8%
3 80
11.3%
7 78
11.0%
4 59
8.3%
6 58
8.2%
9 46
 
6.5%
0 45
 
6.3%
8 34
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
697
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2779
66.1%
Common 1424
33.9%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 207
 
7.4%
노 204
 
7.3%
울 203
 
7.3%
서 202
 
7.3%
시 202
 
7.3%
구 201
 
7.2%
특 200
 
7.2%
별 200
 
7.2%
동 200
 
7.2%
계 190
 
6.8%
Other values (86) 770
27.7%
Common
ValueCountFrequency (%)
697
48.9%
1 125
 
8.8%
5 95
 
6.7%
2 91
 
6.4%
3 80
 
5.6%
7 78
 
5.5%
4 59
 
4.1%
6 58
 
4.1%
9 46
 
3.2%
0 45
 
3.2%
Other values (4) 50
 
3.5%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2779
66.1%
ASCII 1426
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
697
48.9%
1 125
 
8.8%
5 95
 
6.7%
2 91
 
6.4%
3 80
 
5.6%
7 78
 
5.5%
4 59
 
4.1%
6 58
 
4.1%
9 46
 
3.2%
0 45
 
3.2%
Other values (6) 52
 
3.6%
Hangul
ValueCountFrequency (%)
원 207
 
7.4%
노 204
 
7.3%
울 203
 
7.3%
서 202
 
7.3%
시 202
 
7.3%
구 201
 
7.2%
특 200
 
7.2%
별 200
 
7.2%
동 200
 
7.2%
계 190
 
6.8%
Other values (86) 770
27.7%

도로명주소
Text

Distinct169
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T15:47:03.641393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length37
Mean length33.050251
Min length23

Characters and Unicode

Total characters6577
Distinct characters223
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

Unique154 ?
Unique (%)77.4%

Sample

1st row서울특별시 노원구 광운로 20 (월계동, 광운대학교)
2nd row서울특별시 노원구 덕릉로70가길 96, 서울시립뇌성마비복지관 (상계동)
3rd row서울특별시 노원구 광운로19길 38 (월계동, 성북역신도브래뉴)
4th row서울특별시 노원구 섬밭로 209 (하계동, 신한은행)
5th row서울특별시 노원구 동일로204길 13 (중계동, 노원평생학습관)
ValueCountFrequency (%)
서울특별시 199
 
16.8%
노원구 199
 
16.8%
상계동 71
 
6.0%
중계동 52
 
4.4%
월계동 41
 
3.5%
동일로 21
 
1.8%
하계동 17
 
1.4%
공릉동 16
 
1.4%
한글비석로 15
 
1.3%
노원로 10
 
0.8%
Other values (354) 543
45.9%
2024-05-11T15:47:04.139592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
999
 
15.2%
동 272
 
4.1%
계 262
 
4.0%
원 240
 
3.6%
노 235
 
3.6%
구 208
 
3.2%
울 207
 
3.1%
서 204
 
3.1%
시 204
 
3.1%
특 200
 
3.0%
Other values (213) 3546
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4196
63.8%
Space Separator 999
 
15.2%
Decimal Number 781
 
11.9%
Open Punctuation 199
 
3.0%
Close Punctuation 199
 
3.0%
Other Punctuation 191
 
2.9%
Dash Punctuation 10
 
0.2%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 272
 
6.5%
계 262
 
6.2%
원 240
 
5.7%
노 235
 
5.6%
구 208
 
5.0%
울 207
 
4.9%
서 204
 
4.9%
시 204
 
4.9%
특 200
 
4.8%
별 200
 
4.8%
Other values (194) 1964
46.8%
Decimal Number
ValueCountFrequency (%)
2 142
18.2%
1 138
17.7%
4 91
11.7%
3 84
10.8%
6 68
8.7%
5 67
8.6%
8 54
 
6.9%
0 49
 
6.3%
9 47
 
6.0%
7 41
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 186
97.4%
. 3
 
1.6%
/ 2
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
999
100.0%
Open Punctuation
ValueCountFrequency (%)
( 199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 199
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4196
63.8%
Common 2379
36.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 272
 
6.5%
계 262
 
6.2%
원 240
 
5.7%
노 235
 
5.6%
구 208
 
5.0%
울 207
 
4.9%
서 204
 
4.9%
시 204
 
4.9%
특 200
 
4.8%
별 200
 
4.8%
Other values (194) 1964
46.8%
Common
ValueCountFrequency (%)
999
42.0%
( 199
 
8.4%
) 199
 
8.4%
, 186
 
7.8%
2 142
 
6.0%
1 138
 
5.8%
4 91
 
3.8%
3 84
 
3.5%
6 68
 
2.9%
5 67
 
2.8%
Other values (7) 206
 
8.7%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4196
63.8%
ASCII 2381
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
999
42.0%
( 199
 
8.4%
) 199
 
8.4%
, 186
 
7.8%
2 142
 
6.0%
1 138
 
5.8%
4 91
 
3.8%
3 84
 
3.5%
6 68
 
2.9%
5 67
 
2.8%
Other values (9) 208
 
8.7%
Hangul
ValueCountFrequency (%)
동 272
 
6.5%
계 262
 
6.2%
원 240
 
5.7%
노 235
 
5.6%
구 208
 
5.0%
울 207
 
4.9%
서 204
 
4.9%
시 204
 
4.9%
특 200
 
4.8%
별 200
 
4.8%
Other values (194) 1964
46.8%

도로명우편번호
Text

MISSING 

Distinct131
Distinct (%)68.6%
Missing8
Missing (%)4.0%
Memory size1.7 KiB
2024-05-11T15:47:04.577704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9109948
Min length4

Characters and Unicode

Total characters938
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

Unique93 ?
Unique (%)48.7%

Sample

1st row01897
2nd row01772
3rd row01887
4th row01776
5th row01783
ValueCountFrequency (%)
01882 8
 
4.2%
01689 5
 
2.6%
1624 5
 
2.6%
01869 4
 
2.1%
01746 4
 
2.1%
01775 4
 
2.1%
01714 3
 
1.6%
01758 3
 
1.6%
01772 3
 
1.6%
01784 3
 
1.6%
Other values (121) 149
78.0%
2024-05-11T15:47:05.348886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 231
24.6%
0 201
21.4%
7 121
12.9%
6 99
10.6%
8 94
10.0%
4 46
 
4.9%
9 46
 
4.9%
2 39
 
4.2%
5 30
 
3.2%
3 30
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 937
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 231
24.7%
0 201
21.5%
7 121
12.9%
6 99
10.6%
8 94
10.0%
4 46
 
4.9%
9 46
 
4.9%
2 39
 
4.2%
5 30
 
3.2%
3 30
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 938
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 231
24.6%
0 201
21.4%
7 121
12.9%
6 99
10.6%
8 94
10.0%
4 46
 
4.9%
9 46
 
4.9%
2 39
 
4.2%
5 30
 
3.2%
3 30
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 938
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 231
24.6%
0 201
21.4%
7 121
12.9%
6 99
10.6%
8 94
10.0%
4 46
 
4.9%
9 46
 
4.9%
2 39
 
4.2%
5 30
 
3.2%
3 30
 
3.2%

사업장명
Text

Distinct196
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-11T15:47:05.798315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length15.562814
Min length5

Characters and Unicode

Total characters3097
Distinct characters234
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

Unique194 ?
Unique (%)97.5%

Sample

1st row광운대학교 지하2~3층 주차장
2nd row시립뇌성마비복지관 지하1층 식당
3rd row성북역신도브래뉴아파트 지하1층 주차장
4th row벽산상가 지하1층
5th row노원평생학습관 지하1층
ValueCountFrequency (%)
지하1층 118
 
20.8%
주차장 67
 
11.8%
지하주차장 18
 
3.2%
지하 13
 
2.3%
지하2층 12
 
2.1%
공릉2동 11
 
1.9%
1층 10
 
1.8%
주민센터 6
 
1.1%
상가 6
 
1.1%
1~3층 5
 
0.9%
Other values (252) 302
53.2%
2024-05-11T15:47:06.402220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
372
 
12.0%
지 223
 
7.2%
1 205
 
6.6%
하 191
 
6.2%
층 183
 
5.9%
주 117
 
3.8%
차 94
 
3.0%
장 92
 
3.0%
아 80
 
2.6%
파 78
 
2.5%
Other values (224) 1462
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2299
74.2%
Decimal Number 373
 
12.0%
Space Separator 372
 
12.0%
Math Symbol 21
 
0.7%
Other Punctuation 16
 
0.5%
Uppercase Letter 10
 
0.3%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 223
 
9.7%
하 191
 
8.3%
층 183
 
8.0%
주 117
 
5.1%
차 94
 
4.1%
장 92
 
4.0%
아 80
 
3.5%
파 78
 
3.4%
동 74
 
3.2%
트 71
 
3.1%
Other values (205) 1096
47.7%
Decimal Number
ValueCountFrequency (%)
1 205
55.0%
2 66
 
17.7%
3 33
 
8.8%
0 31
 
8.3%
4 11
 
2.9%
5 10
 
2.7%
7 8
 
2.1%
6 4
 
1.1%
9 3
 
0.8%
8 2
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
B 8
80.0%
K 1
 
10.0%
T 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 12
75.0%
. 4
 
25.0%
Space Separator
ValueCountFrequency (%)
372
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2299
74.2%
Common 788
 
25.4%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 223
 
9.7%
하 191
 
8.3%
층 183
 
8.0%
주 117
 
5.1%
차 94
 
4.1%
장 92
 
4.0%
아 80
 
3.5%
파 78
 
3.4%
동 74
 
3.2%
트 71
 
3.1%
Other values (205) 1096
47.7%
Common
ValueCountFrequency (%)
372
47.2%
1 205
26.0%
2 66
 
8.4%
3 33
 
4.2%
0 31
 
3.9%
~ 21
 
2.7%
, 12
 
1.5%
4 11
 
1.4%
5 10
 
1.3%
7 8
 
1.0%
Other values (6) 19
 
2.4%
Latin
ValueCountFrequency (%)
B 8
80.0%
K 1
 
10.0%
T 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2299
74.2%
ASCII 798
 
25.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
372
46.6%
1 205
25.7%
2 66
 
8.3%
3 33
 
4.1%
0 31
 
3.9%
~ 21
 
2.6%
, 12
 
1.5%
4 11
 
1.4%
5 10
 
1.3%
7 8
 
1.0%
Other values (9) 29
 
3.6%
Hangul
ValueCountFrequency (%)
지 223
 
9.7%
하 191
 
8.3%
층 183
 
8.0%
주 117
 
5.1%
차 94
 
4.1%
장 92
 
4.0%
아 80
 
3.5%
파 78
 
3.4%
동 74
 
3.2%
트 71
 
3.1%
Other values (205) 1096
47.7%

최종수정일자
Date

UNIQUE 

Distinct199
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2014-05-26 16:34:02
Maximum2024-02-23 10:49:04
2024-05-11T15:47:06.657899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:06.907975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
U
183 
I
 
16

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 183
92.0%
I 16
 
8.0%

Length

2024-05-11T15:47:07.115146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:07.277953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 183
92.0%
i 16
 
8.0%

데이터갱신일자
Categorical

Distinct31
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-02 00:07:00.0
49 
2023-12-02 00:04:00.0
23 
2022-12-08 00:03:00.0
17 
2018-08-31 23:59:59.0
16 
2023-12-02 00:08:00.0
12 
Other values (26)
82 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique13 ?
Unique (%)6.5%

Sample

1st row2023-12-02 00:04:00.0
2nd row2023-12-01 23:01:00.0
3rd row2023-12-02 00:04:00.0
4th row2022-12-06 23:09:00.0
5th row2022-12-08 23:03:00.0

Common Values

ValueCountFrequency (%)
2023-12-02 00:07:00.0 49
24.6%
2023-12-02 00:04:00.0 23
11.6%
2022-12-08 00:03:00.0 17
 
8.5%
2018-08-31 23:59:59.0 16
 
8.0%
2023-12-02 00:08:00.0 12
 
6.0%
2023-12-01 22:01:00.0 12
 
6.0%
2023-12-01 23:05:00.0 11
 
5.5%
2023-11-30 23:00:00.0 9
 
4.5%
2022-11-01 22:08:00.0 5
 
2.5%
2023-11-30 23:08:00.0 5
 
2.5%
Other values (21) 40
20.1%

Length

2024-05-11T15:47:07.462236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-12-02 84
21.1%
00:07:00.0 50
12.6%
2023-12-01 33
 
8.3%
00:04:00.0 23
 
5.8%
2022-12-08 19
 
4.8%
00:03:00.0 17
 
4.3%
2022-11-01 17
 
4.3%
2018-08-31 16
 
4.0%
23:59:59.0 16
 
4.0%
2023-11-30 14
 
3.5%
Other values (28) 109
27.4%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct154
Distinct (%)80.2%
Missing7
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean205728.07
Minimum204325.99
Maximum207746.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T15:47:07.670087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum204325.99
5-th percentile204542.76
Q1205083.26
median205689.46
Q3206356.22
95-th percentile207255.01
Maximum207746.15
Range3420.1617
Interquartile range (IQR)1272.9582

Descriptive statistics

Standard deviation798.69802
Coefficient of variation (CV)0.0038822997
Kurtosis-0.72754761
Mean205728.07
Median Absolute Deviation (MAD)646.04396
Skewness0.30566511
Sum39499789
Variance637918.52
MonotonicityNot monotonic
2024-05-11T15:47:07.942568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204960.438272562 6
 
3.0%
204589.830805772 5
 
2.5%
206357.874306883 4
 
2.0%
205344.664263273 4
 
2.0%
204481.248686527 4
 
2.0%
204670.573678123 4
 
2.0%
205198.498721037 3
 
1.5%
206002.407274302 2
 
1.0%
205199.04912643 2
 
1.0%
205958.771412076 2
 
1.0%
Other values (144) 156
78.4%
(Missing) 7
 
3.5%
ValueCountFrequency (%)
204325.989587591 1
 
0.5%
204387.387609735 1
 
0.5%
204412.836637873 1
 
0.5%
204454.974085477 1
 
0.5%
204481.248686527 4
2.0%
204496.606261601 1
 
0.5%
204529.936306179 1
 
0.5%
204553.255966506 1
 
0.5%
204589.830805772 5
2.5%
204655.767899739 1
 
0.5%
ValueCountFrequency (%)
207746.151245202 1
0.5%
207290.202271986 1
0.5%
207283.444093204 1
0.5%
207282.938831263 1
0.5%
207281.977032498 1
0.5%
207274.300313358 1
0.5%
207271.120546248 2
1.0%
207261.781710467 1
0.5%
207255.005556152 2
1.0%
207164.201416648 2
1.0%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct154
Distinct (%)80.2%
Missing7
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean460474.59
Minimum457209.35
Maximum464849.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T15:47:08.192717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum457209.35
5-th percentile457574.41
Q1458932.13
median460520.81
Q3461716.41
95-th percentile464099.69
Maximum464849.97
Range7640.6238
Interquartile range (IQR)2784.2788

Descriptive statistics

Standard deviation1873.5632
Coefficient of variation (CV)0.0040687657
Kurtosis-0.76406705
Mean460474.59
Median Absolute Deviation (MAD)1378.4069
Skewness0.19367269
Sum88411122
Variance3510239.2
MonotonicityNot monotonic
2024-05-11T15:47:08.458472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
464099.692139359 6
 
3.0%
458420.680573706 5
 
2.5%
460497.708830729 4
 
2.0%
459333.879372182 4
 
2.0%
459249.51806945 4
 
2.0%
462933.316362013 4
 
2.0%
457486.206509046 3
 
1.5%
462768.072908599 2
 
1.0%
458821.008483722 2
 
1.0%
460765.650465441 2
 
1.0%
Other values (144) 156
78.4%
(Missing) 7
 
3.5%
ValueCountFrequency (%)
457209.345176098 1
 
0.5%
457262.040413664 1
 
0.5%
457275.799282625 1
 
0.5%
457358.731978332 1
 
0.5%
457425.000383899 1
 
0.5%
457486.206509046 3
1.5%
457509.134931641 1
 
0.5%
457510.654347047 1
 
0.5%
457626.566370972 1
 
0.5%
457650.706969898 1
 
0.5%
ValueCountFrequency (%)
464849.968985063 1
 
0.5%
464346.663669239 1
 
0.5%
464241.922622024 1
 
0.5%
464161.702709881 1
 
0.5%
464133.975605555 1
 
0.5%
464099.692139359 6
3.0%
463928.107318353 1
 
0.5%
463895.862348388 1
 
0.5%
463397.088380114 2
 
1.0%
462933.316362013 4
2.0%

비상시설위치
Text

MISSING 

Distinct17
Distinct (%)60.7%
Missing171
Missing (%)85.9%
Memory size1.7 KiB
2024-05-11T15:47:08.720466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length19.928571
Min length19

Characters and Unicode

Total characters558
Distinct characters32
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

Unique12 ?
Unique (%)42.9%

Sample

1st row서울특별시 노원구 상계동 301번지 6호
2nd row서울특별시 노원구 상계동 671번지
3rd row서울특별시 노원구 상계동 693번지 1호
4th row서울특별시 노원구 상계동 647번지
5th row서울특별시 노원구 상계동 624번지
ValueCountFrequency (%)
서울특별시 28
23.5%
노원구 28
23.5%
상계동 17
14.3%
월계동 5
 
4.2%
중계동 5
 
4.2%
1269번지 5
 
4.2%
624번지 4
 
3.4%
942번지 3
 
2.5%
1호 3
 
2.5%
447번지 2
 
1.7%
Other values (18) 19
16.0%
2024-05-11T15:47:09.240001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
16.3%
노 29
 
5.2%
원 29
 
5.2%
서 28
 
5.0%
동 28
 
5.0%
특 28
 
5.0%
별 28
 
5.0%
시 28
 
5.0%
구 28
 
5.0%
울 28
 
5.0%
Other values (22) 213
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 373
66.8%
Decimal Number 94
 
16.8%
Space Separator 91
 
16.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 29
 
7.8%
원 29
 
7.8%
서 28
 
7.5%
동 28
 
7.5%
특 28
 
7.5%
별 28
 
7.5%
시 28
 
7.5%
구 28
 
7.5%
울 28
 
7.5%
지 27
 
7.2%
Other values (11) 92
24.7%
Decimal Number
ValueCountFrequency (%)
1 16
17.0%
6 15
16.0%
2 15
16.0%
4 12
12.8%
9 10
10.6%
7 7
7.4%
3 6
 
6.4%
8 5
 
5.3%
0 4
 
4.3%
5 4
 
4.3%
Space Separator
ValueCountFrequency (%)
91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 373
66.8%
Common 185
33.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 29
 
7.8%
원 29
 
7.8%
서 28
 
7.5%
동 28
 
7.5%
특 28
 
7.5%
별 28
 
7.5%
시 28
 
7.5%
구 28
 
7.5%
울 28
 
7.5%
지 27
 
7.2%
Other values (11) 92
24.7%
Common
ValueCountFrequency (%)
91
49.2%
1 16
 
8.6%
6 15
 
8.1%
2 15
 
8.1%
4 12
 
6.5%
9 10
 
5.4%
7 7
 
3.8%
3 6
 
3.2%
8 5
 
2.7%
0 4
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 373
66.8%
ASCII 185
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
49.2%
1 16
 
8.6%
6 15
 
8.1%
2 15
 
8.1%
4 12
 
6.5%
9 10
 
5.4%
7 7
 
3.8%
3 6
 
3.2%
8 5
 
2.7%
0 4
 
2.2%
Hangul
ValueCountFrequency (%)
노 29
 
7.8%
원 29
 
7.8%
서 28
 
7.5%
동 28
 
7.5%
특 28
 
7.5%
별 28
 
7.5%
시 28
 
7.5%
구 28
 
7.5%
울 28
 
7.5%
지 27
 
7.2%
Other values (11) 92
24.7%

시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
171 
공공시설
19 
공공용시설
 
9

Length

Max length5
Median length4
Mean length4.0452261
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> 171
85.9%
공공시설 19
 
9.5%
공공용시설 9
 
4.5%

Length

2024-05-11T15:47:09.456665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:09.622724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 171
85.9%
공공시설 19
 
9.5%
공공용시설 9
 
4.5%

시설명_건물명
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing171
Missing (%)85.9%
Memory size1.7 KiB
2024-05-11T15:47:09.903978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length12.75
Min length5

Characters and Unicode

Total characters357
Distinct characters101
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

Unique28 ?
Unique (%)100.0%

Sample

1st row아미여성병원
2nd row상계10동 주민센터 지하1층
3rd row노원프라자 주차장 지하2층
4th row상계주공아파트 12단지 관리동 지하1층
5th row주공15단지 지하1층 헬스장
ValueCountFrequency (%)
지하1층 7
 
11.9%
주차장 2
 
3.4%
상계주공아파트 2
 
3.4%
관리동 2
 
3.4%
광운대학교 2
 
3.4%
헬스장 2
 
3.4%
아미여성병원 1
 
1.7%
월계역신도뷰레뉴132 1
 
1.7%
수락파크빌아파트506동 1
 
1.7%
수락파크빌아파트507동 1
 
1.7%
Other values (38) 38
64.4%
2024-05-11T15:47:10.477348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
8.7%
1 17
 
4.8%
동 16
 
4.5%
파 15
 
4.2%
지 14
 
3.9%
아 12
 
3.4%
트 10
 
2.8%
층 9
 
2.5%
하 9
 
2.5%
0 9
 
2.5%
Other values (91) 215
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 273
76.5%
Decimal Number 51
 
14.3%
Space Separator 31
 
8.7%
Other Punctuation 1
 
0.3%
Math Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16
 
5.9%
파 15
 
5.5%
지 14
 
5.1%
아 12
 
4.4%
트 10
 
3.7%
층 9
 
3.3%
하 9
 
3.3%
주 8
 
2.9%
계 8
 
2.9%
학 7
 
2.6%
Other values (79) 165
60.4%
Decimal Number
ValueCountFrequency (%)
1 17
33.3%
0 9
17.6%
5 8
15.7%
2 7
13.7%
3 5
 
9.8%
6 2
 
3.9%
7 1
 
2.0%
8 1
 
2.0%
4 1
 
2.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 273
76.5%
Common 84
 
23.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16
 
5.9%
파 15
 
5.5%
지 14
 
5.1%
아 12
 
4.4%
트 10
 
3.7%
층 9
 
3.3%
하 9
 
3.3%
주 8
 
2.9%
계 8
 
2.9%
학 7
 
2.6%
Other values (79) 165
60.4%
Common
ValueCountFrequency (%)
31
36.9%
1 17
20.2%
0 9
 
10.7%
5 8
 
9.5%
2 7
 
8.3%
3 5
 
6.0%
6 2
 
2.4%
7 1
 
1.2%
. 1
 
1.2%
~ 1
 
1.2%
Other values (2) 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 273
76.5%
ASCII 84
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
36.9%
1 17
20.2%
0 9
 
10.7%
5 8
 
9.5%
2 7
 
8.3%
3 5
 
6.0%
6 2
 
2.4%
7 1
 
1.2%
. 1
 
1.2%
~ 1
 
1.2%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
동 16
 
5.9%
파 15
 
5.5%
지 14
 
5.1%
아 12
 
4.4%
트 10
 
3.7%
층 9
 
3.3%
하 9
 
3.3%
주 8
 
2.9%
계 8
 
2.9%
학 7
 
2.6%
Other values (79) 165
60.4%

해제일자
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)56.2%
Missing183
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean20160430
Minimum20140526
Maximum20170907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-11T15:47:10.666624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20140526
5-th percentile20140527
Q120150623
median20170120
Q320170131
95-th percentile20170619
Maximum20170907
Range30381
Interquartile range (IQR)19508

Descriptive statistics

Standard deviation11974.587
Coefficient of variation (CV)0.00059396487
Kurtosis-1.547629
Mean20160430
Median Absolute Deviation (MAD)595.5
Skewness-0.52403658
Sum3.2256689 × 108
Variance1.4339074 × 108
MonotonicityNot monotonic
2024-05-11T15:47:10.838151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20170131 5
 
2.5%
20150623 3
 
1.5%
20170523 2
 
1.0%
20150626 1
 
0.5%
20140527 1
 
0.5%
20150622 1
 
0.5%
20140526 1
 
0.5%
20170907 1
 
0.5%
20170108 1
 
0.5%
(Missing) 183
92.0%
ValueCountFrequency (%)
20140526 1
 
0.5%
20140527 1
 
0.5%
20150622 1
 
0.5%
20150623 3
1.5%
20150626 1
 
0.5%
20170108 1
 
0.5%
20170131 5
2.5%
20170523 2
 
1.0%
20170907 1
 
0.5%
ValueCountFrequency (%)
20170907 1
 
0.5%
20170523 2
 
1.0%
20170131 5
2.5%
20170108 1
 
0.5%
20150626 1
 
0.5%
20150623 3
1.5%
20150622 1
 
0.5%
20140527 1
 
0.5%
20140526 1
 
0.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
031000003100000-S2017000032017-05-23<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>12202.0<NA>서울특별시 노원구 월계동 447번지 1호서울특별시 노원구 광운로 20 (월계동, 광운대학교)01897광운대학교 지하2~3층 주차장2024-02-02 14:27:18U2023-12-02 00:04:00.0<NA>205198.498721457486.206509<NA><NA><NA><NA>
131000003100000-S2007000092007-06-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>637.0<NA>서울특별시 노원구 상계동 771 서울시립뇌성마비복지관서울특별시 노원구 덕릉로70가길 96, 서울시립뇌성마비복지관 (상계동)01772시립뇌성마비복지관 지하1층 식당2024-02-08 18:38:33U2023-12-01 23:01:00.0<NA>204940.089436459998.31488<NA><NA><NA><NA>
231000003100000-S2012000652012-09-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1000.0<NA>서울특별시 노원구 월계동 941번지서울특별시 노원구 광운로19길 38 (월계동, 성북역신도브래뉴)01887성북역신도브래뉴아파트 지하1층 주차장2024-02-02 14:23:38U2023-12-02 00:04:00.0<NA>205131.946102457868.675564<NA><NA><NA><NA>
331000003100000-S1988000011988-08-012023-07-174취소/말소/만료/정지/중지19사용중지2023-07-17<NA><NA><NA><NA>2500.0<NA>서울특별시 노원구 하계동 271번지 3호서울특별시 노원구 섬밭로 209 (하계동, 신한은행)01776벽산상가 지하1층2023-07-17 17:29:14U2022-12-06 23:09:00.0<NA>205601.066016459233.675552<NA><NA><NA><NA>
431000003100000-S2011000022011-05-022023-09-114취소/말소/만료/정지/중지19사용중지2023-09-11<NA><NA><NA><NA>300.0<NA>서울특별시 노원구 중계동 508번지서울특별시 노원구 동일로204길 13 (중계동, 노원평생학습관)01783노원평생학습관 지하1층2023-09-11 15:56:47U2022-12-08 23:03:00.0<NA>205853.862931459752.225293<NA><NA><NA><NA>
531000003100000-S2012000682012-09-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>600.0<NA>서울특별시 노원구 월계동 942번지서울특별시 노원구 광운로 132 (월계동, 월계역신도브래뉴)01885월계역신도브래뉴아파트 지하1층 주차장2024-02-02 14:24:23U2023-12-02 00:04:00.0<NA>205110.016574458522.043286<NA><NA><NA><NA>
631000003100000-S1997000051997-11-03<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>350.0<NA>서울특별시 노원구 상계동 301번지 6호서울특별시 노원구 노원로 416 (상계동, 모네여성병원)1704아미여성병원2021-01-02 18:30:00U2021-01-05 02:40:00.0<NA>205922.151234461261.657202서울특별시 노원구 상계동 301번지 6호공공시설아미여성병원<NA>
731000003100000-S2012000092012-04-10<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>800.0<NA>서울특별시 노원구 월계동 441번지서울특별시 노원구 광운로2가길 22 (월계동, 삼창아파트)01899삼창아파트 지하1층2024-02-02 14:25:47U2023-12-02 00:04:00.0<NA>205211.357313457262.040414<NA><NA><NA><NA>
831000003100000-S2000000302000-12-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>733.0<NA>서울특별시 노원구 상계동 205-4 한국성서대학교서울특별시 노원구 동일로214길 32, 한국성서대학교 (상계동)01757한국성서대학교 밀알관 지하2층 주차장2024-02-08 16:37:06U2023-12-01 23:01:00.0<NA>205599.458649460693.71091<NA><NA><NA><NA>
931000003100000-S1996000051996-10-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>9217.0<NA>서울특별시 노원구 하계동 273번지 5호서울특별시 노원구 동일로 지하 1196 (하계동, 하계역)01784하계역(지하철 7호선) 지하2층2024-02-08 17:43:12U2023-12-01 23:01:00.0<NA>205979.204079459212.57881<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
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19031000003100000-S2023000022023-05-04<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>857.8<NA>서울특별시 노원구 공릉동 737 삼익아파트서울특별시 노원구 공릉로46길 32 (공릉동, 삼익아파트)01816공릉2동 삼익1차아파트 103동 지하1층 주차장2024-02-06 13:08:08U2023-12-02 00:08:00.0<NA>207164.201417458290.138258<NA><NA><NA><NA>
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19231000003100000-S2009000102009-11-04<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>13500.0<NA>서울특별시 노원구 공릉동 741번지서울특별시 노원구 공릉로27길 110 (공릉동, 현대성우아파트)01834공릉2동 현대성우아파트 지하주차장 1~3층2024-02-06 13:06:20U2023-12-02 00:08:00.0<NA>206767.12663458240.757697<NA><NA><NA><NA>
19331000003100000-S2006000012006-07-14<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>330.0<NA>서울특별시 노원구 공릉동 87번지 7호서울특별시 노원구 노원로1길 68 (공릉동, 공릉2동청사)01823공릉2동 주민센터 지하 1층2024-02-06 13:00:44U2023-12-02 00:08:00.0<NA>207290.202272457665.819152<NA><NA><NA><NA>
19431000003100000-S2005000042005-02-17<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>15156.28<NA>서울특별시 노원구 상계동 713번지서울특별시 노원구 동일로 1414 (상계동, 롯데백화점)01695롯데백화점 노원점 지하2,3층 주차장2024-02-06 11:21:41U2023-12-02 00:08:00.0<NA>205320.284767461419.881795<NA><NA><NA><NA>
19531000003100000-S2001000022001-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>80.4<NA>서울특별시 노원구 공릉동 221번지 3호서울특별시 노원구 공릉로 166-1 (공릉동)01818공릉2동 공릉보건지소 지하 1층2024-02-06 15:59:05U2023-12-02 00:08:00.0<NA>206992.984879458054.70906<NA><NA><NA><NA>
19631000003100000-S2001000062001-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>35000.0<NA>서울특별시 노원구 공릉동 285번지 2호서울특별시 노원구 화랑로 지하 510 (공릉동)01804공릉2동 화랑대역 지하1,2층2024-02-06 13:02:29U2023-12-02 00:08:00.0<NA>207283.444093457509.134932<NA><NA><NA><NA>
19731000003100000-S2001000092001-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1200.0<NA>서울특별시 노원구 공릉동 420번지 2호서울특별시 노원구 공릉로46길 3 (공릉동)01814공릉2동 평화타운 지하 1~3층2024-02-06 13:02:58U2023-12-02 00:08:00.0<NA>206918.939595458317.423099<NA><NA><NA><NA>
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