Overview

Dataset statistics

Number of variables29
Number of observations119
Missing cells1010
Missing cells (%)29.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.6 KiB
Average record size in memory246.1 B

Variable types

Categorical8
Text9
DateTime3
Unsupported6
Numeric3

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),비상시설위치,시설구분명,시설명_건물명,해제일자
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20041/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (64.5%)Imbalance
영업상태명 is highly imbalanced (64.5%)Imbalance
상세영업상태코드 is highly imbalanced (64.5%)Imbalance
상세영업상태명 is highly imbalanced (64.5%)Imbalance
데이터갱신구분 is highly imbalanced (67.7%)Imbalance
해제일자 is highly imbalanced (84.5%)Imbalance
인허가취소일자 has 111 (93.3%) missing valuesMissing
폐업일자 has 111 (93.3%) missing valuesMissing
휴업시작일자 has 119 (100.0%) missing valuesMissing
휴업종료일자 has 119 (100.0%) missing valuesMissing
재개업일자 has 119 (100.0%) missing valuesMissing
전화번호 has 119 (100.0%) missing valuesMissing
소재지우편번호 has 119 (100.0%) missing valuesMissing
도로명우편번호 has 16 (13.4%) missing valuesMissing
업태구분명 has 119 (100.0%) missing valuesMissing
좌표정보(X) has 2 (1.7%) missing valuesMissing
좌표정보(Y) has 2 (1.7%) missing valuesMissing
비상시설위치 has 27 (22.7%) missing valuesMissing
시설명_건물명 has 27 (22.7%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 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 05:45:29.929468
Analysis finished2024-05-11 05:45:30.771582
Duration0.84 seconds
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
119 

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 119
100.0%

Length

2024-05-11T14:45:30.873114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:45:31.003525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 119
100.0%

관리번호
Text

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T14:45:31.254189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters2142
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

Unique119 ?
Unique (%)100.0%

Sample

1st row3140000-S200200008
2nd row3140000-S202300007
3rd row3140000-S202300008
4th row3140000-S201000005
5th row3140000-S201000003
ValueCountFrequency (%)
3140000-s200200008 1
 
0.8%
3140000-s200700006 1
 
0.8%
3140000-s201700003 1
 
0.8%
3140000-s201700002 1
 
0.8%
3140000-s201100015 1
 
0.8%
3140000-s201800001 1
 
0.8%
3140000-s201700009 1
 
0.8%
3140000-s201700008 1
 
0.8%
3140000-s201700007 1
 
0.8%
3140000-s201700006 1
 
0.8%
Other values (109) 109
91.6%
2024-05-11T14:45:31.848753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1091
50.9%
1 241
 
11.3%
2 184
 
8.6%
3 149
 
7.0%
4 134
 
6.3%
- 119
 
5.6%
S 119
 
5.6%
9 29
 
1.4%
8 26
 
1.2%
7 22
 
1.0%
Other values (2) 28
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1904
88.9%
Dash Punctuation 119
 
5.6%
Uppercase Letter 119
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1091
57.3%
1 241
 
12.7%
2 184
 
9.7%
3 149
 
7.8%
4 134
 
7.0%
9 29
 
1.5%
8 26
 
1.4%
7 22
 
1.2%
6 16
 
0.8%
5 12
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 119
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2023
94.4%
Latin 119
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1091
53.9%
1 241
 
11.9%
2 184
 
9.1%
3 149
 
7.4%
4 134
 
6.6%
- 119
 
5.9%
9 29
 
1.4%
8 26
 
1.3%
7 22
 
1.1%
6 16
 
0.8%
Latin
ValueCountFrequency (%)
S 119
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1091
50.9%
1 241
 
11.3%
2 184
 
8.6%
3 149
 
7.0%
4 134
 
6.3%
- 119
 
5.6%
S 119
 
5.6%
9 29
 
1.4%
8 26
 
1.2%
7 22
 
1.0%
Other values (2) 28
 
1.3%

인허가일자
Date

Distinct34
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2002-11-01 00:00:00
Maximum2023-10-11 00:00:00
2024-05-11T14:45:32.039583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:45:32.223224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

인허가취소일자
Text

MISSING 

Distinct4
Distinct (%)50.0%
Missing111
Missing (%)93.3%
Memory size1.1 KiB
2024-05-11T14:45:32.416984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7.5
Mean length7.5
Min length5

Characters and Unicode

Total characters60
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

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-11
2nd row2023-10-11
3rd row2023-12-21
4th row43282
5th row42394
ValueCountFrequency (%)
2023-10-11 2
25.0%
2023-12-21 2
25.0%
43282 2
25.0%
42394 2
25.0%
2024-05-11T14:45:33.185909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 18
30.0%
1 10
16.7%
3 8
13.3%
- 8
13.3%
0 6
 
10.0%
4 6
 
10.0%
8 2
 
3.3%
9 2
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
86.7%
Dash Punctuation 8
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 18
34.6%
1 10
19.2%
3 8
15.4%
0 6
 
11.5%
4 6
 
11.5%
8 2
 
3.8%
9 2
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 18
30.0%
1 10
16.7%
3 8
13.3%
- 8
13.3%
0 6
 
10.0%
4 6
 
10.0%
8 2
 
3.3%
9 2
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 18
30.0%
1 10
16.7%
3 8
13.3%
- 8
13.3%
0 6
 
10.0%
4 6
 
10.0%
8 2
 
3.3%
9 2
 
3.3%

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
1
111 
4
 
8

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 (%)
1 111
93.3%
4 8
 
6.7%

Length

2024-05-11T14:45:33.423508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:45:33.605522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 111
93.3%
4 8
 
6.7%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
영업/정상
111 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length5.605042
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 111
93.3%
취소/말소/만료/정지/중지 8
 
6.7%

Length

2024-05-11T14:45:33.815002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:45:33.992766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 111
93.3%
취소/말소/만료/정지/중지 8
 
6.7%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
18
111 
19
 
8

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 (%)
18 111
93.3%
19 8
 
6.7%

Length

2024-05-11T14:45:34.162590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:45:34.315461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 111
93.3%
19 8
 
6.7%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
사용중
111 
사용중지
 
8

Length

Max length4
Median length3
Mean length3.0672269
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 111
93.3%
사용중지 8
 
6.7%

Length

2024-05-11T14:45:34.507363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:45:34.650715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 111
93.3%
사용중지 8
 
6.7%

폐업일자
Text

MISSING 

Distinct4
Distinct (%)50.0%
Missing111
Missing (%)93.3%
Memory size1.1 KiB
2024-05-11T14:45:34.803601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7.5
Mean length7.5
Min length5

Characters and Unicode

Total characters60
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

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-11
2nd row2023-10-11
3rd row2023-12-21
4th row43282
5th row42394
ValueCountFrequency (%)
2023-10-11 2
25.0%
2023-12-21 2
25.0%
43282 2
25.0%
42394 2
25.0%
2024-05-11T14:45:35.166149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 18
30.0%
1 10
16.7%
3 8
13.3%
- 8
13.3%
0 6
 
10.0%
4 6
 
10.0%
8 2
 
3.3%
9 2
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
86.7%
Dash Punctuation 8
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 18
34.6%
1 10
19.2%
3 8
15.4%
0 6
 
11.5%
4 6
 
11.5%
8 2
 
3.8%
9 2
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 18
30.0%
1 10
16.7%
3 8
13.3%
- 8
13.3%
0 6
 
10.0%
4 6
 
10.0%
8 2
 
3.3%
9 2
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 18
30.0%
1 10
16.7%
3 8
13.3%
- 8
13.3%
0 6
 
10.0%
4 6
 
10.0%
8 2
 
3.3%
9 2
 
3.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing119
Missing (%)100.0%
Memory size1.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing119
Missing (%)100.0%
Memory size1.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing119
Missing (%)100.0%
Memory size1.2 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing119
Missing (%)100.0%
Memory size1.2 KiB

소재지면적
Real number (ℝ)

Distinct113
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6963.8687
Minimum99
Maximum58752
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T14:45:35.392132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum99
5-th percentile429.2
Q11976.5
median4095
Q38285
95-th percentile21020.5
Maximum58752
Range58653
Interquartile range (IQR)6308.5

Descriptive statistics

Standard deviation8886.6975
Coefficient of variation (CV)1.276115
Kurtosis13.900484
Mean6963.8687
Median Absolute Deviation (MAD)2795
Skewness3.3078267
Sum828700.38
Variance78973392
MonotonicityNot monotonic
2024-05-11T14:45:35.625187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3537.0 3
 
2.5%
2938.0 2
 
1.7%
4954.0 2
 
1.7%
6508.0 2
 
1.7%
4000.0 2
 
1.7%
1142.0 1
 
0.8%
1086.0 1
 
0.8%
3302.0 1
 
0.8%
1471.0 1
 
0.8%
11510.0 1
 
0.8%
Other values (103) 103
86.6%
ValueCountFrequency (%)
99.0 1
0.8%
124.0 1
0.8%
132.0 1
0.8%
192.0 1
0.8%
195.0 1
0.8%
242.0 1
0.8%
450.0 1
0.8%
489.0 1
0.8%
516.0 1
0.8%
565.0 1
0.8%
ValueCountFrequency (%)
58752.0 1
0.8%
45544.0 1
0.8%
44194.0 1
0.8%
28984.0 1
0.8%
24730.0 1
0.8%
23023.0 1
0.8%
20798.0 1
0.8%
17575.0 1
0.8%
16784.34 1
0.8%
16464.0 1
0.8%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing119
Missing (%)100.0%
Memory size1.2 KiB

지번주소
Text

Distinct105
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T14:45:36.098040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length21.294118
Min length18

Characters and Unicode

Total characters2534
Distinct characters54
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

Unique95 ?
Unique (%)79.8%

Sample

1st row서울특별시 양천구 목동 923번지 5호
2nd row서울특별시 양천구 목동 908-34 부영그린타운3차
3rd row서울특별시 양천구 목동 929 한신청구아파트
4th row서울특별시 양천구 신월동 48번지 12호
5th row서울특별시 양천구 신월동 150번지 3호
ValueCountFrequency (%)
서울특별시 119
21.9%
양천구 119
21.9%
신월동 44
 
8.1%
신정동 39
 
7.2%
목동 36
 
6.6%
2호 11
 
2.0%
1호 9
 
1.7%
549 5
 
0.9%
276번지 5
 
0.9%
3호 5
 
0.9%
Other values (115) 152
27.9%
2024-05-11T14:45:36.794750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
425
16.8%
동 126
 
5.0%
서 120
 
4.7%
구 120
 
4.7%
울 120
 
4.7%
특 119
 
4.7%
별 119
 
4.7%
시 119
 
4.7%
양 119
 
4.7%
천 119
 
4.7%
Other values (44) 1028
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1634
64.5%
Decimal Number 471
 
18.6%
Space Separator 425
 
16.8%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 126
 
7.7%
서 120
 
7.3%
구 120
 
7.3%
울 120
 
7.3%
특 119
 
7.3%
별 119
 
7.3%
시 119
 
7.3%
양 119
 
7.3%
천 119
 
7.3%
지 111
 
6.8%
Other values (32) 442
27.1%
Decimal Number
ValueCountFrequency (%)
1 101
21.4%
2 68
14.4%
0 55
11.7%
9 53
11.3%
3 53
11.3%
4 34
 
7.2%
7 30
 
6.4%
5 28
 
5.9%
6 28
 
5.9%
8 21
 
4.5%
Space Separator
ValueCountFrequency (%)
425
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1634
64.5%
Common 900
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 126
 
7.7%
서 120
 
7.3%
구 120
 
7.3%
울 120
 
7.3%
특 119
 
7.3%
별 119
 
7.3%
시 119
 
7.3%
양 119
 
7.3%
천 119
 
7.3%
지 111
 
6.8%
Other values (32) 442
27.1%
Common
ValueCountFrequency (%)
425
47.2%
1 101
 
11.2%
2 68
 
7.6%
0 55
 
6.1%
9 53
 
5.9%
3 53
 
5.9%
4 34
 
3.8%
7 30
 
3.3%
5 28
 
3.1%
6 28
 
3.1%
Other values (2) 25
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1634
64.5%
ASCII 900
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
425
47.2%
1 101
 
11.2%
2 68
 
7.6%
0 55
 
6.1%
9 53
 
5.9%
3 53
 
5.9%
4 34
 
3.8%
7 30
 
3.3%
5 28
 
3.1%
6 28
 
3.1%
Other values (2) 25
 
2.8%
Hangul
ValueCountFrequency (%)
동 126
 
7.7%
서 120
 
7.3%
구 120
 
7.3%
울 120
 
7.3%
특 119
 
7.3%
별 119
 
7.3%
시 119
 
7.3%
양 119
 
7.3%
천 119
 
7.3%
지 111
 
6.8%
Other values (32) 442
27.1%

도로명주소
Text

Distinct111
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T14:45:37.238288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length35
Mean length31.588235
Min length22

Characters and Unicode

Total characters3759
Distinct characters185
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)87.4%

Sample

1st row서울특별시 양천구 목동동로 233 (목동, 한국방송회관)
2nd row서울특별시 양천구 목동동로 411 (목동, 부영그린타운3차)
3rd row서울특별시 양천구 목동서로2길 22 (목동, 한신청구아파트)
4th row서울특별시 양천구 가로공원로 85 (신월동)
5th row서울특별시 양천구 가로공원로 86 (신월동, 신월청소년문화쎈타)
ValueCountFrequency (%)
서울특별시 119
 
17.1%
양천구 119
 
17.1%
신월동 44
 
6.3%
신정동 39
 
5.6%
목동 36
 
5.2%
목동동로 14
 
2.0%
지하 7
 
1.0%
목동서로 7
 
1.0%
7 5
 
0.7%
목동로3길 5
 
0.7%
Other values (215) 300
43.2%
2024-05-11T14:45:37.945254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
576
 
15.3%
동 206
 
5.5%
서 137
 
3.6%
양 136
 
3.6%
천 130
 
3.5%
신 129
 
3.4%
로 127
 
3.4%
울 125
 
3.3%
구 123
 
3.3%
시 121
 
3.2%
Other values (175) 1949
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2439
64.9%
Space Separator 576
 
15.3%
Decimal Number 399
 
10.6%
Open Punctuation 119
 
3.2%
Close Punctuation 119
 
3.2%
Other Punctuation 94
 
2.5%
Dash Punctuation 12
 
0.3%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 206
 
8.4%
서 137
 
5.6%
양 136
 
5.6%
천 130
 
5.3%
신 129
 
5.3%
로 127
 
5.2%
울 125
 
5.1%
구 123
 
5.0%
시 121
 
5.0%
특 119
 
4.9%
Other values (158) 1086
44.5%
Decimal Number
ValueCountFrequency (%)
1 92
23.1%
3 69
17.3%
2 45
11.3%
0 45
11.3%
5 43
10.8%
7 28
 
7.0%
8 21
 
5.3%
6 21
 
5.3%
9 18
 
4.5%
4 17
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 93
98.9%
. 1
 
1.1%
Space Separator
ValueCountFrequency (%)
576
100.0%
Open Punctuation
ValueCountFrequency (%)
( 119
100.0%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2439
64.9%
Common 1319
35.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 206
 
8.4%
서 137
 
5.6%
양 136
 
5.6%
천 130
 
5.3%
신 129
 
5.3%
로 127
 
5.2%
울 125
 
5.1%
구 123
 
5.0%
시 121
 
5.0%
특 119
 
4.9%
Other values (158) 1086
44.5%
Common
ValueCountFrequency (%)
576
43.7%
( 119
 
9.0%
) 119
 
9.0%
, 93
 
7.1%
1 92
 
7.0%
3 69
 
5.2%
2 45
 
3.4%
0 45
 
3.4%
5 43
 
3.3%
7 28
 
2.1%
Other values (6) 90
 
6.8%
Latin
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2439
64.9%
ASCII 1319
35.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
576
43.7%
( 119
 
9.0%
) 119
 
9.0%
, 93
 
7.1%
1 92
 
7.0%
3 69
 
5.2%
2 45
 
3.4%
0 45
 
3.4%
5 43
 
3.3%
7 28
 
2.1%
Other values (6) 90
 
6.8%
Hangul
ValueCountFrequency (%)
동 206
 
8.4%
서 137
 
5.6%
양 136
 
5.6%
천 130
 
5.3%
신 129
 
5.3%
로 127
 
5.2%
울 125
 
5.1%
구 123
 
5.0%
시 121
 
5.0%
특 119
 
4.9%
Other values (158) 1086
44.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct76
Distinct (%)73.8%
Missing16
Missing (%)13.4%
Memory size1.1 KiB
2024-05-11T14:45:38.357904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.3203883
Min length4

Characters and Unicode

Total characters445
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

Unique56 ?
Unique (%)54.4%

Sample

1st row07995
2nd row07984
3rd row07979
4th row07909
5th row07910
ValueCountFrequency (%)
07949 5
 
4.9%
8080 3
 
2.9%
07967 3
 
2.9%
7956 3
 
2.9%
8100 3
 
2.9%
7985 2
 
1.9%
8038 2
 
1.9%
7936 2
 
1.9%
07964 2
 
1.9%
07914 2
 
1.9%
Other values (66) 76
73.8%
2024-05-11T14:45:38.997092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 87
19.6%
9 83
18.7%
7 73
16.4%
8 67
15.1%
1 30
 
6.7%
4 26
 
5.8%
3 22
 
4.9%
6 21
 
4.7%
5 19
 
4.3%
2 15
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 443
99.6%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87
19.6%
9 83
18.7%
7 73
16.5%
8 67
15.1%
1 30
 
6.8%
4 26
 
5.9%
3 22
 
5.0%
6 21
 
4.7%
5 19
 
4.3%
2 15
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 445
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 87
19.6%
9 83
18.7%
7 73
16.4%
8 67
15.1%
1 30
 
6.7%
4 26
 
5.8%
3 22
 
4.9%
6 21
 
4.7%
5 19
 
4.3%
2 15
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87
19.6%
9 83
18.7%
7 73
16.4%
8 67
15.1%
1 30
 
6.7%
4 26
 
5.8%
3 22
 
4.9%
6 21
 
4.7%
5 19
 
4.3%
2 15
 
3.4%

사업장명
Text

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T14:45:39.348149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length17.89916
Min length7

Characters and Unicode

Total characters2130
Distinct characters193
Distinct categories10 ?
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 (%)100.0%

Sample

1st row방송회관 지하1~6층 주차장
2nd row부영그린타운3차(지하2~6층) 주차장
3rd row목동한신청구아파트(지하1~2층) 주차장
4th row구립 파란들어린이집 지하1층
5th row신월청소년문화센터 지하1층
ValueCountFrequency (%)
주차장 73
20.3%
지하1층 56
 
15.6%
지하1,2층 18
 
5.0%
지하1층주차장 10
 
2.8%
101동 6
 
1.7%
대합실 4
 
1.1%
아파트 4
 
1.1%
지하1 4
 
1.1%
목동금호베스트빌 4
 
1.1%
지하1~2층 3
 
0.8%
Other values (155) 177
49.3%
2024-05-11T14:45:39.919191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
240
 
11.3%
1 151
 
7.1%
지 133
 
6.2%
층 120
 
5.6%
하 119
 
5.6%
차 102
 
4.8%
주 97
 
4.6%
장 93
 
4.4%
동 70
 
3.3%
트 66
 
3.1%
Other values (183) 939
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1537
72.2%
Decimal Number 276
 
13.0%
Space Separator 240
 
11.3%
Other Punctuation 24
 
1.1%
Math Symbol 19
 
0.9%
Close Punctuation 12
 
0.6%
Open Punctuation 12
 
0.6%
Uppercase Letter 8
 
0.4%
Lowercase Letter 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 133
 
8.7%
층 120
 
7.8%
하 119
 
7.7%
차 102
 
6.6%
주 97
 
6.3%
장 93
 
6.1%
동 70
 
4.6%
트 66
 
4.3%
파 62
 
4.0%
아 61
 
4.0%
Other values (166) 614
39.9%
Decimal Number
ValueCountFrequency (%)
1 151
54.7%
2 55
 
19.9%
0 31
 
11.2%
3 16
 
5.8%
6 8
 
2.9%
4 7
 
2.5%
5 5
 
1.8%
8 2
 
0.7%
7 1
 
0.4%
Space Separator
ValueCountFrequency (%)
240
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1537
72.2%
Common 584
 
27.4%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 133
 
8.7%
층 120
 
7.8%
하 119
 
7.7%
차 102
 
6.6%
주 97
 
6.3%
장 93
 
6.1%
동 70
 
4.6%
트 66
 
4.3%
파 62
 
4.0%
아 61
 
4.0%
Other values (166) 614
39.9%
Common
ValueCountFrequency (%)
240
41.1%
1 151
25.9%
2 55
 
9.4%
0 31
 
5.3%
, 24
 
4.1%
~ 19
 
3.3%
3 16
 
2.7%
) 12
 
2.1%
( 12
 
2.1%
6 8
 
1.4%
Other values (5) 16
 
2.7%
Latin
ValueCountFrequency (%)
B 8
88.9%
e 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1537
72.2%
ASCII 593
 
27.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
240
40.5%
1 151
25.5%
2 55
 
9.3%
0 31
 
5.2%
, 24
 
4.0%
~ 19
 
3.2%
3 16
 
2.7%
) 12
 
2.0%
( 12
 
2.0%
B 8
 
1.3%
Other values (7) 25
 
4.2%
Hangul
ValueCountFrequency (%)
지 133
 
8.7%
층 120
 
7.8%
하 119
 
7.7%
차 102
 
6.6%
주 97
 
6.3%
장 93
 
6.1%
동 70
 
4.6%
트 66
 
4.3%
파 62
 
4.0%
아 61
 
4.0%
Other values (166) 614
39.9%

최종수정일자
Date

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2016-01-25 16:07:34
Maximum2024-01-31 10:02:05
2024-05-11T14:45:40.133794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:45:40.372581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
U
112 
I
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 112
94.1%
I 7
 
5.9%

Length

2024-05-11T14:45:40.595919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:45:40.788999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 112
94.1%
i 7
 
5.9%

데이터갱신일자
Date

Distinct19
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 00:02:00
2024-05-11T14:45:40.947122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:45:41.140608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing119
Missing (%)100.0%
Memory size1.2 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)86.3%
Missing2
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean187163.7
Minimum184359.25
Maximum189954.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T14:45:41.367616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184359.25
5-th percentile184716.04
Q1185737.72
median187734.98
Q3188298.07
95-th percentile189481.02
Maximum189954.81
Range5595.563
Interquartile range (IQR)2560.3552

Descriptive statistics

Standard deviation1559.6753
Coefficient of variation (CV)0.0083332146
Kurtosis-1.2402267
Mean187163.7
Median Absolute Deviation (MAD)1238.7194
Skewness-0.2124852
Sum21898153
Variance2432587
MonotonicityNot monotonic
2024-05-11T14:45:41.593443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188298.07049973 5
 
4.2%
188012.804745161 4
 
3.4%
188160.216268445 3
 
2.5%
187864.50227698 3
 
2.5%
188670.45617406 2
 
1.7%
189000.48603009 2
 
1.7%
185335.210131048 2
 
1.7%
185978.000254037 2
 
1.7%
188246.471504471 2
 
1.7%
187876.785857274 1
 
0.8%
Other values (91) 91
76.5%
(Missing) 2
 
1.7%
ValueCountFrequency (%)
184359.248011837 1
0.8%
184495.17209953 1
0.8%
184506.285307963 1
0.8%
184645.579724418 1
0.8%
184662.037450571 1
0.8%
184676.704972197 1
0.8%
184725.875363456 1
0.8%
184737.734597798 1
0.8%
184773.961624315 1
0.8%
184781.209740863 1
0.8%
ValueCountFrequency (%)
189954.811054416 1
0.8%
189878.40729119 1
0.8%
189755.541308355 1
0.8%
189712.460044056 1
0.8%
189576.475334065 1
0.8%
189519.862506193 1
0.8%
189471.306217651 1
0.8%
189389.386306442 1
0.8%
189199.586460694 1
0.8%
189000.48603009 2
1.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)86.3%
Missing2
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean447201.23
Minimum444911.61
Maximum449649.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T14:45:41.821831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444911.61
5-th percentile445428.45
Q1446213.73
median447037.87
Q3448200.12
95-th percentile449201.17
Maximum449649.02
Range4737.4065
Interquartile range (IQR)1986.3862

Descriptive statistics

Standard deviation1214.4176
Coefficient of variation (CV)0.0027155954
Kurtosis-1.0559369
Mean447201.23
Median Absolute Deviation (MAD)971.61119
Skewness0.21849639
Sum52322544
Variance1474810.2
MonotonicityNot monotonic
2024-05-11T14:45:42.025785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449201.16645888 5
 
4.2%
445428.447103333 4
 
3.4%
447779.16865247 3
 
2.5%
448953.063207171 3
 
2.5%
446284.549419207 2
 
1.7%
445955.944424525 2
 
1.7%
446403.139717435 2
 
1.7%
445725.495629105 2
 
1.7%
447947.627317323 2
 
1.7%
445001.620672229 1
 
0.8%
Other values (91) 91
76.5%
(Missing) 2
 
1.7%
ValueCountFrequency (%)
444911.609710795 1
 
0.8%
445001.620672229 1
 
0.8%
445209.687205241 1
 
0.8%
445428.447103333 4
3.4%
445528.30593777 1
 
0.8%
445601.70796781 1
 
0.8%
445601.995865959 1
 
0.8%
445602.963172845 1
 
0.8%
445725.495629105 2
1.7%
445737.791091401 1
 
0.8%
ValueCountFrequency (%)
449649.016215774 1
 
0.8%
449411.580893629 1
 
0.8%
449321.244359901 1
 
0.8%
449201.16645888 5
4.2%
449158.187080718 1
 
0.8%
449157.023707639 1
 
0.8%
449018.385903531 1
 
0.8%
449016.297098733 1
 
0.8%
448953.063207171 3
2.5%
448902.294659584 1
 
0.8%

비상시설위치
Text

MISSING 

Distinct82
Distinct (%)89.1%
Missing27
Missing (%)22.7%
Memory size1.1 KiB
2024-05-11T14:45:42.422146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length20.793478
Min length18

Characters and Unicode

Total characters1913
Distinct characters41
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

Unique75 ?
Unique (%)81.5%

Sample

1st row서울특별시 양천구 신월동 489-3
2nd row서울특별시 양천구 신정동 313-1 서울남부지방법원
3rd row서울특별시 양천구 신정동 319번지 2호
4th row서울특별시 양천구 목동 911번지 1호
5th row서울특별시 양천구 신월동 465번지 5호
ValueCountFrequency (%)
서울특별시 92
22.3%
양천구 92
22.3%
신정동 38
 
9.2%
신월동 36
 
8.7%
목동 18
 
4.4%
2호 11
 
2.7%
1호 7
 
1.7%
276번지 5
 
1.2%
9호 3
 
0.7%
322번지 3
 
0.7%
Other values (84) 108
26.2%
2024-05-11T14:45:43.142839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
321
16.8%
서 93
 
4.9%
울 93
 
4.9%
동 93
 
4.9%
양 92
 
4.8%
천 92
 
4.8%
구 92
 
4.8%
시 92
 
4.8%
별 92
 
4.8%
특 92
 
4.8%
Other values (31) 761
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1233
64.5%
Decimal Number 357
 
18.7%
Space Separator 321
 
16.8%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 93
 
7.5%
울 93
 
7.5%
동 93
 
7.5%
양 92
 
7.5%
천 92
 
7.5%
구 92
 
7.5%
시 92
 
7.5%
별 92
 
7.5%
특 92
 
7.5%
지 91
 
7.4%
Other values (19) 311
25.2%
Decimal Number
ValueCountFrequency (%)
1 77
21.6%
2 57
16.0%
3 46
12.9%
0 45
12.6%
9 33
9.2%
6 28
 
7.8%
7 24
 
6.7%
8 17
 
4.8%
4 16
 
4.5%
5 14
 
3.9%
Space Separator
ValueCountFrequency (%)
321
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1233
64.5%
Common 680
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 93
 
7.5%
울 93
 
7.5%
동 93
 
7.5%
양 92
 
7.5%
천 92
 
7.5%
구 92
 
7.5%
시 92
 
7.5%
별 92
 
7.5%
특 92
 
7.5%
지 91
 
7.4%
Other values (19) 311
25.2%
Common
ValueCountFrequency (%)
321
47.2%
1 77
 
11.3%
2 57
 
8.4%
3 46
 
6.8%
0 45
 
6.6%
9 33
 
4.9%
6 28
 
4.1%
7 24
 
3.5%
8 17
 
2.5%
4 16
 
2.4%
Other values (2) 16
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1233
64.5%
ASCII 680
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
321
47.2%
1 77
 
11.3%
2 57
 
8.4%
3 46
 
6.8%
0 45
 
6.6%
9 33
 
4.9%
6 28
 
4.1%
7 24
 
3.5%
8 17
 
2.5%
4 16
 
2.4%
Other values (2) 16
 
2.4%
Hangul
ValueCountFrequency (%)
서 93
 
7.5%
울 93
 
7.5%
동 93
 
7.5%
양 92
 
7.5%
천 92
 
7.5%
구 92
 
7.5%
시 92
 
7.5%
별 92
 
7.5%
특 92
 
7.5%
지 91
 
7.4%
Other values (19) 311
25.2%

시설구분명
Categorical

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
공공용시설
88 
<NA>
27 
공공시설
 
4

Length

Max length5
Median length5
Mean length4.7394958
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 (%)
공공용시설 88
73.9%
<NA> 27
 
22.7%
공공시설 4
 
3.4%

Length

2024-05-11T14:45:43.362982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:45:43.519633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용시설 88
73.9%
na 27
 
22.7%
공공시설 4
 
3.4%

시설명_건물명
Text

MISSING 

Distinct92
Distinct (%)100.0%
Missing27
Missing (%)22.7%
Memory size1.1 KiB
2024-05-11T14:45:43.840054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length17.326087
Min length7

Characters and Unicode

Total characters1594
Distinct characters168
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)100.0%

Sample

1st row신목동파라곤아파트 지하2층 주차장
2nd row남부지방법원 별관 지하1층 주차장
3rd row서울출입국 외국인청 지하1층
4th row이화여대부속목동병원 지하1, 2층
5th row보성아파트 지하1층 주차장
ValueCountFrequency (%)
주차장 55
19.9%
지하1층 43
 
15.6%
지하1,2층 17
 
6.2%
지하1층주차장 8
 
2.9%
101동 5
 
1.8%
아파트 4
 
1.4%
대합실 4
 
1.4%
목동2차성원아파트 3
 
1.1%
지하주차장(b1층 3
 
1.1%
지하1 3
 
1.1%
Other values (120) 131
47.5%
2024-05-11T14:45:44.362844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
184
 
11.5%
1 113
 
7.1%
지 102
 
6.4%
층 93
 
5.8%
하 91
 
5.7%
차 79
 
5.0%
주 75
 
4.7%
장 71
 
4.5%
트 49
 
3.1%
파 48
 
3.0%
Other values (158) 689
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1155
72.5%
Decimal Number 197
 
12.4%
Space Separator 184
 
11.5%
Other Punctuation 23
 
1.4%
Math Symbol 9
 
0.6%
Open Punctuation 8
 
0.5%
Uppercase Letter 8
 
0.5%
Close Punctuation 8
 
0.5%
Lowercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 102
 
8.8%
층 93
 
8.1%
하 91
 
7.9%
차 79
 
6.8%
주 75
 
6.5%
장 71
 
6.1%
트 49
 
4.2%
파 48
 
4.2%
아 47
 
4.1%
동 45
 
3.9%
Other values (142) 455
39.4%
Decimal Number
ValueCountFrequency (%)
1 113
57.4%
2 40
 
20.3%
0 18
 
9.1%
3 12
 
6.1%
4 5
 
2.5%
6 4
 
2.0%
5 3
 
1.5%
8 2
 
1.0%
Space Separator
ValueCountFrequency (%)
184
100.0%
Other Punctuation
ValueCountFrequency (%)
, 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1155
72.5%
Common 430
 
27.0%
Latin 9
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 102
 
8.8%
층 93
 
8.1%
하 91
 
7.9%
차 79
 
6.8%
주 75
 
6.5%
장 71
 
6.1%
트 49
 
4.2%
파 48
 
4.2%
아 47
 
4.1%
동 45
 
3.9%
Other values (142) 455
39.4%
Common
ValueCountFrequency (%)
184
42.8%
1 113
26.3%
2 40
 
9.3%
, 23
 
5.3%
0 18
 
4.2%
3 12
 
2.8%
~ 9
 
2.1%
( 8
 
1.9%
) 8
 
1.9%
4 5
 
1.2%
Other values (4) 10
 
2.3%
Latin
ValueCountFrequency (%)
B 8
88.9%
e 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1155
72.5%
ASCII 439
 
27.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
184
41.9%
1 113
25.7%
2 40
 
9.1%
, 23
 
5.2%
0 18
 
4.1%
3 12
 
2.7%
~ 9
 
2.1%
( 8
 
1.8%
B 8
 
1.8%
) 8
 
1.8%
Other values (6) 16
 
3.6%
Hangul
ValueCountFrequency (%)
지 102
 
8.8%
층 93
 
8.1%
하 91
 
7.9%
차 79
 
6.8%
주 75
 
6.5%
장 71
 
6.1%
트 49
 
4.2%
파 48
 
4.2%
아 47
 
4.1%
동 45
 
3.9%
Other values (142) 455
39.4%

해제일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
115 
20180701
 
2
20160125
 
2

Length

Max length8
Median length4
Mean length4.1344538
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> 115
96.6%
20180701 2
 
1.7%
20160125 2
 
1.7%

Length

2024-05-11T14:45:44.602033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:45:44.773228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 115
96.6%
20180701 2
 
1.7%
20160125 2
 
1.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
031400003140000-S2002000082002-11-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>14778.0<NA>서울특별시 양천구 목동 923번지 5호서울특별시 양천구 목동동로 233 (목동, 한국방송회관)07995방송회관 지하1~6층 주차장2023-09-06 10:04:43U2022-12-09 00:08:00.0<NA>188572.108663447198.912626<NA><NA><NA><NA>
131400003140000-S2023000072023-10-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>24730.0<NA>서울특별시 양천구 목동 908-34 부영그린타운3차서울특별시 양천구 목동동로 411 (목동, 부영그린타운3차)07984부영그린타운3차(지하2~6층) 주차장2023-10-13 11:10:15I2022-10-30 23:05:00.0<NA>189519.862506448282.256149<NA><NA><NA><NA>
231400003140000-S2023000082023-10-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>23023.0<NA>서울특별시 양천구 목동 929 한신청구아파트서울특별시 양천구 목동서로2길 22 (목동, 한신청구아파트)07979목동한신청구아파트(지하1~2층) 주차장2023-10-13 17:38:10I2022-10-30 23:05:00.0<NA>189471.306218448806.969144<NA><NA><NA><NA>
331400003140000-S2010000052010-12-102023-10-114취소/말소/만료/정지/중지19사용중지2023-10-11<NA><NA><NA><NA>124.0<NA>서울특별시 양천구 신월동 48번지 12호서울특별시 양천구 가로공원로 85 (신월동)07909구립 파란들어린이집 지하1층2023-10-13 17:46:11U2022-10-30 23:05:00.0<NA>184495.1721448173.566319<NA><NA><NA><NA>
431400003140000-S2010000032010-12-062023-10-114취소/말소/만료/정지/중지19사용중지2023-10-11<NA><NA><NA><NA>242.0<NA>서울특별시 양천구 신월동 150번지 3호서울특별시 양천구 가로공원로 86 (신월동, 신월청소년문화쎈타)07910신월청소년문화센터 지하1층2023-10-13 17:45:16U2022-10-30 23:05:00.0<NA>184506.285308448124.080332<NA><NA><NA><NA>
531400003140000-S2023000012023-06-16<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>13470.0<NA>서울특별시 양천구 신월동 489-3서울특별시 양천구 오목로 55 (신월동)7936신목동파라곤아파트 지하2층 주차장2023-06-27 11:33:42U2023-06-29 02:40:00.0<NA>186139.287304446784.424029서울특별시 양천구 신월동 489-3공공용시설신목동파라곤아파트 지하2층 주차장<NA>
631400003140000-S2003000022003-02-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4095.0<NA>서울특별시 양천구 목동 549 금호베스트빌아파트 101동서울특별시 양천구 목동중앙북로8길 111, 101동 (목동, 금호베스트빌아파트)07949목동금호베스트빌 101동 지하1층 주차장2023-11-02 14:03:22U2022-11-01 00:04:00.0<NA>188298.0705449201.166459<NA><NA><NA><NA>
731400003140000-S2023000062023-06-27<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1399.0<NA>서울특별시 양천구 신정동 313-1 서울남부지방법원서울특별시 양천구 신월로 386, 서울남부지방법원 (신정동)8088남부지방법원 별관 지하1층 주차장2023-06-27 10:43:17I2023-06-29 00:19:12.0<NA>187923.378904446606.56549서울특별시 양천구 신정동 313-1 서울남부지방법원공공용시설남부지방법원 별관 지하1층 주차장<NA>
831400003140000-S2023000022023-06-21<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3833.0<NA>서울특별시 양천구 목동 549 금호베스트빌아파트 102동서울특별시 양천구 목동중앙북로8길 111, 102동 (목동, 금호베스트빌아파트)07949목동금호베스트빌 102동 지하1층 주차장2023-11-02 14:04:23U2022-11-01 00:04:00.0<NA>188298.0705449201.166459<NA><NA><NA><NA>
931400003140000-S2023000042023-06-21<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4454.0<NA>서울특별시 양천구 목동 549 금호베스트빌아파트 104동서울특별시 양천구 목동중앙북로8길 111, 104동 (목동, 금호베스트빌아파트)07949목동금호베스트빌 104동 지하1층 주차장2023-11-02 14:05:58U2022-11-01 00:04:00.0<NA>188298.0705449201.166459<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
10931400003140000-S2010000152010-12-14<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>10581.0<NA>서울특별시 양천구 신정동 337번지 2호서울특별시 양천구 목동남로4길 6-46 (신정동)<NA>목동2차우성아파트 지하1층 주차장2023-06-21 21:58:25U2023-06-23 02:40:00.0<NA>188008.01391444911.609711서울특별시 양천구 신정동 337번지 2호공공용시설목동2차우성아파트 지하1층 주차장<NA>
11031400003140000-S2023000102023-10-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>4674.0<NA>서울특별시 양천구 신월동 1058 신월동코아루2단지서울특별시 양천구 남부순환로56길 15 (신월동, 신월동코아루2단지)07914신월코아루2단지아파트(지하1층) 주차장2023-11-03 15:10:44U2022-11-01 00:05:00.0<NA>184781.209741447718.643842<NA><NA><NA><NA>
11131400003140000-S2002001092002-11-01432824취소/말소/만료/정지/중지19사용중지43282<NA><NA><NA><NA>99.0<NA>서울특별시 양천구 신정동 276번지서울특별시 양천구 목동로3길 41-0 (신정동, 신정지하철차량기지)8100신정기지지하보도2018-07-03 13:10:32I2018-08-31 23:59:59.0<NA>188012.804745445428.447103서울특별시 양천구 신정동 276번지공공시설신정기지지하보도20180701
11231400003140000-S2012000192012-07-12423944취소/말소/만료/정지/중지19사용중지42394<NA><NA><NA><NA>3285.72<NA>서울특별시 양천구 목동 956번지서울특별시 양천구 목동중앙북로 38 (목동)<NA>롯데캐슬위너아파트 113동2016-01-25 16:07:34I2018-08-31 23:59:59.0<NA><NA><NA>서울특별시 양천구 목동 956번지공공시설롯데캐슬위너아파트 113동20160125
11331400003140000-S2002000232002-11-01423944취소/말소/만료/정지/중지19사용중지42394<NA><NA><NA><NA>195.0<NA>서울특별시 양천구 목동 907번지 3호서울특별시 양천구 목동동로 375 (목동)<NA>목5동주민센터2016-01-25 17:07:51I2018-08-31 23:59:59.0<NA><NA><NA>서울특별시 양천구 목동 907번지 3호공공시설목5동주민센터20160125
11431400003140000-S2010000042010-12-08432824취소/말소/만료/정지/중지19사용중지43282<NA><NA><NA><NA>12384.0<NA>서울특별시 양천구 신월동 1022번지서울특별시 양천구 신정로13길 50-0 (신월동)<NA>벽산블루밍 1,2단지2018-07-03 13:11:28I2018-08-31 23:59:59.0<NA>185978.000254445725.495629서울특별시 양천구 신월동 1022번지공공시설벽산블루밍 1,2단지20180701
11531400003140000-S2017000012017-01-092023-12-214취소/말소/만료/정지/중지19사용중지2023-12-21<NA><NA><NA><NA>192.0<NA>서울특별시 양천구 목동 907번지 3호서울특별시 양천구 목동동로 373 (목동, 목1지구대)07983양천구사회적경제지원센터 지하1층2023-12-21 11:28:15U2022-11-01 22:03:00.0<NA>189199.586461448111.708218<NA><NA><NA><NA>
11631400003140000-S2009000162009-12-15<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>16784.34<NA>서울특별시 양천구 목동 951번지서울특별시 양천구 목동중앙서로 37 (목동)07964목동금호어울림아파트 101~106동 지하1~2층 주차장2024-01-31 09:52:07U2023-12-02 00:02:00.0<NA>188246.471504447947.627317<NA><NA><NA><NA>
11731400003140000-S2009000152009-12-15<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6508.0<NA>서울특별시 양천구 목동 941번지서울특별시 양천구 목동중앙로 11 (목동)07967목동대원칸타빌아파트 201동 202동 지하1~2층주차장2024-01-31 10:01:03U2023-12-02 00:02:00.0<NA>188160.216268447779.168652<NA><NA><NA><NA>
11831400003140000-S2009000172009-12-15<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>6508.0<NA>서울특별시 양천구 목동 941번지서울특별시 양천구 목동중앙로 11 (목동, 대원칸타빌2단지아파트)07967목동대원칸타빌아파트 203동 204동 지하1~2층주차장2024-01-31 10:01:40U2023-12-02 00:02:00.0<NA>188160.216268447779.168652<NA><NA><NA><NA>