Overview

Dataset statistics

Number of variables30
Number of observations48
Missing cells568
Missing cells (%)39.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory258.8 B

Variable types

Categorical7
Numeric6
DateTime3
Unsupported8
Text6

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),사용목적,사용방법,월사용량,수용정원수,시설사용여부
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-19120/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 48 (100.0%) missing valuesMissing
폐업일자 has 20 (41.7%) missing valuesMissing
휴업시작일자 has 48 (100.0%) missing valuesMissing
휴업종료일자 has 48 (100.0%) missing valuesMissing
재개업일자 has 48 (100.0%) missing valuesMissing
전화번호 has 42 (87.5%) missing valuesMissing
소재지면적 has 48 (100.0%) missing valuesMissing
소재지우편번호 has 48 (100.0%) missing valuesMissing
지번주소 has 5 (10.4%) missing valuesMissing
도로명주소 has 8 (16.7%) missing valuesMissing
도로명우편번호 has 31 (64.6%) missing valuesMissing
업태구분명 has 48 (100.0%) missing valuesMissing
좌표정보(X) has 3 (6.2%) missing valuesMissing
좌표정보(Y) has 3 (6.2%) missing valuesMissing
사용목적 has 18 (37.5%) missing valuesMissing
사용방법 has 18 (37.5%) missing valuesMissing
월사용량 has 18 (37.5%) missing valuesMissing
수용정원수 has 18 (37.5%) missing valuesMissing
시설사용여부 has 48 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
소재지면적 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
시설사용여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
월사용량 has 2 (4.2%) zerosZeros
수용정원수 has 2 (4.2%) zerosZeros

Reproduction

Analysis started2024-05-18 00:54:34.916892
Analysis finished2024-05-18 00:54:35.892089
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
3180000
48 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 48
100.0%

Length

2024-05-18T09:54:36.027626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:36.314940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 48
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.013818 × 1018
Minimum1.989318 × 1018
Maximum2.023318 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-18T09:54:36.632925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.989318 × 1018
5-th percentile1.993318 × 1018
Q12.012068 × 1018
median2.017318 × 1018
Q32.018568 × 1018
95-th percentile2.023318 × 1018
Maximum2.023318 × 1018
Range3.4000003 × 1016
Interquartile range (IQR)6.5000034 × 1015

Descriptive statistics

Standard deviation8.5278044 × 1015
Coefficient of variation (CV)0.004234645
Kurtosis1.3984168
Mean2.013818 × 1018
Median Absolute Deviation (MAD)2.5000015 × 1015
Skewness-1.4493327
Sum4.4295446 × 1018
Variance7.2723448 × 1031
MonotonicityStrictly increasing
2024-05-18T09:54:37.076782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1989318019012200001 1
 
2.1%
2017318022112200002 1
 
2.1%
2017318022112200004 1
 
2.1%
2017318022112200005 1
 
2.1%
2018318022112200001 1
 
2.1%
2018318022112200002 1
 
2.1%
2018318022112200003 1
 
2.1%
2018318022112200004 1
 
2.1%
2018318022112200005 1
 
2.1%
2018318022112200006 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
1989318019012200001 1
2.1%
1993318019012210000 1
2.1%
1993318019012211111 1
2.1%
1993318022112200001 1
2.1%
2001318007602703193 1
2.1%
2003318007602700001 1
2.1%
2003318007602700002 1
2.1%
2004318007602700001 1
2.1%
2005318007602700001 1
2.1%
2006318007602700001 1
2.1%
ValueCountFrequency (%)
2023318022112200004 1
2.1%
2023318022112200003 1
2.1%
2023318022112200002 1
2.1%
2023318022112200001 1
2.1%
2022318022112200001 1
2.1%
2020318022112200002 1
2.1%
2020318022112200001 1
2.1%
2019318022112200005 1
2.1%
2019318022112200004 1
2.1%
2019318022112200003 1
2.1%

인허가일자
Date

Distinct44
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum1985-12-18 00:00:00
Maximum2023-12-28 00:00:00
2024-05-18T09:54:37.495504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:37.998096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
3
28 
2
11 
1
9 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 28
58.3%
2 11
 
22.9%
1 9
 
18.8%

Length

2024-05-18T09:54:38.374529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:38.734716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 28
58.3%
2 11
 
22.9%
1 9
 
18.8%

영업상태명
Categorical

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
폐업
28 
휴업
11 
영업/정상
9 

Length

Max length5
Median length2
Mean length2.5625
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row휴업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 28
58.3%
휴업 11
 
22.9%
영업/정상 9
 
18.8%

Length

2024-05-18T09:54:39.075902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:39.580435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 28
58.3%
휴업 11
 
22.9%
영업/정상 9
 
18.8%

상세영업상태코드
Categorical

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
2
28 
1
18 
BBBB
 
2

Length

Max length4
Median length1
Mean length1.125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 28
58.3%
1 18
37.5%
BBBB 2
 
4.2%

Length

2024-05-18T09:54:39.913010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:40.230088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 28
58.3%
1 18
37.5%
bbbb 2
 
4.2%

상세영업상태명
Categorical

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size516.0 B
폐업처리
28 
휴업처리
11 
사용중
7 
<NA>
 
2

Length

Max length4
Median length4
Mean length3.8541667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 28
58.3%
휴업처리 11
 
22.9%
사용중 7
 
14.6%
<NA> 2
 
4.2%

Length

2024-05-18T09:54:40.562876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:40.872725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 28
58.3%
휴업처리 11
 
22.9%
사용중 7
 
14.6%
na 2
 
4.2%

폐업일자
Date

MISSING 

Distinct20
Distinct (%)71.4%
Missing20
Missing (%)41.7%
Memory size516.0 B
Minimum2007-03-26 00:00:00
Maximum2023-11-21 00:00:00
2024-05-18T09:54:41.193887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:41.567379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

전화번호
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing42
Missing (%)87.5%
Memory size516.0 B
2024-05-18T09:54:41.929400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters60
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

Unique6 ?
Unique (%)100.0%

Sample

1st row0226353071
2nd row0226790720
3rd row0226326465
4th row0226799855
5th row02 8299202
ValueCountFrequency (%)
0226353071 1
14.3%
0226790720 1
14.3%
0226326465 1
14.3%
0226799855 1
14.3%
02 1
14.3%
8299202 1
14.3%
0220690000 1
14.3%
2024-05-18T09:54:42.663035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16
26.7%
0 15
25.0%
6 7
11.7%
9 6
 
10.0%
5 4
 
6.7%
7 4
 
6.7%
3 3
 
5.0%
8 2
 
3.3%
1 1
 
1.7%
4 1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
98.3%
Space Separator 1
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16
27.1%
0 15
25.4%
6 7
11.9%
9 6
 
10.2%
5 4
 
6.8%
7 4
 
6.8%
3 3
 
5.1%
8 2
 
3.4%
1 1
 
1.7%
4 1
 
1.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 16
26.7%
0 15
25.0%
6 7
11.7%
9 6
 
10.0%
5 4
 
6.7%
7 4
 
6.7%
3 3
 
5.0%
8 2
 
3.3%
1 1
 
1.7%
4 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16
26.7%
0 15
25.0%
6 7
11.7%
9 6
 
10.0%
5 4
 
6.7%
7 4
 
6.7%
3 3
 
5.0%
8 2
 
3.3%
1 1
 
1.7%
4 1
 
1.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

지번주소
Text

MISSING 

Distinct41
Distinct (%)95.3%
Missing5
Missing (%)10.4%
Memory size516.0 B
2024-05-18T09:54:43.154141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length29
Mean length25.488372
Min length19

Characters and Unicode

Total characters1096
Distinct characters95
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)90.7%

Sample

1st row서울특별시 영등포구 양평동5가 109
2nd row서울특별시 영등포구 영등포동7가 94-200번지
3rd row서울특별시 영등포구 영등포동7가 94-200번지
4th row서울특별시 영등포구 대림동 1100-1번지
5th row서울특별시 영등포구 당산동4가 1-3번지
ValueCountFrequency (%)
서울특별시 43
22.1%
영등포구 43
22.1%
여의도동 9
 
4.6%
대림동 8
 
4.1%
영등포동7가 3
 
1.5%
양평동5가 3
 
1.5%
양평동3가 3
 
1.5%
문래동3가 2
 
1.0%
신길동 2
 
1.0%
서울제물포터널2공구 2
 
1.0%
Other values (72) 77
39.5%
2024-05-18T09:54:43.914124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
177
 
16.1%
포 52
 
4.7%
영 50
 
4.6%
등 49
 
4.5%
구 47
 
4.3%
서 46
 
4.2%
울 46
 
4.2%
시 44
 
4.0%
특 43
 
3.9%
별 43
 
3.9%
Other values (85) 499
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 700
63.9%
Space Separator 177
 
16.1%
Decimal Number 165
 
15.1%
Dash Punctuation 31
 
2.8%
Uppercase Letter 8
 
0.7%
Lowercase Letter 6
 
0.5%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 52
 
7.4%
영 50
 
7.1%
등 49
 
7.0%
구 47
 
6.7%
서 46
 
6.6%
울 46
 
6.6%
시 44
 
6.3%
특 43
 
6.1%
별 43
 
6.1%
동 43
 
6.1%
Other values (60) 237
33.9%
Decimal Number
ValueCountFrequency (%)
1 34
20.6%
2 24
14.5%
4 22
13.3%
3 17
10.3%
0 15
9.1%
5 15
9.1%
9 11
 
6.7%
6 9
 
5.5%
8 9
 
5.5%
7 9
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
R 2
25.0%
N 2
25.0%
H 2
25.0%
D 1
12.5%
C 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
m 2
33.3%
p 2
33.3%
a 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3
75.0%
[ 1
 
25.0%
Close Punctuation
ValueCountFrequency (%)
) 3
75.0%
] 1
 
25.0%
Space Separator
ValueCountFrequency (%)
177
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Punctuation
ValueCountFrequency (%)
# 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 700
63.9%
Common 382
34.9%
Latin 14
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 52
 
7.4%
영 50
 
7.1%
등 49
 
7.0%
구 47
 
6.7%
서 46
 
6.6%
울 46
 
6.6%
시 44
 
6.3%
특 43
 
6.1%
별 43
 
6.1%
동 43
 
6.1%
Other values (60) 237
33.9%
Common
ValueCountFrequency (%)
177
46.3%
1 34
 
8.9%
- 31
 
8.1%
2 24
 
6.3%
4 22
 
5.8%
3 17
 
4.5%
0 15
 
3.9%
5 15
 
3.9%
9 11
 
2.9%
6 9
 
2.4%
Other values (7) 27
 
7.1%
Latin
ValueCountFrequency (%)
m 2
14.3%
p 2
14.3%
a 2
14.3%
R 2
14.3%
N 2
14.3%
H 2
14.3%
D 1
7.1%
C 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 700
63.9%
ASCII 396
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
177
44.7%
1 34
 
8.6%
- 31
 
7.8%
2 24
 
6.1%
4 22
 
5.6%
3 17
 
4.3%
0 15
 
3.8%
5 15
 
3.8%
9 11
 
2.8%
6 9
 
2.3%
Other values (15) 41
 
10.4%
Hangul
ValueCountFrequency (%)
포 52
 
7.4%
영 50
 
7.1%
등 49
 
7.0%
구 47
 
6.7%
서 46
 
6.6%
울 46
 
6.6%
시 44
 
6.3%
특 43
 
6.1%
별 43
 
6.1%
동 43
 
6.1%
Other values (60) 237
33.9%

도로명주소
Text

MISSING 

Distinct37
Distinct (%)92.5%
Missing8
Missing (%)16.7%
Memory size516.0 B
2024-05-18T09:54:44.347843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length35.5
Mean length30.975
Min length24

Characters and Unicode

Total characters1239
Distinct characters119
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)85.0%

Sample

1st row서울특별시 영등포구 양평로24길 33 (양평동5가)
2nd row서울특별시 영등포구 버드나루로7길 12 (영등포동7가)
3rd row서울특별시 영등포구 버드나루로7길 12 (영등포동7가)
4th row서울특별시 영등포구 도림천로19길 12-2 (대림동, 1096-1)
5th row서울특별시 영등포구 경인로77가길 7 (문래동2가)
ValueCountFrequency (%)
서울특별시 40
 
17.8%
영등포구 40
 
17.8%
대림동 7
 
3.1%
여의도동 7
 
3.1%
여의대로 5
 
2.2%
영중로 4
 
1.8%
영등포동7가 4
 
1.8%
12 4
 
1.8%
버드나루로7길 3
 
1.3%
양평동3가 3
 
1.3%
Other values (88) 108
48.0%
2024-05-18T09:54:45.226243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
 
14.9%
영 52
 
4.2%
포 48
 
3.9%
등 48
 
3.9%
서 42
 
3.4%
동 42
 
3.4%
시 42
 
3.4%
구 41
 
3.3%
로 41
 
3.3%
) 41
 
3.3%
Other values (109) 657
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 790
63.8%
Space Separator 185
 
14.9%
Decimal Number 152
 
12.3%
Close Punctuation 42
 
3.4%
Open Punctuation 42
 
3.4%
Other Punctuation 17
 
1.4%
Uppercase Letter 4
 
0.3%
Lowercase Letter 4
 
0.3%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 52
 
6.6%
포 48
 
6.1%
등 48
 
6.1%
서 42
 
5.3%
동 42
 
5.3%
시 42
 
5.3%
구 41
 
5.2%
로 41
 
5.2%
별 40
 
5.1%
특 40
 
5.1%
Other values (85) 354
44.8%
Decimal Number
ValueCountFrequency (%)
1 31
20.4%
2 26
17.1%
0 17
11.2%
3 16
10.5%
6 15
9.9%
7 14
9.2%
5 10
 
6.6%
4 9
 
5.9%
9 8
 
5.3%
8 6
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
a 1
25.0%
r 1
25.0%
c 1
25.0%
p 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 41
97.6%
] 1
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 41
97.6%
[ 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 16
94.1%
# 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
N 2
50.0%
H 2
50.0%
Space Separator
ValueCountFrequency (%)
185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 790
63.8%
Common 441
35.6%
Latin 8
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 52
 
6.6%
포 48
 
6.1%
등 48
 
6.1%
서 42
 
5.3%
동 42
 
5.3%
시 42
 
5.3%
구 41
 
5.2%
로 41
 
5.2%
별 40
 
5.1%
특 40
 
5.1%
Other values (85) 354
44.8%
Common
ValueCountFrequency (%)
185
42.0%
) 41
 
9.3%
( 41
 
9.3%
1 31
 
7.0%
2 26
 
5.9%
0 17
 
3.9%
, 16
 
3.6%
3 16
 
3.6%
6 15
 
3.4%
7 14
 
3.2%
Other values (8) 39
 
8.8%
Latin
ValueCountFrequency (%)
N 2
25.0%
H 2
25.0%
a 1
12.5%
r 1
12.5%
c 1
12.5%
p 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 790
63.8%
ASCII 449
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
185
41.2%
) 41
 
9.1%
( 41
 
9.1%
1 31
 
6.9%
2 26
 
5.8%
0 17
 
3.8%
, 16
 
3.6%
3 16
 
3.6%
6 15
 
3.3%
7 14
 
3.1%
Other values (14) 47
 
10.5%
Hangul
ValueCountFrequency (%)
영 52
 
6.6%
포 48
 
6.1%
등 48
 
6.1%
서 42
 
5.3%
동 42
 
5.3%
시 42
 
5.3%
구 41
 
5.2%
로 41
 
5.2%
별 40
 
5.1%
특 40
 
5.1%
Other values (85) 354
44.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)94.1%
Missing31
Missing (%)64.6%
Infinite0
Infinite (%)0.0%
Mean15714.235
Minimum7200
Maximum150096
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-18T09:54:45.581544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7200
5-th percentile7237.6
Q17282
median7324
Q37345
95-th percentile35971.2
Maximum150096
Range142896
Interquartile range (IQR)63

Descriptive statistics

Standard deviation34629.433
Coefficient of variation (CV)2.2036982
Kurtosis16.999895
Mean15714.235
Median Absolute Deviation (MAD)36
Skewness4.1230876
Sum267142
Variance1.1991976 × 109
MonotonicityNot monotonic
2024-05-18T09:54:45.930551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
7325 2
 
4.2%
7299 1
 
2.1%
7301 1
 
2.1%
7247 1
 
2.1%
7272 1
 
2.1%
7281 1
 
2.1%
7308 1
 
2.1%
7335 1
 
2.1%
7440 1
 
2.1%
150096 1
 
2.1%
Other values (6) 6
 
12.5%
(Missing) 31
64.6%
ValueCountFrequency (%)
7200 1
2.1%
7247 1
2.1%
7272 1
2.1%
7281 1
2.1%
7282 1
2.1%
7299 1
2.1%
7301 1
2.1%
7308 1
2.1%
7324 1
2.1%
7325 2
4.2%
ValueCountFrequency (%)
150096 1
2.1%
7440 1
2.1%
7402 1
2.1%
7360 1
2.1%
7345 1
2.1%
7335 1
2.1%
7325 2
4.2%
7324 1
2.1%
7308 1
2.1%
7301 1
2.1%

사업장명
Text

Distinct44
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-05-18T09:54:46.471187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length18.5
Mean length10.520833
Min length5

Characters and Unicode

Total characters505
Distinct characters139
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

Unique41 ?
Unique (%)85.4%

Sample

1st row롯데칠성음료(주)정비공장
2nd row한강성심병원
3rd row한강성심병원
4th row현대직업훈련원
5th row대한통운(주)서울지점
ValueCountFrequency (%)
광혁건설(주)[서울제물포터널2공구 3
 
5.6%
주식회사 2
 
3.7%
주)대련건설 2
 
3.7%
한강성심병원 2
 
3.7%
한강성심병원[(학)일송학원 1
 
1.9%
주)평화토공씨앤씨 1
 
1.9%
주)신한에스엔지 1
 
1.9%
제이랜드건설 1
 
1.9%
주)강구토건 1
 
1.9%
강산건설(주 1
 
1.9%
Other values (39) 39
72.2%
2024-05-18T09:54:47.220239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 27
 
5.3%
( 26
 
5.1%
) 26
 
5.1%
원 21
 
4.2%
병 17
 
3.4%
공 14
 
2.8%
성 14
 
2.8%
건 13
 
2.6%
설 13
 
2.6%
서 12
 
2.4%
Other values (129) 322
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 428
84.8%
Open Punctuation 32
 
6.3%
Close Punctuation 32
 
6.3%
Decimal Number 7
 
1.4%
Space Separator 6
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 27
 
6.3%
원 21
 
4.9%
병 17
 
4.0%
공 14
 
3.3%
성 14
 
3.3%
건 13
 
3.0%
설 13
 
3.0%
서 12
 
2.8%
울 11
 
2.6%
대 11
 
2.6%
Other values (121) 275
64.3%
Decimal Number
ValueCountFrequency (%)
2 5
71.4%
1 1
 
14.3%
5 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 26
81.2%
[ 6
 
18.8%
Close Punctuation
ValueCountFrequency (%)
) 26
81.2%
] 6
 
18.8%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 428
84.8%
Common 77
 
15.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 27
 
6.3%
원 21
 
4.9%
병 17
 
4.0%
공 14
 
3.3%
성 14
 
3.3%
건 13
 
3.0%
설 13
 
3.0%
서 12
 
2.8%
울 11
 
2.6%
대 11
 
2.6%
Other values (121) 275
64.3%
Common
ValueCountFrequency (%)
( 26
33.8%
) 26
33.8%
] 6
 
7.8%
6
 
7.8%
[ 6
 
7.8%
2 5
 
6.5%
1 1
 
1.3%
5 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 428
84.8%
ASCII 77
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 27
 
6.3%
원 21
 
4.9%
병 17
 
4.0%
공 14
 
3.3%
성 14
 
3.3%
건 13
 
3.0%
설 13
 
3.0%
서 12
 
2.8%
울 11
 
2.6%
대 11
 
2.6%
Other values (121) 275
64.3%
ASCII
ValueCountFrequency (%)
( 26
33.8%
) 26
33.8%
] 6
 
7.8%
6
 
7.8%
[ 6
 
7.8%
2 5
 
6.5%
1 1
 
1.3%
5 1
 
1.3%

최종수정일자
Date

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum2013-03-05 13:28:39
Maximum2024-01-02 10:48:36
2024-05-18T09:54:47.558952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:54:48.035438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
U
35 
I
13 

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 (%)
U 35
72.9%
I 13
 
27.1%

Length

2024-05-18T09:54:48.443805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:54:48.736082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 35
72.9%
i 13
 
27.1%

데이터갱신일자
Categorical

Distinct22
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Memory size516.0 B
2018-08-31 23:59:59.0
10 
2019-02-15 02:40:00.0
8 
2022-12-03 22:01:00.0
6 
2021-04-01 02:40:00.0
3 
2020-01-16 02:40:00.0
3 
Other values (17)
18 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique16 ?
Unique (%)33.3%

Sample

1st row2022-12-03 22:03:00.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 10
20.8%
2019-02-15 02:40:00.0 8
16.7%
2022-12-03 22:01:00.0 6
12.5%
2021-04-01 02:40:00.0 3
 
6.2%
2020-01-16 02:40:00.0 3
 
6.2%
2022-01-15 02:40:00.0 2
 
4.2%
2023-12-01 00:04:00.0 1
 
2.1%
2019-05-26 02:40:00.0 1
 
2.1%
2022-10-31 23:01:00.0 1
 
2.1%
2018-10-12 23:59:59.0 1
 
2.1%
Other values (12) 12
25.0%

Length

2024-05-18T09:54:49.052955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02:40:00.0 18
18.8%
23:59:59.0 11
11.5%
2018-08-31 10
 
10.4%
2019-02-15 8
 
8.3%
2022-12-03 7
 
7.3%
22:01:00.0 6
 
6.2%
22:04:00.0 3
 
3.1%
2021-04-01 3
 
3.1%
2020-01-16 3
 
3.1%
2022-01-15 2
 
2.1%
Other values (21) 25
26.0%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)86.7%
Missing3
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean191572.11
Minimum189804.38
Maximum194324.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-18T09:54:49.271667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189804.38
5-th percentile189889.73
Q1190450.21
median191524.69
Q3192946.28
95-th percentile193592
Maximum194324.4
Range4520.0188
Interquartile range (IQR)2496.0711

Descriptive statistics

Standard deviation1292.623
Coefficient of variation (CV)0.0067474488
Kurtosis-1.032345
Mean191572.11
Median Absolute Deviation (MAD)1198.8436
Skewness0.42972026
Sum8620744.8
Variance1670874.2
MonotonicityNot monotonic
2024-05-18T09:54:49.550365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
193592.000380036 3
 
6.2%
191948.638351124 3
 
6.2%
193155.533871263 2
 
4.2%
193034.345962851 2
 
4.2%
190450.209041227 1
 
2.1%
191722.009257399 1
 
2.1%
189814.860666388 1
 
2.1%
191029.590652458 1
 
2.1%
193753.311604119 1
 
2.1%
194324.398950764 1
 
2.1%
Other values (29) 29
60.4%
(Missing) 3
 
6.2%
ValueCountFrequency (%)
189804.380187717 1
2.1%
189814.860666388 1
2.1%
189838.48515188 1
2.1%
190094.718810574 1
2.1%
190099.695152217 1
2.1%
190112.43851718 1
2.1%
190209.933640913 1
2.1%
190222.065574534 1
2.1%
190224.595403248 1
2.1%
190246.487616802 1
2.1%
ValueCountFrequency (%)
194324.398950764 1
 
2.1%
193753.311604119 1
 
2.1%
193592.000380036 3
6.2%
193342.841089002 1
 
2.1%
193155.533871263 2
4.2%
193078.153751051 1
 
2.1%
193034.345962851 2
4.2%
192946.280189392 1
 
2.1%
192318.359252119 1
 
2.1%
191948.638351124 3
6.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)86.7%
Missing3
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean446179.04
Minimum442777.41
Maximum449471.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-18T09:54:49.919868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442777.41
5-th percentile443276.95
Q1445634.9
median446287.56
Q3447092.63
95-th percentile448664.81
Maximum449471.5
Range6694.0851
Interquartile range (IQR)1457.7343

Descriptive statistics

Standard deviation1544.5599
Coefficient of variation (CV)0.003461749
Kurtosis0.037844011
Mean446179.04
Median Absolute Deviation (MAD)753.82586
Skewness-0.42924797
Sum20078057
Variance2385665.1
MonotonicityNot monotonic
2024-05-18T09:54:50.322310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
447092.629432527 3
 
6.2%
446775.416951967 3
 
6.2%
446891.469753398 2
 
4.2%
444796.372057832 2
 
4.2%
445533.73645091 1
 
2.1%
443231.351977519 1
 
2.1%
446221.013701754 1
 
2.1%
444340.940285174 1
 
2.1%
446103.60105115 1
 
2.1%
446208.114169683 1
 
2.1%
Other values (29) 29
60.4%
(Missing) 3
 
6.2%
ValueCountFrequency (%)
442777.411153359 1
2.1%
443157.388663332 1
2.1%
443231.351977519 1
2.1%
443459.357676774 1
2.1%
443528.607969174 1
2.1%
443612.666697479 1
2.1%
444340.940285174 1
2.1%
444795.246645432 1
2.1%
444796.372057832 2
4.2%
445533.73645091 1
2.1%
ValueCountFrequency (%)
449471.496216078 1
 
2.1%
448737.352190615 1
 
2.1%
448717.608427382 1
 
2.1%
448453.616808258 1
 
2.1%
447871.264061327 1
 
2.1%
447415.02687504 1
 
2.1%
447414.684923089 1
 
2.1%
447216.005565246 1
 
2.1%
447096.138540329 1
 
2.1%
447092.629432527 3
6.2%

사용목적
Text

MISSING 

Distinct17
Distinct (%)56.7%
Missing18
Missing (%)37.5%
Memory size516.0 B
2024-05-18T09:54:50.680552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13.5
Mean length4.9333333
Min length3

Characters and Unicode

Total characters148
Distinct characters44
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

Unique12 ?
Unique (%)40.0%

Sample

1st row환자호흡용
2nd row환자호흡용
3rd row실습용
4th row용접, 자동차수리
5th row열처리
ValueCountFrequency (%)
의료용 7
18.4%
용접 4
 
10.5%
절단 3
 
7.9%
공사용 3
 
7.9%
열처리 3
 
7.9%
환자호흡용 2
 
5.3%
배관연결사용 1
 
2.6%
절단작업 1
 
2.6%
용접,절단 1
 
2.6%
작업 1
 
2.6%
Other values (12) 12
31.6%
2024-05-18T09:54:51.184852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 27
18.2%
의 9
 
6.1%
8
 
5.4%
료 8
 
5.4%
단 7
 
4.7%
자 6
 
4.1%
절 6
 
4.1%
접 6
 
4.1%
리 6
 
4.1%
, 5
 
3.4%
Other values (34) 60
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
89.9%
Space Separator 8
 
5.4%
Other Punctuation 5
 
3.4%
Close Punctuation 1
 
0.7%
Open Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 27
20.3%
의 9
 
6.8%
료 8
 
6.0%
단 7
 
5.3%
자 6
 
4.5%
절 6
 
4.5%
접 6
 
4.5%
리 6
 
4.5%
처 5
 
3.8%
열 5
 
3.8%
Other values (30) 48
36.1%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
89.9%
Common 15
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 27
20.3%
의 9
 
6.8%
료 8
 
6.0%
단 7
 
5.3%
자 6
 
4.5%
절 6
 
4.5%
접 6
 
4.5%
리 6
 
4.5%
처 5
 
3.8%
열 5
 
3.8%
Other values (30) 48
36.1%
Common
ValueCountFrequency (%)
8
53.3%
, 5
33.3%
) 1
 
6.7%
( 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133
89.9%
ASCII 15
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 27
20.3%
의 9
 
6.8%
료 8
 
6.0%
단 7
 
5.3%
자 6
 
4.5%
절 6
 
4.5%
접 6
 
4.5%
리 6
 
4.5%
처 5
 
3.8%
열 5
 
3.8%
Other values (30) 48
36.1%
ASCII
ValueCountFrequency (%)
8
53.3%
, 5
33.3%
) 1
 
6.7%
( 1
 
6.7%

사용방법
Text

MISSING 

Distinct26
Distinct (%)86.7%
Missing18
Missing (%)37.5%
Memory size516.0 B
2024-05-18T09:54:51.641144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length96
Median length47.5
Mean length30.433333
Min length1

Characters and Unicode

Total characters913
Distinct characters129
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)80.0%

Sample

1st row의료용
2nd row의료용 특정고압가스 이중등록으로 폐지 표기
3rd row실습용
4th row정비소에서 사용
5th row열처리 -2014.12월 폐업 :화성에서 영업 폐업일자 모름
ValueCountFrequency (%)
13
 
8.7%
특정고압가스 5
 
3.3%
의료용 5
 
3.3%
규모 4
 
2.7%
미만으로 4
 
2.7%
직권취소 4
 
2.7%
처리 4
 
2.7%
신고 4
 
2.7%
48㎥ 3
 
2.0%
4/16 3
 
2.0%
Other values (89) 101
67.3%
2024-05-18T09:54:52.250990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
134
 
14.7%
. 47
 
5.1%
1 46
 
5.0%
0 40
 
4.4%
2 33
 
3.6%
㎥ 22
 
2.4%
용 22
 
2.4%
- 17
 
1.9%
고 17
 
1.9%
9 16
 
1.8%
Other values (119) 519
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 418
45.8%
Decimal Number 211
23.1%
Space Separator 134
 
14.7%
Other Punctuation 66
 
7.2%
Other Symbol 22
 
2.4%
Dash Punctuation 17
 
1.9%
Math Symbol 17
 
1.9%
Lowercase Letter 10
 
1.1%
Close Punctuation 8
 
0.9%
Open Punctuation 8
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 22
 
5.3%
고 17
 
4.1%
소 14
 
3.3%
신 12
 
2.9%
리 12
 
2.9%
장 11
 
2.6%
폐 11
 
2.6%
량 10
 
2.4%
경 10
 
2.4%
산 10
 
2.4%
Other values (93) 289
69.1%
Decimal Number
ValueCountFrequency (%)
1 46
21.8%
0 40
19.0%
2 33
15.6%
9 16
 
7.6%
4 16
 
7.6%
8 15
 
7.1%
5 15
 
7.1%
6 11
 
5.2%
3 10
 
4.7%
7 9
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 47
71.2%
: 8
 
12.1%
, 6
 
9.1%
/ 3
 
4.5%
* 2
 
3.0%
Math Symbol
ValueCountFrequency (%)
→ 12
70.6%
> 3
 
17.6%
= 2
 
11.8%
Lowercase Letter
ValueCountFrequency (%)
g 5
50.0%
k 5
50.0%
Space Separator
ValueCountFrequency (%)
134
100.0%
Other Symbol
ValueCountFrequency (%)
㎥ 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 483
52.9%
Hangul 418
45.8%
Latin 12
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 22
 
5.3%
고 17
 
4.1%
소 14
 
3.3%
신 12
 
2.9%
리 12
 
2.9%
장 11
 
2.6%
폐 11
 
2.6%
량 10
 
2.4%
경 10
 
2.4%
산 10
 
2.4%
Other values (93) 289
69.1%
Common
ValueCountFrequency (%)
134
27.7%
. 47
 
9.7%
1 46
 
9.5%
0 40
 
8.3%
2 33
 
6.8%
㎥ 22
 
4.6%
- 17
 
3.5%
9 16
 
3.3%
4 16
 
3.3%
8 15
 
3.1%
Other values (13) 97
20.1%
Latin
ValueCountFrequency (%)
g 5
41.7%
k 5
41.7%
L 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 461
50.5%
Hangul 418
45.8%
CJK Compat 22
 
2.4%
Arrows 12
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
134
29.1%
. 47
 
10.2%
1 46
 
10.0%
0 40
 
8.7%
2 33
 
7.2%
- 17
 
3.7%
9 16
 
3.5%
4 16
 
3.5%
8 15
 
3.3%
5 15
 
3.3%
Other values (14) 82
17.8%
CJK Compat
ValueCountFrequency (%)
㎥ 22
100.0%
Hangul
ValueCountFrequency (%)
용 22
 
5.3%
고 17
 
4.1%
소 14
 
3.3%
신 12
 
2.9%
리 12
 
2.9%
장 11
 
2.6%
폐 11
 
2.6%
량 10
 
2.4%
경 10
 
2.4%
산 10
 
2.4%
Other values (93) 289
69.1%
Arrows
ValueCountFrequency (%)
→ 12
100.0%

월사용량
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)80.0%
Missing18
Missing (%)37.5%
Infinite0
Infinite (%)0.0%
Mean1878.7367
Minimum0
Maximum7200
Zeros2
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-18T09:54:52.523744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q1205.5
median590
Q33460
95-th percentile6660
Maximum7200
Range7200
Interquartile range (IQR)3254.5

Descriptive statistics

Standard deviation2369.0129
Coefficient of variation (CV)1.2609606
Kurtosis0.0091897161
Mean1878.7367
Median Absolute Deviation (MAD)560.95
Skewness1.1883988
Sum56362.1
Variance5612222.1
MonotonicityNot monotonic
2024-05-18T09:54:52.904052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3460.0 2
 
4.2%
6000.0 2
 
4.2%
7200.0 2
 
4.2%
0.0 2
 
4.2%
900.0 2
 
4.2%
50.0 2
 
4.2%
222.0 1
 
2.1%
8.1 1
 
2.1%
500.0 1
 
2.1%
2000.0 1
 
2.1%
Other values (14) 14
29.2%
(Missing) 18
37.5%
ValueCountFrequency (%)
0.0 2
4.2%
1.0 1
2.1%
8.1 1
2.1%
50.0 2
4.2%
100.0 1
2.1%
200.0 1
2.1%
222.0 1
2.1%
288.0 1
2.1%
300.0 1
2.1%
430.0 1
2.1%
ValueCountFrequency (%)
7200.0 2
4.2%
6000.0 2
4.2%
5000.0 1
2.1%
4650.0 1
2.1%
3500.0 1
2.1%
3460.0 2
4.2%
2000.0 1
2.1%
1500.0 1
2.1%
900.0 2
4.2%
800.0 1
2.1%

수용정원수
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)66.7%
Missing18
Missing (%)37.5%
Infinite0
Infinite (%)0.0%
Mean137.26667
Minimum0
Maximum1800
Zeros2
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-18T09:54:53.261583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q15.25
median17.5
Q366
95-th percentile599.75
Maximum1800
Range1800
Interquartile range (IQR)60.75

Descriptive statistics

Standard deviation352.80863
Coefficient of variation (CV)2.5702425
Kurtosis18.138671
Mean137.26667
Median Absolute Deviation (MAD)16.5
Skewness4.0871086
Sum4118
Variance124473.93
MonotonicityNot monotonic
2024-05-18T09:54:53.627385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
10 4
 
8.3%
1 3
 
6.2%
200 2
 
4.2%
30 2
 
4.2%
6 2
 
4.2%
0 2
 
4.2%
5 2
 
4.2%
1800 1
 
2.1%
54 1
 
2.1%
3 1
 
2.1%
Other values (10) 10
20.8%
(Missing) 18
37.5%
ValueCountFrequency (%)
0 2
4.2%
1 3
6.2%
3 1
 
2.1%
5 2
4.2%
6 2
4.2%
10 4
8.3%
15 1
 
2.1%
20 1
 
2.1%
28 1
 
2.1%
30 2
4.2%
ValueCountFrequency (%)
1800 1
2.1%
800 1
2.1%
355 1
2.1%
250 1
2.1%
200 2
4.2%
100 1
2.1%
68 1
2.1%
60 1
2.1%
54 1
2.1%
40 1
2.1%

시설사용여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사용목적사용방법월사용량수용정원수시설사용여부
0318000019893180190122000011989-08-21<NA>1영업/정상1사용중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 양평동5가 109서울특별시 영등포구 양평로24길 33 (양평동5가)<NA>롯데칠성음료(주)정비공장2023-04-20 16:14:05U2022-12-03 22:03:00.0<NA>190570.251094448717.608427<NA><NA><NA><NA><NA>
13180000199331801901221000019930923<NA>2휴업1휴업처리<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동7가 94-200번지서울특별시 영등포구 버드나루로7길 12 (영등포동7가)<NA>한강성심병원2014-08-29 14:47:50I2018-08-31 23:59:59.0<NA>191948.638351446775.416952환자호흡용의료용0.00<NA>
23180000199331801901221111119930923<NA>3폐업2폐업처리20170901<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동7가 94-200번지서울특별시 영등포구 버드나루로7길 12 (영등포동7가)<NA>한강성심병원2017-09-01 15:25:03I2018-08-31 23:59:59.0<NA>191948.638351446775.416952환자호흡용의료용 특정고압가스 이중등록으로 폐지 표기0.00<NA>
33180000199331802211220000119931221<NA>3폐업2폐업처리20170901<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 1100-1번지서울특별시 영등포구 도림천로19길 12-2 (대림동, 1096-1)<NA>현대직업훈련원2017-09-01 15:23:31I2018-08-31 23:59:59.0<NA>191179.991348442777.411153실습용실습용1.01<NA>
43180000200131800760270319319851218<NA>3폐업2폐업처리20070326<NA><NA><NA>0226353071<NA><NA>서울특별시 영등포구 당산동4가 1-3번지<NA><NA>대한통운(주)서울지점2017-09-01 15:25:53I2018-08-31 23:59:59.0<NA><NA><NA>용접, 자동차수리정비소에서 사용1500.0100<NA>
53180000200331800760270000120030811<NA>3폐업2폐업처리20141231<NA><NA><NA>0226790720<NA><NA>서울특별시 영등포구 문래동2가 29번지서울특별시 영등포구 경인로77가길 7 (문래동2가)<NA>대한진공열처리2018-01-02 13:24:01I2018-08-31 23:59:59.0<NA>190450.209041445533.736451열처리열처리 -2014.12월 폐업 :화성에서 영업 폐업일자 모름100.03<NA>
63180000200331800760270000220031106<NA>3폐업2폐업처리20171114<NA><NA><NA>0226326465<NA><NA>서울특별시 영등포구 양평동2가 33-40번지서울특별시 영등포구 선유서로 99 (양평동2가)<NA>대상진공열처리2018-01-02 21:23:35I2018-08-31 23:59:59.0<NA>189838.485152446938.018596열처리열처리 -2017.11.14 사업장이전 폐업50.05<NA>
73180000200431800760270000120040721<NA>2휴업1휴업처리<NA><NA><NA><NA>0226799855<NA><NA>서울특별시 영등포구 문래동4가 47-8번지서울특별시 영등포구 도림로141길 34 (문래동4가)<NA>케이디시스템2019-05-24 15:27:32U2019-05-26 02:40:00.0<NA>190246.487617445638.965437열처리2015.5.26 상호및 대표자변경 광덕열처리, 이용익->케이디시스템,이준연 2019.5.21 저장량 변경(200kg -> 115kg) 심성은사장()200.01<NA>
83180000200531800760270000120050222<NA>2휴업1휴업처리<NA><NA><NA><NA>02 8299202<NA><NA>서울특별시 영등포구 대림동 978-13번지서울특별시 영등포구 시흥대로 657 (대림동)<NA>대림성모병원2019-02-13 09:38:49U2019-02-15 02:40:00.0<NA>191713.448635443157.388663의료용의료용5000.01800<NA>
93180000200631800760270000120060207<NA>2휴업1휴업처리<NA><NA><NA><NA>0220690000<NA><NA>서울특별시 영등포구 영등포동8가 50-1번지서울특별시 영등포구 영중로 122 (영등포동8가)<NA>마리아성모요양병원2018-04-17 09:43:19I2018-08-31 23:59:59.0<NA>191614.004748447216.005565의료용(환자호흡용)-배관으로공급 -2018.4.17.산소 30㎥ 저장량증설 (상호변경:마리아성모병원→마리아성모요 양병원)3460.0200<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사용목적사용방법월사용량수용정원수시설사용여부
383180000201931802211220000320190604<NA>1영업/정상BBBB<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동3가 54-54번지서울특별시 영등포구 경인로 767 (문래동3가)7299서울센트럴요양병원2019-06-04 17:02:11I2019-06-06 02:21:04.0<NA>190968.870785445750.399306의료용용기3460.0355<NA>
39318000020193180221122000042019-08-12<NA>3폐업2폐업처리2019-11-01<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 양평동5가 64-1 (선유도역 1번 출구)<NA><NA>선일이씨티 주식회사2023-04-19 11:26:57U2022-12-03 22:01:00.0<NA>190530.353487448453.616808<NA><NA><NA><NA><NA>
403180000201931802211220000520191112<NA>3폐업2폐업처리20220923<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 신길동 1375-1<NA><NA>(주)대련건설2022-12-22 13:48:59U2021-11-01 22:04:00.0<NA>193342.841089445634.895091<NA><NA><NA><NA><NA>
41318000020203180221122000012020-11-02<NA>3폐업2폐업처리2022-12-23<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동1가 84 외9필지서울특별시 영등포구 경인로114길 10 (영등포동1가)7308대명건설주택2023-04-19 14:34:36U2022-12-03 22:01:00.0<NA>192318.359252446239.636946<NA><NA><NA><NA><NA>
423180000202031802211220000220201223<NA>2휴업1휴업처리<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동6가 2-1서울특별시 영등포구 선유로 51, 파인그라드빌딩 (문래동6가)7281서울삼성요양병원2021-05-27 09:36:08U2021-05-29 02:40:00.0<NA>190094.718811446267.346676의료용.8.1250<NA>
43318000020223180221122000012022-09-21<NA>3폐업2폐업처리2023-11-21<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 양평동1가 118서울특별시 영등포구 선유로 109 (양평동1가)7272(주)평화토공씨앤씨2023-11-21 16:39:05U2022-10-31 22:03:00.0<NA>190209.933641446851.990579<NA><NA><NA><NA><NA>
44318000020233180221122000012023-02-06<NA>1영업/정상1사용중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동7가 94-200 한강성심병원서울특별시 영등포구 버드나루로7길 12, 한강성심병원 (영등포동7가)7247한강성심병원[(학)일송학원]2023-06-22 10:39:30U2022-12-05 22:04:00.0<NA>191948.638351446775.416952<NA><NA><NA><NA><NA>
45318000020233180221122000022023-05-24<NA>1영업/정상1사용중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동4가 53-3 영중로서울특별시 영등포구 영중로 21-2, 영중로 거리가게 (영등포동4가)7301제이랜드건설 주식회사2023-07-25 14:02:55U2022-12-06 22:07:00.0<NA>191524.693003446287.562306<NA><NA><NA><NA><NA>
46318000020233180221122000032023-12-18<NA>1영업/정상BBBB<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 23-4 NH투자증권빌딩서울특별시 영등포구 여의대로 60, NH투자증권빌딩 (여의도동)7325(주)신한에스엔지2023-12-18 17:36:12I2022-11-01 22:00:00.0<NA>193155.533871446891.469753<NA><NA><NA><NA><NA>
47318000020233180221122000042023-12-28<NA>1영업/정상1사용중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 23-4 NH투자증권빌딩서울특별시 영등포구 여의대로 60, NH투자증권빌딩 (여의도동)7325성도건설산업(주)2023-12-28 14:49:43I2022-11-01 21:00:00.0<NA>193155.533871446891.469753<NA><NA><NA><NA><NA>