Overview

Dataset statistics

Number of variables27
Number of observations66
Missing cells460
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.8 KiB
Average record size in memory230.0 B

Variable types

Categorical12
Numeric3
DateTime5
Unsupported4
Text3

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),제조구분명,사업장부지용도구분명
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-19007/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
재개업일자 is highly imbalanced (88.7%)Imbalance
도로명우편번호 is highly imbalanced (78.2%)Imbalance
업태구분명 is highly imbalanced (63.4%)Imbalance
인허가취소일자 has 66 (100.0%) missing valuesMissing
폐업일자 has 23 (34.8%) missing valuesMissing
휴업시작일자 has 61 (92.4%) missing valuesMissing
휴업종료일자 has 61 (92.4%) missing valuesMissing
전화번호 has 66 (100.0%) missing valuesMissing
소재지면적 has 66 (100.0%) missing valuesMissing
소재지우편번호 has 66 (100.0%) missing valuesMissing
지번주소 has 1 (1.5%) missing valuesMissing
도로명주소 has 38 (57.6%) missing valuesMissing
좌표정보(X) has 6 (9.1%) missing valuesMissing
좌표정보(Y) has 6 (9.1%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 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
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

Reproduction

Analysis started2024-05-11 02:15:10.315149
Analysis finished2024-05-11 02:15:11.259959
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
3050000
66 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 66
100.0%

Length

2024-05-11T02:15:11.545883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:11.920942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 66
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0044414 × 1018
Minimum1.989305 × 1018
Maximum2.022305 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-05-11T02:15:12.419104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.989305 × 1018
5-th percentile2.001305 × 1018
Q12.001305 × 1018
median2.001305 × 1018
Q32.006305 × 1018
95-th percentile2.021305 × 1018
Maximum2.022305 × 1018
Range3.300001 × 1016
Interquartile range (IQR)5 × 1015

Descriptive statistics

Standard deviation6.759353 × 1015
Coefficient of variation (CV)0.0033721879
Kurtosis1.5957958
Mean2.0044414 × 1018
Median Absolute Deviation (MAD)92800
Skewness1.3374445
Sum3.1659221 × 1018
Variance4.5688853 × 1031
MonotonicityStrictly increasing
2024-05-11T02:15:13.109937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1989305010002100029 1
 
1.5%
2006305008202100003 1
 
1.5%
2001305008202200033 1
 
1.5%
2001305008202200035 1
 
1.5%
2001305008202200036 1
 
1.5%
2001305008202200037 1
 
1.5%
2001305008202200038 1
 
1.5%
2001305008202200041 1
 
1.5%
2001305008202200042 1
 
1.5%
2001305008202200044 1
 
1.5%
Other values (56) 56
84.8%
ValueCountFrequency (%)
1989305010002100029 1
1.5%
1993305015702100038 1
1.5%
2001305008202100001 1
1.5%
2001305008202100002 1
1.5%
2001305008202100007 1
1.5%
2001305008202100013 1
1.5%
2001305008202100018 1
1.5%
2001305008202100025 1
1.5%
2001305008202100040 1
1.5%
2001305008202100761 1
1.5%
ValueCountFrequency (%)
2022305020302200002 1
1.5%
2022305020302200001 1
1.5%
2022305020302100002 1
1.5%
2022305020302100001 1
1.5%
2018305015702200001 1
1.5%
2017305015702200001 1
1.5%
2015305015702100001 1
1.5%
2014305015702100001 1
1.5%
2013305015702200002 1
1.5%
2013305015702200001 1
1.5%

인허가일자
Date

Distinct62
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size660.0 B
Minimum1973-12-04 00:00:00
Maximum2022-03-16 00:00:00
2024-05-11T02:15:13.722711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:15:14.396876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing66
Missing (%)100.0%
Memory size726.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
3
43 
1
22 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
3 43
65.2%
1 22
33.3%
2 1
 
1.5%

Length

2024-05-11T02:15:14.922893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:15.351235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 43
65.2%
1 22
33.3%
2 1
 
1.5%

영업상태명
Categorical

Distinct3
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
폐업
43 
영업/정상
22 
휴업
 
1

Length

Max length5
Median length2
Mean length3
Min length2

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 43
65.2%
영업/정상 22
33.3%
휴업 1
 
1.5%

Length

2024-05-11T02:15:15.747859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:16.074900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 43
65.2%
영업/정상 22
33.3%
휴업 1
 
1.5%

상세영업상태코드
Categorical

Distinct3
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
3
43 
1
22 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
3 43
65.2%
1 22
33.3%
2 1
 
1.5%

Length

2024-05-11T02:15:16.394573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:16.731488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 43
65.2%
1 22
33.3%
2 1
 
1.5%

상세영업상태명
Categorical

Distinct3
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
폐업
43 
영업중
22 
휴업
 
1

Length

Max length3
Median length2
Mean length2.3333333
Min length2

Unique

Unique1 ?
Unique (%)1.5%

Sample

1st row폐업
2nd row영업중
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 43
65.2%
영업중 22
33.3%
휴업 1
 
1.5%

Length

2024-05-11T02:15:17.104398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:17.536928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 43
65.2%
영업중 22
33.3%
휴업 1
 
1.5%

폐업일자
Date

MISSING 

Distinct40
Distinct (%)93.0%
Missing23
Missing (%)34.8%
Memory size660.0 B
Minimum2001-04-26 00:00:00
Maximum2023-05-01 00:00:00
2024-05-11T02:15:17.882895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:15:18.369016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

휴업시작일자
Date

MISSING 

Distinct5
Distinct (%)100.0%
Missing61
Missing (%)92.4%
Memory size660.0 B
Minimum2014-01-27 00:00:00
Maximum2023-06-08 00:00:00
2024-05-11T02:15:18.892000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:15:19.273068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

휴업종료일자
Date

MISSING 

Distinct5
Distinct (%)100.0%
Missing61
Missing (%)92.4%
Memory size660.0 B
Minimum2014-12-31 00:00:00
Maximum2024-06-07 00:00:00
2024-05-11T02:15:19.575094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:15:19.949765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
<NA>
65 
20171025
 
1

Length

Max length8
Median length4
Mean length4.0606061
Min length4

Unique

Unique1 ?
Unique (%)1.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 65
98.5%
20171025 1
 
1.5%

Length

2024-05-11T02:15:20.818805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:21.351382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 65
98.5%
20171025 1
 
1.5%

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing66
Missing (%)100.0%
Memory size726.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing66
Missing (%)100.0%
Memory size726.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing66
Missing (%)100.0%
Memory size726.0 B

지번주소
Text

MISSING 

Distinct59
Distinct (%)90.8%
Missing1
Missing (%)1.5%
Memory size660.0 B
2024-05-11T02:15:22.200736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length33
Mean length22.584615
Min length17

Characters and Unicode

Total characters1468
Distinct characters81
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)81.5%

Sample

1st row서울특별시 동대문구 장안동 466-7
2nd row서울특별시 동대문구 장안동 421-1
3rd row서울특별시 동대문구 용두동 104
4th row서울특별시 동대문구 신설동 96-48
5th row서울특별시 동대문구 휘경동 43-12
ValueCountFrequency (%)
서울특별시 65
23.3%
동대문구 65
23.3%
장안동 15
 
5.4%
용두동 8
 
2.9%
신설동 8
 
2.9%
답십리동 7
 
2.5%
제기동 7
 
2.5%
전농동 6
 
2.2%
회기동 5
 
1.8%
1-5 4
 
1.4%
Other values (72) 89
31.9%
2024-05-11T02:15:24.193746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
274
18.7%
동 132
 
9.0%
문 68
 
4.6%
서 67
 
4.6%
대 67
 
4.6%
울 66
 
4.5%
구 65
 
4.4%
시 65
 
4.4%
별 65
 
4.4%
특 65
 
4.4%
Other values (71) 534
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 868
59.1%
Space Separator 274
 
18.7%
Decimal Number 267
 
18.2%
Dash Punctuation 55
 
3.7%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 132
15.2%
문 68
 
7.8%
서 67
 
7.7%
대 67
 
7.7%
울 66
 
7.6%
구 65
 
7.5%
시 65
 
7.5%
별 65
 
7.5%
특 65
 
7.5%
안 15
 
1.7%
Other values (57) 193
22.2%
Decimal Number
ValueCountFrequency (%)
1 50
18.7%
4 40
15.0%
6 35
13.1%
2 27
10.1%
5 25
9.4%
0 24
9.0%
7 22
8.2%
3 18
 
6.7%
8 14
 
5.2%
9 12
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
S 2
50.0%
Space Separator
ValueCountFrequency (%)
274
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 868
59.1%
Common 596
40.6%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 132
15.2%
문 68
 
7.8%
서 67
 
7.7%
대 67
 
7.7%
울 66
 
7.6%
구 65
 
7.5%
시 65
 
7.5%
별 65
 
7.5%
특 65
 
7.5%
안 15
 
1.7%
Other values (57) 193
22.2%
Common
ValueCountFrequency (%)
274
46.0%
- 55
 
9.2%
1 50
 
8.4%
4 40
 
6.7%
6 35
 
5.9%
2 27
 
4.5%
5 25
 
4.2%
0 24
 
4.0%
7 22
 
3.7%
3 18
 
3.0%
Other values (2) 26
 
4.4%
Latin
ValueCountFrequency (%)
K 2
50.0%
S 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 868
59.1%
ASCII 600
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
274
45.7%
- 55
 
9.2%
1 50
 
8.3%
4 40
 
6.7%
6 35
 
5.8%
2 27
 
4.5%
5 25
 
4.2%
0 24
 
4.0%
7 22
 
3.7%
3 18
 
3.0%
Other values (4) 30
 
5.0%
Hangul
ValueCountFrequency (%)
동 132
15.2%
문 68
 
7.8%
서 67
 
7.7%
대 67
 
7.7%
울 66
 
7.6%
구 65
 
7.5%
시 65
 
7.5%
별 65
 
7.5%
특 65
 
7.5%
안 15
 
1.7%
Other values (57) 193
22.2%

도로명주소
Text

MISSING 

Distinct23
Distinct (%)82.1%
Missing38
Missing (%)57.6%
Memory size660.0 B
2024-05-11T02:15:25.014550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length25.357143
Min length22

Characters and Unicode

Total characters710
Distinct characters73
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)64.3%

Sample

1st row서울특별시 동대문구 장한로3길 34 (장안동)
2nd row서울특별시 동대문구 홍릉로 118 (청량리동)
3rd row서울특별시 동대문구 서울시립대로 49-5 (전농동)
4th row서울특별시 동대문구 제기로 82-1 (제기동)
5th row서울특별시 동대문구 경희대로 26 (회기동)
ValueCountFrequency (%)
서울특별시 28
19.7%
동대문구 28
19.7%
천호대로 6
 
4.2%
장안동 5
 
3.5%
제기동 4
 
2.8%
답십리동 3
 
2.1%
용두동 3
 
2.1%
신설동 3
 
2.1%
34 3
 
2.1%
경희대로 3
 
2.1%
Other values (42) 56
39.4%
2024-05-11T02:15:26.227392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
114
 
16.1%
동 57
 
8.0%
대 39
 
5.5%
서 31
 
4.4%
문 30
 
4.2%
울 30
 
4.2%
시 29
 
4.1%
( 28
 
3.9%
특 28
 
3.9%
별 28
 
3.9%
Other values (63) 296
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 458
64.5%
Space Separator 114
 
16.1%
Decimal Number 75
 
10.6%
Open Punctuation 28
 
3.9%
Close Punctuation 28
 
3.9%
Dash Punctuation 5
 
0.7%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 57
12.4%
대 39
 
8.5%
서 31
 
6.8%
문 30
 
6.6%
울 30
 
6.6%
시 29
 
6.3%
특 28
 
6.1%
별 28
 
6.1%
구 28
 
6.1%
로 28
 
6.1%
Other values (48) 130
28.4%
Decimal Number
ValueCountFrequency (%)
2 13
17.3%
1 12
16.0%
3 10
13.3%
4 10
13.3%
8 8
10.7%
9 7
9.3%
5 6
8.0%
6 4
 
5.3%
0 3
 
4.0%
7 2
 
2.7%
Space Separator
ValueCountFrequency (%)
114
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 458
64.5%
Common 252
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 57
12.4%
대 39
 
8.5%
서 31
 
6.8%
문 30
 
6.6%
울 30
 
6.6%
시 29
 
6.3%
특 28
 
6.1%
별 28
 
6.1%
구 28
 
6.1%
로 28
 
6.1%
Other values (48) 130
28.4%
Common
ValueCountFrequency (%)
114
45.2%
( 28
 
11.1%
) 28
 
11.1%
2 13
 
5.2%
1 12
 
4.8%
3 10
 
4.0%
4 10
 
4.0%
8 8
 
3.2%
9 7
 
2.8%
5 6
 
2.4%
Other values (5) 16
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 458
64.5%
ASCII 252
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
45.2%
( 28
 
11.1%
) 28
 
11.1%
2 13
 
5.2%
1 12
 
4.8%
3 10
 
4.0%
4 10
 
4.0%
8 8
 
3.2%
9 7
 
2.8%
5 6
 
2.4%
Other values (5) 16
 
6.3%
Hangul
ValueCountFrequency (%)
동 57
12.4%
대 39
 
8.5%
서 31
 
6.8%
문 30
 
6.6%
울 30
 
6.6%
시 29
 
6.3%
특 28
 
6.1%
별 28
 
6.1%
구 28
 
6.1%
로 28
 
6.1%
Other values (48) 130
28.4%

도로명우편번호
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size660.0 B
<NA>
61 
2635
 
1
2500
 
1
2644
 
1
2603
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique5 ?
Unique (%)7.6%

Sample

1st row<NA>
2nd row2635
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 61
92.4%
2635 1
 
1.5%
2500 1
 
1.5%
2644 1
 
1.5%
2603 1
 
1.5%
2480 1
 
1.5%

Length

2024-05-11T02:15:26.667923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:27.134571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 61
92.4%
2635 1
 
1.5%
2500 1
 
1.5%
2644 1
 
1.5%
2603 1
 
1.5%
2480 1
 
1.5%

사업장명
Text

Distinct60
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size660.0 B
2024-05-11T02:15:27.825976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length7.7424242
Min length4

Characters and Unicode

Total characters511
Distinct characters163
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)83.3%

Sample

1st row국제라이온스클럽
2nd row에스케이텔레콤(주)
3rd row(주)우경알앤씨(R&C)
4th row대상(주)
5th row축산업협동조합중앙회
ValueCountFrequency (%)
경희대학교 3
 
4.1%
도시환경정비사업추진위원회 3
 
4.1%
청량리제4구역 2
 
2.7%
경희의료원 2
 
2.7%
롯데쇼핑(주)롯데슈퍼사업부 2
 
2.7%
효림요양병원 2
 
2.7%
주식회사 2
 
2.7%
성암학원 1
 
1.4%
대흥개발 1
 
1.4%
성북수도사업소 1
 
1.4%
Other values (55) 55
74.3%
2024-05-11T02:15:29.004215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 19
 
3.7%
경 16
 
3.1%
대 16
 
3.1%
업 14
 
2.7%
사 13
 
2.5%
) 12
 
2.3%
( 12
 
2.3%
주 12
 
2.3%
동 11
 
2.2%
회 11
 
2.2%
Other values (153) 375
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 467
91.4%
Close Punctuation 12
 
2.3%
Open Punctuation 12
 
2.3%
Space Separator 8
 
1.6%
Uppercase Letter 8
 
1.6%
Decimal Number 3
 
0.6%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 19
 
4.1%
경 16
 
3.4%
대 16
 
3.4%
업 14
 
3.0%
사 13
 
2.8%
주 12
 
2.6%
동 11
 
2.4%
회 11
 
2.4%
교 9
 
1.9%
시 8
 
1.7%
Other values (141) 338
72.4%
Uppercase Letter
ValueCountFrequency (%)
I 2
25.0%
F 1
12.5%
R 1
12.5%
K 1
12.5%
C 1
12.5%
T 1
12.5%
S 1
12.5%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Decimal Number
ValueCountFrequency (%)
4 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 467
91.4%
Common 36
 
7.0%
Latin 8
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 19
 
4.1%
경 16
 
3.4%
대 16
 
3.4%
업 14
 
3.0%
사 13
 
2.8%
주 12
 
2.6%
동 11
 
2.4%
회 11
 
2.4%
교 9
 
1.9%
시 8
 
1.7%
Other values (141) 338
72.4%
Latin
ValueCountFrequency (%)
I 2
25.0%
F 1
12.5%
R 1
12.5%
K 1
12.5%
C 1
12.5%
T 1
12.5%
S 1
12.5%
Common
ValueCountFrequency (%)
) 12
33.3%
( 12
33.3%
8
22.2%
4 3
 
8.3%
& 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 467
91.4%
ASCII 44
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 19
 
4.1%
경 16
 
3.4%
대 16
 
3.4%
업 14
 
3.0%
사 13
 
2.8%
주 12
 
2.6%
동 11
 
2.4%
회 11
 
2.4%
교 9
 
1.9%
시 8
 
1.7%
Other values (141) 338
72.4%
ASCII
ValueCountFrequency (%)
) 12
27.3%
( 12
27.3%
8
18.2%
4 3
 
6.8%
I 2
 
4.5%
F 1
 
2.3%
R 1
 
2.3%
& 1
 
2.3%
K 1
 
2.3%
C 1
 
2.3%
Other values (2) 2
 
4.5%

최종수정일자
Date

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
Minimum2006-07-03 00:00:00
Maximum2024-01-17 16:43:23
2024-05-11T02:15:29.624458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:15:30.245746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
I
49 
U
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 49
74.2%
U 17
 
25.8%

Length

2024-05-11T02:15:30.714298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:31.192503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 49
74.2%
u 17
 
25.8%

데이터갱신일자
Categorical

Distinct18
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size660.0 B
2018-08-31 23:59:59.0
46 
2021-10-31 23:06:00.0
 
2
2022-12-05 23:00:00.0
 
2
2022-10-31 22:04:00.0
 
2
2021-08-01 02:40:00.0
 
1
Other values (13)
13 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique14 ?
Unique (%)21.2%

Sample

1st row2018-08-31 23:59:59.0
2nd row2019-11-03 00:23:22.0
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 46
69.7%
2021-10-31 23:06:00.0 2
 
3.0%
2022-12-05 23:00:00.0 2
 
3.0%
2022-10-31 22:04:00.0 2
 
3.0%
2021-08-01 02:40:00.0 1
 
1.5%
2022-01-01 02:40:00.0 1
 
1.5%
2021-06-02 02:40:00.0 1
 
1.5%
2019-05-23 02:40:00.0 1
 
1.5%
2020-09-12 02:40:00.0 1
 
1.5%
2019-08-11 02:40:00.0 1
 
1.5%
Other values (8) 8
 
12.1%

Length

2024-05-11T02:15:31.731475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 46
34.8%
23:59:59.0 46
34.8%
02:40:00.0 11
 
8.3%
2021-10-31 2
 
1.5%
23:06:00.0 2
 
1.5%
2022-12-05 2
 
1.5%
23:00:00.0 2
 
1.5%
2022-10-31 2
 
1.5%
22:04:00.0 2
 
1.5%
2020-10-16 1
 
0.8%
Other values (16) 16
 
12.1%

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
제조
59 
판매
 
5
저장소
 
2

Length

Max length3
Median length2
Mean length2.030303
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제조 59
89.4%
판매 5
 
7.6%
저장소 2
 
3.0%

Length

2024-05-11T02:15:32.095497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:32.487998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조 59
89.4%
판매 5
 
7.6%
저장소 2
 
3.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)81.7%
Missing6
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean204271.81
Minimum202023.92
Maximum206311.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-05-11T02:15:32.906206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202023.92
5-th percentile202093.31
Q1203146.52
median204450.89
Q3205598.93
95-th percentile206086.26
Maximum206311.05
Range4287.1317
Interquartile range (IQR)2452.4054

Descriptive statistics

Standard deviation1365.1054
Coefficient of variation (CV)0.0066827888
Kurtosis-1.2686596
Mean204271.81
Median Absolute Deviation (MAD)1216.8205
Skewness-0.20692505
Sum12256309
Variance1863512.7
MonotonicityNot monotonic
2024-05-11T02:15:33.543027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
204469.209049094 4
 
6.1%
203917.462724049 3
 
4.5%
203658.735555875 2
 
3.0%
205271.704936121 2
 
3.0%
204432.565250342 2
 
3.0%
205598.92518598 2
 
3.0%
206084.625088881 2
 
3.0%
202023.921749857 2
 
3.0%
204082.174931922 1
 
1.5%
202175.202011346 1
 
1.5%
Other values (39) 39
59.1%
(Missing) 6
 
9.1%
ValueCountFrequency (%)
202023.921749857 2
3.0%
202081.864808843 1
1.5%
202093.908184725 1
1.5%
202144.279993775 1
1.5%
202175.202011346 1
1.5%
202196.00674169 1
1.5%
202232.554341254 1
1.5%
202421.576749824 1
1.5%
202474.62650398 1
1.5%
202716.197281758 1
1.5%
ValueCountFrequency (%)
206311.053490627 1
1.5%
206199.953197537 1
1.5%
206117.295011037 1
1.5%
206084.625088881 2
3.0%
205939.305204176 1
1.5%
205933.979145565 1
1.5%
205899.907023899 1
1.5%
205865.688377736 1
1.5%
205835.505341825 1
1.5%
205790.199450207 1
1.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)80.0%
Missing6
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean452676.12
Minimum450987.05
Maximum455209.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-05-11T02:15:34.010099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450987.05
5-th percentile451053
Q1451796.13
median452589.17
Q3453021.57
95-th percentile454934.05
Maximum455209.6
Range4222.555
Interquartile range (IQR)1225.4429

Descriptive statistics

Standard deviation1220.4101
Coefficient of variation (CV)0.0026959895
Kurtosis-0.54604367
Mean452676.12
Median Absolute Deviation (MAD)770.45381
Skewness0.58164975
Sum27160567
Variance1489400.7
MonotonicityNot monotonic
2024-05-11T02:15:34.578541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
454934.047367752 5
 
7.6%
452951.998520792 3
 
4.5%
453805.545869663 2
 
3.0%
452706.897879436 2
 
3.0%
451818.712665463 2
 
3.0%
451321.232059013 2
 
3.0%
450987.048392613 2
 
3.0%
452387.764894439 2
 
3.0%
452632.205933838 1
 
1.5%
452938.652905317 1
 
1.5%
Other values (38) 38
57.6%
(Missing) 6
 
9.1%
ValueCountFrequency (%)
450987.048392613 2
3.0%
451038.454241239 1
1.5%
451053.76563095 1
1.5%
451103.146980087 1
1.5%
451110.245309908 1
1.5%
451135.637561446 1
1.5%
451170.628868201 1
1.5%
451306.66042741 1
1.5%
451321.232059013 2
3.0%
451568.721360715 1
1.5%
ValueCountFrequency (%)
455209.603361692 1
 
1.5%
455014.295643133 1
 
1.5%
454934.047367752 5
7.6%
454716.730654251 1
 
1.5%
454246.192680027 1
 
1.5%
454116.153861143 1
 
1.5%
454114.388026134 1
 
1.5%
453805.545869663 2
 
3.0%
453693.437787011 1
 
1.5%
453230.287283096 1
 
1.5%

제조구분명
Categorical

Distinct3
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
냉동
52 
<NA>
8 
일반
6 

Length

Max length4
Median length2
Mean length2.2424242
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row냉동
2nd row<NA>
3rd row냉동
4th row냉동
5th row냉동

Common Values

ValueCountFrequency (%)
냉동 52
78.8%
<NA> 8
 
12.1%
일반 6
 
9.1%

Length

2024-05-11T02:15:35.205556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:35.723631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
냉동 52
78.8%
na 8
 
12.1%
일반 6
 
9.1%

사업장부지용도구분명
Categorical

Distinct10
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size660.0 B
주거용
35 
<NA>
11 
업무용
5 
상업나지
5 
상업.업무용
 
3
Other values (5)
7 

Length

Max length6
Median length3
Mean length3.4393939
Min length2

Unique

Unique3 ?
Unique (%)4.5%

Sample

1st row상업.업무용
2nd row<NA>
3rd row상업.업무용
4th row업무용
5th row주거용

Common Values

ValueCountFrequency (%)
주거용 35
53.0%
<NA> 11
 
16.7%
업무용 5
 
7.6%
상업나지 5
 
7.6%
상업.업무용 3
 
4.5%
아파트 2
 
3.0%
지정되지않음 2
 
3.0%
다세대 1
 
1.5%
연립 1
 
1.5%
기타 1
 
1.5%

Length

2024-05-11T02:15:36.173144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:15:36.660630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주거용 35
53.0%
na 11
 
16.7%
업무용 5
 
7.6%
상업나지 5
 
7.6%
상업.업무용 3
 
4.5%
아파트 2
 
3.0%
지정되지않음 2
 
3.0%
다세대 1
 
1.5%
연립 1
 
1.5%
기타 1
 
1.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)제조구분명사업장부지용도구분명
03050000198930501000210002920090601<NA>3폐업3폐업20090601<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 466-7<NA><NA>국제라이온스클럽2009-06-01 16:26:10I2018-08-31 23:59:59.0제조206084.625089450987.048393냉동상업.업무용
13050000199330501570210003820191101<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 421-1서울특별시 동대문구 장한로3길 34 (장안동)2635에스케이텔레콤(주)2019-11-01 11:34:31I2019-11-03 00:23:22.0제조205598.925186451321.232059<NA><NA>
23050000200130500820210000120110209<NA>3폐업3폐업20110315<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 104<NA><NA>(주)우경알앤씨(R&C)2011-03-17 11:20:28I2018-08-31 23:59:59.0제조<NA><NA>냉동상업.업무용
33050000200130500820210000220100315<NA>3폐업3폐업20100315<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 신설동 96-48<NA><NA>대상(주)2010-03-15 14:38:19I2018-08-31 23:59:59.0제조202232.554341452397.732552냉동업무용
43050000200130500820210000719791115<NA>3폐업3폐업20021231<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 휘경동 43-12<NA><NA>축산업협동조합중앙회2011-12-14 12:54:11I2018-08-31 23:59:59.0제조<NA><NA>냉동주거용
53050000200130500820210001319840818<NA>3폐업3폐업20031105<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 464-8<NA><NA>대흥기업(주)2011-12-14 11:09:18I2018-08-31 23:59:59.0제조205790.19945451038.454241냉동주거용
63050000200130500820210001819850522<NA>3폐업3폐업20140508<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 366-7 경남관광호텔<NA><NA>경남관광호텔2016-02-26 13:31:21I2018-08-31 23:59:59.0제조206199.953198451997.93485냉동주거용
73050000200130500820210002519861008<NA>3폐업3폐업20130715<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 신설동 117-6<NA><NA>경해실업(주)2016-02-26 13:32:12I2018-08-31 23:59:59.0제조202023.92175452387.764894냉동주거용
83050000200130500820210004019951009<NA>3폐업3폐업201501052014012720141231<NA><NA><NA><NA>서울특별시 동대문구 청량리동 206-46서울특별시 동대문구 홍릉로 118 (청량리동)<NA>수림문화재단2016-08-23 11:03:03I2018-08-31 23:59:59.0제조203712.345426454246.19268냉동주거용
93050000200130500820210076119760605<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 643-60서울특별시 동대문구 서울시립대로 49-5 (전농동)<NA>대동성동산소2021-12-30 15:49:29U2022-01-01 02:40:00.0판매204082.174932452632.205934일반상업나지
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)제조구분명사업장부지용도구분명
563050000201330501570220000120130314<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 경희대로 26 (회기동)<NA>경희대학교2014-09-15 10:06:56I2018-08-31 23:59:59.0제조204892.987222454934.047368냉동지정되지않음
573050000201330501570220000220130717<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 신설동 117-6서울특별시 동대문구 난계로 250 (신설동)<NA>경해실업2013-07-17 10:01:15I2018-08-31 23:59:59.0제조202023.92175452387.764894냉동<NA>
583050000201430501570210000120140623<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 회기동 1-5서울특별시 동대문구 경희대로 23 (회기동)<NA>경희의료원2020-10-14 17:40:47U2020-10-16 02:40:00.0제조204469.209049454934.047368냉동업무용
59305000020153050157021000012015-11-04<NA>2휴업2휴업<NA>2023-06-082024-06-07<NA><NA><NA><NA>서울특별시 동대문구 휘경동 29-1 삼육서울병원서울특별시 동대문구 망우로 82, 삼육서울병원 (휘경동)2500삼육서울병원2023-06-08 10:38:07U2022-12-05 23:00:00.0제조205622.068464454114.388026<NA><NA>
603050000201730501570220000120170821<NA>1영업/정상1영업중<NA><NA><NA>20171025<NA><NA><NA>서울특별시 동대문구 장안동 434 동대문소방서서울특별시 동대문구 장한로 34, 동대문소방서 (장안동)2644동대문소방서2019-05-24 11:19:24U2019-05-26 02:40:00.0제조205835.505342451306.660427일반지정되지않음
613050000201830501570220000120180727<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 답십리동 497-66번지서울특별시 동대문구 천호대로 259-1 (답십리동)2603효림요양병원2018-07-27 15:21:30I2018-08-31 23:59:59.0제조204432.56525451818.712665냉동<NA>
62305000020223050203021000012022-03-16<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 620-47<NA><NA>청량리제4구역 도시환경정비사업추진위원회2023-11-22 17:10:01U2022-10-31 22:04:00.0제조203917.462724452951.998521<NA><NA>
633050000202230502030210000219830224<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 제기동 285-5서울특별시 동대문구 제기로 82-1 (제기동)2480홍릉가스상사2022-11-14 17:02:56I2021-10-31 23:06:00.0판매203658.735556453805.54587<NA><NA>
643050000202230502030220000120220311<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 620-47<NA><NA>청량리제4구역 도시환경정비사업추진위원회2022-03-11 15:27:01I2022-03-13 00:22:53.0제조203917.462724452951.998521냉동<NA>
65305000020223050203022000022022-03-11<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 620-47<NA><NA>청량리 제4구역 도시환경정비사업추진위원회2023-11-22 17:10:37U2022-10-31 22:04:00.0제조203917.462724452951.998521<NA><NA>