Overview

Dataset statistics

Number of variables33
Number of observations74
Missing cells747
Missing cells (%)30.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.2 KiB
Average record size in memory279.8 B

Variable types

Categorical9
Numeric6
DateTime5
Unsupported4
Text9

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),환경업무구분명,업종구분명,종별명,주생산품명,배출시설조업시간,배출시설연간가동일수,방지시설조업시간,방지시설연간가동일수
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-19357/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 74 (100.0%) missing valuesMissing
폐업일자 has 40 (54.1%) missing valuesMissing
휴업시작일자 has 72 (97.3%) missing valuesMissing
휴업종료일자 has 74 (100.0%) missing valuesMissing
재개업일자 has 74 (100.0%) missing valuesMissing
전화번호 has 19 (25.7%) missing valuesMissing
소재지면적 has 74 (100.0%) missing valuesMissing
소재지우편번호 has 58 (78.4%) missing valuesMissing
도로명주소 has 17 (23.0%) missing valuesMissing
도로명우편번호 has 17 (23.0%) missing valuesMissing
업태구분명 has 9 (12.2%) missing valuesMissing
좌표정보(X) has 8 (10.8%) missing valuesMissing
좌표정보(Y) has 8 (10.8%) missing valuesMissing
업종구분명 has 32 (43.2%) missing valuesMissing
주생산품명 has 72 (97.3%) missing valuesMissing
배출시설조업시간 has 29 (39.2%) missing valuesMissing
배출시설연간가동일수 has 27 (36.5%) missing valuesMissing
방지시설조업시간 has 43 (58.1%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 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
배출시설조업시간 has 5 (6.8%) zerosZeros
배출시설연간가동일수 has 7 (9.5%) zerosZeros
방지시설조업시간 has 6 (8.1%) zerosZeros

Reproduction

Analysis started2024-04-17 22:14:25.853710
Analysis finished2024-04-17 22:14:26.344144
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
3050000
74 

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 74
100.0%

Length

2024-04-18T07:14:26.404738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:26.505839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 74
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0500002 × 1017
Minimum3.0500002 × 1017
Maximum3.0500002 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-18T07:14:26.590970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0500002 × 1017
5-th percentile3.0500002 × 1017
Q13.0500002 × 1017
median3.0500002 × 1017
Q33.0500002 × 1017
95-th percentile3.0500002 × 1017
Maximum3.0500002 × 1017
Range3099998
Interquartile range (IQR)1774976

Descriptive statistics

Standard deviation961720.55
Coefficient of variation (CV)3.1531819 × 10-12
Kurtosis-1.6054587
Mean3.0500002 × 1017
Median Absolute Deviation (MAD)699968
Skewness-0.18201428
Sum4.1232575 × 1018
Variance9.2490642 × 1011
MonotonicityStrictly increasing
2024-04-18T07:14:26.701760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
305000021199200004 1
 
1.4%
305000021201600003 1
 
1.4%
305000021201600001 1
 
1.4%
305000021201500023 1
 
1.4%
305000021201500022 1
 
1.4%
305000021201500021 1
 
1.4%
305000021201500020 1
 
1.4%
305000021201500019 1
 
1.4%
305000021201500018 1
 
1.4%
305000021201500017 1
 
1.4%
Other values (64) 64
86.5%
ValueCountFrequency (%)
305000021199200004 1
1.4%
305000021199600001 1
1.4%
305000021199700002 1
1.4%
305000021199700003 1
1.4%
305000021199700004 1
1.4%
305000021199700005 1
1.4%
305000021199700007 1
1.4%
305000021199700010 1
1.4%
305000021199700011 1
1.4%
305000021199700013 1
1.4%
ValueCountFrequency (%)
305000021202300002 1
1.4%
305000021202300001 1
1.4%
305000021202200003 1
1.4%
305000021202200002 1
1.4%
305000021202200001 1
1.4%
305000021202100005 1
1.4%
305000021202100004 1
1.4%
305000021202100003 1
1.4%
305000021202100002 1
1.4%
305000021202100001 1
1.4%

인허가일자
Date

Distinct54
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum1992-07-03 00:00:00
Maximum2023-04-12 00:00:00
2024-04-18T07:14:26.816281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:14:26.936304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

영업상태코드
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size724.0 B
1
32 
3
22 
4
17 
2
 
2
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row3
2nd row3
3rd row4
4th row3
5th row4

Common Values

ValueCountFrequency (%)
1 32
43.2%
3 22
29.7%
4 17
23.0%
2 2
 
2.7%
5 1
 
1.4%

Length

2024-04-18T07:14:27.037867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:27.122380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 32
43.2%
3 22
29.7%
4 17
23.0%
2 2
 
2.7%
5 1
 
1.4%

영업상태명
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size724.0 B
영업/정상
32 
폐업
22 
취소/말소/만료/정지/중지
17 
휴업
 
2
제외/삭제/전출
 
1

Length

Max length14
Median length8
Mean length6.1351351
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 32
43.2%
폐업 22
29.7%
취소/말소/만료/정지/중지 17
23.0%
휴업 2
 
2.7%
제외/삭제/전출 1
 
1.4%

Length

2024-04-18T07:14:27.216918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:27.309015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 32
43.2%
폐업 22
29.7%
취소/말소/만료/정지/중지 17
23.0%
휴업 2
 
2.7%
제외/삭제/전출 1
 
1.4%

상세영업상태코드
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size724.0 B
11
32 
2
22 
4
17 
1
 
2
5
 
1

Length

Max length2
Median length1
Mean length1.4324324
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row2
2nd row2
3rd row4
4th row2
5th row4

Common Values

ValueCountFrequency (%)
11 32
43.2%
2 22
29.7%
4 17
23.0%
1 2
 
2.7%
5 1
 
1.4%

Length

2024-04-18T07:14:27.401424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:27.502941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 32
43.2%
2 22
29.7%
4 17
23.0%
1 2
 
2.7%
5 1
 
1.4%

상세영업상태명
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size724.0 B
영업
32 
폐업
22 
폐쇄
17 
휴업
 
2
제외사항
 
1

Length

Max length4
Median length2
Mean length2.027027
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업 32
43.2%
폐업 22
29.7%
폐쇄 17
23.0%
휴업 2
 
2.7%
제외사항 1
 
1.4%

Length

2024-04-18T07:14:27.609270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:27.703032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 32
43.2%
폐업 22
29.7%
폐쇄 17
23.0%
휴업 2
 
2.7%
제외사항 1
 
1.4%

폐업일자
Date

MISSING 

Distinct34
Distinct (%)100.0%
Missing40
Missing (%)54.1%
Memory size724.0 B
Minimum2000-05-01 00:00:00
Maximum2023-03-27 00:00:00
2024-04-18T07:14:27.794269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:14:27.934006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

휴업시작일자
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing72
Missing (%)97.3%
Memory size724.0 B
Minimum2023-02-13 00:00:00
Maximum2024-02-01 00:00:00
2024-04-18T07:14:28.019190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:14:28.088847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

전화번호
Text

MISSING 

Distinct55
Distinct (%)100.0%
Missing19
Missing (%)25.7%
Memory size724.0 B
2024-04-18T07:14:28.245523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.618182
Min length7

Characters and Unicode

Total characters584
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)100.0%

Sample

1st row02 9233463
2nd row02 9671235
3rd row0222495959
4th row02 9623362
5th row02 9582091
ValueCountFrequency (%)
02 8
 
12.7%
9233463 1
 
1.6%
02-2127-4037 1
 
1.6%
965-1711 1
 
1.6%
02-957-8559 1
 
1.6%
02-3299-7114 1
 
1.6%
02-967-9497 1
 
1.6%
02-2210-3620 1
 
1.6%
02-923-9103 1
 
1.6%
02)921-1375 1
 
1.6%
Other values (46) 46
73.0%
2024-04-18T07:14:28.526907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 121
20.7%
0 90
15.4%
9 54
9.2%
- 54
9.2%
3 51
8.7%
1 47
 
8.0%
6 38
 
6.5%
7 34
 
5.8%
4 30
 
5.1%
5 27
 
4.6%
Other values (3) 38
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 513
87.8%
Dash Punctuation 54
 
9.2%
Close Punctuation 9
 
1.5%
Space Separator 8
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 121
23.6%
0 90
17.5%
9 54
10.5%
3 51
9.9%
1 47
 
9.2%
6 38
 
7.4%
7 34
 
6.6%
4 30
 
5.8%
5 27
 
5.3%
8 21
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 584
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 121
20.7%
0 90
15.4%
9 54
9.2%
- 54
9.2%
3 51
8.7%
1 47
 
8.0%
6 38
 
6.5%
7 34
 
5.8%
4 30
 
5.1%
5 27
 
4.6%
Other values (3) 38
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 121
20.7%
0 90
15.4%
9 54
9.2%
- 54
9.2%
3 51
8.7%
1 47
 
8.0%
6 38
 
6.5%
7 34
 
5.8%
4 30
 
5.1%
5 27
 
4.6%
Other values (3) 38
 
6.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

소재지우편번호
Text

MISSING 

Distinct11
Distinct (%)68.8%
Missing58
Missing (%)78.4%
Memory size724.0 B
2024-04-18T07:14:28.659223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters96
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

Unique7 ?
Unique (%)43.8%

Sample

1st row130072
2nd row130010
3rd row130709
4th row130071
5th row130101
ValueCountFrequency (%)
130100 3
18.8%
130010 2
12.5%
130071 2
12.5%
130080 2
12.5%
130072 1
 
6.2%
130709 1
 
6.2%
130101 1
 
6.2%
130104 1
 
6.2%
130092 1
 
6.2%
130083 1
 
6.2%
2024-04-18T07:14:28.882159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37
38.5%
1 25
26.0%
3 16
16.7%
7 4
 
4.2%
8 3
 
3.1%
2 2
 
2.1%
9 2
 
2.1%
l 2
 
2.1%
2
 
2.1%
4 1
 
1.0%
Other values (2) 2
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
93.8%
Lowercase Letter 4
 
4.2%
Space Separator 2
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37
41.1%
1 25
27.8%
3 16
17.8%
7 4
 
4.4%
8 3
 
3.3%
2 2
 
2.2%
9 2
 
2.2%
4 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
l 2
50.0%
n 1
25.0%
u 1
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92
95.8%
Latin 4
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37
40.2%
1 25
27.2%
3 16
17.4%
7 4
 
4.3%
8 3
 
3.3%
2 2
 
2.2%
9 2
 
2.2%
2
 
2.2%
4 1
 
1.1%
Latin
ValueCountFrequency (%)
l 2
50.0%
n 1
25.0%
u 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37
38.5%
1 25
26.0%
3 16
16.7%
7 4
 
4.2%
8 3
 
3.1%
2 2
 
2.1%
9 2
 
2.1%
l 2
 
2.1%
2
 
2.1%
4 1
 
1.0%
Other values (2) 2
 
2.1%

지번주소
Text

Distinct69
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-04-18T07:14:29.099946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29.5
Mean length22.337838
Min length15

Characters and Unicode

Total characters1653
Distinct characters83
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

Unique65 ?
Unique (%)87.8%

Sample

1st row서울특별시 동대문구 용두동 249-5번지
2nd row서울특별시 동대문구 용두동 23-10
3rd row서울특별시 동대문구 장안동 374-4
4th row서울특별시 동대문구 용두동 236-1번지
5th row서울특별시 동대문구 청량리동
ValueCountFrequency (%)
서울특별시 74
24.1%
동대문구 74
24.1%
장안동 16
 
5.2%
용두동 15
 
4.9%
청량리동 8
 
2.6%
제기동 8
 
2.6%
답십리동 8
 
2.6%
이문동 7
 
2.3%
전농동 4
 
1.3%
136-10번지 3
 
1.0%
Other values (77) 90
29.3%
2024-04-18T07:14:29.428243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
284
17.2%
동 150
 
9.1%
문 82
 
5.0%
대 75
 
4.5%
구 75
 
4.5%
서 74
 
4.5%
특 74
 
4.5%
별 74
 
4.5%
시 74
 
4.5%
울 74
 
4.5%
Other values (73) 617
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1037
62.7%
Space Separator 284
 
17.2%
Decimal Number 268
 
16.2%
Dash Punctuation 63
 
3.8%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 150
14.5%
문 82
 
7.9%
대 75
 
7.2%
구 75
 
7.2%
서 74
 
7.1%
특 74
 
7.1%
별 74
 
7.1%
시 74
 
7.1%
울 74
 
7.1%
번 31
 
3.0%
Other values (60) 254
24.5%
Decimal Number
ValueCountFrequency (%)
1 45
16.8%
2 43
16.0%
3 32
11.9%
4 29
10.8%
6 28
10.4%
5 23
8.6%
0 21
7.8%
9 21
7.8%
7 15
 
5.6%
8 11
 
4.1%
Space Separator
ValueCountFrequency (%)
284
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1037
62.7%
Common 616
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 150
14.5%
문 82
 
7.9%
대 75
 
7.2%
구 75
 
7.2%
서 74
 
7.1%
특 74
 
7.1%
별 74
 
7.1%
시 74
 
7.1%
울 74
 
7.1%
번 31
 
3.0%
Other values (60) 254
24.5%
Common
ValueCountFrequency (%)
284
46.1%
- 63
 
10.2%
1 45
 
7.3%
2 43
 
7.0%
3 32
 
5.2%
4 29
 
4.7%
6 28
 
4.5%
5 23
 
3.7%
0 21
 
3.4%
9 21
 
3.4%
Other values (3) 27
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1037
62.7%
ASCII 616
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
284
46.1%
- 63
 
10.2%
1 45
 
7.3%
2 43
 
7.0%
3 32
 
5.2%
4 29
 
4.7%
6 28
 
4.5%
5 23
 
3.7%
0 21
 
3.4%
9 21
 
3.4%
Other values (3) 27
 
4.4%
Hangul
ValueCountFrequency (%)
동 150
14.5%
문 82
 
7.9%
대 75
 
7.2%
구 75
 
7.2%
서 74
 
7.1%
특 74
 
7.1%
별 74
 
7.1%
시 74
 
7.1%
울 74
 
7.1%
번 31
 
3.0%
Other values (60) 254
24.5%

도로명주소
Text

MISSING 

Distinct56
Distinct (%)98.2%
Missing17
Missing (%)23.0%
Memory size724.0 B
2024-04-18T07:14:29.674953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length28.54386
Min length23

Characters and Unicode

Total characters1627
Distinct characters129
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

Unique55 ?
Unique (%)96.5%

Sample

1st row서울특별시 동대문구 무학로 101 (용두동)
2nd row서울특별시 동대문구 왕산로 146 (용두동)
3rd row서울특별시 동대문구 장한로17길 8 (장안동)
4th row서울특별시 동대문구 한천로58길 209 (이문동)
5th row서울특별시 동대문구 신이문로 44 (이문동)
ValueCountFrequency (%)
서울특별시 57
18.2%
동대문구 57
18.2%
왕산로 16
 
5.1%
장안동 11
 
3.5%
용두동 11
 
3.5%
제기동 8
 
2.6%
천호대로 7
 
2.2%
전농동 7
 
2.2%
고산자로 5
 
1.6%
청량리동 5
 
1.6%
Other values (101) 129
41.2%
2024-04-18T07:14:30.027211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
 
15.7%
동 118
 
7.3%
대 72
 
4.4%
문 66
 
4.1%
구 60
 
3.7%
서 59
 
3.6%
로 59
 
3.6%
울 59
 
3.6%
시 58
 
3.6%
특 57
 
3.5%
Other values (119) 763
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1067
65.6%
Space Separator 256
 
15.7%
Decimal Number 162
 
10.0%
Close Punctuation 57
 
3.5%
Open Punctuation 57
 
3.5%
Other Punctuation 27
 
1.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 118
 
11.1%
대 72
 
6.7%
문 66
 
6.2%
구 60
 
5.6%
서 59
 
5.5%
로 59
 
5.5%
울 59
 
5.5%
시 58
 
5.4%
특 57
 
5.3%
별 57
 
5.3%
Other values (104) 402
37.7%
Decimal Number
ValueCountFrequency (%)
1 28
17.3%
2 23
14.2%
5 19
11.7%
4 17
10.5%
0 17
10.5%
3 15
9.3%
7 14
8.6%
8 12
7.4%
6 11
 
6.8%
9 6
 
3.7%
Space Separator
ValueCountFrequency (%)
256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1067
65.6%
Common 560
34.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 118
 
11.1%
대 72
 
6.7%
문 66
 
6.2%
구 60
 
5.6%
서 59
 
5.5%
로 59
 
5.5%
울 59
 
5.5%
시 58
 
5.4%
특 57
 
5.3%
별 57
 
5.3%
Other values (104) 402
37.7%
Common
ValueCountFrequency (%)
256
45.7%
) 57
 
10.2%
( 57
 
10.2%
1 28
 
5.0%
, 27
 
4.8%
2 23
 
4.1%
5 19
 
3.4%
4 17
 
3.0%
0 17
 
3.0%
3 15
 
2.7%
Other values (5) 44
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1067
65.6%
ASCII 560
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
45.7%
) 57
 
10.2%
( 57
 
10.2%
1 28
 
5.0%
, 27
 
4.8%
2 23
 
4.1%
5 19
 
3.4%
4 17
 
3.0%
0 17
 
3.0%
3 15
 
2.7%
Other values (5) 44
 
7.9%
Hangul
ValueCountFrequency (%)
동 118
 
11.1%
대 72
 
6.7%
문 66
 
6.2%
구 60
 
5.6%
서 59
 
5.5%
로 59
 
5.5%
울 59
 
5.5%
시 58
 
5.4%
특 57
 
5.3%
별 57
 
5.3%
Other values (104) 402
37.7%

도로명우편번호
Text

MISSING 

Distinct41
Distinct (%)71.9%
Missing17
Missing (%)23.0%
Memory size724.0 B
2024-04-18T07:14:30.205396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3684211
Min length5

Characters and Unicode

Total characters306
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

Unique31 ?
Unique (%)54.4%

Sample

1st row130823
2nd row130817
3rd row130-842
4th row130827
5th row130828
ValueCountFrequency (%)
130817 4
 
7.0%
02555 4
 
7.0%
02473 3
 
5.3%
02455 3
 
5.3%
02582 2
 
3.5%
02447 2
 
3.5%
02559 2
 
3.5%
02633 2
 
3.5%
02560 2
 
3.5%
02565 2
 
3.5%
Other values (31) 31
54.4%
2024-04-18T07:14:30.541008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 67
21.9%
2 49
16.0%
5 41
13.4%
3 30
9.8%
8 28
9.2%
1 25
 
8.2%
4 24
 
7.8%
6 19
 
6.2%
7 13
 
4.2%
9 6
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 302
98.7%
Dash Punctuation 4
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 67
22.2%
2 49
16.2%
5 41
13.6%
3 30
9.9%
8 28
9.3%
1 25
 
8.3%
4 24
 
7.9%
6 19
 
6.3%
7 13
 
4.3%
9 6
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 306
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 67
21.9%
2 49
16.0%
5 41
13.4%
3 30
9.8%
8 28
9.2%
1 25
 
8.2%
4 24
 
7.8%
6 19
 
6.2%
7 13
 
4.2%
9 6
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 67
21.9%
2 49
16.0%
5 41
13.4%
3 30
9.8%
8 28
9.2%
1 25
 
8.2%
4 24
 
7.8%
6 19
 
6.2%
7 13
 
4.2%
9 6
 
2.0%

사업장명
Text

Distinct64
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-04-18T07:14:30.742840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18.5
Mean length9.527027
Min length4

Characters and Unicode

Total characters705
Distinct characters190
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)78.4%

Sample

1st row동양흥업서비스주식회사
2nd row남성공업사
3rd row장인자동차공업사
4th row태흥자동차공업사
5th row국방품질관리소
ValueCountFrequency (%)
한국국방연구원 3
 
3.4%
흥명자동차공업사(주 3
 
3.4%
동부자동차공업(주 3
 
3.4%
오토랜드 3
 
3.4%
주)대흥모터스 2
 
2.2%
동대문구청 2
 
2.2%
한국철도공사 2
 
2.2%
수도권동부본부 2
 
2.2%
청량리역 2
 
2.2%
삼육서울병원 1
 
1.1%
Other values (66) 66
74.2%
2024-04-18T07:14:31.059660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 33
 
4.7%
) 32
 
4.5%
주 32
 
4.5%
( 32
 
4.5%
사 23
 
3.3%
공 18
 
2.6%
업 17
 
2.4%
한 15
 
2.1%
15
 
2.1%
리 15
 
2.1%
Other values (180) 473
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 617
87.5%
Close Punctuation 33
 
4.7%
Open Punctuation 33
 
4.7%
Space Separator 15
 
2.1%
Uppercase Letter 5
 
0.7%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 33
 
5.3%
주 32
 
5.2%
사 23
 
3.7%
공 18
 
2.9%
업 17
 
2.8%
한 15
 
2.4%
리 15
 
2.4%
국 14
 
2.3%
스 14
 
2.3%
자 14
 
2.3%
Other values (169) 422
68.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
20.0%
Y 1
20.0%
K 1
20.0%
L 1
20.0%
A 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 32
97.0%
] 1
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 32
97.0%
[ 1
 
3.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 617
87.5%
Common 83
 
11.8%
Latin 5
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 33
 
5.3%
주 32
 
5.2%
사 23
 
3.7%
공 18
 
2.9%
업 17
 
2.8%
한 15
 
2.4%
리 15
 
2.4%
국 14
 
2.3%
스 14
 
2.3%
자 14
 
2.3%
Other values (169) 422
68.4%
Common
ValueCountFrequency (%)
) 32
38.6%
( 32
38.6%
15
18.1%
- 2
 
2.4%
[ 1
 
1.2%
] 1
 
1.2%
Latin
ValueCountFrequency (%)
S 1
20.0%
Y 1
20.0%
K 1
20.0%
L 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 617
87.5%
ASCII 88
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 33
 
5.3%
주 32
 
5.2%
사 23
 
3.7%
공 18
 
2.9%
업 17
 
2.8%
한 15
 
2.4%
리 15
 
2.4%
국 14
 
2.3%
스 14
 
2.3%
자 14
 
2.3%
Other values (169) 422
68.4%
ASCII
ValueCountFrequency (%)
) 32
36.4%
( 32
36.4%
15
17.0%
- 2
 
2.3%
[ 1
 
1.1%
S 1
 
1.1%
Y 1
 
1.1%
K 1
 
1.1%
L 1
 
1.1%
A 1
 
1.1%

최종수정일자
Date

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum2001-04-10 11:11:04
Maximum2024-03-20 09:38:17
2024-04-18T07:14:31.177002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:14:31.293843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
U
45 
I
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 45
60.8%
I 29
39.2%

Length

2024-04-18T07:14:31.416500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:31.496066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 45
60.8%
i 29
39.2%

데이터갱신일자
Date

Distinct44
Distinct (%)59.5%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum2018-10-04 11:12:49
Maximum2023-12-03 00:09:00
2024-04-18T07:14:31.579253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:14:31.705538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

업태구분명
Text

MISSING 

Distinct40
Distinct (%)61.5%
Missing9
Missing (%)12.2%
Memory size724.0 B
2024-04-18T07:14:31.910482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length8.4923077
Min length2

Characters and Unicode

Total characters552
Distinct characters103
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)52.3%

Sample

1st row자동차 종합 수리업
2nd row자동차 종합 수리업
3rd row자동차 종합 수리업
4th row자동차 종합 수리업
5th row연구 및 개발업
ValueCountFrequency (%)
수리업 21
 
12.7%
자동차 20
 
12.0%
종합 20
 
12.0%
및 10
 
6.0%
기타 7
 
4.2%
부동산 6
 
3.6%
병원 5
 
3.0%
제조업 4
 
2.4%
개발업 3
 
1.8%
연구 3
 
1.8%
Other values (56) 67
40.4%
2024-04-18T07:14:32.227767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
18.3%
업 57
 
10.3%
동 28
 
5.1%
리 26
 
4.7%
자 22
 
4.0%
수 21
 
3.8%
합 20
 
3.6%
종 20
 
3.6%
차 20
 
3.6%
산 12
 
2.2%
Other values (93) 225
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 449
81.3%
Space Separator 101
 
18.3%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 57
 
12.7%
동 28
 
6.2%
리 26
 
5.8%
자 22
 
4.9%
수 21
 
4.7%
합 20
 
4.5%
종 20
 
4.5%
차 20
 
4.5%
산 12
 
2.7%
및 10
 
2.2%
Other values (90) 213
47.4%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
? 1
50.0%
Space Separator
ValueCountFrequency (%)
101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 449
81.3%
Common 103
 
18.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 57
 
12.7%
동 28
 
6.2%
리 26
 
5.8%
자 22
 
4.9%
수 21
 
4.7%
합 20
 
4.5%
종 20
 
4.5%
차 20
 
4.5%
산 12
 
2.7%
및 10
 
2.2%
Other values (90) 213
47.4%
Common
ValueCountFrequency (%)
101
98.1%
, 1
 
1.0%
? 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 449
81.3%
ASCII 103
 
18.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
98.1%
, 1
 
1.0%
? 1
 
1.0%
Hangul
ValueCountFrequency (%)
업 57
 
12.7%
동 28
 
6.2%
리 26
 
5.8%
자 22
 
4.9%
수 21
 
4.7%
합 20
 
4.5%
종 20
 
4.5%
차 20
 
4.5%
산 12
 
2.7%
및 10
 
2.2%
Other values (90) 213
47.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct58
Distinct (%)87.9%
Missing8
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean204343.69
Minimum202093.91
Maximum206478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-18T07:14:32.342583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202093.91
5-th percentile202552.51
Q1203344.55
median204105.98
Q3205597.25
95-th percentile206185.67
Maximum206478
Range4384.0931
Interquartile range (IQR)2252.695

Descriptive statistics

Standard deviation1258.406
Coefficient of variation (CV)0.0061582817
Kurtosis-1.2338558
Mean204343.69
Median Absolute Deviation (MAD)949.19784
Skewness0.1506389
Sum13486684
Variance1583585.8
MonotonicityNot monotonic
2024-04-18T07:14:32.464698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203156.778795022 3
 
4.1%
203532.398547315 3
 
4.1%
204540.846220699 2
 
2.7%
205857.860991096 2
 
2.7%
204081.282117393 2
 
2.7%
204469.209049094 2
 
2.7%
203243.16761463 1
 
1.4%
204343.550551468 1
 
1.4%
205622.517700168 1
 
1.4%
202093.908184725 1
 
1.4%
Other values (48) 48
64.9%
(Missing) 8
 
10.8%
ValueCountFrequency (%)
202093.908184725 1
1.4%
202233.604900045 1
1.4%
202318.050601995 1
1.4%
202536.147106474 1
1.4%
202601.594014166 1
1.4%
202610.687654389 1
1.4%
202755.502835045 1
1.4%
202950.060576221 1
1.4%
203075.098504907 1
1.4%
203155.504921512 1
1.4%
ValueCountFrequency (%)
206478.001297999 1
1.4%
206464.060139046 1
1.4%
206370.393941274 1
1.4%
206199.953197537 1
1.4%
206142.804223328 1
1.4%
206106.483386124 1
1.4%
206093.662937527 1
1.4%
206086.139474897 1
1.4%
206034.094965709 1
1.4%
205987.067570254 1
1.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct58
Distinct (%)87.9%
Missing8
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean453099.05
Minimum451004.76
Maximum455896.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-18T07:14:32.604701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451004.76
5-th percentile451141.26
Q1452363.65
median452933.77
Q3454065.85
95-th percentile455446.6
Maximum455896.6
Range4891.8337
Interquartile range (IQR)1702.2007

Descriptive statistics

Standard deviation1252.5246
Coefficient of variation (CV)0.0027643504
Kurtosis-0.4332938
Mean453099.05
Median Absolute Deviation (MAD)880.79566
Skewness0.29611698
Sum29904537
Variance1568817.8
MonotonicityNot monotonic
2024-04-18T07:14:32.722961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454065.85249321 3
 
4.1%
454427.801068962 3
 
4.1%
453680.427329437 2
 
2.7%
455590.912797973 2
 
2.7%
453187.395154017 2
 
2.7%
454934.047367752 2
 
2.7%
454119.840088656 1
 
1.4%
453554.680324706 1
 
1.4%
454115.432829144 1
 
1.4%
452612.924194191 1
 
1.4%
Other values (48) 48
64.9%
(Missing) 8
 
10.8%
ValueCountFrequency (%)
451004.764350926 1
1.4%
451011.194201757 1
1.4%
451130.433056754 1
1.4%
451135.637561446 1
1.4%
451158.131495939 1
1.4%
451248.195444631 1
1.4%
451290.385714542 1
1.4%
451404.259091982 1
1.4%
451420.234504681 1
1.4%
451657.395402106 1
1.4%
ValueCountFrequency (%)
455896.598021847 1
 
1.4%
455876.231869346 1
 
1.4%
455590.912797973 2
2.7%
455013.644655621 1
 
1.4%
454934.047367752 2
2.7%
454719.205565844 1
 
1.4%
454427.801068962 3
4.1%
454190.811726547 1
 
1.4%
454119.840088656 1
 
1.4%
454115.432829144 1
 
1.4%

환경업무구분명
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
대기배출업소관리
51 
<NA>
23 

Length

Max length8
Median length8
Mean length6.7567568
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기배출업소관리 51
68.9%
<NA> 23
31.1%

Length

2024-04-18T07:14:32.841626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:32.927548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기배출업소관리 51
68.9%
na 23
31.1%

업종구분명
Text

MISSING 

Distinct26
Distinct (%)61.9%
Missing32
Missing (%)43.2%
Memory size724.0 B
2024-04-18T07:14:33.081483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length8.3809524
Min length2

Characters and Unicode

Total characters352
Distinct characters88
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)52.4%

Sample

1st row자동차 종합 수리업
2nd row자동차 종합 수리업
3rd row자동차 종합 수리업
4th row연구 및 개발업
5th row종합 병원
ValueCountFrequency (%)
종합 16
15.2%
수리업 15
14.3%
자동차 14
 
13.3%
병원 5
 
4.8%
및 5
 
4.8%
기타 4
 
3.8%
서비스업 3
 
2.9%
제조업 3
 
2.9%
임대업 2
 
1.9%
부동산 2
 
1.9%
Other values (34) 36
34.3%
2024-04-18T07:14:33.370775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
17.9%
업 37
 
10.5%
동 17
 
4.8%
종 16
 
4.5%
합 16
 
4.5%
리 16
 
4.5%
수 15
 
4.3%
자 14
 
4.0%
차 14
 
4.0%
산 6
 
1.7%
Other values (78) 138
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 288
81.8%
Space Separator 63
 
17.9%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 37
 
12.8%
동 17
 
5.9%
종 16
 
5.6%
합 16
 
5.6%
리 16
 
5.6%
수 15
 
5.2%
자 14
 
4.9%
차 14
 
4.9%
산 6
 
2.1%
병 5
 
1.7%
Other values (76) 132
45.8%
Space Separator
ValueCountFrequency (%)
63
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 288
81.8%
Common 64
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 37
 
12.8%
동 17
 
5.9%
종 16
 
5.6%
합 16
 
5.6%
리 16
 
5.6%
수 15
 
5.2%
자 14
 
4.9%
차 14
 
4.9%
산 6
 
2.1%
병 5
 
1.7%
Other values (76) 132
45.8%
Common
ValueCountFrequency (%)
63
98.4%
? 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 288
81.8%
ASCII 64
 
18.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
98.4%
? 1
 
1.6%
Hangul
ValueCountFrequency (%)
업 37
 
12.8%
동 17
 
5.9%
종 16
 
5.6%
합 16
 
5.6%
리 16
 
5.6%
수 15
 
5.2%
자 14
 
4.9%
차 14
 
4.9%
산 6
 
2.1%
병 5
 
1.7%
Other values (76) 132
45.8%

종별명
Categorical

Distinct4
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
5종
38 
<NA>
26 
4종
9 
3종
 
1

Length

Max length4
Median length2
Mean length2.7027027
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row5종
2nd row5종
3rd row<NA>
4th row5종
5th row5종

Common Values

ValueCountFrequency (%)
5종 38
51.4%
<NA> 26
35.1%
4종 9
 
12.2%
3종 1
 
1.4%

Length

2024-04-18T07:14:33.483223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:33.576355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5종 38
51.4%
na 26
35.1%
4종 9
 
12.2%
3종 1
 
1.4%

주생산품명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing72
Missing (%)97.3%
Memory size724.0 B
2024-04-18T07:14:33.680212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row수리된차량
2nd row자동차수리
ValueCountFrequency (%)
수리된차량 1
50.0%
자동차수리 1
50.0%
2024-04-18T07:14:33.903079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 2
20.0%
리 2
20.0%
차 2
20.0%
된 1
10.0%
량 1
10.0%
자 1
10.0%
동 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 2
20.0%
리 2
20.0%
차 2
20.0%
된 1
10.0%
량 1
10.0%
자 1
10.0%
동 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 2
20.0%
리 2
20.0%
차 2
20.0%
된 1
10.0%
량 1
10.0%
자 1
10.0%
동 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 2
20.0%
리 2
20.0%
차 2
20.0%
된 1
10.0%
량 1
10.0%
자 1
10.0%
동 1
10.0%

배출시설조업시간
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)33.3%
Missing29
Missing (%)39.2%
Infinite0
Infinite (%)0.0%
Mean6.9044444
Minimum0
Maximum24
Zeros5
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-18T07:14:33.992897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median8
Q38
95-th percentile12.72
Maximum24
Range24
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.4245162
Coefficient of variation (CV)0.64082146
Kurtosis4.6691002
Mean6.9044444
Median Absolute Deviation (MAD)1
Skewness1.2736139
Sum310.7
Variance19.576343
MonotonicityNot monotonic
2024-04-18T07:14:34.076880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
8.0 21
28.4%
0.0 5
 
6.8%
5.0 3
 
4.1%
4.0 2
 
2.7%
3.0 2
 
2.7%
7.0 2
 
2.7%
6.0 2
 
2.7%
10.0 1
 
1.4%
2.0 1
 
1.4%
7.6 1
 
1.4%
Other values (5) 5
 
6.8%
(Missing) 29
39.2%
ValueCountFrequency (%)
0.0 5
 
6.8%
1.5 1
 
1.4%
2.0 1
 
1.4%
3.0 2
 
2.7%
4.0 2
 
2.7%
5.0 3
 
4.1%
6.0 2
 
2.7%
7.0 2
 
2.7%
7.6 1
 
1.4%
8.0 21
28.4%
ValueCountFrequency (%)
24.0 1
 
1.4%
18.0 1
 
1.4%
13.0 1
 
1.4%
11.6 1
 
1.4%
10.0 1
 
1.4%
8.0 21
28.4%
7.6 1
 
1.4%
7.0 2
 
2.7%
6.0 2
 
2.7%
5.0 3
 
4.1%

배출시설연간가동일수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)23.4%
Missing27
Missing (%)36.5%
Infinite0
Infinite (%)0.0%
Mean246.3617
Minimum0
Maximum365
Zeros7
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-18T07:14:34.170232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1224.5
median300
Q3300
95-th percentile365
Maximum365
Range365
Interquartile range (IQR)75.5

Descriptive statistics

Standard deviation121.89098
Coefficient of variation (CV)0.4947643
Kurtosis0.057495927
Mean246.3617
Median Absolute Deviation (MAD)0
Skewness-1.244215
Sum11579
Variance14857.41
MonotonicityNot monotonic
2024-04-18T07:14:34.687159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
300 25
33.8%
0 7
 
9.5%
365 4
 
5.4%
360 4
 
5.4%
79 1
 
1.4%
95 1
 
1.4%
120 1
 
1.4%
160 1
 
1.4%
189 1
 
1.4%
260 1
 
1.4%
(Missing) 27
36.5%
ValueCountFrequency (%)
0 7
 
9.5%
79 1
 
1.4%
95 1
 
1.4%
120 1
 
1.4%
160 1
 
1.4%
189 1
 
1.4%
260 1
 
1.4%
276 1
 
1.4%
300 25
33.8%
360 4
 
5.4%
ValueCountFrequency (%)
365 4
 
5.4%
360 4
 
5.4%
300 25
33.8%
276 1
 
1.4%
260 1
 
1.4%
189 1
 
1.4%
160 1
 
1.4%
120 1
 
1.4%
95 1
 
1.4%
79 1
 
1.4%

방지시설조업시간
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)22.6%
Missing43
Missing (%)58.1%
Infinite0
Infinite (%)0.0%
Mean6.0645161
Minimum0
Maximum10
Zeros6
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-18T07:14:34.795547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.5
median8
Q38
95-th percentile8
Maximum10
Range10
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation3.2551035
Coefficient of variation (CV)0.53674579
Kurtosis-0.18365893
Mean6.0645161
Median Absolute Deviation (MAD)0
Skewness-1.1958616
Sum188
Variance10.595699
MonotonicityNot monotonic
2024-04-18T07:14:34.884838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
8 19
25.7%
0 6
 
8.1%
4 2
 
2.7%
10 1
 
1.4%
7 1
 
1.4%
5 1
 
1.4%
6 1
 
1.4%
(Missing) 43
58.1%
ValueCountFrequency (%)
0 6
 
8.1%
4 2
 
2.7%
5 1
 
1.4%
6 1
 
1.4%
7 1
 
1.4%
8 19
25.7%
10 1
 
1.4%
ValueCountFrequency (%)
10 1
 
1.4%
8 19
25.7%
7 1
 
1.4%
6 1
 
1.4%
5 1
 
1.4%
4 2
 
2.7%
0 6
 
8.1%

방지시설연간가동일수
Categorical

Distinct6
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
38 
300
22 
0
11 
200
 
1
260
 
1

Length

Max length4
Median length4
Mean length3.2162162
Min length1

Unique

Unique3 ?
Unique (%)4.1%

Sample

1st row300
2nd row300
3rd row<NA>
4th row300
5th row300

Common Values

ValueCountFrequency (%)
<NA> 38
51.4%
300 22
29.7%
0 11
 
14.9%
200 1
 
1.4%
260 1
 
1.4%
360 1
 
1.4%

Length

2024-04-18T07:14:34.983721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:14:35.075229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 38
51.4%
300 22
29.7%
0 11
 
14.9%
200 1
 
1.4%
260 1
 
1.4%
360 1
 
1.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
0305000030500002119920000419921005<NA>3폐업2폐업<NA><NA><NA><NA>02 9233463<NA><NA>서울특별시 동대문구 용두동 249-5번지서울특별시 동대문구 무학로 101 (용두동)130823동양흥업서비스주식회사2015-02-09 13:35:56I2018-10-04 11:12:49.0자동차 종합 수리업202610.687654452312.895074대기배출업소관리자동차 종합 수리업5종<NA>8.03008300
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