Overview

Dataset statistics

Number of variables33
Number of observations32
Missing cells330
Missing cells (%)31.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory286.1 B

Variable types

Categorical9
Numeric8
DateTime4
Unsupported7
Text5

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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-19366/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 32 (100.0%) missing valuesMissing
폐업일자 has 23 (71.9%) missing valuesMissing
휴업시작일자 has 32 (100.0%) missing valuesMissing
휴업종료일자 has 32 (100.0%) missing valuesMissing
재개업일자 has 32 (100.0%) missing valuesMissing
전화번호 has 6 (18.8%) missing valuesMissing
소재지면적 has 32 (100.0%) missing valuesMissing
소재지우편번호 has 32 (100.0%) missing valuesMissing
지번주소 has 11 (34.4%) missing valuesMissing
도로명주소 has 1 (3.1%) missing valuesMissing
도로명우편번호 has 4 (12.5%) missing valuesMissing
업종구분명 has 18 (56.2%) missing valuesMissing
주생산품명 has 32 (100.0%) missing valuesMissing
배출시설조업시간 has 8 (25.0%) missing valuesMissing
배출시설연간가동일수 has 8 (25.0%) missing valuesMissing
방지시설조업시간 has 15 (46.9%) missing valuesMissing
방지시설연간가동일수 has 12 (37.5%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 has unique valuesUnique
좌표정보(X) has unique valuesUnique
좌표정보(Y) 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
주생산품명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방지시설연간가동일수 has 3 (9.4%) zerosZeros

Reproduction

Analysis started2024-05-11 05:54:17.527166
Analysis finished2024-05-11 05:54:18.192521
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
3140000
32 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 32
100.0%

Length

2024-05-11T14:54:18.309196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:18.488270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 32
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1400002 × 1017
Minimum3.1400002 × 1017
Maximum3.1400002 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-05-11T14:54:18.668169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1400002 × 1017
5-th percentile3.1400002 × 1017
Q13.1400002 × 1017
median3.1400002 × 1017
Q33.1400002 × 1017
95-th percentile3.1400002 × 1017
Maximum3.1400002 × 1017
Range2899988
Interquartile range (IQR)1400000

Descriptive statistics

Standard deviation858676.95
Coefficient of variation (CV)2.7346398 × 10-12
Kurtosis-1.3313991
Mean3.1400002 × 1017
Median Absolute Deviation (MAD)900000
Skewness-0.12699082
Sum-8.3987434 × 1018
Variance7.3732611 × 1011
MonotonicityStrictly increasing
2024-05-11T14:54:18.900008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
314000021199300014 1
 
3.1%
314000021201500001 1
 
3.1%
314000021202200002 1
 
3.1%
314000021202200001 1
 
3.1%
314000021202100001 1
 
3.1%
314000021201900001 1
 
3.1%
314000021201500014 1
 
3.1%
314000021201500012 1
 
3.1%
314000021201500011 1
 
3.1%
314000021201500010 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
314000021199300014 1
3.1%
314000021199400018 1
3.1%
314000021199900020 1
3.1%
314000021199900021 1
3.1%
314000021199900022 1
3.1%
314000021200100001 1
3.1%
314000021200100002 1
3.1%
314000021200100003 1
3.1%
314000021200100004 1
3.1%
314000021200100007 1
3.1%
ValueCountFrequency (%)
314000021202200002 1
3.1%
314000021202200001 1
3.1%
314000021202100001 1
3.1%
314000021201900001 1
3.1%
314000021201500014 1
3.1%
314000021201500012 1
3.1%
314000021201500011 1
3.1%
314000021201500010 1
3.1%
314000021201500009 1
3.1%
314000021201500007 1
3.1%

인허가일자
Date

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum1993-05-26 00:00:00
Maximum2022-11-21 00:00:00
2024-05-11T14:54:19.109692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:19.298461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
1
22 
3
6 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row3
4th row1
5th row4

Common Values

ValueCountFrequency (%)
1 22
68.8%
3 6
 
18.8%
4 4
 
12.5%

Length

2024-05-11T14:54:19.494452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:19.675231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
68.8%
3 6
 
18.8%
4 4
 
12.5%

영업상태명
Categorical

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
영업/정상
22 
폐업
6 
취소/말소/만료/정지/중지
4 

Length

Max length14
Median length5
Mean length5.5625
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 22
68.8%
폐업 6
 
18.8%
취소/말소/만료/정지/중지 4
 
12.5%

Length

2024-05-11T14:54:19.857591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:20.039728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 22
68.8%
폐업 6
 
18.8%
취소/말소/만료/정지/중지 4
 
12.5%

상세영업상태코드
Categorical

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
11
22 
2
6 
4
4 

Length

Max length2
Median length2
Mean length1.6875
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row2
4th row11
5th row4

Common Values

ValueCountFrequency (%)
11 22
68.8%
2 6
 
18.8%
4 4
 
12.5%

Length

2024-05-11T14:54:20.673805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:20.873859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 22
68.8%
2 6
 
18.8%
4 4
 
12.5%

상세영업상태명
Categorical

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
영업
22 
폐업
6 
폐쇄
4 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 22
68.8%
폐업 6
 
18.8%
폐쇄 4
 
12.5%

Length

2024-05-11T14:54:21.074848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:21.239499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 22
68.8%
폐업 6
 
18.8%
폐쇄 4
 
12.5%

폐업일자
Date

MISSING 

Distinct9
Distinct (%)100.0%
Missing23
Missing (%)71.9%
Memory size388.0 B
Minimum2010-12-30 00:00:00
Maximum2024-08-31 00:00:00
2024-05-11T14:54:21.419222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:21.659311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

전화번호
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing6
Missing (%)18.8%
Memory size388.0 B
2024-05-11T14:54:21.972186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.346154
Min length8

Characters and Unicode

Total characters269
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

Unique26 ?
Unique (%)100.0%

Sample

1st row02-2646-2802
2nd row02-2693-1152
3rd row02-2692-0545
4th row02-2695-0678
5th row26931001
ValueCountFrequency (%)
2645-8851 1
 
3.8%
02-2692-0545 1
 
3.8%
0226405284 1
 
3.8%
02-6923-1100 1
 
3.8%
0226466097 1
 
3.8%
0226941464 1
 
3.8%
0226903460 1
 
3.8%
0232199138 1
 
3.8%
0221633171 1
 
3.8%
0226479613 1
 
3.8%
Other values (16) 16
61.5%
2024-05-11T14:54:22.553942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 59
21.9%
0 46
17.1%
6 41
15.2%
1 25
9.3%
- 19
 
7.1%
9 17
 
6.3%
4 16
 
5.9%
3 15
 
5.6%
5 13
 
4.8%
8 11
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 250
92.9%
Dash Punctuation 19
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 59
23.6%
0 46
18.4%
6 41
16.4%
1 25
10.0%
9 17
 
6.8%
4 16
 
6.4%
3 15
 
6.0%
5 13
 
5.2%
8 11
 
4.4%
7 7
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 59
21.9%
0 46
17.1%
6 41
15.2%
1 25
9.3%
- 19
 
7.1%
9 17
 
6.3%
4 16
 
5.9%
3 15
 
5.6%
5 13
 
4.8%
8 11
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 59
21.9%
0 46
17.1%
6 41
15.2%
1 25
9.3%
- 19
 
7.1%
9 17
 
6.3%
4 16
 
5.9%
3 15
 
5.6%
5 13
 
4.8%
8 11
 
4.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

지번주소
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing11
Missing (%)34.4%
Memory size388.0 B
2024-05-11T14:54:22.854546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length21.714286
Min length19

Characters and Unicode

Total characters456
Distinct characters54
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 신정동 276 신정지하철차량기지
2nd row서울특별시 양천구 신정동 886-12
3rd row서울특별시 양천구 신월동 545-5번지
4th row서울특별시 양천구 신월동 437-5
5th row서울특별시 양천구 신월동 437-6
ValueCountFrequency (%)
서울특별시 21
23.3%
양천구 21
23.3%
신월동 11
12.2%
신정동 8
 
8.9%
목동 2
 
2.2%
319-11 1
 
1.1%
886-12 1
 
1.1%
남부빌딩 1
 
1.1%
1009-6 1
 
1.1%
2호 1
 
1.1%
Other values (22) 22
24.4%
2024-05-11T14:54:23.390747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
18.4%
동 22
 
4.8%
서 21
 
4.6%
특 21
 
4.6%
별 21
 
4.6%
시 21
 
4.6%
양 21
 
4.6%
천 21
 
4.6%
구 21
 
4.6%
울 21
 
4.6%
Other values (44) 182
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 269
59.0%
Decimal Number 85
 
18.6%
Space Separator 84
 
18.4%
Dash Punctuation 18
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
 
8.2%
서 21
 
7.8%
특 21
 
7.8%
별 21
 
7.8%
시 21
 
7.8%
양 21
 
7.8%
천 21
 
7.8%
구 21
 
7.8%
울 21
 
7.8%
신 20
 
7.4%
Other values (32) 59
21.9%
Decimal Number
ValueCountFrequency (%)
2 15
17.6%
1 13
15.3%
6 10
11.8%
9 9
10.6%
7 8
9.4%
3 7
8.2%
8 6
 
7.1%
4 6
 
7.1%
0 6
 
7.1%
5 5
 
5.9%
Space Separator
ValueCountFrequency (%)
84
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 269
59.0%
Common 187
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
 
8.2%
서 21
 
7.8%
특 21
 
7.8%
별 21
 
7.8%
시 21
 
7.8%
양 21
 
7.8%
천 21
 
7.8%
구 21
 
7.8%
울 21
 
7.8%
신 20
 
7.4%
Other values (32) 59
21.9%
Common
ValueCountFrequency (%)
84
44.9%
- 18
 
9.6%
2 15
 
8.0%
1 13
 
7.0%
6 10
 
5.3%
9 9
 
4.8%
7 8
 
4.3%
3 7
 
3.7%
8 6
 
3.2%
4 6
 
3.2%
Other values (2) 11
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 269
59.0%
ASCII 187
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
44.9%
- 18
 
9.6%
2 15
 
8.0%
1 13
 
7.0%
6 10
 
5.3%
9 9
 
4.8%
7 8
 
4.3%
3 7
 
3.7%
8 6
 
3.2%
4 6
 
3.2%
Other values (2) 11
 
5.9%
Hangul
ValueCountFrequency (%)
동 22
 
8.2%
서 21
 
7.8%
특 21
 
7.8%
별 21
 
7.8%
시 21
 
7.8%
양 21
 
7.8%
천 21
 
7.8%
구 21
 
7.8%
울 21
 
7.8%
신 20
 
7.4%
Other values (32) 59
21.9%

도로명주소
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing1
Missing (%)3.1%
Memory size388.0 B
2024-05-11T14:54:23.778742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length26.354839
Min length21

Characters and Unicode

Total characters817
Distinct characters81
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

Unique31 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 목동로3길 41 (신정동)
2nd row서울특별시 양천구 신정중앙로 81 (신정동)
3rd row서울특별시 양천구 신월로 157 (신월동)
4th row서울특별시 양천구 오목로1길 15 (신월동)
5th row서울특별시 양천구 오목로1길 9 (신월동)
ValueCountFrequency (%)
서울특별시 31
18.8%
양천구 31
18.8%
신월동 14
 
8.5%
목동 9
 
5.5%
신정동 8
 
4.8%
신목로 2
 
1.2%
목동로1길 2
 
1.2%
화곡로 2
 
1.2%
월정로 2
 
1.2%
오목로 2
 
1.2%
Other values (57) 62
37.6%
2024-05-11T14:54:24.374813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
 
16.5%
동 44
 
5.4%
서 33
 
4.0%
양 33
 
4.0%
로 33
 
4.0%
천 32
 
3.9%
시 31
 
3.8%
구 31
 
3.8%
특 31
 
3.8%
울 31
 
3.8%
Other values (71) 383
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 518
63.4%
Space Separator 135
 
16.5%
Decimal Number 89
 
10.9%
Close Punctuation 31
 
3.8%
Open Punctuation 31
 
3.8%
Other Punctuation 10
 
1.2%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 44
 
8.5%
서 33
 
6.4%
양 33
 
6.4%
로 33
 
6.4%
천 32
 
6.2%
시 31
 
6.0%
구 31
 
6.0%
특 31
 
6.0%
울 31
 
6.0%
별 31
 
6.0%
Other values (56) 188
36.3%
Decimal Number
ValueCountFrequency (%)
1 22
24.7%
7 11
12.4%
4 9
10.1%
2 9
10.1%
5 8
 
9.0%
3 8
 
9.0%
0 7
 
7.9%
9 6
 
6.7%
6 5
 
5.6%
8 4
 
4.5%
Space Separator
ValueCountFrequency (%)
135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 518
63.4%
Common 299
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 44
 
8.5%
서 33
 
6.4%
양 33
 
6.4%
로 33
 
6.4%
천 32
 
6.2%
시 31
 
6.0%
구 31
 
6.0%
특 31
 
6.0%
울 31
 
6.0%
별 31
 
6.0%
Other values (56) 188
36.3%
Common
ValueCountFrequency (%)
135
45.2%
) 31
 
10.4%
( 31
 
10.4%
1 22
 
7.4%
7 11
 
3.7%
, 10
 
3.3%
4 9
 
3.0%
2 9
 
3.0%
5 8
 
2.7%
3 8
 
2.7%
Other values (5) 25
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 518
63.4%
ASCII 299
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
45.2%
) 31
 
10.4%
( 31
 
10.4%
1 22
 
7.4%
7 11
 
3.7%
, 10
 
3.3%
4 9
 
3.0%
2 9
 
3.0%
5 8
 
2.7%
3 8
 
2.7%
Other values (5) 25
 
8.4%
Hangul
ValueCountFrequency (%)
동 44
 
8.5%
서 33
 
6.4%
양 33
 
6.4%
로 33
 
6.4%
천 32
 
6.2%
시 31
 
6.0%
구 31
 
6.0%
특 31
 
6.0%
울 31
 
6.0%
별 31
 
6.0%
Other values (56) 188
36.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)96.4%
Missing4
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean72576.071
Minimum7901
Maximum158850
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-05-11T14:54:24.596585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7901
5-th percentile7921.15
Q18000.5
median8044
Q3158756.25
95-th percentile158835.6
Maximum158850
Range150949
Interquartile range (IQR)150755.75

Descriptive statistics

Standard deviation75932.785
Coefficient of variation (CV)1.046251
Kurtosis-2.0595747
Mean72576.071
Median Absolute Deviation (MAD)115.5
Skewness0.30529653
Sum2032130
Variance5.7657879 × 109
MonotonicityNot monotonic
2024-05-11T14:54:24.830090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
158833 2
 
6.2%
7953 1
 
3.1%
8013 1
 
3.1%
8023 1
 
3.1%
8001 1
 
3.1%
8103 1
 
3.1%
8007 1
 
3.1%
7901 1
 
3.1%
7904 1
 
3.1%
7999 1
 
3.1%
Other values (17) 17
53.1%
(Missing) 4
 
12.5%
ValueCountFrequency (%)
7901 1
3.1%
7904 1
3.1%
7953 1
3.1%
7994 1
3.1%
7996 1
3.1%
7998 1
3.1%
7999 1
3.1%
8001 1
3.1%
8006 1
3.1%
8007 1
3.1%
ValueCountFrequency (%)
158850 1
3.1%
158837 1
3.1%
158833 2
6.2%
158825 1
3.1%
158823 1
3.1%
158796 1
3.1%
158743 1
3.1%
158710 1
3.1%
158705 1
3.1%
158077 1
3.1%

사업장명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-05-11T14:54:25.190657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length15.5
Mean length9.6875
Min length4

Characters and Unicode

Total characters310
Distinct characters111
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

Unique32 ?
Unique (%)100.0%

Sample

1st row서울교통공사 신정차량사업소
2nd row목동현대자동차정비
3rd row풍양운수(주)
4th row포창운수(주)
5th row선일관광콜택시(주)
ValueCountFrequency (%)
목동점 2
 
4.9%
서울교통공사 1
 
2.4%
신정차량사업소 1
 
2.4%
주)에스비에스 1
 
2.4%
양천구청(목동문화체육센터 1
 
2.4%
양천구청(신월문화체육센터 1
 
2.4%
청학산업(주 1
 
2.4%
한무쇼핑(주)목동점 1
 
2.4%
현대백화점 1
 
2.4%
목동힘찬병원 1
 
2.4%
Other values (30) 30
73.2%
2024-05-11T14:54:25.871033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 19
 
6.1%
) 19
 
6.1%
주 16
 
5.2%
동 14
 
4.5%
목 9
 
2.9%
9
 
2.9%
서 6
 
1.9%
사 6
 
1.9%
터 6
 
1.9%
운 6
 
1.9%
Other values (101) 200
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 258
83.2%
Open Punctuation 20
 
6.5%
Close Punctuation 20
 
6.5%
Space Separator 9
 
2.9%
Uppercase Letter 2
 
0.6%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 16
 
6.2%
동 14
 
5.4%
목 9
 
3.5%
서 6
 
2.3%
사 6
 
2.3%
터 6
 
2.3%
운 6
 
2.3%
화 6
 
2.3%
대 5
 
1.9%
센 5
 
1.9%
Other values (93) 179
69.4%
Open Punctuation
ValueCountFrequency (%)
( 19
95.0%
[ 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 19
95.0%
] 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 258
83.2%
Common 50
 
16.1%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 16
 
6.2%
동 14
 
5.4%
목 9
 
3.5%
서 6
 
2.3%
사 6
 
2.3%
터 6
 
2.3%
운 6
 
2.3%
화 6
 
2.3%
대 5
 
1.9%
센 5
 
1.9%
Other values (93) 179
69.4%
Common
ValueCountFrequency (%)
( 19
38.0%
) 19
38.0%
9
18.0%
] 1
 
2.0%
[ 1
 
2.0%
3 1
 
2.0%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 258
83.2%
ASCII 52
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 19
36.5%
) 19
36.5%
9
17.3%
] 1
 
1.9%
[ 1
 
1.9%
3 1
 
1.9%
K 1
 
1.9%
T 1
 
1.9%
Hangul
ValueCountFrequency (%)
주 16
 
6.2%
동 14
 
5.4%
목 9
 
3.5%
서 6
 
2.3%
사 6
 
2.3%
터 6
 
2.3%
운 6
 
2.3%
화 6
 
2.3%
대 5
 
1.9%
센 5
 
1.9%
Other values (93) 179
69.4%

최종수정일자
Date

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2011-03-29 17:19:08
Maximum2024-03-11 16:47:01
2024-05-11T14:54:26.064677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:26.275243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
U
26 
I
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 26
81.2%
I 6
 
18.8%

Length

2024-05-11T14:54:26.483664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:26.657669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 26
81.2%
i 6
 
18.8%

데이터갱신일자
Date

Distinct23
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2018-10-04 11:12:49
Maximum2023-12-03 00:08:00
2024-05-11T14:54:26.852538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:27.141978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

업태구분명
Categorical

Distinct11
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
<NA>
10 
택시 운송업
8 
자동차 종합 수리업
4 
종합 병원
2 
사업시설 유지관리 서비스업
2 
Other values (6)
6 

Length

Max length14
Median length10
Mean length6.21875
Min length3

Unique

Unique6 ?
Unique (%)18.8%

Sample

1st row철도운송업
2nd row자동차 종합 수리업
3rd row<NA>
4th row택시 운송업
5th row택시 운송업

Common Values

ValueCountFrequency (%)
<NA> 10
31.2%
택시 운송업 8
25.0%
자동차 종합 수리업 4
 
12.5%
종합 병원 2
 
6.2%
사업시설 유지관리 서비스업 2
 
6.2%
철도운송업 1
 
3.1%
시내버스 운송업 1
 
3.1%
기타 발전업 1
 
3.1%
욕탕업 1
 
3.1%
종합 소매업 1
 
3.1%

Length

2024-05-11T14:54:27.421047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 10
17.2%
운송업 9
15.5%
택시 8
13.8%
종합 7
12.1%
자동차 4
 
6.9%
수리업 4
 
6.9%
유지관리 2
 
3.4%
서비스업 2
 
3.4%
사업시설 2
 
3.4%
병원 2
 
3.4%
Other values (8) 8
13.8%

좌표정보(X)
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187067.71
Minimum184242.73
Maximum189878.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-05-11T14:54:27.647779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184242.73
5-th percentile184578.94
Q1185560.23
median187774.13
Q3188535.99
95-th percentile189322.97
Maximum189878.41
Range5635.6773
Interquartile range (IQR)2975.7606

Descriptive statistics

Standard deviation1772.5219
Coefficient of variation (CV)0.0094752959
Kurtosis-1.5968419
Mean187067.71
Median Absolute Deviation (MAD)1579.4083
Skewness-0.1267651
Sum5986166.8
Variance3141834
MonotonicityNot monotonic
2024-05-11T14:54:27.874512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
188012.804745161 1
 
3.1%
189878.40729119 1
 
3.1%
188449.804112163 1
 
3.1%
187925.667553697 1
 
3.1%
188472.759197224 1
 
3.1%
188489.902054043 1
 
3.1%
188656.783840714 1
 
3.1%
184860.070432602 1
 
3.1%
184806.911534822 1
 
3.1%
189047.941727937 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
184242.730019702 1
3.1%
184373.07604881 1
3.1%
184747.377754795 1
3.1%
184806.911534822 1
3.1%
184860.070432602 1
3.1%
185199.68755324 1
3.1%
185335.210131048 1
3.1%
185548.644123279 1
3.1%
185564.093879304 1
3.1%
185578.8443236 1
3.1%
ValueCountFrequency (%)
189878.40729119 1
3.1%
189659.125277836 1
3.1%
189047.941727937 1
3.1%
188904.571764159 1
3.1%
188884.075622342 1
3.1%
188753.192363527 1
3.1%
188656.783840714 1
3.1%
188538.244361038 1
3.1%
188535.241325326 1
3.1%
188489.902054043 1
3.1%

좌표정보(Y)
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447018.18
Minimum444991.87
Maximum449017.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-05-11T14:54:28.108512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444991.87
5-th percentile445219.53
Q1446413.66
median446918.3
Q3447650.76
95-th percentile448766.56
Maximum449017.83
Range4025.9594
Interquartile range (IQR)1237.1005

Descriptive statistics

Standard deviation1113.8562
Coefficient of variation (CV)0.0024917471
Kurtosis-0.67668558
Mean447018.18
Median Absolute Deviation (MAD)557.57345
Skewness0.10773846
Sum14304582
Variance1240675.7
MonotonicityNot monotonic
2024-05-11T14:54:28.332875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
445428.447103333 1
 
3.1%
448255.199632516 1
 
3.1%
446515.366800956 1
 
3.1%
446739.797762899 1
 
3.1%
447091.855963511 1
 
3.1%
444991.866084561 1
 
3.1%
446479.058882981 1
 
3.1%
448949.473058282 1
 
3.1%
448551.489178583 1
 
3.1%
446975.068504489 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
444991.866084561 1
3.1%
445122.597331747 1
3.1%
445298.843582937 1
3.1%
445428.447103333 1
3.1%
445905.159432261 1
3.1%
445949.686943443 1
3.1%
446229.979269615 1
3.1%
446403.139717435 1
3.1%
446417.164914271 1
3.1%
446474.7574493 1
3.1%
ValueCountFrequency (%)
449017.825528364 1
3.1%
448949.473058282 1
3.1%
448616.907017756 1
3.1%
448551.489178583 1
3.1%
448537.930084122 1
3.1%
448381.981336552 1
3.1%
448255.199632516 1
3.1%
448174.209450269 1
3.1%
447476.275717561 1
3.1%
447475.465042757 1
3.1%

환경업무구분명
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
대기배출업소관리
24 
<NA>
8 

Length

Max length8
Median length8
Mean length7
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기배출업소관리 24
75.0%
<NA> 8
 
25.0%

Length

2024-05-11T14:54:28.574106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:28.756347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기배출업소관리 24
75.0%
na 8
 
25.0%

업종구분명
Text

MISSING 

Distinct7
Distinct (%)50.0%
Missing18
Missing (%)56.2%
Memory size388.0 B
2024-05-11T14:54:28.957780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.7857143
Min length5

Characters and Unicode

Total characters95
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)28.6%

Sample

1st row철도운송업
2nd row자동차 종합 수리업
3rd row택시 운송업
4th row택시 운송업
5th row택시 운송업
ValueCountFrequency (%)
운송업 6
20.0%
종합 6
20.0%
택시 5
16.7%
자동차 3
10.0%
수리업 3
10.0%
병원 2
 
6.7%
철도운송업 1
 
3.3%
시내버스 1
 
3.3%
기타 1
 
3.3%
발전업 1
 
3.3%
2024-05-11T14:54:29.527287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
16.8%
업 12
12.6%
운 7
 
7.4%
송 7
 
7.4%
종 6
 
6.3%
합 6
 
6.3%
시 6
 
6.3%
택 5
 
5.3%
자 3
 
3.2%
동 3
 
3.2%
Other values (16) 24
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79
83.2%
Space Separator 16
 
16.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 12
15.2%
운 7
 
8.9%
송 7
 
8.9%
종 6
 
7.6%
합 6
 
7.6%
시 6
 
7.6%
택 5
 
6.3%
자 3
 
3.8%
동 3
 
3.8%
차 3
 
3.8%
Other values (15) 21
26.6%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79
83.2%
Common 16
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 12
15.2%
운 7
 
8.9%
송 7
 
8.9%
종 6
 
7.6%
합 6
 
7.6%
시 6
 
7.6%
택 5
 
6.3%
자 3
 
3.8%
동 3
 
3.8%
차 3
 
3.8%
Other values (15) 21
26.6%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79
83.2%
ASCII 16
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
100.0%
Hangul
ValueCountFrequency (%)
업 12
15.2%
운 7
 
8.9%
송 7
 
8.9%
종 6
 
7.6%
합 6
 
7.6%
시 6
 
7.6%
택 5
 
6.3%
자 3
 
3.8%
동 3
 
3.8%
차 3
 
3.8%
Other values (15) 21
26.6%

종별명
Categorical

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
5종
15 
<NA>
8 
4종
7 
1종
 
1
2종
 
1

Length

Max length4
Median length2
Mean length2.5
Min length2

Unique

Unique2 ?
Unique (%)6.2%

Sample

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

Common Values

ValueCountFrequency (%)
5종 15
46.9%
<NA> 8
25.0%
4종 7
21.9%
1종 1
 
3.1%
2종 1
 
3.1%

Length

2024-05-11T14:54:29.772956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:29.976498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5종 15
46.9%
na 8
25.0%
4종 7
21.9%
1종 1
 
3.1%
2종 1
 
3.1%

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

배출시설조업시간
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)54.2%
Missing8
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean9.5833333
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-05-11T14:54:30.139655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14.5
median8
Q312.25
95-th percentile24
Maximum24
Range23
Interquartile range (IQR)7.75

Descriptive statistics

Standard deviation6.8201534
Coefficient of variation (CV)0.71166818
Kurtosis0.47465287
Mean9.5833333
Median Absolute Deviation (MAD)4.5
Skewness1.022223
Sum230
Variance46.514493
MonotonicityNot monotonic
2024-05-11T14:54:30.339611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
8 6
18.8%
3 3
 
9.4%
24 3
 
9.4%
2 2
 
6.2%
15 2
 
6.2%
1 1
 
3.1%
12 1
 
3.1%
6 1
 
3.1%
10 1
 
3.1%
11 1
 
3.1%
Other values (3) 3
 
9.4%
(Missing) 8
25.0%
ValueCountFrequency (%)
1 1
 
3.1%
2 2
 
6.2%
3 3
9.4%
5 1
 
3.1%
6 1
 
3.1%
8 6
18.8%
9 1
 
3.1%
10 1
 
3.1%
11 1
 
3.1%
12 1
 
3.1%
ValueCountFrequency (%)
24 3
9.4%
15 2
 
6.2%
13 1
 
3.1%
12 1
 
3.1%
11 1
 
3.1%
10 1
 
3.1%
9 1
 
3.1%
8 6
18.8%
6 1
 
3.1%
5 1
 
3.1%

배출시설연간가동일수
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)37.5%
Missing8
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean271
Minimum25
Maximum365
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-05-11T14:54:30.526258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile120
Q1272.5
median300
Q3332
95-th percentile365
Maximum365
Range340
Interquartile range (IQR)59.5

Descriptive statistics

Standard deviation94.168674
Coefficient of variation (CV)0.34748588
Kurtosis0.69308213
Mean271
Median Absolute Deviation (MAD)34
Skewness-1.2788986
Sum6504
Variance8867.7391
MonotonicityNot monotonic
2024-05-11T14:54:30.703766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
300 11
34.4%
365 4
 
12.5%
120 2
 
6.2%
338 2
 
6.2%
25 1
 
3.1%
190 1
 
3.1%
330 1
 
3.1%
123 1
 
3.1%
160 1
 
3.1%
(Missing) 8
25.0%
ValueCountFrequency (%)
25 1
 
3.1%
120 2
 
6.2%
123 1
 
3.1%
160 1
 
3.1%
190 1
 
3.1%
300 11
34.4%
330 1
 
3.1%
338 2
 
6.2%
365 4
 
12.5%
ValueCountFrequency (%)
365 4
 
12.5%
338 2
 
6.2%
330 1
 
3.1%
300 11
34.4%
190 1
 
3.1%
160 1
 
3.1%
123 1
 
3.1%
120 2
 
6.2%
25 1
 
3.1%

방지시설조업시간
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)47.1%
Missing15
Missing (%)46.9%
Infinite0
Infinite (%)0.0%
Mean9.4117647
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-05-11T14:54:30.890548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.8
Q13
median8
Q311
95-th percentile24
Maximum24
Range23
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.6408346
Coefficient of variation (CV)0.81183867
Kurtosis0.3642071
Mean9.4117647
Median Absolute Deviation (MAD)4
Skewness1.1657997
Sum160
Variance58.382353
MonotonicityNot monotonic
2024-05-11T14:54:31.074309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
8 6
 
18.8%
24 3
 
9.4%
2 2
 
6.2%
3 2
 
6.2%
1 1
 
3.1%
6 1
 
3.1%
12 1
 
3.1%
11 1
 
3.1%
(Missing) 15
46.9%
ValueCountFrequency (%)
1 1
 
3.1%
2 2
 
6.2%
3 2
 
6.2%
6 1
 
3.1%
8 6
18.8%
11 1
 
3.1%
12 1
 
3.1%
24 3
9.4%
ValueCountFrequency (%)
24 3
9.4%
12 1
 
3.1%
11 1
 
3.1%
8 6
18.8%
6 1
 
3.1%
3 2
 
6.2%
2 2
 
6.2%
1 1
 
3.1%

방지시설연간가동일수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)30.0%
Missing12
Missing (%)37.5%
Infinite0
Infinite (%)0.0%
Mean243.5
Minimum0
Maximum365
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-05-11T14:54:31.266012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1255
median300
Q3300
95-th percentile365
Maximum365
Range365
Interquartile range (IQR)45

Descriptive statistics

Standard deviation131.34026
Coefficient of variation (CV)0.53938504
Kurtosis-0.16953715
Mean243.5
Median Absolute Deviation (MAD)0
Skewness-1.2290394
Sum4870
Variance17250.263
MonotonicityNot monotonic
2024-05-11T14:54:31.472850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
300 11
34.4%
365 3
 
9.4%
0 3
 
9.4%
120 1
 
3.1%
25 1
 
3.1%
330 1
 
3.1%
(Missing) 12
37.5%
ValueCountFrequency (%)
0 3
 
9.4%
25 1
 
3.1%
120 1
 
3.1%
300 11
34.4%
330 1
 
3.1%
365 3
 
9.4%
ValueCountFrequency (%)
365 3
 
9.4%
330 1
 
3.1%
300 11
34.4%
120 1
 
3.1%
25 1
 
3.1%
0 3
 
9.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
0314000031400002119930001419930526<NA>1영업/정상11영업<NA><NA><NA><NA>02-2646-2802<NA><NA>서울특별시 양천구 신정동 276 신정지하철차량기지서울특별시 양천구 목동로3길 41 (신정동)158705서울교통공사 신정차량사업소2021-11-22 10:09:46U2021-11-24 02:40:00.0철도운송업188012.804745445428.447103대기배출업소관리철도운송업5종<NA>83008300
1314000031400002119940001819940924<NA>1영업/정상11영업<NA><NA><NA><NA>02-2693-1152<NA><NA>서울특별시 양천구 신정동 886-12서울특별시 양천구 신정중앙로 81 (신정동)158074목동현대자동차정비2021-12-27 09:04:18U2021-12-29 02:40:00.0자동차 종합 수리업187622.58282447193.975631대기배출업소관리자동차 종합 수리업5종<NA>83008300
2314000031400002119990002019990524<NA>3폐업2폐업20110329<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 545-5번지서울특별시 양천구 신월로 157 (신월동)<NA>풍양운수(주)2011-03-29 17:19:08I2018-10-04 11:12:49.0<NA>185872.921927446229.97927대기배출업소관리<NA>5종<NA>83008300
3314000031400002119990002119990714<NA>1영업/정상11영업<NA><NA><NA><NA>02-2692-0545<NA><NA>서울특별시 양천구 신월동 437-5서울특별시 양천구 오목로1길 15 (신월동)158833포창운수(주)2022-03-25 16:01:37U2022-03-27 02:40:00.0택시 운송업185564.093879446682.69319대기배출업소관리택시 운송업5종<NA>21202120
4314000031400002119990002219990714<NA>4취소/말소/만료/정지/중지4폐쇄20221025<NA><NA><NA>02-2695-0678<NA><NA>서울특별시 양천구 신월동 437-6서울특별시 양천구 오목로1길 9 (신월동)158833선일관광콜택시(주)2022-10-27 09:00:44U2021-10-30 22:09:00.0택시 운송업185581.30145446647.195269<NA><NA><NA><NA><NA><NA><NA><NA>
531400003140000212001000012019-06-13<NA>1영업/정상11영업<NA><NA><NA><NA>26931001<NA><NA>서울특별시 양천구 신월동 998-3 강성교통서울특별시 양천구 남부순환로72길 5-3, 강성교통 (신월동)8041(주)강성교통2024-01-23 14:56:58U2023-11-30 22:05:00.0택시 운송업185548.644123446474.757449<NA><NA><NA><NA><NA><NA><NA><NA>
6314000031400002120010000220010312<NA>1영업/정상11영업<NA><NA><NA><NA>26025886<NA><NA>서울특별시 양천구 신월동 473-7서울특별시 양천구 중앙로 341-3 (신월동)158837명화운수(주)2022-01-21 09:51:16U2022-01-23 02:40:00.0택시 운송업186586.647972447106.091316대기배출업소관리택시 운송업5종<NA>23002300
7314000031400002120010000320010122<NA>1영업/정상11영업<NA><NA><NA><NA>02-2605-9363<NA><NA>서울특별시 양천구 신월동 1014-6서울특별시 양천구 남부순환로 596 (신월동)8047국도산업(주)2022-04-07 14:25:20U2021-12-04 00:09:00.0택시 운송업185753.07429445949.686943<NA><NA><NA><NA><NA><NA><NA><NA>
8314000031400002120010000420010122<NA>1영업/정상11영업<NA><NA><NA><NA>02-2604-1821<NA><NA>서울특별시 양천구 신월동 47-2서울특별시 양천구 가로공원로 71 (신월동)158823동훈운수(주)2022-02-11 16:47:30U2022-02-13 02:40:00.0택시 운송업184373.076049448174.20945대기배출업소관리택시 운송업5종<NA>33003300
9314000031400002120010000720010307<NA>1영업/정상11영업<NA><NA><NA><NA>02-2691-1177<NA><NA>서울특별시 양천구 신월동 998-1서울특별시 양천구 남부순환로74길 2 (신월동)<NA>삼기통산(주)2021-11-22 09:52:25U2021-11-24 02:40:00.0택시 운송업185578.844324446417.164914대기배출업소관리택시 운송업5종<NA>13001300
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
22314000031400002120150000720151201<NA>3폐업2폐업<NA><NA><NA><NA>0226479613<NA><NA><NA>서울특별시 양천구 오목로 344 (목동, 청학빌딩)8006청학산업(주)2017-06-01 18:16:09I2018-10-04 11:12:49.0<NA>188904.571764446861.525363대기배출업소관리<NA>5종<NA>10120<NA><NA>
23314000031400002120150000920151217<NA>3폐업2폐업20201229<NA><NA><NA>0221633171<NA><NA><NA>서울특별시 양천구 목동동로 257 (목동, 하이페리온)7998한무쇼핑(주)목동점 [현대백화점 목동점]2020-12-31 09:03:08U2021-01-02 02:40:00.0<NA>188884.075622447186.888604대기배출업소관리<NA>5종<NA>1133011330
24314000031400002120150001020151223<NA>4취소/말소/만료/정지/중지4폐쇄20200608<NA><NA><NA>0232199138<NA><NA><NA>서울특별시 양천구 신목로 120 (목동, 힘찬병원)7999목동힘찬병원2020-06-11 12:45:01U2020-06-13 02:40:00.0종합 병원189047.941728446975.068504대기배출업소관리종합 병원4종<NA>13365<NA><NA>
25314000031400002120150001120151228<NA>4취소/말소/만료/정지/중지4폐쇄20220203<NA><NA><NA>0226903460<NA><NA><NA>서울특별시 양천구 화곡로 64 (신월동)7904동화사우나2022-02-03 13:17:28U2022-02-08 02:40:00.0<NA>184806.911535448551.489179대기배출업소관리<NA>4종<NA>2436524365
26314000031400002120150001220151229<NA>1영업/정상11영업<NA><NA><NA><NA>0226941464<NA><NA><NA>서울특별시 양천구 월정로 280 (신월동)7901서울시학생체육관 강서분관2021-04-21 19:01:02U2021-04-23 02:40:00.0<NA>184860.070433448949.473058대기배출업소관리<NA>5종<NA>5123<NA><NA>
2731400003140000212015000142015-12-30<NA>1영업/정상11영업<NA><NA><NA><NA>0226466097<NA><NA><NA>서울특별시 양천구 신목로 53 (목동)8007미진빌딩2024-03-11 16:47:01U2023-12-02 23:03:00.0욕탕업188656.783841446479.058883<NA><NA><NA><NA><NA><NA><NA><NA>
2831400003140000212019000012019-09-27<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 162-6서울특별시 양천구 목동로1길 42 (신정동)8103서울모터스2024-01-12 10:50:02U2023-11-30 23:04:00.0자동차 종합 수리업188489.902054444991.866085<NA><NA><NA><NA><NA><NA><NA><NA>
29314000031400002120210000120211203<NA>1영업/정상11영업<NA><NA><NA><NA>02-6923-1100<NA><NA>서울특별시 양천구 목동 962 목동트라팰리스서울특별시 양천구 오목로 299, 목동트라팰리스 (목동)8001(주)이마트 목동점2021-12-03 17:23:45I2021-12-05 00:22:43.0종합 소매업188472.759197447091.855964대기배출업소관리종합 소매업5종<NA>9160<NA>0
30314000031400002120220000120220617<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1009-6 남부빌딩서울특별시 양천구 신월로 389, 남부빌딩 (신정동)8023남부빌딩 관리단2022-06-20 09:00:22I2021-12-05 22:02:00.0사업시설 유지관리 서비스업187925.667554446739.797763<NA><NA><NA><NA><NA><NA><NA><NA>
31314000031400002120220000220221121<NA>1영업/정상11영업<NA><NA><NA><NA>02-2650-2214<NA><NA>서울특별시 양천구 신정동 319-11 국제템플스테이센터서울특별시 양천구 목동동로 167, 국제템플스테이센터 (신정동)8013대한불교조계종 국제선센터2022-11-30 13:50:38U2021-11-02 00:02:00.0종교 단체188449.804112446515.366801<NA><NA><NA><NA><NA><NA><NA><NA>