Overview

Dataset statistics

Number of variables7
Number of observations127
Missing cells127
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory58.0 B

Variable types

Categorical4
Text3

Dataset

Description2019년부터 2021년까지의 안산시에 있는 소규모 사업장들에 대기오염물질 방지시설 설치를 지원한 현황입니다.
Author경기도 안산시
URLhttps://www.data.go.kr/data/15088416/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
소재지도로명주소 has 15 (11.8%) missing valuesMissing
소재지지번주소 has 112 (88.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:09:41.376161
Analysis finished2023-12-12 18:09:42.184497
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치연도
Categorical

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020
83 
2021
30 
2019
14 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2020 83
65.4%
2021 30
 
23.6%
2019 14
 
11.0%

Length

2023-12-13T03:09:42.281750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:09:42.421954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 83
65.4%
2021 30
 
23.6%
2019 14
 
11.0%

업체명
Text

Distinct125
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T03:09:42.708821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.3070866
Min length2

Characters and Unicode

Total characters801
Distinct characters178
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)96.9%

Sample

1st row(주)선경내셔날
2nd row(주)신동아전자
3rd row성원산업
4th row(주)수신화학
5th row(주)티에스텍
ValueCountFrequency (%)
주식회사 8
 
5.8%
안산공장 2
 
1.4%
서진모터스 2
 
1.4%
성원산업 2
 
1.4%
주)신대양정비 1
 
0.7%
㈜신성프리시젼 1
 
0.7%
㈜파워셀 1
 
0.7%
주)선경내셔날 1
 
0.7%
삼우금속 1
 
0.7%
한성금속 1
 
0.7%
Other values (119) 119
85.6%
2023-12-13T03:09:43.193293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 57
 
7.1%
주 29
 
3.6%
금 28
 
3.5%
속 24
 
3.0%
스 21
 
2.6%
산 19
 
2.4%
( 18
 
2.2%
피 18
 
2.2%
) 18
 
2.2%
사 18
 
2.2%
Other values (168) 551
68.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 693
86.5%
Other Symbol 57
 
7.1%
Open Punctuation 18
 
2.2%
Close Punctuation 18
 
2.2%
Space Separator 12
 
1.5%
Decimal Number 1
 
0.1%
Dash Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 29
 
4.2%
금 28
 
4.0%
속 24
 
3.5%
스 21
 
3.0%
산 19
 
2.7%
피 18
 
2.6%
사 18
 
2.6%
이 18
 
2.6%
업 18
 
2.6%
동 15
 
2.2%
Other values (161) 485
70.0%
Other Symbol
ValueCountFrequency (%)
㈜ 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 750
93.6%
Common 50
 
6.2%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 57
 
7.6%
주 29
 
3.9%
금 28
 
3.7%
속 24
 
3.2%
스 21
 
2.8%
산 19
 
2.5%
피 18
 
2.4%
사 18
 
2.4%
이 18
 
2.4%
업 18
 
2.4%
Other values (162) 500
66.7%
Common
ValueCountFrequency (%)
( 18
36.0%
) 18
36.0%
12
24.0%
1 1
 
2.0%
- 1
 
2.0%
Latin
ValueCountFrequency (%)
E 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 693
86.5%
None 57
 
7.1%
ASCII 51
 
6.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 57
100.0%
Hangul
ValueCountFrequency (%)
주 29
 
4.2%
금 28
 
4.0%
속 24
 
3.5%
스 21
 
3.0%
산 19
 
2.7%
피 18
 
2.6%
사 18
 
2.6%
이 18
 
2.6%
업 18
 
2.6%
동 15
 
2.2%
Other values (161) 485
70.0%
ASCII
ValueCountFrequency (%)
( 18
35.3%
) 18
35.3%
12
23.5%
1 1
 
2.0%
- 1
 
2.0%
E 1
 
2.0%

소재지도로명주소
Text

MISSING 

Distinct107
Distinct (%)95.5%
Missing15
Missing (%)11.8%
Memory size1.1 KiB
2023-12-13T03:09:43.489828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30
Mean length24.821429
Min length18

Characters and Unicode

Total characters2780
Distinct characters79
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

Unique103 ?
Unique (%)92.0%

Sample

1st row경기도 안산시 단원구 별망로159번길 18(성곡동 673-22)
2nd row경기도 안산시 단원구 첨단로 623(원시동)
3rd row경기도 안산시 단원구 해안로213번길 26(원시동)
4th row경기도 안산시 상록구 용담로 83(팔곡이동)
5th row경기도 안산시 상록구 선진로 30(사동)
ValueCountFrequency (%)
경기도 112
18.5%
안산시 112
18.5%
단원구 85
 
14.1%
상록구 25
 
4.1%
산단로 14
 
2.3%
신원로 10
 
1.7%
동산로27번길 7
 
1.2%
별망로 7
 
1.2%
79(성곡동 6
 
1.0%
96 5
 
0.8%
Other values (172) 221
36.6%
2023-12-13T03:09:44.006159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
493
17.7%
산 137
 
4.9%
시 136
 
4.9%
원 124
 
4.5%
안 122
 
4.4%
도 117
 
4.2%
기 116
 
4.2%
경 112
 
4.0%
구 111
 
4.0%
단 106
 
3.8%
Other values (69) 1206
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1675
60.3%
Space Separator 493
 
17.7%
Decimal Number 450
 
16.2%
Open Punctuation 68
 
2.4%
Close Punctuation 68
 
2.4%
Dash Punctuation 22
 
0.8%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 137
 
8.2%
시 136
 
8.1%
원 124
 
7.4%
안 122
 
7.3%
도 117
 
7.0%
기 116
 
6.9%
경 112
 
6.7%
구 111
 
6.6%
단 106
 
6.3%
로 99
 
5.9%
Other values (53) 495
29.6%
Decimal Number
ValueCountFrequency (%)
1 76
16.9%
2 75
16.7%
3 61
13.6%
6 45
10.0%
7 43
9.6%
5 38
8.4%
4 32
7.1%
9 31
6.9%
8 26
 
5.8%
0 23
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
L 2
50.0%
Space Separator
ValueCountFrequency (%)
493
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1675
60.3%
Common 1101
39.6%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 137
 
8.2%
시 136
 
8.1%
원 124
 
7.4%
안 122
 
7.3%
도 117
 
7.0%
기 116
 
6.9%
경 112
 
6.7%
구 111
 
6.6%
단 106
 
6.3%
로 99
 
5.9%
Other values (53) 495
29.6%
Common
ValueCountFrequency (%)
493
44.8%
1 76
 
6.9%
2 75
 
6.8%
( 68
 
6.2%
) 68
 
6.2%
3 61
 
5.5%
6 45
 
4.1%
7 43
 
3.9%
5 38
 
3.5%
4 32
 
2.9%
Other values (4) 102
 
9.3%
Latin
ValueCountFrequency (%)
B 2
50.0%
L 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1675
60.3%
ASCII 1105
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
493
44.6%
1 76
 
6.9%
2 75
 
6.8%
( 68
 
6.2%
) 68
 
6.2%
3 61
 
5.5%
6 45
 
4.1%
7 43
 
3.9%
5 38
 
3.4%
4 32
 
2.9%
Other values (6) 106
 
9.6%
Hangul
ValueCountFrequency (%)
산 137
 
8.2%
시 136
 
8.1%
원 124
 
7.4%
안 122
 
7.3%
도 117
 
7.0%
기 116
 
6.9%
경 112
 
6.7%
구 111
 
6.6%
단 106
 
6.3%
로 99
 
5.9%
Other values (53) 495
29.6%

소재지지번주소
Text

MISSING 

Distinct14
Distinct (%)93.3%
Missing112
Missing (%)88.2%
Memory size1.1 KiB
2023-12-13T03:09:44.219069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length22.4
Min length19

Characters and Unicode

Total characters336
Distinct characters41
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

Unique13 ?
Unique (%)86.7%

Sample

1st row경기도 안산시 단원구 원시동 779-5
2nd row경기도 안산시 단원구 원시동 737-3
3rd row경기도 안산시 상록구 본오동 729-8
4th row경기도 안산시 단원구 원시동 769-1 2호 1층
5th row경기도 안산시 단원구 목내동 446-15 4롯트
ValueCountFrequency (%)
경기도 15
18.5%
안산시 15
18.5%
단원구 12
14.8%
목내동 5
 
6.2%
원시동 4
 
4.9%
성곡동 3
 
3.7%
상록구 3
 
3.7%
395-1 2
 
2.5%
1490-5 1
 
1.2%
632-11 1
 
1.2%
Other values (20) 20
24.7%
2023-12-13T03:09:44.580876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
19.6%
시 19
 
5.7%
원 16
 
4.8%
경 15
 
4.5%
기 15
 
4.5%
구 15
 
4.5%
동 15
 
4.5%
산 15
 
4.5%
안 15
 
4.5%
도 15
 
4.5%
Other values (31) 130
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
55.7%
Decimal Number 67
 
19.9%
Space Separator 66
 
19.6%
Dash Punctuation 14
 
4.2%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 19
10.2%
원 16
8.6%
경 15
8.0%
기 15
8.0%
구 15
8.0%
동 15
8.0%
산 15
8.0%
안 15
8.0%
도 15
8.0%
단 13
 
7.0%
Other values (17) 34
18.2%
Decimal Number
ValueCountFrequency (%)
4 11
16.4%
1 11
16.4%
7 8
11.9%
5 8
11.9%
3 7
10.4%
2 7
10.4%
9 6
9.0%
6 5
7.5%
8 2
 
3.0%
0 2
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
55.7%
Common 147
43.8%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 19
10.2%
원 16
8.6%
경 15
8.0%
기 15
8.0%
구 15
8.0%
동 15
8.0%
산 15
8.0%
안 15
8.0%
도 15
8.0%
단 13
 
7.0%
Other values (17) 34
18.2%
Common
ValueCountFrequency (%)
66
44.9%
- 14
 
9.5%
4 11
 
7.5%
1 11
 
7.5%
7 8
 
5.4%
5 8
 
5.4%
3 7
 
4.8%
2 7
 
4.8%
9 6
 
4.1%
6 5
 
3.4%
Other values (2) 4
 
2.7%
Latin
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187
55.7%
ASCII 149
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
44.3%
- 14
 
9.4%
4 11
 
7.4%
1 11
 
7.4%
7 8
 
5.4%
5 8
 
5.4%
3 7
 
4.7%
2 7
 
4.7%
9 6
 
4.0%
6 5
 
3.4%
Other values (4) 6
 
4.0%
Hangul
ValueCountFrequency (%)
시 19
10.2%
원 16
8.6%
경 15
8.0%
기 15
8.0%
구 15
8.0%
동 15
8.0%
산 15
8.0%
안 15
8.0%
도 15
8.0%
단 13
 
7.0%
Other values (17) 34
18.2%

방지시설종류
Categorical

Distinct11
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
흡수에의한시설
80 
여과및흡착에의한시설
20 
흡착에의한시설
10 
여과집진시설
10 
여과에의한시설
 
1
Other values (6)
 
6

Length

Max length15
Median length7
Mean length7.5905512
Min length3

Unique

Unique7 ?
Unique (%)5.5%

Sample

1st row흡착에의한시설
2nd row흡수에의한시설
3rd row여과에의한시설
4th row흡수에의한시설
5th row흡착에의한시설

Common Values

ValueCountFrequency (%)
흡수에의한시설 80
63.0%
여과및흡착에의한시설 20
 
15.7%
흡착에의한시설 10
 
7.9%
여과집진시설 10
 
7.9%
여과에의한시설 1
 
0.8%
여과에의한시설+흡착에의한시설 1
 
0.8%
RTO 1
 
0.8%
전기집진시설 1
 
0.8%
흡착에의한시설+흡수에의한시설 1
 
0.8%
원심력집진시설+흡수에의한시설 1
 
0.8%

Length

2023-12-13T03:09:44.769411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
흡수에의한시설 80
63.0%
여과및흡착에의한시설 20
 
15.7%
흡착에의한시설 10
 
7.9%
여과집진시설 10
 
7.9%
여과에의한시설 1
 
0.8%
여과에의한시설+흡착에의한시설 1
 
0.8%
rto 1
 
0.8%
전기집진시설 1
 
0.8%
흡착에의한시설+흡수에의한시설 1
 
0.8%
원심력집진시설+흡수에의한시설 1
 
0.8%

시간당 방지 용량(m3 per min)
Categorical

Distinct47
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
400
17 
300
9 
600
 
8
250
 
7
420
 
6
Other values (42)
80 

Length

Max length7
Median length3
Mean length3.2204724
Min length2

Unique

Unique27 ?
Unique (%)21.3%

Sample

1st row250
2nd row440
3rd row450
4th row200
5th row150

Common Values

ValueCountFrequency (%)
400 17
 
13.4%
300 9
 
7.1%
600 8
 
6.3%
250 7
 
5.5%
420 6
 
4.7%
800 6
 
4.7%
1000 5
 
3.9%
550 4
 
3.1%
350 4
 
3.1%
500 4
 
3.1%
Other values (37) 57
44.9%

Length

2023-12-13T03:09:44.913142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
400 17
 
13.4%
300 9
 
7.1%
600 8
 
6.3%
250 7
 
5.5%
420 6
 
4.7%
800 6
 
4.7%
1000 5
 
3.9%
550 4
 
3.1%
350 4
 
3.1%
500 4
 
3.1%
Other values (37) 57
44.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2021-09-10
127 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-10
2nd row2021-09-10
3rd row2021-09-10
4th row2021-09-10
5th row2021-09-10

Common Values

ValueCountFrequency (%)
2021-09-10 127
100.0%

Length

2023-12-13T03:09:45.044162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:09:45.152068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-10 127
100.0%

Correlations

2023-12-13T03:09:45.218377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도소재지지번주소방지시설종류시간당 방지 용량(m3 per min)
설치연도1.0001.0000.4650.280
소재지지번주소1.0001.0001.0000.923
방지시설종류0.4651.0001.0000.824
시간당 방지 용량(m3 per min)0.2800.9230.8241.000
2023-12-13T03:09:45.350456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간당 방지 용량(m3 per min)방지시설종류설치연도
시간당 방지 용량(m3 per min)1.0000.3600.101
방지시설종류0.3601.0000.297
설치연도0.1010.2971.000
2023-12-13T03:09:45.473144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도방지시설종류시간당 방지 용량(m3 per min)
설치연도1.0000.2970.101
방지시설종류0.2971.0000.360
시간당 방지 용량(m3 per min)0.1010.3601.000

Missing values

2023-12-13T03:09:41.781322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:09:41.916584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-13T03:09:42.084469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

설치연도업체명소재지도로명주소소재지지번주소방지시설종류시간당 방지 용량(m3 per min)데이터기준일자
02019(주)선경내셔날경기도 안산시 단원구 별망로159번길 18(성곡동 673-22)<NA>흡착에의한시설2502021-09-10
12019(주)신동아전자<NA>경기도 안산시 단원구 원시동 779-5흡수에의한시설4402021-09-10
22019성원산업경기도 안산시 단원구 첨단로 623(원시동)<NA>여과에의한시설4502021-09-10
32019(주)수신화학경기도 안산시 단원구 해안로213번길 26(원시동)<NA>흡수에의한시설2002021-09-10
42019(주)티에스텍<NA>경기도 안산시 단원구 원시동 737-3흡착에의한시설1502021-09-10
52019(주)신대양정비경기도 안산시 상록구 용담로 83(팔곡이동)<NA>여과및흡착에의한시설3802021-09-10
62019안산사동자동차공업사경기도 안산시 상록구 선진로 30(사동)<NA>여과및흡착에의한시설3802021-09-10
72019경수산업경기도 안산시 단원구 성곡로 134번길 24(성곡동)<NA>흡착에의한시설3502021-09-10
82019명성금속경기도 안산시 단원구 동산로27번길 96 01-4<NA>흡수에의한시설5002021-09-10
92019세기자동차정비㈜경기도 안산시 상록구 선진안길 25(사동)<NA>여과및흡착에의한시설4202021-09-10
설치연도업체명소재지도로명주소소재지지번주소방지시설종류시간당 방지 용량(m3 per min)데이터기준일자
1172021㈜이피코리아경기도 안산시 상록구 도금단지2길 22<NA>흡수에의한시설5002021-09-10
1182021(주)대천텍스타일경기도 안산시 단원구 신안산대학로 29(초지동)<NA>흡수에의한시설2502021-09-10
1192021백상산업경기도 안산시 단원구 해안로 85(목내동)<NA>흡수에의한시설15002021-09-10
1202021스탠다드인터내셔널(주)경기도 안산시 단원구 신원로 355<NA>여과집진시설6502021-09-10
1212021평안제관(주)금속인쇄공장경기도 안산시 단원구 별망로 521<NA>흡착에의한시설7002021-09-10
1222021㈜몰텍스안산경기도 안산시 상록구 안산테콤길 57 (사사동)<NA>흡수에의한시설2302021-09-10
1232021(주)하이피텍경기도 안산시 단원구 산단로 35번길36(원시동)<NA>흡수에의한시설8002021-09-10
1242021㈜동진엠아이 안산지점경기도 안산시 단원구 지원로115번길 26(성곡동)<NA>여과집진시설7202021-09-10
1252021(주)라온씨앤에프경기도 안산시 단원구 번영로 94번길 35 (성곡동)<NA>여과집진시설3002021-09-10
1262021(주)경기금속경기도 안산시 단원구 범지기로 40<NA>흡수에의한시설9302021-09-10