Overview

Dataset statistics

Number of variables5
Number of observations40
Missing cells14
Missing cells (%)7.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory43.3 B

Variable types

Categorical2
Text3

Dataset

Description인천광역시 계양구 관내 사업장 폐기물 처리업체에 대한 데이터로, 폐기물종류, 업종, 업체명, 소재지 주소, 연락처 등을 제공합니다.
Author인천광역시 계양구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3078031&srcSe=7661IVAWM27C61E190

Alerts

업종 is highly overall correlated with 폐기물종류High correlation
폐기물종류 is highly overall correlated with 업종High correlation
폐기물종류 is highly imbalanced (50.9%)Imbalance
업종 is highly imbalanced (71.4%)Imbalance
연락처 has 14 (35.0%) missing valuesMissing

Reproduction

Analysis started2024-01-28 13:59:41.778620
Analysis finished2024-01-28 13:59:42.155584
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

폐기물종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
사업장배출시설
32 
사업장비배출시설
폐기물재활용업
 
2
폐기물처분업
 
1

Length

Max length8
Median length7
Mean length7.1
Min length6

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
사업장배출시설 32
80.0%
사업장비배출시설 5
 
12.5%
폐기물재활용업 2
 
5.0%
폐기물처분업 1
 
2.5%

Length

2024-01-28T22:59:42.218447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:59:42.325636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장배출시설 32
80.0%
사업장비배출시설 5
 
12.5%
폐기물재활용업 2
 
5.0%
폐기물처분업 1
 
2.5%

업종
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
수집운반업
37 
중간재활용
 
2
중간처분
 
1

Length

Max length5
Median length5
Mean length4.975
Min length4

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
수집운반업 37
92.5%
중간재활용 2
 
5.0%
중간처분 1
 
2.5%

Length

2024-01-28T22:59:42.422535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:59:42.522767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수집운반업 37
92.5%
중간재활용 2
 
5.0%
중간처분 1
 
2.5%
Distinct35
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-01-28T22:59:42.709854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length5.725
Min length2

Characters and Unicode

Total characters229
Distinct characters93
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)77.5%

Sample

1st row㈜오성자원
2nd row동부환경개발㈜
3rd row㈜주일도시개발
4th row㈜우인종합물류
5th row㈜구룡산업
ValueCountFrequency (%)
㈜오성자원 3
 
7.1%
㈜휴먼랜드 2
 
4.8%
㈜우인종합물류 2
 
4.8%
우성환경개발㈜ 2
 
4.8%
주식회사 1
 
2.4%
인성환경 1
 
2.4%
씨티에스(cts 1
 
2.4%
echo 1
 
2.4%
조양인더스트리㈜ 1
 
2.4%
㈜제이케이물류 1
 
2.4%
Other values (27) 27
64.3%
2024-01-28T22:59:43.011325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
 
9.6%
18
 
7.9%
17
 
7.4%
7
 
3.1%
7
 
3.1%
7
 
3.1%
6
 
2.6%
5
 
2.2%
5
 
2.2%
5
 
2.2%
Other values (83) 130
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 196
85.6%
Other Symbol 22
 
9.6%
Uppercase Letter 7
 
3.1%
Space Separator 2
 
0.9%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
9.2%
17
 
8.7%
7
 
3.6%
7
 
3.6%
7
 
3.6%
6
 
3.1%
5
 
2.6%
5
 
2.6%
5
 
2.6%
5
 
2.6%
Other values (73) 114
58.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
O 1
14.3%
H 1
14.3%
E 1
14.3%
S 1
14.3%
T 1
14.3%
Other Symbol
ValueCountFrequency (%)
22
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 218
95.2%
Latin 7
 
3.1%
Common 4
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
22
 
10.1%
18
 
8.3%
17
 
7.8%
7
 
3.2%
7
 
3.2%
7
 
3.2%
6
 
2.8%
5
 
2.3%
5
 
2.3%
5
 
2.3%
Other values (74) 119
54.6%
Latin
ValueCountFrequency (%)
C 2
28.6%
O 1
14.3%
H 1
14.3%
E 1
14.3%
S 1
14.3%
T 1
14.3%
Common
ValueCountFrequency (%)
2
50.0%
) 1
25.0%
( 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 196
85.6%
None 22
 
9.6%
ASCII 11
 
4.8%

Most frequent character per block

None
ValueCountFrequency (%)
22
100.0%
Hangul
ValueCountFrequency (%)
18
 
9.2%
17
 
8.7%
7
 
3.6%
7
 
3.6%
7
 
3.6%
6
 
3.1%
5
 
2.6%
5
 
2.6%
5
 
2.6%
5
 
2.6%
Other values (73) 114
58.2%
ASCII
ValueCountFrequency (%)
C 2
18.2%
2
18.2%
O 1
9.1%
H 1
9.1%
E 1
9.1%
) 1
9.1%
S 1
9.1%
( 1
9.1%
T 1
9.1%
Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-01-28T22:59:43.265103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length37
Mean length30.05
Min length22

Characters and Unicode

Total characters1202
Distinct characters83
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)90.0%

Sample

1st row인천광역시 계양구 아나지로 438번길 16(작전동)
2nd row인천광역시 계양구 아나지로 575(서운동)
3rd row인천광역시 계양구 서운로 43-15, 1층(서운동)
4th row인천광역시 계양구 계양문화로 86, 215호(계산동)
5th row인천광역시 계양구 아나지로 247번길 11, 모닝프라자 105호(효성동)
ValueCountFrequency (%)
인천광역시 40
18.6%
계양구 40
18.6%
계양문화로 12
 
5.6%
아나지로 8
 
3.7%
48 4
 
1.9%
계산동 3
 
1.4%
86 3
 
1.4%
54 3
 
1.4%
작전동 2
 
0.9%
1층(선주지동 2
 
0.9%
Other values (92) 98
45.6%
2024-01-28T22:59:43.625285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
 
14.6%
66
 
5.5%
1 57
 
4.7%
52
 
4.3%
47
 
3.9%
40
 
3.3%
40
 
3.3%
40
 
3.3%
40
 
3.3%
40
 
3.3%
Other values (73) 604
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 680
56.6%
Decimal Number 231
 
19.2%
Space Separator 176
 
14.6%
Open Punctuation 38
 
3.2%
Close Punctuation 38
 
3.2%
Other Punctuation 25
 
2.1%
Dash Punctuation 12
 
1.0%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
66
 
9.7%
52
 
7.6%
47
 
6.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
39
 
5.7%
Other values (56) 236
34.7%
Decimal Number
ValueCountFrequency (%)
1 57
24.7%
4 32
13.9%
5 26
11.3%
0 25
10.8%
8 23
10.0%
7 17
 
7.4%
2 16
 
6.9%
3 16
 
6.9%
6 11
 
4.8%
9 8
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 680
56.6%
Common 520
43.3%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
66
 
9.7%
52
 
7.6%
47
 
6.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
39
 
5.7%
Other values (56) 236
34.7%
Common
ValueCountFrequency (%)
176
33.8%
1 57
 
11.0%
( 38
 
7.3%
) 38
 
7.3%
4 32
 
6.2%
5 26
 
5.0%
0 25
 
4.8%
, 25
 
4.8%
8 23
 
4.4%
7 17
 
3.3%
Other values (5) 63
 
12.1%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 680
56.6%
ASCII 522
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
33.7%
1 57
 
10.9%
( 38
 
7.3%
) 38
 
7.3%
4 32
 
6.1%
5 26
 
5.0%
0 25
 
4.8%
, 25
 
4.8%
8 23
 
4.4%
7 17
 
3.3%
Other values (7) 65
 
12.5%
Hangul
ValueCountFrequency (%)
66
 
9.7%
52
 
7.6%
47
 
6.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
39
 
5.7%
Other values (56) 236
34.7%

연락처
Text

MISSING 

Distinct21
Distinct (%)80.8%
Missing14
Missing (%)35.0%
Memory size452.0 B
2024-01-28T22:59:43.794511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters312
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

Unique17 ?
Unique (%)65.4%

Sample

1st row032-551-0787
2nd row032-553-2255
3rd row032-543-6400
4th row032-543-2381
5th row032-556-1980
ValueCountFrequency (%)
032-551-0787 3
 
11.5%
032-503-3366 2
 
7.7%
032-555-6255 2
 
7.7%
032-543-2381 2
 
7.7%
032-221-0853 1
 
3.8%
032-554-1118 1
 
3.8%
032-671-9888 1
 
3.8%
032-547-2230 1
 
3.8%
032-554-5872 1
 
3.8%
032-569-4427 1
 
3.8%
Other values (11) 11
42.3%
2024-01-28T22:59:44.059206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
16.7%
5 49
15.7%
3 46
14.7%
2 46
14.7%
0 36
11.5%
4 16
 
5.1%
7 15
 
4.8%
1 14
 
4.5%
8 14
 
4.5%
6 14
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 260
83.3%
Dash Punctuation 52
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 49
18.8%
3 46
17.7%
2 46
17.7%
0 36
13.8%
4 16
 
6.2%
7 15
 
5.8%
1 14
 
5.4%
8 14
 
5.4%
6 14
 
5.4%
9 10
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 52
16.7%
5 49
15.7%
3 46
14.7%
2 46
14.7%
0 36
11.5%
4 16
 
5.1%
7 15
 
4.8%
1 14
 
4.5%
8 14
 
4.5%
6 14
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
16.7%
5 49
15.7%
3 46
14.7%
2 46
14.7%
0 36
11.5%
4 16
 
5.1%
7 15
 
4.8%
1 14
 
4.5%
8 14
 
4.5%
6 14
 
4.5%

Correlations

2024-01-28T22:59:44.140959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물종류업종업체명소재지연락처
폐기물종류1.0001.0000.0000.0000.000
업종1.0001.0000.0000.0000.000
업체명0.0000.0001.0001.0001.000
소재지0.0000.0001.0001.0001.000
연락처0.0000.0001.0001.0001.000
2024-01-28T22:59:44.233582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종폐기물종류
업종1.0000.986
폐기물종류0.9861.000
2024-01-28T22:59:44.306349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물종류업종
폐기물종류1.0000.986
업종0.9861.000

Missing values

2024-01-28T22:59:42.047223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T22:59:42.125309image/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.

Sample

폐기물종류업종업체명소재지연락처
0사업장배출시설수집운반업㈜오성자원인천광역시 계양구 아나지로 438번길 16(작전동)032-551-0787
1사업장배출시설수집운반업동부환경개발㈜인천광역시 계양구 아나지로 575(서운동)032-553-2255
2사업장배출시설수집운반업㈜주일도시개발인천광역시 계양구 서운로 43-15, 1층(서운동)032-543-6400
3사업장배출시설수집운반업㈜우인종합물류인천광역시 계양구 계양문화로 86, 215호(계산동)032-543-2381
4사업장배출시설수집운반업㈜구룡산업인천광역시 계양구 아나지로 247번길 11, 모닝프라자 105호(효성동)032-556-1980
5사업장배출시설수집운반업이룸인천광역시 계양구 안남로573번길 18 상가동 116호(효성동)032-547-2753
6사업장배출시설수집운반업한도환경인천광역시 계양구 아나지로 187번길 11(효성동)032-424-1675
7사업장배출시설수집운반업㈜수재환경인천광역시 계양구 주부토로 467, 4층 404호(작전동)032-259-2599
8사업장배출시설수집운반업대호환경자원인천광역시 계양구 임학동로 55번길 7(임학동)032-512-8256
9사업장배출시설수집운반업산호환경인천광역시 계양구 장제로 920번길 33032-546-9349
폐기물종류업종업체명소재지연락처
30사업장배출시설수집운반업조양인더스트리㈜인천광역시 계양구 계산새로 71, A동 1419호 (계산동)032-554-5872
31사업장배출시설수집운반업씨티에스(CTS) ECHO인천광역시 계양구 계양문화로 90, 5층 504-B호 (용종동)<NA>
32사업장비배출시설수집운반업㈜오성자원인천광역시 계양구 작전동 610-8(작전동)032-551-0787
33사업장비배출시설수집운반업인성환경인천광역시 계양구 아나지로 577(서운동)032-555-6255
34사업장비배출시설수집운반업㈜우인종합물류인천광역시 계양구 계양문화로 86, 대우프라자032-543-2381
35사업장비배출시설수집운반업㈜휴먼랜드인천광역시 계양구 선주로 48-18 1층(선주지동)032-503-3366
36사업장비배출시설수집운반업우성환경개발㈜인천광역시 계양구 계양문화로 54, 505호 (계산동)032-547-2230
37폐기물처분업중간처분㈜오성자원인천광역시 계양구 아나지로 438번길 16(작전동)032-551-0787
38폐기물재활용업중간재활용키움산업인천광역시 계양구 안남로 457번길 14(효성동)032-671-9888
39폐기물재활용업중간재활용파트너환경㈜인천광역시 계양구 아나지로 586(서운동)032-543-9936