Overview

Dataset statistics

Number of variables5
Number of observations80
Missing cells17
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory42.6 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description한국환경공단에서 운영하는 실내공기질 관리 종합정보망(www.inair.or.kr)에 등록된 측정대행업체 목록 정보를 제공합니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15093407/fileData.do

Alerts

전화번호 has 17 (21.2%) missing valuesMissing
번호 has unique valuesUnique
측정대행업체명 has unique valuesUnique
사업장주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:11:48.025703
Analysis finished2023-12-12 02:11:48.823616
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.5
Minimum1
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T11:11:48.943481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.95
Q120.75
median40.5
Q360.25
95-th percentile76.05
Maximum80
Range79
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation23.2379
Coefficient of variation (CV)0.57377531
Kurtosis-1.2
Mean40.5
Median Absolute Deviation (MAD)20
Skewness0
Sum3240
Variance540
MonotonicityStrictly increasing
2023-12-12T11:11:49.151846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
42 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
53 1
 
1.2%
Other values (70) 70
87.5%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%
72 1
1.2%
71 1
1.2%

지역
Categorical

Distinct25
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
경기도
16 
서울시
11 
대구광역시
5 
서울
5 
서울특별시
5 
Other values (20)
38 

Length

Max length7
Median length5
Mean length3.425
Min length2

Unique

Unique10 ?
Unique (%)12.5%

Sample

1st row경기도
2nd row서울시
3rd row경기도
4th row강원도
5th row대구광역시

Common Values

ValueCountFrequency (%)
경기도 16
20.0%
서울시 11
13.8%
대구광역시 5
 
6.2%
서울 5
 
6.2%
서울특별시 5
 
6.2%
부산광역시 4
 
5.0%
경남 4
 
5.0%
광주광역시 4
 
5.0%
강원도 3
 
3.8%
충청남도 3
 
3.8%
Other values (15) 20
25.0%

Length

2023-12-12T11:11:49.379094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 16
20.0%
서울시 11
13.8%
대구광역시 5
 
6.2%
서울 5
 
6.2%
서울특별시 5
 
6.2%
부산광역시 4
 
5.0%
경남 4
 
5.0%
광주광역시 4
 
5.0%
강원도 3
 
3.8%
충청남도 3
 
3.8%
Other values (15) 20
25.0%

측정대행업체명
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-12T11:11:49.674350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length10.2875
Min length3

Characters and Unicode

Total characters823
Distinct characters150
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

Unique80 ?
Unique (%)100.0%

Sample

1st row인에어
2nd row(주)환경연구소 가람솔
3rd row(주)대한환경기술연구소
4th row(주)알렉스분석시험소
5th row주식회사 명문환경연구소
ValueCountFrequency (%)
주식회사 6
 
6.2%
사)대한산업보건협회 3
 
3.1%
산업보건센터 2
 
2.1%
인에어 1
 
1.0%
주)대한환경분석기 1
 
1.0%
주)피켐코리아 1
 
1.0%
한솔환경산업 1
 
1.0%
주)청담이엠텍 1
 
1.0%
한국건설생활환경시험연구원 1
 
1.0%
환경측정분석센터 1
 
1.0%
Other values (78) 78
81.2%
2023-12-12T11:11:50.209102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 61
 
7.4%
( 59
 
7.2%
) 59
 
7.2%
경 45
 
5.5%
환 44
 
5.3%
구 29
 
3.5%
연 28
 
3.4%
소 23
 
2.8%
한 22
 
2.7%
이 17
 
2.1%
Other values (140) 436
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 674
81.9%
Open Punctuation 59
 
7.2%
Close Punctuation 59
 
7.2%
Space Separator 16
 
1.9%
Uppercase Letter 14
 
1.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 61
 
9.1%
경 45
 
6.7%
환 44
 
6.5%
구 29
 
4.3%
연 28
 
4.2%
소 23
 
3.4%
한 22
 
3.3%
이 17
 
2.5%
대 16
 
2.4%
산 16
 
2.4%
Other values (127) 373
55.3%
Uppercase Letter
ValueCountFrequency (%)
I 3
21.4%
E 2
14.3%
S 2
14.3%
H 2
14.3%
B 1
 
7.1%
A 1
 
7.1%
L 1
 
7.1%
T 1
 
7.1%
F 1
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 674
81.9%
Common 135
 
16.4%
Latin 14
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 61
 
9.1%
경 45
 
6.7%
환 44
 
6.5%
구 29
 
4.3%
연 28
 
4.2%
소 23
 
3.4%
한 22
 
3.3%
이 17
 
2.5%
대 16
 
2.4%
산 16
 
2.4%
Other values (127) 373
55.3%
Latin
ValueCountFrequency (%)
I 3
21.4%
E 2
14.3%
S 2
14.3%
H 2
14.3%
B 1
 
7.1%
A 1
 
7.1%
L 1
 
7.1%
T 1
 
7.1%
F 1
 
7.1%
Common
ValueCountFrequency (%)
( 59
43.7%
) 59
43.7%
16
 
11.9%
- 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 674
81.9%
ASCII 149
 
18.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 61
 
9.1%
경 45
 
6.7%
환 44
 
6.5%
구 29
 
4.3%
연 28
 
4.2%
소 23
 
3.4%
한 22
 
3.3%
이 17
 
2.5%
대 16
 
2.4%
산 16
 
2.4%
Other values (127) 373
55.3%
ASCII
ValueCountFrequency (%)
( 59
39.6%
) 59
39.6%
16
 
10.7%
I 3
 
2.0%
E 2
 
1.3%
S 2
 
1.3%
H 2
 
1.3%
B 1
 
0.7%
A 1
 
0.7%
L 1
 
0.7%
Other values (3) 3
 
2.0%

사업장주소
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-12T11:11:50.475826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length33
Mean length27.0125
Min length12

Characters and Unicode

Total characters2161
Distinct characters231
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st row경기도 남양주시 순화궁로 116 202호 별내노블레스
2nd row서울시 금천구 가산디지털2로 184 1005호
3rd row경기도 수원시 팔달구 수성로 92 농민회관 5층(화서동)
4th row강원도 원주시 지정면 청정로 80-1
5th row대구광역시 서구 통학로 86-1, 2층
ValueCountFrequency (%)
경기도 16
 
3.5%
서울시 12
 
2.6%
2층 8
 
1.8%
구로구 6
 
1.3%
금천구 6
 
1.3%
서구 5
 
1.1%
대구광역시 5
 
1.1%
디지털로 5
 
1.1%
서울 5
 
1.1%
광주광역시 4
 
0.9%
Other values (323) 382
84.1%
2023-12-12T11:11:50.943200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
375
 
17.4%
1 88
 
4.1%
로 79
 
3.7%
구 73
 
3.4%
시 72
 
3.3%
2 60
 
2.8%
0 52
 
2.4%
3 49
 
2.3%
경 37
 
1.7%
6 35
 
1.6%
Other values (221) 1241
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1260
58.3%
Decimal Number 409
 
18.9%
Space Separator 375
 
17.4%
Other Punctuation 36
 
1.7%
Open Punctuation 23
 
1.1%
Close Punctuation 23
 
1.1%
Uppercase Letter 21
 
1.0%
Dash Punctuation 13
 
0.6%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 79
 
6.3%
구 73
 
5.8%
시 72
 
5.7%
경 37
 
2.9%
서 33
 
2.6%
대 32
 
2.5%
길 31
 
2.5%
도 30
 
2.4%
호 29
 
2.3%
광 29
 
2.3%
Other values (193) 815
64.7%
Uppercase Letter
ValueCountFrequency (%)
S 4
19.0%
I 3
14.3%
A 3
14.3%
K 2
9.5%
V 2
9.5%
T 2
9.5%
P 1
 
4.8%
D 1
 
4.8%
B 1
 
4.8%
H 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 88
21.5%
2 60
14.7%
0 52
12.7%
3 49
12.0%
6 35
 
8.6%
5 29
 
7.1%
4 26
 
6.4%
9 26
 
6.4%
7 23
 
5.6%
8 21
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 35
97.2%
/ 1
 
2.8%
Space Separator
ValueCountFrequency (%)
375
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1260
58.3%
Common 880
40.7%
Latin 21
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 79
 
6.3%
구 73
 
5.8%
시 72
 
5.7%
경 37
 
2.9%
서 33
 
2.6%
대 32
 
2.5%
길 31
 
2.5%
도 30
 
2.4%
호 29
 
2.3%
광 29
 
2.3%
Other values (193) 815
64.7%
Common
ValueCountFrequency (%)
375
42.6%
1 88
 
10.0%
2 60
 
6.8%
0 52
 
5.9%
3 49
 
5.6%
6 35
 
4.0%
, 35
 
4.0%
5 29
 
3.3%
4 26
 
3.0%
9 26
 
3.0%
Other values (7) 105
 
11.9%
Latin
ValueCountFrequency (%)
S 4
19.0%
I 3
14.3%
A 3
14.3%
K 2
9.5%
V 2
9.5%
T 2
9.5%
P 1
 
4.8%
D 1
 
4.8%
B 1
 
4.8%
H 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1259
58.3%
ASCII 901
41.7%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
375
41.6%
1 88
 
9.8%
2 60
 
6.7%
0 52
 
5.8%
3 49
 
5.4%
6 35
 
3.9%
, 35
 
3.9%
5 29
 
3.2%
4 26
 
2.9%
9 26
 
2.9%
Other values (18) 126
 
14.0%
Hangul
ValueCountFrequency (%)
로 79
 
6.3%
구 73
 
5.8%
시 72
 
5.7%
경 37
 
2.9%
서 33
 
2.6%
대 32
 
2.5%
길 31
 
2.5%
도 30
 
2.4%
호 29
 
2.3%
광 29
 
2.3%
Other values (192) 814
64.7%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%

전화번호
Text

MISSING 

Distinct63
Distinct (%)100.0%
Missing17
Missing (%)21.2%
Memory size772.0 B
2023-12-12T11:11:51.260281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.888889
Min length9

Characters and Unicode

Total characters749
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row031-574-1709
2nd row02-6925-6787
3rd row070-4204-1050
4th row070-4112-2817
5th row053-563-1515
ValueCountFrequency (%)
031-574-1709 1
 
1.6%
051-441-7599 1
 
1.6%
02-852-5583 1
 
1.6%
053-814-5576 1
 
1.6%
042-866-8738 1
 
1.6%
051-506-2828 1
 
1.6%
02-6264-2950 1
 
1.6%
053-563-6806 1
 
1.6%
02-2614-7875 1
 
1.6%
055-249-2773 1
 
1.6%
Other values (53) 53
84.1%
2023-12-12T11:11:51.744060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 124
16.6%
0 114
15.2%
2 77
10.3%
5 76
10.1%
3 61
8.1%
6 61
8.1%
1 57
7.6%
4 55
7.3%
7 52
6.9%
8 47
 
6.3%
Other values (2) 25
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 624
83.3%
Dash Punctuation 124
 
16.6%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 114
18.3%
2 77
12.3%
5 76
12.2%
3 61
9.8%
6 61
9.8%
1 57
9.1%
4 55
8.8%
7 52
8.3%
8 47
7.5%
9 24
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 749
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 124
16.6%
0 114
15.2%
2 77
10.3%
5 76
10.1%
3 61
8.1%
6 61
8.1%
1 57
7.6%
4 55
7.3%
7 52
6.9%
8 47
 
6.3%
Other values (2) 25
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 749
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 124
16.6%
0 114
15.2%
2 77
10.3%
5 76
10.1%
3 61
8.1%
6 61
8.1%
1 57
7.6%
4 55
7.3%
7 52
6.9%
8 47
 
6.3%
Other values (2) 25
 
3.3%

Interactions

2023-12-12T11:11:48.453764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:11:51.883843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역측정대행업체명사업장주소전화번호
번호1.0000.1781.0001.0001.000
지역0.1781.0001.0001.0001.000
측정대행업체명1.0001.0001.0001.0001.000
사업장주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
2023-12-12T11:11:51.995150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역
번호1.0000.000
지역0.0001.000

Missing values

2023-12-12T11:11:48.650724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:11:48.773197image/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

번호지역측정대행업체명사업장주소전화번호
01경기도인에어경기도 남양주시 순화궁로 116 202호 별내노블레스031-574-1709
12서울시(주)환경연구소 가람솔서울시 금천구 가산디지털2로 184 1005호02-6925-6787
23경기도(주)대한환경기술연구소경기도 수원시 팔달구 수성로 92 농민회관 5층(화서동)070-4204-1050
34강원도(주)알렉스분석시험소강원도 원주시 지정면 청정로 80-1070-4112-2817
45대구광역시주식회사 명문환경연구소대구광역시 서구 통학로 86-1, 2층053-563-1515
56경기도(주)케이에스디 성대환경시험연구원경기도 의왕시 갈미2로 30, 7층1577-4446
67서울시한국친환경연구소서울시 금천구 가산디지털ㄹ1로 128, 1601-1호02-3432-8741
78경기도영진환경산업(주)경기도 수원시 권선구 매송고색로634-21031-239-6625
89강원도(주)에코엔비텍강원도 원주시 홍업면 북원로 1389 원주환경친화기술센터 302호<NA>
910부산광역시(주)대한생활환경시험원부산광역시 동래구 아시아드대로 255번길9, 비동 201호051-557-6907
번호지역측정대행업체명사업장주소전화번호
7071서울시상록환경위생(주)서울시 송파구 송파대로 167, 문정역 테라타워 A동 410호02-556-6929
7172부산광역시실내환경연구소(주)부산광역시 해운대구 센텀북대로 60(센텀IS타워, 1609호)051-512-4225
7273서울특별시(주)블루스쿼드서울시 금천구 가산디지털로 16 SK V1 AP타워 916호02-2054-8997
7374충청남도(주)엘지텍충청남도 아산시 배방읍 모산로 124, 2층<NA>
7475전남(재)전라남도환경산업진흥원전남 강진군 성전면 강진산단로1길 1 (재)전라남도환경산업진흥원061-430-8325
7576인천광역시에코앤텍 주식회사인천광역시 미추홀구 소성로 195 (학익동, 2층)032-715-5425
7677대구광역시(주)이앤비테크대구광역시 달성군 옥포면 간경길 20<NA>
7778경기도워터스생활환경연구소경기도 군포시 공단로 140번길 46 12층 군포엠테크노센터02-1544-7712
7879강원도아람기술이앤지(주)강원도 춘천시 칠전동길 31-5033-264-6543
7980세종특별자치시주식회사 세종환경기술개발세종특별자치시 한누리대로 2149, 509호(보람동, 엔젤타워)044-867-0006