Overview

Dataset statistics

Number of variables4
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory36.4 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description인천광역시 계양구 특정토양오염관리대상업체현황에 대한 데이터로서 연번 , 업체명, 도로명주소, 데이터기준일자를 포함하고 있는 있는 데이터파일입니다. 데이터관련은 환경과(450-5405)로 문의바랍니다.
Author인천광역시 계양구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15127346&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
업체명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 09:39:33.139451
Analysis finished2024-04-06 09:39:35.089721
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-04-06T18:39:35.170813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q110.5
median20
Q329.5
95-th percentile37.1
Maximum39
Range38
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.401754
Coefficient of variation (CV)0.57008771
Kurtosis-1.2
Mean20
Median Absolute Deviation (MAD)10
Skewness0
Sum780
Variance130
MonotonicityStrictly increasing
2024-04-06T18:39:35.466589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 1
 
2.6%
2 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
30 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
39 1
2.6%
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%

업체명
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-04-06T18:39:36.375010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9.7179487
Min length4

Characters and Unicode

Total characters379
Distinct characters114
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st rowKH에너지㈜직영에이원주유소
2nd row주식회사 보라미주유소
3rd row동일석유㈜동일주유소
4th row동일석유㈜
5th row미담주유소
ValueCountFrequency (%)
kh에너지㈜직영에이원주유소 1
 
2.3%
박촌주유소 1
 
2.3%
성풍화학 1
 
2.3%
㈜신진에너지 1
 
2.3%
양정셀프주유소 1
 
2.3%
믿음주유소 1
 
2.3%
육군제9100부대 1
 
2.3%
에이치디현대오일뱅크㈜직영오주유소 1
 
2.3%
경동석유산업㈜ 1
 
2.3%
거보주유소 1
 
2.3%
Other values (34) 34
77.3%
2024-04-06T18:39:37.076007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 39
 
10.3%
주 33
 
8.7%
소 29
 
7.7%
㈜ 19
 
5.0%
에 13
 
3.4%
일 10
 
2.6%
지 10
 
2.6%
동 7
 
1.8%
너 7
 
1.8%
오 7
 
1.8%
Other values (104) 205
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 329
86.8%
Other Symbol 19
 
5.0%
Decimal Number 9
 
2.4%
Uppercase Letter 8
 
2.1%
Space Separator 6
 
1.6%
Open Punctuation 4
 
1.1%
Close Punctuation 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 39
 
11.9%
주 33
 
10.0%
소 29
 
8.8%
에 13
 
4.0%
일 10
 
3.0%
지 10
 
3.0%
동 7
 
2.1%
너 7
 
2.1%
오 7
 
2.1%
석 7
 
2.1%
Other values (88) 167
50.8%
Decimal Number
ValueCountFrequency (%)
1 2
22.2%
0 2
22.2%
9 1
11.1%
8 1
11.1%
7 1
11.1%
6 1
11.1%
2 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
K 3
37.5%
S 2
25.0%
C 1
 
12.5%
I 1
 
12.5%
H 1
 
12.5%
Other Symbol
ValueCountFrequency (%)
㈜ 19
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 348
91.8%
Common 23
 
6.1%
Latin 8
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 39
 
11.2%
주 33
 
9.5%
소 29
 
8.3%
㈜ 19
 
5.5%
에 13
 
3.7%
일 10
 
2.9%
지 10
 
2.9%
동 7
 
2.0%
너 7
 
2.0%
오 7
 
2.0%
Other values (89) 174
50.0%
Common
ValueCountFrequency (%)
6
26.1%
( 4
17.4%
) 4
17.4%
1 2
 
8.7%
0 2
 
8.7%
9 1
 
4.3%
8 1
 
4.3%
7 1
 
4.3%
6 1
 
4.3%
2 1
 
4.3%
Latin
ValueCountFrequency (%)
K 3
37.5%
S 2
25.0%
C 1
 
12.5%
I 1
 
12.5%
H 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 329
86.8%
ASCII 31
 
8.2%
None 19
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 39
 
11.9%
주 33
 
10.0%
소 29
 
8.8%
에 13
 
4.0%
일 10
 
3.0%
지 10
 
3.0%
동 7
 
2.1%
너 7
 
2.1%
오 7
 
2.1%
석 7
 
2.1%
Other values (88) 167
50.8%
None
ValueCountFrequency (%)
㈜ 19
100.0%
ASCII
ValueCountFrequency (%)
6
19.4%
( 4
12.9%
) 4
12.9%
K 3
9.7%
1 2
 
6.5%
0 2
 
6.5%
S 2
 
6.5%
9 1
 
3.2%
8 1
 
3.2%
7 1
 
3.2%
Other values (5) 5
16.1%

도로명주소
Text

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-04-06T18:39:37.334572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length18
Mean length17.769231
Min length9

Characters and Unicode

Total characters693
Distinct characters48
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

Unique37 ?
Unique (%)94.9%

Sample

1st row인천광역시 계양구 벌말로 583
2nd row인천광역시 계양구 장기로 9
3rd row인천광역시 계양구 아나지로 283
4th row인천광역시 계양구 아나지로 279
5th row인천광역시 계양구 계양대로 108
ValueCountFrequency (%)
인천광역시 39
25.2%
계양구 39
25.2%
아나지로 12
 
7.7%
벌말로 5
 
3.2%
장제로 4
 
2.6%
경명대로 4
 
2.6%
계양대로16번길 2
 
1.3%
계양대로 2
 
1.3%
봉오대로 2
 
1.3%
942 1
 
0.6%
Other values (45) 45
29.0%
2024-04-06T18:39:37.719875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
16.7%
양 45
 
6.5%
계 43
 
6.2%
시 40
 
5.8%
구 40
 
5.8%
인 39
 
5.6%
광 39
 
5.6%
역 39
 
5.6%
천 39
 
5.6%
로 36
 
5.2%
Other values (38) 217
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 463
66.8%
Space Separator 116
 
16.7%
Decimal Number 114
 
16.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 45
9.7%
계 43
9.3%
시 40
8.6%
구 40
8.6%
인 39
8.4%
광 39
8.4%
역 39
8.4%
천 39
8.4%
로 36
 
7.8%
아 12
 
2.6%
Other values (27) 91
19.7%
Decimal Number
ValueCountFrequency (%)
1 18
15.8%
5 16
14.0%
2 14
12.3%
3 13
11.4%
4 12
10.5%
6 11
9.6%
9 11
9.6%
8 7
 
6.1%
0 6
 
5.3%
7 6
 
5.3%
Space Separator
ValueCountFrequency (%)
116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 463
66.8%
Common 230
33.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 45
9.7%
계 43
9.3%
시 40
8.6%
구 40
8.6%
인 39
8.4%
광 39
8.4%
역 39
8.4%
천 39
8.4%
로 36
 
7.8%
아 12
 
2.6%
Other values (27) 91
19.7%
Common
ValueCountFrequency (%)
116
50.4%
1 18
 
7.8%
5 16
 
7.0%
2 14
 
6.1%
3 13
 
5.7%
4 12
 
5.2%
6 11
 
4.8%
9 11
 
4.8%
8 7
 
3.0%
0 6
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 463
66.8%
ASCII 230
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
50.4%
1 18
 
7.8%
5 16
 
7.0%
2 14
 
6.1%
3 13
 
5.7%
4 12
 
5.2%
6 11
 
4.8%
9 11
 
4.8%
8 7
 
3.0%
0 6
 
2.6%
Hangul
ValueCountFrequency (%)
양 45
9.7%
계 43
9.3%
시 40
8.6%
구 40
8.6%
인 39
8.4%
광 39
8.4%
역 39
8.4%
천 39
8.4%
로 36
 
7.8%
아 12
 
2.6%
Other values (27) 91
19.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-03-25
39 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-25
2nd row2024-03-25
3rd row2024-03-25
4th row2024-03-25
5th row2024-03-25

Common Values

ValueCountFrequency (%)
2024-03-25 39
100.0%

Length

2024-04-06T18:39:37.892229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:39:38.053883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-25 39
100.0%

Interactions

2024-04-06T18:39:34.741661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:39:38.157516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명도로명주소
연번1.0001.0000.933
업체명1.0001.0001.000
도로명주소0.9331.0001.000

Missing values

2024-04-06T18:39:34.956908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:39:35.044428image/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

연번업체명도로명주소데이터기준일자
01KH에너지㈜직영에이원주유소인천광역시 계양구 벌말로 5832024-03-25
12주식회사 보라미주유소인천광역시 계양구 장기로 92024-03-25
23동일석유㈜동일주유소인천광역시 계양구 아나지로 2832024-03-25
34동일석유㈜인천광역시 계양구 아나지로 2792024-03-25
45미담주유소인천광역시 계양구 계양대로 1082024-03-25
56동일석유㈜임학주유소인천광역시 계양구 경명대로 11612024-03-25
67SK에너지(주)하나원주유소인천광역시 계양구 아나지로 4262024-03-25
78삼미상사(주)북인천주유소인천광역시 계양구 경명대로 10822024-03-25
89계현주유소인천광역시 계양구 장제로 12632024-03-25
910에이치디현대오일뱅크㈜직영유화셀프주유소인천광역시 계양구 아나지로 2402024-03-25
연번업체명도로명주소데이터기준일자
2930대한송유관공사경인지사인천광역시 계양구 경기도 고양시 덕양구 중앙로 3232024-03-25
3031성풍화학인천광역시 계양구 계양대로16번길 252024-03-25
3132미래석유㈜미래주유소인천광역시 계양구 경명대로 9662024-03-25
3233명품주유소인천광역시 계양구 경명대로 9712024-03-25
3334삼미상사㈜하늘빛셀프주유소인천광역시 계양구 벌말로 5452024-03-25
3435상야주유소인천광역시 계양구 벌말로584번길 12024-03-25
3536㈜그린에너지인천광역시 계양구 솔고개길 22024-03-25
3637에이치디현대오일뱅크㈜직영계양IC주유소인천광역시 계양구 서부간선로 2502024-03-25
3738씨앤에스유통㈜구도일주유소인천광역시 계양구 봉오대로 3912024-03-25
3839켐텍씨앤피인천광역시 계양구 아나지로 5912024-03-25