Overview

Dataset statistics

Number of variables4
Number of observations69
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory34.9 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description부산광역시 사상구 관내 특정토양오염관리대상시설에 대한 데이터로 업종, 상호, 소재지 등이 포함된 현황에 관한 데이터입니다.
URLhttps://www.data.go.kr/data/15034131/fileData.do

Alerts

연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:41:47.035956
Analysis finished2023-12-12 22:41:47.524169
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35
Minimum1
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-13T07:41:47.610879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q118
median35
Q352
95-th percentile65.6
Maximum69
Range68
Interquartile range (IQR)34

Descriptive statistics

Standard deviation20.062403
Coefficient of variation (CV)0.5732115
Kurtosis-1.2
Mean35
Median Absolute Deviation (MAD)17
Skewness0
Sum2415
Variance402.5
MonotonicityStrictly increasing
2023-12-13T07:41:47.770864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
45 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
46 1
 
1.4%
44 1
 
1.4%
53 1
 
1.4%
Other values (59) 59
85.5%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%
60 1
1.4%

업소명
Text

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-13T07:41:48.041670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length8.2173913
Min length3

Characters and Unicode

Total characters567
Distinct characters138
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

Unique69 ?
Unique (%)100.0%

Sample

1st row중앙주유소
2nd row대림주유소
3rd row조광페인트㈜
4th row흥일주유소㈜
5th row지에스칼텍스(주)서부주유소
ValueCountFrequency (%)
직영 3
 
3.5%
㈜성은에너지 2
 
2.3%
㈜덕양에너지 2
 
2.3%
중앙주유소 1
 
1.2%
경동주유소 1
 
1.2%
㈜지오에너지 1
 
1.2%
행복한셀프주유소 1
 
1.2%
㈜부경에너지 1
 
1.2%
아산주유소 1
 
1.2%
구룡주유소 1
 
1.2%
Other values (72) 72
83.7%
2023-12-13T07:41:48.470693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 57
 
10.1%
주 50
 
8.8%
소 45
 
7.9%
㈜ 37
 
6.5%
17
 
3.0%
지 15
 
2.6%
에 14
 
2.5%
스 13
 
2.3%
동 11
 
1.9%
대 10
 
1.8%
Other values (128) 298
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
86.6%
Other Symbol 37
 
6.5%
Space Separator 17
 
3.0%
Uppercase Letter 7
 
1.2%
Open Punctuation 6
 
1.1%
Close Punctuation 6
 
1.1%
Decimal Number 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 57
 
11.6%
주 50
 
10.2%
소 45
 
9.2%
지 15
 
3.1%
에 14
 
2.9%
스 13
 
2.6%
동 11
 
2.2%
대 10
 
2.0%
너 9
 
1.8%
영 9
 
1.8%
Other values (115) 258
52.5%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
S 1
14.3%
I 1
14.3%
P 1
14.3%
O 1
14.3%
T 1
14.3%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
2 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 37
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 528
93.1%
Common 32
 
5.6%
Latin 7
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 57
 
10.8%
주 50
 
9.5%
소 45
 
8.5%
㈜ 37
 
7.0%
지 15
 
2.8%
에 14
 
2.7%
스 13
 
2.5%
동 11
 
2.1%
대 10
 
1.9%
너 9
 
1.7%
Other values (116) 267
50.6%
Common
ValueCountFrequency (%)
17
53.1%
( 6
 
18.8%
) 6
 
18.8%
3 1
 
3.1%
2 1
 
3.1%
& 1
 
3.1%
Latin
ValueCountFrequency (%)
C 2
28.6%
S 1
14.3%
I 1
14.3%
P 1
14.3%
O 1
14.3%
T 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
86.6%
ASCII 39
 
6.9%
None 37
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 57
 
11.6%
주 50
 
10.2%
소 45
 
9.2%
지 15
 
3.1%
에 14
 
2.9%
스 13
 
2.6%
동 11
 
2.2%
대 10
 
2.0%
너 9
 
1.8%
영 9
 
1.8%
Other values (115) 258
52.5%
None
ValueCountFrequency (%)
㈜ 37
100.0%
ASCII
ValueCountFrequency (%)
17
43.6%
( 6
 
15.4%
) 6
 
15.4%
C 2
 
5.1%
S 1
 
2.6%
3 1
 
2.6%
2 1
 
2.6%
I 1
 
2.6%
P 1
 
2.6%
O 1
 
2.6%
Other values (2) 2
 
5.1%

소재지
Text

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-13T07:41:48.787568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length23.507246
Min length20

Characters and Unicode

Total characters1622
Distinct characters55
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)100.0%

Sample

1st row부산광역시 사상구 낙동대로 1316(삼락동)
2nd row부산광역시 사상구 낙동대로 1320(삼락동)
3rd row부산광역시 사상구 삼덕로5번길 148(삼락동)
4th row부산광역시 사상구 낙동대로 1520(삼락동)
5th row부산광역시 사상구 낙동대로 1380(삼락동)
ValueCountFrequency (%)
부산광역시 69
25.0%
사상구 69
25.0%
낙동대로 17
 
6.2%
가야대로 7
 
2.5%
학감대로 7
 
2.5%
백양대로 6
 
2.2%
새벽로 4
 
1.4%
사상로 3
 
1.1%
학장로 2
 
0.7%
105(감전동 2
 
0.7%
Other values (86) 90
32.6%
2023-12-13T07:41:49.217684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
207
 
12.8%
동 89
 
5.5%
사 74
 
4.6%
상 74
 
4.6%
시 71
 
4.4%
산 70
 
4.3%
) 69
 
4.3%
( 69
 
4.3%
로 69
 
4.3%
부 69
 
4.3%
Other values (45) 761
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1044
64.4%
Decimal Number 228
 
14.1%
Space Separator 207
 
12.8%
Close Punctuation 69
 
4.3%
Open Punctuation 69
 
4.3%
Dash Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 89
 
8.5%
사 74
 
7.1%
상 74
 
7.1%
시 71
 
6.8%
산 70
 
6.7%
로 69
 
6.6%
부 69
 
6.6%
광 69
 
6.6%
역 69
 
6.6%
구 69
 
6.6%
Other values (31) 321
30.7%
Decimal Number
ValueCountFrequency (%)
1 35
15.4%
3 28
12.3%
7 27
11.8%
0 26
11.4%
9 23
10.1%
4 21
9.2%
2 21
9.2%
5 18
7.9%
8 17
7.5%
6 12
 
5.3%
Space Separator
ValueCountFrequency (%)
207
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1044
64.4%
Common 578
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 89
 
8.5%
사 74
 
7.1%
상 74
 
7.1%
시 71
 
6.8%
산 70
 
6.7%
로 69
 
6.6%
부 69
 
6.6%
광 69
 
6.6%
역 69
 
6.6%
구 69
 
6.6%
Other values (31) 321
30.7%
Common
ValueCountFrequency (%)
207
35.8%
) 69
 
11.9%
( 69
 
11.9%
1 35
 
6.1%
3 28
 
4.8%
7 27
 
4.7%
0 26
 
4.5%
9 23
 
4.0%
4 21
 
3.6%
2 21
 
3.6%
Other values (4) 52
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1044
64.4%
ASCII 578
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
207
35.8%
) 69
 
11.9%
( 69
 
11.9%
1 35
 
6.1%
3 28
 
4.8%
7 27
 
4.7%
0 26
 
4.5%
9 23
 
4.0%
4 21
 
3.6%
2 21
 
3.6%
Other values (4) 52
 
9.0%
Hangul
ValueCountFrequency (%)
동 89
 
8.5%
사 74
 
7.1%
상 74
 
7.1%
시 71
 
6.8%
산 70
 
6.7%
로 69
 
6.6%
부 69
 
6.6%
광 69
 
6.6%
역 69
 
6.6%
구 69
 
6.6%
Other values (31) 321
30.7%

업종
Categorical

Distinct4
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size684.0 B
주유소
46 
산업체
15 
석유류판매
6 
유독물
 
2

Length

Max length5
Median length3
Mean length3.173913
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주유소
2nd row주유소
3rd row산업체
4th row주유소
5th row주유소

Common Values

ValueCountFrequency (%)
주유소 46
66.7%
산업체 15
 
21.7%
석유류판매 6
 
8.7%
유독물 2
 
2.9%

Length

2023-12-13T07:41:49.376704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:41:49.555288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주유소 46
66.7%
산업체 15
 
21.7%
석유류판매 6
 
8.7%
유독물 2
 
2.9%

Interactions

2023-12-13T07:41:47.270725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:41:49.649549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명소재지업종
연번1.0001.0001.0000.143
업소명1.0001.0001.0001.000
소재지1.0001.0001.0001.000
업종0.1431.0001.0001.000
2023-12-13T07:41:49.764725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.069
업종0.0691.000

Missing values

2023-12-13T07:41:47.404788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:41:47.494882image/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

연번업소명소재지업종
01중앙주유소부산광역시 사상구 낙동대로 1316(삼락동)주유소
12대림주유소부산광역시 사상구 낙동대로 1320(삼락동)주유소
23조광페인트㈜부산광역시 사상구 삼덕로5번길 148(삼락동)산업체
34흥일주유소㈜부산광역시 사상구 낙동대로 1520(삼락동)주유소
45지에스칼텍스(주)서부주유소부산광역시 사상구 낙동대로 1380(삼락동)주유소
56현대오일뱅크㈜직영 낙동로주유소부산광역시 사상구 낙동대로 1274(삼락동)주유소
67㈜엔티케이부산광역시 사상구 낙동대로 1346(삼락동)석유류판매
78㈜동일주유소부산광역시 사상구 사상로 456(모라동)주유소
89대원석유상사부산광역시 사상구 모라로 28-3(모라동)석유류판매
910성경주유소부산광역시 사상구 모덕로 69(모라동)주유소
연번업소명소재지업종
5960서부산IC주유소부산광역시 사상구 학감대로 170(학장동)주유소
6061대흥주유소부산광역시 사상구 새벽로 2(학장동)주유소
6162가락타운주유소부산광역시 사상구 낙동대로 730(엄궁동)주유소
6263농산물주유소부산광역시 사상구 농산물시장로25번길 94(엄궁동)주유소
6364㈜성은에너지 자이언트주유소(제2주유소)부산광역시 사상구 강변대로 458(엄궁동)주유소
6465대동주유소부산광역시 사상구 낙동대로 681(엄궁동)주유소
6566㈜유창주유소부산광역시 사상구 낙동대로 753(엄궁동)주유소
6667㈜호림에너지부산광역시 사상구 낙동대로 669(엄궁동)주유소
6768㈜성은에너지 제3주유소부산광역시 사상구 강변대로 412(엄궁동)주유소
6869부산서부버스터미널㈜부산광역시 사상구 사상로 201(괘법동)산업체