Overview

Dataset statistics

Number of variables11
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory94.3 B

Variable types

Numeric3
Text4
Categorical4

Dataset

Description대전광역시 서구 휘발성유기화합물 배출시설 현황데이터입니다.(순번, 업소명, 소재지, 지번주소, 도로명주소, 행정동명, 행정동코드, 법정동명, 법정동코드, 업종, 오염물질)
URLhttps://www.data.go.kr/data/15104536/fileData.do

Alerts

업종 has constant value ""Constant
오염물질 has constant value ""Constant
법정동명 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
행정동명 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
행정동코드 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
순번 has unique valuesUnique
업소명 has unique valuesUnique
소재지 has unique valuesUnique
지번주소 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:23:04.551893
Analysis finished2023-12-12 09:23:06.307905
Duration1.76 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.025
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T18:23:06.420604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q111.75
median21.5
Q332.5
95-th percentile41.05
Maximum43
Range42
Interquartile range (IQR)20.75

Descriptive statistics

Standard deviation12.595252
Coefficient of variation (CV)0.57186163
Kurtosis-1.1832658
Mean22.025
Median Absolute Deviation (MAD)10.5
Skewness0.040429133
Sum881
Variance158.64038
MonotonicityStrictly increasing
2023-12-12T18:23:06.593983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
23 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
32 1
 
2.5%
34 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
11 1
2.5%
ValueCountFrequency (%)
43 1
2.5%
42 1
2.5%
41 1
2.5%
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%

업소명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:23:06.808627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length21
Mean length11.275
Min length5

Characters and Unicode

Total characters451
Distinct characters119
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

Unique40 ?
Unique (%)100.0%

Sample

1st row에이치디현대오일뱅크㈜직영신대전셀프주유소
2nd row주식회사 제이비엘티디(구-선진주유소)
3rd row㈜연정 주홍셀프
4th row코끼리셀프주유소
5th row유진주유소
ValueCountFrequency (%)
둔산주유소 2
 
4.3%
㈜에너비즈 2
 
4.3%
주식회사 2
 
4.3%
백산주유소 1
 
2.2%
도마진실주유소(구-은하수self주유소 1
 
2.2%
갈마주유소 1
 
2.2%
씨앤에스유통㈜구도일주유소도안신도시 1
 
2.2%
중도석유㈜월드컵주유소 1
 
2.2%
중도석유㈜도마동주유소 1
 
2.2%
중도석유㈜대덕주유소 1
 
2.2%
Other values (33) 33
71.7%
2023-12-12T18:23:07.221431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 52
 
11.5%
주 48
 
10.6%
소 44
 
9.8%
㈜ 21
 
4.7%
프 13
 
2.9%
셀 13
 
2.9%
에 11
 
2.4%
구 9
 
2.0%
도 9
 
2.0%
대 8
 
1.8%
Other values (109) 223
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 398
88.2%
Other Symbol 21
 
4.7%
Close Punctuation 7
 
1.6%
Open Punctuation 7
 
1.6%
Space Separator 6
 
1.3%
Dash Punctuation 6
 
1.3%
Uppercase Letter 6
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 52
 
13.1%
주 48
 
12.1%
소 44
 
11.1%
프 13
 
3.3%
셀 13
 
3.3%
에 11
 
2.8%
구 9
 
2.3%
도 9
 
2.3%
대 8
 
2.0%
스 7
 
1.8%
Other values (98) 184
46.2%
Uppercase Letter
ValueCountFrequency (%)
H 1
16.7%
K 1
16.7%
S 1
16.7%
E 1
16.7%
L 1
16.7%
F 1
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 419
92.9%
Common 26
 
5.8%
Latin 6
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 52
 
12.4%
주 48
 
11.5%
소 44
 
10.5%
㈜ 21
 
5.0%
프 13
 
3.1%
셀 13
 
3.1%
에 11
 
2.6%
구 9
 
2.1%
도 9
 
2.1%
대 8
 
1.9%
Other values (99) 191
45.6%
Latin
ValueCountFrequency (%)
H 1
16.7%
K 1
16.7%
S 1
16.7%
E 1
16.7%
L 1
16.7%
F 1
16.7%
Common
ValueCountFrequency (%)
) 7
26.9%
( 7
26.9%
6
23.1%
- 6
23.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 398
88.2%
ASCII 32
 
7.1%
None 21
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 52
 
13.1%
주 48
 
12.1%
소 44
 
11.1%
프 13
 
3.3%
셀 13
 
3.3%
에 11
 
2.8%
구 9
 
2.3%
도 9
 
2.3%
대 8
 
2.0%
스 7
 
1.8%
Other values (98) 184
46.2%
None
ValueCountFrequency (%)
㈜ 21
100.0%
ASCII
ValueCountFrequency (%)
) 7
21.9%
( 7
21.9%
6
18.8%
- 6
18.8%
H 1
 
3.1%
K 1
 
3.1%
S 1
 
3.1%
E 1
 
3.1%
L 1
 
3.1%
F 1
 
3.1%

소재지
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:23:07.494334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.975
Min length6

Characters and Unicode

Total characters479
Distinct characters64
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

Unique40 ?
Unique (%)100.0%

Sample

1st row도산로 213 (변동)
2nd row배재로 205(도마동)
3rd row도산로475 (탄방동)
4th row도산로446 (용문동)
5th row동서대로 1069(내동)
ValueCountFrequency (%)
계백로 8
 
9.8%
동서대로 4
 
4.9%
도산로 3
 
3.7%
배재로 3
 
3.7%
계룡로 2
 
2.4%
변동 2
 
2.4%
유등로 2
 
2.4%
문정로 2
 
2.4%
대덕대로 2
 
2.4%
224(둔산동 1
 
1.2%
Other values (53) 53
64.6%
2023-12-12T18:23:07.898706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 45
 
9.4%
42
 
8.8%
로 38
 
7.9%
( 38
 
7.9%
) 38
 
7.9%
1 27
 
5.6%
2 18
 
3.8%
도 14
 
2.9%
3 13
 
2.7%
7 12
 
2.5%
Other values (54) 194
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
49.7%
Decimal Number 122
25.5%
Space Separator 42
 
8.8%
Open Punctuation 38
 
7.9%
Close Punctuation 38
 
7.9%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 45
18.9%
로 38
16.0%
도 14
 
5.9%
산 11
 
4.6%
계 10
 
4.2%
마 9
 
3.8%
백 8
 
3.4%
정 8
 
3.4%
대 8
 
3.4%
둔 6
 
2.5%
Other values (40) 81
34.0%
Decimal Number
ValueCountFrequency (%)
1 27
22.1%
2 18
14.8%
3 13
10.7%
7 12
9.8%
8 11
9.0%
6 9
 
7.4%
4 9
 
7.4%
0 9
 
7.4%
5 8
 
6.6%
9 6
 
4.9%
Space Separator
ValueCountFrequency (%)
42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 241
50.3%
Hangul 238
49.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 45
18.9%
로 38
16.0%
도 14
 
5.9%
산 11
 
4.6%
계 10
 
4.2%
마 9
 
3.8%
백 8
 
3.4%
정 8
 
3.4%
대 8
 
3.4%
둔 6
 
2.5%
Other values (40) 81
34.0%
Common
ValueCountFrequency (%)
42
17.4%
( 38
15.8%
) 38
15.8%
1 27
11.2%
2 18
7.5%
3 13
 
5.4%
7 12
 
5.0%
8 11
 
4.6%
6 9
 
3.7%
4 9
 
3.7%
Other values (4) 24
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 241
50.3%
Hangul 238
49.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 45
18.9%
로 38
16.0%
도 14
 
5.9%
산 11
 
4.6%
계 10
 
4.2%
마 9
 
3.8%
백 8
 
3.4%
정 8
 
3.4%
대 8
 
3.4%
둔 6
 
2.5%
Other values (40) 81
34.0%
ASCII
ValueCountFrequency (%)
42
17.4%
( 38
15.8%
) 38
15.8%
1 27
11.2%
2 18
7.5%
3 13
 
5.4%
7 12
 
5.0%
8 11
 
4.6%
6 9
 
3.7%
4 9
 
3.7%
Other values (4) 24
10.0%

지번주소
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:23:08.146696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length34
Mean length18.95
Min length16

Characters and Unicode

Total characters758
Distinct characters69
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

Unique40 ?
Unique (%)100.0%

Sample

1st row대전광역시 서구 변동 29-2 현대오일뱅크
2nd row대전광역시 서구 도마동 417
3rd row대전광역시 서구 탄방동 1483-5
4th row대전광역시 서구 용문동 227-10
5th row대전광역시 서구 내동 12-9
ValueCountFrequency (%)
대전광역시 40
24.0%
서구 40
24.0%
도마동 7
 
4.2%
정림동 5
 
3.0%
변동 5
 
3.0%
탄방동 4
 
2.4%
둔산동 4
 
2.4%
내동 3
 
1.8%
관저동 2
 
1.2%
월평동 2
 
1.2%
Other values (54) 55
32.9%
2023-12-12T18:23:08.556180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
16.8%
대 41
 
5.4%
시 41
 
5.4%
동 40
 
5.3%
광 40
 
5.3%
역 40
 
5.3%
서 40
 
5.3%
구 40
 
5.3%
전 40
 
5.3%
1 39
 
5.1%
Other values (59) 270
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
58.0%
Decimal Number 148
 
19.5%
Space Separator 127
 
16.8%
Dash Punctuation 29
 
3.8%
Uppercase Letter 10
 
1.3%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 41
9.3%
시 41
9.3%
동 40
 
9.1%
광 40
 
9.1%
역 40
 
9.1%
서 40
 
9.1%
구 40
 
9.1%
전 40
 
9.1%
마 9
 
2.0%
도 8
 
1.8%
Other values (43) 101
23.0%
Decimal Number
ValueCountFrequency (%)
1 39
26.4%
2 18
12.2%
9 15
 
10.1%
5 15
 
10.1%
4 13
 
8.8%
3 13
 
8.8%
6 10
 
6.8%
0 9
 
6.1%
8 9
 
6.1%
7 7
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
K 5
50.0%
S 5
50.0%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 440
58.0%
Common 308
40.6%
Latin 10
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 41
9.3%
시 41
9.3%
동 40
 
9.1%
광 40
 
9.1%
역 40
 
9.1%
서 40
 
9.1%
구 40
 
9.1%
전 40
 
9.1%
마 9
 
2.0%
도 8
 
1.8%
Other values (43) 101
23.0%
Common
ValueCountFrequency (%)
127
41.2%
1 39
 
12.7%
- 29
 
9.4%
2 18
 
5.8%
9 15
 
4.9%
5 15
 
4.9%
4 13
 
4.2%
3 13
 
4.2%
6 10
 
3.2%
0 9
 
2.9%
Other values (4) 20
 
6.5%
Latin
ValueCountFrequency (%)
K 5
50.0%
S 5
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
58.0%
ASCII 318
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
39.9%
1 39
 
12.3%
- 29
 
9.1%
2 18
 
5.7%
9 15
 
4.7%
5 15
 
4.7%
4 13
 
4.1%
3 13
 
4.1%
6 10
 
3.1%
0 9
 
2.8%
Other values (6) 30
 
9.4%
Hangul
ValueCountFrequency (%)
대 41
9.3%
시 41
9.3%
동 40
 
9.1%
광 40
 
9.1%
역 40
 
9.1%
서 40
 
9.1%
구 40
 
9.1%
전 40
 
9.1%
마 9
 
2.0%
도 8
 
1.8%
Other values (43) 101
23.0%

도로명주소
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:23:08.810953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length21.025
Min length17

Characters and Unicode

Total characters841
Distinct characters67
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row대전광역시 서구 도산로 213(변동)
2nd row대전광역시 서구 배재로 205(도마동)
3rd row대전광역시 서구 도산로 475(탄방동)
4th row대전광역시 서구 도산로 446(용문동)
5th row대전광역시 서구 동서대로 1069(내동)
ValueCountFrequency (%)
대전광역시 40
25.2%
서구 40
25.2%
계백로 8
 
5.0%
도산로 5
 
3.1%
동서대로 4
 
2.5%
배재로 3
 
1.9%
문정로 2
 
1.3%
계룡로 2
 
1.3%
대덕대로 2
 
1.3%
유등로 2
 
1.3%
Other values (51) 51
32.1%
2023-12-12T18:23:09.240740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
 
14.1%
대 49
 
5.8%
동 46
 
5.5%
서 45
 
5.4%
구 41
 
4.9%
역 40
 
4.8%
광 40
 
4.8%
시 40
 
4.8%
전 40
 
4.8%
) 39
 
4.6%
Other values (57) 342
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 521
62.0%
Decimal Number 123
 
14.6%
Space Separator 119
 
14.1%
Close Punctuation 39
 
4.6%
Open Punctuation 39
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 49
 
9.4%
동 46
 
8.8%
서 45
 
8.6%
구 41
 
7.9%
역 40
 
7.7%
광 40
 
7.7%
시 40
 
7.7%
전 40
 
7.7%
로 39
 
7.5%
도 15
 
2.9%
Other values (44) 126
24.2%
Decimal Number
ValueCountFrequency (%)
1 28
22.8%
2 19
15.4%
3 13
10.6%
7 12
9.8%
8 11
 
8.9%
0 10
 
8.1%
4 9
 
7.3%
6 9
 
7.3%
5 6
 
4.9%
9 6
 
4.9%
Space Separator
ValueCountFrequency (%)
119
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 521
62.0%
Common 320
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 49
 
9.4%
동 46
 
8.8%
서 45
 
8.6%
구 41
 
7.9%
역 40
 
7.7%
광 40
 
7.7%
시 40
 
7.7%
전 40
 
7.7%
로 39
 
7.5%
도 15
 
2.9%
Other values (44) 126
24.2%
Common
ValueCountFrequency (%)
119
37.2%
) 39
 
12.2%
( 39
 
12.2%
1 28
 
8.8%
2 19
 
5.9%
3 13
 
4.1%
7 12
 
3.8%
8 11
 
3.4%
0 10
 
3.1%
4 9
 
2.8%
Other values (3) 21
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 521
62.0%
ASCII 320
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
37.2%
) 39
 
12.2%
( 39
 
12.2%
1 28
 
8.8%
2 19
 
5.9%
3 13
 
4.1%
7 12
 
3.8%
8 11
 
3.4%
0 10
 
3.1%
4 9
 
2.8%
Other values (3) 21
 
6.6%
Hangul
ValueCountFrequency (%)
대 49
 
9.4%
동 46
 
8.8%
서 45
 
8.6%
구 41
 
7.9%
역 40
 
7.7%
광 40
 
7.7%
시 40
 
7.7%
전 40
 
7.7%
로 39
 
7.5%
도 15
 
2.9%
Other values (44) 126
24.2%

행정동명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
변동
5 
정림동
5 
탄방동
4 
도마2동
4 
둔산2동
3 
Other values (13)
19 

Length

Max length4
Median length3
Mean length3.25
Min length2

Unique

Unique9 ?
Unique (%)22.5%

Sample

1st row변동
2nd row도마2동
3rd row탄방동
4th row용문동
5th row내동

Common Values

ValueCountFrequency (%)
변동 5
12.5%
정림동 5
12.5%
탄방동 4
10.0%
도마2동 4
10.0%
둔산2동 3
 
7.5%
도마1동 3
 
7.5%
내동 3
 
7.5%
관저2동 2
 
5.0%
갈마1동 2
 
5.0%
월평2동 1
 
2.5%
Other values (8) 8
20.0%

Length

2023-12-12T18:23:09.798520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
변동 5
12.5%
정림동 5
12.5%
탄방동 4
10.0%
도마2동 4
10.0%
둔산2동 3
 
7.5%
도마1동 3
 
7.5%
내동 3
 
7.5%
관저2동 2
 
5.0%
갈마1동 2
 
5.0%
월평1동 1
 
2.5%
Other values (8) 8
20.0%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170565 × 109
Minimum3.017052 × 109
Maximum3.017065 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T18:23:09.944754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017052 × 109
5-th percentile3.017052 × 109
Q13.0170535 × 109
median3.0170555 × 109
Q33.0170588 × 109
95-th percentile3.017064 × 109
Maximum3.017065 × 109
Range13000
Interquartile range (IQR)5275

Descriptive statistics

Standard deviation3715.0413
Coefficient of variation (CV)1.2313463 × 10-6
Kurtosis-0.24231635
Mean3.0170565 × 109
Median Absolute Deviation (MAD)2500
Skewness0.83326424
Sum1.2068226 × 1011
Variance13801532
MonotonicityNot monotonic
2023-12-12T18:23:10.109926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3017054000 5
12.5%
3017053500 5
12.5%
3017055500 4
10.0%
3017053000 4
10.0%
3017064000 3
7.5%
3017052000 3
7.5%
3017057500 3
7.5%
3017059700 2
 
5.0%
3017058100 2
 
5.0%
3017059000 2
 
5.0%
Other values (7) 7
17.5%
ValueCountFrequency (%)
3017052000 3
7.5%
3017053000 4
10.0%
3017053500 5
12.5%
3017054000 5
12.5%
3017055000 1
 
2.5%
3017055500 4
10.0%
3017056000 1
 
2.5%
3017057500 3
7.5%
3017058100 2
 
5.0%
3017058600 1
 
2.5%
ValueCountFrequency (%)
3017065000 1
 
2.5%
3017064000 3
7.5%
3017063000 1
 
2.5%
3017060000 1
 
2.5%
3017059700 2
5.0%
3017059000 2
5.0%
3017058700 1
 
2.5%
3017058600 1
 
2.5%
3017058100 2
5.0%
3017057500 3
7.5%

법정동명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
도마동
7 
변동
5 
정림동
5 
탄방동
4 
둔산동
4 
Other values (10)
15 

Length

Max length4
Median length3
Mean length2.825
Min length2

Unique

Unique6 ?
Unique (%)15.0%

Sample

1st row변동
2nd row도마동
3rd row탄방동
4th row용문동
5th row내동

Common Values

ValueCountFrequency (%)
도마동 7
17.5%
변동 5
12.5%
정림동 5
12.5%
탄방동 4
10.0%
둔산동 4
10.0%
내동 3
7.5%
월평동 2
 
5.0%
관저동 2
 
5.0%
갈마동 2
 
5.0%
용문동 1
 
2.5%
Other values (5) 5
12.5%

Length

2023-12-12T18:23:10.299961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도마동 7
17.5%
변동 5
12.5%
정림동 5
12.5%
탄방동 4
10.0%
둔산동 4
10.0%
내동 3
7.5%
월평동 2
 
5.0%
관저동 2
 
5.0%
갈마동 2
 
5.0%
용문동 1
 
2.5%
Other values (5) 5
12.5%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170108 × 109
Minimum3.0170102 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T18:23:10.444171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170102 × 109
5-th percentile3.0170102 × 109
Q13.0170103 × 109
median3.0170106 × 109
Q33.0170112 × 109
95-th percentile3.0170116 × 109
Maximum3.0170128 × 109
Range2600
Interquartile range (IQR)900

Descriptive statistics

Standard deviation576.90598
Coefficient of variation (CV)1.9121774 × 10-7
Kurtosis1.971521
Mean3.0170108 × 109
Median Absolute Deviation (MAD)400
Skewness1.2035715
Sum1.2068043 × 1011
Variance332820.51
MonotonicityNot monotonic
2023-12-12T18:23:10.574785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3017010300 7
17.5%
3017010200 5
12.5%
3017010400 5
12.5%
3017010600 4
10.0%
3017011200 4
10.0%
3017011000 3
7.5%
3017011300 2
 
5.0%
3017011600 2
 
5.0%
3017011100 2
 
5.0%
3017010500 1
 
2.5%
Other values (5) 5
12.5%
ValueCountFrequency (%)
3017010200 5
12.5%
3017010300 7
17.5%
3017010400 5
12.5%
3017010500 1
 
2.5%
3017010600 4
10.0%
3017010800 1
 
2.5%
3017011000 3
7.5%
3017011100 2
 
5.0%
3017011200 4
10.0%
3017011300 2
 
5.0%
ValueCountFrequency (%)
3017012800 1
 
2.5%
3017011700 1
 
2.5%
3017011600 2
5.0%
3017011500 1
 
2.5%
3017011400 1
 
2.5%
3017011300 2
5.0%
3017011200 4
10.0%
3017011100 2
5.0%
3017011000 3
7.5%
3017010800 1
 
2.5%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
주유소
40 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주유소 40
100.0%

Length

2023-12-12T18:23:10.715771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:23:10.820648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주유소 40
100.0%

오염물질
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
휘발성유기화합물
40 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휘발성유기화합물 40
100.0%

Length

2023-12-12T18:23:10.933233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:23:11.038402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휘발성유기화합물 40
100.0%

Interactions

2023-12-12T18:23:05.702589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:05.105902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:05.408068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:05.787019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:05.214202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:05.499084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:05.882205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:05.310838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:23:05.608554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:23:11.128357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업소명소재지지번주소도로명주소행정동명행정동코드법정동명법정동코드
순번1.0001.0001.0001.0001.0000.0000.1780.2860.419
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동명0.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동코드0.1781.0001.0001.0001.0001.0001.0000.9810.914
법정동명0.2861.0001.0001.0001.0001.0000.9811.0001.000
법정동코드0.4191.0001.0001.0001.0001.0000.9141.0001.000
2023-12-12T18:23:11.285891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명행정동명
법정동명1.0000.938
행정동명0.9381.000
2023-12-12T18:23:11.403471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드법정동코드행정동명법정동명
순번1.0000.0230.0080.0000.000
행정동코드0.0231.0000.8720.8420.812
법정동코드0.0080.8721.0000.8160.870
행정동명0.0000.8420.8161.0000.938
법정동명0.0000.8120.8700.9381.000

Missing values

2023-12-12T18:23:06.012017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:23:06.227252image/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

순번업소명소재지지번주소도로명주소행정동명행정동코드법정동명법정동코드업종오염물질
01에이치디현대오일뱅크㈜직영신대전셀프주유소도산로 213 (변동)대전광역시 서구 변동 29-2 현대오일뱅크대전광역시 서구 도산로 213(변동)변동3017054000변동3017010200주유소휘발성유기화합물
12주식회사 제이비엘티디(구-선진주유소)배재로 205(도마동)대전광역시 서구 도마동 417대전광역시 서구 배재로 205(도마동)도마2동3017053000도마동3017010300주유소휘발성유기화합물
23㈜연정 주홍셀프도산로475 (탄방동)대전광역시 서구 탄방동 1483-5대전광역시 서구 도산로 475(탄방동)탄방동3017055500탄방동3017010600주유소휘발성유기화합물
34코끼리셀프주유소도산로446 (용문동)대전광역시 서구 용문동 227-10대전광역시 서구 도산로 446(용문동)용문동3017055000용문동3017010500주유소휘발성유기화합물
46유진주유소동서대로 1069(내동)대전광역시 서구 내동 12-9대전광역시 서구 동서대로 1069(내동)내동3017057500내동3017011000주유소휘발성유기화합물
57㈜동건에너지만년교주유소(구-현대오일뱅크㈜만년교셀프주유소)계룡로 202(월평동)대전광역시 서구 월평동 161-3 SK네트워스(주)SK만년교주유소대전광역시 서구 계룡로 202(월평동)월평1동3017058600월평동3017011300주유소휘발성유기화합물
68타임셀프주유소(구-현대오일뱅크㈜대전청사셀프주유소)대덕대로 188(둔산동)대전광역시 서구 둔산동 1161대전광역시 서구 대덕대로 188(둔산동)둔산2동3017064000둔산동3017011200주유소휘발성유기화합물
79KH에너지㈜직영 둔산주유소둔산로 139(둔산동)대전광역시 서구 둔산동 1486 SK네트워스(주)SK둔산주유소대전광역시 서구 둔산로 139(둔산동)둔산1동3017063000둔산동3017011200주유소휘발성유기화합물
810그린주유소㈜동서대로 953(내동)대전광역시 서구 내동 152-3대전광역시 서구 동서대로 953(내동)내동3017057500내동3017011000주유소휘발성유기화합물
911지에스칼텍스㈜정림주유소계백로 1277(정림동)대전광역시 서구 정림동 293-5대전광역시 서구 계백로 1277(정림동)정림동3017053500정림동3017010400주유소휘발성유기화합물
순번업소명소재지지번주소도로명주소행정동명행정동코드법정동명법정동코드업종오염물질
3034우리주유소도산로 216(변동)대전광역시 서구 변동 12-31대전광역시 서구 도산로 216(변동)변동3017054000변동3017010200주유소휘발성유기화합물
3135㈜탄방주유소유등로 659(탄방동)대전광역시 서구 탄방동 1480-20대전광역시 서구 유등로 659(탄방동)탄방동3017055500탄방동3017010600주유소휘발성유기화합물
3236주식회사 가수원하늘셀프주유소계백로 1176(가수원동)대전광역시 서구 가수원동 210-7 쌍용주유소대전광역시 서구 계백로 1176(가수원동)가수원동3017059000가수원동3017011400주유소휘발성유기화합물
3337극동유화㈜한밭주유소(구-구도일주유소한밭)문정로 3(둔산동)대전광역시 서구 둔산동 1142대전광역시 서구 문정로 3(둔산동)둔산2동3017064000둔산동3017011200주유소휘발성유기화합물
3438㈜에너비즈 명품주유소배재로 218(도마동)대전광역시 서구 도마동 14-1대전광역시 서구 배재로 218(도마동)도마1동3017052000도마동3017010300주유소휘발성유기화합물
3539남선석유㈜계백셀프주유소계백로 1327(정림동)대전광역시 서구 정림동 1-1대전광역시 서구 계백로 1327(정림동)정림동3017053500정림동3017010400주유소휘발성유기화합물
3640백산주유소동서대로 1068(변동)대전광역시 서구 변동 14-3대전광역시 서구 동서대로 1068(변동)변동3017054000변동3017010200주유소휘발성유기화합물
3741도마진실주유소(구-은하수SELF주유소)도산로 123(도마동)대전광역시 서구 도마동 65-5대전광역시 서구 도산로 123(도마동)도마1동3017052000도마동3017010300주유소휘발성유기화합물
3842구봉산셀프주유소구봉로 208(관저동)대전광역시 서구 관저동 1609 오일앤워시대전광역시 서구 구봉로 208(관저동)관저2동3017059700관저동3017011600주유소휘발성유기화합물
3943우리하나에너지(주)우리하나셀프주유소서구 변동 5-15대전광역시 서구 변동 5-15대전광역시 서구 동서대로1120변동3017054000변동3017010200주유소휘발성유기화합물