Overview

Dataset statistics

Number of variables4
Number of observations53
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory35.5 B

Variable types

Numeric1
Text2
DateTime1

Dataset

Description대구광역시 수성구 관내 특정오염관리대상시설에 대한 데이터로 관내 특정오염관리대상시설의 업소명(상호), 소재지에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/3075365/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
상호 has unique valuesUnique
소재지(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:32:13.313011
Analysis finished2023-12-12 04:32:13.779929
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T13:32:13.901675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q114
median27
Q340
95-th percentile50.4
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.443445
Coefficient of variation (CV)0.57197945
Kurtosis-1.2
Mean27
Median Absolute Deviation (MAD)13
Skewness0
Sum1431
Variance238.5
MonotonicityStrictly increasing
2023-12-12T13:32:14.112942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
41 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%

상호
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T13:32:14.400950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.0377358
Min length4

Characters and Unicode

Total characters426
Distinct characters123
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

Unique53 ?
Unique (%)100.0%

Sample

1st row수성주유소
2nd row한국광유(주)청기와주유소
3rd row육군제6199부대본부사령실
4th row기분좋은주유소
5th row노변주유소
ValueCountFrequency (%)
구도일주유소 2
 
3.6%
수성주유소 1
 
1.8%
메트로팔레스주유소 1
 
1.8%
수성셀프주유소 1
 
1.8%
연호주유소 1
 
1.8%
케이케이(주)중앙2self주유소 1
 
1.8%
그린주유소 1
 
1.8%
한국광유(주)남부주유소 1
 
1.8%
만촌하나석유 1
 
1.8%
수산석유 1
 
1.8%
Other values (45) 45
80.4%
2023-12-12T13:32:14.908365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 49
 
11.5%
유 48
 
11.3%
소 37
 
8.7%
대 14
 
3.3%
( 12
 
2.8%
) 12
 
2.8%
스 11
 
2.6%
석 8
 
1.9%
수 7
 
1.6%
성 7
 
1.6%
Other values (113) 221
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 375
88.0%
Decimal Number 18
 
4.2%
Open Punctuation 12
 
2.8%
Close Punctuation 12
 
2.8%
Uppercase Letter 6
 
1.4%
Space Separator 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 49
 
13.1%
유 48
 
12.8%
소 37
 
9.9%
대 14
 
3.7%
스 11
 
2.9%
석 8
 
2.1%
수 7
 
1.9%
성 7
 
1.9%
에 7
 
1.9%
한 7
 
1.9%
Other values (98) 180
48.0%
Decimal Number
ValueCountFrequency (%)
1 4
22.2%
6 4
22.2%
9 3
16.7%
5 2
11.1%
3 2
11.1%
2 2
11.1%
0 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
33.3%
L 1
16.7%
F 1
16.7%
E 1
16.7%
K 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 375
88.0%
Common 45
 
10.6%
Latin 6
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 49
 
13.1%
유 48
 
12.8%
소 37
 
9.9%
대 14
 
3.7%
스 11
 
2.9%
석 8
 
2.1%
수 7
 
1.9%
성 7
 
1.9%
에 7
 
1.9%
한 7
 
1.9%
Other values (98) 180
48.0%
Common
ValueCountFrequency (%)
( 12
26.7%
) 12
26.7%
1 4
 
8.9%
6 4
 
8.9%
3
 
6.7%
9 3
 
6.7%
5 2
 
4.4%
3 2
 
4.4%
2 2
 
4.4%
0 1
 
2.2%
Latin
ValueCountFrequency (%)
S 2
33.3%
L 1
16.7%
F 1
16.7%
E 1
16.7%
K 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 375
88.0%
ASCII 51
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 49
 
13.1%
유 48
 
12.8%
소 37
 
9.9%
대 14
 
3.7%
스 11
 
2.9%
석 8
 
2.1%
수 7
 
1.9%
성 7
 
1.9%
에 7
 
1.9%
한 7
 
1.9%
Other values (98) 180
48.0%
ASCII
ValueCountFrequency (%)
( 12
23.5%
) 12
23.5%
1 4
 
7.8%
6 4
 
7.8%
3
 
5.9%
9 3
 
5.9%
5 2
 
3.9%
3 2
 
3.9%
S 2
 
3.9%
2 2
 
3.9%
Other values (5) 5
9.8%

소재지(지번)
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T13:32:15.222577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length20.339623
Min length16

Characters and Unicode

Total characters1078
Distinct characters49
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

Unique53 ?
Unique (%)100.0%

Sample

1st row대구광역시 수성구 상동 623-2
2nd row대구광역시 수성구 만촌동 132-3 (1221-11)
3rd row대구광역시 수성구 만촌동 사서함503-17호
4th row대구광역시 수성구 중동 537-21
5th row대구광역시 수성구 노변동 4
ValueCountFrequency (%)
대구광역시 53
24.4%
수성구 53
24.4%
만촌동 13
 
6.0%
범어동 6
 
2.8%
지산동 6
 
2.8%
상동 5
 
2.3%
황금동 4
 
1.8%
연호동 3
 
1.4%
두산동 3
 
1.4%
887-1 2
 
0.9%
Other values (65) 69
31.8%
2023-12-12T13:32:15.631044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
217
20.1%
구 106
 
9.8%
시 54
 
5.0%
대 53
 
4.9%
광 53
 
4.9%
역 53
 
4.9%
수 53
 
4.9%
성 53
 
4.9%
동 53
 
4.9%
1 47
 
4.4%
Other values (39) 336
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 587
54.5%
Decimal Number 226
 
21.0%
Space Separator 217
 
20.1%
Dash Punctuation 46
 
4.3%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 106
18.1%
시 54
9.2%
대 53
9.0%
광 53
9.0%
역 53
9.0%
수 53
9.0%
성 53
9.0%
동 53
9.0%
촌 13
 
2.2%
만 13
 
2.2%
Other values (25) 83
14.1%
Decimal Number
ValueCountFrequency (%)
1 47
20.8%
3 30
13.3%
4 27
11.9%
2 21
9.3%
7 20
8.8%
5 18
 
8.0%
9 18
 
8.0%
8 15
 
6.6%
6 15
 
6.6%
0 15
 
6.6%
Space Separator
ValueCountFrequency (%)
217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 587
54.5%
Common 491
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 106
18.1%
시 54
9.2%
대 53
9.0%
광 53
9.0%
역 53
9.0%
수 53
9.0%
성 53
9.0%
동 53
9.0%
촌 13
 
2.2%
만 13
 
2.2%
Other values (25) 83
14.1%
Common
ValueCountFrequency (%)
217
44.2%
1 47
 
9.6%
- 46
 
9.4%
3 30
 
6.1%
4 27
 
5.5%
2 21
 
4.3%
7 20
 
4.1%
5 18
 
3.7%
9 18
 
3.7%
8 15
 
3.1%
Other values (4) 32
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 587
54.5%
ASCII 491
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
217
44.2%
1 47
 
9.6%
- 46
 
9.4%
3 30
 
6.1%
4 27
 
5.5%
2 21
 
4.3%
7 20
 
4.1%
5 18
 
3.7%
9 18
 
3.7%
8 15
 
3.1%
Other values (4) 32
 
6.5%
Hangul
ValueCountFrequency (%)
구 106
18.1%
시 54
9.2%
대 53
9.0%
광 53
9.0%
역 53
9.0%
수 53
9.0%
성 53
9.0%
동 53
9.0%
촌 13
 
2.2%
만 13
 
2.2%
Other values (25) 83
14.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2023-08-04 00:00:00
Maximum2023-08-04 00:00:00
2023-12-12T13:32:15.752245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:32:15.837016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T13:32:13.492215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:32:15.906216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호소재지(지번)
연번1.0001.0001.000
상호1.0001.0001.000
소재지(지번)1.0001.0001.000

Missing values

2023-12-12T13:32:13.643505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:32:13.736270image/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

연번상호소재지(지번)데이터기준일자
01수성주유소대구광역시 수성구 상동 623-22023-08-04
12한국광유(주)청기와주유소대구광역시 수성구 만촌동 132-3 (1221-11)2023-08-04
23육군제6199부대본부사령실대구광역시 수성구 만촌동 사서함503-17호2023-08-04
34기분좋은주유소대구광역시 수성구 중동 537-212023-08-04
45노변주유소대구광역시 수성구 노변동 42023-08-04
56사랑가득주유소대구광역시 수성구 황금동 670-12023-08-04
67파동주유소대구광역시 수성구 파동 506-42023-08-04
78흥구석유(주)만촌주유소대구광역시 수성구 만촌동 1331-132023-08-04
89대림석유대구광역시 수성구 범물동 1362-192023-08-04
910수성착한주유소대구광역시 수성구 상동 2082023-08-04
연번상호소재지(지번)데이터기준일자
4344황금기름창고주유소대구광역시 수성구 황금동 887-1 외12023-08-04
4445수성현대셀프주유소대구광역시 수성구 지산동 997-22023-08-04
4546대림주유소대구광역시 수성구 지산동 1205-32023-08-04
4647태영주유소대구광역시 수성구 범어동 428-42023-08-04
4748구도일주유소대구광역시 수성구 범어동 165-172023-08-04
4849(주)삼우대구공장대구광역시 수성구 사월동 4472023-08-04
4950육군제6619부대대구광역시 수성구 만촌동 503-12023-08-04
5051제6335부대대구광역시 수성구 가천동 산 45 사서함 96-102023-08-04
5152공군 제1방공유도탄여단대구광역시 수성구 이천동 2392023-08-04
5253제2150부대대구광역시 수성구 가천동 사서함96-12-12023-08-04