Overview

Dataset statistics

Number of variables8
Number of observations30
Missing cells3
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory70.4 B

Variable types

Numeric2
Text3
Categorical3

Dataset

Description이 데이터는 경상북도 영천시의 경질유 중질유 사용업체 정보(업체명, 제공기관, 사용량, 데이터 기준일자 등)를 제공합니다.
Author경상북도 영천시
URLhttps://www.data.go.kr/data/15107790/fileData.do

Alerts

제공기관 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 사용연료High correlation
사용연료 is highly overall correlated with 연번High correlation
전화번호 has 3 (10.0%) missing valuesMissing
연번 has unique valuesUnique
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:31:25.037496
Analysis finished2023-12-12 01:31:26.406749
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T10:31:26.486377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-12-12T10:31:26.641060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

업체명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T10:31:26.859375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.4666667
Min length3

Characters and Unicode

Total characters194
Distinct characters92
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row남양캐미칼
2nd row현철유지
3rd row대양산업
4th row이에프특장차㈜
5th row성희엔지니어링
ValueCountFrequency (%)
주식회사 2
 
6.1%
남양캐미칼 1
 
3.0%
도동종합1급정비공장 1
 
3.0%
㈜동화산업 1
 
3.0%
㈜동원산업 1
 
3.0%
대원엔비폴 1
 
3.0%
평산금속 1
 
3.0%
대원스티로폴 1
 
3.0%
㈜삼한알엔텍 1
 
3.0%
우리아스콘㈜ 1
 
3.0%
Other values (22) 22
66.7%
2023-12-12T10:31:27.226350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 16
 
8.2%
산 7
 
3.6%
장 6
 
3.1%
공 5
 
2.6%
동 5
 
2.6%
이 5
 
2.6%
업 5
 
2.6%
대 4
 
2.1%
영 4
 
2.1%
화 4
 
2.1%
Other values (82) 133
68.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 171
88.1%
Other Symbol 16
 
8.2%
Space Separator 3
 
1.5%
Decimal Number 2
 
1.0%
Uppercase Letter 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 7
 
4.1%
장 6
 
3.5%
공 5
 
2.9%
동 5
 
2.9%
이 5
 
2.9%
업 5
 
2.9%
대 4
 
2.3%
영 4
 
2.3%
화 4
 
2.3%
비 4
 
2.3%
Other values (76) 122
71.3%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
5 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
M 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 16
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
96.4%
Common 5
 
2.6%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 16
 
8.6%
산 7
 
3.7%
장 6
 
3.2%
공 5
 
2.7%
동 5
 
2.7%
이 5
 
2.7%
업 5
 
2.7%
대 4
 
2.1%
영 4
 
2.1%
화 4
 
2.1%
Other values (77) 126
67.4%
Common
ValueCountFrequency (%)
3
60.0%
1 1
 
20.0%
5 1
 
20.0%
Latin
ValueCountFrequency (%)
S 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 171
88.1%
None 16
 
8.2%
ASCII 7
 
3.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 16
100.0%
Hangul
ValueCountFrequency (%)
산 7
 
4.1%
장 6
 
3.5%
공 5
 
2.9%
동 5
 
2.9%
이 5
 
2.9%
업 5
 
2.9%
대 4
 
2.3%
영 4
 
2.3%
화 4
 
2.3%
비 4
 
2.3%
Other values (76) 122
71.3%
ASCII
ValueCountFrequency (%)
3
42.9%
1 1
 
14.3%
S 1
 
14.3%
M 1
 
14.3%
5 1
 
14.3%

전화번호
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing3
Missing (%)10.0%
Memory size372.0 B
2023-12-12T10:31:27.461837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters324
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row054-333-3048
2nd row054-335-7797
3rd row053-811-9173
4th row054-332-2382
5th row054-336-2290
ValueCountFrequency (%)
054-333-3048 1
 
3.7%
054-335-2580 1
 
3.7%
054-335-1395 1
 
3.7%
054-336-0999 1
 
3.7%
054-462-0005 1
 
3.7%
054-336-2801 1
 
3.7%
054-335-9000 1
 
3.7%
054-338-5584 1
 
3.7%
054-337-1888 1
 
3.7%
054-336-6531 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T10:31:27.827088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 64
19.8%
- 54
16.7%
0 49
15.1%
5 45
13.9%
4 32
9.9%
9 17
 
5.2%
2 15
 
4.6%
6 15
 
4.6%
7 12
 
3.7%
8 11
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270
83.3%
Dash Punctuation 54
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 64
23.7%
0 49
18.1%
5 45
16.7%
4 32
11.9%
9 17
 
6.3%
2 15
 
5.6%
6 15
 
5.6%
7 12
 
4.4%
8 11
 
4.1%
1 10
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 324
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 64
19.8%
- 54
16.7%
0 49
15.1%
5 45
13.9%
4 32
9.9%
9 17
 
5.2%
2 15
 
4.6%
6 15
 
4.6%
7 12
 
3.7%
8 11
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 64
19.8%
- 54
16.7%
0 49
15.1%
5 45
13.9%
4 32
9.9%
9 17
 
5.2%
2 15
 
4.6%
6 15
 
4.6%
7 12
 
3.7%
8 11
 
3.4%

주소
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T10:31:28.059093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length20.066667
Min length15

Characters and Unicode

Total characters602
Distinct characters64
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st row경상북도 영천시 칠백로 808-3
2nd row경상북도 영천시 청통면 금송로 711-37
3rd row경상북도 영천시 대창면 강회2길108
4th row경상북도 영천시 대창면 한제길 7-59
5th row경상북도 영천시 안야사길 151
ValueCountFrequency (%)
경상북도 30
21.7%
영천시 30
21.7%
대창면 8
 
5.8%
고경면 4
 
2.9%
유봉길 3
 
2.2%
화산면 3
 
2.2%
선진길 3
 
2.2%
113 2
 
1.4%
20 2
 
1.4%
금박로 2
 
1.4%
Other values (48) 51
37.0%
2023-12-12T10:31:28.448262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
17.9%
경 34
 
5.6%
도 34
 
5.6%
북 31
 
5.1%
상 31
 
5.1%
영 30
 
5.0%
천 30
 
5.0%
시 30
 
5.0%
1 30
 
5.0%
길 20
 
3.3%
Other values (54) 224
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 373
62.0%
Space Separator 108
 
17.9%
Decimal Number 106
 
17.6%
Dash Punctuation 15
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 34
 
9.1%
도 34
 
9.1%
북 31
 
8.3%
상 31
 
8.3%
영 30
 
8.0%
천 30
 
8.0%
시 30
 
8.0%
길 20
 
5.4%
면 18
 
4.8%
로 10
 
2.7%
Other values (42) 105
28.2%
Decimal Number
ValueCountFrequency (%)
1 30
28.3%
0 12
 
11.3%
8 11
 
10.4%
2 11
 
10.4%
3 9
 
8.5%
9 8
 
7.5%
6 8
 
7.5%
7 6
 
5.7%
4 6
 
5.7%
5 5
 
4.7%
Space Separator
ValueCountFrequency (%)
108
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 373
62.0%
Common 229
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 34
 
9.1%
도 34
 
9.1%
북 31
 
8.3%
상 31
 
8.3%
영 30
 
8.0%
천 30
 
8.0%
시 30
 
8.0%
길 20
 
5.4%
면 18
 
4.8%
로 10
 
2.7%
Other values (42) 105
28.2%
Common
ValueCountFrequency (%)
108
47.2%
1 30
 
13.1%
- 15
 
6.6%
0 12
 
5.2%
8 11
 
4.8%
2 11
 
4.8%
3 9
 
3.9%
9 8
 
3.5%
6 8
 
3.5%
7 6
 
2.6%
Other values (2) 11
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 373
62.0%
ASCII 229
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
47.2%
1 30
 
13.1%
- 15
 
6.6%
0 12
 
5.2%
8 11
 
4.8%
2 11
 
4.8%
3 9
 
3.9%
9 8
 
3.5%
6 8
 
3.5%
7 6
 
2.6%
Other values (2) 11
 
4.8%
Hangul
ValueCountFrequency (%)
경 34
 
9.1%
도 34
 
9.1%
북 31
 
8.3%
상 31
 
8.3%
영 30
 
8.0%
천 30
 
8.0%
시 30
 
8.0%
길 20
 
5.4%
면 18
 
4.8%
로 10
 
2.7%
Other values (42) 105
28.2%

사용연료
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
경유
21 
중유C
8 
중유B
 
1

Length

Max length3
Median length2
Mean length2.3
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
경유 21
70.0%
중유C 8
 
26.7%
중유B 1
 
3.3%

Length

2023-12-12T10:31:28.585147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:31:28.695908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경유 21
70.0%
중유c 8
 
26.7%
중유b 1
 
3.3%

사용량(L_년)
Real number (ℝ)

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79977.533
Minimum12
Maximum780000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T10:31:28.805654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile29.75
Q1103.5
median461
Q344250
95-th percentile495930
Maximum780000
Range779988
Interquartile range (IQR)44146.5

Descriptive statistics

Standard deviation188231.53
Coefficient of variation (CV)2.3535551
Kurtosis7.7257197
Mean79977.533
Median Absolute Deviation (MAD)438.5
Skewness2.8339707
Sum2399326
Variance3.5431108 × 1010
MonotonicityNot monotonic
2023-12-12T10:31:28.968479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
200 3
 
10.0%
60000 2
 
6.7%
6000 1
 
3.3%
12 1
 
3.3%
609600 1
 
3.3%
357000 1
 
3.3%
90 1
 
3.3%
780000 1
 
3.3%
288000 1
 
3.3%
133472 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
12 1
 
3.3%
23 1
 
3.3%
38 1
 
3.3%
63 1
 
3.3%
64 1
 
3.3%
80 1
 
3.3%
90 1
 
3.3%
100 1
 
3.3%
114 1
 
3.3%
200 3
10.0%
ValueCountFrequency (%)
780000 1
3.3%
609600 1
3.3%
357000 1
3.3%
288000 1
3.3%
133472 1
3.3%
60000 2
6.7%
45000 1
3.3%
42000 1
3.3%
12000 1
3.3%
6000 1
3.3%

제공기관
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경상북도 영천시청
30 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도 영천시청
2nd row경상북도 영천시청
3rd row경상북도 영천시청
4th row경상북도 영천시청
5th row경상북도 영천시청

Common Values

ValueCountFrequency (%)
경상북도 영천시청 30
100.0%

Length

2023-12-12T10:31:29.192932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:31:29.315110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 30
50.0%
영천시청 30
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2022-10-31
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-31
2nd row2022-10-31
3rd row2022-10-31
4th row2022-10-31
5th row2022-10-31

Common Values

ValueCountFrequency (%)
2022-10-31 30
100.0%

Length

2023-12-12T10:31:29.477427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:31:29.607473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-31 30
100.0%

Interactions

2023-12-12T10:31:25.614850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:31:25.381806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:31:25.730444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:31:25.488959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:31:29.718666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명전화번호주소사용연료사용량(L_년)
연번1.0001.0001.0001.0000.7930.362
업체명1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.000
사용연료0.7931.0001.0001.0001.0000.674
사용량(L_년)0.3621.0001.0001.0000.6741.000
2023-12-12T10:31:29.837794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사용량(L_년)사용연료
연번1.0000.2160.581
사용량(L_년)0.2161.0000.332
사용연료0.5810.3321.000

Missing values

2023-12-12T10:31:26.208805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:31:26.356605image/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

연번업체명전화번호주소사용연료사용량(L_년)제공기관데이터기준일자
01남양캐미칼054-333-3048경상북도 영천시 칠백로 808-3경유6000경상북도 영천시청2022-10-31
12현철유지<NA>경상북도 영천시 청통면 금송로 711-37경유60000경상북도 영천시청2022-10-31
23대양산업054-335-7797경상북도 영천시 대창면 강회2길108경유1260경상북도 영천시청2022-10-31
34이에프특장차㈜053-811-9173경상북도 영천시 대창면 한제길 7-59경유1500경상북도 영천시청2022-10-31
45성희엔지니어링054-332-2382경상북도 영천시 안야사길 151경유538경상북도 영천시청2022-10-31
56㈜피제이산업 영천지점054-336-2290경상북도 영천시 칠백로 808-11경유200경상북도 영천시청2022-10-31
67SM화진㈜5공장054-335-9655경상북도 영천시 도남공단1길 20경유64경상북도 영천시청2022-10-31
78영창산업054-336-3900경상북도 영천시 대창면 한제길 12-31경유200경상북도 영천시청2022-10-31
89세명자동차종합정비공장054-332-2742경상북도 영천시 유봉길 24경유200경상북도 영천시청2022-10-31
910유성테크054-338-5430경상북도 영천시 화산면 석촌1길 50-16경유80경상북도 영천시청2022-10-31
연번업체명전화번호주소사용연료사용량(L_년)제공기관데이터기준일자
2021디엘환경㈜054-337-3220경상북도 영천시 고경면 호국로 1516-81경유63경상북도 영천시청2022-10-31
2122한융금속㈜대창공장054-336-6531경상북도 영천시 대창면 금박로 914중유B114경상북도 영천시청2022-10-31
2223우리아스콘㈜054-337-1888경상북도 영천시 고경면 산수골길 47중유C45000경상북도 영천시청2022-10-31
2324㈜삼한알엔텍054-338-5584경상북도 영천시 채신1공단길 60-8중유C248경상북도 영천시청2022-10-31
2425대원스티로폴054-335-9000경상북도 영천시 대창면 선진길 202-1중유C133472경상북도 영천시청2022-10-31
2526평산금속054-336-2801경상북도 영천시 도남공단3길 28-36중유C288000경상북도 영천시청2022-10-31
2627주식회사 대원엔비폴054-462-0005경상북도 영천시 대창면 선진길 46-19중유C780000경상북도 영천시청2022-10-31
2728㈜동원산업054-336-0999경상북도 영천시 고경면 상리공단길 51중유C90경상북도 영천시청2022-10-31
2829㈜동화산업054-335-1395경상북도 영천시 화산면 화산공단길 20중유C357000경상북도 영천시청2022-10-31
2930㈜삼안콘크리트054-336-0306경상북도 영천시 신녕면 신화로 93중유C609600경상북도 영천시청2022-10-31