Overview

Dataset statistics

Number of variables6
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory50.9 B

Variable types

Text4
Categorical2

Dataset

Description충청북도 충주시 경질유 및 중질유(경유, 등유, 벙커C유, 벙커A유등) 사용업체 현황(상호, 주소, 사용연료, 생산품, 연료사용량 등)
Author충청북도 충주시
URLhttps://www.data.go.kr/data/15107153/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
주소 has unique valuesUnique

Reproduction

Analysis started2024-04-18 08:53:42.878349
Analysis finished2024-04-18 08:53:43.716087
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct45
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-04-18T17:53:43.932078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.4782609
Min length3

Characters and Unicode

Total characters390
Distinct characters120
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)95.7%

Sample

1st row유성콘크리트(주)
2nd row(주)이랜드파크한국콘도수안보점
3rd row정안산업(주)
4th row주식회사 명승
5th row(주)성신
ValueCountFrequency (%)
주식회사 3
 
5.8%
충주공업사 2
 
3.8%
일급삼형제공업사 1
 
1.9%
주)신화하이테크 1
 
1.9%
주)금성농산 1
 
1.9%
한국지엠충주서비스센터(주 1
 
1.9%
주)에이맥스통상 1
 
1.9%
중원자동차공업사(주 1
 
1.9%
승광자동차정비(주 1
 
1.9%
주)psi테크 1
 
1.9%
Other values (39) 39
75.0%
2024-04-18T17:53:44.394633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 33
 
8.5%
( 24
 
6.2%
) 24
 
6.2%
업 18
 
4.6%
공 15
 
3.8%
사 14
 
3.6%
이 11
 
2.8%
동 10
 
2.6%
차 8
 
2.1%
자 8
 
2.1%
Other values (110) 225
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 329
84.4%
Open Punctuation 24
 
6.2%
Close Punctuation 24
 
6.2%
Space Separator 6
 
1.5%
Other Symbol 4
 
1.0%
Uppercase Letter 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 33
 
10.0%
업 18
 
5.5%
공 15
 
4.6%
사 14
 
4.3%
이 11
 
3.3%
동 10
 
3.0%
차 8
 
2.4%
자 8
 
2.4%
성 8
 
2.4%
비 7
 
2.1%
Other values (103) 197
59.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
P 1
33.3%
I 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 333
85.4%
Common 54
 
13.8%
Latin 3
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 33
 
9.9%
업 18
 
5.4%
공 15
 
4.5%
사 14
 
4.2%
이 11
 
3.3%
동 10
 
3.0%
차 8
 
2.4%
자 8
 
2.4%
성 8
 
2.4%
비 7
 
2.1%
Other values (104) 201
60.4%
Common
ValueCountFrequency (%)
( 24
44.4%
) 24
44.4%
6
 
11.1%
Latin
ValueCountFrequency (%)
S 1
33.3%
P 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 329
84.4%
ASCII 57
 
14.6%
None 4
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 33
 
10.0%
업 18
 
5.5%
공 15
 
4.6%
사 14
 
4.3%
이 11
 
3.3%
동 10
 
3.0%
차 8
 
2.4%
자 8
 
2.4%
성 8
 
2.4%
비 7
 
2.1%
Other values (103) 197
59.9%
ASCII
ValueCountFrequency (%)
( 24
42.1%
) 24
42.1%
6
 
10.5%
S 1
 
1.8%
P 1
 
1.8%
I 1
 
1.8%
None
ValueCountFrequency (%)
㈜ 4
100.0%

주소
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-04-18T17:53:44.720167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length26
Mean length21.086957
Min length16

Characters and Unicode

Total characters970
Distinct characters94
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row충청북도 충주시 동량면 6-1
2nd row충청북도 충주시 수안보면 온천리 778
3rd row충청북도 충주시 살미면 세성리 산 11-1
4th row충청북도 충주시 앙성면 조천리 56-1
5th row충청북도 충주시 산척면 명서리 74
ValueCountFrequency (%)
충청북도 46
20.9%
충주시 46
20.9%
봉방동 5
 
2.3%
주덕읍 5
 
2.3%
산척면 4
 
1.8%
동량면 4
 
1.8%
외 4
 
1.8%
목행동 3
 
1.4%
풍동 3
 
1.4%
당우리 2
 
0.9%
Other values (90) 98
44.5%
2024-04-18T17:53:45.260540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
21.4%
충 92
 
9.5%
주 52
 
5.4%
도 47
 
4.8%
북 46
 
4.7%
시 46
 
4.7%
청 46
 
4.7%
- 34
 
3.5%
1 34
 
3.5%
동 26
 
2.7%
Other values (84) 339
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 547
56.4%
Space Separator 208
 
21.4%
Decimal Number 177
 
18.2%
Dash Punctuation 34
 
3.5%
Other Punctuation 2
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 92
16.8%
주 52
 
9.5%
도 47
 
8.6%
북 46
 
8.4%
시 46
 
8.4%
청 46
 
8.4%
동 26
 
4.8%
리 22
 
4.0%
면 19
 
3.5%
덕 7
 
1.3%
Other values (69) 144
26.3%
Decimal Number
ValueCountFrequency (%)
1 34
19.2%
7 21
11.9%
2 20
11.3%
6 17
9.6%
3 17
9.6%
4 15
8.5%
5 15
8.5%
0 13
 
7.3%
8 13
 
7.3%
9 12
 
6.8%
Space Separator
ValueCountFrequency (%)
208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 547
56.4%
Common 423
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 92
16.8%
주 52
 
9.5%
도 47
 
8.6%
북 46
 
8.4%
시 46
 
8.4%
청 46
 
8.4%
동 26
 
4.8%
리 22
 
4.0%
면 19
 
3.5%
덕 7
 
1.3%
Other values (69) 144
26.3%
Common
ValueCountFrequency (%)
208
49.2%
- 34
 
8.0%
1 34
 
8.0%
7 21
 
5.0%
2 20
 
4.7%
6 17
 
4.0%
3 17
 
4.0%
4 15
 
3.5%
5 15
 
3.5%
0 13
 
3.1%
Other values (5) 29
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 547
56.4%
ASCII 423
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
49.2%
- 34
 
8.0%
1 34
 
8.0%
7 21
 
5.0%
2 20
 
4.7%
6 17
 
4.0%
3 17
 
4.0%
4 15
 
3.5%
5 15
 
3.5%
0 13
 
3.1%
Other values (5) 29
 
6.9%
Hangul
ValueCountFrequency (%)
충 92
16.8%
주 52
 
9.5%
도 47
 
8.6%
북 46
 
8.4%
시 46
 
8.4%
청 46
 
8.4%
동 26
 
4.8%
리 22
 
4.0%
면 19
 
3.5%
덕 7
 
1.3%
Other values (69) 144
26.3%

사용연료
Categorical

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
경유
35 
벙커C유
6 
등유
4 
벙커A유
 
1

Length

Max length4
Median length2
Mean length2.3043478
Min length2

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
경유 35
76.1%
벙커C유 6
 
13.0%
등유 4
 
8.7%
벙커A유 1
 
2.2%

Length

2024-04-18T17:53:45.447802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:53:45.593383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경유 35
76.1%
벙커c유 6
 
13.0%
등유 4
 
8.7%
벙커a유 1
 
2.2%

생산품
Text

Distinct34
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-04-18T17:53:45.822286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length4.2391304
Min length2

Characters and Unicode

Total characters195
Distinct characters71
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

Unique24 ?
Unique (%)52.2%

Sample

1st row콘크리트관
2nd row스팀 및 온수
3rd row아스팔트
4th row건고추
5th row백운석
ValueCountFrequency (%)
도장된차량 3
 
5.4%
자동차 3
 
5.4%
차량정비 3
 
5.4%
및 3
 
5.4%
건고추 2
 
3.6%
모래 2
 
3.6%
차량수선 2
 
3.6%
난방 2
 
3.6%
콘크리트관 2
 
3.6%
차량 2
 
3.6%
Other values (29) 32
57.1%
2024-04-18T17:53:46.284008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
차 19
 
9.7%
량 14
 
7.2%
10
 
5.1%
수 10
 
5.1%
자 7
 
3.6%
도 6
 
3.1%
장 6
 
3.1%
트 5
 
2.6%
정 5
 
2.6%
비 5
 
2.6%
Other values (61) 108
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 184
94.4%
Space Separator 10
 
5.1%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 19
 
10.3%
량 14
 
7.6%
수 10
 
5.4%
자 7
 
3.8%
도 6
 
3.3%
장 6
 
3.3%
트 5
 
2.7%
정 5
 
2.7%
비 5
 
2.7%
동 5
 
2.7%
Other values (59) 102
55.4%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 184
94.4%
Common 11
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 19
 
10.3%
량 14
 
7.6%
수 10
 
5.4%
자 7
 
3.8%
도 6
 
3.3%
장 6
 
3.3%
트 5
 
2.7%
정 5
 
2.7%
비 5
 
2.7%
동 5
 
2.7%
Other values (59) 102
55.4%
Common
ValueCountFrequency (%)
10
90.9%
, 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 184
94.4%
ASCII 11
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
차 19
 
10.3%
량 14
 
7.6%
수 10
 
5.4%
자 7
 
3.8%
도 6
 
3.3%
장 6
 
3.3%
트 5
 
2.7%
정 5
 
2.7%
비 5
 
2.7%
동 5
 
2.7%
Other values (59) 102
55.4%
ASCII
ValueCountFrequency (%)
10
90.9%
, 1
 
9.1%

연간 사용량
Text

Distinct35
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-04-18T17:53:46.521857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.6521739
Min length3

Characters and Unicode

Total characters260
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)58.7%

Sample

1st row609600L
2nd row100L
3rd row30L
4th row808000kg
5th row120000L
ValueCountFrequency (%)
18000l 4
 
8.7%
15900l 3
 
6.5%
12000l 2
 
4.3%
6600l 2
 
4.3%
19800l 2
 
4.3%
60000l 2
 
4.3%
30000l 2
 
4.3%
6000l 2
 
4.3%
65125l 1
 
2.2%
27000l 1
 
2.2%
Other values (25) 25
54.3%
2024-04-18T17:53:46.926360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 111
42.7%
L 45
17.3%
6 19
 
7.3%
1 18
 
6.9%
8 14
 
5.4%
9 12
 
4.6%
5 11
 
4.2%
2 11
 
4.2%
3 7
 
2.7%
4 6
 
2.3%
Other values (4) 6
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 212
81.5%
Uppercase Letter 45
 
17.3%
Lowercase Letter 2
 
0.8%
Other Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 111
52.4%
6 19
 
9.0%
1 18
 
8.5%
8 14
 
6.6%
9 12
 
5.7%
5 11
 
5.2%
2 11
 
5.2%
3 7
 
3.3%
4 6
 
2.8%
7 3
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
g 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
L 45
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 213
81.9%
Latin 47
 
18.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 111
52.1%
6 19
 
8.9%
1 18
 
8.5%
8 14
 
6.6%
9 12
 
5.6%
5 11
 
5.2%
2 11
 
5.2%
3 7
 
3.3%
4 6
 
2.8%
7 3
 
1.4%
Latin
ValueCountFrequency (%)
L 45
95.7%
k 1
 
2.1%
g 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 260
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 111
42.7%
L 45
17.3%
6 19
 
7.3%
1 18
 
6.9%
8 14
 
5.4%
9 12
 
4.6%
5 11
 
4.2%
2 11
 
4.2%
3 7
 
2.7%
4 6
 
2.3%
Other values (4) 6
 
2.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-09-30
46 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-30
2nd row2023-09-30
3rd row2023-09-30
4th row2023-09-30
5th row2023-09-30

Common Values

ValueCountFrequency (%)
2023-09-30 46
100.0%

Length

2024-04-18T17:53:47.106948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T17:53:47.233935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-30 46
100.0%

Correlations

2024-04-18T17:53:47.313138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호주소사용연료생산품연간 사용량
상호1.0001.0001.0000.9841.000
주소1.0001.0001.0001.0001.000
사용연료1.0001.0001.0000.9880.980
생산품0.9841.0000.9881.0000.893
연간 사용량1.0001.0000.9800.8931.000

Missing values

2024-04-18T17:53:43.662700image/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

상호주소사용연료생산품연간 사용량데이터기준일자
0유성콘크리트(주)충청북도 충주시 동량면 6-1벙커C유콘크리트관609600L2023-09-30
1(주)이랜드파크한국콘도수안보점충청북도 충주시 수안보면 온천리 778벙커C유스팀 및 온수100L2023-09-30
2정안산업(주)충청북도 충주시 살미면 세성리 산 11-1벙커C유아스팔트30L2023-09-30
3주식회사 명승충청북도 충주시 앙성면 조천리 56-1벙커C유건고추808000kg2023-09-30
4(주)성신충청북도 충주시 산척면 명서리 74벙커C유백운석120000L2023-09-30
5(주)케이이씨충청북도 충주시 풍동 579-11벙커C유콘크리트관45000L2023-09-30
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