Overview

Dataset statistics

Number of variables3
Number of observations226
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory24.6 B

Variable types

Categorical1
Text2

Dataset

Description□ 천연가스 공급설비의 분류(설비구성) 현황을 공개하여 중소기업이 가스공급시설의 설비별 구성내역 및 설비를 구성하는 계기, 경보설비 단위장치의 기기 등을 파악하고 민간기업의 완성품 및 우수 기술,제품의 사업화 및 판로, 기술개발 등 민간의 신규사업 창출에 도움이 되고자 함
URLhttps://www.data.go.kr/data/15117931/fileData.do

Reproduction

Analysis started2023-12-12 14:07:55.705085
Analysis finished2023-12-12 14:07:56.043173
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

1차 분류
Categorical

Distinct34
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
통제설비
26 
계량설비
18 
계기
17 
LCNG충전설비
17 
COMPACT형 가스히터 설비
14 
Other values (29)
134 

Length

Max length20
Median length14
Mean length9.1725664
Min length5

Unique

Unique5 ?
Unique (%)2.2%

Sample

1st row 가스필터설비
2nd row 일반형 가스히터 설비
3rd row 일반형 가스히터 설비
4th row 일반형 가스히터 설비
5th row 일반형 가스히터 설비

Common Values

ValueCountFrequency (%)
통제설비 26
 
11.5%
계량설비 18
 
8.0%
계기 17
 
7.5%
LCNG충전설비 17
 
7.5%
COMPACT형 가스히터 설비 14
 
6.2%
냉난방설비 13
 
5.8%
일반형 가스히터 설비 12
 
5.3%
부대설비 11
 
4.9%
승압설비 10
 
4.4%
정압설비 9
 
4.0%
Other values (24) 79
35.0%

Length

2023-12-12T23:07:56.121621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
설비 36
 
11.7%
통제설비 26
 
8.4%
가스히터 26
 
8.4%
계량설비 18
 
5.8%
lcng충전설비 17
 
5.5%
계기 17
 
5.5%
compact형 14
 
4.5%
냉난방설비 13
 
4.2%
일반형 12
 
3.9%
부대설비 11
 
3.6%
Other values (31) 119
38.5%

2차 분류
Text

Distinct175
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T23:07:56.479099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length11.181416
Min length4

Characters and Unicode

Total characters2527
Distinct characters167
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

Unique140 ?
Unique (%)61.9%

Sample

1st row 가스필터
2nd row HTR-31A
3rd row HTR-32A
4th row HTR-33A
5th row HTR-34A
ValueCountFrequency (%)
panel 8
 
2.6%
지시계 6
 
2.0%
gas 6
 
2.0%
전송기 6
 
2.0%
태양열 5
 
1.6%
온수시스템 5
 
1.6%
detector 5
 
1.6%
transmitter 4
 
1.3%
compressor 4
 
1.3%
server 4
 
1.3%
Other values (200) 253
82.7%
2023-12-12T23:07:56.975965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
768
30.4%
R 141
 
5.6%
T 138
 
5.5%
E 128
 
5.1%
A 103
 
4.1%
N 76
 
3.0%
I 75
 
3.0%
S 68
 
2.7%
O 67
 
2.7%
P 58
 
2.3%
Other values (157) 905
35.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1174
46.5%
Space Separator 770
30.5%
Other Letter 470
18.6%
Decimal Number 66
 
2.6%
Dash Punctuation 34
 
1.3%
Close Punctuation 5
 
0.2%
Open Punctuation 5
 
0.2%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 36
 
7.7%
전 18
 
3.8%
시 15
 
3.2%
지 15
 
3.2%
스 15
 
3.2%
비 14
 
3.0%
계 14
 
3.0%
설 13
 
2.8%
수 12
 
2.6%
반 11
 
2.3%
Other values (116) 307
65.3%
Uppercase Letter
ValueCountFrequency (%)
R 141
12.0%
T 138
11.8%
E 128
10.9%
A 103
 
8.8%
N 76
 
6.5%
I 75
 
6.4%
S 68
 
5.8%
O 67
 
5.7%
P 58
 
4.9%
C 56
 
4.8%
Other values (15) 264
22.5%
Decimal Number
ValueCountFrequency (%)
3 21
31.8%
4 18
27.3%
1 5
 
7.6%
2 5
 
7.6%
9 3
 
4.5%
7 3
 
4.5%
6 3
 
4.5%
5 3
 
4.5%
8 3
 
4.5%
0 2
 
3.0%
Space Separator
ValueCountFrequency (%)
768
99.7%
　 2
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1174
46.5%
Common 883
34.9%
Hangul 470
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 36
 
7.7%
전 18
 
3.8%
시 15
 
3.2%
지 15
 
3.2%
스 15
 
3.2%
비 14
 
3.0%
계 14
 
3.0%
설 13
 
2.8%
수 12
 
2.6%
반 11
 
2.3%
Other values (116) 307
65.3%
Latin
ValueCountFrequency (%)
R 141
12.0%
T 138
11.8%
E 128
10.9%
A 103
 
8.8%
N 76
 
6.5%
I 75
 
6.4%
S 68
 
5.8%
O 67
 
5.7%
P 58
 
4.9%
C 56
 
4.8%
Other values (15) 264
22.5%
Common
ValueCountFrequency (%)
768
87.0%
- 34
 
3.9%
3 21
 
2.4%
4 18
 
2.0%
1 5
 
0.6%
) 5
 
0.6%
( 5
 
0.6%
2 5
 
0.6%
9 3
 
0.3%
7 3
 
0.3%
Other values (6) 16
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2055
81.3%
Hangul 470
 
18.6%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
768
37.4%
R 141
 
6.9%
T 138
 
6.7%
E 128
 
6.2%
A 103
 
5.0%
N 76
 
3.7%
I 75
 
3.6%
S 68
 
3.3%
O 67
 
3.3%
P 58
 
2.8%
Other values (30) 433
21.1%
Hangul
ValueCountFrequency (%)
기 36
 
7.7%
전 18
 
3.8%
시 15
 
3.2%
지 15
 
3.2%
스 15
 
3.2%
비 14
 
3.0%
계 14
 
3.0%
설 13
 
2.8%
수 12
 
2.6%
반 11
 
2.3%
Other values (116) 307
65.3%
None
ValueCountFrequency (%)
　 2
100.0%

3차 분류
Text

Distinct69
Distinct (%)30.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T23:07:57.296280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length4
Mean length7.3628319
Min length3

Characters and Unicode

Total characters1664
Distinct characters77
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

Unique55 ?
Unique (%)24.3%

Sample

1st row
2nd row HEATER 본체
3rd row 가스히터용 FILTER
4th row BLOWER
5th row 가스히터용 PCV
ValueCountFrequency (%)
가스히터용 6
 
4.6%
pressure 6
 
4.6%
transmitter 5
 
3.8%
indicator 5
 
3.8%
temperature 4
 
3.1%
level 4
 
3.1%
detector 4
 
3.1%
controller 3
 
2.3%
pcv 3
 
2.3%
승압설비용 3
 
2.3%
Other values (64) 88
67.2%
2023-12-12T23:07:57.789069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
754
45.3%
　 120
 
7.2%
E 98
 
5.9%
R 89
 
5.3%
T 74
 
4.4%
I 40
 
2.4%
L 36
 
2.2%
O 34
 
2.0%
A 34
 
2.0%
S 31
 
1.9%
Other values (67) 354
21.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 874
52.5%
Uppercase Letter 612
36.8%
Other Letter 175
 
10.5%
Decimal Number 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 14
 
8.0%
터 11
 
6.3%
스 11
 
6.3%
기 9
 
5.1%
가 9
 
5.1%
히 7
 
4.0%
열 6
 
3.4%
프 6
 
3.4%
펌 6
 
3.4%
압 5
 
2.9%
Other values (41) 91
52.0%
Uppercase Letter
ValueCountFrequency (%)
E 98
16.0%
R 89
14.5%
T 74
12.1%
I 40
 
6.5%
L 36
 
5.9%
O 34
 
5.6%
A 34
 
5.6%
S 31
 
5.1%
C 30
 
4.9%
N 30
 
4.9%
Other values (11) 116
19.0%
Space Separator
ValueCountFrequency (%)
754
86.3%
　 120
 
13.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 877
52.7%
Latin 612
36.8%
Hangul 175
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 14
 
8.0%
터 11
 
6.3%
스 11
 
6.3%
기 9
 
5.1%
가 9
 
5.1%
히 7
 
4.0%
열 6
 
3.4%
프 6
 
3.4%
펌 6
 
3.4%
압 5
 
2.9%
Other values (41) 91
52.0%
Latin
ValueCountFrequency (%)
E 98
16.0%
R 89
14.5%
T 74
12.1%
I 40
 
6.5%
L 36
 
5.9%
O 34
 
5.6%
A 34
 
5.6%
S 31
 
5.1%
C 30
 
4.9%
N 30
 
4.9%
Other values (11) 116
19.0%
Common
ValueCountFrequency (%)
754
86.0%
　 120
 
13.7%
- 1
 
0.1%
2 1
 
0.1%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1369
82.3%
Hangul 175
 
10.5%
None 120
 
7.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
754
55.1%
E 98
 
7.2%
R 89
 
6.5%
T 74
 
5.4%
I 40
 
2.9%
L 36
 
2.6%
O 34
 
2.5%
A 34
 
2.5%
S 31
 
2.3%
C 30
 
2.2%
Other values (15) 149
 
10.9%
None
ValueCountFrequency (%)
　 120
100.0%
Hangul
ValueCountFrequency (%)
용 14
 
8.0%
터 11
 
6.3%
스 11
 
6.3%
기 9
 
5.1%
가 9
 
5.1%
히 7
 
4.0%
열 6
 
3.4%
프 6
 
3.4%
펌 6
 
3.4%
압 5
 
2.9%
Other values (41) 91
52.0%

Correlations

2023-12-12T23:07:57.906776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1차 분류3차 분류
1차 분류1.0000.000
3차 분류0.0001.000

Missing values

2023-12-12T23:07:55.928518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:07:56.014049image/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

1차 분류2차 분류3차 분류
0가스필터설비가스필터
1일반형 가스히터 설비HTR-31AHEATER 본체
2일반형 가스히터 설비HTR-32A가스히터용 FILTER
3일반형 가스히터 설비HTR-33ABLOWER
4일반형 가스히터 설비HTR-34A가스히터용 PCV
5일반형 가스히터 설비HTR-35AFLAME DETECTOR
6일반형 가스히터 설비HTR-36AGAS DETECTOR
7일반형 가스히터 설비HTR-37ACONTROL PANEL
8일반형 가스히터 설비HTR-38ABURNER CONTROLLER
9일반형 가스히터 설비HTR-39ATIC
1차 분류2차 분류3차 분류
216부대설비통신설비
217부대설비소화설비주펌프
218부대설비소화설비물탱크
219부대설비기타설비
220배관
221배관 부속시설물TB
222배관 부속시설물GLP
223배관 부속시설물표시못
224배관 부속시설물표지판
225배관 부속시설물표석