Overview

Dataset statistics

Number of variables6
Number of observations103
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory50.3 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description익산시 관내 가스판매 및 충전소의 상호, 사업의 종류, 대표자, 도로명주소, 전화번호 등의 데이터를 제공하고 있습니다.
Author전라북도 익산시
URLhttps://www.data.go.kr/data/3079211/fileData.do

Alerts

순번 is highly overall correlated with 사업의종류High correlation
사업의종류 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:18:55.955222
Analysis finished2023-12-12 08:18:57.204196
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct103
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52
Minimum1
Maximum103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T17:18:57.308976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.1
Q126.5
median52
Q377.5
95-th percentile97.9
Maximum103
Range102
Interquartile range (IQR)51

Descriptive statistics

Standard deviation29.877528
Coefficient of variation (CV)0.57456784
Kurtosis-1.2
Mean52
Median Absolute Deviation (MAD)26
Skewness0
Sum5356
Variance892.66667
MonotonicityStrictly increasing
2023-12-12T17:18:57.514605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
2 1
 
1.0%
77 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
Other values (93) 93
90.3%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
103 1
1.0%
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%

법인명(상호)
Text

Distinct86
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size956.0 B
2023-12-12T17:18:57.834517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length6.6116505
Min length4

Characters and Unicode

Total characters681
Distinct characters115
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)68.0%

Sample

1st row승리산업가스
2nd row굿모닝신용특수가스
3rd row(주)삼화에너지 가스판매
4th row영생종합가스
5th row한신특수가스
ValueCountFrequency (%)
주)삼화에너지 5
 
4.5%
한국특수가스(주 3
 
2.7%
문화종합가스 2
 
1.8%
왕궁가스 2
 
1.8%
대한가스 2
 
1.8%
굿모닝신용특수가스 2
 
1.8%
신흥가스 2
 
1.8%
용안가스 2
 
1.8%
황등가스 2
 
1.8%
마한가스 2
 
1.8%
Other values (80) 88
78.6%
2023-12-12T17:18:58.349123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 74
 
10.9%
가 73
 
10.7%
소 23
 
3.4%
전 22
 
3.2%
) 21
 
3.1%
( 20
 
2.9%
충 18
 
2.6%
지 18
 
2.6%
산 16
 
2.3%
대 16
 
2.3%
Other values (105) 380
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 602
88.4%
Uppercase Letter 29
 
4.3%
Close Punctuation 21
 
3.1%
Open Punctuation 20
 
2.9%
Space Separator 9
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 74
 
12.3%
가 73
 
12.1%
소 23
 
3.8%
전 22
 
3.7%
충 18
 
3.0%
지 18
 
3.0%
산 16
 
2.7%
대 16
 
2.7%
에 16
 
2.7%
한 16
 
2.7%
Other values (97) 310
51.5%
Uppercase Letter
ValueCountFrequency (%)
L 9
31.0%
G 9
31.0%
P 9
31.0%
I 1
 
3.4%
C 1
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 602
88.4%
Common 50
 
7.3%
Latin 29
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 74
 
12.3%
가 73
 
12.1%
소 23
 
3.8%
전 22
 
3.7%
충 18
 
3.0%
지 18
 
3.0%
산 16
 
2.7%
대 16
 
2.7%
에 16
 
2.7%
한 16
 
2.7%
Other values (97) 310
51.5%
Latin
ValueCountFrequency (%)
L 9
31.0%
G 9
31.0%
P 9
31.0%
I 1
 
3.4%
C 1
 
3.4%
Common
ValueCountFrequency (%)
) 21
42.0%
( 20
40.0%
9
18.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 602
88.4%
ASCII 79
 
11.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 74
 
12.3%
가 73
 
12.1%
소 23
 
3.8%
전 22
 
3.7%
충 18
 
3.0%
지 18
 
3.0%
산 16
 
2.7%
대 16
 
2.7%
에 16
 
2.7%
한 16
 
2.7%
Other values (97) 310
51.5%
ASCII
ValueCountFrequency (%)
) 21
26.6%
( 20
25.3%
L 9
11.4%
9
11.4%
G 9
11.4%
P 9
11.4%
I 1
 
1.3%
C 1
 
1.3%

사업의종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
액화석유가스판매
58 
액화석유가스충전
23 
고압가스판매
22 

Length

Max length8
Median length8
Mean length7.5728155
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
액화석유가스판매 58
56.3%
액화석유가스충전 23
 
22.3%
고압가스판매 22
 
21.4%

Length

2023-12-12T17:18:58.511091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:18:58.680940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
액화석유가스판매 58
56.3%
액화석유가스충전 23
 
22.3%
고압가스판매 22
 
21.4%

사업소소재지
Text

Distinct86
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size956.0 B
2023-12-12T17:18:59.095763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length22.165049
Min length18

Characters and Unicode

Total characters2283
Distinct characters119
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

Unique69 ?
Unique (%)67.0%

Sample

1st row전라북도 익산시 석암로 169 (석암동)
2nd row전라북도 익산시 황등면 죽촌리 224-5번지
3rd row전라북도 익산시 함열읍 익산대로 1899
4th row전라북도 익산시 계문길 47-5 (현영동)
5th row전라북도 익산시 삼기면 간촌길 11
ValueCountFrequency (%)
전라북도 103
 
19.9%
익산시 103
 
19.9%
금강동 8
 
1.5%
황등면 7
 
1.4%
함열읍 7
 
1.4%
익산대로 6
 
1.2%
낭산면 6
 
1.2%
신용동 6
 
1.2%
오산면 6
 
1.2%
춘포면 5
 
1.0%
Other values (173) 261
50.4%
2023-12-12T17:18:59.618847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
425
18.6%
산 129
 
5.7%
익 111
 
4.9%
도 106
 
4.6%
라 106
 
4.6%
북 105
 
4.6%
전 103
 
4.5%
시 103
 
4.5%
1 90
 
3.9%
로 60
 
2.6%
Other values (109) 945
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1399
61.3%
Space Separator 425
 
18.6%
Decimal Number 343
 
15.0%
Close Punctuation 46
 
2.0%
Open Punctuation 46
 
2.0%
Dash Punctuation 22
 
1.0%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 129
 
9.2%
익 111
 
7.9%
도 106
 
7.6%
라 106
 
7.6%
북 105
 
7.5%
전 103
 
7.4%
시 103
 
7.4%
로 60
 
4.3%
동 58
 
4.1%
길 53
 
3.8%
Other values (94) 465
33.2%
Decimal Number
ValueCountFrequency (%)
1 90
26.2%
3 47
13.7%
2 35
 
10.2%
6 34
 
9.9%
5 30
 
8.7%
9 26
 
7.6%
0 23
 
6.7%
8 21
 
6.1%
4 19
 
5.5%
7 18
 
5.2%
Space Separator
ValueCountFrequency (%)
425
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1399
61.3%
Common 884
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 129
 
9.2%
익 111
 
7.9%
도 106
 
7.6%
라 106
 
7.6%
북 105
 
7.5%
전 103
 
7.4%
시 103
 
7.4%
로 60
 
4.3%
동 58
 
4.1%
길 53
 
3.8%
Other values (94) 465
33.2%
Common
ValueCountFrequency (%)
425
48.1%
1 90
 
10.2%
3 47
 
5.3%
) 46
 
5.2%
( 46
 
5.2%
2 35
 
4.0%
6 34
 
3.8%
5 30
 
3.4%
9 26
 
2.9%
0 23
 
2.6%
Other values (5) 82
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1399
61.3%
ASCII 884
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
425
48.1%
1 90
 
10.2%
3 47
 
5.3%
) 46
 
5.2%
( 46
 
5.2%
2 35
 
4.0%
6 34
 
3.8%
5 30
 
3.4%
9 26
 
2.9%
0 23
 
2.6%
Other values (5) 82
 
9.3%
Hangul
ValueCountFrequency (%)
산 129
 
9.2%
익 111
 
7.9%
도 106
 
7.6%
라 106
 
7.6%
북 105
 
7.5%
전 103
 
7.4%
시 103
 
7.4%
로 60
 
4.3%
동 58
 
4.1%
길 53
 
3.8%
Other values (94) 465
33.2%

대표자명
Text

Distinct80
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Memory size956.0 B
2023-12-12T17:18:59.978652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.961165
Min length2

Characters and Unicode

Total characters305
Distinct characters103
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)58.3%

Sample

1st row한신
2nd row최동진
3rd row손주환
4th row윤미애
5th row이정옥
ValueCountFrequency (%)
한신 3
 
2.9%
김순자 3
 
2.9%
서흥남 3
 
2.9%
조정현 2
 
1.9%
최광석 2
 
1.9%
이중근 2
 
1.9%
유기춘 2
 
1.9%
이영구 2
 
1.9%
박원우 2
 
1.9%
김대성 2
 
1.9%
Other values (70) 80
77.7%
2023-12-12T17:19:00.541118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 19
 
6.2%
김 16
 
5.2%
최 9
 
3.0%
박 8
 
2.6%
영 7
 
2.3%
상 7
 
2.3%
정 7
 
2.3%
진 6
 
2.0%
남 6
 
2.0%
순 6
 
2.0%
Other values (93) 214
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 19
 
6.2%
김 16
 
5.2%
최 9
 
3.0%
박 8
 
2.6%
영 7
 
2.3%
상 7
 
2.3%
정 7
 
2.3%
진 6
 
2.0%
남 6
 
2.0%
순 6
 
2.0%
Other values (93) 214
70.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 19
 
6.2%
김 16
 
5.2%
최 9
 
3.0%
박 8
 
2.6%
영 7
 
2.3%
상 7
 
2.3%
정 7
 
2.3%
진 6
 
2.0%
남 6
 
2.0%
순 6
 
2.0%
Other values (93) 214
70.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 19
 
6.2%
김 16
 
5.2%
최 9
 
3.0%
박 8
 
2.6%
영 7
 
2.3%
상 7
 
2.3%
정 7
 
2.3%
진 6
 
2.0%
남 6
 
2.0%
순 6
 
2.0%
Other values (93) 214
70.2%

전화번호
Text

Distinct84
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Memory size956.0 B
2023-12-12T17:19:00.794781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1236
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

Unique65 ?
Unique (%)63.1%

Sample

1st row063-835-0848
2nd row063-854-8777
3rd row063-861-5144
4th row063-857-0070
5th row063-842-6060
ValueCountFrequency (%)
063-835-0848 2
 
1.9%
063-836-6953 2
 
1.9%
063-832-4585 2
 
1.9%
063-856-7297 2
 
1.9%
063-862-3737 2
 
1.9%
063-861-8878 2
 
1.9%
063-856-2320 2
 
1.9%
063-861-3440 2
 
1.9%
063-836-3451 2
 
1.9%
063-858-8111 2
 
1.9%
Other values (74) 83
80.6%
2023-12-12T17:19:01.161224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 206
16.7%
3 174
14.1%
0 172
13.9%
6 166
13.4%
8 155
12.5%
5 89
7.2%
7 66
 
5.3%
4 65
 
5.3%
1 60
 
4.9%
2 53
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1030
83.3%
Dash Punctuation 206
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 174
16.9%
0 172
16.7%
6 166
16.1%
8 155
15.0%
5 89
8.6%
7 66
 
6.4%
4 65
 
6.3%
1 60
 
5.8%
2 53
 
5.1%
9 30
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 206
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1236
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 206
16.7%
3 174
14.1%
0 172
13.9%
6 166
13.4%
8 155
12.5%
5 89
7.2%
7 66
 
5.3%
4 65
 
5.3%
1 60
 
4.9%
2 53
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1236
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 206
16.7%
3 174
14.1%
0 172
13.9%
6 166
13.4%
8 155
12.5%
5 89
7.2%
7 66
 
5.3%
4 65
 
5.3%
1 60
 
4.9%
2 53
 
4.3%

Interactions

2023-12-12T17:18:56.841022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:19:01.298830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번법인명(상호)사업의종류사업소소재지대표자명전화번호
순번1.0000.0000.9450.0000.4380.000
법인명(상호)0.0001.0000.0001.0001.0000.999
사업의종류0.9450.0001.0000.0000.0000.000
사업소소재지0.0001.0000.0001.0001.0000.999
대표자명0.4381.0000.0001.0001.0001.000
전화번호0.0000.9990.0000.9991.0001.000
2023-12-12T17:19:01.405652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번사업의종류
순번1.0000.900
사업의종류0.9001.000

Missing values

2023-12-12T17:18:56.974381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:18:57.141812image/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

순번법인명(상호)사업의종류사업소소재지대표자명전화번호
01승리산업가스고압가스판매전라북도 익산시 석암로 169 (석암동)한신063-835-0848
12굿모닝신용특수가스고압가스판매전라북도 익산시 황등면 죽촌리 224-5번지최동진063-854-8777
23(주)삼화에너지 가스판매고압가스판매전라북도 익산시 함열읍 익산대로 1899손주환063-861-5144
34영생종합가스고압가스판매전라북도 익산시 계문길 47-5 (현영동)윤미애063-857-0070
45한신특수가스고압가스판매전라북도 익산시 삼기면 간촌길 11이정옥063-842-6060
56가스켐솔루션(주)고압가스판매전라북도 익산시 낭산면 함낭로 1032-36조정현063-861-0494
67한국특수가스(주)고압가스판매전라북도 익산시 석암로7길 19 (용제동)서흥남063-833-8383
78금마가스고압가스판매전라북도 익산시 금마면 미륵사지로1길 64-11송상섭063-836-6953
89대영가스고압가스판매전라북도 익산시 여산면 태성길 19이승복063-836-5465
910대명산소고압가스판매전라북도 익산시 황등면 죽촌1길 9김종오063-858-4050
순번법인명(상호)사업의종류사업소소재지대표자명전화번호
9394우리가스액화석유가스판매전라북도 익산시 선화로30길 60-13 (신흥동)조기덕063-853-2448
9495부송에너지 협동조합액화석유가스판매전라북도 익산시 부평1길 19 (부송동)윤성식063-832-0600
9596신흥가스액화석유가스판매전라북도 익산시 망성면 동안로 300이영구063-861-8878
9697대성가스액화석유가스판매전라북도 익산시 성당면 강변로 981박옥순063-837-5800
9798문화종합가스액화석유가스판매전라북도 익산시 삼기면 검지길 33최광석063-858-8111
9899린나이가스액화석유가스판매전라북도 익산시 춘포면 춘포4길 66-2김경숙063-842-8040
99100낭산가스액화석유가스판매전라북도 익산시 낭산면 호천길 76최인규063-861-2475
100101대영가스액화석유가스판매전라북도 익산시 여산면 태성길 19이승복063-836-5465
101102대한가스액화석유가스판매전라북도 익산시 오산면 서오산1길 23이삼용063-856-7707
102103한국가스액화석유가스판매전라북도 익산시 서동로27길 95 (신흥동)소순준063-834-0015