Overview

Dataset statistics

Number of variables10
Number of observations906
Missing cells160
Missing cells (%)1.8%
Duplicate rows6
Duplicate rows (%)0.7%
Total size in memory71.8 KiB
Average record size in memory81.1 B

Variable types

Categorical3
Text5
DateTime1
Numeric1

Dataset

Description강원도 가스사업자 정보(구분, 업체명, 취급품목, 허가일자, 연락처, 소재지도로명주소, 위치 위도/경도 등) 데이터를 제공합니다.
Author강원도
URLhttps://www.data.go.kr/data/15033688/fileData.do

Alerts

시도명 has constant value ""Constant
Dataset has 6 (0.7%) duplicate rowsDuplicates
위도 is highly overall correlated with 시군구명High correlation
시군구명 is highly overall correlated with 위도High correlation
연락처 has 93 (10.3%) missing valuesMissing
소재지도로명주소 has 66 (7.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 04:17:27.982735
Analysis finished2023-12-12 04:17:29.718800
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
강원도
906 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 906
100.0%

Length

2023-12-12T13:17:29.807615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:17:29.911066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 906
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
원주시
174 
강릉시
95 
횡성군
91 
평창군
89 
고성군
53 
Other values (13)
404 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원주시 174
19.2%
강릉시 95
10.5%
횡성군 91
10.0%
평창군 89
9.8%
고성군 53
 
5.8%
춘천시 53
 
5.8%
영월군 51
 
5.6%
삼척시 48
 
5.3%
홍천군 48
 
5.3%
인제군 34
 
3.8%
Other values (8) 170
18.8%

Length

2023-12-12T13:17:30.015851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
원주시 174
19.2%
강릉시 95
10.5%
횡성군 91
10.0%
평창군 89
9.8%
고성군 53
 
5.8%
춘천시 53
 
5.8%
영월군 51
 
5.6%
삼척시 48
 
5.3%
홍천군 48
 
5.3%
인제군 34
 
3.8%
Other values (8) 170
18.8%

구분
Categorical

Distinct16
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
LPG판매
292 
고압가스제조
229 
LPG충전
140 
고압가스판매
89 
고압가스저장
47 
Other values (11)
109 

Length

Max length14
Median length12
Mean length5.4227373
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
LPG판매 292
32.2%
고압가스제조 229
25.3%
LPG충전 140
15.5%
고압가스판매 89
 
9.8%
고압가스저장 47
 
5.2%
집단공급 38
 
4.2%
기타 30
 
3.3%
특정고압가스 14
 
1.5%
고압가스제조(냉동제조) 11
 
1.2%
CNG충전 5
 
0.6%
Other values (6) 11
 
1.2%

Length

2023-12-12T13:17:30.156855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
lpg판매 292
32.2%
고압가스제조 229
25.3%
lpg충전 140
15.5%
고압가스판매 89
 
9.8%
고압가스저장 47
 
5.2%
집단공급 38
 
4.2%
기타 30
 
3.3%
특정고압가스 14
 
1.5%
고압가스제조(냉동제조 11
 
1.2%
cng충전 5
 
0.6%
Other values (6) 11
 
1.2%

업체명
Text

Distinct674
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T13:17:30.501173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length7.7064018
Min length3

Characters and Unicode

Total characters6982
Distinct characters396
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique544 ?
Unique (%)60.0%

Sample

1st row강릉아이스아레나
2nd row강원도청 강릉 아이스하키Ⅱ 주경기장
3rd row강원도청 강릉 아이스하키Ⅱ 보조경기장
4th row강원도청 스피드스케이팅경기장
5th row강원도청 아이스하키 Ⅰ주경기장
ValueCountFrequency (%)
주식회사 27
 
2.5%
현대가스 12
 
1.1%
강원도개발공사 10
 
0.9%
강원가스 10
 
0.9%
서울대학교 9
 
0.8%
국립대학법인 8
 
0.7%
동방산업(주 7
 
0.7%
주)덕일 7
 
0.7%
우리가스 6
 
0.6%
강원도청 6
 
0.6%
Other values (739) 966
90.4%
2023-12-12T13:17:31.067509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 434
 
6.2%
가 389
 
5.6%
주 273
 
3.9%
( 258
 
3.7%
) 258
 
3.7%
162
 
2.3%
소 148
 
2.1%
원 146
 
2.1%
대 142
 
2.0%
전 140
 
2.0%
Other values (386) 4632
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6037
86.5%
Open Punctuation 258
 
3.7%
Close Punctuation 258
 
3.7%
Space Separator 162
 
2.3%
Uppercase Letter 148
 
2.1%
Other Symbol 50
 
0.7%
Decimal Number 45
 
0.6%
Other Punctuation 15
 
0.2%
Letter Number 4
 
0.1%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 434
 
7.2%
가 389
 
6.4%
주 273
 
4.5%
소 148
 
2.5%
원 146
 
2.4%
대 142
 
2.4%
전 140
 
2.3%
지 135
 
2.2%
동 128
 
2.1%
충 120
 
2.0%
Other values (345) 3982
66.0%
Uppercase Letter
ValueCountFrequency (%)
G 34
23.0%
P 32
21.6%
L 32
21.6%
C 14
9.5%
K 6
 
4.1%
S 6
 
4.1%
N 5
 
3.4%
A 5
 
3.4%
O 3
 
2.0%
T 2
 
1.4%
Other values (7) 9
 
6.1%
Decimal Number
ValueCountFrequency (%)
2 9
20.0%
8 8
17.8%
5 7
15.6%
1 6
13.3%
6 5
11.1%
3 4
8.9%
7 3
 
6.7%
0 3
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 6
40.0%
. 4
26.7%
/ 3
20.0%
& 1
 
6.7%
· 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
p 1
25.0%
o 1
25.0%
h 1
25.0%
a 1
25.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 258
100.0%
Close Punctuation
ValueCountFrequency (%)
) 258
100.0%
Space Separator
ValueCountFrequency (%)
162
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6087
87.2%
Common 739
 
10.6%
Latin 156
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 434
 
7.1%
가 389
 
6.4%
주 273
 
4.5%
소 148
 
2.4%
원 146
 
2.4%
대 142
 
2.3%
전 140
 
2.3%
지 135
 
2.2%
동 128
 
2.1%
충 120
 
2.0%
Other values (346) 4032
66.2%
Latin
ValueCountFrequency (%)
G 34
21.8%
P 32
20.5%
L 32
20.5%
C 14
9.0%
K 6
 
3.8%
S 6
 
3.8%
N 5
 
3.2%
A 5
 
3.2%
O 3
 
1.9%
T 2
 
1.3%
Other values (13) 17
10.9%
Common
ValueCountFrequency (%)
( 258
34.9%
) 258
34.9%
162
21.9%
2 9
 
1.2%
8 8
 
1.1%
5 7
 
0.9%
1 6
 
0.8%
, 6
 
0.8%
6 5
 
0.7%
. 4
 
0.5%
Other values (7) 16
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6037
86.5%
ASCII 890
 
12.7%
None 51
 
0.7%
Number Forms 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 434
 
7.2%
가 389
 
6.4%
주 273
 
4.5%
소 148
 
2.5%
원 146
 
2.4%
대 142
 
2.4%
전 140
 
2.3%
지 135
 
2.2%
동 128
 
2.1%
충 120
 
2.0%
Other values (345) 3982
66.0%
ASCII
ValueCountFrequency (%)
( 258
29.0%
) 258
29.0%
162
18.2%
G 34
 
3.8%
P 32
 
3.6%
L 32
 
3.6%
C 14
 
1.6%
2 9
 
1.0%
8 8
 
0.9%
5 7
 
0.8%
Other values (27) 76
 
8.5%
None
ValueCountFrequency (%)
㈜ 50
98.0%
· 1
 
2.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%

취급품목
Text

Distinct272
Distinct (%)30.1%
Missing1
Missing (%)0.1%
Memory size7.2 KiB
2023-12-12T13:17:31.309860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length87
Mean length9.8066298
Min length2

Characters and Unicode

Total characters8875
Distinct characters109
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique219 ?
Unique (%)24.2%

Sample

1st row프레온
2nd row프레온
3rd row프레온
4th row프레온
5th row프레온
ValueCountFrequency (%)
액화석유가스 418
32.4%
산소 61
 
4.7%
질소 53
 
4.1%
프레온 46
 
3.6%
아르곤 44
 
3.4%
아세틸렌 35
 
2.7%
탄산가스 34
 
2.6%
산소(0kg/㎠ 28
 
2.2%
프로판 24
 
1.9%
수소 21
 
1.6%
Other values (284) 525
40.7%
2023-12-12T13:17:31.760844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 545
 
6.1%
스 545
 
6.1%
화 512
 
5.8%
액 494
 
5.6%
석 470
 
5.3%
유 470
 
5.3%
) 417
 
4.7%
( 416
 
4.7%
, 385
 
4.3%
385
 
4.3%
Other values (99) 4236
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5306
59.8%
Decimal Number 993
 
11.2%
Other Punctuation 624
 
7.0%
Close Punctuation 417
 
4.7%
Open Punctuation 416
 
4.7%
Space Separator 385
 
4.3%
Uppercase Letter 361
 
4.1%
Lowercase Letter 201
 
2.3%
Other Symbol 165
 
1.9%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 545
 
10.3%
스 545
 
10.3%
화 512
 
9.6%
액 494
 
9.3%
석 470
 
8.9%
유 470
 
8.9%
소 261
 
4.9%
프 215
 
4.1%
온 213
 
4.0%
레 209
 
3.9%
Other values (68) 1372
25.9%
Decimal Number
ValueCountFrequency (%)
0 270
27.2%
2 148
14.9%
1 118
11.9%
4 86
 
8.7%
9 72
 
7.3%
5 67
 
6.7%
6 65
 
6.5%
7 56
 
5.6%
3 56
 
5.6%
8 55
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
K 138
38.2%
T 106
29.4%
R 106
29.4%
N 3
 
0.8%
C 3
 
0.8%
G 3
 
0.8%
S 1
 
0.3%
F 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 385
61.7%
/ 121
 
19.4%
. 118
 
18.9%
Lowercase Letter
ValueCountFrequency (%)
g 169
84.1%
k 31
 
15.4%
a 1
 
0.5%
Other Symbol
ValueCountFrequency (%)
㎠ 121
73.3%
㎥ 41
 
24.8%
㎏ 3
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 417
100.0%
Open Punctuation
ValueCountFrequency (%)
( 416
100.0%
Space Separator
ValueCountFrequency (%)
385
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5306
59.8%
Common 3007
33.9%
Latin 562
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 545
 
10.3%
스 545
 
10.3%
화 512
 
9.6%
액 494
 
9.3%
석 470
 
8.9%
유 470
 
8.9%
소 261
 
4.9%
프 215
 
4.1%
온 213
 
4.0%
레 209
 
3.9%
Other values (68) 1372
25.9%
Common
ValueCountFrequency (%)
) 417
13.9%
( 416
13.8%
, 385
12.8%
385
12.8%
0 270
9.0%
2 148
 
4.9%
/ 121
 
4.0%
㎠ 121
 
4.0%
1 118
 
3.9%
. 118
 
3.9%
Other values (10) 508
16.9%
Latin
ValueCountFrequency (%)
g 169
30.1%
K 138
24.6%
T 106
18.9%
R 106
18.9%
k 31
 
5.5%
N 3
 
0.5%
C 3
 
0.5%
G 3
 
0.5%
S 1
 
0.2%
F 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5306
59.8%
ASCII 3404
38.4%
CJK Compat 165
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 545
 
10.3%
스 545
 
10.3%
화 512
 
9.6%
액 494
 
9.3%
석 470
 
8.9%
유 470
 
8.9%
소 261
 
4.9%
프 215
 
4.1%
온 213
 
4.0%
레 209
 
3.9%
Other values (68) 1372
25.9%
ASCII
ValueCountFrequency (%)
) 417
12.3%
( 416
12.2%
, 385
11.3%
385
11.3%
0 270
 
7.9%
g 169
 
5.0%
2 148
 
4.3%
K 138
 
4.1%
/ 121
 
3.6%
1 118
 
3.5%
Other values (18) 837
24.6%
CJK Compat
ValueCountFrequency (%)
㎠ 121
73.3%
㎥ 41
 
24.8%
㎏ 3
 
1.8%

허가일자
Date

Distinct750
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
Minimum1977-02-15 00:00:00
Maximum2018-01-23 00:00:00
2023-12-12T13:17:31.935575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:17:32.160603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

연락처
Text

MISSING 

Distinct620
Distinct (%)76.3%
Missing93
Missing (%)10.3%
Memory size7.2 KiB
2023-12-12T13:17:32.457153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length12
Mean length11.97909
Min length1

Characters and Unicode

Total characters9739
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique512 ?
Unique (%)63.0%

Sample

1st row033-249-3281
2nd row033-249-3281
3rd row033-249-3281
4th row033-249-3281
5th row033-249-3281
ValueCountFrequency (%)
02-880-5149 12
 
1.5%
033-332-4427 10
 
1.2%
033-635-5913 8
 
1.0%
033-249-3281 7
 
0.9%
031-972-1480 6
 
0.7%
033-374-2620 6
 
0.7%
033-745-1517 6
 
0.7%
033-734-2676 5
 
0.6%
033-646-6671 5
 
0.6%
033-330-6000 5
 
0.6%
Other values (610) 743
91.4%
2023-12-12T13:17:32.876722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2303
23.6%
- 1620
16.6%
0 1386
14.2%
4 714
 
7.3%
2 656
 
6.7%
6 636
 
6.5%
5 603
 
6.2%
1 598
 
6.1%
7 571
 
5.9%
8 400
 
4.1%
Other values (3) 252
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8116
83.3%
Dash Punctuation 1620
 
16.6%
Space Separator 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2303
28.4%
0 1386
17.1%
4 714
 
8.8%
2 656
 
8.1%
6 636
 
7.8%
5 603
 
7.4%
1 598
 
7.4%
7 571
 
7.0%
8 400
 
4.9%
9 249
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 1620
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9739
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2303
23.6%
- 1620
16.6%
0 1386
14.2%
4 714
 
7.3%
2 656
 
6.7%
6 636
 
6.5%
5 603
 
6.2%
1 598
 
6.1%
7 571
 
5.9%
8 400
 
4.1%
Other values (3) 252
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9739
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2303
23.6%
- 1620
16.6%
0 1386
14.2%
4 714
 
7.3%
2 656
 
6.7%
6 636
 
6.5%
5 603
 
6.2%
1 598
 
6.1%
7 571
 
5.9%
8 400
 
4.1%
Other values (3) 252
 
2.6%

소재지도로명주소
Text

MISSING 

Distinct659
Distinct (%)78.5%
Missing66
Missing (%)7.3%
Memory size7.2 KiB
2023-12-12T13:17:33.201132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length21.114286
Min length14

Characters and Unicode

Total characters17736
Distinct characters318
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique534 ?
Unique (%)63.6%

Sample

1st row강원도 강릉시 범일로 579번길 24
2nd row강원도 강릉시 범일로 579번길 24
3rd row강원도 강릉시 공제로 357
4th row강원도 강릉시 종합운동장길 72-21
5th row강원도 강릉시 옥계면 산계길 225
ValueCountFrequency (%)
강원도 836
 
20.3%
원주시 173
 
4.2%
강릉시 91
 
2.2%
횡성군 76
 
1.8%
평창군 71
 
1.7%
춘천시 53
 
1.3%
고성군 53
 
1.3%
홍천군 48
 
1.2%
삼척시 45
 
1.1%
문막읍 33
 
0.8%
Other values (1123) 2642
64.1%
2023-12-12T13:17:33.708040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3326
 
18.8%
원 1131
 
6.4%
강 1001
 
5.6%
도 873
 
4.9%
로 560
 
3.2%
1 549
 
3.1%
시 466
 
2.6%
2 410
 
2.3%
면 410
 
2.3%
동 408
 
2.3%
Other values (308) 8602
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10891
61.4%
Space Separator 3326
 
18.8%
Decimal Number 2799
 
15.8%
Open Punctuation 262
 
1.5%
Close Punctuation 262
 
1.5%
Dash Punctuation 182
 
1.0%
Other Punctuation 10
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1131
 
10.4%
강 1001
 
9.2%
도 873
 
8.0%
로 560
 
5.1%
시 466
 
4.3%
면 410
 
3.8%
동 408
 
3.7%
군 395
 
3.6%
길 333
 
3.1%
성 214
 
2.0%
Other values (289) 5100
46.8%
Decimal Number
ValueCountFrequency (%)
1 549
19.6%
2 410
14.6%
3 300
10.7%
4 293
10.5%
5 248
8.9%
6 223
8.0%
7 214
 
7.6%
8 198
 
7.1%
0 191
 
6.8%
9 173
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
A 1
25.0%
H 1
25.0%
L 1
25.0%
Space Separator
ValueCountFrequency (%)
3326
100.0%
Open Punctuation
ValueCountFrequency (%)
( 262
100.0%
Close Punctuation
ValueCountFrequency (%)
) 262
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10891
61.4%
Common 6841
38.6%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 1131
 
10.4%
강 1001
 
9.2%
도 873
 
8.0%
로 560
 
5.1%
시 466
 
4.3%
면 410
 
3.8%
동 408
 
3.7%
군 395
 
3.6%
길 333
 
3.1%
성 214
 
2.0%
Other values (289) 5100
46.8%
Common
ValueCountFrequency (%)
3326
48.6%
1 549
 
8.0%
2 410
 
6.0%
3 300
 
4.4%
4 293
 
4.3%
( 262
 
3.8%
) 262
 
3.8%
5 248
 
3.6%
6 223
 
3.3%
7 214
 
3.1%
Other values (5) 754
 
11.0%
Latin
ValueCountFrequency (%)
C 1
25.0%
A 1
25.0%
H 1
25.0%
L 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10891
61.4%
ASCII 6845
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3326
48.6%
1 549
 
8.0%
2 410
 
6.0%
3 300
 
4.4%
4 293
 
4.3%
( 262
 
3.8%
) 262
 
3.8%
5 248
 
3.6%
6 223
 
3.3%
7 214
 
3.1%
Other values (9) 758
 
11.1%
Hangul
ValueCountFrequency (%)
원 1131
 
10.4%
강 1001
 
9.2%
도 873
 
8.0%
로 560
 
5.1%
시 466
 
4.3%
면 410
 
3.8%
동 408
 
3.7%
군 395
 
3.6%
길 333
 
3.1%
성 214
 
2.0%
Other values (289) 5100
46.8%

경도
Text

Distinct690
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T13:17:34.061661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.032009
Min length7

Characters and Unicode

Total characters9089
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

Unique563 ?
Unique (%)62.1%

Sample

1st row128.896195
2nd row128.874228
3rd row128.874228
4th row128.895531
5th row128.895531
ValueCountFrequency (%)
128.652088 11
 
1.2%
128.444739 8
 
0.9%
128.327311 7
 
0.8%
127.875086 7
 
0.8%
128.960318 5
 
0.6%
128.139004 5
 
0.6%
127.826683 5
 
0.6%
128.32278 5
 
0.6%
127.880903 4
 
0.4%
128.903747 4
 
0.4%
Other values (680) 845
93.3%
2023-12-12T13:17:34.773935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1484
16.3%
2 1387
15.3%
8 1095
12.0%
. 907
10.0%
7 877
9.6%
9 766
8.4%
5 566
 
6.2%
4 531
 
5.8%
6 524
 
5.8%
3 502
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8182
90.0%
Other Punctuation 907
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1484
18.1%
2 1387
17.0%
8 1095
13.4%
7 877
10.7%
9 766
9.4%
5 566
 
6.9%
4 531
 
6.5%
6 524
 
6.4%
3 502
 
6.1%
0 450
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 907
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9089
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1484
16.3%
2 1387
15.3%
8 1095
12.0%
. 907
10.0%
7 877
9.6%
9 766
8.4%
5 566
 
6.2%
4 531
 
5.8%
6 524
 
5.8%
3 502
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9089
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1484
16.3%
2 1387
15.3%
8 1095
12.0%
. 907
10.0%
7 877
9.6%
9 766
8.4%
5 566
 
6.2%
4 531
 
5.8%
6 524
 
5.8%
3 502
 
5.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct689
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.62663
Minimum32.522023
Maximum38.575757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.1 KiB
2023-12-12T13:17:34.997616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.522023
5-th percentile37.180274
Q137.37273
median37.58125
Q337.869767
95-th percentile38.243587
Maximum38.575757
Range6.053734
Interquartile range (IQR)0.49703637

Descriptive statistics

Standard deviation0.48050598
Coefficient of variation (CV)0.01277037
Kurtosis54.273181
Mean37.62663
Median Absolute Deviation (MAD)0.232316
Skewness-5.0525248
Sum34089.727
Variance0.230886
MonotonicityNot monotonic
2023-12-12T13:17:35.239076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.654248 11
 
1.2%
37.544147 8
 
0.9%
37.58125 7
 
0.8%
37.339443 7
 
0.8%
37.716285 5
 
0.6%
37.461165 5
 
0.6%
37.180255 5
 
0.6%
37.323991 5
 
0.6%
37.551767 4
 
0.4%
38.204831 4
 
0.4%
Other values (679) 845
93.3%
ValueCountFrequency (%)
32.522023 4
0.4%
37.094186 1
 
0.1%
37.116848 1
 
0.1%
37.123121 1
 
0.1%
37.1242702 1
 
0.1%
37.125338 3
0.3%
37.127765 2
0.2%
37.135038 1
 
0.1%
37.135068 1
 
0.1%
37.136673 1
 
0.1%
ValueCountFrequency (%)
38.575757 1
 
0.1%
38.48419 2
0.2%
38.44912 2
0.2%
38.445747 1
 
0.1%
38.436376 1
 
0.1%
38.434892 2
0.2%
38.389227 1
 
0.1%
38.38762 1
 
0.1%
38.384973 3
0.3%
38.379978 1
 
0.1%

Interactions

2023-12-12T13:17:29.076858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:17:35.405495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명구분위도
시군구명1.0000.7230.885
구분0.7231.0000.530
위도0.8850.5301.000
2023-12-12T13:17:35.521660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명구분
시군구명1.0000.322
구분0.3221.000
2023-12-12T13:17:35.611203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도시군구명구분
위도1.0000.7070.272
시군구명0.7071.0000.322
구분0.2720.3221.000

Missing values

2023-12-12T13:17:29.262408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:17:29.474626image/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.
2023-12-12T13:17:29.633299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시도명시군구명구분업체명취급품목허가일자연락처소재지도로명주소경도위도
0강원도강릉시고압가스제조강릉아이스아레나프레온08/29/2016033-249-3281<NA>128.89619537.778951
1강원도강릉시고압가스제조강원도청 강릉 아이스하키Ⅱ 주경기장프레온08/29/2016033-249-3281강원도 강릉시 범일로 579번길 24128.87422837.736399
2강원도강릉시고압가스제조강원도청 강릉 아이스하키Ⅱ 보조경기장프레온08/29/2016033-249-3281강원도 강릉시 범일로 579번길 24128.87422837.736399
3강원도강릉시고압가스제조강원도청 스피드스케이팅경기장프레온10/10/2016033-249-3281<NA>128.89553137.780362
4강원도강릉시고압가스제조강원도청 아이스하키 Ⅰ주경기장프레온10/10/2016033-249-3281<NA>128.89553137.780362
5강원도강릉시고압가스제조강원도청 아이스하키 Ⅰ보조경기장프레온10/10/2016033-249-3281<NA>128.89553137.780362
6강원도강릉시고압가스제조강원도청 쇼트트랙보조경기장프레온07/12/2017033-249-3281강원도 강릉시 공제로 357128.855723237.747205
7강원도강릉시고압가스제조2018평창동계올림픽 조직위원회프레온01/19/2018033-350-2018강원도 강릉시 종합운동장길 72-21128.893627337.772128
8강원도강릉시고압가스제조라파즈한라시멘트㈜프레온11/02/1992033-530-1015강원도 강릉시 옥계면 산계길 225129.00842337.589046
9강원도강릉시고압가스제조라파즈한라시멘트㈜프레온03/12/1996033-530-1015강원도 강릉시 옥계면 산계길 225129.00842337.589046
시도명시군구명구분업체명취급품목허가일자연락처소재지도로명주소경도위도
896강원도횡성군집단공급동방에너지(주)액화석유가스08/27/2001<NA>강원도 횡성군 횡성읍 읍하로25번길 17127.984574437.494872
897강원도횡성군LPG충전(주)대현유통 횡성(서창) 충전소액화석유가스02/12/2001<NA>강원도 횡성군 안흥면 영동고속도로 153-1128.135071337.464894
898강원도횡성군LPG판매영목가스액화석유가스05/09/2000<NA>강원도 횡성군 횡성읍 태기로개전7길 46128.013476337.508619
899강원도횡성군집단공급주식회사 충훈에너지액화석유가스03/19/1999<NA>경기도 고양시 덕양구 충장로 2126.834467637.613093
900강원도횡성군고압가스저장소사(상)휴게소액화석유가스11/04/1997<NA>강원도 횡성군 안흥면 영동고속도로 153128.135443337.464985
901강원도횡성군LPG판매소사(상)휴게소액화석유가스11/04/1997<NA>강원도 횡성군 안흥면 영동고속도로 153128.135443337.464985
902강원도횡성군LPG판매횡성에너지액화석유가스07/30/1996<NA>강원도 횡성군 안흥면 안흥시장2길 53128.163176937.410242
903강원도횡성군LPG판매성우가스액화석유가스07/20/1995<NA>강원도 횡성군 둔내면 검두재길 71128.20120237.519191
904강원도횡성군LPG판매우천태양가스액화석유가스01/08/1988<NA>강원도 횡성군 우천면 하대길 102128.078191537.457867
905강원도횡성군LPG판매갑천매일가스액화석유가스01/08/1988<NA>강원도 횡성군 갑천면 청정로매일7길 24128.108763837.561258

Duplicate rows

Most frequently occurring

시도명시군구명구분업체명취급품목허가일자연락처소재지도로명주소경도위도# duplicates
4강원도평창군고압가스제조국립대학법인 서울대학교프레온(24.04RT)12/11/201302-880-5149<NA>128.44473937.5441476
0강원도강릉시고압가스제조㈜승산 라카이샌드파인리조트프레온03/06/20121644-3001강원도 강릉시 해안로 536 (안현동)128.90374737.8071314
2강원도원주시고압가스제조삼양식품(주)프레온(23.6RT)08/16/2013033-735-3311강원도 원주시 문막읍 왕건로 49127.82668337.3239913
3강원도평창군고압가스제조강원도개발공사프레온(44.7RT)04/14/2009033-259-6114강원도 평창군 대관령면 솔봉로 325128.65208837.6542483
5강원도횡성군집단공급원광에너지액화석유가스10/09/2001<NA>강원도 횡성군 횡성읍 문화체육로 2127.982615637.4950813
1강원도강릉시고압가스제조동그린㈜암모니아03/18/2002033-646-6671강원도 강릉시 강동면 단경로 114128.96031837.7162852