Overview

Dataset statistics

Number of variables5
Number of observations38
Missing cells14
Missing cells (%)7.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory43.4 B

Variable types

Categorical1
Text4

Dataset

Description광주광역시 자치구별(동구, 서구, 남구, 북구, 광산구) LPG 판매업소 현황으로 상호, 주소, 대표자, 전화번호를 제공하는 데이터입니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15001884/fileData.do

Alerts

대표자 has 14 (36.8%) missing valuesMissing
상호 has unique valuesUnique
전화번호(지역번호 포함) has unique valuesUnique

Reproduction

Analysis started2024-03-14 17:23:45.469402
Analysis finished2024-03-14 17:23:46.362335
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

Distinct5
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size432.0 B
광산구
20 
서구
6 
동구
4 
남구
4 
북구
4 

Length

Max length3
Median length3
Mean length2.5263158
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동구
2nd row동구
3rd row동구
4th row동구
5th row서구

Common Values

ValueCountFrequency (%)
광산구 20
52.6%
서구 6
 
15.8%
동구 4
 
10.5%
남구 4
 
10.5%
북구 4
 
10.5%

Length

2024-03-15T02:23:46.583772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:23:46.935034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광산구 20
52.6%
서구 6
 
15.8%
동구 4
 
10.5%
남구 4
 
10.5%
북구 4
 
10.5%

상호
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size432.0 B
2024-03-15T02:23:48.555420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.3157895
Min length4

Characters and Unicode

Total characters240
Distinct characters75
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

Unique38 ?
Unique (%)100.0%

Sample

1st row(유)청기와예향에너지
2nd row(유)전남가스
3rd row하이가스
4th row동산가스
5th row서부에너지
ValueCountFrequency (%)
유)청기와예향에너지 1
 
2.6%
금성특수가스 1
 
2.6%
합)호남고압가스 1
 
2.6%
광산lpg 1
 
2.6%
날으는가스 1
 
2.6%
보배가스 1
 
2.6%
신일가스㈜ 1
 
2.6%
건국특수가스 1
 
2.6%
유)광주벌크에너지 1
 
2.6%
유)전남가스 1
 
2.6%
Other values (29) 29
74.4%
2024-03-15T02:23:50.199668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 30
 
12.5%
스 29
 
12.1%
( 14
 
5.8%
) 14
 
5.8%
유 10
 
4.2%
주 8
 
3.3%
지 7
 
2.9%
광 7
 
2.9%
에 6
 
2.5%
너 6
 
2.5%
Other values (65) 109
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
84.6%
Open Punctuation 14
 
5.8%
Close Punctuation 14
 
5.8%
Other Symbol 5
 
2.1%
Uppercase Letter 3
 
1.2%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 30
 
14.8%
스 29
 
14.3%
유 10
 
4.9%
주 8
 
3.9%
지 7
 
3.4%
광 7
 
3.4%
에 6
 
3.0%
너 6
 
3.0%
수 5
 
2.5%
특 5
 
2.5%
Other values (58) 90
44.3%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
L 1
33.3%
P 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 208
86.7%
Common 29
 
12.1%
Latin 3
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 30
 
14.4%
스 29
 
13.9%
유 10
 
4.8%
주 8
 
3.8%
지 7
 
3.4%
광 7
 
3.4%
에 6
 
2.9%
너 6
 
2.9%
㈜ 5
 
2.4%
수 5
 
2.4%
Other values (59) 95
45.7%
Common
ValueCountFrequency (%)
( 14
48.3%
) 14
48.3%
1
 
3.4%
Latin
ValueCountFrequency (%)
G 1
33.3%
L 1
33.3%
P 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
84.6%
ASCII 32
 
13.3%
None 5
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 30
 
14.8%
스 29
 
14.3%
유 10
 
4.9%
주 8
 
3.9%
지 7
 
3.4%
광 7
 
3.4%
에 6
 
3.0%
너 6
 
3.0%
수 5
 
2.5%
특 5
 
2.5%
Other values (58) 90
44.3%
ASCII
ValueCountFrequency (%)
( 14
43.8%
) 14
43.8%
G 1
 
3.1%
L 1
 
3.1%
1
 
3.1%
P 1
 
3.1%
None
ValueCountFrequency (%)
㈜ 5
100.0%

도로명 주소
Text

Distinct32
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size432.0 B
2024-03-15T02:23:51.187049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length23.157895
Min length16

Characters and Unicode

Total characters880
Distinct characters78
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)71.1%

Sample

1st row광주광역시 동구 화산로238번길 9-10 (용산동)
2nd row광주광역시 동구 남문로 415-5 (월남동)
3rd row광주광역시 동구 소태길 72 (소태동)
4th row광주광역시 동구 밤실로4번길 43 (지산동)
5th row광주광역시 서구 내방마을1길 15(화정동)
ValueCountFrequency (%)
광주광역시 38
21.2%
광산구 20
 
11.2%
체암로 7
 
3.9%
양동 6
 
3.4%
서구 6
 
3.4%
남구 4
 
2.2%
동구 4
 
2.2%
북구 4
 
2.2%
고봉로 3
 
1.7%
241 3
 
1.7%
Other values (69) 84
46.9%
2024-03-15T02:23:52.565689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
17.0%
광 97
 
11.0%
동 44
 
5.0%
주 41
 
4.7%
역 38
 
4.3%
시 38
 
4.3%
구 38
 
4.3%
로 35
 
4.0%
) 33
 
3.8%
( 33
 
3.8%
Other values (68) 333
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 524
59.5%
Space Separator 150
 
17.0%
Decimal Number 135
 
15.3%
Close Punctuation 33
 
3.8%
Open Punctuation 33
 
3.8%
Dash Punctuation 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 97
18.5%
동 44
 
8.4%
주 41
 
7.8%
역 38
 
7.3%
시 38
 
7.3%
구 38
 
7.3%
로 35
 
6.7%
산 29
 
5.5%
서 10
 
1.9%
번 9
 
1.7%
Other values (54) 145
27.7%
Decimal Number
ValueCountFrequency (%)
1 26
19.3%
2 19
14.1%
5 19
14.1%
4 15
11.1%
3 14
10.4%
8 12
8.9%
7 11
8.1%
6 9
 
6.7%
0 5
 
3.7%
9 5
 
3.7%
Space Separator
ValueCountFrequency (%)
150
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 524
59.5%
Common 356
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 97
18.5%
동 44
 
8.4%
주 41
 
7.8%
역 38
 
7.3%
시 38
 
7.3%
구 38
 
7.3%
로 35
 
6.7%
산 29
 
5.5%
서 10
 
1.9%
번 9
 
1.7%
Other values (54) 145
27.7%
Common
ValueCountFrequency (%)
150
42.1%
) 33
 
9.3%
( 33
 
9.3%
1 26
 
7.3%
2 19
 
5.3%
5 19
 
5.3%
4 15
 
4.2%
3 14
 
3.9%
8 12
 
3.4%
7 11
 
3.1%
Other values (4) 24
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 524
59.5%
ASCII 356
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
42.1%
) 33
 
9.3%
( 33
 
9.3%
1 26
 
7.3%
2 19
 
5.3%
5 19
 
5.3%
4 15
 
4.2%
3 14
 
3.9%
8 12
 
3.4%
7 11
 
3.1%
Other values (4) 24
 
6.7%
Hangul
ValueCountFrequency (%)
광 97
18.5%
동 44
 
8.4%
주 41
 
7.8%
역 38
 
7.3%
시 38
 
7.3%
구 38
 
7.3%
로 35
 
6.7%
산 29
 
5.5%
서 10
 
1.9%
번 9
 
1.7%
Other values (54) 145
27.7%

대표자
Text

MISSING 

Distinct22
Distinct (%)91.7%
Missing14
Missing (%)36.8%
Memory size432.0 B
2024-03-15T02:23:53.430736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.375
Min length3

Characters and Unicode

Total characters81
Distinct characters49
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

Unique20 ?
Unique (%)83.3%

Sample

1st row장영호
2nd row노상희
3rd row정수연
4th row노상희
5th row안정국
ValueCountFrequency (%)
노상희 2
 
8.0%
김동모 2
 
8.0%
전미아 1
 
4.0%
장영호 1
 
4.0%
김종호 1
 
4.0%
김명환 1
 
4.0%
한승문 1
 
4.0%
문병현 1
 
4.0%
정병서 1
 
4.0%
홍형호 1
 
4.0%
Other values (13) 13
52.0%
2024-03-15T02:23:54.660030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 8
 
9.9%
정 5
 
6.2%
호 3
 
3.7%
희 3
 
3.7%
영 3
 
3.7%
문 3
 
3.7%
국 2
 
2.5%
병 2
 
2.5%
준 2
 
2.5%
상 2
 
2.5%
Other values (39) 48
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
96.3%
Other Punctuation 2
 
2.5%
Space Separator 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 8
 
10.3%
정 5
 
6.4%
호 3
 
3.8%
희 3
 
3.8%
영 3
 
3.8%
문 3
 
3.8%
국 2
 
2.6%
병 2
 
2.6%
준 2
 
2.6%
상 2
 
2.6%
Other values (37) 45
57.7%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
96.3%
Common 3
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 8
 
10.3%
정 5
 
6.4%
호 3
 
3.8%
희 3
 
3.8%
영 3
 
3.8%
문 3
 
3.8%
국 2
 
2.6%
병 2
 
2.6%
준 2
 
2.6%
상 2
 
2.6%
Other values (37) 45
57.7%
Common
ValueCountFrequency (%)
, 2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
96.3%
ASCII 3
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 8
 
10.3%
정 5
 
6.4%
호 3
 
3.8%
희 3
 
3.8%
영 3
 
3.8%
문 3
 
3.8%
국 2
 
2.6%
병 2
 
2.6%
준 2
 
2.6%
상 2
 
2.6%
Other values (37) 45
57.7%
ASCII
ValueCountFrequency (%)
, 2
66.7%
1
33.3%

전화번호(지역번호 포함)
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size432.0 B
2024-03-15T02:23:55.625024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length12
Mean length12.736842
Min length12

Characters and Unicode

Total characters484
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

Unique38 ?
Unique (%)100.0%

Sample

1st row062-681-1818
2nd row062-234-6147
3rd row062-223-4445
4th row062-234-9871
5th row062-376-6300
ValueCountFrequency (%)
062-681-1818 1
 
2.5%
062-381-6002 1
 
2.5%
062-951-4148 1
 
2.5%
062-943-3002 1
 
2.5%
062-945-8000 1
 
2.5%
062-954-3333 1
 
2.5%
062-944-7877 1
 
2.5%
062-951-0011 1
 
2.5%
062-944-5989 1
 
2.5%
062-945-0808 1
 
2.5%
Other values (30) 30
75.0%
2024-03-15T02:23:57.100761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 80
16.5%
0 76
15.7%
2 69
14.3%
6 63
13.0%
3 36
7.4%
4 36
7.4%
1 31
 
6.4%
5 28
 
5.8%
9 23
 
4.8%
8 19
 
3.9%
Other values (3) 23
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400
82.6%
Dash Punctuation 80
 
16.5%
Other Punctuation 2
 
0.4%
Space Separator 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76
19.0%
2 69
17.2%
6 63
15.8%
3 36
9.0%
4 36
9.0%
1 31
7.8%
5 28
 
7.0%
9 23
 
5.8%
8 19
 
4.8%
7 19
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 484
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 80
16.5%
0 76
15.7%
2 69
14.3%
6 63
13.0%
3 36
7.4%
4 36
7.4%
1 31
 
6.4%
5 28
 
5.8%
9 23
 
4.8%
8 19
 
3.9%
Other values (3) 23
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 484
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 80
16.5%
0 76
15.7%
2 69
14.3%
6 63
13.0%
3 36
7.4%
4 36
7.4%
1 31
 
6.4%
5 28
 
5.8%
9 23
 
4.8%
8 19
 
3.9%
Other values (3) 23
 
4.8%

Correlations

2024-03-15T02:23:57.684392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구상호도로명 주소대표자전화번호(지역번호 포함)
시군구1.0001.0001.0001.0001.000
상호1.0001.0001.0001.0001.000
도로명 주소1.0001.0001.0000.8711.000
대표자1.0001.0000.8711.0001.000
전화번호(지역번호 포함)1.0001.0001.0001.0001.000

Missing values

2024-03-15T02:23:45.909463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:23:46.233761image/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

시군구상호도로명 주소대표자전화번호(지역번호 포함)
0동구(유)청기와예향에너지광주광역시 동구 화산로238번길 9-10 (용산동)장영호062-681-1818
1동구(유)전남가스광주광역시 동구 남문로 415-5 (월남동)노상희062-234-6147
2동구하이가스광주광역시 동구 소태길 72 (소태동)정수연062-223-4445
3동구동산가스광주광역시 동구 밤실로4번길 43 (지산동)노상희062-234-9871
4서구서부에너지광주광역시 서구 내방마을1길 15(화정동)<NA>062-376-6300
5서구팔팔가스광주광역시 서구 천변좌하로634번길 1-34(광천동)<NA>062-368-9111
6서구동아광일가스광주광역시 서구 풍서좌로 227(매월동)<NA>062-352-2222
7서구시민가스(유)광주광역시 서구 회재로 755(매월동)<NA>062-681-2222
8서구하나가스광주광역시 서구 회재로 755(매월동)<NA>062-381-6002
9서구신일특수가스광주광역시 서구 풍서좌로 227(매월동)<NA>062-366-2300
시군구상호도로명 주소대표자전화번호(지역번호 포함)
28광산구㈜가온에너지광주광역시 광산구 본동로 536 (양산동)오유나, 전미아062-675-4501
29광산구금성특수가스광주광역시 광산구 체암로 1808 (삼거동)나문정062-954-2484, 062-954-0050
30광산구(주)합동특수가스광주광역시 광산구 평동산단외로 131 (지죽동)홍형호062-944-1071
31광산구한국종합가스광주광역시 광산구 체암로 1648 (양동)정병서062-943-0330
32광산구(유)천일가스광주광역시 광산구 체암로 1647 (양동)김동모062-951-0098
33광산구신화가스광주광역시 광산구 체암로 1649 (양동)문병현062-955-4445
34광산구한국특수가스㈜광주광역시 광산구 평동로803번길 93 (용동)한승문062-954-3355
35광산구고려가스 주식회사광주광역시 광산구 평동로 853-9 (옥동)김명환062-653-6711
36광산구㈜세광이엔지광주광역시 광산구 본동로 538 (양산동)김영재062-672-1222
37광산구쌍용가스광주광역시 광산구 안청동 2번지 3호김동모062-953-0033