Overview

Dataset statistics

Number of variables6
Number of observations200
Missing cells6
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory50.7 B

Variable types

Numeric2
Text3
Categorical1

Dataset

Description도시가스를 연료로 사용하는 자동차를 충전하기 위한 충전소 현황(관할 지역본부/지사, 행정구역, 시설명, 주소지, 휴/폐업 여부)를 제공하여 CNG차량 운전자에게 유용한 정보를 제공하기 위한 데이터입니다.
Author한국가스안전공사
URLhttps://www.data.go.kr/data/15001508/fileData.do

Alerts

우편 is highly overall correlated with 지역본부_지사High correlation
지역본부_지사 is highly overall correlated with 우편High correlation
우편 has 6 (3.0%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:13:06.942926
Analysis finished2023-12-12 02:13:07.957372
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.5
Minimum1
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T11:13:08.033710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.95
Q150.75
median100.5
Q3150.25
95-th percentile190.05
Maximum200
Range199
Interquartile range (IQR)99.5

Descriptive statistics

Standard deviation57.879185
Coefficient of variation (CV)0.57591228
Kurtosis-1.2
Mean100.5
Median Absolute Deviation (MAD)50
Skewness0
Sum20100
Variance3350
MonotonicityStrictly increasing
2023-12-12T11:13:08.177218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
139 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%

행정구역
Text

Distinct113
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T11:13:08.480367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length6
Mean length6.745
Min length3

Characters and Unicode

Total characters1349
Distinct characters94
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)27.0%

Sample

1st row부산 사하구
2nd row강원 홍천군
3rd row전북 익산시
4th row전북 전주시 완산구
5th row경기 안성시
ValueCountFrequency (%)
경기 64
 
14.5%
서울 29
 
6.6%
부산 18
 
4.1%
인천 15
 
3.4%
경남 13
 
2.9%
대구 9
 
2.0%
북구 8
 
1.8%
전북 8
 
1.8%
경북 7
 
1.6%
서구 7
 
1.6%
Other values (118) 263
59.6%
2023-12-12T11:13:08.928504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
242
17.9%
구 134
 
9.9%
시 108
 
8.0%
경 87
 
6.4%
기 66
 
4.9%
서 50
 
3.7%
산 45
 
3.3%
남 39
 
2.9%
울 38
 
2.8%
주 34
 
2.5%
Other values (84) 506
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1107
82.1%
Space Separator 242
 
17.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 134
 
12.1%
시 108
 
9.8%
경 87
 
7.9%
기 66
 
6.0%
서 50
 
4.5%
산 45
 
4.1%
남 39
 
3.5%
울 38
 
3.4%
주 34
 
3.1%
북 32
 
2.9%
Other values (83) 474
42.8%
Space Separator
ValueCountFrequency (%)
242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1107
82.1%
Common 242
 
17.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 134
 
12.1%
시 108
 
9.8%
경 87
 
7.9%
기 66
 
6.0%
서 50
 
4.5%
산 45
 
4.1%
남 39
 
3.5%
울 38
 
3.4%
주 34
 
3.1%
북 32
 
2.9%
Other values (83) 474
42.8%
Common
ValueCountFrequency (%)
242
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1107
82.1%
ASCII 242
 
17.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
242
100.0%
Hangul
ValueCountFrequency (%)
구 134
 
12.1%
시 108
 
9.8%
경 87
 
7.9%
기 66
 
6.0%
서 50
 
4.5%
산 45
 
4.1%
남 39
 
3.5%
울 38
 
3.4%
주 34
 
3.1%
북 32
 
2.9%
Other values (83) 474
42.8%

지역본부_지사
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
경기광역본부
18 
경기중부지사
15 
인천본부
15 
경기동부지사
13 
서울동부지사
13 
Other values (22)
126 

Length

Max length6
Median length6
Mean length5.55
Min length4

Unique

Unique3 ?
Unique (%)1.5%

Sample

1st row부산광역본부
2nd row강원광역본부
3rd row전북본부
4th row전북본부
5th row경기광역본부

Common Values

ValueCountFrequency (%)
경기광역본부 18
 
9.0%
경기중부지사 15
 
7.5%
인천본부 15
 
7.5%
경기동부지사 13
 
6.5%
서울동부지사 13
 
6.5%
대구광역본부 13
 
6.5%
경남본부 11
 
5.5%
경기서부지사 11
 
5.5%
부산광역본부 10
 
5.0%
전북본부 8
 
4.0%
Other values (17) 73
36.5%

Length

2023-12-12T11:13:09.094444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기광역본부 18
 
9.0%
경기중부지사 15
 
7.5%
인천본부 15
 
7.5%
경기동부지사 13
 
6.5%
서울동부지사 13
 
6.5%
대구광역본부 13
 
6.5%
경남본부 11
 
5.5%
경기서부지사 11
 
5.5%
부산광역본부 10
 
5.0%
전북본부 8
 
4.0%
Other values (17) 73
36.5%

업소명
Text

Distinct195
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T11:13:09.319422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length14.305
Min length5

Characters and Unicode

Total characters2861
Distinct characters233
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)96.0%

Sample

1st row(주)진원에너지
2nd row두원에너지 홍천CNG충전소
3rd row전북에너지서비스(주) 송학 CNG충전소
4th row(유)제일씨엔지에너지평화동CNG충전소
5th row안성터미널주유소,충전소
ValueCountFrequency (%)
cng충전소 16
 
5.5%
주식회사 13
 
4.5%
주)해양에너지 6
 
2.1%
주)대원고속 5
 
1.7%
주)항만엘엔지 5
 
1.7%
주)에스이모빌리티 5
 
1.7%
서울씨엔지(주 4
 
1.4%
주)대원운수 4
 
1.4%
주)예스코서비스 3
 
1.0%
주)경동도시가스 2
 
0.7%
Other values (221) 228
78.4%
2023-12-12T11:13:09.729169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 167
 
5.8%
( 160
 
5.6%
) 160
 
5.6%
전 154
 
5.4%
소 152
 
5.3%
충 150
 
5.2%
N 131
 
4.6%
G 129
 
4.5%
C 127
 
4.4%
지 105
 
3.7%
Other values (223) 1426
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2030
71.0%
Uppercase Letter 404
 
14.1%
Open Punctuation 160
 
5.6%
Close Punctuation 160
 
5.6%
Space Separator 91
 
3.2%
Lowercase Letter 10
 
0.3%
Dash Punctuation 3
 
0.1%
Decimal Number 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 167
 
8.2%
전 154
 
7.6%
소 152
 
7.5%
충 150
 
7.4%
지 105
 
5.2%
에 67
 
3.3%
너 57
 
2.8%
스 48
 
2.4%
대 40
 
2.0%
엔 34
 
1.7%
Other values (198) 1056
52.0%
Uppercase Letter
ValueCountFrequency (%)
N 131
32.4%
G 129
31.9%
C 127
31.4%
T 4
 
1.0%
L 4
 
1.0%
P 3
 
0.7%
B 2
 
0.5%
S 1
 
0.2%
I 1
 
0.2%
H 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
t 2
20.0%
n 2
20.0%
a 2
20.0%
o 1
10.0%
i 1
10.0%
e 1
10.0%
l 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 160
100.0%
Close Punctuation
ValueCountFrequency (%)
) 160
100.0%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2030
71.0%
Common 417
 
14.6%
Latin 414
 
14.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 167
 
8.2%
전 154
 
7.6%
소 152
 
7.5%
충 150
 
7.4%
지 105
 
5.2%
에 67
 
3.3%
너 57
 
2.8%
스 48
 
2.4%
대 40
 
2.0%
엔 34
 
1.7%
Other values (198) 1056
52.0%
Latin
ValueCountFrequency (%)
N 131
31.6%
G 129
31.2%
C 127
30.7%
T 4
 
1.0%
L 4
 
1.0%
P 3
 
0.7%
B 2
 
0.5%
t 2
 
0.5%
n 2
 
0.5%
a 2
 
0.5%
Other values (8) 8
 
1.9%
Common
ValueCountFrequency (%)
( 160
38.4%
) 160
38.4%
91
21.8%
- 3
 
0.7%
1 1
 
0.2%
, 1
 
0.2%
2 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2030
71.0%
ASCII 831
29.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 167
 
8.2%
전 154
 
7.6%
소 152
 
7.5%
충 150
 
7.4%
지 105
 
5.2%
에 67
 
3.3%
너 57
 
2.8%
스 48
 
2.4%
대 40
 
2.0%
엔 34
 
1.7%
Other values (198) 1056
52.0%
ASCII
ValueCountFrequency (%)
( 160
19.3%
) 160
19.3%
N 131
15.8%
G 129
15.5%
C 127
15.3%
91
11.0%
T 4
 
0.5%
L 4
 
0.5%
P 3
 
0.4%
- 3
 
0.4%
Other values (15) 19
 
2.3%

우편
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct187
Distinct (%)96.4%
Missing6
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean29693.433
Minimum1137
Maximum380190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T11:13:09.889346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1137
5-th percentile2702.6
Q112810
median22341
Q346170.25
95-th percentile58391.5
Maximum380190
Range379053
Interquartile range (IQR)33360.25

Descriptive statistics

Standard deviation31189.24
Coefficient of variation (CV)1.050375
Kurtosis82.392896
Mean29693.433
Median Absolute Deviation (MAD)14296.5
Skewness7.4350522
Sum5760526
Variance9.7276869 × 108
MonotonicityNot monotonic
2023-12-12T11:13:10.501895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13636 2
 
1.0%
46767 2
 
1.0%
55322 2
 
1.0%
15082 2
 
1.0%
16511 2
 
1.0%
22341 2
 
1.0%
10069 2
 
1.0%
2700 1
 
0.5%
22770 1
 
0.5%
39214 1
 
0.5%
Other values (177) 177
88.5%
(Missing) 6
 
3.0%
ValueCountFrequency (%)
1137 1
0.5%
1300 1
0.5%
1365 1
0.5%
1405 1
0.5%
1691 1
0.5%
1884 1
0.5%
1906 1
0.5%
2056 1
0.5%
2254 1
0.5%
2700 1
0.5%
ValueCountFrequency (%)
380190 1
0.5%
62455 1
0.5%
62076 1
0.5%
62070 1
0.5%
61513 1
0.5%
61140 1
0.5%
61000 1
0.5%
59649 1
0.5%
59625 1
0.5%
58606 1
0.5%

주소
Text

Distinct199
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T11:13:10.937377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length21.63
Min length14

Characters and Unicode

Total characters4326
Distinct characters258
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)99.0%

Sample

1st row부산광역시 사하구 다대로 722 (다대동)
2nd row강원도 홍천군 북방면 홍천로 179
3rd row전라북도 익산시 평동로 382 (송학동)
4th row전라북도 전주시 완산구 난전들로 59 (평화동3가)
5th row경기도 안성시 비봉로 71-14 안성터미널주유소
ValueCountFrequency (%)
경기도 64
 
6.8%
서울특별시 29
 
3.1%
부산광역시 18
 
1.9%
인천광역시 15
 
1.6%
경상남도 13
 
1.4%
대구광역시 9
 
1.0%
전라북도 8
 
0.8%
북구 8
 
0.8%
경상북도 7
 
0.7%
서구 7
 
0.7%
Other values (584) 769
81.2%
2023-12-12T11:13:11.387775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
757
 
17.5%
시 202
 
4.7%
로 184
 
4.3%
구 141
 
3.3%
1 138
 
3.2%
도 124
 
2.9%
경 91
 
2.1%
2 77
 
1.8%
광 76
 
1.8%
3 74
 
1.7%
Other values (248) 2462
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2754
63.7%
Space Separator 757
 
17.5%
Decimal Number 678
 
15.7%
Open Punctuation 39
 
0.9%
Close Punctuation 39
 
0.9%
Dash Punctuation 28
 
0.6%
Uppercase Letter 25
 
0.6%
Other Punctuation 3
 
0.1%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 202
 
7.3%
로 184
 
6.7%
구 141
 
5.1%
도 124
 
4.5%
경 91
 
3.3%
광 76
 
2.8%
기 71
 
2.6%
동 70
 
2.5%
산 65
 
2.4%
역 62
 
2.3%
Other values (225) 1668
60.6%
Decimal Number
ValueCountFrequency (%)
1 138
20.4%
2 77
11.4%
3 74
10.9%
4 63
9.3%
0 62
9.1%
6 59
8.7%
8 57
8.4%
7 56
8.3%
5 54
 
8.0%
9 38
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
C 8
32.0%
N 8
32.0%
G 7
28.0%
A 1
 
4.0%
P 1
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
33.3%
n 1
33.3%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
757
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2754
63.7%
Common 1544
35.7%
Latin 28
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 202
 
7.3%
로 184
 
6.7%
구 141
 
5.1%
도 124
 
4.5%
경 91
 
3.3%
광 76
 
2.8%
기 71
 
2.6%
동 70
 
2.5%
산 65
 
2.4%
역 62
 
2.3%
Other values (225) 1668
60.6%
Common
ValueCountFrequency (%)
757
49.0%
1 138
 
8.9%
2 77
 
5.0%
3 74
 
4.8%
4 63
 
4.1%
0 62
 
4.0%
6 59
 
3.8%
8 57
 
3.7%
7 56
 
3.6%
5 54
 
3.5%
Other values (5) 147
 
9.5%
Latin
ValueCountFrequency (%)
C 8
28.6%
N 8
28.6%
G 7
25.0%
A 1
 
3.6%
P 1
 
3.6%
g 1
 
3.6%
n 1
 
3.6%
c 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2754
63.7%
ASCII 1572
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
757
48.2%
1 138
 
8.8%
2 77
 
4.9%
3 74
 
4.7%
4 63
 
4.0%
0 62
 
3.9%
6 59
 
3.8%
8 57
 
3.6%
7 56
 
3.6%
5 54
 
3.4%
Other values (13) 175
 
11.1%
Hangul
ValueCountFrequency (%)
시 202
 
7.3%
로 184
 
6.7%
구 141
 
5.1%
도 124
 
4.5%
경 91
 
3.3%
광 76
 
2.8%
기 71
 
2.6%
동 70
 
2.5%
산 65
 
2.4%
역 62
 
2.3%
Other values (225) 1668
60.6%

Interactions

2023-12-12T11:13:07.565116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:13:07.356612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:13:07.682376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:13:07.470670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:13:11.507621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지역본부_지사우편
순번1.0000.4400.200
지역본부_지사0.4401.0001.000
우편0.2001.0001.000
2023-12-12T11:13:11.605340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편지역본부_지사
순번1.000-0.1560.165
우편-0.1561.0000.925
지역본부_지사0.1650.9251.000

Missing values

2023-12-12T11:13:07.818523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:13:07.917621image/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

순번행정구역지역본부_지사업소명우편주소
01부산 사하구부산광역본부(주)진원에너지49505부산광역시 사하구 다대로 722 (다대동)
12강원 홍천군강원광역본부두원에너지 홍천CNG충전소25115강원도 홍천군 북방면 홍천로 179
23전북 익산시전북본부전북에너지서비스(주) 송학 CNG충전소54670전라북도 익산시 평동로 382 (송학동)
34전북 전주시 완산구전북본부(유)제일씨엔지에너지평화동CNG충전소55141전라북도 전주시 완산구 난전들로 59 (평화동3가)
45경기 안성시경기광역본부안성터미널주유소,충전소17585경기도 안성시 비봉로 71-14 안성터미널주유소
56경기 평택시경기광역본부평택 용이CNG충전소17870경기도 평택시 이화로 89
67경남 양산시경남본부(주)경동도시가스 웅상공영차고지CNG충전소50524경상남도 양산시 웅상대로 1510
78경남 창원시 성산구경남본부경남에너지(주)불모산CNG충전소51541경상남도 창원시 성산구 성주동 176번지
89경남 창원시 진해구경남본부(주)항만엘엔지51611경상남도 창원시 진해구 신항로 341 PNC터미널 내
910경남 함안군경남본부광신기계공업(주)52029경상남도 함안군 칠원읍 오곡로 124
순번행정구역지역본부_지사업소명우편주소
190191경기 시흥시경기서부지사재연(주) CNG충전소15082경기도 시흥시 희망공원로 278
191192인천 서구인천본부매립지충전소관리 주식회사<NA>인천광역시 서구 거월로 61
192193인천 중구인천본부인천그린에너지(주) 신흥동CNG충전소22341인천광역시 중구 축항대로290번길 124
193194경기 성남시 분당구경기동부지사에코플러스(주)13636경기도 성남시 분당구 탄천상로163번길 10
194195경기 성남시 수정구경기동부지사성남천연가스(주)사송동지점13446경기도 성남시 수정구 사송로 41
195196경기 광주시경기동부지사(주)대원고속 광주씨엔지충전소12739경기도 광주시 광주대로 171 (송정동)
196197경기 파주시경기중부지사신성문산CNG충전소(주)10813경기도 파주시 문산읍 통일로 1699
197198경기 고양시 일산서구경기중부지사(주)오천고양지점 씨엔지충전소10373경기도 고양시 일산서구 경의로 772
198199경기 양주시경기중부지사(주)양주씨엔지11494경기도 양주시 고삼로 17-22
199200충북 충주시충북북부지사(주)서진에너지-충주CNG충전소380190충청북도 충주시 벌터3길 12 (달천동)