Overview

Dataset statistics

Number of variables9
Number of observations151
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.9 KiB
Average record size in memory73.9 B

Variable types

Numeric1
Text2
Categorical6

Dataset

Description수소유통 전담기관에서 조사한 수소충전소별 부대시설(화장실, 대기실, 카페, 정비소, 세차장, 편의점) 정보를 제공합니다.
Author한국가스공사
URLhttps://www.data.go.kr/data/15102835/fileData.do

Alerts

카페 is highly overall correlated with 화장실 and 4 other fieldsHigh correlation
편의점 is highly overall correlated with 화장실 and 4 other fieldsHigh correlation
화장실 is highly overall correlated with 대기실 and 4 other fieldsHigh correlation
대기실 is highly overall correlated with 화장실 and 4 other fieldsHigh correlation
정비소 is highly overall correlated with 화장실 and 4 other fieldsHigh correlation
세차장 is highly overall correlated with 화장실 and 4 other fieldsHigh correlation
화장실 is highly imbalanced (60.3%)Imbalance
카페 is highly imbalanced (51.0%)Imbalance
정비소 is highly imbalanced (68.5%)Imbalance
구분 has unique valuesUnique
충전소 코드 has unique valuesUnique
충전소 명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:28:17.182732
Analysis finished2024-04-06 08:28:18.877626
Duration1.69 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76
Minimum1
Maximum151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-06T17:28:19.074838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.5
Q138.5
median76
Q3113.5
95-th percentile143.5
Maximum151
Range150
Interquartile range (IQR)75

Descriptive statistics

Standard deviation43.734045
Coefficient of variation (CV)0.57544796
Kurtosis-1.2
Mean76
Median Absolute Deviation (MAD)38
Skewness0
Sum11476
Variance1912.6667
MonotonicityStrictly increasing
2024-04-06T17:28:19.408216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
105 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
106 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%

충전소 코드
Text

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-06T17:28:19.845985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters2869
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique151 ?
Unique (%)100.0%

Sample

1st row2920020121HS2014001
2nd row4480020121HS2015001
3rd row3114020121HS2017001
4th row4812120121HS2017002
5th row2771020121HS2017003
ValueCountFrequency (%)
2920020121hs2014001 1
 
0.7%
4686020121hs2022035 1
 
0.7%
4372020121hs2022018 1
 
0.7%
4157020121hs2022019 1
 
0.7%
2671020121hs2022020 1
 
0.7%
2917020121hs2022021 1
 
0.7%
4281020121hs2022022 1
 
0.7%
4128120121hs2022023 1
 
0.7%
4623020121hs2022024 1
 
0.7%
1150020121hs2022025 1
 
0.7%
Other values (141) 141
93.4%
2024-04-06T17:28:20.425138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 757
26.4%
0 679
23.7%
1 587
20.5%
4 161
 
5.6%
H 151
 
5.3%
S 151
 
5.3%
3 123
 
4.3%
5 65
 
2.3%
7 60
 
2.1%
8 49
 
1.7%
Other values (2) 86
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2567
89.5%
Uppercase Letter 302
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 757
29.5%
0 679
26.5%
1 587
22.9%
4 161
 
6.3%
3 123
 
4.8%
5 65
 
2.5%
7 60
 
2.3%
8 49
 
1.9%
9 45
 
1.8%
6 41
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
H 151
50.0%
S 151
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2567
89.5%
Latin 302
 
10.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 757
29.5%
0 679
26.5%
1 587
22.9%
4 161
 
6.3%
3 123
 
4.8%
5 65
 
2.5%
7 60
 
2.3%
8 49
 
1.9%
9 45
 
1.8%
6 41
 
1.6%
Latin
ValueCountFrequency (%)
H 151
50.0%
S 151
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2869
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 757
26.4%
0 679
23.7%
1 587
20.5%
4 161
 
5.6%
H 151
 
5.3%
S 151
 
5.3%
3 123
 
4.3%
5 65
 
2.3%
7 60
 
2.1%
8 49
 
1.7%
Other values (2) 86
 
3.0%

충전소 명
Text

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-06T17:28:20.963553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length12.682119
Min length6

Characters and Unicode

Total characters1915
Distinct characters209
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

Unique151 ?
Unique (%)100.0%

Sample

1st row광주 진곡수소충전소
2nd row내포수소충전소
3rd row옥동LPG 수소 복합충전소
4th row창원팔룡 수소충전소
5th row대구 주행시험장 수소충전소
ValueCountFrequency (%)
수소충전소 99
27.8%
하이넷 40
 
11.2%
광주 4
 
1.1%
충전소 4
 
1.1%
서울특별시 3
 
0.8%
e1 3
 
0.8%
수소 3
 
0.8%
린데 3
 
0.8%
서울 2
 
0.6%
버스 2
 
0.6%
Other values (188) 193
54.2%
2024-04-06T17:28:21.882171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 321
16.8%
213
 
11.1%
전 158
 
8.3%
충 153
 
8.0%
수 151
 
7.9%
하 48
 
2.5%
이 48
 
2.5%
넷 41
 
2.1%
게 27
 
1.4%
) 27
 
1.4%
Other values (199) 728
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1584
82.7%
Space Separator 213
 
11.1%
Uppercase Letter 38
 
2.0%
Close Punctuation 27
 
1.4%
Open Punctuation 27
 
1.4%
Decimal Number 11
 
0.6%
Lowercase Letter 10
 
0.5%
Other Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 321
20.3%
전 158
 
10.0%
충 153
 
9.7%
수 151
 
9.5%
하 48
 
3.0%
이 48
 
3.0%
넷 41
 
2.6%
게 27
 
1.7%
산 26
 
1.6%
휴 26
 
1.6%
Other values (173) 585
36.9%
Uppercase Letter
ValueCountFrequency (%)
H 13
34.2%
E 4
 
10.5%
S 3
 
7.9%
G 3
 
7.9%
P 3
 
7.9%
K 2
 
5.3%
O 2
 
5.3%
L 2
 
5.3%
T 2
 
5.3%
M 1
 
2.6%
Other values (3) 3
 
7.9%
Lowercase Letter
ValueCountFrequency (%)
n 2
20.0%
i 2
20.0%
t 2
20.0%
g 1
10.0%
a 1
10.0%
v 1
10.0%
e 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 6
54.5%
2 5
45.5%
Space Separator
ValueCountFrequency (%)
213
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1584
82.7%
Common 283
 
14.8%
Latin 48
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 321
20.3%
전 158
 
10.0%
충 153
 
9.7%
수 151
 
9.5%
하 48
 
3.0%
이 48
 
3.0%
넷 41
 
2.6%
게 27
 
1.7%
산 26
 
1.6%
휴 26
 
1.6%
Other values (173) 585
36.9%
Latin
ValueCountFrequency (%)
H 13
27.1%
E 4
 
8.3%
S 3
 
6.2%
G 3
 
6.2%
P 3
 
6.2%
K 2
 
4.2%
O 2
 
4.2%
n 2
 
4.2%
i 2
 
4.2%
L 2
 
4.2%
Other values (10) 12
25.0%
Common
ValueCountFrequency (%)
213
75.3%
) 27
 
9.5%
( 27
 
9.5%
1 6
 
2.1%
/ 5
 
1.8%
2 5
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1584
82.7%
ASCII 331
 
17.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 321
20.3%
전 158
 
10.0%
충 153
 
9.7%
수 151
 
9.5%
하 48
 
3.0%
이 48
 
3.0%
넷 41
 
2.6%
게 27
 
1.7%
산 26
 
1.6%
휴 26
 
1.6%
Other values (173) 585
36.9%
ASCII
ValueCountFrequency (%)
213
64.4%
) 27
 
8.2%
( 27
 
8.2%
H 13
 
3.9%
1 6
 
1.8%
/ 5
 
1.5%
2 5
 
1.5%
E 4
 
1.2%
S 3
 
0.9%
G 3
 
0.9%
Other values (16) 25
 
7.6%

화장실
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
O
133 
X
 
13
o
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th rowO
5th rowX

Common Values

ValueCountFrequency (%)
O 133
88.1%
X 13
 
8.6%
o 5
 
3.3%

Length

2024-04-06T17:28:22.268702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:22.615745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 138
91.4%
x 13
 
8.6%

대기실
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
X
91 
O
55 
x
 
4
o
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st rowX
2nd rowO
3rd rowX
4th rowX
5th rowO

Common Values

ValueCountFrequency (%)
X 91
60.3%
O 55
36.4%
x 4
 
2.6%
o 1
 
0.7%

Length

2024-04-06T17:28:22.947589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:23.218867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 95
62.9%
o 56
37.1%

카페
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
X
113 
O
33 
x
 
4
o
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
X 113
74.8%
O 33
 
21.9%
x 4
 
2.6%
o 1
 
0.7%

Length

2024-04-06T17:28:23.458668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:23.701889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 117
77.5%
o 34
 
22.5%

정비소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
X
134 
O
 
12
x
 
4
o
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
X 134
88.7%
O 12
 
7.9%
x 4
 
2.6%
o 1
 
0.7%

Length

2024-04-06T17:28:23.925323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:24.257694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 138
91.4%
o 13
 
8.6%

세차장
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
X
104 
O
42 
x
 
3
o
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowX
2nd rowX
3rd rowO
4th rowX
5th rowX

Common Values

ValueCountFrequency (%)
X 104
68.9%
O 42
27.8%
x 3
 
2.0%
o 2
 
1.3%

Length

2024-04-06T17:28:24.568521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:24.920087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 107
70.9%
o 44
29.1%

편의점
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
X
109 
O
37 
x
 
4
o
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
X 109
72.2%
O 37
 
24.5%
x 4
 
2.6%
o 1
 
0.7%

Length

2024-04-06T17:28:25.234550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:25.473838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 113
74.8%
o 38
 
25.2%

Interactions

2024-04-06T17:28:18.242882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:28:25.654321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분화장실대기실카페정비소세차장편의점
구분1.0000.5130.4130.3710.3990.3690.401
화장실0.5131.0000.6770.6790.6730.6770.680
대기실0.4130.6771.0000.9040.9820.9380.900
카페0.3710.6790.9041.0000.9090.9160.997
정비소0.3990.6730.9820.9091.0000.9390.911
세차장0.3690.6770.9380.9160.9391.0000.914
편의점0.4010.6800.9000.9970.9110.9141.000
2024-04-06T17:28:25.886549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정비소세차장화장실대기실카페편의점
정비소1.0000.6710.7010.8160.6030.607
세차장0.6711.0000.7050.6690.6180.614
화장실0.7010.7051.0000.7050.7080.709
대기실0.8160.6690.7051.0000.5940.587
카페0.6030.6180.7080.5941.0000.920
편의점0.6070.6140.7090.5870.9201.000
2024-04-06T17:28:26.139414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분화장실대기실카페정비소세차장편의점
구분1.0000.3480.2720.2320.2370.2240.257
화장실0.3481.0000.7050.7080.7010.7050.709
대기실0.2720.7051.0000.5940.8160.6690.587
카페0.2320.7080.5941.0000.6030.6180.920
정비소0.2370.7010.8160.6031.0000.6710.607
세차장0.2240.7050.6690.6180.6711.0000.614
편의점0.2570.7090.5870.9200.6070.6141.000

Missing values

2024-04-06T17:28:18.482725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:28:18.743561image/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

구분충전소 코드충전소 명화장실대기실카페정비소세차장편의점
012920020121HS2014001광주 진곡수소충전소OXXXXX
124480020121HS2015001내포수소충전소OOXXXX
233114020121HS2017001옥동LPG 수소 복합충전소OXXXOX
344812120121HS2017002창원팔룡 수소충전소OXXXXX
452771020121HS2017003대구 주행시험장 수소충전소XOXXXX
562920020121HS2018001광주 동곡수소충전소XXXXXX
673120020121HS2018002경동수소복합충전소OXXXOX
784812320121HS2018003창원성주수소충전소OXXXXX
893171020121HS2019001신일복합 수소충전소OXXXOX
9104155020121HS2019002H안성휴게소 수소충전소 (서울 상행)OXOXOO
구분충전소 코드충전소 명화장실대기실카페정비소세차장편의점
1411424812720121HS2023009마산자유무역지역 수소충전소OXXXXX
1421434215020121HS2022056하이넷 강릉시청 수소충전소OXXXXX
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