Overview

Dataset statistics

Number of variables33
Number of observations157
Missing cells9
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.7 KiB
Average record size in memory271.8 B

Variable types

Numeric5
Text5
Categorical23

Dataset

Description수소유통센터에서 조사된 수소충전소 위치 및 가격, 영업시간 등 수소충전소 운영현황으로 수소 차 이용자들의 편의 증대 및 수소 충전소 보급 현황 조회 가능
Author한국가스공사
URLhttps://www.data.go.kr/data/15098704/fileData.do

Alerts

화요일_시작 is highly imbalanced (51.1%)Imbalance
목요일_시작 is highly imbalanced (51.1%)Imbalance
금요일_시작 is highly imbalanced (51.2%)Imbalance
휴식_시작 is highly imbalanced (72.0%)Imbalance
휴식_종료 is highly imbalanced (70.1%)Imbalance
전화번호 has 6 (3.8%) missing valuesMissing
도로명주소 has 3 (1.9%) missing valuesMissing
순번 has unique valuesUnique
충전소_관리번호 has unique valuesUnique
충전소_명 has unique valuesUnique
지번주소 has unique valuesUnique

Reproduction

Analysis started2024-04-13 13:29:26.692427
Analysis finished2024-04-13 13:29:28.654493
Duration1.96 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct157
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79
Minimum1
Maximum157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-13T22:29:28.872117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.8
Q140
median79
Q3118
95-th percentile149.2
Maximum157
Range156
Interquartile range (IQR)78

Descriptive statistics

Standard deviation45.466105
Coefficient of variation (CV)0.57552031
Kurtosis-1.2
Mean79
Median Absolute Deviation (MAD)39
Skewness0
Sum12403
Variance2067.1667
MonotonicityStrictly increasing
2024-04-13T22:29:29.326795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
109 1
 
0.6%
102 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
110 1
 
0.6%
Other values (147) 147
93.6%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
157 1
0.6%
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%
149 1
0.6%
148 1
0.6%

충전소_관리번호
Text

UNIQUE 

Distinct157
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-13T22:29:30.072656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters2983
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

Unique157 ?
Unique (%)100.0%

Sample

1st row2826020121HS2022033
2nd row1150020121HS2022001
3rd row4725020121HS2022012
4th row4313020121HS2020003
5th row4513020121HS2022050
ValueCountFrequency (%)
2826020121hs2022033 1
 
0.6%
3114020121hs2017001 1
 
0.6%
3611020121hs2020007 1
 
0.6%
2729020121hs2020009 1
 
0.6%
3023020121hs2020019 1
 
0.6%
4159020121hs2020012 1
 
0.6%
4511320121hs2020013 1
 
0.6%
4420020121hs2020015 1
 
0.6%
4122020121hs2020016 1
 
0.6%
2920020121hs2018001 1
 
0.6%
Other values (147) 147
93.6%
2024-04-13T22:29:31.186591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 792
26.6%
0 703
23.6%
1 608
20.4%
4 163
 
5.5%
H 157
 
5.3%
S 157
 
5.3%
3 132
 
4.4%
5 68
 
2.3%
7 61
 
2.0%
8 52
 
1.7%
Other values (2) 90
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2669
89.5%
Uppercase Letter 314
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 792
29.7%
0 703
26.3%
1 608
22.8%
4 163
 
6.1%
3 132
 
4.9%
5 68
 
2.5%
7 61
 
2.3%
8 52
 
1.9%
9 46
 
1.7%
6 44
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
H 157
50.0%
S 157
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2669
89.5%
Latin 314
 
10.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 792
29.7%
0 703
26.3%
1 608
22.8%
4 163
 
6.1%
3 132
 
4.9%
5 68
 
2.5%
7 61
 
2.3%
8 52
 
1.9%
9 46
 
1.7%
6 44
 
1.6%
Latin
ValueCountFrequency (%)
H 157
50.0%
S 157
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 792
26.6%
0 703
23.6%
1 608
20.4%
4 163
 
5.5%
H 157
 
5.3%
S 157
 
5.3%
3 132
 
4.4%
5 68
 
2.3%
7 61
 
2.0%
8 52
 
1.7%
Other values (2) 90
 
3.0%

충전소_명
Text

UNIQUE 

Distinct157
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-13T22:29:32.279365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length13.127389
Min length6

Characters and Unicode

Total characters2061
Distinct characters214
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

Unique157 ?
Unique (%)100.0%

Sample

1st row하이넷 환경산업연구단지 수소충전소
2nd row마곡 에코 수소충전소
3rd row하이넷 상주외답 수소충전소
4th row충주 연수 수소충전소
5th row하이넷 군산지곡 수소충전소
ValueCountFrequency (%)
수소충전소 102
26.5%
하이넷 44
 
11.4%
충전소 6
 
1.6%
창원 5
 
1.3%
광주 4
 
1.0%
서울특별시 3
 
0.8%
울산 3
 
0.8%
e1 3
 
0.8%
평택 3
 
0.8%
삼척 2
 
0.5%
Other values (199) 210
54.5%
2024-04-13T22:29:33.813481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 329
16.0%
230
 
11.2%
전 163
 
7.9%
충 159
 
7.7%
수 153
 
7.4%
이 53
 
2.6%
하 52
 
2.5%
넷 44
 
2.1%
) 33
 
1.6%
( 33
 
1.6%
Other values (204) 812
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1709
82.9%
Space Separator 230
 
11.2%
Close Punctuation 33
 
1.6%
Open Punctuation 33
 
1.6%
Uppercase Letter 31
 
1.5%
Lowercase Letter 12
 
0.6%
Decimal Number 9
 
0.4%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 329
19.3%
전 163
 
9.5%
충 159
 
9.3%
수 153
 
9.0%
이 53
 
3.1%
하 52
 
3.0%
넷 44
 
2.6%
향 29
 
1.7%
게 28
 
1.6%
휴 27
 
1.6%
Other values (178) 672
39.3%
Uppercase Letter
ValueCountFrequency (%)
H 12
38.7%
E 3
 
9.7%
S 3
 
9.7%
T 2
 
6.5%
P 2
 
6.5%
G 2
 
6.5%
K 2
 
6.5%
L 1
 
3.2%
N 1
 
3.2%
C 1
 
3.2%
Other values (2) 2
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
n 2
16.7%
i 2
16.7%
o 2
16.7%
t 2
16.7%
e 1
8.3%
g 1
8.3%
a 1
8.3%
v 1
8.3%
Decimal Number
ValueCountFrequency (%)
1 5
55.6%
2 4
44.4%
Space Separator
ValueCountFrequency (%)
230
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1709
82.9%
Common 309
 
15.0%
Latin 43
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 329
19.3%
전 163
 
9.5%
충 159
 
9.3%
수 153
 
9.0%
이 53
 
3.1%
하 52
 
3.0%
넷 44
 
2.6%
향 29
 
1.7%
게 28
 
1.6%
휴 27
 
1.6%
Other values (178) 672
39.3%
Latin
ValueCountFrequency (%)
H 12
27.9%
E 3
 
7.0%
S 3
 
7.0%
T 2
 
4.7%
P 2
 
4.7%
G 2
 
4.7%
K 2
 
4.7%
n 2
 
4.7%
i 2
 
4.7%
o 2
 
4.7%
Other values (10) 11
25.6%
Common
ValueCountFrequency (%)
230
74.4%
) 33
 
10.7%
( 33
 
10.7%
1 5
 
1.6%
/ 4
 
1.3%
2 4
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1709
82.9%
ASCII 352
 
17.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 329
19.3%
전 163
 
9.5%
충 159
 
9.3%
수 153
 
9.0%
이 53
 
3.1%
하 52
 
3.0%
넷 44
 
2.6%
향 29
 
1.7%
게 28
 
1.6%
휴 27
 
1.6%
Other values (178) 672
39.3%
ASCII
ValueCountFrequency (%)
230
65.3%
) 33
 
9.4%
( 33
 
9.4%
H 12
 
3.4%
1 5
 
1.4%
/ 4
 
1.1%
2 4
 
1.1%
E 3
 
0.9%
S 3
 
0.9%
T 2
 
0.6%
Other values (16) 23
 
6.5%

전화번호
Text

MISSING 

Distinct151
Distinct (%)100.0%
Missing6
Missing (%)3.8%
Memory size1.4 KiB
2024-04-13T22:29:34.742943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.15894
Min length1

Characters and Unicode

Total characters1836
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
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 row070-7727-1719
2nd row02-6081-8883
3rd row054-532-3600
4th row043-724-2430
5th row0507-1304-1145
ValueCountFrequency (%)
052-998-8488 1
 
0.7%
042-716-4015 1
 
0.7%
070-4304-0786 1
 
0.7%
053-606-1188 1
 
0.7%
070-7780-2046 1
 
0.7%
031-8043-7800 1
 
0.7%
063-278-0109 1
 
0.7%
041-536-8870 1
 
0.7%
031-656-3543 1
 
0.7%
043-653-5987 1
 
0.7%
Other values (140) 140
93.3%
2024-04-13T22:29:36.083959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 313
17.0%
- 300
16.3%
3 169
9.2%
7 164
8.9%
5 163
8.9%
4 159
8.7%
6 132
7.2%
2 131
7.1%
1 127
6.9%
8 101
 
5.5%
Other values (2) 77
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1535
83.6%
Dash Punctuation 300
 
16.3%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 313
20.4%
3 169
11.0%
7 164
10.7%
5 163
10.6%
4 159
10.4%
6 132
8.6%
2 131
8.5%
1 127
8.3%
8 101
 
6.6%
9 76
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 300
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 313
17.0%
- 300
16.3%
3 169
9.2%
7 164
8.9%
5 163
8.9%
4 159
8.7%
6 132
7.2%
2 131
7.1%
1 127
6.9%
8 101
 
5.5%
Other values (2) 77
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 313
17.0%
- 300
16.3%
3 169
9.2%
7 164
8.9%
5 163
8.9%
4 159
8.7%
6 132
7.2%
2 131
7.1%
1 127
6.9%
8 101
 
5.5%
Other values (2) 77
 
4.2%

도로명주소
Text

MISSING 

Distinct154
Distinct (%)100.0%
Missing3
Missing (%)1.9%
Memory size1.4 KiB
2024-04-13T22:29:37.221306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length19.162338
Min length12

Characters and Unicode

Total characters2951
Distinct characters206
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)100.0%

Sample

1st row인천 서구 정서진로 410
2nd row서울 강서구 양천로 225
3rd row경북 상주시 영남제일로 1339
4th row충청북도 충주시 금봉대로 605 연수LPG충전소
5th row전북 군산시 월명로 112
ValueCountFrequency (%)
경기 18
 
2.6%
강원특별자치도 12
 
1.7%
창원시 10
 
1.4%
경상남도 10
 
1.4%
경기도 9
 
1.3%
전북 8
 
1.1%
충청북도 8
 
1.1%
충북 8
 
1.1%
서울 7
 
1.0%
충남 7
 
1.0%
Other values (450) 607
86.2%
2024-04-13T22:29:38.533303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
550
 
18.6%
로 145
 
4.9%
시 104
 
3.5%
1 92
 
3.1%
구 80
 
2.7%
5 67
 
2.3%
도 66
 
2.2%
2 64
 
2.2%
경 58
 
2.0%
3 55
 
1.9%
Other values (196) 1670
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1885
63.9%
Space Separator 550
 
18.6%
Decimal Number 492
 
16.7%
Dash Punctuation 11
 
0.4%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Uppercase Letter 4
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 145
 
7.7%
시 104
 
5.5%
구 80
 
4.2%
도 66
 
3.5%
경 58
 
3.1%
남 54
 
2.9%
산 51
 
2.7%
대 50
 
2.7%
북 42
 
2.2%
원 41
 
2.2%
Other values (177) 1194
63.3%
Decimal Number
ValueCountFrequency (%)
1 92
18.7%
5 67
13.6%
2 64
13.0%
3 55
11.2%
7 41
8.3%
4 40
8.1%
0 39
7.9%
6 39
7.9%
9 29
 
5.9%
8 26
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
P 1
25.0%
L 1
25.0%
G 1
25.0%
B 1
25.0%
Space Separator
ValueCountFrequency (%)
550
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1886
63.9%
Common 1061
36.0%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 145
 
7.7%
시 104
 
5.5%
구 80
 
4.2%
도 66
 
3.5%
경 58
 
3.1%
남 54
 
2.9%
산 51
 
2.7%
대 50
 
2.7%
북 42
 
2.2%
원 41
 
2.2%
Other values (178) 1195
63.4%
Common
ValueCountFrequency (%)
550
51.8%
1 92
 
8.7%
5 67
 
6.3%
2 64
 
6.0%
3 55
 
5.2%
7 41
 
3.9%
4 40
 
3.8%
0 39
 
3.7%
6 39
 
3.7%
9 29
 
2.7%
Other values (4) 45
 
4.2%
Latin
ValueCountFrequency (%)
P 1
25.0%
L 1
25.0%
G 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1885
63.9%
ASCII 1065
36.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
550
51.6%
1 92
 
8.6%
5 67
 
6.3%
2 64
 
6.0%
3 55
 
5.2%
7 41
 
3.8%
4 40
 
3.8%
0 39
 
3.7%
6 39
 
3.7%
9 29
 
2.7%
Other values (8) 49
 
4.6%
Hangul
ValueCountFrequency (%)
로 145
 
7.7%
시 104
 
5.5%
구 80
 
4.2%
도 66
 
3.5%
경 58
 
3.1%
남 54
 
2.9%
산 51
 
2.7%
대 50
 
2.7%
북 42
 
2.2%
원 41
 
2.2%
Other values (177) 1194
63.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

지번주소
Text

UNIQUE 

Distinct157
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-13T22:29:39.774429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length19.732484
Min length10

Characters and Unicode

Total characters3098
Distinct characters217
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)100.0%

Sample

1st row인천 서구 오류동 1708
2nd row서울 강서구 마곡동 61-1
3rd row경북 상주시 외답동 718
4th row충청북도 충주시 연수동 315-6 연수LPG충전소
5th row전북 군산시 지곡동 2-6
ValueCountFrequency (%)
경기 18
 
2.4%
강원특별자치도 11
 
1.5%
창원시 10
 
1.3%
경남 9
 
1.2%
경기도 9
 
1.2%
전북 8
 
1.1%
충북 8
 
1.1%
충청북도 8
 
1.1%
대전 7
 
0.9%
경상남도 7
 
0.9%
Other values (503) 647
87.2%
2024-04-13T22:29:41.251192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
589
 
19.0%
1 128
 
4.1%
동 119
 
3.8%
- 110
 
3.6%
시 104
 
3.4%
구 82
 
2.6%
3 70
 
2.3%
2 63
 
2.0%
6 60
 
1.9%
산 56
 
1.8%
Other values (207) 1717
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1802
58.2%
Space Separator 589
 
19.0%
Decimal Number 588
 
19.0%
Dash Punctuation 110
 
3.6%
Uppercase Letter 4
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 119
 
6.6%
시 104
 
5.8%
구 82
 
4.6%
산 56
 
3.1%
리 55
 
3.1%
남 53
 
2.9%
경 52
 
2.9%
도 50
 
2.8%
북 43
 
2.4%
충 40
 
2.2%
Other values (188) 1148
63.7%
Decimal Number
ValueCountFrequency (%)
1 128
21.8%
3 70
11.9%
2 63
10.7%
6 60
10.2%
7 51
 
8.7%
4 50
 
8.5%
8 49
 
8.3%
5 41
 
7.0%
0 39
 
6.6%
9 37
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
G 1
25.0%
P 1
25.0%
L 1
25.0%
B 1
25.0%
Space Separator
ValueCountFrequency (%)
589
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1801
58.1%
Common 1291
41.7%
Latin 5
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 119
 
6.6%
시 104
 
5.8%
구 82
 
4.6%
산 56
 
3.1%
리 55
 
3.1%
남 53
 
2.9%
경 52
 
2.9%
도 50
 
2.8%
북 43
 
2.4%
충 40
 
2.2%
Other values (187) 1147
63.7%
Common
ValueCountFrequency (%)
589
45.6%
1 128
 
9.9%
- 110
 
8.5%
3 70
 
5.4%
2 63
 
4.9%
6 60
 
4.6%
7 51
 
4.0%
4 50
 
3.9%
8 49
 
3.8%
5 41
 
3.2%
Other values (4) 80
 
6.2%
Latin
ValueCountFrequency (%)
e 1
20.0%
G 1
20.0%
P 1
20.0%
L 1
20.0%
B 1
20.0%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1801
58.1%
ASCII 1296
41.8%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
589
45.4%
1 128
 
9.9%
- 110
 
8.5%
3 70
 
5.4%
2 63
 
4.9%
6 60
 
4.6%
7 51
 
3.9%
4 50
 
3.9%
8 49
 
3.8%
5 41
 
3.2%
Other values (9) 85
 
6.6%
Hangul
ValueCountFrequency (%)
동 119
 
6.6%
시 104
 
5.8%
구 82
 
4.6%
산 56
 
3.1%
리 55
 
3.1%
남 53
 
2.9%
경 52
 
2.9%
도 50
 
2.8%
북 43
 
2.4%
충 40
 
2.2%
Other values (187) 1147
63.7%
CJK
ValueCountFrequency (%)
內 1
100.0%

충전소_유형코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2
92 
1
65 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 92
58.6%
1 65
41.4%

Length

2024-04-13T22:29:41.477997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:29:41.656139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 92
58.6%
1 65
41.4%

충전소_유형명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
복합
92 
단독
65 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row단독
2nd row단독
3rd row복합
4th row복합
5th row복합

Common Values

ValueCountFrequency (%)
복합 92
58.6%
단독 65
41.4%

Length

2024-04-13T22:29:41.837356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:29:42.009991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복합 92
58.6%
단독 65
41.4%

충전소유형비고
Categorical

Distinct18
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
69 
LPG
33 
CNG
12 
주유소
12 
LPG,주유소
7 
Other values (13)
24 

Length

Max length12
Median length10
Mean length4.3821656
Min length2

Unique

Unique10 ?
Unique (%)6.4%

Sample

1st row<NA>
2nd row<NA>
3rd rowLNG
4th rowLPG
5th rowLPG

Common Values

ValueCountFrequency (%)
<NA> 69
43.9%
LPG 33
21.0%
CNG 12
 
7.6%
주유소 12
 
7.6%
LPG,주유소 7
 
4.5%
LPG,주유소,전기 6
 
3.8%
주유소, LPG 6
 
3.8%
주유소,전기 2
 
1.3%
가스, 주유소 1
 
0.6%
LPG, 전기 1
 
0.6%
Other values (8) 8
 
5.1%

Length

2024-04-13T22:29:42.209985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 69
40.4%
lpg 42
24.6%
주유소 23
 
13.5%
cng 12
 
7.0%
lpg,주유소 7
 
4.1%
lpg,주유소,전기 6
 
3.5%
전기 5
 
2.9%
주유소,전기 2
 
1.2%
가스 2
 
1.2%
lpg,전기차충전 1
 
0.6%
Other values (2) 2
 
1.2%

충전가능차량코드
Categorical

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
1
93 
5
41 
6
21 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row1
4th row1
5th row6

Common Values

ValueCountFrequency (%)
1 93
59.2%
5 41
26.1%
6 21
 
13.4%
3 2
 
1.3%

Length

2024-04-13T22:29:42.425518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:29:42.744334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 93
59.2%
5 41
26.1%
6 21
 
13.4%
3 2
 
1.3%

충전가능차량
Categorical

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
승용
93 
승용/버스
41 
승용/버스/트럭
21 
버스
 
2

Length

Max length8
Median length2
Mean length3.5859873
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row승용/버스
2nd row승용/버스
3rd row승용
4th row승용
5th row승용/버스/트럭

Common Values

ValueCountFrequency (%)
승용 93
59.2%
승용/버스 41
26.1%
승용/버스/트럭 21
 
13.4%
버스 2
 
1.3%

Length

2024-04-13T22:29:42.944019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:29:43.134386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승용 93
59.2%
승용/버스 41
26.1%
승용/버스/트럭 21
 
13.4%
버스 2
 
1.3%

판매가격
Real number (ℝ)

Distinct21
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9729.6815
Minimum7700
Maximum12400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-13T22:29:43.321328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7700
5-th percentile8500
Q19400
median9900
Q39900
95-th percentile10432
Maximum12400
Range4700
Interquartile range (IQR)500

Descriptive statistics

Standard deviation705.8423
Coefficient of variation (CV)0.072545263
Kurtosis4.809486
Mean9729.6815
Median Absolute Deviation (MAD)0
Skewness0.35707616
Sum1527560
Variance498213.36
MonotonicityNot monotonic
2024-04-13T22:29:43.517683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
9900 88
56.1%
9400 22
 
14.0%
8500 6
 
3.8%
9700 5
 
3.2%
10400 5
 
3.2%
8800 5
 
3.2%
9600 4
 
2.5%
7700 3
 
1.9%
9500 3
 
1.9%
9800 2
 
1.3%
Other values (11) 14
 
8.9%
ValueCountFrequency (%)
7700 3
 
1.9%
7800 1
 
0.6%
7900 1
 
0.6%
8300 2
 
1.3%
8500 6
 
3.8%
8800 5
 
3.2%
9200 1
 
0.6%
9400 22
14.0%
9500 3
 
1.9%
9600 4
 
2.5%
ValueCountFrequency (%)
12400 2
 
1.3%
12100 2
 
1.3%
11900 1
 
0.6%
10900 1
 
0.6%
10600 1
 
0.6%
10560 1
 
0.6%
10400 5
 
3.2%
10000 1
 
0.6%
9900 88
56.1%
9800 2
 
1.3%

이용가능요일
Real number (ℝ)

Distinct12
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10337155
Minimum1111000
Maximum11111111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-13T22:29:43.705351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1111000
5-th percentile1111111
Q111111101
median11111111
Q311111111
95-th percentile11111111
Maximum11111111
Range10000111
Interquartile range (IQR)10

Descriptive statistics

Standard deviation2663870.6
Coefficient of variation (CV)0.25769863
Kurtosis8.4501396
Mean10337155
Median Absolute Deviation (MAD)0
Skewness-3.2142796
Sum1.6229333 × 109
Variance7.0962064 × 1012
MonotonicityNot monotonic
2024-04-13T22:29:43.900480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
11111111 101
64.3%
11111101 28
 
17.8%
1111111 9
 
5.7%
11011111 5
 
3.2%
11111011 4
 
2.5%
11111000 3
 
1.9%
11111100 2
 
1.3%
1111110 1
 
0.6%
11101111 1
 
0.6%
1111101 1
 
0.6%
Other values (2) 2
 
1.3%
ValueCountFrequency (%)
1111000 1
 
0.6%
1111101 1
 
0.6%
1111110 1
 
0.6%
1111111 9
5.7%
10111111 1
 
0.6%
11011111 5
3.2%
11101111 1
 
0.6%
11111000 3
 
1.9%
11111011 4
2.5%
11111100 2
 
1.3%
ValueCountFrequency (%)
11111111 101
64.3%
11111101 28
 
17.8%
11111100 2
 
1.3%
11111011 4
 
2.5%
11111000 3
 
1.9%
11101111 1
 
0.6%
11011111 5
 
3.2%
10111111 1
 
0.6%
1111111 9
 
5.7%
1111110 1
 
0.6%

월요일_시작
Categorical

Distinct15
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
95 
09:00
17 
<NA>
12 
07:00
11 
06:00
 
8
Other values (10)
14 

Length

Max length5
Median length5
Mean length4.9235669
Min length4

Unique

Unique7 ?
Unique (%)4.5%

Sample

1st row<NA>
2nd row09:00
3rd row08:00
4th row07:30
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 95
60.5%
09:00 17
 
10.8%
<NA> 12
 
7.6%
07:00 11
 
7.0%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
Other values (5) 5
 
3.2%

Length

2024-04-13T22:29:44.117881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 95
60.5%
09:00 17
 
10.8%
na 12
 
7.6%
07:00 11
 
7.0%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
Other values (5) 5
 
3.2%

월요일_종료
Categorical

Distinct12
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
51 
22:00
49 
21:00
15 
<NA>
12 
19:00
10 
Other values (7)
20 

Length

Max length5
Median length5
Mean length4.9235669
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row18:00
3rd row20:00
4th row20:30
5th row20:00

Common Values

ValueCountFrequency (%)
20:00 51
32.5%
22:00 49
31.2%
21:00 15
 
9.6%
<NA> 12
 
7.6%
19:00 10
 
6.4%
18:00 6
 
3.8%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
Other values (2) 4
 
2.5%

Length

2024-04-13T22:29:44.337048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 51
32.5%
22:00 49
31.2%
21:00 15
 
9.6%
na 12
 
7.6%
19:00 10
 
6.4%
18:00 6
 
3.8%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
Other values (2) 4
 
2.5%

화요일_시작
Categorical

IMBALANCE 

Distinct15
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
103 
09:00
19 
07:00
12 
06:00
 
8
08:30
 
3
Other values (10)
12 

Length

Max length5
Median length5
Mean length4.9936306
Min length4

Unique

Unique8 ?
Unique (%)5.1%

Sample

1st row08:00
2nd row09:00
3rd row08:00
4th row07:30
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 103
65.6%
09:00 19
 
12.1%
07:00 12
 
7.6%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
12:00 1
 
0.6%
Other values (5) 5
 
3.2%

Length

2024-04-13T22:29:44.553348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 103
65.6%
09:00 19
 
12.1%
07:00 12
 
7.6%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
12:00 1
 
0.6%
Other values (5) 5
 
3.2%

화요일_종료
Categorical

Distinct12
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
60 
22:00
49 
21:00
15 
19:00
11 
18:00
7 
Other values (7)
15 

Length

Max length5
Median length5
Mean length4.9936306
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row20:00
2nd row18:00
3rd row20:00
4th row20:30
5th row20:00

Common Values

ValueCountFrequency (%)
20:00 60
38.2%
22:00 49
31.2%
21:00 15
 
9.6%
19:00 11
 
7.0%
18:00 7
 
4.5%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
23:00 2
 
1.3%
Other values (2) 3
 
1.9%

Length

2024-04-13T22:29:44.764460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 60
38.2%
22:00 49
31.2%
21:00 15
 
9.6%
19:00 11
 
7.0%
18:00 7
 
4.5%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
23:00 2
 
1.3%
Other values (2) 3
 
1.9%

수요일_시작
Categorical

Distinct15
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
97 
09:00
23 
07:00
10 
06:00
 
8
<NA>
 
5
Other values (10)
14 

Length

Max length5
Median length5
Mean length4.9681529
Min length4

Unique

Unique7 ?
Unique (%)4.5%

Sample

1st row08:00
2nd row09:00
3rd row08:00
4th row07:30
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 97
61.8%
09:00 23
 
14.6%
07:00 10
 
6.4%
06:00 8
 
5.1%
<NA> 5
 
3.2%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
Other values (5) 5
 
3.2%

Length

2024-04-13T22:29:44.979747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 97
61.8%
09:00 23
 
14.6%
07:00 10
 
6.4%
06:00 8
 
5.1%
na 5
 
3.2%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
Other values (5) 5
 
3.2%

수요일_종료
Categorical

Distinct12
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
56 
22:00
49 
21:00
13 
18:00
11 
19:00
9 
Other values (7)
19 

Length

Max length5
Median length5
Mean length4.9681529
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20:00
2nd row18:00
3rd row20:00
4th row20:30
5th row20:00

Common Values

ValueCountFrequency (%)
20:00 56
35.7%
22:00 49
31.2%
21:00 13
 
8.3%
18:00 11
 
7.0%
19:00 9
 
5.7%
<NA> 5
 
3.2%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
Other values (2) 4
 
2.5%

Length

2024-04-13T22:29:45.197075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 56
35.7%
22:00 49
31.2%
21:00 13
 
8.3%
18:00 11
 
7.0%
19:00 9
 
5.7%
na 5
 
3.2%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
Other values (2) 4
 
2.5%

목요일_시작
Categorical

IMBALANCE 

Distinct15
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
103 
09:00
19 
07:00
12 
06:00
 
8
08:30
 
3
Other values (10)
12 

Length

Max length5
Median length5
Mean length4.9936306
Min length4

Unique

Unique8 ?
Unique (%)5.1%

Sample

1st row08:00
2nd row09:00
3rd row08:00
4th row07:30
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 103
65.6%
09:00 19
 
12.1%
07:00 12
 
7.6%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
12:00 1
 
0.6%
Other values (5) 5
 
3.2%

Length

2024-04-13T22:29:45.416266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 103
65.6%
09:00 19
 
12.1%
07:00 12
 
7.6%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
12:00 1
 
0.6%
Other values (5) 5
 
3.2%

목요일_종료
Categorical

Distinct12
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
61 
22:00
49 
21:00
15 
19:00
10 
18:00
7 
Other values (7)
15 

Length

Max length5
Median length5
Mean length4.9936306
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row20:00
2nd row18:00
3rd row20:00
4th row20:30
5th row20:00

Common Values

ValueCountFrequency (%)
20:00 61
38.9%
22:00 49
31.2%
21:00 15
 
9.6%
19:00 10
 
6.4%
18:00 7
 
4.5%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
23:00 2
 
1.3%
Other values (2) 3
 
1.9%

Length

2024-04-13T22:29:45.629319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 61
38.9%
22:00 49
31.2%
21:00 15
 
9.6%
19:00 10
 
6.4%
18:00 7
 
4.5%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
23:00 2
 
1.3%
Other values (2) 3
 
1.9%

금요일_시작
Categorical

IMBALANCE 

Distinct14
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
104 
09:00
19 
07:00
12 
06:00
 
8
08:30
 
3
Other values (9)
11 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique7 ?
Unique (%)4.5%

Sample

1st row08:00
2nd row09:00
3rd row08:00
4th row07:30
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 104
66.2%
09:00 19
 
12.1%
07:00 12
 
7.6%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
12:00 1
 
0.6%
Other values (4) 4
 
2.5%

Length

2024-04-13T22:29:45.834799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 104
66.2%
09:00 19
 
12.1%
07:00 12
 
7.6%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
12:00 1
 
0.6%
Other values (4) 4
 
2.5%

금요일_종료
Categorical

Distinct11
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
61 
22:00
49 
21:00
15 
19:00
11 
18:00
7 
Other values (6)
14 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20:00
2nd row18:00
3rd row20:00
4th row20:30
5th row20:00

Common Values

ValueCountFrequency (%)
20:00 61
38.9%
22:00 49
31.2%
21:00 15
 
9.6%
19:00 11
 
7.0%
18:00 7
 
4.5%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
23:00 2
 
1.3%

Length

2024-04-13T22:29:46.036515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 61
38.9%
22:00 49
31.2%
21:00 15
 
9.6%
19:00 11
 
7.0%
18:00 7
 
4.5%
00:00 4
 
2.5%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
23:00 2
 
1.3%

토요일_시작
Categorical

Distinct14
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
98 
09:00
20 
07:00
 
9
<NA>
 
8
06:00
 
8
Other values (9)
14 

Length

Max length5
Median length5
Mean length4.9490446
Min length4

Unique

Unique5 ?
Unique (%)3.2%

Sample

1st row08:00
2nd row<NA>
3rd row08:00
4th row07:30
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 98
62.4%
09:00 20
 
12.7%
07:00 9
 
5.7%
<NA> 8
 
5.1%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
13:00 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
Other values (4) 4
 
2.5%

Length

2024-04-13T22:29:46.250077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 98
62.4%
09:00 20
 
12.7%
07:00 9
 
5.7%
na 8
 
5.1%
06:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
13:00 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
Other values (4) 4
 
2.5%

토요일_종료
Categorical

Distinct15
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
50 
22:00
46 
18:00
14 
21:00
11 
19:00
9 
Other values (10)
27 

Length

Max length5
Median length5
Mean length4.9490446
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row20:00
2nd row<NA>
3rd row20:00
4th row20:30
5th row20:00

Common Values

ValueCountFrequency (%)
20:00 50
31.8%
22:00 46
29.3%
18:00 14
 
8.9%
21:00 11
 
7.0%
19:00 9
 
5.7%
<NA> 8
 
5.1%
00:00 3
 
1.9%
17:00 3
 
1.9%
20:30 2
 
1.3%
18:30 2
 
1.3%
Other values (5) 9
 
5.7%

Length

2024-04-13T22:29:46.469044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 50
31.8%
22:00 46
29.3%
18:00 14
 
8.9%
21:00 11
 
7.0%
19:00 9
 
5.7%
na 8
 
5.1%
00:00 3
 
1.9%
17:00 3
 
1.9%
20:30 2
 
1.3%
18:30 2
 
1.3%
Other values (5) 9
 
5.7%

일요일_시작
Categorical

Distinct13
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
77 
<NA>
35 
09:00
17 
06:00
8 
07:00
8 
Other values (8)
12 

Length

Max length5
Median length5
Mean length4.7770701
Min length4

Unique

Unique5 ?
Unique (%)3.2%

Sample

1st row08:00
2nd row<NA>
3rd row<NA>
4th row07:30
5th row<NA>

Common Values

ValueCountFrequency (%)
08:00 77
49.0%
<NA> 35
22.3%
09:00 17
 
10.8%
06:00 8
 
5.1%
07:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
13:00 2
 
1.3%
04:30 1
 
0.6%
10:00 1
 
0.6%
Other values (3) 3
 
1.9%

Length

2024-04-13T22:29:46.684270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 77
49.0%
na 35
22.3%
09:00 17
 
10.8%
06:00 8
 
5.1%
07:00 8
 
5.1%
08:30 3
 
1.9%
07:30 2
 
1.3%
13:00 2
 
1.3%
04:30 1
 
0.6%
10:00 1
 
0.6%
Other values (3) 3
 
1.9%

일요일_종료
Categorical

Distinct14
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
22:00
46 
<NA>
35 
20:00
33 
18:00
11 
21:00
9 
Other values (9)
23 

Length

Max length5
Median length5
Mean length4.7770701
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row20:00
2nd row<NA>
3rd row<NA>
4th row20:30
5th row<NA>

Common Values

ValueCountFrequency (%)
22:00 46
29.3%
<NA> 35
22.3%
20:00 33
21.0%
18:00 11
 
7.0%
21:00 9
 
5.7%
19:00 5
 
3.2%
13:00 3
 
1.9%
00:00 3
 
1.9%
17:00 3
 
1.9%
20:30 2
 
1.3%
Other values (4) 7
 
4.5%

Length

2024-04-13T22:29:46.902155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
22:00 46
29.3%
na 35
22.3%
20:00 33
21.0%
18:00 11
 
7.0%
21:00 9
 
5.7%
19:00 5
 
3.2%
13:00 3
 
1.9%
00:00 3
 
1.9%
17:00 3
 
1.9%
20:30 2
 
1.3%
Other values (4) 7
 
4.5%

공휴일_시작
Categorical

Distinct14
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
99 
09:00
21 
07:00
 
9
06:00
 
8
<NA>
 
7
Other values (9)
13 

Length

Max length5
Median length5
Mean length4.955414
Min length4

Unique

Unique6 ?
Unique (%)3.8%

Sample

1st row08:00
2nd row<NA>
3rd row08:00
4th row07:30
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 99
63.1%
09:00 21
 
13.4%
07:00 9
 
5.7%
06:00 8
 
5.1%
<NA> 7
 
4.5%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
Other values (4) 4
 
2.5%

Length

2024-04-13T22:29:47.120356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 99
63.1%
09:00 21
 
13.4%
07:00 9
 
5.7%
06:00 8
 
5.1%
na 7
 
4.5%
08:30 3
 
1.9%
07:30 2
 
1.3%
10:00 2
 
1.3%
15:00 1
 
0.6%
04:30 1
 
0.6%
Other values (4) 4
 
2.5%

공휴일_종료
Categorical

Distinct13
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
55 
22:00
46 
18:00
14 
21:00
13 
19:00
8 
Other values (8)
21 

Length

Max length5
Median length5
Mean length4.955414
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row20:00
2nd row<NA>
3rd row20:00
4th row20:30
5th row20:00

Common Values

ValueCountFrequency (%)
20:00 55
35.0%
22:00 46
29.3%
18:00 14
 
8.9%
21:00 13
 
8.3%
19:00 8
 
5.1%
<NA> 7
 
4.5%
00:00 3
 
1.9%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
Other values (3) 5
 
3.2%

Length

2024-04-13T22:29:47.342928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 55
35.0%
22:00 46
29.3%
18:00 14
 
8.9%
21:00 13
 
8.3%
19:00 8
 
5.1%
na 7
 
4.5%
00:00 3
 
1.9%
20:30 2
 
1.3%
18:30 2
 
1.3%
19:30 2
 
1.3%
Other values (3) 5
 
3.2%

휴식_시작
Categorical

IMBALANCE 

Distinct7
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
134 
12:00
18 
13:00
 
1
11:30
 
1
12:30
 
1
Other values (2)
 
2

Length

Max length5
Median length4
Mean length4.1464968
Min length4

Unique

Unique5 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 134
85.4%
12:00 18
 
11.5%
13:00 1
 
0.6%
11:30 1
 
0.6%
12:30 1
 
0.6%
00:00 1
 
0.6%
11:00 1
 
0.6%

Length

2024-04-13T22:29:47.560226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:29:47.766588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
85.4%
12:00 18
 
11.5%
13:00 1
 
0.6%
11:30 1
 
0.6%
12:30 1
 
0.6%
00:00 1
 
0.6%
11:00 1
 
0.6%

휴식_종료
Categorical

IMBALANCE 

Distinct7
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
134 
13:00
15 
12:30
 
4
13:30
 
1
12:00
 
1
Other values (2)
 
2

Length

Max length5
Median length4
Mean length4.1464968
Min length4

Unique

Unique4 ?
Unique (%)2.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 134
85.4%
13:00 15
 
9.6%
12:30 4
 
2.5%
13:30 1
 
0.6%
12:00 1
 
0.6%
00:01 1
 
0.6%
11:30 1
 
0.6%

Length

2024-04-13T22:29:47.988270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:29:48.191678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
85.4%
13:00 15
 
9.6%
12:30 4
 
2.5%
13:30 1
 
0.6%
12:00 1
 
0.6%
00:01 1
 
0.6%
11:30 1
 
0.6%

경도
Real number (ℝ)

Distinct156
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.64572
Minimum126.42364
Maximum129.35814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-13T22:29:48.422742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.42364
5-th percentile126.61923
Q1126.92668
median127.38684
Q3128.42776
95-th percentile129.23286
Maximum129.35814
Range2.9344976
Interquartile range (IQR)1.5010816

Descriptive statistics

Standard deviation0.86690831
Coefficient of variation (CV)0.0067915188
Kurtosis-0.94874758
Mean127.64572
Median Absolute Deviation (MAD)0.5565808
Skewness0.60848579
Sum20040.378
Variance0.75153002
MonotonicityNot monotonic
2024-04-13T22:29:48.672276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7062138 2
 
1.3%
126.6468357 1
 
0.6%
127.0609027 1
 
0.6%
127.2627363 1
 
0.6%
128.4933499 1
 
0.6%
127.4181837 1
 
0.6%
127.0860457 1
 
0.6%
127.1073934 1
 
0.6%
126.9779179 1
 
0.6%
126.4749956 1
 
0.6%
Other values (146) 146
93.0%
ValueCountFrequency (%)
126.423642 1
0.6%
126.4749956 1
0.6%
126.4785611 1
0.6%
126.4928859 1
0.6%
126.5572591 1
0.6%
126.5836975 1
0.6%
126.5935182 1
0.6%
126.6160767 1
0.6%
126.6200137 1
0.6%
126.6238205 1
0.6%
ValueCountFrequency (%)
129.3581396 1
0.6%
129.3574959 1
0.6%
129.352642 1
0.6%
129.3405148 1
0.6%
129.3340931 1
0.6%
129.32001 1
0.6%
129.309184 1
0.6%
129.2912722 1
0.6%
129.2182584 1
0.6%
129.2052601 1
0.6%

위도
Real number (ℝ)

Distinct156
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.457038
Minimum34.778618
Maximum38.217694
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-13T22:29:48.927975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.778618
5-th percentile35.110432
Q135.541794
median36.6206
Q337.295371
95-th percentile37.609221
Maximum38.217694
Range3.4390758
Interquartile range (IQR)1.7535769

Descriptive statistics

Standard deviation0.91900186
Coefficient of variation (CV)0.025207804
Kurtosis-1.3394175
Mean36.457038
Median Absolute Deviation (MAD)0.81806281
Skewness-0.20665987
Sum5723.755
Variance0.84456443
MonotonicityNot monotonic
2024-04-13T22:29:49.184616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.97641805 2
 
1.3%
37.56883834 1
 
0.6%
36.95458273 1
 
0.6%
36.50239111 1
 
0.6%
35.83546204 1
 
0.6%
36.42813799 1
 
0.6%
37.17751144 1
 
0.6%
35.86957651 1
 
0.6%
36.74763293 1
 
0.6%
37.45024251 1
 
0.6%
Other values (146) 146
93.0%
ValueCountFrequency (%)
34.7786179 1
0.6%
34.83026653 1
0.6%
34.89107035 1
0.6%
34.89459925 1
0.6%
34.9479768 1
0.6%
35.0684913 1
0.6%
35.08501212 1
0.6%
35.10725968 1
0.6%
35.11122459 1
0.6%
35.11316969 1
0.6%
ValueCountFrequency (%)
38.21769367 1
0.6%
37.91729242 1
0.6%
37.82228602 1
0.6%
37.81232681 1
0.6%
37.75237182 1
0.6%
37.68554894 1
0.6%
37.67063254 1
0.6%
37.64286644 1
0.6%
37.6008094 1
0.6%
37.58151064 1
0.6%

Sample

순번충전소_관리번호충전소_명전화번호도로명주소지번주소충전소_유형코드충전소_유형명충전소유형비고충전가능차량코드충전가능차량판매가격이용가능요일월요일_시작월요일_종료화요일_시작화요일_종료수요일_시작수요일_종료목요일_시작목요일_종료금요일_시작금요일_종료토요일_시작토요일_종료일요일_시작일요일_종료공휴일_시작공휴일_종료휴식_시작휴식_종료경도위도
012826020121HS2022033하이넷 환경산업연구단지 수소충전소070-7727-1719인천 서구 정서진로 410인천 서구 오류동 17081단독<NA>5승용/버스99001111111<NA><NA>08:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:00<NA><NA>126.64683637.568838
121150020121HS2022001마곡 에코 수소충전소02-6081-8883서울 강서구 양천로 225서울 강서구 마곡동 61-11단독<NA>5승용/버스99001111100009:0018:0009:0018:0009:0018:0009:0018:0009:0018:00<NA><NA><NA><NA><NA><NA><NA><NA>126.82915137.573081
234725020121HS2022012하이넷 상주외답 수소충전소054-532-3600경북 상주시 영남제일로 1339경북 상주시 외답동 7182복합LNG1승용99001111110108:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:00<NA><NA>08:0020:00<NA><NA>128.19302836.418211
344313020121HS2020003충주 연수 수소충전소043-724-2430충청북도 충주시 금봉대로 605 연수LPG충전소충청북도 충주시 연수동 315-6 연수LPG충전소2복합LPG1승용77001111111107:3020:3007:3020:3007:3020:3007:3020:3007:3020:3007:3020:3007:3020:3007:3020:30<NA><NA>127.9450236.98875
454513020121HS2022050하이넷 군산지곡 수소충전소0507-1304-1145전북 군산시 월명로 112전북 군산시 지곡동 2-62복합LPG6승용/버스/트럭99001111110108:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:00<NA><NA>08:0020:00<NA><NA>126.71609435.954126
564413320121HS2022015린데 수소충전소/입장휴게소(서울방향)070-4066-0205충남 천안시 서북구 입장면 연곡길 407충남 천안시 서북구 입장면 가산리 362-12복합주유소,전기1승용99001111111108:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:00<NA><NA>127.19360236.943068
674812720121HS2023009마산자유무역지역 수소충전소055-292-0270경남 창원시 마산회원구 무역로 27경남 창원시 마산회원구 양덕동 975-71단독<NA>1승용94001111111106:0022:0006:0022:0006:0022:0006:0022:0006:0022:0006:0022:0006:0022:0006:0022:00<NA><NA>128.58938235.211573
784311320121HS2023005청주휴게소(서울방향) 수소충전소043-231-3560충북 청주시 흥덕구 옥산면 경부고속도로 318충북 청주시 흥덕구 옥산면 장남리 284-162복합가스, 주유소1승용124001111111108:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:00<NA><NA>127.3476936.717547
893114020121HS2023012울산상개 SK수소충전소052-998-8488울산 남구 산업로 100울산 남구 상개동 502복합주유소, 전기6승용/버스/트럭85001111110<NA><NA>09:0020:0009:0020:0009:0020:0009:0020:0009:0020:0009:0020:00<NA><NA>12:0013:00129.3200135.505914
9103171020121HS2019001신일복합충전소052-225-1500울산 울주군 웅촌면 웅촌로 490울산 울주군 웅촌면 곡천리 1-112복합LPG1승용85001111111107:0018:3007:0018:3007:0018:3007:0018:3007:0018:3007:0018:3007:0018:3007:0018:30<NA><NA>129.21825835.471699
순번충전소_관리번호충전소_명전화번호도로명주소지번주소충전소_유형코드충전소_유형명충전소유형비고충전가능차량코드충전가능차량판매가격이용가능요일월요일_시작월요일_종료화요일_시작화요일_종료수요일_시작수요일_종료목요일_시작목요일_종료금요일_시작금요일_종료토요일_시작토요일_종료일요일_시작일요일_종료공휴일_시작공휴일_종료휴식_시작휴식_종료경도위도
1471484623020121HS2022024하이넷 광양성황 수소충전소061-794-8005전남 광양시 백운로 955-4전남 광양시 성황동 75-32복합LPG6승용/버스/트럭99001011111108:0020:00<NA><NA>08:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:00<NA><NA>127.67714134.947977
1481494686020121HS2022035하이넷 함평천지휴게소(목포방향) 수소충전소061-324-4136전남 함평군 함평읍 서해안고속도로 31-1전남 함평군 함평읍 장교리 산 78-52복합주유소1승용99001111111108:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0012:0013:00126.47856135.068491
1491503014020121HS2022044하이넷 대전중촌 수소충전소042-257-8898대전 중구 대전천서로 767대전 중구 중촌동 413-432복합LPG, 전기5승용/버스99001111111<NA><NA>08:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:00<NA><NA>127.40593236.34807
1501514817020121HS2021007진주 수소충전소(LPG 복합)055-741-1122경상남도 진주시 판문로 192경상남도 진주시 판문동 517-162복합LPG1승용94001111111107:0021:0007:0021:0007:0021:0007:0021:0007:0021:0008:0018:0008:0018:0007:0021:00<NA><NA>128.04005635.183561
1511524311420121HS2020002충북 청주 도원수소충전소043-214-7788충청북도 청주시 청원구 충청대로 771 부3충청북도 청주시 청원구 내수읍 도원리 175-1 부32복합주유소1승용99001111111108:0020:0008:0020:0008:0020:0008:0020:0008:0020:0013:0018:0013:0018:0008:0020:00<NA><NA>127.53382436.711917
1521534311220121HS2023022성일 수소충전소043-266-9643충북 청주시 서원구 남이면 청남로 871충북 청주시 서원구 남이면 부용외천리 468-12복합주유소6승용/버스/트럭99001111111108:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0012:0008:0012:0008:0012:00<NA><NA>127.42740136.53093
1531542635020121HS2022060하이넷 해운대 수소충전소070-4077-5092부산 해운대구 해운대로 1255부산 해운대구 송정동 77-72복합<NA>1승용99001111110109:0019:0009:0019:0009:0019:0009:0019:0009:0019:0009:0019:00<NA><NA>09:0019:00<NA><NA>129.2052635.196728
1541554127320121HS2021008안산 수소e로움 충전소031-492-7047경기도 안산시 단원구 첨단로 660경기도 안산시 단원구 초지동 672-2 안산 수소e로움 충전소1단독<NA>1승용99001111111108:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:0008:0020:00<NA><NA>126.79334437.296128
1551564418020121HS2022065하이넷 대천휴게소(서울방향) 수소충전소070-4196-6575충남 보령시 주교면 서해안고속도로 200충남 보령시 주교면 주교리 897-12복합주유소, LPG, 전기6승용/버스/트럭99001111111108:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0008:0022:0011:0011:30126.55725936.374754
1561574812320121HS2023025(재)창원산업진흥원 창원터널 수소충전소055-262-7716<NA>경남 창원시 성산구 불모산동 463-21단독<NA>1승용94001111111106:0022:0006:0022:0006:0022:0006:0022:0006:0022:0006:0022:0006:0022:0006:0022:00<NA><NA>128.6033235.25242