Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory71.5 B

Variable types

Text5
Numeric2
Categorical1

Dataset

Description김해시 액화석유가스 충전업소 현황에 대한 데이터로 사업자명,전화번호,지번주소,도로명주소,위도,경도,가스종류 및 저장능력,비고 항목을 제공합니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033415/fileData.do

Alerts

사업자명 has unique valuesUnique
전화번호 has unique valuesUnique
지번주소 has unique valuesUnique
도로명주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:39:10.986603
Analysis finished2023-12-12 07:39:11.827435
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업자명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T16:39:11.991807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length9.125
Min length4

Characters and Unicode

Total characters219
Distinct characters76
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

Unique24 ?
Unique (%)100.0%

Sample

1st row김해LPG
2nd row이원 김해LPG충전소
3rd rowMS에너지㈜
4th row비앤지㈜
5th row김해어방LPG충전소
ValueCountFrequency (%)
김해lpg 1
 
4.0%
럭키lpg충전소 1
 
4.0%
제우스유화공업㈜ 1
 
4.0%
서일산업㈜김해가스 1
 
4.0%
에코lpg충전소김해 1
 
4.0%
구산럭키lpg충전소 1
 
4.0%
동창원ic충전소 1
 
4.0%
삼계lpg충전소 1
 
4.0%
부경에너지㈜알뜰제2충전소 1
 
4.0%
㈜경인석유고속도로진영(상)충전소 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T16:39:12.353430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 19
 
8.7%
충 19
 
8.7%
소 19
 
8.7%
L 8
 
3.7%
P 8
 
3.7%
G 8
 
3.7%
㈜ 7
 
3.2%
김 7
 
3.2%
해 7
 
3.2%
스 6
 
2.7%
Other values (66) 111
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
79.0%
Uppercase Letter 30
 
13.7%
Other Symbol 7
 
3.2%
Close Punctuation 3
 
1.4%
Open Punctuation 3
 
1.4%
Decimal Number 1
 
0.5%
Space Separator 1
 
0.5%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 19
 
11.0%
충 19
 
11.0%
소 19
 
11.0%
김 7
 
4.0%
해 7
 
4.0%
스 6
 
3.5%
가 6
 
3.5%
산 5
 
2.9%
유 4
 
2.3%
지 4
 
2.3%
Other values (53) 77
44.5%
Uppercase Letter
ValueCountFrequency (%)
L 8
26.7%
P 8
26.7%
G 8
26.7%
I 2
 
6.7%
C 2
 
6.7%
S 1
 
3.3%
M 1
 
3.3%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
82.2%
Latin 30
 
13.7%
Common 9
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 19
 
10.6%
충 19
 
10.6%
소 19
 
10.6%
㈜ 7
 
3.9%
김 7
 
3.9%
해 7
 
3.9%
스 6
 
3.3%
가 6
 
3.3%
산 5
 
2.8%
유 4
 
2.2%
Other values (54) 81
45.0%
Latin
ValueCountFrequency (%)
L 8
26.7%
P 8
26.7%
G 8
26.7%
I 2
 
6.7%
C 2
 
6.7%
S 1
 
3.3%
M 1
 
3.3%
Common
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
2 1
 
11.1%
1
 
11.1%
. 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
79.0%
ASCII 39
 
17.8%
None 7
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 19
 
11.0%
충 19
 
11.0%
소 19
 
11.0%
김 7
 
4.0%
해 7
 
4.0%
스 6
 
3.5%
가 6
 
3.5%
산 5
 
2.9%
유 4
 
2.3%
지 4
 
2.3%
Other values (53) 77
44.5%
ASCII
ValueCountFrequency (%)
L 8
20.5%
P 8
20.5%
G 8
20.5%
) 3
 
7.7%
( 3
 
7.7%
I 2
 
5.1%
C 2
 
5.1%
2 1
 
2.6%
S 1
 
2.6%
M 1
 
2.6%
Other values (2) 2
 
5.1%
None
ValueCountFrequency (%)
㈜ 7
100.0%

전화번호
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T16:39:12.563668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique24 ?
Unique (%)100.0%

Sample

1st row055-334-9466
2nd row055-322-2311
3rd row055-345-1117
4th row055-343-1370
5th row055-327-2311
ValueCountFrequency (%)
055-334-9466 1
 
4.2%
055-322-2311 1
 
4.2%
055-314-8182 1
 
4.2%
055-345-2738 1
 
4.2%
055-336-6444 1
 
4.2%
055-336-2321 1
 
4.2%
055-346-0301 1
 
4.2%
055-314-2311 1
 
4.2%
051-333-0036 1
 
4.2%
055-342-0878 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T16:39:12.890772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 55
19.1%
- 48
16.7%
3 46
16.0%
0 41
14.2%
1 24
8.3%
2 19
 
6.6%
4 18
 
6.2%
6 13
 
4.5%
7 9
 
3.1%
8 9
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 55
22.9%
3 46
19.2%
0 41
17.1%
1 24
10.0%
2 19
 
7.9%
4 18
 
7.5%
6 13
 
5.4%
7 9
 
3.8%
8 9
 
3.8%
9 6
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 55
19.1%
- 48
16.7%
3 46
16.0%
0 41
14.2%
1 24
8.3%
2 19
 
6.6%
4 18
 
6.2%
6 13
 
4.5%
7 9
 
3.1%
8 9
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 55
19.1%
- 48
16.7%
3 46
16.0%
0 41
14.2%
1 24
8.3%
2 19
 
6.6%
4 18
 
6.2%
6 13
 
4.5%
7 9
 
3.1%
8 9
 
3.1%

지번주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T16:39:13.116961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length18.958333
Min length16

Characters and Unicode

Total characters455
Distinct characters54
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 안동 260-24
2nd row경상남도 김해시 어방동 1067-2
3rd row경상남도 김해시 한림면 가산리 347-5
4th row경상남도 김해시 한림면 신천리 285-3
5th row경상남도 김해시 어방동 1062-14
ValueCountFrequency (%)
경상남도 24
22.9%
김해시 24
22.9%
진영읍 6
 
5.7%
풍유동 4
 
3.8%
한림면 3
 
2.9%
어방동 2
 
1.9%
신천리 2
 
1.9%
부곡동 2
 
1.9%
595 1
 
1.0%
우동리 1
 
1.0%
Other values (36) 36
34.3%
2023-12-12T16:39:13.454226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
17.8%
경 24
 
5.3%
남 24
 
5.3%
도 24
 
5.3%
김 24
 
5.3%
해 24
 
5.3%
시 24
 
5.3%
상 24
 
5.3%
1 17
 
3.7%
동 17
 
3.7%
Other values (44) 172
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
58.5%
Decimal Number 92
 
20.2%
Space Separator 81
 
17.8%
Dash Punctuation 16
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 24
 
9.0%
남 24
 
9.0%
도 24
 
9.0%
김 24
 
9.0%
해 24
 
9.0%
시 24
 
9.0%
상 24
 
9.0%
동 17
 
6.4%
리 9
 
3.4%
진 7
 
2.6%
Other values (32) 65
24.4%
Decimal Number
ValueCountFrequency (%)
1 17
18.5%
2 17
18.5%
3 14
15.2%
7 9
9.8%
9 8
8.7%
0 8
8.7%
5 7
7.6%
4 5
 
5.4%
6 4
 
4.3%
8 3
 
3.3%
Space Separator
ValueCountFrequency (%)
81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
58.5%
Common 189
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 24
 
9.0%
남 24
 
9.0%
도 24
 
9.0%
김 24
 
9.0%
해 24
 
9.0%
시 24
 
9.0%
상 24
 
9.0%
동 17
 
6.4%
리 9
 
3.4%
진 7
 
2.6%
Other values (32) 65
24.4%
Common
ValueCountFrequency (%)
81
42.9%
1 17
 
9.0%
2 17
 
9.0%
- 16
 
8.5%
3 14
 
7.4%
7 9
 
4.8%
9 8
 
4.2%
0 8
 
4.2%
5 7
 
3.7%
4 5
 
2.6%
Other values (2) 7
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
58.5%
ASCII 189
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
42.9%
1 17
 
9.0%
2 17
 
9.0%
- 16
 
8.5%
3 14
 
7.4%
7 9
 
4.8%
9 8
 
4.2%
0 8
 
4.2%
5 7
 
3.7%
4 5
 
2.6%
Other values (2) 7
 
3.7%
Hangul
ValueCountFrequency (%)
경 24
 
9.0%
남 24
 
9.0%
도 24
 
9.0%
김 24
 
9.0%
해 24
 
9.0%
시 24
 
9.0%
상 24
 
9.0%
동 17
 
6.4%
리 9
 
3.4%
진 7
 
2.6%
Other values (32) 65
24.4%

도로명주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T16:39:13.660593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length23
Mean length20.708333
Min length15

Characters and Unicode

Total characters497
Distinct characters60
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

Unique24 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 김해대로 2625
2nd row경상남도 김해시 김해대로2567번길 38-14
3rd row경상남도 김해시 한림면 한림로 1027
4th row경상남도 김해시 한림면 김해대로 1565
5th row경상남도 김해시 분성로 555
ValueCountFrequency (%)
경상남도 24
22.0%
김해시 24
22.0%
진영읍 6
 
5.5%
금관대로 5
 
4.6%
김해대로 4
 
3.7%
한림면 3
 
2.8%
장유로 2
 
1.8%
1604 1
 
0.9%
3 1
 
0.9%
관동신안가스충전소 1
 
0.9%
Other values (38) 38
34.9%
2023-12-12T16:39:14.033499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
17.5%
김 29
 
5.8%
해 29
 
5.8%
경 24
 
4.8%
상 24
 
4.8%
남 24
 
4.8%
도 24
 
4.8%
시 24
 
4.8%
로 24
 
4.8%
1 21
 
4.2%
Other values (50) 187
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
62.6%
Space Separator 87
 
17.5%
Decimal Number 86
 
17.3%
Close Punctuation 5
 
1.0%
Open Punctuation 5
 
1.0%
Dash Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 29
 
9.3%
해 29
 
9.3%
경 24
 
7.7%
상 24
 
7.7%
남 24
 
7.7%
도 24
 
7.7%
시 24
 
7.7%
로 24
 
7.7%
대 12
 
3.9%
진 7
 
2.3%
Other values (36) 90
28.9%
Decimal Number
ValueCountFrequency (%)
1 21
24.4%
6 10
11.6%
2 9
10.5%
5 9
10.5%
4 9
10.5%
3 7
 
8.1%
9 7
 
8.1%
8 6
 
7.0%
0 5
 
5.8%
7 3
 
3.5%
Space Separator
ValueCountFrequency (%)
87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
62.6%
Common 186
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 29
 
9.3%
해 29
 
9.3%
경 24
 
7.7%
상 24
 
7.7%
남 24
 
7.7%
도 24
 
7.7%
시 24
 
7.7%
로 24
 
7.7%
대 12
 
3.9%
진 7
 
2.3%
Other values (36) 90
28.9%
Common
ValueCountFrequency (%)
87
46.8%
1 21
 
11.3%
6 10
 
5.4%
2 9
 
4.8%
5 9
 
4.8%
4 9
 
4.8%
3 7
 
3.8%
9 7
 
3.8%
8 6
 
3.2%
0 5
 
2.7%
Other values (4) 16
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
62.6%
ASCII 186
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
46.8%
1 21
 
11.3%
6 10
 
5.4%
2 9
 
4.8%
5 9
 
4.8%
4 9
 
4.8%
3 7
 
3.8%
9 7
 
3.8%
8 6
 
3.2%
0 5
 
2.7%
Other values (4) 16
 
8.6%
Hangul
ValueCountFrequency (%)
김 29
 
9.3%
해 29
 
9.3%
경 24
 
7.7%
상 24
 
7.7%
남 24
 
7.7%
도 24
 
7.7%
시 24
 
7.7%
로 24
 
7.7%
대 12
 
3.9%
진 7
 
2.3%
Other values (36) 90
28.9%

위도
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.250443
Minimum35.177158
Maximum35.328591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T16:39:14.174356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.177158
5-th percentile35.183312
Q135.216193
median35.233966
Q335.286134
95-th percentile35.315828
Maximum35.328591
Range0.15143372
Interquartile range (IQR)0.069940838

Descriptive statistics

Standard deviation0.04494337
Coefficient of variation (CV)0.0012749732
Kurtosis-1.1430848
Mean35.250443
Median Absolute Deviation (MAD)0.032192677
Skewness0.2205605
Sum846.01063
Variance0.0020199065
MonotonicityNot monotonic
2023-12-12T16:39:14.304990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
35.2292814106 1
 
4.2%
35.1785706313 1
 
4.2%
35.3098098301 1
 
4.2%
35.2147681223 1
 
4.2%
35.3154591216 1
 
4.2%
35.1771577522 1
 
4.2%
35.2474006117 1
 
4.2%
35.2994023062 1
 
4.2%
35.2745682797 1
 
4.2%
35.2834209828 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
35.1771577522 1
4.2%
35.1785706313 1
4.2%
35.2101829266 1
4.2%
35.2112415177 1
4.2%
35.2147681223 1
4.2%
35.2149332588 1
4.2%
35.2166129613 1
4.2%
35.2171104104 1
4.2%
35.2216247797 1
4.2%
35.2273803163 1
4.2%
ValueCountFrequency (%)
35.3285914701 1
4.2%
35.3158928382 1
4.2%
35.3154591216 1
4.2%
35.3098098301 1
4.2%
35.2994023062 1
4.2%
35.2942725471 1
4.2%
35.2834209828 1
4.2%
35.2795872388 1
4.2%
35.2754327341 1
4.2%
35.2745682797 1
4.2%

경도
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.81563
Minimum128.70886
Maximum128.91364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T16:39:14.428426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70886
5-th percentile128.71682
Q1128.7606
median128.83505
Q3128.84809
95-th percentile128.90796
Maximum128.91364
Range0.20477706
Interquartile range (IQR)0.087484774

Descriptive statistics

Standard deviation0.061550521
Coefficient of variation (CV)0.00047781871
Kurtosis-0.96536097
Mean128.81563
Median Absolute Deviation (MAD)0.041590225
Skewness-0.2018016
Sum3091.5752
Variance0.0037884666
MonotonicityNot monotonic
2023-12-12T16:39:14.550086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
128.9136354714 1
 
4.2%
128.7858330581 1
 
4.2%
128.7408567666 1
 
4.2%
128.8154081407 1
 
4.2%
128.7483572142 1
 
4.2%
128.8276816834 1
 
4.2%
128.8772696176 1
 
4.2%
128.7088584148 1
 
4.2%
128.8459648474 1
 
4.2%
128.8665743983 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
128.7088584148 1
4.2%
128.7147666776 1
4.2%
128.728460282 1
4.2%
128.7408567666 1
4.2%
128.7483572142 1
4.2%
128.7542100661 1
4.2%
128.762735211 1
4.2%
128.7858330581 1
4.2%
128.7940891679 1
4.2%
128.79760161 1
4.2%
ValueCountFrequency (%)
128.9136354714 1
4.2%
128.908213043 1
4.2%
128.9065557639 1
4.2%
128.8772696176 1
4.2%
128.8665743983 1
4.2%
128.8492355512 1
4.2%
128.847706415 1
4.2%
128.847245813 1
4.2%
128.8463806283 1
4.2%
128.8459648474 1
4.2%

가스종류 및 저장능력
Text

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T16:39:14.700028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length11.291667
Min length6

Characters and Unicode

Total characters271
Distinct characters22
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)41.7%

Sample

1st row프로판 20톤, 부탄 20톤
2nd row프로판 150톤(50톤X3기), 부탄 67톤(57톤X1기)(10톤X1기)
3rd row프로판 100톤(50톤X2기), 부탄 20톤
4th row부탄 20톤
5th row부탄 21톤
ValueCountFrequency (%)
부탄 23
41.1%
19.9톤 7
 
12.5%
20톤 6
 
10.7%
프로판 5
 
8.9%
29.99톤 4
 
7.1%
150톤(50톤x3기 1
 
1.8%
67톤(57톤x1기)(10톤x1기 1
 
1.8%
100톤(50톤x2기 1
 
1.8%
21톤 1
 
1.8%
20.12톤 1
 
1.8%
Other values (6) 6
 
10.7%
2023-12-12T16:39:15.044297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 34
12.5%
32
11.8%
톤 32
11.8%
부 23
8.5%
탄 23
8.5%
2 19
 
7.0%
0 19
 
7.0%
. 17
 
6.3%
1 15
 
5.5%
기 7
 
2.6%
Other values (12) 50
18.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103
38.0%
Other Letter 100
36.9%
Space Separator 32
 
11.8%
Other Punctuation 21
 
7.7%
Uppercase Letter 7
 
2.6%
Open Punctuation 4
 
1.5%
Close Punctuation 4
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 34
33.0%
2 19
18.4%
0 19
18.4%
1 15
14.6%
5 6
 
5.8%
3 5
 
4.9%
7 2
 
1.9%
4 2
 
1.9%
6 1
 
1.0%
Other Letter
ValueCountFrequency (%)
톤 32
32.0%
부 23
23.0%
탄 23
23.0%
기 7
 
7.0%
판 5
 
5.0%
로 5
 
5.0%
프 5
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 17
81.0%
, 4
 
19.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 164
60.5%
Hangul 100
36.9%
Latin 7
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
9 34
20.7%
32
19.5%
2 19
11.6%
0 19
11.6%
. 17
10.4%
1 15
9.1%
5 6
 
3.7%
3 5
 
3.0%
( 4
 
2.4%
, 4
 
2.4%
Other values (4) 9
 
5.5%
Hangul
ValueCountFrequency (%)
톤 32
32.0%
부 23
23.0%
탄 23
23.0%
기 7
 
7.0%
판 5
 
5.0%
로 5
 
5.0%
프 5
 
5.0%
Latin
ValueCountFrequency (%)
X 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171
63.1%
Hangul 100
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 34
19.9%
32
18.7%
2 19
11.1%
0 19
11.1%
. 17
9.9%
1 15
8.8%
X 7
 
4.1%
5 6
 
3.5%
3 5
 
2.9%
( 4
 
2.3%
Other values (5) 13
 
7.6%
Hangul
ValueCountFrequency (%)
톤 32
32.0%
부 23
23.0%
탄 23
23.0%
기 7
 
7.0%
판 5
 
5.0%
로 5
 
5.0%
프 5
 
5.0%

비고
Categorical

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
자동차
17 
자동차+용기
5 
용기/탱크
 
1
용기/가스난방기용기/자동차에고정된 탱크
 
1

Length

Max length21
Median length3
Mean length4.4583333
Min length3

Unique

Unique2 ?
Unique (%)8.3%

Sample

1st row자동차+용기
2nd row자동차+용기
3rd row자동차+용기
4th row자동차
5th row자동차

Common Values

ValueCountFrequency (%)
자동차 17
70.8%
자동차+용기 5
 
20.8%
용기/탱크 1
 
4.2%
용기/가스난방기용기/자동차에고정된 탱크 1
 
4.2%

Length

2023-12-12T16:39:15.194650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:39:15.307825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차 17
68.0%
자동차+용기 5
 
20.0%
용기/탱크 1
 
4.0%
용기/가스난방기용기/자동차에고정된 1
 
4.0%
탱크 1
 
4.0%

Interactions

2023-12-12T16:39:11.452108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:39:11.297565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:39:11.542118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:39:11.380533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:39:15.379701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업자명전화번호지번주소도로명주소위도경도가스종류 및 저장능력비고
사업자명1.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
위도1.0001.0001.0001.0001.0000.8400.6980.000
경도1.0001.0001.0001.0000.8401.0000.8480.698
가스종류 및 저장능력1.0001.0001.0001.0000.6980.8481.0000.942
비고1.0001.0001.0001.0000.0000.6980.9421.000
2023-12-12T16:39:15.482728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도비고
위도1.000-0.3670.000
경도-0.3671.0000.422
비고0.0000.4221.000

Missing values

2023-12-12T16:39:11.642005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:39:11.764674image/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

사업자명전화번호지번주소도로명주소위도경도가스종류 및 저장능력비고
0김해LPG055-334-9466경상남도 김해시 안동 260-24경상남도 김해시 김해대로 262535.229281128.913635프로판 20톤, 부탄 20톤자동차+용기
1이원 김해LPG충전소055-322-2311경상남도 김해시 어방동 1067-2경상남도 김해시 김해대로2567번길 38-1435.231919128.908213프로판 150톤(50톤X3기), 부탄 67톤(57톤X1기)(10톤X1기)자동차+용기
2MS에너지㈜055-345-1117경상남도 김해시 한림면 가산리 347-5경상남도 김해시 한림면 한림로 102735.328591128.75421프로판 100톤(50톤X2기), 부탄 20톤자동차+용기
3비앤지㈜055-343-1370경상남도 김해시 한림면 신천리 285-3경상남도 김해시 한림면 김해대로 156535.275433128.842413부탄 20톤자동차
4김해어방LPG충전소055-327-2311경상남도 김해시 어방동 1062-14경상남도 김해시 분성로 55535.236013128.906556부탄 21톤자동차
5진영가스충전소055-342-0056경상남도 김해시 진영읍 진영리 1035경상남도 김해시 진영읍 진산대로 10835.315893128.72846부탄 20.12톤자동차
6태영가스충전소055-345-6345경상남도 김해시 진영읍 내룡리 11경상남도 김해시 진영읍 서부로 1835.294273128.762735부탄 19.9톤자동차+용기
7김해개인택시복지충전소055-333-9689경상남도 김해시 외동 1107-2경상남도 김해시 금관대로 111235.22738128.849236부탄 19.9톤자동차
8장유LPG충전소055-314-1003경상남도 김해시 부곡동 192경상남도 김해시 장유로 6135.214933128.797602부탄 19.9톤자동차+용기
9칠산충전소055-321-0070경상남도 김해시 풍유동 713-9경상남도 김해시 금관대로 916 (풍유동)35.210183128.845187부탄 19.9톤자동차
사업자명전화번호지번주소도로명주소위도경도가스종류 및 저장능력비고
14가온충전소055-335-0518경상남도 김해시 풍유동 224-1경상남도 김해시 금관대로 99435.21711128.847246부탄 20톤자동차
15㈜경인석유고속도로진영(상)충전소055-342-0878경상남도 김해시 진영읍 우동리 300-3경상남도 김해시 진영읍 하계로96번길 44-4935.279587128.714767부탄 20톤자동차
16부경에너지㈜알뜰제2충전소051-333-0036경상남도 김해시 삼계동 923-2경상남도 김해시 생림대로 16235.283421128.866574부탄 29.9톤자동차
17삼계LPG충전소055-314-2311경상남도 김해시 한림면 신천리 173-4경상남도 김해시 한림면 김해대로 160435.274568128.845965부탄 29.99톤자동차
18동창원IC충전소055-346-0301경상남도 김해시 진영읍 좌곤리 595경상남도 김해시 진영읍 김해대로 13335.299402128.708858부탄 29.99톤자동차
19구산럭키LPG충전소055-336-2321경상남도 김해시 구산동 352경상남도 김해시 가야로 353 (구산동)35.247401128.87727부탄 29.99톤자동차
20에코LPG충전소김해055-336-6444경상남도 김해시 응달동 282-1경상남도 김해시 장유로 58135.177158128.827682부탄 29.99톤자동차
21서일산업㈜김해가스055-345-2738경상남도 김해시 진영읍 본산리 303-9경상남도 김해시 진영읍 본산로212번길 835.315459128.748357프로판 50.044톤X2기용기/탱크
22제우스유화공업㈜055-314-8182경상남도 김해시 유하동 712경상남도 김해시 유하로 131(유하동)35.214768128.815408프로판 50.003톤X2기, 부탄 29.993톤X1기용기/가스난방기용기/자동차에고정된 탱크
23구암충전소055-346-1739경상남도 김해시 진영읍 여래리 977경상남도 김해시 진영읍 본산로 6035.30981128.740857부탄 29.993톤자동차