Overview

Dataset statistics

Number of variables10
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory86.3 B

Variable types

Categorical3
Text4
Numeric2
DateTime1

Dataset

Description성남시내 고압가스 저장소 현황에 대한 데이터로, 상호명,주소,고압가스종류,인허가일자 등의 항목으로 구성되어 있습니다
URLhttps://www.data.go.kr/data/15037039/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일 has constant value ""Constant
인허가일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:30:24.244797
Analysis finished2023-12-12 22:30:25.154343
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
성남시
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 31
100.0%

Length

2023-12-13T07:30:25.217805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:30:25.307846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시 31
100.0%

상호명
Text

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T07:30:25.489131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length10.451613
Min length3

Characters and Unicode

Total characters324
Distinct characters105
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)83.9%

Sample

1st row국군수도병원
2nd row맑은물관리사업소
3rd row분당서울대학교병원
4th row삼영전자
5th row㈜샤니
ValueCountFrequency (%)
한국남동발전㈜ 3
 
6.4%
분당발전본부 3
 
6.4%
수자원공사 2
 
4.3%
성남권관리단 2
 
4.3%
성남충전소 2
 
4.3%
분당gs충전소 1
 
2.1%
궁내동가스충전소 1
 
2.1%
주)소모홀딩스엔테크놀러지 1
 
2.1%
분당충전소 1
 
2.1%
에스케이오케이 1
 
2.1%
Other values (30) 30
63.8%
2023-12-13T07:30:25.840196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 19
 
5.9%
16
 
4.9%
소 14
 
4.3%
충 11
 
3.4%
남 10
 
3.1%
스 10
 
3.1%
원 10
 
3.1%
성 9
 
2.8%
분 8
 
2.5%
당 8
 
2.5%
Other values (95) 209
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 285
88.0%
Space Separator 16
 
4.9%
Open Punctuation 7
 
2.2%
Close Punctuation 7
 
2.2%
Other Symbol 7
 
2.2%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 19
 
6.7%
소 14
 
4.9%
충 11
 
3.9%
남 10
 
3.5%
스 10
 
3.5%
원 10
 
3.5%
성 9
 
3.2%
분 8
 
2.8%
당 8
 
2.8%
주 7
 
2.5%
Other values (89) 179
62.8%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 292
90.1%
Common 30
 
9.3%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 19
 
6.5%
소 14
 
4.8%
충 11
 
3.8%
남 10
 
3.4%
스 10
 
3.4%
원 10
 
3.4%
성 9
 
3.1%
분 8
 
2.7%
당 8
 
2.7%
주 7
 
2.4%
Other values (90) 186
63.7%
Common
ValueCountFrequency (%)
16
53.3%
( 7
23.3%
) 7
23.3%
Latin
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 285
88.0%
ASCII 32
 
9.9%
None 7
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 19
 
6.7%
소 14
 
4.9%
충 11
 
3.9%
남 10
 
3.5%
스 10
 
3.5%
원 10
 
3.5%
성 9
 
3.2%
분 8
 
2.8%
당 8
 
2.8%
주 7
 
2.5%
Other values (89) 179
62.8%
ASCII
ValueCountFrequency (%)
16
50.0%
( 7
21.9%
) 7
21.9%
G 1
 
3.1%
S 1
 
3.1%
None
ValueCountFrequency (%)
㈜ 7
100.0%

소재지지번주소
Text

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T07:30:26.100557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length22.193548
Min length20

Characters and Unicode

Total characters688
Distinct characters50
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

Unique26 ?
Unique (%)83.9%

Sample

1st row경기도 성남시 분당구 율동 222번지
2nd row경기도 성남시 수정구 복정동 515번지
3rd row경기도 성남시 분당구 구미동 300번지
4th row경기도 성남시 중원구 상대원동 146-1번지
5th row경기도 성남시 중원구 상대원동 305번지
ValueCountFrequency (%)
경기도 31
20.0%
성남시 31
20.0%
분당구 13
 
8.4%
수정구 10
 
6.5%
중원구 8
 
5.2%
상대원동 4
 
2.6%
515번지 3
 
1.9%
궁내동 3
 
1.9%
186번지 3
 
1.9%
갈현동 3
 
1.9%
Other values (37) 46
29.7%
2023-12-13T07:30:26.476835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124
18.0%
구 33
 
4.8%
시 33
 
4.8%
경 31
 
4.5%
지 31
 
4.5%
번 31
 
4.5%
동 31
 
4.5%
기 31
 
4.5%
남 31
 
4.5%
성 31
 
4.5%
Other values (40) 281
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 438
63.7%
Space Separator 124
 
18.0%
Decimal Number 113
 
16.4%
Dash Punctuation 13
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 33
 
7.5%
시 33
 
7.5%
경 31
 
7.1%
지 31
 
7.1%
번 31
 
7.1%
동 31
 
7.1%
기 31
 
7.1%
남 31
 
7.1%
성 31
 
7.1%
도 31
 
7.1%
Other values (28) 124
28.3%
Decimal Number
ValueCountFrequency (%)
1 21
18.6%
2 19
16.8%
5 18
15.9%
3 12
10.6%
6 12
10.6%
4 10
8.8%
0 7
 
6.2%
9 6
 
5.3%
8 6
 
5.3%
7 2
 
1.8%
Space Separator
ValueCountFrequency (%)
124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 438
63.7%
Common 250
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 33
 
7.5%
시 33
 
7.5%
경 31
 
7.1%
지 31
 
7.1%
번 31
 
7.1%
동 31
 
7.1%
기 31
 
7.1%
남 31
 
7.1%
성 31
 
7.1%
도 31
 
7.1%
Other values (28) 124
28.3%
Common
ValueCountFrequency (%)
124
49.6%
1 21
 
8.4%
2 19
 
7.6%
5 18
 
7.2%
- 13
 
5.2%
3 12
 
4.8%
6 12
 
4.8%
4 10
 
4.0%
0 7
 
2.8%
9 6
 
2.4%
Other values (2) 8
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 438
63.7%
ASCII 250
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124
49.6%
1 21
 
8.4%
2 19
 
7.6%
5 18
 
7.2%
- 13
 
5.2%
3 12
 
4.8%
6 12
 
4.8%
4 10
 
4.0%
0 7
 
2.8%
9 6
 
2.4%
Other values (2) 8
 
3.2%
Hangul
ValueCountFrequency (%)
구 33
 
7.5%
시 33
 
7.5%
경 31
 
7.1%
지 31
 
7.1%
번 31
 
7.1%
동 31
 
7.1%
기 31
 
7.1%
남 31
 
7.1%
성 31
 
7.1%
도 31
 
7.1%
Other values (28) 124
28.3%

소재지도로명주소
Text

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T07:30:26.703050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length23.322581
Min length18

Characters and Unicode

Total characters723
Distinct characters68
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)83.9%

Sample

1st row경기도 성남시 분당구 새마을로177번길 81
2nd row경기도 성남시 수정구 성남대로1416번길 22
3rd row경기도 성남시 분당구 구미로173번길 82
4th row경기도 성남시 중원구 사기막골로 47
5th row경기도 성남시 중원구 둔촌대로457번길 13
ValueCountFrequency (%)
경기도 31
18.6%
성남시 31
18.6%
분당구 13
 
7.8%
수정구 10
 
6.0%
중원구 8
 
4.8%
대왕판교로 6
 
3.6%
336 3
 
1.8%
경충대로 3
 
1.8%
분당로 3
 
1.8%
성남대로 3
 
1.8%
Other values (51) 56
33.5%
2023-12-13T07:30:27.108318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136
18.8%
성 36
 
5.0%
남 35
 
4.8%
경 34
 
4.7%
기 33
 
4.6%
구 33
 
4.6%
시 32
 
4.4%
로 31
 
4.3%
도 31
 
4.3%
1 22
 
3.0%
Other values (58) 300
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 454
62.8%
Space Separator 136
 
18.8%
Decimal Number 107
 
14.8%
Close Punctuation 13
 
1.8%
Open Punctuation 13
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 36
 
7.9%
남 35
 
7.7%
경 34
 
7.5%
기 33
 
7.3%
구 33
 
7.3%
시 32
 
7.0%
로 31
 
6.8%
도 31
 
6.8%
대 17
 
3.7%
분 16
 
3.5%
Other values (45) 156
34.4%
Decimal Number
ValueCountFrequency (%)
1 22
20.6%
3 15
14.0%
2 15
14.0%
6 10
9.3%
5 10
9.3%
7 10
9.3%
4 7
 
6.5%
0 6
 
5.6%
9 6
 
5.6%
8 6
 
5.6%
Space Separator
ValueCountFrequency (%)
136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 454
62.8%
Common 269
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 36
 
7.9%
남 35
 
7.7%
경 34
 
7.5%
기 33
 
7.3%
구 33
 
7.3%
시 32
 
7.0%
로 31
 
6.8%
도 31
 
6.8%
대 17
 
3.7%
분 16
 
3.5%
Other values (45) 156
34.4%
Common
ValueCountFrequency (%)
136
50.6%
1 22
 
8.2%
3 15
 
5.6%
2 15
 
5.6%
) 13
 
4.8%
( 13
 
4.8%
6 10
 
3.7%
5 10
 
3.7%
7 10
 
3.7%
4 7
 
2.6%
Other values (3) 18
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 454
62.8%
ASCII 269
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
136
50.6%
1 22
 
8.2%
3 15
 
5.6%
2 15
 
5.6%
) 13
 
4.8%
( 13
 
4.8%
6 10
 
3.7%
5 10
 
3.7%
7 10
 
3.7%
4 7
 
2.6%
Other values (3) 18
 
6.7%
Hangul
ValueCountFrequency (%)
성 36
 
7.9%
남 35
 
7.7%
경 34
 
7.5%
기 33
 
7.3%
구 33
 
7.3%
시 32
 
7.0%
로 31
 
6.8%
도 31
 
6.8%
대 17
 
3.7%
분 16
 
3.5%
Other values (45) 156
34.4%

위도
Real number (ℝ)

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.4081
Minimum37.342233
Maximum37.467872
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T07:30:27.242127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.342233
5-th percentile37.353586
Q137.372823
median37.414879
Q337.4354
95-th percentile37.452681
Maximum37.467872
Range0.1256389
Interquartile range (IQR)0.06257695

Descriptive statistics

Standard deviation0.034498646
Coefficient of variation (CV)0.00092222396
Kurtosis-1.028676
Mean37.4081
Median Absolute Deviation (MAD)0.0237179
Skewness-0.34608092
Sum1159.6511
Variance0.0011901566
MonotonicityNot monotonic
2023-12-13T07:30:27.393048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
37.36561 3
 
9.7%
37.4148787 2
 
6.5%
37.3924238 1
 
3.2%
37.417201 1
 
3.2%
37.4218 1
 
3.2%
37.44487 1
 
3.2%
37.41372 1
 
3.2%
37.3698485 1
 
3.2%
37.3757975 1
 
3.2%
37.3551434 1
 
3.2%
Other values (18) 18
58.1%
ValueCountFrequency (%)
37.342233 1
 
3.2%
37.3520288 1
 
3.2%
37.3551434 1
 
3.2%
37.36561 3
9.7%
37.3676669 1
 
3.2%
37.3698485 1
 
3.2%
37.3757975 1
 
3.2%
37.3882052 1
 
3.2%
37.3924238 1
 
3.2%
37.4039996 1
 
3.2%
ValueCountFrequency (%)
37.4678719 1
3.2%
37.4564094 1
3.2%
37.4489522 1
3.2%
37.44487 1
3.2%
37.438968 1
3.2%
37.4385966 1
3.2%
37.4385403 1
3.2%
37.4372137 1
3.2%
37.4335862 1
3.2%
37.4329849 1
3.2%

경도
Real number (ℝ)

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.13463
Minimum127.09991
Maximum127.17582
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T07:30:27.532280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.09991
5-th percentile127.10129
Q1127.10988
median127.1306
Q3127.1554
95-th percentile127.17384
Maximum127.17582
Range0.0759128
Interquartile range (IQR)0.0455195

Descriptive statistics

Standard deviation0.02490698
Coefficient of variation (CV)0.00019591028
Kurtosis-1.2627407
Mean127.13463
Median Absolute Deviation (MAD)0.0218656
Skewness0.095684733
Sum3941.1734
Variance0.00062035767
MonotonicityNot monotonic
2023-12-13T07:30:27.966712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
127.14674 3
 
9.7%
127.1087298 2
 
6.5%
127.1491436 1
 
3.2%
127.1023081 1
 
3.2%
127.1552 1
 
3.2%
127.1389 1
 
3.2%
127.09991 1
 
3.2%
127.1023185 1
 
3.2%
127.1013784 1
 
3.2%
127.1012066 1
 
3.2%
Other values (18) 18
58.1%
ValueCountFrequency (%)
127.09991 1
3.2%
127.1012066 1
3.2%
127.1013784 1
3.2%
127.1021864 1
3.2%
127.1023081 1
3.2%
127.1023185 1
3.2%
127.1087298 2
6.5%
127.1110323 1
3.2%
127.1217835 1
3.2%
127.1244845 1
3.2%
ValueCountFrequency (%)
127.1758228 1
3.2%
127.1751265 1
3.2%
127.1725522 1
3.2%
127.1683401 1
3.2%
127.1665186 1
3.2%
127.1588059 1
3.2%
127.1562157 1
3.2%
127.1556011 1
3.2%
127.1552 1
3.2%
127.1491436 1
3.2%

고압가스 종류
Categorical

Distinct12
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
LPG가스
13 
액화산소
5 
질소
3 
수소혼합
2 
액화이산화탄소
 
1
Other values (7)
7 

Length

Max length9
Median length7
Mean length4.7419355
Min length2

Unique

Unique8 ?
Unique (%)25.8%

Sample

1st row액화산소
2nd row액화이산화탄소
3rd row액화산소,액화질소
4th row액화알곤
5th row질소

Common Values

ValueCountFrequency (%)
LPG가스 13
41.9%
액화산소 5
 
16.1%
질소 3
 
9.7%
수소혼합 2
 
6.5%
액화이산화탄소 1
 
3.2%
액화산소,액화질소 1
 
3.2%
액화알곤 1
 
3.2%
액체이산화탄소 1
 
3.2%
산소 1
 
3.2%
액화질소 1
 
3.2%
Other values (2) 2
 
6.5%

Length

2023-12-13T07:30:28.112744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
lpg가스 13
39.4%
액화산소 5
 
15.2%
질소 5
 
15.2%
수소혼합 2
 
6.1%
액화이산화탄소 1
 
3.0%
액화산소,액화질소 1
 
3.0%
액화알곤 1
 
3.0%
액체이산화탄소 1
 
3.0%
산소 1
 
3.0%
액화질소 1
 
3.0%
Other values (2) 2
 
6.1%

인허가일자
Date

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum1981-07-16 00:00:00
Maximum2020-09-02 00:00:00
2023-12-13T07:30:28.257908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:28.410631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

인허가번호
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T07:30:28.609522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length7.7419355
Min length4

Characters and Unicode

Total characters240
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st row제99-3호
2nd row제10-02-1-05호
3rd row제123호
4th row제00-1호
5th row제10-02-1-02호
ValueCountFrequency (%)
제00-1호 2
 
6.5%
제99-3호 1
 
3.2%
제00-4 1
 
3.2%
제18-02-1-01호 1
 
3.2%
제17-02-1-10호 1
 
3.2%
제17-02-1-05호 1
 
3.2%
제17-02-1-01호 1
 
3.2%
제16-02-1-04호 1
 
3.2%
제11-1 1
 
3.2%
제00-7 1
 
3.2%
Other values (20) 20
64.5%
2023-12-13T07:30:28.964624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 50
20.8%
1 42
17.5%
0 41
17.1%
제 31
12.9%
호 19
 
7.9%
2 18
 
7.5%
4 8
 
3.3%
3 7
 
2.9%
5 6
 
2.5%
8 6
 
2.5%
Other values (3) 12
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 140
58.3%
Dash Punctuation 50
 
20.8%
Other Letter 50
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 42
30.0%
0 41
29.3%
2 18
12.9%
4 8
 
5.7%
3 7
 
5.0%
5 6
 
4.3%
8 6
 
4.3%
7 6
 
4.3%
9 3
 
2.1%
6 3
 
2.1%
Other Letter
ValueCountFrequency (%)
제 31
62.0%
호 19
38.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 190
79.2%
Hangul 50
 
20.8%

Most frequent character per script

Common
ValueCountFrequency (%)
- 50
26.3%
1 42
22.1%
0 41
21.6%
2 18
 
9.5%
4 8
 
4.2%
3 7
 
3.7%
5 6
 
3.2%
8 6
 
3.2%
7 6
 
3.2%
9 3
 
1.6%
Hangul
ValueCountFrequency (%)
제 31
62.0%
호 19
38.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190
79.2%
Hangul 50
 
20.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 50
26.3%
1 42
22.1%
0 41
21.6%
2 18
 
9.5%
4 8
 
4.2%
3 7
 
3.7%
5 6
 
3.2%
8 6
 
3.2%
7 6
 
3.2%
9 3
 
1.6%
Hangul
ValueCountFrequency (%)
제 31
62.0%
호 19
38.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-05-31
31 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-31
2nd row2023-05-31
3rd row2023-05-31
4th row2023-05-31
5th row2023-05-31

Common Values

ValueCountFrequency (%)
2023-05-31 31
100.0%

Length

2023-12-13T07:30:29.117958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:30:29.234725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-31 31
100.0%

Interactions

2023-12-13T07:30:24.737813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:24.601727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:24.817475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:24.665456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:30:29.300114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호명소재지지번주소소재지도로명주소위도경도고압가스 종류인허가일자인허가번호
상호명1.0001.0001.0001.0001.0000.8191.0000.968
소재지지번주소1.0001.0001.0001.0001.0000.8191.0000.968
소재지도로명주소1.0001.0001.0001.0001.0000.8191.0000.968
위도1.0001.0001.0001.0000.8820.6951.0000.977
경도1.0001.0001.0000.8821.0000.6101.0000.984
고압가스 종류0.8190.8190.8190.6950.6101.0001.0000.866
인허가일자1.0001.0001.0001.0001.0001.0001.0001.000
인허가번호0.9680.9680.9680.9770.9840.8661.0001.000
2023-12-13T07:30:29.415194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도고압가스 종류
위도1.0000.4050.342
경도0.4051.0000.267
고압가스 종류0.3420.2671.000

Missing values

2023-12-13T07:30:24.924615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:30:25.066520image/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

시군명상호명소재지지번주소소재지도로명주소위도경도고압가스 종류인허가일자인허가번호데이터기준일
0성남시국군수도병원경기도 성남시 분당구 율동 222번지경기도 성남시 분당구 새마을로177번길 8137.392424127.149144액화산소1999-09-15제99-3호2023-05-31
1성남시맑은물관리사업소경기도 성남시 수정구 복정동 515번지경기도 성남시 수정구 성남대로1416번길 2237.456409127.130595액화이산화탄소2010-10-04제10-02-1-05호2023-05-31
2성남시분당서울대학교병원경기도 성남시 분당구 구미동 300번지경기도 성남시 분당구 구미로173번길 8237.352029127.124484액화산소,액화질소2002-07-18제123호2023-05-31
3성남시삼영전자경기도 성남시 중원구 상대원동 146-1번지경기도 성남시 중원구 사기막골로 4737.438968127.172552액화알곤2000-09-23제00-1호2023-05-31
4성남시㈜샤니경기도 성남시 중원구 상대원동 305번지경기도 성남시 중원구 둔촌대로457번길 1337.433586127.16834질소2010-04-16제10-02-1-02호2023-05-31
5성남시수자원공사 성남권관리단경기도 성남시 수정구 사송동 515번지경기도 성남시 수정구 사송로 9637.414879127.10873액화산소2011-06-16제11-02-1-03호2023-05-31
6성남시수자원공사 성남권관리단경기도 성남시 수정구 사송동 515번지경기도 성남시 수정구 사송로 9637.414879127.10873액체이산화탄소2014-12-02제14-02-1-04호2023-05-31
7성남시양진공업사경기도 성남시 중원구 상대원동 206-6번지경기도 성남시 중원구 사기막골로 11037.43854127.175823산소1989-09-01제13호2023-05-31
8성남시인베니아㈜경기도 성남시 중원구 상대원동 333-11번지경기도 성남시 중원구 갈마치로 21437.432985127.175127질소2011-07-19제11-02-1-05호2023-05-31
9성남시한국전자기술연구원경기도 성남시 분당구 야탑동 68번지경기도 성남시 분당구 새나리로 2537.404127.158806액화질소2004-06-04제04-2-05호2023-05-31
시군명상호명소재지지번주소소재지도로명주소위도경도고압가스 종류인허가일자인허가번호데이터기준일
21성남시(주)소모홀딩스엔테크놀러지 분당충전소경기도 성남시 분당구 구미동 194번지경기도 성남시 분당구 탄천상로 116 (구미동)37.342233127.111032LPG가스2000-04-17제00-32023-05-31
22성남시에스케이오케이 충전소경기도 성남시 분당구 금곡동 344번지경기도 성남시 분당구 대왕판교로 131 (금곡동)37.355143127.101207LPG가스2000-05-20제00-62023-05-31
23성남시(주)허스코 분당GS충전소경기도 성남시 분당구 궁내동 302-8번지경기도 성남시 분당구 대왕판교로 359 (궁내동)37.375797127.101378LPG가스2000-12-16제00-72023-05-31
24성남시길사랑장학사업단㈜ 하이패스센터충전소경기도 성남시 분당구 궁내동 257-2번지경기도 성남시 분당구 대왕판교로 294(궁내동)37.369849127.102318LPG가스2011-10-07제11-12023-05-31
25성남시한국남동발전㈜ 분당발전본부경기도 성남시 분당구 분당동 186번지경기도 성남시 분당구 분당로 33637.36561127.14674질소2016-07-04제16-02-1-04호2023-05-31
26성남시판교창조경제밸리 기업지원허브경기도 성남시 수정구 시흥동 285-2번지경기도 성남시 수정구 대왕판교로 81537.41372127.09991질소, 이산화탄소2017-02-13제17-02-1-01호2023-05-31
27성남시성남시의료원경기도 성남시 수정구 태평동 3309번지경기도 성남시 수정구 수정로171번길 1037.44487127.1389액화산소2017-07-07제17-02-1-05호2023-05-31
28성남시한국남동발전㈜ 분당발전본부경기도 성남시 분당구 분당동 186번지경기도 성남시 분당구 분당로 33637.36561127.14674수소혼합2017-11-15제17-02-1-10호2023-05-31
29성남시한국남동발전㈜ 분당발전본부경기도 성남시 분당구 분당동 186번지경기도 성남시 분당구 분당로 33637.36561127.14674수소혼합2018-01-03제18-02-1-01호2023-05-31
30성남시주식회사 성남수소충전소경기도 성남시 중원구 갈현동 546-9번지경기도 성남시 중원구 경충대로 265937.4218127.1552수소, 질소2020-09-02제20-02-1-07호2023-05-31