Overview

Dataset statistics

Number of variables9
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory78.7 B

Variable types

Text5
Numeric2
DateTime2

Dataset

Description고압가스 저장 상호명, 고압가스종류, 소재지 주소 정보 등 기준에 따라 분류한 경기도 파주시 내 고압가스 저장탱크 현황입니다.
Author경기도 파주시
URLhttps://www.data.go.kr/data/15037602/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 04:33:05.528882
Analysis finished2023-12-12 04:33:06.598748
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T13:33:06.761365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length10.321429
Min length3

Characters and Unicode

Total characters289
Distinct characters96
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

Unique28 ?
Unique (%)100.0%

Sample

1st row파주시 축분혼합 공공처리시설
2nd row엘지디스플레이(P7)
3rd row에이에스이코리아㈜
4th row엘지디스플레이(P8)
5th row엘지디스플레이(P8 YARD)
ValueCountFrequency (%)
엘지디스플레이(p8 3
 
7.9%
yard 3
 
7.9%
엘지디스플레이(p9 2
 
5.3%
한국수자원공사 2
 
5.3%
파주시 1
 
2.6%
파주공업정수장 1
 
2.6%
㈜동아나이스메탈 1
 
2.6%
갈릴리농원수산b 1
 
2.6%
전기초자코리아㈜ 1
 
2.6%
운정환경관리센타 1
 
2.6%
Other values (22) 22
57.9%
2023-12-12T13:33:07.119812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 15
 
5.2%
㈜ 14
 
4.8%
스 14
 
4.8%
이 13
 
4.5%
엘 11
 
3.8%
10
 
3.5%
레 10
 
3.5%
플 9
 
3.1%
디 9
 
3.1%
) 8
 
2.8%
Other values (86) 176
60.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 208
72.0%
Uppercase Letter 29
 
10.0%
Other Symbol 14
 
4.8%
Decimal Number 11
 
3.8%
Space Separator 10
 
3.5%
Close Punctuation 8
 
2.8%
Open Punctuation 8
 
2.8%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 15
 
7.2%
스 14
 
6.7%
이 13
 
6.2%
엘 11
 
5.3%
레 10
 
4.8%
플 9
 
4.3%
디 9
 
4.3%
수 6
 
2.9%
파 6
 
2.9%
주 6
 
2.9%
Other values (68) 109
52.4%
Uppercase Letter
ValueCountFrequency (%)
P 8
27.6%
A 5
17.2%
D 4
13.8%
R 4
13.8%
Y 3
 
10.3%
B 3
 
10.3%
F 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
8 3
27.3%
9 3
27.3%
1 2
18.2%
2 1
 
9.1%
7 1
 
9.1%
0 1
 
9.1%
Other Symbol
ValueCountFrequency (%)
㈜ 14
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
76.8%
Common 38
 
13.1%
Latin 29
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 15
 
6.8%
㈜ 14
 
6.3%
스 14
 
6.3%
이 13
 
5.9%
엘 11
 
5.0%
레 10
 
4.5%
플 9
 
4.1%
디 9
 
4.1%
수 6
 
2.7%
파 6
 
2.7%
Other values (69) 115
51.8%
Common
ValueCountFrequency (%)
10
26.3%
) 8
21.1%
( 8
21.1%
8 3
 
7.9%
9 3
 
7.9%
1 2
 
5.3%
2 1
 
2.6%
& 1
 
2.6%
7 1
 
2.6%
0 1
 
2.6%
Latin
ValueCountFrequency (%)
P 8
27.6%
A 5
17.2%
D 4
13.8%
R 4
13.8%
Y 3
 
10.3%
B 3
 
10.3%
F 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 208
72.0%
ASCII 67
 
23.2%
None 14
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 15
 
7.2%
스 14
 
6.7%
이 13
 
6.2%
엘 11
 
5.3%
레 10
 
4.8%
플 9
 
4.3%
디 9
 
4.3%
수 6
 
2.9%
파 6
 
2.9%
주 6
 
2.9%
Other values (68) 109
52.4%
None
ValueCountFrequency (%)
㈜ 14
100.0%
ASCII
ValueCountFrequency (%)
10
14.9%
) 8
11.9%
P 8
11.9%
( 8
11.9%
A 5
7.5%
D 4
 
6.0%
R 4
 
6.0%
8 3
 
4.5%
Y 3
 
4.5%
B 3
 
4.5%
Other values (7) 11
16.4%

소재지지번주소
Text

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T13:33:07.323783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length15.785714
Min length11

Characters and Unicode

Total characters442
Distinct characters51
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

Unique17 ?
Unique (%)60.7%

Sample

1st row파주시 파주읍 봉암리 1039-4
2nd row파주시 월롱면 덕은리 1007
3rd row파주시 문발동 494
4th row파주시 월롱면 덕은리 1007
5th row파주시 월롱면 덕은리 1007
ValueCountFrequency (%)
파주시 28
25.7%
월롱면 11
 
10.1%
덕은리 9
 
8.3%
1007 9
 
8.3%
문산읍 5
 
4.6%
파주읍 4
 
3.7%
봉암리 4
 
3.7%
선유리 2
 
1.8%
탄현면 2
 
1.8%
광탄면 2
 
1.8%
Other values (31) 33
30.3%
2023-12-12T13:33:07.667443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
18.6%
파 32
 
7.2%
주 32
 
7.2%
시 28
 
6.3%
리 26
 
5.9%
0 21
 
4.8%
1 17
 
3.8%
면 15
 
3.4%
4 14
 
3.2%
7 13
 
2.9%
Other values (41) 162
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 244
55.2%
Decimal Number 107
24.2%
Space Separator 82
 
18.6%
Dash Punctuation 9
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 32
13.1%
주 32
13.1%
시 28
11.5%
리 26
10.7%
면 15
 
6.1%
롱 11
 
4.5%
월 11
 
4.5%
읍 10
 
4.1%
덕 9
 
3.7%
은 9
 
3.7%
Other values (29) 61
25.0%
Decimal Number
ValueCountFrequency (%)
0 21
19.6%
1 17
15.9%
4 14
13.1%
7 13
12.1%
3 12
11.2%
8 9
8.4%
5 7
 
6.5%
2 6
 
5.6%
6 5
 
4.7%
9 3
 
2.8%
Space Separator
ValueCountFrequency (%)
82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 244
55.2%
Common 198
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 32
13.1%
주 32
13.1%
시 28
11.5%
리 26
10.7%
면 15
 
6.1%
롱 11
 
4.5%
월 11
 
4.5%
읍 10
 
4.1%
덕 9
 
3.7%
은 9
 
3.7%
Other values (29) 61
25.0%
Common
ValueCountFrequency (%)
82
41.4%
0 21
 
10.6%
1 17
 
8.6%
4 14
 
7.1%
7 13
 
6.6%
3 12
 
6.1%
- 9
 
4.5%
8 9
 
4.5%
5 7
 
3.5%
2 6
 
3.0%
Other values (2) 8
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 244
55.2%
ASCII 198
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
41.4%
0 21
 
10.6%
1 17
 
8.6%
4 14
 
7.1%
7 13
 
6.6%
3 12
 
6.1%
- 9
 
4.5%
8 9
 
4.5%
5 7
 
3.5%
2 6
 
3.0%
Other values (2) 8
 
4.0%
Hangul
ValueCountFrequency (%)
파 32
13.1%
주 32
13.1%
시 28
11.5%
리 26
10.7%
면 15
 
6.1%
롱 11
 
4.5%
월 11
 
4.5%
읍 10
 
4.1%
덕 9
 
3.7%
은 9
 
3.7%
Other values (29) 61
25.0%

소재지도로명주소
Text

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T13:33:07.911488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length16.107143
Min length11

Characters and Unicode

Total characters451
Distinct characters65
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

Unique17 ?
Unique (%)60.7%

Sample

1st row파주시 파주읍 통일로 1089-100
2nd row파주시 월롱면 엘지로 245
3rd row파주시 산업단지길 76
4th row파주시 월롱면 엘지로 245
5th row파주시 월롱면 엘지로 245
ValueCountFrequency (%)
파주시 28
25.5%
월롱면 14
12.7%
엘지로 9
 
8.2%
245 9
 
8.2%
휴암로 4
 
3.6%
문산읍 4
 
3.6%
탄현면 2
 
1.8%
파주읍 2
 
1.8%
130 2
 
1.8%
광탄면 2
 
1.8%
Other values (33) 34
30.9%
2023-12-12T13:33:08.294179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
18.2%
파 30
 
6.7%
주 30
 
6.7%
시 28
 
6.2%
로 23
 
5.1%
4 20
 
4.4%
면 18
 
4.0%
2 16
 
3.5%
3 16
 
3.5%
월 14
 
3.1%
Other values (55) 174
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 253
56.1%
Decimal Number 107
23.7%
Space Separator 82
 
18.2%
Dash Punctuation 9
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 30
11.9%
주 30
11.9%
시 28
 
11.1%
로 23
 
9.1%
면 18
 
7.1%
월 14
 
5.5%
롱 14
 
5.5%
지 10
 
4.0%
엘 9
 
3.6%
읍 7
 
2.8%
Other values (43) 70
27.7%
Decimal Number
ValueCountFrequency (%)
4 20
18.7%
2 16
15.0%
3 16
15.0%
5 13
12.1%
1 12
11.2%
0 11
10.3%
7 7
 
6.5%
6 5
 
4.7%
8 5
 
4.7%
9 2
 
1.9%
Space Separator
ValueCountFrequency (%)
82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 253
56.1%
Common 198
43.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 30
11.9%
주 30
11.9%
시 28
 
11.1%
로 23
 
9.1%
면 18
 
7.1%
월 14
 
5.5%
롱 14
 
5.5%
지 10
 
4.0%
엘 9
 
3.6%
읍 7
 
2.8%
Other values (43) 70
27.7%
Common
ValueCountFrequency (%)
82
41.4%
4 20
 
10.1%
2 16
 
8.1%
3 16
 
8.1%
5 13
 
6.6%
1 12
 
6.1%
0 11
 
5.6%
- 9
 
4.5%
7 7
 
3.5%
6 5
 
2.5%
Other values (2) 7
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 253
56.1%
ASCII 198
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
41.4%
4 20
 
10.1%
2 16
 
8.1%
3 16
 
8.1%
5 13
 
6.6%
1 12
 
6.1%
0 11
 
5.6%
- 9
 
4.5%
7 7
 
3.5%
6 5
 
2.5%
Other values (2) 7
 
3.5%
Hangul
ValueCountFrequency (%)
파 30
11.9%
주 30
11.9%
시 28
 
11.1%
로 23
 
9.1%
면 18
 
7.1%
월 14
 
5.5%
롱 14
 
5.5%
지 10
 
4.0%
엘 9
 
3.6%
읍 7
 
2.8%
Other values (43) 70
27.7%

위도
Real number (ℝ)

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.808453
Minimum37.727818
Maximum37.877377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T13:33:08.470346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.727818
5-th percentile37.737214
Q137.786831
median37.81117
Q337.830025
95-th percentile37.86775
Maximum37.877377
Range0.14955905
Interquartile range (IQR)0.04319407

Descriptive statistics

Standard deviation0.038842094
Coefficient of variation (CV)0.0010273389
Kurtosis-0.079040545
Mean37.808453
Median Absolute Deviation (MAD)0.020992435
Skewness-0.39285105
Sum1058.6367
Variance0.0015087083
MonotonicityNot monotonic
2023-12-12T13:33:08.610134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
37.81117033 9
32.1%
37.8300247 2
 
7.1%
37.80588853 1
 
3.6%
37.85934216 1
 
3.6%
37.82209021 1
 
3.6%
37.73714336 1
 
3.6%
37.86557263 1
 
3.6%
37.82934935 1
 
3.6%
37.78381677 1
 
3.6%
37.86892187 1
 
3.6%
Other values (9) 9
32.1%
ValueCountFrequency (%)
37.72781812 1
 
3.6%
37.73714336 1
 
3.6%
37.73734407 1
 
3.6%
37.75488198 1
 
3.6%
37.76728204 1
 
3.6%
37.77741791 1
 
3.6%
37.78381677 1
 
3.6%
37.78783525 1
 
3.6%
37.80588853 1
 
3.6%
37.81117033 9
32.1%
ValueCountFrequency (%)
37.87737717 1
 
3.6%
37.86892187 1
 
3.6%
37.86557263 1
 
3.6%
37.85934216 1
 
3.6%
37.83972034 1
 
3.6%
37.83430083 1
 
3.6%
37.8300247 2
 
7.1%
37.82934935 1
 
3.6%
37.82209021 1
 
3.6%
37.81117033 9
32.1%

경도
Real number (ℝ)

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.77795
Minimum126.7071
Maximum126.8489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T13:33:08.770609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.7071
5-th percentile126.71149
Q1126.76696
median126.77859
Q3126.78737
95-th percentile126.83934
Maximum126.8489
Range0.1418008
Interquartile range (IQR)0.020414425

Descriptive statistics

Standard deviation0.033056405
Coefficient of variation (CV)0.00026074253
Kurtosis1.1757303
Mean126.77795
Median Absolute Deviation (MAD)0.0116342
Skewness-0.10280072
Sum3549.7827
Variance0.0010927259
MonotonicityNot monotonic
2023-12-12T13:33:08.928636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
126.766959 9
32.1%
126.7839916 2
 
7.1%
126.7884979 1
 
3.6%
126.8086365 1
 
3.6%
126.799251 1
 
3.6%
126.7676987 1
 
3.6%
126.7808966 1
 
3.6%
126.713563 1
 
3.6%
126.8444284 1
 
3.6%
126.7815348 1
 
3.6%
Other values (9) 9
32.1%
ValueCountFrequency (%)
126.7070955 1
 
3.6%
126.7103737 1
 
3.6%
126.713563 1
 
3.6%
126.766959 9
32.1%
126.7676987 1
 
3.6%
126.7775484 1
 
3.6%
126.779638 1
 
3.6%
126.7808966 1
 
3.6%
126.7815348 1
 
3.6%
126.7823443 1
 
3.6%
ValueCountFrequency (%)
126.8488963 1
3.6%
126.8444284 1
3.6%
126.8299021 1
3.6%
126.8086365 1
3.6%
126.8048113 1
3.6%
126.799251 1
3.6%
126.7884979 1
3.6%
126.7869986 1
3.6%
126.7839916 2
7.1%
126.7823443 1
3.6%

고압가스 종류
Text

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T13:33:09.139676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length5.5357143
Min length2

Characters and Unicode

Total characters155
Distinct characters29
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

Unique14 ?
Unique (%)50.0%

Sample

1st row산소
2nd row산소, 질소 등7여종
3rd row수소
4th row산소, 아르곤 등6종
5th row산소, 질소 등10여종
ValueCountFrequency (%)
산소 14
32.6%
질소 7
16.3%
아르곤 6
14.0%
이산화탄소 3
 
7.0%
암모니아 2
 
4.7%
수소 2
 
4.7%
액화질소 1
 
2.3%
액화가스 1
 
2.3%
압축가스 1
 
2.3%
수소,이산화탄소 1
 
2.3%
Other values (5) 5
 
11.6%
2023-12-12T13:33:09.538789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 31
20.0%
산 18
11.6%
15
 
9.7%
, 14
 
9.0%
질 9
 
5.8%
아 8
 
5.2%
르 6
 
3.9%
곤 6
 
3.9%
화 6
 
3.9%
탄 4
 
2.6%
Other values (19) 38
24.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
78.7%
Space Separator 15
 
9.7%
Other Punctuation 14
 
9.0%
Decimal Number 4
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 31
25.4%
산 18
14.8%
질 9
 
7.4%
아 8
 
6.6%
르 6
 
4.9%
곤 6
 
4.9%
화 6
 
4.9%
탄 4
 
3.3%
이 4
 
3.3%
수 4
 
3.3%
Other values (13) 26
21.3%
Decimal Number
ValueCountFrequency (%)
7 1
25.0%
1 1
25.0%
0 1
25.0%
6 1
25.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122
78.7%
Common 33
 
21.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 31
25.4%
산 18
14.8%
질 9
 
7.4%
아 8
 
6.6%
르 6
 
4.9%
곤 6
 
4.9%
화 6
 
4.9%
탄 4
 
3.3%
이 4
 
3.3%
수 4
 
3.3%
Other values (13) 26
21.3%
Common
ValueCountFrequency (%)
15
45.5%
, 14
42.4%
7 1
 
3.0%
1 1
 
3.0%
0 1
 
3.0%
6 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122
78.7%
ASCII 33
 
21.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 31
25.4%
산 18
14.8%
질 9
 
7.4%
아 8
 
6.6%
르 6
 
4.9%
곤 6
 
4.9%
화 6
 
4.9%
탄 4
 
3.3%
이 4
 
3.3%
수 4
 
3.3%
Other values (13) 26
21.3%
ASCII
ValueCountFrequency (%)
15
45.5%
, 14
42.4%
7 1
 
3.0%
1 1
 
3.0%
0 1
 
3.0%
6 1
 
3.0%

인허가일자
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum1997-05-12 00:00:00
Maximum2017-09-15 00:00:00
2023-12-12T13:33:09.741351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:09.887278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

인허가번호
Text

Distinct26
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T13:33:10.146149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length14.214286
Min length14

Characters and Unicode

Total characters398
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 (%)85.7%

Sample

1st row2007-4060110-5
2nd row2004-4060110-10
3rd row1997-4060110-7
4th row2006-4060110-14
5th row2008-4060110-2
ValueCountFrequency (%)
2008-4060110-2 2
 
7.1%
2016-4060110-2 2
 
7.1%
2007-4060110-5 1
 
3.6%
2012-4060110-2 1
 
3.6%
2016-4060110-6 1
 
3.6%
2016-4060110-5 1
 
3.6%
2015-4060110-4 1
 
3.6%
2014-4060110-5 1
 
3.6%
2013-4060110-1 1
 
3.6%
2012-4060110-11 1
 
3.6%
Other values (16) 16
57.1%
2023-12-12T13:33:10.519874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 122
30.7%
1 91
22.9%
- 56
14.1%
2 40
 
10.1%
6 35
 
8.8%
4 33
 
8.3%
5 6
 
1.5%
7 5
 
1.3%
3 4
 
1.0%
8 3
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 342
85.9%
Dash Punctuation 56
 
14.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 122
35.7%
1 91
26.6%
2 40
 
11.7%
6 35
 
10.2%
4 33
 
9.6%
5 6
 
1.8%
7 5
 
1.5%
3 4
 
1.2%
8 3
 
0.9%
9 3
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 398
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 122
30.7%
1 91
22.9%
- 56
14.1%
2 40
 
10.1%
6 35
 
8.8%
4 33
 
8.3%
5 6
 
1.5%
7 5
 
1.3%
3 4
 
1.0%
8 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 398
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 122
30.7%
1 91
22.9%
- 56
14.1%
2 40
 
10.1%
6 35
 
8.8%
4 33
 
8.3%
5 6
 
1.5%
7 5
 
1.3%
3 4
 
1.0%
8 3
 
0.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2018-06-20 00:00:00
Maximum2018-06-20 00:00:00
2023-12-12T13:33:10.662864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:10.756317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T13:33:06.165648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:05.951001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:06.266150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:06.071414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:33:10.843568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호명소재지지번주소소재지도로명주소위도경도고압가스 종류인허가일자인허가번호
상호명1.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0000.7061.0000.971
소재지도로명주소1.0001.0001.0001.0001.0000.7061.0000.971
위도1.0001.0001.0001.0000.7830.8071.0000.938
경도1.0001.0001.0000.7831.0000.7001.0000.918
고압가스 종류1.0000.7060.7060.8070.7001.0001.0000.727
인허가일자1.0001.0001.0001.0001.0001.0001.0001.000
인허가번호1.0000.9710.9710.9380.9180.7271.0001.000
2023-12-12T13:33:10.991457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.141
경도0.1411.000

Missing values

2023-12-12T13:33:06.408234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:33:06.543079image/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

상호명소재지지번주소소재지도로명주소위도경도고압가스 종류인허가일자인허가번호데이터기준일
0파주시 축분혼합 공공처리시설파주시 파주읍 봉암리 1039-4파주시 파주읍 통일로 1089-10037.805889126.788498산소2007-07-212007-4060110-52018-06-20
1엘지디스플레이(P7)파주시 월롱면 덕은리 1007파주시 월롱면 엘지로 24537.81117126.766959산소, 질소 등7여종2004-09-012004-4060110-102018-06-20
2에이에스이코리아㈜파주시 문발동 494파주시 산업단지길 7637.727818126.710374수소1997-05-121997-4060110-72018-06-20
3엘지디스플레이(P8)파주시 월롱면 덕은리 1007파주시 월롱면 엘지로 24537.81117126.766959산소, 아르곤 등6종2006-05-262006-4060110-142018-06-20
4엘지디스플레이(P8 YARD)파주시 월롱면 덕은리 1007파주시 월롱면 엘지로 24537.81117126.766959산소, 질소 등10여종2008-06-252008-4060110-22018-06-20
5시그네틱스㈜파주시 탄현면 법흥리 483-3파주시 탄현면 평화로 71137.777418126.707095질소2008-10-202008-4060110-22018-06-20
6한국수자원공사 문산정수장파주시 문산읍 선유리 343파주시 문산읍 화석정로 43-237.877377126.804811산소, 이산화탄소2009-09-142009-4060110-42018-06-20
7엘지이노텍㈜파주시 문산읍 내포리 1633파주시 월롱면 휴암로 57037.83972126.782344산소, 질소2010-03-192010-4060110-32018-06-20
8파주병원파주시 금촌동 798파주시 중앙로 20737.754882126.779638산소2010-05-282010-4060110-22018-06-20
9㈜엘지화학파주시 월롱면 능산리 658파주시 월롱면 휴암로 47737.834301126.777548천연가스2010-11-022010-4060110-52018-06-20
상호명소재지지번주소소재지도로명주소위도경도고압가스 종류인허가일자인허가번호데이터기준일
18㈜동아나이스메탈파주시 광탄면 신산리 362-5파주시 광탄면 만장산로 243-8137.783817126.844428산소2012-07-042012-4060110-82018-06-20
19갈릴리농원수산B파주시 탄현면 오금리 781-2파주시 탄현면 자유로 3810-4837.829349126.713563산소2012-12-112012-4060110-112018-06-20
20전기초자코리아㈜파주시 문산읍 당동리 883-5파주시 문산읍 방촌로 1695-3537.865573126.780897암모니아2013-02-282013-4060110-12018-06-20
21운정환경관리센타파주시 와동동 1503파주시 가람로 150번길 41-3437.737143126.767699산소2014-05-162014-4060110-52018-06-20
22한국수자원공사 파주공업정수장파주시 파주읍 봉암리 260파주시 파주읍 샛봉우재길 13037.82209126.799251이산화탄소2015-08-042015-4060110-42018-06-20
23파주에너지서비스㈜1호기파주시 파주읍 봉암리 544-4파주시 월롱면 휴암로 336-23437.830025126.783992수소,이산화탄소2016-08-012016-4060110-22018-06-20
24엘지디스플레이 P9 FAB파주시 월롱면 덕은리 1007파주시 월롱면 엘지로 24537.81117126.766959액화가스, 압축가스2016-09-082016-4060110-22018-06-20
25솔브레인㈜파주시 문산읍 선유리 1372-4파주시 문산읍 돈유2로 3737.859342126.808637액화질소2016-10-072016-4060110-52018-06-20
26파주에너지서비스㈜2호기파주시 파주읍 봉암리 544-4파주시 월롱면 휴암로 336-23437.830025126.783992수소, 이산화탄소2016-10-132016-4060110-62018-06-20
27엘지디스플레이㈜(P10 YARD)파주시 월롱면 덕은리 1007파주시 월롱면 엘지로 24537.81117126.766959암모니아2017-09-152017-4060110-22018-06-20