Overview

Dataset statistics

Number of variables7
Number of observations26
Missing cells26
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory63.1 B

Variable types

Numeric1
Text4
Categorical1
Unsupported1

Dataset

Description경상남도 양산소방서에서 지정한 관내 중점관리대상 현황 데이터로 대상물명, 위치, 용도, 연면적 등을 포함한 데이터입니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15092256

Alerts

연번 is highly overall correlated with 용도High correlation
용도 is highly overall correlated with 연번High correlation
비고 has 26 (100.0%) missing valuesMissing
연번 has unique valuesUnique
대상명 has unique valuesUnique
위치 has unique valuesUnique
면적 has unique valuesUnique
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:54:11.098023
Analysis finished2023-12-10 22:54:11.636922
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T07:54:11.712668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-11T07:54:11.832279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

지역
Text

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T07:54:12.008800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length4.1153846
Min length2

Characters and Unicode

Total characters107
Distinct characters41
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)69.2%

Sample

1st row유산동
2nd row유산동
3rd row교동
4th row어곡동
5th row산막동
ValueCountFrequency (%)
중부동 4
 
11.8%
물금읍 3
 
8.8%
하북면 2
 
5.9%
유산동 2
 
5.9%
가촌리 2
 
5.9%
덕계동 2
 
5.9%
신전리 1
 
2.9%
상북면 1
 
2.9%
삼호동 1
 
2.9%
소주동 1
 
2.9%
Other values (15) 15
44.1%
2023-12-11T07:54:12.348005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 19
17.8%
리 8
 
7.5%
8
 
7.5%
산 5
 
4.7%
북 4
 
3.7%
면 4
 
3.7%
부 4
 
3.7%
읍 4
 
3.7%
물 4
 
3.7%
중 4
 
3.7%
Other values (31) 43
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
92.5%
Space Separator 8
 
7.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 19
19.2%
리 8
 
8.1%
산 5
 
5.1%
북 4
 
4.0%
면 4
 
4.0%
부 4
 
4.0%
읍 4
 
4.0%
물 4
 
4.0%
중 4
 
4.0%
금 3
 
3.0%
Other values (30) 40
40.4%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
92.5%
Common 8
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 19
19.2%
리 8
 
8.1%
산 5
 
5.1%
북 4
 
4.0%
면 4
 
4.0%
부 4
 
4.0%
읍 4
 
4.0%
물 4
 
4.0%
중 4
 
4.0%
금 3
 
3.0%
Other values (30) 40
40.4%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
92.5%
ASCII 8
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 19
19.2%
리 8
 
8.1%
산 5
 
5.1%
북 4
 
4.0%
면 4
 
4.0%
부 4
 
4.0%
읍 4
 
4.0%
물 4
 
4.0%
중 4
 
4.0%
금 3
 
3.0%
Other values (30) 40
40.4%
ASCII
ValueCountFrequency (%)
8
100.0%

대상명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T07:54:12.574873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.7692308
Min length3

Characters and Unicode

Total characters150
Distinct characters83
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row넥센타이어
2nd row동아타이어
3rd row㈜화승알앤에이
4th row(주)화승티엔씨
5th row롯데제과
ValueCountFrequency (%)
넥센타이어 1
 
3.4%
통도환타지아콘도 1
 
3.4%
덕계상설시장 1
 
3.4%
양산남부시장 1
 
3.4%
양산점 1
 
3.4%
이마트 1
 
3.4%
모다아울렛 1
 
3.4%
웅상점 1
 
3.4%
롯데마트 1
 
3.4%
㈜세정 1
 
3.4%
Other values (19) 19
65.5%
2023-12-11T07:54:12.939070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 7
 
4.7%
원 6
 
4.0%
양 6
 
4.0%
병 6
 
4.0%
타 5
 
3.3%
도 4
 
2.7%
스 4
 
2.7%
이 4
 
2.7%
마 3
 
2.0%
상 3
 
2.0%
Other values (73) 102
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143
95.3%
Space Separator 3
 
2.0%
Other Symbol 2
 
1.3%
Open Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 7
 
4.9%
원 6
 
4.2%
양 6
 
4.2%
병 6
 
4.2%
타 5
 
3.5%
도 4
 
2.8%
스 4
 
2.8%
이 4
 
2.8%
마 3
 
2.1%
상 3
 
2.1%
Other values (69) 95
66.4%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145
96.7%
Common 5
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 7
 
4.8%
원 6
 
4.1%
양 6
 
4.1%
병 6
 
4.1%
타 5
 
3.4%
도 4
 
2.8%
스 4
 
2.8%
이 4
 
2.8%
마 3
 
2.1%
상 3
 
2.1%
Other values (70) 97
66.9%
Common
ValueCountFrequency (%)
3
60.0%
( 1
 
20.0%
) 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 143
95.3%
ASCII 5
 
3.3%
None 2
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 7
 
4.9%
원 6
 
4.2%
양 6
 
4.2%
병 6
 
4.2%
타 5
 
3.5%
도 4
 
2.8%
스 4
 
2.8%
이 4
 
2.8%
마 3
 
2.1%
상 3
 
2.1%
Other values (69) 95
66.4%
ASCII
ValueCountFrequency (%)
3
60.0%
( 1
 
20.0%
) 1
 
20.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

위치
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T07:54:13.149942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length12.346154
Min length9

Characters and Unicode

Total characters321
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

Unique26 ?
Unique (%)100.0%

Sample

1st row양산시 충렬로 355
2nd row양산시 유산공단 11길 11
3rd row양산시 충렬로 61
4th row양산시 어곡공단5길 39
5th row양산시 양산대로 1158
ValueCountFrequency (%)
양산시 26
31.0%
물금읍 2
 
2.4%
충렬로 2
 
2.4%
68 2
 
2.4%
11 2
 
2.4%
양산대로 2
 
2.4%
하북면 2
 
2.4%
어실로 1
 
1.2%
1206 1
 
1.2%
백호로 1
 
1.2%
Other values (43) 43
51.2%
2023-12-11T07:54:13.433714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58
18.1%
산 32
 
10.0%
양 29
 
9.0%
시 26
 
8.1%
1 19
 
5.9%
로 16
 
5.0%
2 10
 
3.1%
길 10
 
3.1%
5 8
 
2.5%
6 7
 
2.2%
Other values (55) 106
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
58.3%
Decimal Number 75
23.4%
Space Separator 58
 
18.1%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 32
17.1%
양 29
15.5%
시 26
13.9%
로 16
 
8.6%
길 10
 
5.3%
단 4
 
2.1%
공 4
 
2.1%
북 3
 
1.6%
대 3
 
1.6%
면 3
 
1.6%
Other values (43) 57
30.5%
Decimal Number
ValueCountFrequency (%)
1 19
25.3%
2 10
13.3%
5 8
10.7%
6 7
 
9.3%
7 6
 
8.0%
8 6
 
8.0%
4 6
 
8.0%
3 5
 
6.7%
0 5
 
6.7%
9 3
 
4.0%
Space Separator
ValueCountFrequency (%)
58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
58.3%
Common 134
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 32
17.1%
양 29
15.5%
시 26
13.9%
로 16
 
8.6%
길 10
 
5.3%
단 4
 
2.1%
공 4
 
2.1%
북 3
 
1.6%
대 3
 
1.6%
면 3
 
1.6%
Other values (43) 57
30.5%
Common
ValueCountFrequency (%)
58
43.3%
1 19
 
14.2%
2 10
 
7.5%
5 8
 
6.0%
6 7
 
5.2%
7 6
 
4.5%
8 6
 
4.5%
4 6
 
4.5%
3 5
 
3.7%
0 5
 
3.7%
Other values (2) 4
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187
58.3%
ASCII 134
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58
43.3%
1 19
 
14.2%
2 10
 
7.5%
5 8
 
6.0%
6 7
 
5.2%
7 6
 
4.5%
8 6
 
4.5%
4 6
 
4.5%
3 5
 
3.7%
0 5
 
3.7%
Other values (2) 4
 
3.0%
Hangul
ValueCountFrequency (%)
산 32
17.1%
양 29
15.5%
시 26
13.9%
로 16
 
8.6%
길 10
 
5.3%
단 4
 
2.1%
공 4
 
2.1%
북 3
 
1.6%
대 3
 
1.6%
면 3
 
1.6%
Other values (43) 57
30.5%

면적
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T07:54:13.609014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.8461538
Min length7

Characters and Unicode

Total characters230
Distinct characters12
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

Unique26 ?
Unique (%)100.0%

Sample

1st row178,741.49
2nd row34,078.18
3rd row37,856.00
4th row67,863.00
5th row88,530.03
ValueCountFrequency (%)
178,741.49 1
 
3.8%
34,078.18 1
 
3.8%
11,728.02 1
 
3.8%
9,496.00 1
 
3.8%
46,029.00 1
 
3.8%
28,269.00 1
 
3.8%
30,533.32 1
 
3.8%
42,894.68 1
 
3.8%
198,935.45 1
 
3.8%
12,763.00 1
 
3.8%
Other values (16) 16
61.5%
2023-12-11T07:54:13.918742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 29
12.6%
, 26
11.3%
. 25
10.9%
8 23
10.0%
2 22
9.6%
3 18
7.8%
1 15
6.5%
7 15
6.5%
9 15
6.5%
5 15
6.5%
Other values (2) 27
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 179
77.8%
Other Punctuation 51
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 29
16.2%
8 23
12.8%
2 22
12.3%
3 18
10.1%
1 15
8.4%
7 15
8.4%
9 15
8.4%
5 15
8.4%
6 14
7.8%
4 13
7.3%
Other Punctuation
ValueCountFrequency (%)
, 26
51.0%
. 25
49.0%

Most occurring scripts

ValueCountFrequency (%)
Common 230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 29
12.6%
, 26
11.3%
. 25
10.9%
8 23
10.0%
2 22
9.6%
3 18
7.8%
1 15
6.5%
7 15
6.5%
9 15
6.5%
5 15
6.5%
Other values (2) 27
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 29
12.6%
, 26
11.3%
. 25
10.9%
8 23
10.0%
2 22
9.6%
3 18
7.8%
1 15
6.5%
7 15
6.5%
9 15
6.5%
5 15
6.5%
Other values (2) 27
11.7%

용도
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size340.0 B
공장
7 
의료
6 
판매
5 
숙박
2 
창고
2 
Other values (4)
4 

Length

Max length6
Median length2
Mean length2.2692308
Min length2

Unique

Unique4 ?
Unique (%)15.4%

Sample

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

Common Values

ValueCountFrequency (%)
공장 7
26.9%
의료 6
23.1%
판매 5
19.2%
숙박 2
 
7.7%
창고 2
 
7.7%
복합 1
 
3.8%
가연성외장재 1
 
3.8%
영화상영관 1
 
3.8%
종교 1
 
3.8%

Length

2023-12-11T07:54:14.045593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:54:14.174578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공장 7
26.9%
의료 6
23.1%
판매 5
19.2%
숙박 2
 
7.7%
창고 2
 
7.7%
복합 1
 
3.8%
가연성외장재 1
 
3.8%
영화상영관 1
 
3.8%
종교 1
 
3.8%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

Interactions

2023-12-11T07:54:11.366221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:54:14.261137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지역대상명위치면적용도
연번1.0000.9061.0001.0001.0000.825
지역0.9061.0001.0001.0001.0000.904
대상명1.0001.0001.0001.0001.0001.000
위치1.0001.0001.0001.0001.0001.000
면적1.0001.0001.0001.0001.0001.000
용도0.8250.9041.0001.0001.0001.000
2023-12-11T07:54:14.344183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번용도
연번1.0000.581
용도0.5811.000

Missing values

2023-12-11T07:54:11.469423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:54:11.591118image/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

연번지역대상명위치면적용도비고
01유산동넥센타이어양산시 충렬로 355178,741.49공장<NA>
12유산동동아타이어양산시 유산공단 11길 1134,078.18공장<NA>
23교동㈜화승알앤에이양산시 충렬로 6137,856.00공장<NA>
34어곡동(주)화승티엔씨양산시 어곡공단5길 3967,863.00공장<NA>
45산막동롯데제과양산시 양산대로 115888,530.03공장<NA>
56북정동폼윅스 양산지점양산시 산막공단남2길 1126,881.25공장<NA>
67물급읍 가촌리라피에스타양산양산시 증산역로 177128,778복합<NA>
78용당동한창제지양산시 웅상대로 156437,524.07공장<NA>
89물금읍 범어리양산부산대학교병원양산시 물금읍 금오로 20204,645.99의료<NA>
910신기동베데스다병원양산시 신기로 287,020.80의료<NA>
연번지역대상명위치면적용도비고
1617물금읍 가촌리큐엠씨네마타워양산시 백호로 687,605.53가연성외장재<NA>
1718중부동메가박스양산시 강변로 44012,763.00영화상영관<NA>
1819물금읍 증산리한국복합물류양산시 물금읍 제방로 27198,935.45창고<NA>
1920소주동㈜세정양산시 소주공단2길 542,894.68창고<NA>
2021삼호동롯데마트 웅상점양산시 삼호1길 3430,533.32판매<NA>
2122중부동모다아울렛양산시 중부로 228,269.00판매<NA>
2223중부동이마트 양산점양산시 양산역6길 1246,029.00판매<NA>
2324중부동양산남부시장양산시 중앙로 1339,496.00판매<NA>
2425덕계동덕계상설시장양산시 덕계2길 711,728.02판매<NA>
2526하북면 지산리통도사양산시 하북면 통도사로 10811,532.80종교<NA>