Overview

Dataset statistics

Number of variables15
Number of observations77
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.6 KiB
Average record size in memory127.7 B

Variable types

Categorical10
Text2
Numeric3

Dataset

Description부산광역시남구_현수막지정게시대현황_20211213
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3081661

Alerts

관리기관명 has constant value ""Constant
부착제한일 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
구군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
규격 is highly overall correlated with 부착면수 and 2 other fieldsHigh correlation
점용료 is highly overall correlated with 부착면수 and 2 other fieldsHigh correlation
민원수수료 is highly overall correlated with 부착면수 and 1 other fieldsHigh correlation
특징 is highly overall correlated with 부착면수 and 1 other fieldsHigh correlation
부착면수 is highly overall correlated with 특징 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 행정동High correlation
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
특징 is highly imbalanced (76.2%)Imbalance
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:57:17.488051
Analysis finished2023-12-10 16:57:19.738529
Duration2.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
부산광역시 남구청
77 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 남구청
2nd row부산광역시 남구청
3rd row부산광역시 남구청
4th row부산광역시 남구청
5th row부산광역시 남구청

Common Values

ValueCountFrequency (%)
부산광역시 남구청 77
100.0%

Length

2023-12-11T01:57:19.825212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:20.260922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 77
50.0%
남구청 77
50.0%

행정동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size748.0 B
대연제3동
14 
용당동
11 
대연제6동
7 
대연제1동
6 
용호제3동
4 
Other values (12)
35 

Length

Max length5
Median length5
Mean length4.6103896
Min length3

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row감만제1동
2nd row감만제1동
3rd row감만제1동
4th row감만제1동
5th row감만제2동

Common Values

ValueCountFrequency (%)
대연제3동 14
18.2%
용당동 11
14.3%
대연제6동 7
9.1%
대연제1동 6
 
7.8%
용호제3동 4
 
5.2%
용호제1동 4
 
5.2%
우암동 4
 
5.2%
문현제4동 4
 
5.2%
감만제1동 4
 
5.2%
문현제3동 3
 
3.9%
Other values (7) 16
20.8%

Length

2023-12-11T01:57:20.433002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대연제3동 14
18.2%
용당동 11
14.3%
대연제6동 7
9.1%
대연제1동 6
 
7.8%
우암동 4
 
5.2%
문현제4동 4
 
5.2%
감만제1동 4
 
5.2%
용호제1동 4
 
5.2%
용호제3동 4
 
5.2%
문현제3동 3
 
3.9%
Other values (7) 16
20.8%

위치
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T01:57:20.777594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length24
Mean length16.662338
Min length4

Characters and Unicode

Total characters1283
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

Unique77 ?
Unique (%)100.0%

Sample

1st row감만삼거리
2nd row수영돼지국밥 앞
3rd row우암로 54(감만동 버스종점 우측) 앞
4th row무민사로 40 앞
5th row홈플러스 감만점 건너편
ValueCountFrequency (%)
앞 23
 
9.6%
맞은편 10
 
4.2%
사거리 7
 
2.9%
대연동 5
 
2.1%
옆 5
 
2.1%
용호지구대 5
 
2.1%
앞(제1게시대 4
 
1.7%
입구 4
 
1.7%
앞(제2게시대 4
 
1.7%
못골지하철역 3
 
1.3%
Other values (133) 169
70.7%
2023-12-11T01:57:21.283625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
163
 
12.7%
대 65
 
5.1%
) 43
 
3.4%
( 42
 
3.3%
시 39
 
3.0%
앞 36
 
2.8%
게 34
 
2.7%
제 29
 
2.3%
동 25
 
1.9%
구 21
 
1.6%
Other values (204) 786
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 921
71.8%
Space Separator 163
 
12.7%
Decimal Number 82
 
6.4%
Close Punctuation 43
 
3.4%
Open Punctuation 42
 
3.3%
Uppercase Letter 17
 
1.3%
Other Punctuation 10
 
0.8%
Dash Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 65
 
7.1%
시 39
 
4.2%
앞 36
 
3.9%
게 34
 
3.7%
제 29
 
3.1%
동 25
 
2.7%
구 21
 
2.3%
리 20
 
2.2%
로 20
 
2.2%
거 19
 
2.1%
Other values (181) 613
66.6%
Decimal Number
ValueCountFrequency (%)
1 21
25.6%
2 19
23.2%
3 14
17.1%
4 11
13.4%
6 4
 
4.9%
5 4
 
4.9%
9 4
 
4.9%
0 3
 
3.7%
7 2
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
E 4
23.5%
D 3
17.6%
L 3
17.6%
S 2
11.8%
K 2
11.8%
W 1
 
5.9%
I 1
 
5.9%
V 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 7
70.0%
* 3
30.0%
Space Separator
ValueCountFrequency (%)
163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 921
71.8%
Common 345
 
26.9%
Latin 17
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 65
 
7.1%
시 39
 
4.2%
앞 36
 
3.9%
게 34
 
3.7%
제 29
 
3.1%
동 25
 
2.7%
구 21
 
2.3%
리 20
 
2.2%
로 20
 
2.2%
거 19
 
2.1%
Other values (181) 613
66.6%
Common
ValueCountFrequency (%)
163
47.2%
) 43
 
12.5%
( 42
 
12.2%
1 21
 
6.1%
2 19
 
5.5%
3 14
 
4.1%
4 11
 
3.2%
. 7
 
2.0%
- 5
 
1.4%
6 4
 
1.2%
Other values (5) 16
 
4.6%
Latin
ValueCountFrequency (%)
E 4
23.5%
D 3
17.6%
L 3
17.6%
S 2
11.8%
K 2
11.8%
W 1
 
5.9%
I 1
 
5.9%
V 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 921
71.8%
ASCII 362
 
28.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
163
45.0%
) 43
 
11.9%
( 42
 
11.6%
1 21
 
5.8%
2 19
 
5.2%
3 14
 
3.9%
4 11
 
3.0%
. 7
 
1.9%
- 5
 
1.4%
6 4
 
1.1%
Other values (13) 33
 
9.1%
Hangul
ValueCountFrequency (%)
대 65
 
7.1%
시 39
 
4.2%
앞 36
 
3.9%
게 34
 
3.7%
제 29
 
3.1%
동 25
 
2.7%
구 21
 
2.3%
리 20
 
2.2%
로 20
 
2.2%
거 19
 
2.1%
Other values (181) 613
66.6%

주소
Text

Distinct58
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T01:57:21.523809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length250
Mean length169.20779
Min length12

Characters and Unicode

Total characters13029
Distinct characters49
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

Unique43 ?
Unique (%)55.8%

Sample

1st row부산광역시 남구 감만동 75-56
2nd row부산광역시 남구 감만동 84-21
3rd row부산광역시 남구 우암로 54
4th row부산광역시 남구 무민사로 40
5th row부산광역시 남구 감만동 51-8
ValueCountFrequency (%)
부산광역시 77
24.9%
남구 77
24.9%
대연동 29
 
9.4%
용호동 11
 
3.6%
문현동 11
 
3.6%
용당동 9
 
2.9%
172-18 5
 
1.6%
우암동 4
 
1.3%
1740-8 3
 
1.0%
1872 3
 
1.0%
Other values (62) 80
25.9%
2023-12-11T01:57:21.913135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11890
91.3%
산 78
 
0.6%
부 77
 
0.6%
광 77
 
0.6%
역 77
 
0.6%
시 77
 
0.6%
남 77
 
0.6%
구 77
 
0.6%
1 74
 
0.6%
동 67
 
0.5%
Other values (39) 458
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 11890
91.3%
Other Letter 779
 
6.0%
Decimal Number 305
 
2.3%
Dash Punctuation 55
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 78
10.0%
부 77
9.9%
광 77
9.9%
역 77
9.9%
시 77
9.9%
남 77
9.9%
구 77
9.9%
동 67
8.6%
대 29
 
3.7%
연 29
 
3.7%
Other values (27) 114
14.6%
Decimal Number
ValueCountFrequency (%)
1 74
24.3%
2 39
12.8%
8 33
10.8%
4 28
 
9.2%
3 28
 
9.2%
5 25
 
8.2%
7 24
 
7.9%
9 21
 
6.9%
6 19
 
6.2%
0 14
 
4.6%
Space Separator
ValueCountFrequency (%)
11890
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12250
94.0%
Hangul 779
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 78
10.0%
부 77
9.9%
광 77
9.9%
역 77
9.9%
시 77
9.9%
남 77
9.9%
구 77
9.9%
동 67
8.6%
대 29
 
3.7%
연 29
 
3.7%
Other values (27) 114
14.6%
Common
ValueCountFrequency (%)
11890
97.1%
1 74
 
0.6%
- 55
 
0.4%
2 39
 
0.3%
8 33
 
0.3%
4 28
 
0.2%
3 28
 
0.2%
5 25
 
0.2%
7 24
 
0.2%
9 21
 
0.2%
Other values (2) 33
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12250
94.0%
Hangul 779
 
6.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11890
97.1%
1 74
 
0.6%
- 55
 
0.4%
2 39
 
0.3%
8 33
 
0.3%
4 28
 
0.2%
3 28
 
0.2%
5 25
 
0.2%
7 24
 
0.2%
9 21
 
0.2%
Other values (2) 33
 
0.3%
Hangul
ValueCountFrequency (%)
산 78
10.0%
부 77
9.9%
광 77
9.9%
역 77
9.9%
시 77
9.9%
남 77
9.9%
구 77
9.9%
동 67
8.6%
대 29
 
3.7%
연 29
 
3.7%
Other values (27) 114
14.6%

특징
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size748.0 B
탱탱이 걸이식(좌측고정)
74 
LED 전자게시대
 
3

Length

Max length13
Median length13
Mean length12.844156
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row탱탱이 걸이식(좌측고정)
2nd row탱탱이 걸이식(좌측고정)
3rd row탱탱이 걸이식(좌측고정)
4th row탱탱이 걸이식(좌측고정)
5th row탱탱이 걸이식(좌측고정)

Common Values

ValueCountFrequency (%)
탱탱이 걸이식(좌측고정) 74
96.1%
LED 전자게시대 3
 
3.9%

Length

2023-12-11T01:57:22.084693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:22.195805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
탱탱이 74
48.1%
걸이식(좌측고정 74
48.1%
led 3
 
1.9%
전자게시대 3
 
1.9%

규격
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size748.0 B
6.0*0.7
54 
7.0*0.9
17 
6.3*1.2
 
3
6.5*0.9
 
2
7.0*0.7
 
1

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row7.0*0.9
2nd row6.0*0.7
3rd row6.0*0.7
4th row6.0*0.7
5th row6.0*0.7

Common Values

ValueCountFrequency (%)
6.0*0.7 54
70.1%
7.0*0.9 17
 
22.1%
6.3*1.2 3
 
3.9%
6.5*0.9 2
 
2.6%
7.0*0.7 1
 
1.3%

Length

2023-12-11T01:57:22.296503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:22.394761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6.0*0.7 54
70.1%
7.0*0.9 17
 
22.1%
6.3*1.2 3
 
3.9%
6.5*0.9 2
 
2.6%
7.0*0.7 1
 
1.3%

부착면수
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.961039
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T01:57:22.518059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile5.2
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0802426
Coefficient of variation (CV)0.70253808
Kurtosis3.0075709
Mean2.961039
Median Absolute Deviation (MAD)1
Skewness1.5748303
Sum228
Variance4.3274094
MonotonicityNot monotonic
2023-12-11T01:57:22.616347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 23
29.9%
1 20
26.0%
5 17
22.1%
3 11
14.3%
10 3
 
3.9%
4 2
 
2.6%
6 1
 
1.3%
ValueCountFrequency (%)
1 20
26.0%
2 23
29.9%
3 11
14.3%
4 2
 
2.6%
5 17
22.1%
6 1
 
1.3%
10 3
 
3.9%
ValueCountFrequency (%)
10 3
 
3.9%
6 1
 
1.3%
5 17
22.1%
4 2
 
2.6%
3 11
14.3%
2 23
29.9%
1 20
26.0%

부착제한일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
10
77 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 77
100.0%

Length

2023-12-11T01:57:22.748645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:22.874331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 77
100.0%

민원수수료
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size748.0 B
10000
47 
0
30 

Length

Max length5
Median length5
Mean length3.4415584
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10000
2nd row10000
3rd row10000
4th row10000
5th row10000

Common Values

ValueCountFrequency (%)
10000 47
61.0%
0 30
39.0%

Length

2023-12-11T01:57:22.993419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:23.099535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10000 47
61.0%
0 30
39.0%

점용료
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size748.0 B
0
30 
1260
28 
1890
16 
1755
 
2
1470
 
1

Length

Max length4
Median length4
Mean length2.8311688
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row1890
2nd row1260
3rd row1260
4th row1260
5th row1260

Common Values

ValueCountFrequency (%)
0 30
39.0%
1260 28
36.4%
1890 16
20.8%
1755 2
 
2.6%
1470 1
 
1.3%

Length

2023-12-11T01:57:23.220519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:23.362961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
39.0%
1260 28
36.4%
1890 16
20.8%
1755 2
 
2.6%
1470 1
 
1.3%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
051-607-4626
77 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row051-607-4626
2nd row051-607-4626
3rd row051-607-4626
4th row051-607-4626
5th row051-607-4626

Common Values

ValueCountFrequency (%)
051-607-4626 77
100.0%

Length

2023-12-11T01:57:23.484413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:23.573480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-607-4626 77
100.0%

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
부산광역시 남구
77 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 남구
2nd row부산광역시 남구
3rd row부산광역시 남구
4th row부산광역시 남구
5th row부산광역시 남구

Common Values

ValueCountFrequency (%)
부산광역시 남구 77
100.0%

Length

2023-12-11T01:57:23.683857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:23.795840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 77
50.0%
남구 77
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
2021-12-13
77 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-12-13
2nd row2021-12-13
3rd row2021-12-13
4th row2021-12-13
5th row2021-12-13

Common Values

ValueCountFrequency (%)
2021-12-13 77
100.0%

Length

2023-12-11T01:57:23.906376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:24.013797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-12-13 77
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.13013
Minimum35.1
Maximum35.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T01:57:24.145280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.1
5-th percentile35.11
Q135.12
median35.13
Q335.14
95-th percentile35.15
Maximum35.17
Range0.07
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.01141254
Coefficient of variation (CV)0.00032486473
Kurtosis1.21622
Mean35.13013
Median Absolute Deviation (MAD)0.01
Skewness0.35573385
Sum2705.02
Variance0.00013024607
MonotonicityNot monotonic
2023-12-11T01:57:24.306832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
35.13 28
36.4%
35.12 20
26.0%
35.14 18
23.4%
35.15 5
 
6.5%
35.11 4
 
5.2%
35.17 1
 
1.3%
35.1 1
 
1.3%
ValueCountFrequency (%)
35.1 1
 
1.3%
35.11 4
 
5.2%
35.12 20
26.0%
35.13 28
36.4%
35.14 18
23.4%
35.15 5
 
6.5%
35.17 1
 
1.3%
ValueCountFrequency (%)
35.17 1
 
1.3%
35.15 5
 
6.5%
35.14 18
23.4%
35.13 28
36.4%
35.12 20
26.0%
35.11 4
 
5.2%
35.1 1
 
1.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct58
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.09152
Minimum129.06418
Maximum129.11576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T01:57:24.524262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.06418
5-th percentile129.06795
Q1129.08151
median129.0921
Q3129.10107
95-th percentile129.11436
Maximum129.11576
Range0.0515817
Interquartile range (IQR)0.0195577

Descriptive statistics

Standard deviation0.013966205
Coefficient of variation (CV)0.0001081884
Kurtosis-0.91903941
Mean129.09152
Median Absolute Deviation (MAD)0.0099698
Skewness-0.15814246
Sum9940.0473
Variance0.00019505488
MonotonicityNot monotonic
2023-12-11T01:57:24.716334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1143634 4
 
5.2%
129.100254 3
 
3.9%
129.068023 2
 
2.6%
129.0931872 2
 
2.6%
129.08443 2
 
2.6%
129.098535 2
 
2.6%
129.0815124 2
 
2.6%
129.0973949 2
 
2.6%
129.0978175 2
 
2.6%
129.0903983 2
 
2.6%
Other values (48) 54
70.1%
ValueCountFrequency (%)
129.0641817 1
1.3%
129.066676 1
1.3%
129.0674 1
1.3%
129.067675 1
1.3%
129.068023 2
2.6%
129.0699938 1
1.3%
129.0711 1
1.3%
129.072471 1
1.3%
129.0733207 1
1.3%
129.073657 1
1.3%
ValueCountFrequency (%)
129.1157634 1
 
1.3%
129.1143634 4
5.2%
129.112343 1
 
1.3%
129.1116617 1
 
1.3%
129.110065 1
 
1.3%
129.109865 1
 
1.3%
129.109179 1
 
1.3%
129.109106 1
 
1.3%
129.106744 1
 
1.3%
129.1058734 1
 
1.3%

Interactions

2023-12-11T01:57:18.966051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:18.296032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:18.651716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:19.072104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:18.421152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:18.754979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:19.190465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:18.545260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:18.871803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:57:24.840655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동위치주소특징규격부착면수민원수수료점용료위도경도
행정동1.0001.0000.9970.3920.0000.6360.4990.0000.8430.890
위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소0.9971.0001.0000.0000.6720.8590.7650.7451.0001.000
특징0.3921.0000.0001.0001.0001.0000.2250.0900.0000.074
규격0.0001.0000.6721.0001.0000.8930.3370.9900.3290.463
부착면수0.6361.0000.8591.0000.8931.0000.6880.8420.0000.447
민원수수료0.4991.0000.7650.2250.3370.6881.0001.0000.0570.000
점용료0.0001.0000.7450.0900.9900.8421.0001.0000.3600.218
위도0.8431.0001.0000.0000.3290.0000.0570.3601.0000.387
경도0.8901.0001.0000.0740.4630.4470.0000.2180.3871.000
2023-12-11T01:57:24.985925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동규격점용료민원수수료특징
행정동1.0000.0000.0000.3990.312
규격0.0001.0000.8550.4020.980
점용료0.0000.8551.0000.9800.105
민원수수료0.3990.4020.9801.0000.144
특징0.3120.9800.1050.1441.000
2023-12-11T01:57:25.144351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부착면수위도경도행정동특징규격민원수수료점용료
부착면수1.0000.128-0.1210.3210.9660.8210.7170.735
위도0.1281.000-0.1050.5440.0000.2120.0490.234
경도-0.121-0.1051.0000.5950.0000.1790.0000.058
행정동0.3210.5440.5951.0000.3120.0000.3990.000
특징0.9660.0000.0000.3121.0000.9800.1440.105
규격0.8210.2120.1790.0000.9801.0000.4020.855
민원수수료0.7170.0490.0000.3990.1440.4021.0000.980
점용료0.7350.2340.0580.0000.1050.8550.9801.000

Missing values

2023-12-11T01:57:19.363662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:57:19.656115image/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

관리기관명행정동위치주소특징규격부착면수부착제한일민원수수료점용료관리기관전화번호구군명데이터기준일자위도경도
0부산광역시 남구청감만제1동감만삼거리부산광역시 남구 감만동 75-56탱탱이 걸이식(좌측고정)7.0*0.9510100001890051-607-4626부산광역시 남구2021-12-1335.12129.07396
1부산광역시 남구청감만제1동수영돼지국밥 앞부산광역시 남구 감만동 84-21탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-12-1335.12129.080185
2부산광역시 남구청감만제1동우암로 54(감만동 버스종점 우측) 앞부산광역시 남구 우암로 54탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-12-1335.11129.0815
3부산광역시 남구청감만제1동무민사로 40 앞부산광역시 남구 무민사로 40탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-12-1335.11129.0818
4부산광역시 남구청감만제2동홈플러스 감만점 건너편부산광역시 남구 감만동 51-8탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-12-1335.12129.080734
5부산광역시 남구청감만제2동남광시장 입구부산광역시 남구 석포로 66탱탱이 걸이식(좌측고정)6.0*0.741000051-607-4626부산광역시 남구2021-12-1335.12129.084558
6부산광역시 남구청대연제1동대연동 사거리 부산은행 앞(제1게시대)부산광역시 남구 대연동 1740-8탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-12-1335.13129.092227
7부산광역시 남구청대연제1동대연동 사거리 부산은행 앞(제2게시대)부산광역시 남구 대연동 1740-8탱탱이 걸이식(좌측고정)6.0*0.721000051-607-4626부산광역시 남구2021-12-1335.13129.092227
8부산광역시 남구청대연제1동못골지하철역 3번출구(제1게시대)부산광역시 남구 수영로 158 앞탱탱이 걸이식(좌측고정)6.0*0.721000051-607-4626부산광역시 남구2021-12-1335.13129.083952
9부산광역시 남구청대연제1동못골지하철역 3번출구(제2게시대)부산광역시 남구 수영로 158 앞탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2021-12-1335.13129.083952
관리기관명행정동위치주소특징규격부착면수부착제한일민원수수료점용료관리기관전화번호구군명데이터기준일자위도경도
67부산광역시 남구청용호제3동용호지구대 맞은편 제1게시대(좌측)부산광역시 남구 용호동 172-18탱탱이 걸이식(좌측고정)6.0*0.7310100001260051-607-4626부산광역시 남구2021-12-1335.13129.114363
68부산광역시 남구청용호제3동용호지구대 맞은편 제2게시대(우측-용호복지관 쪽)-맨 오른쪽)부산광역시 남구 용호동 172-18탱탱이 걸이식(좌측고정)6.0*0.7310100001260051-607-4626부산광역시 남구2021-12-1335.13129.114363
69부산광역시 남구청용호제3동용호지구대 맞은편 제3게시대(광안대교 쪽)부산광역시 남구 용호동 172-18탱탱이 걸이식(좌측고정)6.0*0.7310100001260051-607-4626부산광역시 남구2021-12-1335.13129.114363
70부산광역시 남구청용호제3동용호지구대 맞은편 제4게시대(광안대교 쪽)-맨 왼쪽부산광역시 남구 용호동 172-18탱탱이 걸이식(좌측고정)6.0*0.731000051-607-4626부산광역시 남구2021-12-1335.13129.114363
71부산광역시 남구청용호제4동백운포 체육공원 주차장부산광역시 남구 용호동 895-3탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2021-12-1335.1129.109865
72부산광역시 남구청용호제4동성모병원 주차장 입구 옆부산광역시 남구 용호동 538-41탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2021-12-1335.11129.109179
73부산광역시 남구청우암동뉴서울아파트 앞부산광역시 남구 우암동 53-1탱탱이 걸이식(좌측고정)7.0*0.9510100001890051-607-4626부산광역시 남구2021-12-1335.12129.079691
74부산광역시 남구청우암동새마을금고(구.부산은행) 맞은편(제1게시대)부산광역시 남구 우암동 184-250탱탱이 걸이식(좌측고정)7.0*0.9510100001890051-607-4626부산광역시 남구2021-12-1335.12129.07396
75부산광역시 남구청우암동새마을금고(구.부산은행) 맞은편(제2게시대)부산광역시 남구 우암동 184-250탱탱이 걸이식(좌측고정)7.0*0.9510100001890051-607-4626부산광역시 남구2021-12-1335.12129.07396
76부산광역시 남구청우암동남부중앙새마을금고 본점 맞은편 LED 전자게시대 (6.34*1.2)부산광역시 남구 우암동 232LED 전자게시대6.3*1.2101000051-607-4626부산광역시 남구2021-12-1335.12129.0711