Overview

Dataset statistics

Number of variables15
Number of observations120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.9 KiB
Average record size in memory127.1 B

Variable types

Categorical10
Text2
Numeric3

Dataset

Description부산광역시남구_현수막지정게시대현황_20221213
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3081661

Alerts

관리기관명 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 특징 and 1 other fieldsHigh correlation
점용료 is highly overall correlated with 규격 and 1 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 1 other fieldsHigh correlation
위도 is highly overall correlated with 행정동High correlation
경도 is highly overall correlated with 행정동 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
부착제한일 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
특징 is highly imbalanced (75.0%)Imbalance
규격 is highly imbalanced (72.4%)Imbalance
부착제한일 is highly imbalanced (78.9%)Imbalance
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:56:33.397833
Analysis finished2023-12-10 16:56:37.136224
Duration3.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
부산광역시 남구청
120 

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 120
100.0%

Length

2023-12-11T01:56:37.260670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:37.431270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 120
50.0%
남구청 120
50.0%

행정동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
대연제3동
17 
용호제1동
16 
대연제6동
13 
용당동
12 
대연제4동
9 
Other values (12)
53 

Length

Max length5
Median length5
Mean length4.7166667
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
대연제3동 17
14.2%
용호제1동 16
13.3%
대연제6동 13
10.8%
용당동 12
10.0%
대연제4동 9
 
7.5%
대연제1동 8
 
6.7%
문현제2동 6
 
5.0%
문현제3동 6
 
5.0%
우암동 5
 
4.2%
감만제1동 5
 
4.2%
Other values (7) 23
19.2%

Length

2023-12-11T01:56:37.631445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대연제3동 17
14.2%
용호제1동 16
13.3%
대연제6동 13
10.8%
용당동 12
10.0%
대연제4동 9
 
7.5%
대연제1동 8
 
6.7%
문현제2동 6
 
5.0%
문현제3동 6
 
5.0%
대연제5동 5
 
4.2%
우암동 5
 
4.2%
Other values (7) 23
19.2%

위치
Text

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:56:38.094010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length25
Mean length15.866667
Min length4

Characters and Unicode

Total characters1904
Distinct characters226
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

Unique120 ?
Unique (%)100.0%

Sample

1st row감만삼거리
2nd row수영돼지국밥 앞
3rd row우암로 54(감만동 버스종점 우측) 앞
4th row무민사로 40 앞
5th row감만현대2차아파트 상가 건너편
ValueCountFrequency (%)
앞 47
 
12.1%
맞은편 14
 
3.6%
사거리 9
 
2.3%
옆 8
 
2.1%
용호지구대 6
 
1.5%
게시대 5
 
1.3%
아파트 5
 
1.3%
대연동 5
 
1.3%
황령터널 4
 
1.0%
입구 4
 
1.0%
Other values (194) 282
72.5%
2023-12-11T01:56:38.822958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
 
14.2%
대 89
 
4.7%
앞 61
 
3.2%
시 60
 
3.2%
게 50
 
2.6%
) 42
 
2.2%
( 42
 
2.2%
로 36
 
1.9%
동 35
 
1.8%
제 32
 
1.7%
Other values (216) 1187
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1371
72.0%
Space Separator 270
 
14.2%
Decimal Number 130
 
6.8%
Close Punctuation 42
 
2.2%
Open Punctuation 42
 
2.2%
Uppercase Letter 31
 
1.6%
Other Punctuation 16
 
0.8%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 89
 
6.5%
앞 61
 
4.4%
시 60
 
4.4%
게 50
 
3.6%
로 36
 
2.6%
동 35
 
2.6%
제 32
 
2.3%
구 27
 
2.0%
리 25
 
1.8%
은 24
 
1.8%
Other values (192) 932
68.0%
Decimal Number
ValueCountFrequency (%)
1 32
24.6%
2 32
24.6%
3 20
15.4%
4 15
11.5%
0 8
 
6.2%
6 7
 
5.4%
5 6
 
4.6%
7 6
 
4.6%
9 4
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
E 7
22.6%
L 6
19.4%
D 5
16.1%
K 3
9.7%
S 3
9.7%
W 2
 
6.5%
I 2
 
6.5%
V 2
 
6.5%
G 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 11
68.8%
* 5
31.2%
Space Separator
ValueCountFrequency (%)
270
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1371
72.0%
Common 502
 
26.4%
Latin 31
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 89
 
6.5%
앞 61
 
4.4%
시 60
 
4.4%
게 50
 
3.6%
로 36
 
2.6%
동 35
 
2.6%
제 32
 
2.3%
구 27
 
2.0%
리 25
 
1.8%
은 24
 
1.8%
Other values (192) 932
68.0%
Common
ValueCountFrequency (%)
270
53.8%
) 42
 
8.4%
( 42
 
8.4%
1 32
 
6.4%
2 32
 
6.4%
3 20
 
4.0%
4 15
 
3.0%
. 11
 
2.2%
0 8
 
1.6%
6 7
 
1.4%
Other values (5) 23
 
4.6%
Latin
ValueCountFrequency (%)
E 7
22.6%
L 6
19.4%
D 5
16.1%
K 3
9.7%
S 3
9.7%
W 2
 
6.5%
I 2
 
6.5%
V 2
 
6.5%
G 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1371
72.0%
ASCII 533
 
28.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
270
50.7%
) 42
 
7.9%
( 42
 
7.9%
1 32
 
6.0%
2 32
 
6.0%
3 20
 
3.8%
4 15
 
2.8%
. 11
 
2.1%
0 8
 
1.5%
E 7
 
1.3%
Other values (14) 54
 
10.1%
Hangul
ValueCountFrequency (%)
대 89
 
6.5%
앞 61
 
4.4%
시 60
 
4.4%
게 50
 
3.6%
로 36
 
2.6%
동 35
 
2.6%
제 32
 
2.3%
구 27
 
2.0%
리 25
 
1.8%
은 24
 
1.8%
Other values (192) 932
68.0%

주소
Text

Distinct89
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:56:39.380984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length248.5
Mean length118.60833
Min length12

Characters and Unicode

Total characters14233
Distinct characters63
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

Unique65 ?
Unique (%)54.2%

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 329-48
ValueCountFrequency (%)
부산광역시 120
25.1%
남구 118
24.7%
대연동 34
 
7.1%
용호동 17
 
3.6%
문현동 12
 
2.5%
용당동 9
 
1.9%
172-18 5
 
1.0%
석포로 5
 
1.0%
1268-1 4
 
0.8%
감만동 4
 
0.8%
Other values (107) 150
31.4%
2023-12-11T01:56:40.142292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12479
87.7%
산 121
 
0.9%
시 120
 
0.8%
부 120
 
0.8%
역 120
 
0.8%
광 120
 
0.8%
남 119
 
0.8%
구 118
 
0.8%
1 109
 
0.8%
동 82
 
0.6%
Other values (53) 725
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 12479
87.7%
Other Letter 1231
 
8.6%
Decimal Number 454
 
3.2%
Dash Punctuation 69
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 121
9.8%
시 120
9.7%
부 120
9.7%
역 120
9.7%
광 120
9.7%
남 119
9.7%
구 118
9.6%
동 82
 
6.7%
로 40
 
3.2%
대 36
 
2.9%
Other values (41) 235
19.1%
Decimal Number
ValueCountFrequency (%)
1 109
24.0%
2 62
13.7%
3 45
9.9%
8 42
 
9.3%
7 39
 
8.6%
4 35
 
7.7%
5 34
 
7.5%
6 32
 
7.0%
9 30
 
6.6%
0 26
 
5.7%
Space Separator
ValueCountFrequency (%)
12479
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13002
91.4%
Hangul 1231
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 121
9.8%
시 120
9.7%
부 120
9.7%
역 120
9.7%
광 120
9.7%
남 119
9.7%
구 118
9.6%
동 82
 
6.7%
로 40
 
3.2%
대 36
 
2.9%
Other values (41) 235
19.1%
Common
ValueCountFrequency (%)
12479
96.0%
1 109
 
0.8%
- 69
 
0.5%
2 62
 
0.5%
3 45
 
0.3%
8 42
 
0.3%
7 39
 
0.3%
4 35
 
0.3%
5 34
 
0.3%
6 32
 
0.2%
Other values (2) 56
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13002
91.4%
Hangul 1231
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12479
96.0%
1 109
 
0.8%
- 69
 
0.5%
2 62
 
0.5%
3 45
 
0.3%
8 42
 
0.3%
7 39
 
0.3%
4 35
 
0.3%
5 34
 
0.3%
6 32
 
0.2%
Other values (2) 56
 
0.4%
Hangul
ValueCountFrequency (%)
산 121
9.8%
시 120
9.7%
부 120
9.7%
역 120
9.7%
광 120
9.7%
남 119
9.7%
구 118
9.6%
동 82
 
6.7%
로 40
 
3.2%
대 36
 
2.9%
Other values (41) 235
19.1%

특징
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
탱탱이 걸이식(좌측고정)
115 
LED 전자게시대
 
5

Length

Max length13
Median length13
Mean length12.833333
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) 115
95.8%
LED 전자게시대 5
 
4.2%

Length

2023-12-11T01:56:40.394328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:40.575650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
탱탱이 115
47.9%
걸이식(좌측고정 115
47.9%
led 5
 
2.1%
전자게시대 5
 
2.1%

규격
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
6.0*0.7
108 
7.0*0.9
 
6
6.3*1.2
 
3
6.3*1.0
 
2
5.8*0.7
 
1

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row6.0*0.7
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*0.7 108
90.0%
7.0*0.9 6
 
5.0%
6.3*1.2 3
 
2.5%
6.3*1.0 2
 
1.7%
5.8*0.7 1
 
0.8%

Length

2023-12-11T01:56:40.738484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:40.901059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6.0*0.7 108
90.0%
7.0*0.9 6
 
5.0%
6.3*1.2 3
 
2.5%
6.3*1.0 2
 
1.7%
5.8*0.7 1
 
0.8%

부착면수
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.625
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:56:41.073826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5.05
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1066621
Coefficient of variation (CV)0.80253794
Kurtosis4.0346718
Mean2.625
Median Absolute Deviation (MAD)1
Skewness1.9281496
Sum315
Variance4.4380252
MonotonicityNot monotonic
2023-12-11T01:56:41.253736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 44
36.7%
2 36
30.0%
5 19
15.8%
3 12
 
10.0%
10 5
 
4.2%
4 3
 
2.5%
6 1
 
0.8%
ValueCountFrequency (%)
1 44
36.7%
2 36
30.0%
3 12
 
10.0%
4 3
 
2.5%
5 19
15.8%
6 1
 
0.8%
10 5
 
4.2%
ValueCountFrequency (%)
10 5
 
4.2%
6 1
 
0.8%
5 19
15.8%
4 3
 
2.5%
3 12
 
10.0%
2 36
30.0%
1 44
36.7%

부착제한일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
10
116 
0
 
4

Length

Max length2
Median length2
Mean length1.9666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10 116
96.7%
0 4
 
3.3%

Length

2023-12-11T01:56:41.469953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:41.642236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 116
96.7%
0 4
 
3.3%

민원수수료
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
65 
10000
55 

Length

Max length5
Median length1
Mean length2.8333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10000
2nd row10000
3rd row10000
4th row10000
5th row0

Common Values

ValueCountFrequency (%)
0 65
54.2%
10000 55
45.8%

Length

2023-12-11T01:56:41.844000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:42.036913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 65
54.2%
10000 55
45.8%

점용료
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
65 
1260
49 
1890
 
5
1270
 
1

Length

Max length4
Median length1
Mean length2.375
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row1260
2nd row1260
3rd row1260
4th row1260
5th row0

Common Values

ValueCountFrequency (%)
0 65
54.2%
1260 49
40.8%
1890 5
 
4.2%
1270 1
 
0.8%

Length

2023-12-11T01:56:42.267265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:42.465247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 65
54.2%
1260 49
40.8%
1890 5
 
4.2%
1270 1
 
0.8%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
051-607-4626
120 

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 120
100.0%

Length

2023-12-11T01:56:42.655949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:42.857901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-607-4626 120
100.0%

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
부산광역시 남구
120 

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 120
100.0%

Length

2023-12-11T01:56:43.038043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:43.209957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 120
50.0%
남구 120
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2022-12-13
120 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-13
2nd row2022-12-13
3rd row2022-12-13
4th row2022-12-13
5th row2022-12-13

Common Values

ValueCountFrequency (%)
2022-12-13 120
100.0%

Length

2023-12-11T01:56:43.409260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:43.580252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-13 120
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.128583
Minimum35.1
Maximum35.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:56:43.732213image/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 deviation0.011397761
Coefficient of variation (CV)0.00032445833
Kurtosis0.98944745
Mean35.128583
Median Absolute Deviation (MAD)0.01
Skewness0.14453522
Sum4215.43
Variance0.00012990896
MonotonicityNot monotonic
2023-12-11T01:56:44.008311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
35.13 44
36.7%
35.12 33
27.5%
35.14 25
20.8%
35.11 8
 
6.7%
35.15 6
 
5.0%
35.1 3
 
2.5%
35.17 1
 
0.8%
ValueCountFrequency (%)
35.1 3
 
2.5%
35.11 8
 
6.7%
35.12 33
27.5%
35.13 44
36.7%
35.14 25
20.8%
35.15 6
 
5.0%
35.17 1
 
0.8%
ValueCountFrequency (%)
35.17 1
 
0.8%
35.15 6
 
5.0%
35.14 25
20.8%
35.13 44
36.7%
35.12 33
27.5%
35.11 8
 
6.7%
35.1 3
 
2.5%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.09175
Minimum129.06418
Maximum129.1175
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:56:44.292827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.06418
5-th percentile129.0669
Q1129.08187
median129.09203
Q3129.1026
95-th percentile129.11297
Maximum129.1175
Range0.0533183
Interquartile range (IQR)0.0207251

Descriptive statistics

Standard deviation0.014383728
Coefficient of variation (CV)0.00011142252
Kurtosis-0.91498149
Mean129.09175
Median Absolute Deviation (MAD)0.010178
Skewness-0.17691792
Sum15491.011
Variance0.00020689164
MonotonicityNot monotonic
2023-12-11T01:56:44.665067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1143634 4
 
3.3%
129.08443 4
 
3.3%
129.0876 3
 
2.5%
129.0973949 3
 
2.5%
129.0647 3
 
2.5%
129.0849 3
 
2.5%
129.100254 3
 
2.5%
129.092056 2
 
1.7%
129.098535 2
 
1.7%
129.0978175 2
 
1.7%
Other values (79) 91
75.8%
ValueCountFrequency (%)
129.0641817 1
 
0.8%
129.0647 3
2.5%
129.066676 1
 
0.8%
129.0669 2
1.7%
129.0674 1
 
0.8%
129.067675 1
 
0.8%
129.068023 2
1.7%
129.0699938 1
 
0.8%
129.0711 1
 
0.8%
129.0717 1
 
0.8%
ValueCountFrequency (%)
129.1175 1
 
0.8%
129.1157634 1
 
0.8%
129.1143634 4
3.3%
129.1129 1
 
0.8%
129.112343 1
 
0.8%
129.1121 1
 
0.8%
129.1119 1
 
0.8%
129.1116617 1
 
0.8%
129.1112 1
 
0.8%
129.111 1
 
0.8%

Interactions

2023-12-11T01:56:35.612318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:34.434470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:34.938899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:35.764574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:34.617298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:35.111159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:35.937118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:34.785950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:35.379402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:56:44.848120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동주소특징규격부착면수부착제한일민원수수료점용료위도경도
행정동1.0001.0000.0000.0000.3680.8270.3940.5310.8100.903
주소1.0001.0000.0000.0000.6881.0000.7590.9520.9960.998
특징0.0000.0001.0001.0001.0000.0000.1870.1660.0000.000
규격0.0000.0001.0001.0000.6590.0000.1610.5880.1050.000
부착면수0.3680.6881.0000.6591.0000.0000.5150.4290.3380.259
부착제한일0.8271.0000.0000.0000.0001.0000.1330.0990.2730.731
민원수수료0.3940.7590.1870.1610.5150.1331.0001.0000.0000.000
점용료0.5310.9520.1660.5880.4290.0991.0001.0000.4350.000
위도0.8100.9960.0000.1050.3380.2730.0000.4351.0000.503
경도0.9030.9980.0000.0000.2590.7310.0000.0000.5031.000
2023-12-11T01:56:45.090625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동규격부착제한일점용료민원수수료특징
행정동1.0000.0000.7250.3040.3290.000
규격0.0001.0000.0000.5130.1930.987
부착제한일0.7250.0001.0000.0630.0840.000
점용료0.3040.5130.0631.0000.9910.108
민원수수료0.3290.1930.0840.9911.0000.119
특징0.0000.9870.0000.1080.1191.000
2023-12-11T01:56:45.341286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부착면수위도경도행정동특징규격부착제한일민원수수료점용료
부착면수1.0000.179-0.0750.1640.9790.4980.0000.5410.304
위도0.1791.000-0.2890.5130.0000.0630.2850.0000.308
경도-0.075-0.2891.0000.6330.0000.0000.5180.0000.000
행정동0.1640.5130.6331.0000.0000.0000.7250.3290.304
특징0.9790.0000.0000.0001.0000.9870.0000.1190.108
규격0.4980.0630.0000.0000.9871.0000.0000.1930.513
부착제한일0.0000.2850.5180.7250.0000.0001.0000.0840.063
민원수수료0.5410.0000.0000.3290.1190.1930.0841.0000.991
점용료0.3040.3080.0000.3040.1080.5130.0630.9911.000

Missing values

2023-12-11T01:56:36.568022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:56:36.995129image/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)6.0*0.7510100001260051-607-4626부산광역시 남구2022-12-1335.12129.07396
1부산광역시 남구청감만제1동수영돼지국밥 앞부산광역시 남구 감만동 84-21탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2022-12-1335.12129.080185
2부산광역시 남구청감만제1동우암로 54(감만동 버스종점 우측) 앞부산광역시 남구 우암로 54탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2022-12-1335.11129.0815
3부산광역시 남구청감만제1동무민사로 40 앞부산광역시 남구 무민사로 40탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2022-12-1335.11129.0818
4부산광역시 남구청감만제1동감만현대2차아파트 상가 건너편부산광역시 남구 감만동 329-48탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2022-12-1335.11129.0819
5부산광역시 남구청감만제2동홈플러스 감만점 건너편부산광역시 남구 감만동 51-8탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2022-12-1335.12129.080734
6부산광역시 남구청감만제2동남광시장 입구부산광역시 남구 석포로 66탱탱이 걸이식(좌측고정)6.0*0.741000051-607-4626부산광역시 남구2022-12-1335.12129.084558
7부산광역시 남구청감만제2동감만2동행정복지센터 앞부산광역시 남구 석포로 32-1탱탱이 걸이식(좌측고정)6.0*0.721000051-607-4626부산광역시 남구2022-12-1335.12129.0845
8부산광역시 남구청대연제1동대연동 사거리 부산은행 앞(제1게시대)부산광역시 남구 대연동 1740-8탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2022-12-1335.13129.092227
9부산광역시 남구청대연제1동대연동 사거리 부산은행 앞(제2게시대)부산광역시 남구 대연동 1740-8탱탱이 걸이식(좌측고정)6.0*0.721000051-607-4626부산광역시 남구2022-12-1335.13129.092227
관리기관명행정동위치주소특징규격부착면수부착제한일민원수수료점용료관리기관전화번호구군명데이터기준일자위도경도
110부산광역시 남구청용호제2동오륙도 SK VIEW 아파트 정문 육교 근처부산광역시 남구 오륙도로 85탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2022-12-1335.1129.1175
111부산광역시 남구청용호제3동용호3동 행정복지센터 옆부산광역시 남구 동명로145번길 33탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2022-12-1335.12129.1129
112부산광역시 남구청용호제4동백운포 체육공원 주차장부산광역시 남구 용호동 895-3탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2022-12-1335.1129.109865
113부산광역시 남구청용호제4동성모병원 주차장 입구 옆부산광역시 남구 용호동 538-41탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2022-12-1335.11129.109179
114부산광역시 남구청용호제4동용호4동 행정복지센터 앞부산광역시 남구 용호로216번길 10탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2022-12-1335.11129.1104
115부산광역시 남구청우암동뉴서울아파트 앞부산광역시 남구 우암동 53-1탱탱이 걸이식(좌측고정)6.0*0.7510100001260051-607-4626부산광역시 남구2022-12-1335.12129.079691
116부산광역시 남구청우암동새마을금고(구.부산은행) 맞은편(제1게시대)부산광역시 남구 우암동 184-250탱탱이 걸이식(좌측고정)6.0*0.7510100001260051-607-4626부산광역시 남구2022-12-1335.12129.07396
117부산광역시 남구청우암동새마을금고(구.부산은행) 맞은편(제2게시대)부산광역시 남구 우암동 184-250탱탱이 걸이식(좌측고정)6.0*0.7510100001260051-607-4626부산광역시 남구2022-12-1335.12129.07396
118부산광역시 남구청우암동남부중앙새마을금고 본점 맞은편 LED 전자게시대 (6.34*1.2)부산광역시 남구 우암동 232LED 전자게시대6.3*1.2101000051-607-4626부산광역시 남구2022-12-1335.12129.0711
119부산광역시 남구청우암동동일아파트 담벼락부산광역시 남구 유엔로 1-1탱탱이 걸이식(좌측고정)6.0*0.721000051-607-4626부산광역시 남구2022-12-1335.12129.0792