Overview

Dataset statistics

Number of variables15
Number of observations71
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory127.9 B

Variable types

Categorical11
Text2
Numeric2

Dataset

Description부산광역시남구_현수막지정게시대현황_20210628
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3081661

Alerts

관리기관명 has constant value ""Constant
특징 has constant value ""Constant
부착제한일 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
구군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
점용료 is highly overall correlated with 규격 and 2 other fieldsHigh correlation
민원수수료 is highly overall correlated with 부착면수 and 1 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
규격 is highly overall correlated with 부착면수 and 1 other fieldsHigh correlation
부착면수 is highly overall correlated with 규격 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 16:57:40.422164
Analysis finished2023-12-10 16:57:43.109430
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
부산광역시 남구청
71 

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 71
100.0%

Length

2023-12-11T01:57:43.237983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:43.388692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 71
50.0%
남구청 71
50.0%

행정동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Memory size700.0 B
대연제3동
12 
용당동
12 
대연제6동
7 
용호제3동
4 
대연제1동
4 
Other values (12)
32 

Length

Max length5
Median length5
Mean length4.5774648
Min length3

Unique

Unique2 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
대연제3동 12
16.9%
용당동 12
16.9%
대연제6동 7
9.9%
용호제3동 4
 
5.6%
대연제1동 4
 
5.6%
문현제4동 4
 
5.6%
용호제1동 4
 
5.6%
문현제1동 3
 
4.2%
문현제3동 3
 
4.2%
감만제2동 3
 
4.2%
Other values (7) 15
21.1%

Length

2023-12-11T01:57:43.524765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대연제3동 12
16.9%
용당동 12
16.9%
대연제6동 7
9.9%
용호제3동 4
 
5.6%
대연제1동 4
 
5.6%
문현제4동 4
 
5.6%
용호제1동 4
 
5.6%
대연제4동 3
 
4.2%
우암동 3
 
4.2%
대연제5동 3
 
4.2%
Other values (7) 15
21.1%

위치
Text

Distinct70
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T01:57:43.798355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length23
Mean length16.338028
Min length4

Characters and Unicode

Total characters1160
Distinct characters201
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

Unique69 ?
Unique (%)97.2%

Sample

1st row감만삼거리
2nd row수영돼지국밥 앞
3rd row홈플러스 감만점 건너편
4th row감만2동행정복지센터 앞(좌)
5th row감만2동행정복지센터 앞(우)
ValueCountFrequency (%)
앞 19
 
9.1%
맞은편 9
 
4.3%
사거리 6
 
2.9%
용호지구대 5
 
2.4%
대연동 4
 
1.9%
앞(제1게시대 4
 
1.9%
앞(제2게시대 4
 
1.9%
못골지하철역 3
 
1.4%
입구 3
 
1.4%
옆 3
 
1.4%
Other values (116) 148
71.2%
2023-12-11T01:57:44.319417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
138
 
11.9%
대 60
 
5.2%
) 42
 
3.6%
( 41
 
3.5%
시 36
 
3.1%
앞 34
 
2.9%
게 32
 
2.8%
제 29
 
2.5%
동 26
 
2.2%
2 20
 
1.7%
Other values (191) 702
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 849
73.2%
Space Separator 138
 
11.9%
Decimal Number 69
 
5.9%
Close Punctuation 42
 
3.6%
Open Punctuation 41
 
3.5%
Uppercase Letter 11
 
0.9%
Dash Punctuation 5
 
0.4%
Other Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 60
 
7.1%
시 36
 
4.2%
앞 34
 
4.0%
게 32
 
3.8%
제 29
 
3.4%
동 26
 
3.1%
리 20
 
2.4%
구 19
 
2.2%
거 19
 
2.2%
은 17
 
2.0%
Other values (168) 557
65.6%
Decimal Number
ValueCountFrequency (%)
2 20
29.0%
1 18
26.1%
3 12
17.4%
4 7
 
10.1%
9 4
 
5.8%
0 2
 
2.9%
7 2
 
2.9%
5 2
 
2.9%
6 2
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
K 2
18.2%
E 2
18.2%
V 1
9.1%
W 1
9.1%
D 1
9.1%
L 1
9.1%
I 1
9.1%
Other Punctuation
ValueCountFrequency (%)
. 4
80.0%
* 1
 
20.0%
Space Separator
ValueCountFrequency (%)
138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 849
73.2%
Common 300
 
25.9%
Latin 11
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 60
 
7.1%
시 36
 
4.2%
앞 34
 
4.0%
게 32
 
3.8%
제 29
 
3.4%
동 26
 
3.1%
리 20
 
2.4%
구 19
 
2.2%
거 19
 
2.2%
은 17
 
2.0%
Other values (168) 557
65.6%
Common
ValueCountFrequency (%)
138
46.0%
) 42
 
14.0%
( 41
 
13.7%
2 20
 
6.7%
1 18
 
6.0%
3 12
 
4.0%
4 7
 
2.3%
- 5
 
1.7%
. 4
 
1.3%
9 4
 
1.3%
Other values (5) 9
 
3.0%
Latin
ValueCountFrequency (%)
S 2
18.2%
K 2
18.2%
E 2
18.2%
V 1
9.1%
W 1
9.1%
D 1
9.1%
L 1
9.1%
I 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 849
73.2%
ASCII 311
 
26.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138
44.4%
) 42
 
13.5%
( 41
 
13.2%
2 20
 
6.4%
1 18
 
5.8%
3 12
 
3.9%
4 7
 
2.3%
- 5
 
1.6%
. 4
 
1.3%
9 4
 
1.3%
Other values (13) 20
 
6.4%
Hangul
ValueCountFrequency (%)
대 60
 
7.1%
시 36
 
4.2%
앞 34
 
4.0%
게 32
 
3.8%
제 29
 
3.4%
동 26
 
3.1%
리 20
 
2.4%
구 19
 
2.2%
거 19
 
2.2%
은 17
 
2.0%
Other values (168) 557
65.6%

주소
Text

Distinct52
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T01:57:44.628613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length250
Mean length175.71831
Min length15

Characters and Unicode

Total characters12476
Distinct characters42
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

Unique36 ?
Unique (%)50.7%

Sample

1st row부산광역시 남구 감만동 75-56
2nd row부산광역시 남구 감만동 84-21
3rd row부산광역시 남구 감만동 51-8
4th row부산광역시 남구 석포로 32-1
5th row부산광역시 남구 석포로 32-1
ValueCountFrequency (%)
부산광역시 71
24.8%
남구 71
24.8%
대연동 27
 
9.4%
용호동 11
 
3.8%
용당동 10
 
3.5%
문현동 10
 
3.5%
172-18 5
 
1.7%
1872 3
 
1.0%
우암동 3
 
1.0%
감만동 3
 
1.0%
Other values (54) 72
25.2%
2023-12-11T01:57:45.177727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11412
91.5%
1 73
 
0.6%
산 72
 
0.6%
부 71
 
0.6%
광 71
 
0.6%
역 71
 
0.6%
시 71
 
0.6%
남 71
 
0.6%
구 71
 
0.6%
동 64
 
0.5%
Other values (32) 429
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 11412
91.5%
Other Letter 716
 
5.7%
Decimal Number 292
 
2.3%
Dash Punctuation 56
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 72
10.1%
부 71
9.9%
광 71
9.9%
역 71
9.9%
시 71
9.9%
남 71
9.9%
구 71
9.9%
동 64
8.9%
연 27
 
3.8%
대 27
 
3.8%
Other values (20) 100
14.0%
Decimal Number
ValueCountFrequency (%)
1 73
25.0%
2 39
13.4%
8 31
10.6%
3 28
 
9.6%
4 25
 
8.6%
5 22
 
7.5%
7 22
 
7.5%
9 21
 
7.2%
6 20
 
6.8%
0 11
 
3.8%
Space Separator
ValueCountFrequency (%)
11412
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11760
94.3%
Hangul 716
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 72
10.1%
부 71
9.9%
광 71
9.9%
역 71
9.9%
시 71
9.9%
남 71
9.9%
구 71
9.9%
동 64
8.9%
연 27
 
3.8%
대 27
 
3.8%
Other values (20) 100
14.0%
Common
ValueCountFrequency (%)
11412
97.0%
1 73
 
0.6%
- 56
 
0.5%
2 39
 
0.3%
8 31
 
0.3%
3 28
 
0.2%
4 25
 
0.2%
5 22
 
0.2%
7 22
 
0.2%
9 21
 
0.2%
Other values (2) 31
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11760
94.3%
Hangul 716
 
5.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11412
97.0%
1 73
 
0.6%
- 56
 
0.5%
2 39
 
0.3%
8 31
 
0.3%
3 28
 
0.2%
4 25
 
0.2%
5 22
 
0.2%
7 22
 
0.2%
9 21
 
0.2%
Other values (2) 31
 
0.3%
Hangul
ValueCountFrequency (%)
산 72
10.1%
부 71
9.9%
광 71
9.9%
역 71
9.9%
시 71
9.9%
남 71
9.9%
구 71
9.9%
동 64
8.9%
연 27
 
3.8%
대 27
 
3.8%
Other values (20) 100
14.0%

특징
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
탱탱이 걸이식(좌측고정)
71 

Length

Max length13
Median length13
Mean length13
Min length13

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) 71
100.0%

Length

2023-12-11T01:57:45.412971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:45.570758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
탱탱이 71
50.0%
걸이식(좌측고정 71
50.0%

규격
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
6.0*0.7
50 
7.0*0.9
17 
6.5*0.9
 
2
7.0*0.7
 
1
6.3*1.2
 
1

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique2 ?
Unique (%)2.8%

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 50
70.4%
7.0*0.9 17
 
23.9%
6.5*0.9 2
 
2.8%
7.0*0.7 1
 
1.4%
6.3*1.2 1
 
1.4%

Length

2023-12-11T01:57:45.728487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:45.892948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6.0*0.7 50
70.4%
7.0*0.9 17
 
23.9%
6.5*0.9 2
 
2.8%
7.0*0.7 1
 
1.4%
6.3*1.2 1
 
1.4%

부착면수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2
22 
1
20 
5
17 
3
11 
6
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row5
2nd row2
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 22
31.0%
1 20
28.2%
5 17
23.9%
3 11
15.5%
6 1
 
1.4%

Length

2023-12-11T01:57:46.045464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:46.216626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 22
31.0%
1 20
28.2%
5 17
23.9%
3 11
15.5%
6 1
 
1.4%

부착제한일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
10
71 

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 71
100.0%

Length

2023-12-11T01:57:46.378739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:46.515328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 71
100.0%

민원수수료
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
10000
45 
0
26 

Length

Max length5
Median length5
Mean length3.5352113
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10000 45
63.4%
0 26
36.6%

Length

2023-12-11T01:57:46.702061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:46.894996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10000 45
63.4%
0 26
36.6%

점용료
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
1260
26 
0
26 
1890
16 
1755
 
2
1470
 
1

Length

Max length4
Median length4
Mean length2.9014085
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row1890
2nd row1260
3rd row1260
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1260 26
36.6%
0 26
36.6%
1890 16
22.5%
1755 2
 
2.8%
1470 1
 
1.4%

Length

2023-12-11T01:57:47.385452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:47.563171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1260 26
36.6%
0 26
36.6%
1890 16
22.5%
1755 2
 
2.8%
1470 1
 
1.4%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
051-607-4626
71 

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 71
100.0%

Length

2023-12-11T01:57:47.760674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:47.901240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-607-4626 71
100.0%

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
부산광역시 남구
71 

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 71
100.0%

Length

2023-12-11T01:57:48.052978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:48.200475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 71
50.0%
남구 71
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
2021-06-28
71 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-06-28
2nd row2021-06-28
3rd row2021-06-28
4th row2021-06-28
5th row2021-06-28

Common Values

ValueCountFrequency (%)
2021-06-28 71
100.0%

Length

2023-12-11T01:57:48.347658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:57:48.503720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-06-28 71
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.130423
Minimum35.1
Maximum35.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T01:57:48.640024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.01139381
Coefficient of variation (CV)0.00032432887
Kurtosis1.284704
Mean35.130423
Median Absolute Deviation (MAD)0.01
Skewness0.45194101
Sum2494.26
Variance0.00012981891
MonotonicityNot monotonic
2023-12-11T01:57:48.820116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
35.13 24
33.8%
35.12 21
29.6%
35.14 17
23.9%
35.15 5
 
7.0%
35.11 2
 
2.8%
35.17 1
 
1.4%
35.1 1
 
1.4%
ValueCountFrequency (%)
35.1 1
 
1.4%
35.11 2
 
2.8%
35.12 21
29.6%
35.13 24
33.8%
35.14 17
23.9%
35.15 5
 
7.0%
35.17 1
 
1.4%
ValueCountFrequency (%)
35.17 1
 
1.4%
35.15 5
 
7.0%
35.14 17
23.9%
35.13 24
33.8%
35.12 21
29.6%
35.11 2
 
2.8%
35.1 1
 
1.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.09193
Minimum129.06418
Maximum129.11576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T01:57:49.036100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.06418
5-th percentile129.06802
Q1129.082
median129.09223
Q3129.10066
95-th percentile129.11436
Maximum129.11576
Range0.0515817
Interquartile range (IQR)0.01866685

Descriptive statistics

Standard deviation0.013798564
Coefficient of variation (CV)0.00010688944
Kurtosis-0.84318157
Mean129.09193
Median Absolute Deviation (MAD)0.0097489
Skewness-0.16011837
Sum9165.5273
Variance0.00019040037
MonotonicityNot monotonic
2023-12-11T01:57:49.263197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1143634 4
 
5.6%
129.0903983 3
 
4.2%
129.100254 3
 
4.2%
129.098535 2
 
2.8%
129.08443 2
 
2.8%
129.092056 2
 
2.8%
129.0931872 2
 
2.8%
129.0973949 2
 
2.8%
129.0978175 2
 
2.8%
129.0815124 2
 
2.8%
Other values (41) 47
66.2%
ValueCountFrequency (%)
129.0641817 1
1.4%
129.066676 1
1.4%
129.067675 1
1.4%
129.068023 2
2.8%
129.0699938 1
1.4%
129.072471 1
1.4%
129.0733207 1
1.4%
129.073657 1
1.4%
129.0739595 2
2.8%
129.0739596 1
1.4%
ValueCountFrequency (%)
129.1157634 1
 
1.4%
129.1143634 4
5.6%
129.112343 1
 
1.4%
129.1116617 1
 
1.4%
129.110065 1
 
1.4%
129.109865 1
 
1.4%
129.109179 1
 
1.4%
129.109106 1
 
1.4%
129.106744 1
 
1.4%
129.1058734 1
 
1.4%

Interactions

2023-12-11T01:57:42.120370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:41.613021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:42.366099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:57:41.821457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:57:49.384365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동위치주소규격부착면수민원수수료점용료위도경도
행정동1.0001.0000.9980.0000.6330.6080.2170.8670.875
위치1.0001.0000.9920.9710.9450.0000.9491.0001.000
주소0.9980.9921.0000.0000.8220.7830.7901.0001.000
규격0.0000.9710.0001.0000.9430.3030.9890.3120.568
부착면수0.6330.9450.8220.9431.0000.5760.9660.2500.671
민원수수료0.6080.0000.7830.3030.5761.0001.0000.1260.331
점용료0.2170.9490.7900.9890.9661.0001.0000.3750.510
위도0.8671.0001.0000.3120.2500.1260.3751.0000.353
경도0.8751.0001.0000.5680.6710.3310.5100.3531.000
2023-12-11T01:57:49.626824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동규격점용료부착면수민원수수료
행정동1.0000.0000.0850.3480.486
규격0.0001.0000.8490.6660.361
점용료0.0850.8491.0000.7360.978
부착면수0.3480.6660.7361.0000.681
민원수수료0.4860.3610.9780.6811.000
2023-12-11T01:57:49.758455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정동규격부착면수민원수수료점용료
위도1.000-0.1770.5780.1990.1560.1250.245
경도-0.1771.0000.5590.2440.3250.2520.213
행정동0.5780.5591.0000.0000.3480.4860.085
규격0.1990.2440.0001.0000.6660.3610.849
부착면수0.1560.3250.3480.6661.0000.6810.736
민원수수료0.1250.2520.4860.3610.6811.0000.978
점용료0.2450.2130.0850.8490.7360.9781.000

Missing values

2023-12-11T01:57:42.660906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:57:42.981192image/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 남구2021-06-2835.12129.07396
1부산광역시 남구청감만제1동수영돼지국밥 앞부산광역시 남구 감만동 84-21탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-06-2835.12129.080185
2부산광역시 남구청감만제2동홈플러스 감만점 건너편부산광역시 남구 감만동 51-8탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-06-2835.12129.080734
3부산광역시 남구청감만제2동감만2동행정복지센터 앞(좌)부산광역시 남구 석포로 32-1탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2021-06-2835.12129.084558
4부산광역시 남구청감만제2동감만2동행정복지센터 앞(우)부산광역시 남구 석포로 32-1탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2021-06-2835.12129.084558
5부산광역시 남구청대연제1동대연동 사거리 부산은행 앞(제1게시대)부산광역시 남구 대연동 1740-8탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-06-2835.13129.092227
6부산광역시 남구청대연제1동대연동 사거리 부산은행 앞(제2게시대)부산광역시 남구 대연동 1740-8탱탱이 걸이식(좌측고정)6.0*0.721000051-607-4626부산광역시 남구2021-06-2835.13129.092227
7부산광역시 남구청대연제1동못골지하철역 3번출구(제1게시대)부산광역시 남구 수영로 158 앞탱탱이 걸이식(좌측고정)6.0*0.721000051-607-4626부산광역시 남구2021-06-2835.13129.083952
8부산광역시 남구청대연제1동못골지하철역 3번출구(제2게시대)부산광역시 남구 수영로 158 앞탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2021-06-2835.13129.083952
9부산광역시 남구청대연제3동경성대부경대역 4번출구부산광역시 남구 대연동 73-8탱탱이 걸이식(좌측고정)6.0*0.7210100001260051-607-4626부산광역시 남구2021-06-2835.14129.099916
관리기관명행정동위치주소특징규격부착면수부착제한일민원수수료점용료관리기관전화번호구군명데이터기준일자위도경도
61부산광역시 남구청용호제2동오륙도 SK VIEW 아파트 입구(늘빛교회 맞은편)부산광역시 남구 용호동 894-3탱탱이 걸이식(좌측고정)7.0*0.9310100001890051-607-4626부산광역시 남구2021-06-2835.11129.111662
62부산광역시 남구청용호제3동용호지구대 맞은편 제1게시대(좌측)부산광역시 남구 용호동 172-18탱탱이 걸이식(좌측고정)6.0*0.7310100001260051-607-4626부산광역시 남구2021-06-2835.13129.114363
63부산광역시 남구청용호제3동용호지구대 맞은편 제2게시대(우측-용호복지관 쪽)-맨 오른쪽)부산광역시 남구 용호동 172-18탱탱이 걸이식(좌측고정)6.0*0.7310100001260051-607-4626부산광역시 남구2021-06-2835.13129.114363
64부산광역시 남구청용호제3동용호지구대 맞은편 제3게시대(광안대교 쪽)부산광역시 남구 용호동 172-18탱탱이 걸이식(좌측고정)6.0*0.7310100001260051-607-4626부산광역시 남구2021-06-2835.13129.114363
65부산광역시 남구청용호제3동용호지구대 맞은편 제4게시대(광안대교 쪽)-맨 왼쪽부산광역시 남구 용호동 172-18탱탱이 걸이식(좌측고정)6.0*0.731000051-607-4626부산광역시 남구2021-06-2835.13129.114363
66부산광역시 남구청용호제4동백운포 체육공원 주차장부산광역시 남구 용호동 895-3탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2021-06-2835.1129.109865
67부산광역시 남구청용호제4동성모병원 주차장 입구 옆부산광역시 남구 용호동 538-41탱탱이 걸이식(좌측고정)6.0*0.711000051-607-4626부산광역시 남구2021-06-2835.11129.109179
68부산광역시 남구청우암동뉴서울아파트 앞부산광역시 남구 우암동 53-1탱탱이 걸이식(좌측고정)7.0*0.9510100001890051-607-4626부산광역시 남구2021-06-2835.12129.079691
69부산광역시 남구청우암동새마을금고(구.부산은행) 맞은편(제1게시대)부산광역시 남구 우암동 184-250탱탱이 걸이식(좌측고정)7.0*0.9510100001890051-607-4626부산광역시 남구2021-06-2835.12129.07396
70부산광역시 남구청우암동새마을금고(구.부산은행) 맞은편(제2게시대)부산광역시 남구 우암동 184-250탱탱이 걸이식(좌측고정)7.0*0.9510100001890051-607-4626부산광역시 남구2021-06-2835.12129.07396