Overview

Dataset statistics

Number of variables9
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory81.4 B

Variable types

Numeric2
Categorical6
Text1

Dataset

Description부산광역시 북구 관내에 위치한 현수막 지정게시대에 대한 데이터로 (행정동, 위치, 특징, 규격 ,수수료 등)을 포함하고 있습니다.
Author부산광역시 북구
URLhttps://www.data.go.kr/data/15021080/fileData.do

Alerts

부착제한일 has constant value ""Constant
민원수수료 has constant value ""Constant
번호 is highly overall correlated with 행정동High correlation
일일도로점용료 is highly overall correlated with 특징 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 번호High correlation
특징 is highly overall correlated with 일일도로점용료 and 1 other fieldsHigh correlation
규격 is highly overall correlated with 일일도로점용료 and 1 other fieldsHigh correlation
번호 has unique valuesUnique
위치 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:04:51.783388
Analysis finished2024-03-14 12:04:53.938567
Duration2.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size389.0 B
2024-03-14T21:04:54.114773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2024-03-14T21:04:54.507944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

행정동
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Memory size360.0 B
화명제3동
9 
금곡동
5 
구포제2동
3 
구포제1동
2 
구포제3동
2 
Other values (5)
8 

Length

Max length5
Median length5
Mean length4.6551724
Min length3

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row구포제1동
2nd row구포제1동
3rd row구포제2동
4th row구포제2동
5th row구포제2동

Common Values

ValueCountFrequency (%)
화명제3동 9
31.0%
금곡동 5
17.2%
구포제2동 3
 
10.3%
구포제1동 2
 
6.9%
구포제3동 2
 
6.9%
덕천제2동 2
 
6.9%
만덕제2동 2
 
6.9%
화명제1동 2
 
6.9%
만덕제3동 1
 
3.4%
화명제2동 1
 
3.4%

Length

2024-03-14T21:04:54.957215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:04:55.336517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화명제3동 9
31.0%
금곡동 5
17.2%
구포제2동 3
 
10.3%
구포제1동 2
 
6.9%
구포제3동 2
 
6.9%
덕천제2동 2
 
6.9%
만덕제2동 2
 
6.9%
화명제1동 2
 
6.9%
만덕제3동 1
 
3.4%
화명제2동 1
 
3.4%

위치
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size360.0 B
2024-03-14T21:04:56.311577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length18
Mean length13.172414
Min length4

Characters and Unicode

Total characters382
Distinct characters127
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

Unique29 ?
Unique (%)100.0%

Sample

1st row구포동 247-1번지 일원(동원로얄듀크비스타 맞은편),사다리필수(높음)
2nd row백양삼거리
3rd row구남역2번출구(구 구포삼정그린코아)
4th row구포삼거리(북구청 방향에서 오른쪽)
5th row구포삼거리(북구청 방향에서 왼쪽)
ValueCountFrequency (%)
구포동 2
 
4.1%
구포삼거리(북구청 2
 
4.1%
방향에서 2
 
4.1%
성훈강변아파트 2
 
4.1%
용수중학교앞 1
 
2.0%
북부산우체국옆도로변(공공청사예정부지앞도로변 1
 
2.0%
맞은편(2 1
 
2.0%
만덕삼성아파트입구 1
 
2.0%
신광주유소 1
 
2.0%
입구 1
 
2.0%
Other values (35) 35
71.4%
2024-03-14T21:04:57.658649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
5.2%
구 18
 
4.7%
( 12
 
3.1%
) 12
 
3.1%
로 9
 
2.4%
리 9
 
2.4%
2 9
 
2.4%
변 8
 
2.1%
앞 7
 
1.8%
삼 7
 
1.8%
Other values (117) 271
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 302
79.1%
Decimal Number 27
 
7.1%
Space Separator 20
 
5.2%
Open Punctuation 12
 
3.1%
Close Punctuation 12
 
3.1%
Uppercase Letter 6
 
1.6%
Dash Punctuation 2
 
0.5%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 18
 
6.0%
로 9
 
3.0%
리 9
 
3.0%
변 8
 
2.6%
앞 7
 
2.3%
삼 7
 
2.3%
거 7
 
2.3%
포 7
 
2.3%
동 7
 
2.3%
도 6
 
2.0%
Other values (102) 217
71.9%
Decimal Number
ValueCountFrequency (%)
2 9
33.3%
1 6
22.2%
4 4
14.8%
0 3
 
11.1%
7 2
 
7.4%
8 2
 
7.4%
6 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
33.3%
T 2
33.3%
P 2
33.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 302
79.1%
Common 74
 
19.4%
Latin 6
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 18
 
6.0%
로 9
 
3.0%
리 9
 
3.0%
변 8
 
2.6%
앞 7
 
2.3%
삼 7
 
2.3%
거 7
 
2.3%
포 7
 
2.3%
동 7
 
2.3%
도 6
 
2.0%
Other values (102) 217
71.9%
Common
ValueCountFrequency (%)
20
27.0%
( 12
16.2%
) 12
16.2%
2 9
12.2%
1 6
 
8.1%
4 4
 
5.4%
0 3
 
4.1%
- 2
 
2.7%
7 2
 
2.7%
8 2
 
2.7%
Other values (2) 2
 
2.7%
Latin
ValueCountFrequency (%)
A 2
33.3%
T 2
33.3%
P 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 302
79.1%
ASCII 80
 
20.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
25.0%
( 12
15.0%
) 12
15.0%
2 9
11.2%
1 6
 
7.5%
4 4
 
5.0%
0 3
 
3.8%
A 2
 
2.5%
T 2
 
2.5%
P 2
 
2.5%
Other values (5) 8
 
10.0%
Hangul
ValueCountFrequency (%)
구 18
 
6.0%
로 9
 
3.0%
리 9
 
3.0%
변 8
 
2.6%
앞 7
 
2.3%
삼 7
 
2.3%
거 7
 
2.3%
포 7
 
2.3%
동 7
 
2.3%
도 6
 
2.0%
Other values (102) 217
71.9%

특징
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Memory size360.0 B
탱탱이형,우측고정
9 
접이형,좌측고정
5 
탱탱이형, 우측고정
5 
접이형, 좌측 고정
2 
탱탱이형, 좌측고정
1 
Other values (7)
7 

Length

Max length11
Median length10
Mean length9.1034483
Min length8

Unique

Unique8 ?
Unique (%)27.6%

Sample

1st row접이형,좌측고정
2nd row탱탱이형, 좌측고정
3rd row탱탱이형, 우측고정
4th row접이형, 좌측 고정
5th row접이형.우측고정

Common Values

ValueCountFrequency (%)
탱탱이형,우측고정 9
31.0%
접이형,좌측고정 5
17.2%
탱탱이형, 우측고정 5
17.2%
접이형, 좌측 고정 2
 
6.9%
탱탱이형, 좌측고정 1
 
3.4%
접이형.우측고정 1
 
3.4%
반접이형, 좌측고정 1
 
3.4%
접이형, 우측고정 1
 
3.4%
탱탱이형, 우측 고정 1
 
3.4%
탱탱이식,우측고정 1
 
3.4%
Other values (2) 2
 
6.9%

Length

2024-03-14T21:04:58.088661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
탱탱이형,우측고정 9
20.9%
탱탱이형 7
16.3%
우측고정 6
14.0%
접이형,좌측고정 5
11.6%
접이형 3
 
7.0%
고정 3
 
7.0%
좌측 2
 
4.7%
좌측고정 2
 
4.7%
접이형.우측고정 1
 
2.3%
반접이형 1
 
2.3%
Other values (4) 4
9.3%

규격
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size360.0 B
도안크기 5.9*0.9
11 
도안크기 5.8*0.9
6 
도안크기 6*0.7
4 
도안크기 6.0*0.9
2 
도안크기 5.6*0.9
2 
Other values (3)
4 

Length

Max length12
Median length12
Mean length11.724138
Min length10

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row도안크기 6*0.7
2nd row도안크기 5.8*0.9
3rd row도안크기 5.8*0.9
4th row도안크기 6.0*0.9
5th row도안크기 5.6*0.9

Common Values

ValueCountFrequency (%)
도안크기 5.9*0.9 11
37.9%
도안크기 5.8*0.9 6
20.7%
도안크기 6*0.7 4
 
13.8%
도안크기 6.0*0.9 2
 
6.9%
도안크기 5.6*0.9 2
 
6.9%
도안크기 5.7*0.9 2
 
6.9%
도안크기 5.0*0.7 1
 
3.4%
도안크기 6.0*0.7 1
 
3.4%

Length

2024-03-14T21:04:58.510581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:04:58.874913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도안크기 29
50.0%
5.9*0.9 11
 
19.0%
5.8*0.9 6
 
10.3%
6*0.7 4
 
6.9%
6.0*0.9 2
 
3.4%
5.6*0.9 2
 
3.4%
5.7*0.9 2
 
3.4%
5.0*0.7 1
 
1.7%
6.0*0.7 1
 
1.7%

부착면수
Categorical

Distinct5
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size360.0 B
6
18 
5
6 
12
3 
18
 
1
4
 
1

Length

Max length2
Median length1
Mean length1.137931
Min length1

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row6
2nd row6
3rd row6
4th row5
5th row5

Common Values

ValueCountFrequency (%)
6 18
62.1%
5 6
 
20.7%
12 3
 
10.3%
18 1
 
3.4%
4 1
 
3.4%

Length

2024-03-14T21:04:59.285253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:04:59.613942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6 18
62.1%
5 6
 
20.7%
12 3
 
10.3%
18 1
 
3.4%
4 1
 
3.4%

부착제한일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size360.0 B
10
29 

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 29
100.0%

Length

2024-03-14T21:04:59.978334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:05:00.276828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 29
100.0%

민원수수료
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size360.0 B
10000
29 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10000 29
100.0%

Length

2024-03-14T21:05:00.592986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:05:00.887241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10000 29
100.0%

일일도로점용료
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1490.3448
Minimum1050
Maximum1650
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size389.0 B
2024-03-14T21:05:01.134455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1050
5-th percentile1260
Q11510
median1560
Q31590
95-th percentile1608
Maximum1650
Range600
Interquartile range (IQR)80

Descriptive statistics

Standard deviation156.62701
Coefficient of variation (CV)0.10509448
Kurtosis0.80895597
Mean1490.3448
Median Absolute Deviation (MAD)30
Skewness-1.401678
Sum43220
Variance24532.02
MonotonicityNot monotonic
2024-03-14T21:05:01.467007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1590 10
34.5%
1260 6
20.7%
1560 6
20.7%
1510 2
 
6.9%
1530 2
 
6.9%
1620 1
 
3.4%
1050 1
 
3.4%
1650 1
 
3.4%
ValueCountFrequency (%)
1050 1
 
3.4%
1260 6
20.7%
1510 2
 
6.9%
1530 2
 
6.9%
1560 6
20.7%
1590 10
34.5%
1620 1
 
3.4%
1650 1
 
3.4%
ValueCountFrequency (%)
1650 1
 
3.4%
1620 1
 
3.4%
1590 10
34.5%
1560 6
20.7%
1530 2
 
6.9%
1510 2
 
6.9%
1260 6
20.7%
1050 1
 
3.4%

Interactions

2024-03-14T21:04:52.734758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:04:52.249546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:04:52.980167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:04:52.491868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:05:01.711162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호행정동위치특징규격부착면수일일도로점용료
번호1.0000.9581.0000.5500.3310.6060.000
행정동0.9581.0001.0000.5230.0000.7180.000
위치1.0001.0001.0001.0001.0001.0001.000
특징0.5500.5231.0001.0000.8880.0000.858
규격0.3310.0001.0000.8881.0000.0000.955
부착면수0.6060.7181.0000.0000.0001.0000.376
일일도로점용료0.0000.0001.0000.8580.9550.3761.000
2024-03-14T21:05:02.008700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부착면수특징행정동규격
부착면수1.0000.0000.3200.000
특징0.0001.0000.1930.561
행정동0.3200.1931.0000.000
규격0.0000.5610.0001.000
2024-03-14T21:05:02.284011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호일일도로점용료행정동특징규격부착면수
번호1.000-0.0430.5880.0000.0000.255
일일도로점용료-0.0431.0000.0940.6620.9020.194
행정동0.5880.0941.0000.1930.0000.320
특징0.0000.6620.1931.0000.5610.000
규격0.0000.9020.0000.5611.0000.000
부착면수0.2550.1940.3200.0000.0001.000

Missing values

2024-03-14T21:04:53.317997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:04:53.768624image/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

번호행정동위치특징규격부착면수부착제한일민원수수료일일도로점용료
01구포제1동구포동 247-1번지 일원(동원로얄듀크비스타 맞은편),사다리필수(높음)접이형,좌측고정도안크기 6*0.7610100001260
12구포제1동백양삼거리탱탱이형, 좌측고정도안크기 5.8*0.9610100001560
23구포제2동구남역2번출구(구 구포삼정그린코아)탱탱이형, 우측고정도안크기 5.8*0.9610100001560
34구포제2동구포삼거리(북구청 방향에서 오른쪽)접이형, 좌측 고정도안크기 6.0*0.9510100001620
45구포제2동구포삼거리(북구청 방향에서 왼쪽)접이형.우측고정도안크기 5.6*0.9510100001510
56구포제3동시랑로 76(구포동 1218-24) (구포동 포천사거리 일원)접이형,좌측고정도안크기 6*0.7610100001260
67구포제3동홍삼당약국사거리반접이형, 좌측고정도안크기 5.0*0.7610100001050
78금곡동금곡주공2단지입구탱탱이형,우측고정도안크기 5.9*0.9610100001590
89금곡동금곡주공4단지입구탱탱이형, 우측고정도안크기 5.9*0.9610100001590
910금곡동농협하나로마트 맞은편탱탱이형, 우측고정도안크기 5.9*0.9610100001590
번호행정동위치특징규격부착면수부착제한일민원수수료일일도로점용료
1920화명제2동화신중학교 도로변탱탱이형,우측고정도안크기 5.9*0.91210100001590
2021화명제3동경부선화명역접이식,좌측고정도안크기 6*0.7610100001260
2122화명제3동롯데낙천대 108동 앞탱탱이형,우측고정도안크기 5.9*0.9410100001590
2223화명제3동북구보건소맞은편접이형,좌측고정도안크기 5.9*0.9510100001590
2324화명제3동북부경찰서입구탱탱이형,우측고정도안크기 5.9*0.9610100001590
2425화명제3동북부산우체국옆도로변(공공청사예정부지앞도로변)탱탱이형,우측고정도안크기 5.8*0.9610100001560
2526화명제3동용수중학교앞접이식,우측고정도안크기 5.7*0.9510100001530
2627화명제3동코오롱하늘채APT201동앞도로변탱탱이형,우측고정도안크기 5.6*0.9610100001510
2728화명제3동코오롱하늘채APT204동앞도로변접이형,좌측고정도안크기 6.0*0.7610100001260
2829화명제3동화명고등학교맞은편접이형,좌측고정도안크기 6*0.7610100001260