Overview

Dataset statistics

Number of variables5
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1014.0 B
Average record size in memory48.3 B

Variable types

Text2
Numeric2
Categorical1

Dataset

Description부산광역시 중구 불법주정차 무인단속 카메라 현황자료 입니다. 불법 주정차 무인단속 카메라 설치 위치, 위도, 경도 등을 포함하고 있습니다.
Author부산광역시 중구
URLhttps://www.data.go.kr/data/15092748/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
명칭 has unique valuesUnique
주소 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:26:46.394914
Analysis finished2023-12-16 15:26:50.942017
Duration4.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-16T15:26:51.560939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length9.4761905
Min length5

Characters and Unicode

Total characters199
Distinct characters91
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

Unique21 ?
Unique (%)100.0%

Sample

1st row국제시장 로뎀나무 앞
2nd row수협 남포동지점 부근
3rd row건강의료기 앞
4th row제창주차장 옆
5th row중앙아파트
ValueCountFrequency (%)
앞 14
26.4%
국제시장 2
 
3.8%
부산터널 2
 
3.8%
남포동 2
 
3.8%
남포동지점 1
 
1.9%
다이소 1
 
1.9%
자갈치공영주차장 1
 
1.9%
교통섬 1
 
1.9%
삼거리 1
 
1.9%
일대 1
 
1.9%
Other values (27) 27
50.9%
2023-12-16T15:26:53.624083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
16.1%
앞 16
 
8.0%
장 7
 
3.5%
리 5
 
2.5%
주 5
 
2.5%
차 4
 
2.0%
거 4
 
2.0%
사 4
 
2.0%
남 4
 
2.0%
포 4
 
2.0%
Other values (81) 114
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
81.9%
Space Separator 32
 
16.1%
Close Punctuation 2
 
1.0%
Open Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 16
 
9.8%
장 7
 
4.3%
리 5
 
3.1%
주 5
 
3.1%
차 4
 
2.5%
거 4
 
2.5%
사 4
 
2.5%
남 4
 
2.5%
포 4
 
2.5%
동 4
 
2.5%
Other values (78) 106
65.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
81.9%
Common 36
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 16
 
9.8%
장 7
 
4.3%
리 5
 
3.1%
주 5
 
3.1%
차 4
 
2.5%
거 4
 
2.5%
사 4
 
2.5%
남 4
 
2.5%
포 4
 
2.5%
동 4
 
2.5%
Other values (78) 106
65.0%
Common
ValueCountFrequency (%)
32
88.9%
) 2
 
5.6%
( 2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
81.9%
ASCII 36
 
18.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
88.9%
) 2
 
5.6%
( 2
 
5.6%
Hangul
ValueCountFrequency (%)
앞 16
 
9.8%
장 7
 
4.3%
리 5
 
3.1%
주 5
 
3.1%
차 4
 
2.5%
거 4
 
2.5%
사 4
 
2.5%
남 4
 
2.5%
포 4
 
2.5%
동 4
 
2.5%
Other values (78) 106
65.0%

주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-16T15:26:54.321193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length18.809524
Min length15

Characters and Unicode

Total characters395
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row부산광역시 중구 중구로 42(신창동4가)
2nd row부산광역시 중구 용미길10번길 3(남포동1가)
3rd row부산광역시 중구 보수대로 20
4th row부산광역시 중구 자갈치로59번길 1
5th row부산광역시 중구 광복중앙로 31
ValueCountFrequency (%)
부산광역시 21
25.0%
중구 21
25.0%
중구로 3
 
3.6%
1 2
 
2.4%
구덕로 2
 
2.4%
15 1
 
1.2%
54-2(부평동2가 1
 
1.2%
대청로 1
 
1.2%
73 1
 
1.2%
영주동 1
 
1.2%
Other values (30) 30
35.7%
2023-12-16T15:26:55.876441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
15.9%
중 27
 
6.8%
구 26
 
6.6%
부 23
 
5.8%
광 22
 
5.6%
역 21
 
5.3%
시 21
 
5.3%
산 21
 
5.3%
1 16
 
4.1%
로 15
 
3.8%
Other values (39) 140
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
63.8%
Decimal Number 66
 
16.7%
Space Separator 63
 
15.9%
Dash Punctuation 6
 
1.5%
Close Punctuation 4
 
1.0%
Open Punctuation 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 27
10.7%
구 26
10.3%
부 23
 
9.1%
광 22
 
8.7%
역 21
 
8.3%
시 21
 
8.3%
산 21
 
8.3%
로 15
 
6.0%
동 10
 
4.0%
가 8
 
3.2%
Other values (25) 58
23.0%
Decimal Number
ValueCountFrequency (%)
1 16
24.2%
2 13
19.7%
3 10
15.2%
4 5
 
7.6%
7 4
 
6.1%
5 4
 
6.1%
6 4
 
6.1%
0 4
 
6.1%
8 3
 
4.5%
9 3
 
4.5%
Space Separator
ValueCountFrequency (%)
63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
63.8%
Common 143
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 27
10.7%
구 26
10.3%
부 23
 
9.1%
광 22
 
8.7%
역 21
 
8.3%
시 21
 
8.3%
산 21
 
8.3%
로 15
 
6.0%
동 10
 
4.0%
가 8
 
3.2%
Other values (25) 58
23.0%
Common
ValueCountFrequency (%)
63
44.1%
1 16
 
11.2%
2 13
 
9.1%
3 10
 
7.0%
- 6
 
4.2%
4 5
 
3.5%
7 4
 
2.8%
5 4
 
2.8%
) 4
 
2.8%
6 4
 
2.8%
Other values (4) 14
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
63.8%
ASCII 143
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
44.1%
1 16
 
11.2%
2 13
 
9.1%
3 10
 
7.0%
- 6
 
4.2%
4 5
 
3.5%
7 4
 
2.8%
5 4
 
2.8%
) 4
 
2.8%
6 4
 
2.8%
Other values (4) 14
 
9.8%
Hangul
ValueCountFrequency (%)
중 27
10.7%
구 26
10.3%
부 23
 
9.1%
광 22
 
8.7%
역 21
 
8.3%
시 21
 
8.3%
산 21
 
8.3%
로 15
 
6.0%
동 10
 
4.0%
가 8
 
3.2%
Other values (25) 58
23.0%

위도
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.101853
Minimum35.09667
Maximum35.11298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-16T15:26:56.520724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.09667
5-th percentile35.09693
Q135.09803
median35.10101
Q335.10329
95-th percentile35.11203
Maximum35.11298
Range0.01631
Interquartile range (IQR)0.00526

Descriptive statistics

Standard deviation0.0047398052
Coefficient of variation (CV)0.00013503006
Kurtosis0.58062799
Mean35.101853
Median Absolute Deviation (MAD)0.00298
Skewness1.0937493
Sum737.13892
Variance2.2465753 × 10-5
MonotonicityNot monotonic
2023-12-16T15:26:57.177398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
35.10157 1
 
4.8%
35.09693 1
 
4.8%
35.09667 1
 
4.8%
35.11203 1
 
4.8%
35.09763 1
 
4.8%
35.10329 1
 
4.8%
35.0975 1
 
4.8%
35.10101 1
 
4.8%
35.09941 1
 
4.8%
35.10307 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
35.09667 1
4.8%
35.09693 1
4.8%
35.0975 1
4.8%
35.09763 1
4.8%
35.09765 1
4.8%
35.09803 1
4.8%
35.09805 1
4.8%
35.0988 1
4.8%
35.09941 1
4.8%
35.10029 1
4.8%
ValueCountFrequency (%)
35.11298 1
4.8%
35.11203 1
4.8%
35.10763 1
4.8%
35.10641 1
4.8%
35.10503 1
4.8%
35.10329 1
4.8%
35.10307 1
4.8%
35.10282 1
4.8%
35.10212 1
4.8%
35.10157 1
4.8%

경도
Real number (ℝ)

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.03102
Minimum129.02518
Maximum129.03754
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-16T15:26:58.268224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.02518
5-th percentile129.02518
Q1129.02788
median129.0317
Q3129.0345
95-th percentile129.03665
Maximum129.03754
Range0.01236
Interquartile range (IQR)0.00662

Descriptive statistics

Standard deviation0.0039286218
Coefficient of variation (CV)3.044711 × 10-5
Kurtosis-1.2311384
Mean129.03102
Median Absolute Deviation (MAD)0.0036
Skewness-0.054852799
Sum2709.6515
Variance1.5434069 × 10-5
MonotonicityNot monotonic
2023-12-16T15:26:58.901435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
129.02518 2
 
9.5%
129.0281 1
 
4.8%
129.03208 1
 
4.8%
129.02691 1
 
4.8%
129.0345 1
 
4.8%
129.03399 1
 
4.8%
129.02766 1
 
4.8%
129.02519 1
 
4.8%
129.02788 1
 
4.8%
129.0279 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
129.02518 2
9.5%
129.02519 1
4.8%
129.02691 1
4.8%
129.02766 1
4.8%
129.02788 1
4.8%
129.0279 1
4.8%
129.0281 1
4.8%
129.03058 1
4.8%
129.03061 1
4.8%
129.0317 1
4.8%
ValueCountFrequency (%)
129.03754 1
4.8%
129.03665 1
4.8%
129.03556 1
4.8%
129.03496 1
4.8%
129.03453 1
4.8%
129.0345 1
4.8%
129.03399 1
4.8%
129.03306 1
4.8%
129.03208 1
4.8%
129.03171 1
4.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-11-30
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-30
2nd row2023-11-30
3rd row2023-11-30
4th row2023-11-30
5th row2023-11-30

Common Values

ValueCountFrequency (%)
2023-11-30 21
100.0%

Length

2023-12-16T15:26:59.626404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:27:00.443575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-30 21
100.0%

Interactions

2023-12-16T15:26:48.411331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:26:47.129709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:26:49.211849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:26:47.612505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:27:00.824489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭주소위도경도
명칭1.0001.0001.0001.000
주소1.0001.0001.0001.000
위도1.0001.0001.0000.646
경도1.0001.0000.6461.000
2023-12-16T15:27:01.539587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.218
경도0.2181.000

Missing values

2023-12-16T15:26:50.039857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:26:50.606802image/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

명칭주소위도경도데이터기준일자
0국제시장 로뎀나무 앞부산광역시 중구 중구로 42(신창동4가)35.10157129.02812023-11-30
1수협 남포동지점 부근부산광역시 중구 용미길10번길 3(남포동1가)35.09693129.034532023-11-30
2건강의료기 앞부산광역시 중구 보수대로 2035.0988129.025182023-11-30
3제창주차장 옆부산광역시 중구 자갈치로59번길 135.09765129.030582023-11-30
4중앙아파트부산광역시 중구 광복중앙로 3135.10212129.030612023-11-30
5메리놀병원 앞부산광역시 중구 중구로 12135.10763129.033062023-11-30
6부산터널 위부산광역시 중구 동영로93번길 335.11298129.031712023-11-30
7고려화공 인도 앞부산광역시 중구 충장대로13번길 935.10641129.037542023-11-30
8반도빌딩 앞부산광역시 중구 중앙대로81번길 10-135.10503129.035562023-11-30
9롯데주차장 앞부산광역시 중구 중앙대로42번길 235.10029129.036652023-11-30
명칭주소위도경도데이터기준일자
11남포동 미니몰 앞(남포동 다이소 앞)부산광역시 중구 남포동4가 37-235.09803129.032082023-11-30
12필드모아 앞(용두산 공영주차장 앞)부산광역시 중구 대청동2가 10635.10282129.03172023-11-30
13대청사거리 앞부산광역시 중구 대청동3가 7-3635.10307129.02792023-11-30
14국제시장 사거리부산광역시 중구 중구로 16-135.09941129.027882023-11-30
15홍일한의원 앞부산광역시 중구 부평동2가 82(흑교로)35.10101129.025192023-11-30
16남포동 농협 앞부산광역시 중구 구덕로 7335.0975129.027662023-11-30
17보수사거리 아카데미사진관 앞부산광역시 중구 대청로 54-2(부평동2가)35.10329129.025182023-11-30
18건어물시장 일대부산광역시 중구 구덕로 1535.09763129.033992023-11-30
19부산터널 삼거리 교통섬 앞부산광역시 중구 영주동 58-235.11203129.03452023-11-30
20자갈치공영주차장 주변부산광역시 중구 자갈치로23번길 135.09667129.026912023-11-30