Overview

Dataset statistics

Number of variables6
Number of observations126
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory51.0 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-20484/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
현장구분 has constant value ""Constant
고정형CCTV지번주소 has unique valuesUnique
단속지점명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 10:13:20.339274
Analysis finished2024-04-06 10:13:21.650813
Duration1.31 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T19:13:22.034480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length11.68254
Min length7

Characters and Unicode

Total characters1472
Distinct characters40
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

Unique126 ?
Unique (%)100.0%

Sample

1st row대현동 56-12
2nd row대현동 37-72
3rd row신촌동 74-12
4th row대현동 101-34
5th row창천동 4-96
ValueCountFrequency (%)
서대문구 27
 
9.0%
서울 27
 
9.0%
창천동 17
 
5.7%
홍제동 13
 
4.3%
연희동 11
 
3.7%
북아현동 11
 
3.7%
남가좌동 10
 
3.3%
북가좌동 10
 
3.3%
홍은동 8
 
2.7%
남가좌2동 6
 
2.0%
Other values (138) 159
53.2%
2024-04-06T19:13:22.855882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
221
 
15.0%
동 120
 
8.2%
- 111
 
7.5%
1 103
 
7.0%
2 93
 
6.3%
3 73
 
5.0%
서 54
 
3.7%
6 51
 
3.5%
4 44
 
3.0%
5 43
 
2.9%
Other values (30) 559
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 589
40.0%
Decimal Number 551
37.4%
Space Separator 221
 
15.0%
Dash Punctuation 111
 
7.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 120
20.4%
서 54
 
9.2%
홍 38
 
6.5%
가 37
 
6.3%
대 32
 
5.4%
좌 31
 
5.3%
구 27
 
4.6%
문 27
 
4.6%
울 27
 
4.6%
북 25
 
4.2%
Other values (18) 171
29.0%
Decimal Number
ValueCountFrequency (%)
1 103
18.7%
2 93
16.9%
3 73
13.2%
6 51
9.3%
4 44
8.0%
5 43
7.8%
7 42
7.6%
8 41
 
7.4%
9 33
 
6.0%
0 28
 
5.1%
Space Separator
ValueCountFrequency (%)
221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 883
60.0%
Hangul 589
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 120
20.4%
서 54
 
9.2%
홍 38
 
6.5%
가 37
 
6.3%
대 32
 
5.4%
좌 31
 
5.3%
구 27
 
4.6%
문 27
 
4.6%
울 27
 
4.6%
북 25
 
4.2%
Other values (18) 171
29.0%
Common
ValueCountFrequency (%)
221
25.0%
- 111
12.6%
1 103
11.7%
2 93
10.5%
3 73
 
8.3%
6 51
 
5.8%
4 44
 
5.0%
5 43
 
4.9%
7 42
 
4.8%
8 41
 
4.6%
Other values (2) 61
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 883
60.0%
Hangul 589
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
221
25.0%
- 111
12.6%
1 103
11.7%
2 93
10.5%
3 73
 
8.3%
6 51
 
5.8%
4 44
 
5.0%
5 43
 
4.9%
7 42
 
4.8%
8 41
 
4.6%
Other values (2) 61
 
6.9%
Hangul
ValueCountFrequency (%)
동 120
20.4%
서 54
 
9.2%
홍 38
 
6.5%
가 37
 
6.3%
대 32
 
5.4%
좌 31
 
5.3%
구 27
 
4.6%
문 27
 
4.6%
울 27
 
4.6%
북 25
 
4.2%
Other values (18) 171
29.0%

위도
Real number (ℝ)

Distinct123
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.573613
Minimum37.555785
Maximum37.599337
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T19:13:23.199543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.555785
5-th percentile37.557514
Q137.561174
median37.575163
Q337.582037
95-th percentile37.594111
Maximum37.599337
Range0.04355159
Interquartile range (IQR)0.020863004

Descriptive statistics

Standard deviation0.012153596
Coefficient of variation (CV)0.00032346094
Kurtosis-1.0497447
Mean37.573613
Median Absolute Deviation (MAD)0.010284527
Skewness0.19510119
Sum4734.2752
Variance0.0001477099
MonotonicityNot monotonic
2024-04-06T19:13:23.571739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5915256919396 2
 
1.6%
37.5644574096506 2
 
1.6%
37.5803178219093 2
 
1.6%
37.5802559910773 1
 
0.8%
37.5765839122894 1
 
0.8%
37.5795037787514 1
 
0.8%
37.5975764 1
 
0.8%
37.5826172055294 1
 
0.8%
37.5924210723757 1
 
0.8%
37.5578762621725 1
 
0.8%
Other values (113) 113
89.7%
ValueCountFrequency (%)
37.5557853830354 1
0.8%
37.5568737550141 1
0.8%
37.5570428343671 1
0.8%
37.5572428309629 1
0.8%
37.5572617475756 1
0.8%
37.5574975793333 1
0.8%
37.5575039264551 1
0.8%
37.557542958606 1
0.8%
37.5576424521668 1
0.8%
37.557684 1
0.8%
ValueCountFrequency (%)
37.5993369726343 1
0.8%
37.598599682182 1
0.8%
37.5975764 1
0.8%
37.5969013032541 1
0.8%
37.5960511261654 1
0.8%
37.5952353 1
0.8%
37.5943090503857 1
0.8%
37.5935181997828 1
0.8%
37.5927384055554 1
0.8%
37.5924210723757 1
0.8%

경도
Real number (ℝ)

Distinct124
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.93701
Minimum126.90779
Maximum126.96691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T19:13:23.825414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.90779
5-th percentile126.91344
Q1126.92474
median126.93708
Q3126.94755
95-th percentile126.96339
Maximum126.96691
Range0.059118507
Interquartile range (IQR)0.022812586

Descriptive statistics

Standard deviation0.015075241
Coefficient of variation (CV)0.00011876159
Kurtosis-0.83290861
Mean126.93701
Median Absolute Deviation (MAD)0.011788632
Skewness0.0056080137
Sum15994.063
Variance0.00022726289
MonotonicityNot monotonic
2024-04-06T19:13:24.058562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.944881550926 2
 
1.6%
126.963706691184 2
 
1.6%
126.946796 1
 
0.8%
126.935317751294 1
 
0.8%
126.917050713943 1
 
0.8%
126.950026 1
 
0.8%
126.930626341269 1
 
0.8%
126.947387654106 1
 
0.8%
126.955310084656 1
 
0.8%
126.966770694443 1
 
0.8%
Other values (114) 114
90.5%
ValueCountFrequency (%)
126.907786957368 1
0.8%
126.908863441946 1
0.8%
126.9104672227473 1
0.8%
126.910863283399 1
0.8%
126.911127092974 1
0.8%
126.912865423017 1
0.8%
126.913418113152 1
0.8%
126.913519512815 1
0.8%
126.913590626984 1
0.8%
126.914324801258 1
0.8%
ValueCountFrequency (%)
126.966905463962 1
0.8%
126.966770694443 1
0.8%
126.964394571758 1
0.8%
126.964183411045 1
0.8%
126.963706691184 2
1.6%
126.963482597553 1
0.8%
126.96312833495502 1
0.8%
126.962236 1
0.8%
126.961881720238 1
0.8%
126.961701784061 1
0.8%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
서대문구
126 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서대문구 126
100.0%

Length

2024-04-06T19:13:24.268084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:13:24.478843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서대문구 126
100.0%

단속지점명
Text

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T19:13:24.866597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length19
Mean length11.380952
Min length5

Characters and Unicode

Total characters1434
Distinct characters209
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)100.0%

Sample

1st row이대찾고싶은거리1
2nd row이대찾고싶은거리2
3rd row신촌역광장 주변
4th row하나은행 주변
5th row쫄병부대찌개 주변
ValueCountFrequency (%)
주변 74
 
24.2%
앞 5
 
1.6%
증가로 5
 
1.6%
사거리 4
 
1.3%
정문 3
 
1.0%
북아현길 3
 
1.0%
인근 3
 
1.0%
홍은중앙길 2
 
0.7%
모래내로 2
 
0.7%
12 2
 
0.7%
Other values (194) 203
66.3%
2024-04-06T19:13:25.584324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
187
 
13.0%
주 79
 
5.5%
변 76
 
5.3%
1 37
 
2.6%
로 34
 
2.4%
길 29
 
2.0%
교 28
 
2.0%
2 27
 
1.9%
동 25
 
1.7%
가 24
 
1.7%
Other values (199) 888
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1072
74.8%
Space Separator 187
 
13.0%
Decimal Number 152
 
10.6%
Dash Punctuation 11
 
0.8%
Uppercase Letter 9
 
0.6%
Lowercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 79
 
7.4%
변 76
 
7.1%
로 34
 
3.2%
길 29
 
2.7%
교 28
 
2.6%
동 25
 
2.3%
가 24
 
2.2%
대 22
 
2.1%
초 22
 
2.1%
연 21
 
2.0%
Other values (181) 712
66.4%
Decimal Number
ValueCountFrequency (%)
1 37
24.3%
2 27
17.8%
4 17
11.2%
6 16
10.5%
3 15
9.9%
5 11
 
7.2%
9 10
 
6.6%
0 9
 
5.9%
7 6
 
3.9%
8 4
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
D 3
33.3%
C 3
33.3%
M 3
33.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
c 1
33.3%
u 1
33.3%
Space Separator
ValueCountFrequency (%)
187
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1072
74.8%
Common 350
 
24.4%
Latin 12
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 79
 
7.4%
변 76
 
7.1%
로 34
 
3.2%
길 29
 
2.7%
교 28
 
2.6%
동 25
 
2.3%
가 24
 
2.2%
대 22
 
2.1%
초 22
 
2.1%
연 21
 
2.0%
Other values (181) 712
66.4%
Common
ValueCountFrequency (%)
187
53.4%
1 37
 
10.6%
2 27
 
7.7%
4 17
 
4.9%
6 16
 
4.6%
3 15
 
4.3%
- 11
 
3.1%
5 11
 
3.1%
9 10
 
2.9%
0 9
 
2.6%
Other values (2) 10
 
2.9%
Latin
ValueCountFrequency (%)
D 3
25.0%
C 3
25.0%
M 3
25.0%
e 1
 
8.3%
c 1
 
8.3%
u 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1072
74.8%
ASCII 362
 
25.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
187
51.7%
1 37
 
10.2%
2 27
 
7.5%
4 17
 
4.7%
6 16
 
4.4%
3 15
 
4.1%
- 11
 
3.0%
5 11
 
3.0%
9 10
 
2.8%
0 9
 
2.5%
Other values (8) 22
 
6.1%
Hangul
ValueCountFrequency (%)
주 79
 
7.4%
변 76
 
7.1%
로 34
 
3.2%
길 29
 
2.7%
교 28
 
2.6%
동 25
 
2.3%
가 24
 
2.2%
대 22
 
2.1%
초 22
 
2.1%
연 21
 
2.0%
Other values (181) 712
66.4%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
불법주정차구역
126 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
불법주정차구역 126
100.0%

Length

2024-04-06T19:13:25.903557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:13:26.151354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 126
100.0%

Interactions

2024-04-06T19:13:20.979790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:13:20.672442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:13:21.203856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:13:20.825449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T19:13:26.248229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.795
경도0.7951.000
2024-04-06T19:13:26.438721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.136
경도-0.1361.000

Missing values

2024-04-06T19:13:21.397956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T19:13:21.587327image/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

고정형CCTV지번주소위도경도자치구단속지점명현장구분
0대현동 56-1237.558202126.945686서대문구이대찾고싶은거리1불법주정차구역
1대현동 37-7237.559115126.94449서대문구이대찾고싶은거리2불법주정차구역
2신촌동 74-1237.559028126.942913서대문구신촌역광장 주변불법주정차구역
3대현동 101-3437.557504126.942959서대문구하나은행 주변불법주정차구역
4창천동 4-9637.559011126.941046서대문구쫄병부대찌개 주변불법주정차구역
5천연동 4137.568572126.961702서대문구동명여중사거리불법주정차구역
6충정로2가 184-1337.564457126.963707서대문구경기초등학교사거리불법주정차구역
7북아현동 130-1237.564457126.963707서대문구북아현길불법주정차구역
8창천동 2-3337.558676126.93875서대문구걷고싶은거리 1불법주정차구역
9연희동 69-2237.567667126.931731서대문구연희삼거리 주변불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
116서울 서대문구 홍은동 48-27537.592738126.94356서대문구홍제초 정문앞 주변불법주정차구역
117서울 서대문구 북가좌동 5-1037.581114126.920613서대문구명지대 아이파크 사이길불법주정차구역
118서울 서대문구 홍제동 47-2437.580513126.951195서대문구안산초 푸르지오 정문 주변불법주정차구역
119서울 서대문구 창천동 80-1637.559242126.937124서대문구일심약국 앞불법주정차구역
120서울 서대문구 북가좌동 292-437.581472126.91352서대문구풍천백세장어 부근불법주정차구역
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