Overview

Dataset statistics

Number of variables6
Number of observations105
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory51.3 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-20480/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
현장구분 has constant value ""Constant
위도 has unique valuesUnique
경도 has unique valuesUnique
단속지점명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 10:38:20.836572
Analysis finished2024-04-06 10:38:22.481994
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct104
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
2024-04-06T19:38:22.887434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length11.171429
Min length7

Characters and Unicode

Total characters1173
Distinct characters37
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

Unique103 ?
Unique (%)98.1%

Sample

1st row서울 강북구 미아동 838-19
2nd row미아동 158-10
3rd row미아동 125-61
4th row미아동 125-9
5th row번1동 460-46
ValueCountFrequency (%)
서울 25
 
9.8%
강북구 25
 
9.8%
송중동 13
 
5.1%
번동 12
 
4.7%
미아동 12
 
4.7%
수유동 9
 
3.5%
인수동 8
 
3.1%
송천동 8
 
3.1%
우이동 7
 
2.7%
수유1동 6
 
2.4%
Other values (113) 130
51.0%
2024-04-06T19:38:23.690481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
 
13.2%
동 105
 
9.0%
- 93
 
7.9%
1 92
 
7.8%
2 62
 
5.3%
3 61
 
5.2%
5 56
 
4.8%
4 53
 
4.5%
6 41
 
3.5%
8 37
 
3.2%
Other values (27) 418
35.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 490
41.8%
Other Letter 435
37.1%
Space Separator 155
 
13.2%
Dash Punctuation 93
 
7.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 105
24.1%
수 31
 
7.1%
북 25
 
5.7%
구 25
 
5.7%
강 25
 
5.7%
울 25
 
5.7%
서 25
 
5.7%
유 23
 
5.3%
번 23
 
5.3%
송 22
 
5.1%
Other values (15) 106
24.4%
Decimal Number
ValueCountFrequency (%)
1 92
18.8%
2 62
12.7%
3 61
12.4%
5 56
11.4%
4 53
10.8%
6 41
8.4%
8 37
7.6%
7 32
 
6.5%
9 31
 
6.3%
0 25
 
5.1%
Space Separator
ValueCountFrequency (%)
155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 738
62.9%
Hangul 435
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 105
24.1%
수 31
 
7.1%
북 25
 
5.7%
구 25
 
5.7%
강 25
 
5.7%
울 25
 
5.7%
서 25
 
5.7%
유 23
 
5.3%
번 23
 
5.3%
송 22
 
5.1%
Other values (15) 106
24.4%
Common
ValueCountFrequency (%)
155
21.0%
- 93
12.6%
1 92
12.5%
2 62
 
8.4%
3 61
 
8.3%
5 56
 
7.6%
4 53
 
7.2%
6 41
 
5.6%
8 37
 
5.0%
7 32
 
4.3%
Other values (2) 56
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 738
62.9%
Hangul 435
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
21.0%
- 93
12.6%
1 92
12.5%
2 62
 
8.4%
3 61
 
8.3%
5 56
 
7.6%
4 53
 
7.2%
6 41
 
5.6%
8 37
 
5.0%
7 32
 
4.3%
Other values (2) 56
 
7.6%
Hangul
ValueCountFrequency (%)
동 105
24.1%
수 31
 
7.1%
북 25
 
5.7%
구 25
 
5.7%
강 25
 
5.7%
울 25
 
5.7%
서 25
 
5.7%
유 23
 
5.3%
번 23
 
5.3%
송 22
 
5.1%
Other values (15) 106
24.4%

위도
Real number (ℝ)

UNIQUE 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.629604
Minimum37.612164
Maximum37.663927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T19:38:23.942379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.612164
5-th percentile37.614112
Q137.618898
median37.628216
Q337.637333
95-th percentile37.658447
Maximum37.663927
Range0.051763763
Interquartile range (IQR)0.01843528

Descriptive statistics

Standard deviation0.012522861
Coefficient of variation (CV)0.00033279279
Kurtosis0.41964195
Mean37.629604
Median Absolute Deviation (MAD)0.0093181499
Skewness0.87934667
Sum3951.1084
Variance0.00015682204
MonotonicityNot monotonic
2024-04-06T19:38:24.212653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6200256347656 1
 
1.0%
37.63855362 1
 
1.0%
37.6540184 1
 
1.0%
37.65955353 1
 
1.0%
37.65959167 1
 
1.0%
37.63916779 1
 
1.0%
37.63864136 1
 
1.0%
37.64006805 1
 
1.0%
37.64109802 1
 
1.0%
37.64208984 1
 
1.0%
Other values (95) 95
90.5%
ValueCountFrequency (%)
37.61216354 1
1.0%
37.61286163 1
1.0%
37.61314779317265 1
1.0%
37.6133194 1
1.0%
37.61371231 1
1.0%
37.61407471 1
1.0%
37.61426163 1
1.0%
37.6145632473928 1
1.0%
37.61468124 1
1.0%
37.61502457 1
1.0%
ValueCountFrequency (%)
37.66392730338878 1
1.0%
37.6631141411706 1
1.0%
37.662240435987215 1
1.0%
37.66113914592847 1
1.0%
37.65959167 1
1.0%
37.65955353 1
1.0%
37.6540184 1
1.0%
37.6516876220703 1
1.0%
37.64447403 1
1.0%
37.64401627 1
1.0%

경도
Real number (ℝ)

UNIQUE 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02401
Minimum127.00737
Maximum127.04649
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T19:38:24.470699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.00737
5-th percentile127.0108
Q1127.01705
median127.02391
Q3127.03046
95-th percentile127.03804
Maximum127.04649
Range0.039125398
Interquartile range (IQR)0.0134048

Descriptive statistics

Standard deviation0.0089007939
Coefficient of variation (CV)7.0071743 × 10-5
Kurtosis-0.48051987
Mean127.02401
Median Absolute Deviation (MAD)0.0068512
Skewness0.27152509
Sum13337.521
Variance7.9224133 × 10-5
MonotonicityNot monotonic
2024-04-06T19:38:24.744968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.018348693847 1
 
1.0%
127.0159225 1
 
1.0%
127.0117645 1
 
1.0%
127.010788 1
 
1.0%
127.0114746 1
 
1.0%
127.0257645 1
 
1.0%
127.0247421 1
 
1.0%
127.0264893 1
 
1.0%
127.025032 1
 
1.0%
127.0236664 1
 
1.0%
Other values (95) 95
90.5%
ValueCountFrequency (%)
127.00736810169096 1
1.0%
127.0095749 1
1.0%
127.00958958221868 1
1.0%
127.0106354 1
1.0%
127.0106659 1
1.0%
127.010788 1
1.0%
127.0108337 1
1.0%
127.0110245 1
1.0%
127.011108398437 1
1.0%
127.0114746 1
1.0%
ValueCountFrequency (%)
127.0464935 1
1.0%
127.0460739 1
1.0%
127.0452118 1
1.0%
127.04003928682246 1
1.0%
127.0389252 1
1.0%
127.0381012 1
1.0%
127.03778014377 1
1.0%
127.0377274 1
1.0%
127.0358429 1
1.0%
127.0351181 1
1.0%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
강북구
105 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강북구 105
100.0%

Length

2024-04-06T19:38:25.060782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:38:25.224287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강북구 105
100.0%

단속지점명
Text

UNIQUE 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
2024-04-06T19:38:25.525251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length32.152381
Min length21

Characters and Unicode

Total characters3376
Distinct characters223
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

Unique105 ?
Unique (%)100.0%

Sample

1st row주정차(삼양)-306 (솔샘로 229-1, 미양 온누리약국 앞)
2nd row주정차(미아)-059 (덕릉로 108, 강북 여성인력 개발센터)
3rd row주정차(미아)-017 (솔매로52길 31, 애화학교 앞)
4th row주정차(미아)-018 (솔매로50길 43, KT강북플라자 앞)
5th row주정차(번1)-033 (한천로124길 14, 수송초 정문)
ValueCountFrequency (%)
앞 50
 
10.3%
솔샘로 8
 
1.6%
후문 8
 
1.6%
정문 7
 
1.4%
한천로 5
 
1.0%
입구 5
 
1.0%
오현로 5
 
1.0%
덕릉로 4
 
0.8%
오패산로 4
 
0.8%
삼양로 4
 
0.8%
Other values (344) 386
79.4%
2024-04-06T19:38:26.144624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
382
 
11.3%
( 212
 
6.3%
) 212
 
6.3%
0 138
 
4.1%
1 131
 
3.9%
2 121
 
3.6%
차 113
 
3.3%
정 112
 
3.3%
주 112
 
3.3%
- 112
 
3.3%
Other values (213) 1731
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1587
47.0%
Decimal Number 772
22.9%
Space Separator 382
 
11.3%
Open Punctuation 212
 
6.3%
Close Punctuation 212
 
6.3%
Dash Punctuation 112
 
3.3%
Other Punctuation 91
 
2.7%
Uppercase Letter 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 113
 
7.1%
정 112
 
7.1%
주 112
 
7.1%
로 105
 
6.6%
길 69
 
4.3%
삼 58
 
3.7%
앞 53
 
3.3%
수 46
 
2.9%
양 42
 
2.6%
유 32
 
2.0%
Other values (191) 845
53.2%
Decimal Number
ValueCountFrequency (%)
0 138
17.9%
1 131
17.0%
2 121
15.7%
3 92
11.9%
5 58
7.5%
7 53
 
6.9%
9 49
 
6.3%
6 49
 
6.3%
4 46
 
6.0%
8 35
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
S 2
25.0%
G 1
12.5%
H 1
12.5%
U 1
12.5%
C 1
12.5%
T 1
12.5%
K 1
12.5%
Space Separator
ValueCountFrequency (%)
382
100.0%
Open Punctuation
ValueCountFrequency (%)
( 212
100.0%
Close Punctuation
ValueCountFrequency (%)
) 212
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Other Punctuation
ValueCountFrequency (%)
, 91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1781
52.8%
Hangul 1587
47.0%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 113
 
7.1%
정 112
 
7.1%
주 112
 
7.1%
로 105
 
6.6%
길 69
 
4.3%
삼 58
 
3.7%
앞 53
 
3.3%
수 46
 
2.9%
양 42
 
2.6%
유 32
 
2.0%
Other values (191) 845
53.2%
Common
ValueCountFrequency (%)
382
21.4%
( 212
11.9%
) 212
11.9%
0 138
 
7.7%
1 131
 
7.4%
2 121
 
6.8%
- 112
 
6.3%
3 92
 
5.2%
, 91
 
5.1%
5 58
 
3.3%
Other values (5) 232
13.0%
Latin
ValueCountFrequency (%)
S 2
25.0%
G 1
12.5%
H 1
12.5%
U 1
12.5%
C 1
12.5%
T 1
12.5%
K 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1789
53.0%
Hangul 1587
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
382
21.4%
( 212
11.9%
) 212
11.9%
0 138
 
7.7%
1 131
 
7.3%
2 121
 
6.8%
- 112
 
6.3%
3 92
 
5.1%
, 91
 
5.1%
5 58
 
3.2%
Other values (12) 240
13.4%
Hangul
ValueCountFrequency (%)
차 113
 
7.1%
정 112
 
7.1%
주 112
 
7.1%
로 105
 
6.6%
길 69
 
4.3%
삼 58
 
3.7%
앞 53
 
3.3%
수 46
 
2.9%
양 42
 
2.6%
유 32
 
2.0%
Other values (191) 845
53.2%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
불법주정차구역
105 

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 105
100.0%

Length

2024-04-06T19:38:26.637426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:38:27.003345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 105
100.0%

Interactions

2024-04-06T19:38:21.450850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:38:21.137691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:38:22.019578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:38:21.296531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T19:38:27.113657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.694
경도0.6941.000
2024-04-06T19:38:27.253991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.420
경도-0.4201.000

Missing values

2024-04-06T19:38:22.234516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T19:38:22.407510image/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
0서울 강북구 미아동 838-1937.620026127.018349강북구주정차(삼양)-306 (솔샘로 229-1, 미양 온누리약국 앞)불법주정차구역
1미아동 158-1037.63475127.025581강북구주정차(미아)-059 (덕릉로 108, 강북 여성인력 개발센터)불법주정차구역
2미아동 125-6137.625134127.02829강북구주정차(미아)-017 (솔매로52길 31, 애화학교 앞)불법주정차구역
3미아동 125-937.624584127.027725강북구주정차(미아)-018 (솔매로50길 43, KT강북플라자 앞)불법주정차구역
4번1동 460-4637.637333127.032661강북구주정차(번1)-033 (한천로124길 14, 수송초 정문)불법주정차구역
5번1동 454-5837.636402127.033966강북구주정차(번1)-034 (한천로122길 21, 수송중 옆)불법주정차구역
6번1동 428-8737.634682127.035843강북구주정차(번1)-026 (한천로 940, 번동 프라자약국 옆)불법주정차구역
7번동 417-3237.638958127.028145강북구주정차(번1)-050 (한천로 1019, 토마토24시)불법주정차구역
8번동 415-1537.63715127.026993강북구주정차(번1)-051 (오패산로 406, 강북경찰서 앞)불법주정차구역
9번동 414-2537.636246127.028244강북구주정차(번1)-052 (오패산로 390, GS25시)불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
95서울 강북구 미아동 754-6337.623281127.021311강북구주정차(송천)-193 (삼양로54길 60, 큰마을효심경로당)불법주정차구역
96서울 강북구 번동 526-5937.634088127.029936강북구주정차(번2)-191(덕릉로40다길13, 번동제일교회 앞)불법주정차구역
97서울 강북구 미아동 318-537.621862127.026847강북구주정차(송천)-205(도봉로33길18, 성북프라자 앞)불법주정차구역
98서울 강북구 우이동 26537.661139127.007368강북구주정차(우이)-325(삼양로173길112, 북한산국립공원우이분소 앞)불법주정차구역
99서울 강북구 우이동 181-237.66224127.00959강북구주정차(우이)-278(삼양로173길66, 우이맨숀 앞)불법주정차구역
100서울 강북구 미아동 47437.613148127.025989강북구주정차(미아)-240(숭인로7가길 37,미아동부센트레빌)불법주정차구역
101서울 강북구 우이동 4-137.663927127.011993강북구주정차(우이)-331(삼양로 685, 우이동견인차량보관소 맞은편)불법주정차구역
102서울 강북구 번동 442-637.633951127.028426강북구주정차(번2)-190(덕릉로36길22-4, 선향사 입구)불법주정차구역
103서울 강북구 우이동 16-437.663114127.012253강북구주정차(우이)-279(삼양로173길7, 삼양교통 앞)불법주정차구역
104서울 강북구 미아동 1267-2037.616082127.019038강북구주정차(삼각산)-074(삼양로19길 69, 삼각산아이원 앞)불법주정차구역