Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory51.3 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-20474/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 10:06:19.327454
Analysis finished2024-04-06 10:06:20.888965
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-06T19:06:21.272319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length12.82
Min length6

Characters and Unicode

Total characters1282
Distinct characters45
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

Unique97 ?
Unique (%)97.0%

Sample

1st row후암동 418-13
2nd row후암동 105-3
3rd row후암동 336-11
4th row용산동2가 11-13
5th row용산동2가 46-3
ValueCountFrequency (%)
서울 40
 
14.2%
용산구 40
 
14.2%
한남동 21
 
7.5%
이태원동 13
 
4.6%
이촌동 13
 
4.6%
한강로2가 6
 
2.1%
후암동 5
 
1.8%
용산동2가 4
 
1.4%
이태원1동 4
 
1.4%
한강로3가 4
 
1.4%
Other values (117) 131
46.6%
2024-04-06T19:06:22.223326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
217
16.9%
동 87
 
6.8%
- 85
 
6.6%
2 81
 
6.3%
1 80
 
6.2%
3 56
 
4.4%
산 47
 
3.7%
용 45
 
3.5%
서 43
 
3.4%
구 40
 
3.1%
Other values (35) 501
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 550
42.9%
Decimal Number 430
33.5%
Space Separator 217
 
16.9%
Dash Punctuation 85
 
6.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 87
15.8%
산 47
 
8.5%
용 45
 
8.2%
서 43
 
7.8%
구 40
 
7.3%
울 40
 
7.3%
한 32
 
5.8%
이 31
 
5.6%
가 27
 
4.9%
원 23
 
4.2%
Other values (23) 135
24.5%
Decimal Number
ValueCountFrequency (%)
2 81
18.8%
1 80
18.6%
3 56
13.0%
4 38
8.8%
0 36
8.4%
5 36
8.4%
7 30
 
7.0%
6 28
 
6.5%
9 26
 
6.0%
8 19
 
4.4%
Space Separator
ValueCountFrequency (%)
217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 732
57.1%
Hangul 550
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 87
15.8%
산 47
 
8.5%
용 45
 
8.2%
서 43
 
7.8%
구 40
 
7.3%
울 40
 
7.3%
한 32
 
5.8%
이 31
 
5.6%
가 27
 
4.9%
원 23
 
4.2%
Other values (23) 135
24.5%
Common
ValueCountFrequency (%)
217
29.6%
- 85
 
11.6%
2 81
 
11.1%
1 80
 
10.9%
3 56
 
7.7%
4 38
 
5.2%
0 36
 
4.9%
5 36
 
4.9%
7 30
 
4.1%
6 28
 
3.8%
Other values (2) 45
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 732
57.1%
Hangul 550
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
217
29.6%
- 85
 
11.6%
2 81
 
11.1%
1 80
 
10.9%
3 56
 
7.7%
4 38
 
5.2%
0 36
 
4.9%
5 36
 
4.9%
7 30
 
4.1%
6 28
 
3.8%
Other values (2) 45
 
6.1%
Hangul
ValueCountFrequency (%)
동 87
15.8%
산 47
 
8.5%
용 45
 
8.2%
서 43
 
7.8%
구 40
 
7.3%
울 40
 
7.3%
한 32
 
5.8%
이 31
 
5.6%
가 27
 
4.9%
원 23
 
4.2%
Other values (23) 135
24.5%

위도
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.534671
Minimum37.517058
Maximum37.551608
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T19:06:22.603167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.517058
5-th percentile37.519584
Q137.529572
median37.535073
Q337.539947
95-th percentile37.548336
Maximum37.551608
Range0.034550233
Interquartile range (IQR)0.010374594

Descriptive statistics

Standard deviation0.008579763
Coefficient of variation (CV)0.00022858234
Kurtosis-0.45255375
Mean37.534671
Median Absolute Deviation (MAD)0.0050332613
Skewness-0.21090077
Sum3753.4671
Variance7.3612333 × 10-5
MonotonicityNot monotonic
2024-04-06T19:06:22.863313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.546817 1
 
1.0%
37.5516082331175 1
 
1.0%
37.54729359733699 1
 
1.0%
37.535002087034 1
 
1.0%
37.5291046239838 1
 
1.0%
37.536139181613855 1
 
1.0%
37.5351998232206 1
 
1.0%
37.5210195125212 1
 
1.0%
37.5502817129658 1
 
1.0%
37.5286815474116 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
37.517058 1
1.0%
37.517929 1
1.0%
37.518019 1
1.0%
37.518503 1
1.0%
37.518926 1
1.0%
37.519619 1
1.0%
37.5196486041968 1
1.0%
37.520388 1
1.0%
37.520547 1
1.0%
37.52101220921755 1
1.0%
ValueCountFrequency (%)
37.5516082331175 1
1.0%
37.55040709202023 1
1.0%
37.5502817129658 1
1.0%
37.550083 1
1.0%
37.549946 1
1.0%
37.54825115720208 1
1.0%
37.54810206894342 1
1.0%
37.547677 1
1.0%
37.54729359733699 1
1.0%
37.5469 1
1.0%

경도
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98298
Minimum126.95059
Maximum127.01209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T19:06:23.201892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.95059
5-th percentile126.95991
Q1126.96937
median126.98184
Q3126.99565
95-th percentile127.00772
Maximum127.01209
Range0.06149699
Interquartile range (IQR)0.026279818

Descriptive statistics

Standard deviation0.015965004
Coefficient of variation (CV)0.00012572554
Kurtosis-1.2032489
Mean126.98298
Median Absolute Deviation (MAD)0.0131165
Skewness0.050394648
Sum12698.298
Variance0.00025488137
MonotonicityNot monotonic
2024-04-06T19:06:23.477980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.981377 1
 
1.0%
126.980076286451 1
 
1.0%
126.96340938141388 1
 
1.0%
126.95059340676 1
 
1.0%
126.966972245302 1
 
1.0%
126.97143109655434 1
 
1.0%
126.97116274086866 1
 
1.0%
126.973141261532 1
 
1.0%
126.963551075117 1
 
1.0%
126.992169732044 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.95059340676 1
1.0%
126.95451863904457 1
1.0%
126.955966 1
1.0%
126.959219 1
1.0%
126.959814 1
1.0%
126.959912549858 1
1.0%
126.960716 1
1.0%
126.961533 1
1.0%
126.961815 1
1.0%
126.963064 1
1.0%
ValueCountFrequency (%)
127.012090396824 1
1.0%
127.010732 1
1.0%
127.01027 1
1.0%
127.0088531 1
1.0%
127.007861 1
1.0%
127.0077128 1
1.0%
127.00638 1
1.0%
127.006133 1
1.0%
127.0056028 1
1.0%
127.00521327294338 1
1.0%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
용산구
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용산구 100
100.0%

Length

2024-04-06T19:06:23.783242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:06:23.944171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용산구 100
100.0%

단속지점명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-06T19:06:24.381665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length10.01
Min length4

Characters and Unicode

Total characters1001
Distinct characters244
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

Unique100 ?
Unique (%)100.0%

Sample

1st row후암동 로타리 앞
2nd row후암시장 앞
3rd row대림하이츠타운 앞
4th row용산동2가 주민센터 앞
5th row수호빌라 앞
ValueCountFrequency (%)
앞 57
 
23.1%
정문 10
 
4.0%
이태원 7
 
2.8%
건너편 5
 
2.0%
삼거리 4
 
1.6%
입구 4
 
1.6%
한남동 4
 
1.6%
삼각지 3
 
1.2%
옆 3
 
1.2%
폭스바겐 2
 
0.8%
Other values (141) 148
59.9%
2024-04-06T19:06:25.174595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
 
14.8%
앞 58
 
5.8%
동 21
 
2.1%
원 19
 
1.9%
교 17
 
1.7%
아 17
 
1.7%
이 17
 
1.7%
문 16
 
1.6%
산 16
 
1.6%
리 16
 
1.6%
Other values (234) 656
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 798
79.7%
Space Separator 148
 
14.8%
Decimal Number 27
 
2.7%
Uppercase Letter 12
 
1.2%
Close Punctuation 7
 
0.7%
Open Punctuation 7
 
0.7%
Dash Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 58
 
7.3%
동 21
 
2.6%
원 19
 
2.4%
교 17
 
2.1%
아 17
 
2.1%
이 17
 
2.1%
문 16
 
2.0%
산 16
 
2.0%
리 16
 
2.0%
학 16
 
2.0%
Other values (214) 585
73.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
25.0%
G 3
25.0%
N 1
 
8.3%
U 1
 
8.3%
L 1
 
8.3%
P 1
 
8.3%
H 1
 
8.3%
K 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 8
29.6%
2 8
29.6%
0 4
14.8%
5 3
 
11.1%
3 2
 
7.4%
7 1
 
3.7%
4 1
 
3.7%
Space Separator
ValueCountFrequency (%)
148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 798
79.7%
Common 191
 
19.1%
Latin 12
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 58
 
7.3%
동 21
 
2.6%
원 19
 
2.4%
교 17
 
2.1%
아 17
 
2.1%
이 17
 
2.1%
문 16
 
2.0%
산 16
 
2.0%
리 16
 
2.0%
학 16
 
2.0%
Other values (214) 585
73.3%
Common
ValueCountFrequency (%)
148
77.5%
1 8
 
4.2%
2 8
 
4.2%
) 7
 
3.7%
( 7
 
3.7%
0 4
 
2.1%
5 3
 
1.6%
3 2
 
1.0%
- 1
 
0.5%
~ 1
 
0.5%
Other values (2) 2
 
1.0%
Latin
ValueCountFrequency (%)
S 3
25.0%
G 3
25.0%
N 1
 
8.3%
U 1
 
8.3%
L 1
 
8.3%
P 1
 
8.3%
H 1
 
8.3%
K 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 798
79.7%
ASCII 203
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
72.9%
1 8
 
3.9%
2 8
 
3.9%
) 7
 
3.4%
( 7
 
3.4%
0 4
 
2.0%
S 3
 
1.5%
G 3
 
1.5%
5 3
 
1.5%
3 2
 
1.0%
Other values (10) 10
 
4.9%
Hangul
ValueCountFrequency (%)
앞 58
 
7.3%
동 21
 
2.6%
원 19
 
2.4%
교 17
 
2.1%
아 17
 
2.1%
이 17
 
2.1%
문 16
 
2.0%
산 16
 
2.0%
리 16
 
2.0%
학 16
 
2.0%
Other values (214) 585
73.3%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
불법주정차구역
100 

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 100
100.0%

Length

2024-04-06T19:06:25.477449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:06:25.639956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 100
100.0%

Interactions

2024-04-06T19:06:20.131529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:06:19.741688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:06:20.311771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:06:19.922489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T19:06:25.843221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고정형CCTV지번주소위도경도단속지점명
고정형CCTV지번주소1.0001.0001.0001.000
위도1.0001.0000.5691.000
경도1.0000.5691.0001.000
단속지점명1.0001.0001.0001.000
2024-04-06T19:06:25.997721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.004
경도-0.0041.000

Missing values

2024-04-06T19:06:20.629953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T19:06:20.823411image/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
0후암동 418-1337.546817126.981377용산구후암동 로타리 앞불법주정차구역
1후암동 105-337.550083126.977114용산구후암시장 앞불법주정차구역
2후암동 336-1137.549946126.981385용산구대림하이츠타운 앞불법주정차구역
3용산동2가 11-1337.546044126.985556용산구용산동2가 주민센터 앞불법주정차구역
4용산동2가 46-337.540632126.987036용산구수호빌라 앞불법주정차구역
5용산동2가 45-537.541919126.987423용산구새마을금고 건너편불법주정차구역
6갈월동 87-237.543886126.97193용산구숙대입구역 앞불법주정차구역
7청파동2가 72-537.544861126.968672용산구리소헤어 앞불법주정차구역
8청파동2가 1-15737.5469126.965273용산구숙대 명재관 삼거리불법주정차구역
9신계동 40-137.533911126.961533용산구전자상가 4공영주차장 앞불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
90서울 용산구 이촌동 206-137.527207126.954519용산구이촌어린이집 삼거리불법주정차구역
91서울 용산구 이태원동 92-937.53139126.995098용산구세븐일레븐 청화점불법주정차구역
92서울 용산구 이태원동 22-237.528157126.993484용산구청화아파트 후문불법주정차구역
93서울 용산구 청파동3가 105-537.543495126.96936용산구GS25 숙대제일점 앞불법주정차구역
94서울 용산구 후암동 403-1537.548102126.982217용산구산정현교회불법주정차구역
95서울 용산구 용산동2가 137.545842126.978568용산구용산고 삼거리불법주정차구역
96서울 용산구 한남동 683-13937.53711127.001122용산구헌터 매장 앞(한강진 스타벅스)불법주정차구역
97서울 용산구 원효로2가 54-137.5357126.964252용산구남정초등학교 정문 앞불법주정차구역
98서울 용산구 이태원동 243-3737.53948126.995276용산구GS25 용산하얏트점 앞불법주정차구역
99서울 용산구 이태원동 225-6137.539311126.98955용산구박공헤어 앞불법주정차구역