Overview

Dataset statistics

Number of variables6
Number of observations98
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory51.3 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-20496/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
현장구분 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
위도 has unique valuesUnique
단속지점명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 12:17:05.398557
Analysis finished2024-04-06 12:17:06.844527
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct91
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size916.0 B
2024-04-06T21:17:07.200185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length10.918367
Min length6

Characters and Unicode

Total characters1070
Distinct characters31
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

Unique84 ?
Unique (%)85.7%

Sample

1st row서울 강동구 상일동 121
2nd row서울 강동구 명일동 296-1
3rd row서울 강동구 상일동 121
4th row명일동 46-6
5th row암사동 501
ValueCountFrequency (%)
서울 37
 
13.7%
강동구 37
 
13.7%
천호동 16
 
5.9%
성내동 14
 
5.2%
길동 14
 
5.2%
상일동 11
 
4.1%
암사동 10
 
3.7%
명일동 10
 
3.7%
강일동 9
 
3.3%
고덕동 8
 
3.0%
Other values (91) 104
38.5%
2024-04-06T21:17:08.002402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
172
16.1%
동 135
 
12.6%
- 66
 
6.2%
1 61
 
5.7%
4 57
 
5.3%
2 48
 
4.5%
5 48
 
4.5%
강 46
 
4.3%
3 38
 
3.6%
서 37
 
3.5%
Other values (21) 362
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 465
43.5%
Decimal Number 367
34.3%
Space Separator 172
 
16.1%
Dash Punctuation 66
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 135
29.0%
강 46
 
9.9%
서 37
 
8.0%
울 37
 
8.0%
구 37
 
8.0%
일 30
 
6.5%
호 16
 
3.4%
천 16
 
3.4%
성 14
 
3.0%
내 14
 
3.0%
Other values (9) 83
17.8%
Decimal Number
ValueCountFrequency (%)
1 61
16.6%
4 57
15.5%
2 48
13.1%
5 48
13.1%
3 38
10.4%
6 31
8.4%
7 25
6.8%
0 23
 
6.3%
8 18
 
4.9%
9 18
 
4.9%
Space Separator
ValueCountFrequency (%)
172
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 605
56.5%
Hangul 465
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 135
29.0%
강 46
 
9.9%
서 37
 
8.0%
울 37
 
8.0%
구 37
 
8.0%
일 30
 
6.5%
호 16
 
3.4%
천 16
 
3.4%
성 14
 
3.0%
내 14
 
3.0%
Other values (9) 83
17.8%
Common
ValueCountFrequency (%)
172
28.4%
- 66
 
10.9%
1 61
 
10.1%
4 57
 
9.4%
2 48
 
7.9%
5 48
 
7.9%
3 38
 
6.3%
6 31
 
5.1%
7 25
 
4.1%
0 23
 
3.8%
Other values (2) 36
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 605
56.5%
Hangul 465
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
172
28.4%
- 66
 
10.9%
1 61
 
10.1%
4 57
 
9.4%
2 48
 
7.9%
5 48
 
7.9%
3 38
 
6.3%
6 31
 
5.1%
7 25
 
4.1%
0 23
 
3.8%
Other values (2) 36
 
6.0%
Hangul
ValueCountFrequency (%)
동 135
29.0%
강 46
 
9.9%
서 37
 
8.0%
울 37
 
8.0%
구 37
 
8.0%
일 30
 
6.5%
호 16
 
3.4%
천 16
 
3.4%
성 14
 
3.0%
내 14
 
3.0%
Other values (9) 83
17.8%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.545796
Minimum37.523678
Maximum37.573723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-04-06T21:17:08.335968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.523678
5-th percentile37.528717
Q137.53688
median37.546265
Q337.55475
95-th percentile37.564659
Maximum37.573723
Range0.050045599
Interquartile range (IQR)0.017870924

Descriptive statistics

Standard deviation0.011536028
Coefficient of variation (CV)0.0003072522
Kurtosis-0.7064579
Mean37.545796
Median Absolute Deviation (MAD)0.008665085
Skewness0.14796432
Sum3679.488
Variance0.00013307995
MonotonicityNot monotonic
2024-04-06T21:17:08.634248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.556539 1
 
1.0%
37.55570899281977 1
 
1.0%
37.53616324271502 1
 
1.0%
37.528778516440255 1
 
1.0%
37.564392 1
 
1.0%
37.5567623333733 1
 
1.0%
37.558169 1
 
1.0%
37.542021 1
 
1.0%
37.5509309412134 1
 
1.0%
37.55034 1
 
1.0%
Other values (88) 88
89.8%
ValueCountFrequency (%)
37.52367783 1
1.0%
37.52590179 1
1.0%
37.52671814 1
1.0%
37.52825165 1
1.0%
37.5283713288208 1
1.0%
37.528778516440255 1
1.0%
37.52890202866953 1
1.0%
37.5291481 1
1.0%
37.52954599359322 1
1.0%
37.52995682 1
1.0%
ValueCountFrequency (%)
37.57372342906648 1
1.0%
37.57187296545797 1
1.0%
37.56800278903468 1
1.0%
37.56623459 1
1.0%
37.56616974 1
1.0%
37.564392 1
1.0%
37.56384659 1
1.0%
37.56228578977196 1
1.0%
37.56120664464993 1
1.0%
37.56041457128061 1
1.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.14503
Minimum127.12032
Maximum127.17968
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-04-06T21:17:08.905980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.12032
5-th percentile127.12246
Q1127.13242
median127.14187
Q3127.15603
95-th percentile127.17387
Maximum127.17968
Range0.059355851
Interquartile range (IQR)0.023612975

Descriptive statistics

Standard deviation0.016682448
Coefficient of variation (CV)0.00013120802
Kurtosis-0.82138226
Mean127.14503
Median Absolute Deviation (MAD)0.010992304
Skewness0.54600761
Sum12460.213
Variance0.00027830408
MonotonicityNot monotonic
2024-04-06T21:17:09.161239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1402664 2
 
2.0%
127.165508 1
 
1.0%
127.147082524967 1
 
1.0%
127.17401708848259 1
 
1.0%
127.13220332121682 1
 
1.0%
127.14088455574782 1
 
1.0%
127.178237 1
 
1.0%
127.145081475071 1
 
1.0%
127.169929 1
 
1.0%
127.147479 1
 
1.0%
Other values (87) 87
88.8%
ValueCountFrequency (%)
127.1203232 1
1.0%
127.1219788 1
1.0%
127.1222382 1
1.0%
127.1223068 1
1.0%
127.1223145 1
1.0%
127.1224899 1
1.0%
127.1228406006307 1
1.0%
127.1239319 1
1.0%
127.12464652496406 1
1.0%
127.124794 1
1.0%
ValueCountFrequency (%)
127.17967905122998 1
1.0%
127.178237 1
1.0%
127.17478362505832 1
1.0%
127.1744614 1
1.0%
127.17401708848259 1
1.0%
127.1738434 1
1.0%
127.1734772 1
1.0%
127.1734543 1
1.0%
127.1733246 1
1.0%
127.17332063789584 1
1.0%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
강동구
98 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강동구 98
100.0%

Length

2024-04-06T21:17:09.430842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:17:09.610562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강동구 98
100.0%

단속지점명
Text

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2024-04-06T21:17:09.931610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length10.387755
Min length3

Characters and Unicode

Total characters1018
Distinct characters199
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

Unique98 ?
Unique (%)100.0%

Sample

1st row상일파출소 앞
2nd row고명초교 앞
3rd row고현초교 앞
4th row명일이마트앞
5th row암사역1번출구
ValueCountFrequency (%)
앞 30
 
16.1%
주변 11
 
5.9%
사거리 4
 
2.2%
건너편 3
 
1.6%
국민은행 3
 
1.6%
중앙보훈병원 2
 
1.1%
강일동 2
 
1.1%
옆 2
 
1.1%
정문 2
 
1.1%
회전교차로 2
 
1.1%
Other values (124) 125
67.2%
2024-04-06T21:17:10.621820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
8.7%
앞 46
 
4.5%
동 34
 
3.3%
교 34
 
3.3%
초 24
 
2.4%
강 23
 
2.3%
( 21
 
2.1%
) 21
 
2.1%
일 20
 
2.0%
구 19
 
1.9%
Other values (189) 687
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 856
84.1%
Space Separator 89
 
8.7%
Open Punctuation 21
 
2.1%
Close Punctuation 21
 
2.1%
Decimal Number 21
 
2.1%
Dash Punctuation 5
 
0.5%
Uppercase Letter 4
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 46
 
5.4%
동 34
 
4.0%
교 34
 
4.0%
초 24
 
2.8%
강 23
 
2.7%
일 20
 
2.3%
구 19
 
2.2%
역 19
 
2.2%
리 17
 
2.0%
지 14
 
1.6%
Other values (172) 606
70.8%
Decimal Number
ValueCountFrequency (%)
3 5
23.8%
1 4
19.0%
4 3
14.3%
2 3
14.3%
0 2
 
9.5%
5 2
 
9.5%
8 1
 
4.8%
6 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
K 1
25.0%
G 1
25.0%
L 1
25.0%
Space Separator
ValueCountFrequency (%)
89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 856
84.1%
Common 158
 
15.5%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 46
 
5.4%
동 34
 
4.0%
교 34
 
4.0%
초 24
 
2.8%
강 23
 
2.7%
일 20
 
2.3%
구 19
 
2.2%
역 19
 
2.2%
리 17
 
2.0%
지 14
 
1.6%
Other values (172) 606
70.8%
Common
ValueCountFrequency (%)
89
56.3%
( 21
 
13.3%
) 21
 
13.3%
- 5
 
3.2%
3 5
 
3.2%
1 4
 
2.5%
4 3
 
1.9%
2 3
 
1.9%
0 2
 
1.3%
5 2
 
1.3%
Other values (3) 3
 
1.9%
Latin
ValueCountFrequency (%)
T 1
25.0%
K 1
25.0%
G 1
25.0%
L 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 856
84.1%
ASCII 162
 
15.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
54.9%
( 21
 
13.0%
) 21
 
13.0%
- 5
 
3.1%
3 5
 
3.1%
1 4
 
2.5%
4 3
 
1.9%
2 3
 
1.9%
0 2
 
1.2%
5 2
 
1.2%
Other values (7) 7
 
4.3%
Hangul
ValueCountFrequency (%)
앞 46
 
5.4%
동 34
 
4.0%
교 34
 
4.0%
초 24
 
2.8%
강 23
 
2.7%
일 20
 
2.3%
구 19
 
2.2%
역 19
 
2.2%
리 17
 
2.0%
지 14
 
1.6%
Other values (172) 606
70.8%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
불법주정차구역
98 

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 98
100.0%

Length

2024-04-06T21:17:10.877541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:17:11.047692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 98
100.0%

Interactions

2024-04-06T21:17:06.175820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:17:05.834556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:17:06.337879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:17:05.979943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T21:17:11.156443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고정형CCTV지번주소위도경도단속지점명
고정형CCTV지번주소1.0001.0001.0001.000
위도1.0001.0000.6051.000
경도1.0000.6051.0001.000
단속지점명1.0001.0001.0001.000
2024-04-06T21:17:11.362567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.625
경도0.6251.000

Missing values

2024-04-06T21:17:06.573997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T21:17:06.769702image/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 강동구 상일동 12137.556539127.165508강동구상일파출소 앞불법주정차구역
1서울 강동구 명일동 296-137.552208127.146122강동구고명초교 앞불법주정차구역
2서울 강동구 상일동 12137.553801127.166031강동구고현초교 앞불법주정차구역
3명일동 46-637.554173127.156326강동구명일이마트앞불법주정차구역
4암사동 50137.551193127.12809강동구암사역1번출구불법주정차구역
5길동 391-537.537952127.140282강동구길동역(시민당약국건너편)불법주정차구역
6길동 391-537.537891127.140266강동구길동역(시민당약국건너편)-보조불법주정차구역
7천호동 454-1437.538136127.125923강동구천호이마트앞불법주정차구역
8길동 413-4537.53553127.138908강동구길동역 LG베스트샵불법주정차구역
9길동 411-137.536659127.139793강동구길동역3번출구 앞(남경빌딩)불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
88서울 강동구 성내동 434-837.528371127.128586강동구성일초등학교(후문) 주변불법주정차구역
89서울 강동구 고덕동 30237.557647127.156543강동구고덕동 공공급식센터 주변불법주정차구역
90서울 강동구 강일동 72437.557259127.173321강동구능골근린공원사거리(고덕리엔파크2단지) 주변불법주정차구역
91서울 강동구 암사동 474-837.551945127.135683강동구구립보람나무어린이집 주변불법주정차구역
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