Overview

Dataset statistics

Number of variables6
Number of observations121
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory51.1 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-20481/S/1/datasetView.do

Alerts

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

Reproduction

Analysis started2024-04-06 10:15:11.418610
Analysis finished2024-04-06 10:15:12.880746
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct115
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T19:15:13.263856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length15.165289
Min length12

Characters and Unicode

Total characters1835
Distinct characters24
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

Unique109 ?
Unique (%)90.1%

Sample

1st row서울 도봉구 창동 533-1
2nd row서울 도봉구 창동 453-1
3rd row서울 도봉구 쌍문동 88-2
4th row서울 도봉구 창동 822
5th row서울 도봉구 쌍문동 419
ValueCountFrequency (%)
서울 121
24.9%
도봉구 121
24.9%
창동 55
11.3%
쌍문동 24
 
4.9%
방학동 22
 
4.5%
도봉동 20
 
4.1%
670-7 2
 
0.4%
산 2
 
0.4%
135-1 2
 
0.4%
1-28 2
 
0.4%
Other values (112) 115
23.7%
2024-04-06T19:15:14.065821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
365
19.9%
도 141
 
7.7%
봉 141
 
7.7%
서 121
 
6.6%
구 121
 
6.6%
동 121
 
6.6%
울 121
 
6.6%
- 87
 
4.7%
1 74
 
4.0%
2 57
 
3.1%
Other values (14) 486
26.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 915
49.9%
Decimal Number 468
25.5%
Space Separator 365
 
19.9%
Dash Punctuation 87
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 141
15.4%
봉 141
15.4%
서 121
13.2%
구 121
13.2%
동 121
13.2%
울 121
13.2%
창 55
 
6.0%
문 24
 
2.6%
쌍 24
 
2.6%
학 22
 
2.4%
Other values (2) 24
 
2.6%
Decimal Number
ValueCountFrequency (%)
1 74
15.8%
2 57
12.2%
3 51
10.9%
6 50
10.7%
4 48
10.3%
5 46
9.8%
8 43
9.2%
7 36
7.7%
0 33
7.1%
9 30
6.4%
Space Separator
ValueCountFrequency (%)
365
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 920
50.1%
Hangul 915
49.9%

Most frequent character per script

Common
ValueCountFrequency (%)
365
39.7%
- 87
 
9.5%
1 74
 
8.0%
2 57
 
6.2%
3 51
 
5.5%
6 50
 
5.4%
4 48
 
5.2%
5 46
 
5.0%
8 43
 
4.7%
7 36
 
3.9%
Other values (2) 63
 
6.8%
Hangul
ValueCountFrequency (%)
도 141
15.4%
봉 141
15.4%
서 121
13.2%
구 121
13.2%
동 121
13.2%
울 121
13.2%
창 55
 
6.0%
문 24
 
2.6%
쌍 24
 
2.6%
학 22
 
2.4%
Other values (2) 24
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 920
50.1%
Hangul 915
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
365
39.7%
- 87
 
9.5%
1 74
 
8.0%
2 57
 
6.2%
3 51
 
5.5%
6 50
 
5.4%
4 48
 
5.2%
5 46
 
5.0%
8 43
 
4.7%
7 36
 
3.9%
Other values (2) 63
 
6.8%
Hangul
ValueCountFrequency (%)
도 141
15.4%
봉 141
15.4%
서 121
13.2%
구 121
13.2%
동 121
13.2%
울 121
13.2%
창 55
 
6.0%
문 24
 
2.6%
쌍 24
 
2.6%
학 22
 
2.4%
Other values (2) 24
 
2.6%

위도
Real number (ℝ)

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.657509
Minimum37.632076
Maximum37.690823
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T19:15:14.358089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.632076
5-th percentile37.638018
Q137.648593
median37.655489
Q337.662982
95-th percentile37.686887
Maximum37.690823
Range0.058747548
Interquartile range (IQR)0.014388856

Descriptive statistics

Standard deviation0.013452468
Coefficient of variation (CV)0.00035723202
Kurtosis0.28456272
Mean37.657509
Median Absolute Deviation (MAD)0.0069728835
Skewness0.71515108
Sum4556.5585
Variance0.00018096889
MonotonicityNot monotonic
2024-04-06T19:15:14.592947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6369427467146 1
 
0.8%
37.64651888108575 1
 
0.8%
37.64687221088815 1
 
0.8%
37.67796382129351 1
 
0.8%
37.65115655227842 1
 
0.8%
37.648191560619225 1
 
0.8%
37.655512091702825 1
 
0.8%
37.63207554735144 1
 
0.8%
37.653567701566416 1
 
0.8%
37.64859266968353 1
 
0.8%
Other values (111) 111
91.7%
ValueCountFrequency (%)
37.63207554735144 1
0.8%
37.63228677803527 1
0.8%
37.63399906372995 1
0.8%
37.63562731701762 1
0.8%
37.63629656365773 1
0.8%
37.6369427467146 1
0.8%
37.6380176604893 1
0.8%
37.639309002707655 1
0.8%
37.63989122458467 1
0.8%
37.64054553428 1
0.8%
ValueCountFrequency (%)
37.69082309522302 1
0.8%
37.69013773708887 1
0.8%
37.68931953088563 1
0.8%
37.68921764030013 1
0.8%
37.68907212870832 1
0.8%
37.68709169022678 1
0.8%
37.686887247365725 1
0.8%
37.6865455806275 1
0.8%
37.68384416224055 1
0.8%
37.683274044176514 1
0.8%

경도
Real number (ℝ)

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03926
Minimum127.01354
Maximum127.05279
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T19:15:14.849413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.01354
5-th percentile127.02514
Q1127.03457
median127.04061
Q3127.04574
95-th percentile127.04976
Maximum127.05279
Range0.039249736
Interquartile range (IQR)0.01116902

Descriptive statistics

Standard deviation0.008086676
Coefficient of variation (CV)6.3654934 × 10-5
Kurtosis1.2382429
Mean127.03926
Median Absolute Deviation (MAD)0.005473935
Skewness-0.98253731
Sum15371.751
Variance6.5394328 × 10-5
MonotonicityNot monotonic
2024-04-06T19:15:15.123857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.039936007032 1
 
0.8%
127.03933463444784 1
 
0.8%
127.04024273259527 1
 
0.8%
127.04375665168544 1
 
0.8%
127.03238641072836 1
 
0.8%
127.0263823175192 1
 
0.8%
127.0418112808522 1
 
0.8%
127.04094564358056 1
 
0.8%
127.0490146430156 1
 
0.8%
127.03445328779128 1
 
0.8%
Other values (111) 111
91.7%
ValueCountFrequency (%)
127.01354464369696 1
0.8%
127.01368328741997 1
0.8%
127.01458185081044 1
0.8%
127.01589100194502 1
0.8%
127.024323906668 1
0.8%
127.0244404671444 1
0.8%
127.025138236022 1
0.8%
127.02591857846753 1
0.8%
127.0263823175192 1
0.8%
127.02684625196986 1
0.8%
ValueCountFrequency (%)
127.05279437924784 1
0.8%
127.05234717298488 1
0.8%
127.05233568495274 1
0.8%
127.05069594735346 1
0.8%
127.04990542720044 1
0.8%
127.04976052084 1
0.8%
127.04975794143026 1
0.8%
127.04929425572954 1
0.8%
127.04921641555865 1
0.8%
127.0490146430156 1
0.8%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
도봉구
121 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도봉구 121
100.0%

Length

2024-04-06T19:15:15.455905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:15:15.633117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도봉구 121
100.0%

단속지점명
Text

Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T19:15:15.902617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length13.892562
Min length4

Characters and Unicode

Total characters1681
Distinct characters243
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)98.3%

Sample

1st row서울탁주 건너편 (덕릉로54길 편의점앞)
2nd row덕릉로60길49-1앞 사거리
3rd row삼성어린이집 삼거리
4th row창동역2번출구 대림아파트앞
5th row덕성여대 정문 진입로
ValueCountFrequency (%)
앞 33
 
10.5%
사거리 15
 
4.8%
정문 12
 
3.8%
삼거리 10
 
3.2%
입구 6
 
1.9%
근처 4
 
1.3%
담장 4
 
1.3%
후문 4
 
1.3%
도봉산역 3
 
1.0%
창동금호연립 2
 
0.6%
Other values (208) 220
70.3%
2024-04-06T19:15:16.491714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
200
 
11.9%
앞 52
 
3.1%
( 41
 
2.4%
) 41
 
2.4%
학 39
 
2.3%
리 39
 
2.3%
교 36
 
2.1%
동 34
 
2.0%
거 34
 
2.0%
1 33
 
2.0%
Other values (233) 1132
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1252
74.5%
Space Separator 200
 
11.9%
Decimal Number 114
 
6.8%
Open Punctuation 42
 
2.5%
Close Punctuation 42
 
2.5%
Other Punctuation 16
 
1.0%
Uppercase Letter 7
 
0.4%
Dash Punctuation 4
 
0.2%
Lowercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 52
 
4.2%
학 39
 
3.1%
리 39
 
3.1%
교 36
 
2.9%
동 34
 
2.7%
거 34
 
2.7%
사 29
 
2.3%
창 28
 
2.2%
문 25
 
2.0%
봉 25
 
2.0%
Other values (206) 911
72.8%
Decimal Number
ValueCountFrequency (%)
1 33
28.9%
0 15
13.2%
2 13
 
11.4%
3 13
 
11.4%
5 11
 
9.6%
6 7
 
6.1%
4 7
 
6.1%
9 6
 
5.3%
7 5
 
4.4%
8 4
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
T 2
28.6%
K 2
28.6%
H 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
l 1
25.0%
i 1
25.0%
o 1
25.0%
s 1
25.0%
Other Punctuation
ValueCountFrequency (%)
@ 9
56.2%
, 6
37.5%
/ 1
 
6.2%
Open Punctuation
ValueCountFrequency (%)
( 41
97.6%
[ 1
 
2.4%
Close Punctuation
ValueCountFrequency (%)
) 41
97.6%
] 1
 
2.4%
Space Separator
ValueCountFrequency (%)
200
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1252
74.5%
Common 418
 
24.9%
Latin 11
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 52
 
4.2%
학 39
 
3.1%
리 39
 
3.1%
교 36
 
2.9%
동 34
 
2.7%
거 34
 
2.7%
사 29
 
2.3%
창 28
 
2.2%
문 25
 
2.0%
봉 25
 
2.0%
Other values (206) 911
72.8%
Common
ValueCountFrequency (%)
200
47.8%
( 41
 
9.8%
) 41
 
9.8%
1 33
 
7.9%
0 15
 
3.6%
2 13
 
3.1%
3 13
 
3.1%
5 11
 
2.6%
@ 9
 
2.2%
6 7
 
1.7%
Other values (9) 35
 
8.4%
Latin
ValueCountFrequency (%)
S 2
18.2%
T 2
18.2%
K 2
18.2%
H 1
9.1%
l 1
9.1%
i 1
9.1%
o 1
9.1%
s 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1252
74.5%
ASCII 429
 
25.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
200
46.6%
( 41
 
9.6%
) 41
 
9.6%
1 33
 
7.7%
0 15
 
3.5%
2 13
 
3.0%
3 13
 
3.0%
5 11
 
2.6%
@ 9
 
2.1%
6 7
 
1.6%
Other values (17) 46
 
10.7%
Hangul
ValueCountFrequency (%)
앞 52
 
4.2%
학 39
 
3.1%
리 39
 
3.1%
교 36
 
2.9%
동 34
 
2.7%
거 34
 
2.7%
사 29
 
2.3%
창 28
 
2.2%
문 25
 
2.0%
봉 25
 
2.0%
Other values (206) 911
72.8%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
불법주정차구역
121 

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 121
100.0%

Length

2024-04-06T19:15:16.699704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:15:16.861716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 121
100.0%

Interactions

2024-04-06T19:15:12.129946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:15:11.773136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:15:12.294025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:15:11.927266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T19:15:16.947401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.450
경도0.4501.000
2024-04-06T19:15:17.075474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.129
경도0.1291.000

Missing values

2024-04-06T19:15:12.605198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T19:15:12.799764image/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 도봉구 창동 533-137.636943127.039936도봉구서울탁주 건너편 (덕릉로54길 편의점앞)불법주정차구역
1서울 도봉구 창동 453-137.638018127.040615도봉구덕릉로60길49-1앞 사거리불법주정차구역
2서울 도봉구 쌍문동 88-237.651192127.035245도봉구삼성어린이집 삼거리불법주정차구역
3서울 도봉구 창동 82237.652893127.045904도봉구창동역2번출구 대림아파트앞불법주정차구역
4서울 도봉구 쌍문동 41937.651622127.013683도봉구덕성여대 정문 진입로불법주정차구역
5서울 도봉구 쌍문동 20937.658114127.033001도봉구금호한양아파트사거리불법주정차구역
6서울 도봉구 창동 26637.654824127.044576도봉구창동초등학교 정문앞불법주정차구역
7서울 도봉구 창동 1-1037.655369127.049905도봉구창동하나로마트 사거리불법주정차구역
8서울 도봉구 방학동 720-137.665888127.046147도봉구삼성래미안@사거리 (사랑유치원)불법주정차구역
9서울 도봉구 창동 350-237.648112127.043578도봉구창1동 주민센터 (광역과학수사10팀)불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
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