Overview

Dataset statistics

Number of variables6
Number of observations207
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.2 KiB
Average record size in memory50.6 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-20483/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
경도 has unique valuesUnique

Reproduction

Analysis started2024-04-06 10:31:48.614245
Analysis finished2024-04-06 10:31:50.068508
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct203
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-06T19:31:50.652323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length15.7343
Min length10

Characters and Unicode

Total characters3257
Distinct characters44
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique199 ?
Unique (%)96.1%

Sample

1st row서울 은평구 불광동 442-48
2nd row서울 은평구 진관동 102
3rd row서울 은평구 구산동 152-2
4th row서울 은평구 역촌동 71-12
5th row서울 은평구 갈현동 396-9
ValueCountFrequency (%)
서울 206
24.9%
은평구 206
24.9%
응암동 34
 
4.1%
진관동 27
 
3.3%
대조동 22
 
2.7%
역촌동 22
 
2.7%
불광동 22
 
2.7%
갈현동 19
 
2.3%
신사동 17
 
2.1%
구산동 15
 
1.8%
Other values (209) 237
28.7%
2024-04-06T19:31:51.973161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
620
19.0%
구 221
 
6.8%
서 206
 
6.3%
은 206
 
6.3%
평 206
 
6.3%
울 206
 
6.3%
동 205
 
6.3%
1 169
 
5.2%
- 169
 
5.2%
2 109
 
3.3%
Other values (34) 940
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1657
50.9%
Decimal Number 809
24.8%
Space Separator 620
 
19.0%
Dash Punctuation 169
 
5.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 221
13.3%
서 206
12.4%
은 206
12.4%
평 206
12.4%
울 206
12.4%
동 205
12.4%
암 34
 
2.1%
응 34
 
2.1%
진 27
 
1.6%
관 27
 
1.6%
Other values (20) 285
17.2%
Decimal Number
ValueCountFrequency (%)
1 169
20.9%
2 109
13.5%
3 101
12.5%
4 86
10.6%
5 69
8.5%
9 61
 
7.5%
0 58
 
7.2%
7 54
 
6.7%
8 54
 
6.7%
6 48
 
5.9%
Space Separator
ValueCountFrequency (%)
620
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 169
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1657
50.9%
Common 1600
49.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 221
13.3%
서 206
12.4%
은 206
12.4%
평 206
12.4%
울 206
12.4%
동 205
12.4%
암 34
 
2.1%
응 34
 
2.1%
진 27
 
1.6%
관 27
 
1.6%
Other values (20) 285
17.2%
Common
ValueCountFrequency (%)
620
38.8%
1 169
 
10.6%
- 169
 
10.6%
2 109
 
6.8%
3 101
 
6.3%
4 86
 
5.4%
5 69
 
4.3%
9 61
 
3.8%
0 58
 
3.6%
7 54
 
3.4%
Other values (4) 104
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1657
50.9%
ASCII 1600
49.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
620
38.8%
1 169
 
10.6%
- 169
 
10.6%
2 109
 
6.8%
3 101
 
6.3%
4 86
 
5.4%
5 69
 
4.3%
9 61
 
3.8%
0 58
 
3.6%
7 54
 
3.4%
Other values (4) 104
 
6.5%
Hangul
ValueCountFrequency (%)
구 221
13.3%
서 206
12.4%
은 206
12.4%
평 206
12.4%
울 206
12.4%
동 205
12.4%
암 34
 
2.1%
응 34
 
2.1%
진 27
 
1.6%
관 27
 
1.6%
Other values (20) 285
17.2%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct207
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.608764
Minimum37.577589
Maximum37.647935
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T19:31:52.224607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.577589
5-th percentile37.584331
Q137.597643
median37.608104
Q337.619054
95-th percentile37.639921
Maximum37.647935
Range0.070346464
Interquartile range (IQR)0.021411582

Descriptive statistics

Standard deviation0.016443077
Coefficient of variation (CV)0.00043721396
Kurtosis-0.38541013
Mean37.608764
Median Absolute Deviation (MAD)0.010791434
Skewness0.37726154
Sum7785.0142
Variance0.00027037478
MonotonicityNot monotonic
2024-04-06T19:31:52.478812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.623959092158735 1
 
0.5%
37.63138769372603 1
 
0.5%
37.58519838688566 1
 
0.5%
37.614846272679735 1
 
0.5%
37.60432102597487 1
 
0.5%
37.63996373042509 1
 
0.5%
37.59612326494904 1
 
0.5%
37.61634270766617 1
 
0.5%
37.5965027038866 1
 
0.5%
37.590290326119074 1
 
0.5%
Other values (197) 197
95.2%
ValueCountFrequency (%)
37.57758856127466 1
0.5%
37.57851780657093 1
0.5%
37.579212032636505 1
0.5%
37.57993754834718 1
0.5%
37.58128905432437 1
0.5%
37.58177584497712 1
0.5%
37.58235969009905 1
0.5%
37.58380309627926 1
0.5%
37.58390601481632 1
0.5%
37.58412595822115 1
0.5%
ValueCountFrequency (%)
37.647935024827454 1
0.5%
37.64677209515243 1
0.5%
37.64582652015224 1
0.5%
37.6451509270282 1
0.5%
37.645144183813926 1
0.5%
37.64382991674794 1
0.5%
37.643071337919466 1
0.5%
37.64303738954038 1
0.5%
37.64194895034804 1
0.5%
37.64125358298444 1
0.5%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct207
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.91844
Minimum126.89054
Maximum126.94128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T19:31:52.740633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.89054
5-th percentile126.90454
Q1126.91322
median126.91876
Q3126.92464
95-th percentile126.93318
Maximum126.94128
Range0.050741222
Interquartile range (IQR)0.011426069

Descriptive statistics

Standard deviation0.0091922418
Coefficient of variation (CV)7.242637 × 10-5
Kurtosis0.38826286
Mean126.91844
Median Absolute Deviation (MAD)0.0058235515
Skewness-0.22912579
Sum26272.117
Variance8.449731 × 10-5
MonotonicityNot monotonic
2024-04-06T19:31:52.993035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.92522717792612 1
 
0.5%
126.92170637942137 1
 
0.5%
126.91825350310882 1
 
0.5%
126.91616957714388 1
 
0.5%
126.92363023302448 1
 
0.5%
126.93844474647274 1
 
0.5%
126.91245949597692 1
 
0.5%
126.91414185950288 1
 
0.5%
126.92366653309875 1
 
0.5%
126.92019966858126 1
 
0.5%
Other values (197) 197
95.2%
ValueCountFrequency (%)
126.89053787706328 1
0.5%
126.89297450945747 1
0.5%
126.89429422855208 1
0.5%
126.89492834317568 1
0.5%
126.89637504324344 1
0.5%
126.89771008632086 1
0.5%
126.89959479693036 1
0.5%
126.90097532542369 1
0.5%
126.90152630123704 1
0.5%
126.90221192543387 1
0.5%
ValueCountFrequency (%)
126.94127909940816 1
0.5%
126.94001691898802 1
0.5%
126.9400010445048 1
0.5%
126.93893804621548 1
0.5%
126.93844474647274 1
0.5%
126.93731862217942 1
0.5%
126.93587125076876 1
0.5%
126.9342301986244 1
0.5%
126.93382454419432 1
0.5%
126.933819451558 1
0.5%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
은평구
207 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
은평구 207
100.0%

Length

2024-04-06T19:31:53.236811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:31:53.443092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
은평구 207
100.0%

단속지점명
Text

Distinct206
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-06T19:31:53.774641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length9.6714976
Min length4

Characters and Unicode

Total characters2002
Distinct characters200
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique205 ?
Unique (%)99.0%

Sample

1st row연광초등학교정문 (주변)
2nd row은진초등학교(주변)
3rd row구산초(마을마당 주변)
4th row은평대영학교(주변)
5th row통일로855-20(주변)
ValueCountFrequency (%)
주변 36
 
11.0%
후문 8
 
2.4%
정문 7
 
2.1%
앞 5
 
1.5%
진관동 4
 
1.2%
대조동 4
 
1.2%
부근 4
 
1.2%
구산동 3
 
0.9%
선일 3
 
0.9%
사거리 3
 
0.9%
Other values (235) 251
76.5%
2024-04-06T19:31:54.504346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
6.0%
주 113
 
5.6%
변 108
 
5.4%
( 79
 
3.9%
) 79
 
3.9%
동 74
 
3.7%
1 69
 
3.4%
2 55
 
2.7%
- 53
 
2.6%
교 47
 
2.3%
Other values (190) 1204
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1344
67.1%
Decimal Number 319
 
15.9%
Space Separator 121
 
6.0%
Open Punctuation 79
 
3.9%
Close Punctuation 79
 
3.9%
Dash Punctuation 53
 
2.6%
Uppercase Letter 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 113
 
8.4%
변 108
 
8.0%
동 74
 
5.5%
교 47
 
3.5%
초 41
 
3.1%
학 31
 
2.3%
서 27
 
2.0%
로 25
 
1.9%
구 25
 
1.9%
등 25
 
1.9%
Other values (170) 828
61.6%
Decimal Number
ValueCountFrequency (%)
1 69
21.6%
2 55
17.2%
5 33
10.3%
3 33
10.3%
7 25
 
7.8%
4 24
 
7.5%
9 23
 
7.2%
0 20
 
6.3%
8 19
 
6.0%
6 18
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
D 1
14.3%
M 1
14.3%
N 1
14.3%
S 1
14.3%
W 1
14.3%
Space Separator
ValueCountFrequency (%)
121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1344
67.1%
Common 651
32.5%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 113
 
8.4%
변 108
 
8.0%
동 74
 
5.5%
교 47
 
3.5%
초 41
 
3.1%
학 31
 
2.3%
서 27
 
2.0%
로 25
 
1.9%
구 25
 
1.9%
등 25
 
1.9%
Other values (170) 828
61.6%
Common
ValueCountFrequency (%)
121
18.6%
( 79
12.1%
) 79
12.1%
1 69
10.6%
2 55
8.4%
- 53
8.1%
5 33
 
5.1%
3 33
 
5.1%
7 25
 
3.8%
4 24
 
3.7%
Other values (4) 80
12.3%
Latin
ValueCountFrequency (%)
C 2
28.6%
D 1
14.3%
M 1
14.3%
N 1
14.3%
S 1
14.3%
W 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1344
67.1%
ASCII 658
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
18.4%
( 79
12.0%
) 79
12.0%
1 69
10.5%
2 55
8.4%
- 53
8.1%
5 33
 
5.0%
3 33
 
5.0%
7 25
 
3.8%
4 24
 
3.6%
Other values (10) 87
13.2%
Hangul
ValueCountFrequency (%)
주 113
 
8.4%
변 108
 
8.0%
동 74
 
5.5%
교 47
 
3.5%
초 41
 
3.1%
학 31
 
2.3%
서 27
 
2.0%
로 25
 
1.9%
구 25
 
1.9%
등 25
 
1.9%
Other values (170) 828
61.6%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
불법주정차구역
207 

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 207
100.0%

Length

2024-04-06T19:31:54.771312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:31:55.044148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 207
100.0%

Interactions

2024-04-06T19:31:49.399123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:31:48.990159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:31:49.595839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:31:49.237708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T19:31:55.150652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.721
경도0.7211.000
2024-04-06T19:31:55.287498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.524
경도0.5241.000

Missing values

2024-04-06T19:31:49.822303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T19:31:49.997584image/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 은평구 불광동 442-4837.623959126.925227은평구연광초등학교정문 (주변)불법주정차구역
1서울 은평구 진관동 10237.631388126.921706은평구은진초등학교(주변)불법주정차구역
2서울 은평구 구산동 152-237.6117126.910102은평구구산초(마을마당 주변)불법주정차구역
3서울 은평구 역촌동 71-1237.605211126.908474은평구은평대영학교(주변)불법주정차구역
4서울 은평구 갈현동 396-937.619401126.919844은평구통일로855-20(주변)불법주정차구역
5서울 은평구 갈현동 403-137.620966126.919196은평구청구병원 후문(주변)불법주정차구역
6서울 은평구 갈현동 393-1337.622182126.918985은평구통일로85길6(주변)불법주정차구역
7서울 은평구 증산동 209-1737.58236126.905428은평구증산초교 정문 앞불법주정차구역
8서울 은평구 불광동 42337.62157126.926566은평구서서울농협건너(주변)불법주정차구역
9서울 은평구 불광동 104-4337.623413126.927632은평구불광주유소(주변)불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
197서울 은평구 대조동 185-7137.617506126.92146은평구대조동185-71불법주정차구역
198서울 은평구 수색로 190-2 (가로판매대)37.579212126.901526은평구수색성당 앞불법주정차구역
199서울 은평구 신사동 12-1637.599395126.907785은평구신사동12-16불법주정차구역
200서울 은평구 역촌동 23-5537.604336126.918383은평구역촌동 23-55불법주정차구역
201서울 은평구 구산동 178-1937.608026126.90772은평구구산동 178-19불법주정차구역
202서울 은평구 진관동 7837.634714126.920648은평구진관동 주민센터 주변불법주정차구역
203서울 은평구 응암동 334-937.590136126.918796은평구응암감리교회불법주정차구역
204서울 은평구 갈현동 430-1737.620676126.917177은평구갈현1동 430-17불법주정차구역
205서울 은평구 응암동 604-537.589917126.917323은평구응암오거리불법주정차구역
206서울 은평구 신사동 237-4337.597214126.904888은평구봉산 공영주차장 주변불법주정차구역