Overview

Dataset statistics

Number of variables6
Number of observations3210
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory160.0 KiB
Average record size in memory51.0 B

Variable types

Categorical2
Text1
Numeric2
DateTime1

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-20939/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
수정 일시 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
CCTV 수량 is highly imbalanced (81.7%)Imbalance

Reproduction

Analysis started2024-03-13 13:37:49.392221
Analysis finished2024-03-13 13:37:50.907057
Duration1.51 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
강서구
3210 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강서구 3210
100.0%

Length

2024-03-13T22:37:50.978389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:37:51.080600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강서구 3210
100.0%

안심 주소
Text

Distinct3165
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2024-03-13T22:37:51.346888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length60
Mean length33.278505
Min length10

Characters and Unicode

Total characters106824
Distinct characters506
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3122 ?
Unique (%)97.3%

Sample

1st row(공사중)C231003(A1069)_염창동 280-21
2nd row(교체예정) C181022(SC121) - 마곡중앙5로 마곡중학교 맞은편
3rd row(교체예정) S312010_화곡본동 748-24 화일초등학교 병설유치원
4th row(교체예정)C181011(SC131) - 마곡중앙로 국제업무단지 CP2앞(보조1)
5th row(교체예정)C181026(SC106) - 마곡서1로 8단지 공원부지앞 삼거리
ValueCountFrequency (%)
방향 831
 
6.9%
564
 
4.7%
카메라 128
 
1.1%
1 128
 
1.1%
앞 80
 
0.7%
화곡동 78
 
0.7%
아파트 63
 
0.5%
6시 57
 
0.5%
고정1 51
 
0.4%
7시 49
 
0.4%
Other values (5943) 9943
83.1%
2024-03-13T22:37:51.947060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10848
 
10.2%
8806
 
8.2%
0 6864
 
6.4%
2 6383
 
6.0%
( 4210
 
3.9%
) 4202
 
3.9%
3 4074
 
3.8%
- 3327
 
3.1%
동 3241
 
3.0%
_ 3210
 
3.0%
Other values (496) 51659
48.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42670
39.9%
Other Letter 35196
32.9%
Space Separator 8806
 
8.2%
Uppercase Letter 4935
 
4.6%
Open Punctuation 4295
 
4.0%
Close Punctuation 4287
 
4.0%
Dash Punctuation 3327
 
3.1%
Connector Punctuation 3210
 
3.0%
Other Punctuation 69
 
0.1%
Lowercase Letter 28
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3241
 
9.2%
화 2303
 
6.5%
곡 2035
 
5.8%
방 1583
 
4.5%
정 1491
 
4.2%
고 1398
 
4.0%
향 1077
 
3.1%
로 875
 
2.5%
보 716
 
2.0%
공 694
 
2.0%
Other values (442) 19783
56.2%
Uppercase Letter
ValueCountFrequency (%)
C 2714
55.0%
A 666
 
13.5%
S 562
 
11.4%
P 400
 
8.1%
I 179
 
3.6%
T 142
 
2.9%
Z 82
 
1.7%
G 68
 
1.4%
D 36
 
0.7%
B 33
 
0.7%
Other values (11) 53
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 10848
25.4%
0 6864
16.1%
2 6383
15.0%
3 4074
 
9.5%
4 3002
 
7.0%
6 2733
 
6.4%
5 2508
 
5.9%
8 2390
 
5.6%
7 2013
 
4.7%
9 1855
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
a 8
28.6%
e 5
17.9%
r 4
14.3%
m 4
14.3%
o 2
 
7.1%
n 2
 
7.1%
b 1
 
3.6%
y 1
 
3.6%
l 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 32
46.4%
, 25
36.2%
# 5
 
7.2%
/ 4
 
5.8%
? 2
 
2.9%
& 1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 4210
98.0%
[ 85
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 4202
98.0%
] 85
 
2.0%
Space Separator
ValueCountFrequency (%)
8806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3327
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3210
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66665
62.4%
Hangul 35196
32.9%
Latin 4963
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3241
 
9.2%
화 2303
 
6.5%
곡 2035
 
5.8%
방 1583
 
4.5%
정 1491
 
4.2%
고 1398
 
4.0%
향 1077
 
3.1%
로 875
 
2.5%
보 716
 
2.0%
공 694
 
2.0%
Other values (442) 19783
56.2%
Latin
ValueCountFrequency (%)
C 2714
54.7%
A 666
 
13.4%
S 562
 
11.3%
P 400
 
8.1%
I 179
 
3.6%
T 142
 
2.9%
Z 82
 
1.7%
G 68
 
1.4%
D 36
 
0.7%
B 33
 
0.7%
Other values (20) 81
 
1.6%
Common
ValueCountFrequency (%)
1 10848
16.3%
8806
13.2%
0 6864
10.3%
2 6383
9.6%
( 4210
 
6.3%
) 4202
 
6.3%
3 4074
 
6.1%
- 3327
 
5.0%
_ 3210
 
4.8%
4 3002
 
4.5%
Other values (14) 11739
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71628
67.1%
Hangul 35196
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10848
15.1%
8806
12.3%
0 6864
9.6%
2 6383
 
8.9%
( 4210
 
5.9%
) 4202
 
5.9%
3 4074
 
5.7%
- 3327
 
4.6%
_ 3210
 
4.5%
4 3002
 
4.2%
Other values (44) 16702
23.3%
Hangul
ValueCountFrequency (%)
동 3241
 
9.2%
화 2303
 
6.5%
곡 2035
 
5.8%
방 1583
 
4.5%
정 1491
 
4.2%
고 1398
 
4.0%
향 1077
 
3.1%
로 875
 
2.5%
보 716
 
2.0%
공 694
 
2.0%
Other values (442) 19783
56.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct519
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.551925
Minimum37.5272
Maximum37.5888
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-03-13T22:37:52.087474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.5272
5-th percentile37.5308
Q137.5393
median37.5514
Q337.563075
95-th percentile37.5773
Maximum37.5888
Range0.0616
Interquartile range (IQR)0.023775

Descriptive statistics

Standard deviation0.014519404
Coefficient of variation (CV)0.00038664873
Kurtosis-0.8640024
Mean37.551925
Median Absolute Deviation (MAD)0.01195
Skewness0.27464143
Sum120541.68
Variance0.0002108131
MonotonicityNot monotonic
2024-03-13T22:37:52.269541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5579 25
 
0.8%
37.546 21
 
0.7%
37.5356 20
 
0.6%
37.5527 18
 
0.6%
37.5602 18
 
0.6%
37.5344 18
 
0.6%
37.5308 18
 
0.6%
37.5535 17
 
0.5%
37.5561 16
 
0.5%
37.5502 16
 
0.5%
Other values (509) 3023
94.2%
ValueCountFrequency (%)
37.5272 1
 
< 0.1%
37.5276 3
0.1%
37.5277 4
0.1%
37.5278 2
 
0.1%
37.528 1
 
< 0.1%
37.5281 1
 
< 0.1%
37.5283 4
0.1%
37.5284 3
0.1%
37.5285 1
 
< 0.1%
37.5287 6
0.2%
ValueCountFrequency (%)
37.5888 2
0.1%
37.5887 1
 
< 0.1%
37.5881 2
0.1%
37.5878 3
0.1%
37.5876 1
 
< 0.1%
37.587 2
0.1%
37.5868 2
0.1%
37.5865 2
0.1%
37.5864 3
0.1%
37.586 3
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct597
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.83895
Minimum126.7986
Maximum126.8772
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-03-13T22:37:52.417738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.7986
5-th percentile126.8075
Q1126.8253
median126.8422
Q3126.8516
95-th percentile126.86326
Maximum126.8772
Range0.0786
Interquartile range (IQR)0.0263

Descriptive statistics

Standard deviation0.018012035
Coefficient of variation (CV)0.00014200712
Kurtosis-0.63894382
Mean126.83895
Median Absolute Deviation (MAD)0.011
Skewness-0.42541219
Sum407153.04
Variance0.00032443339
MonotonicityNot monotonic
2024-03-13T22:37:52.571561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8416 20
 
0.6%
126.8433 19
 
0.6%
126.8443 19
 
0.6%
126.8488 19
 
0.6%
126.8501 16
 
0.5%
126.8503 16
 
0.5%
126.846 16
 
0.5%
126.8442 16
 
0.5%
126.8422 16
 
0.5%
126.843 16
 
0.5%
Other values (587) 3037
94.6%
ValueCountFrequency (%)
126.7986 2
 
0.1%
126.7987 2
 
0.1%
126.7988 3
 
0.1%
126.7991 11
0.3%
126.7992 2
 
0.1%
126.7993 2
 
0.1%
126.7994 5
0.2%
126.7996 2
 
0.1%
126.7997 3
 
0.1%
126.7998 3
 
0.1%
ValueCountFrequency (%)
126.8772 5
0.2%
126.8769 1
 
< 0.1%
126.8767 1
 
< 0.1%
126.8766 6
0.2%
126.8765 2
 
0.1%
126.8762 3
0.1%
126.8755 1
 
< 0.1%
126.8752 3
0.1%
126.8746 2
 
0.1%
126.8743 5
0.2%

CCTV 수량
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
1
2969 
2
 
215
3
 
24
6
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2969
92.5%
2 215
 
6.7%
3 24
 
0.7%
6 1
 
< 0.1%
4 1
 
< 0.1%

Length

2024-03-13T22:37:52.719923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:37:52.822539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2969
92.5%
2 215
 
6.7%
3 24
 
0.7%
6 1
 
< 0.1%
4 1
 
< 0.1%

수정 일시
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
Minimum2022-12-01 00:00:00
Maximum2022-12-01 00:00:00
2024-03-13T22:37:52.921007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:37:53.030970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-13T22:37:50.471326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:37:49.818530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:37:50.577981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:37:50.365243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:37:53.108500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV 수량
위도1.0000.8020.017
경도0.8021.0000.023
CCTV 수량0.0170.0231.000
2024-03-13T22:37:53.203337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV 수량
위도1.000-0.5790.007
경도-0.5791.0000.010
CCTV 수량0.0070.0101.000

Missing values

2024-03-13T22:37:50.755644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:37:50.861096image/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

자치구안심 주소위도경도CCTV 수량수정 일시
0강서구(공사중)C231003(A1069)_염창동 280-2137.5486126.871212022-12-01
1강서구(교체예정) C181022(SC121) - 마곡중앙5로 마곡중학교 맞은편37.567126.821912022-12-01
2강서구(교체예정) S312010_화곡본동 748-24 화일초등학교 병설유치원37.5405126.84812022-12-01
3강서구(교체예정)C181011(SC131) - 마곡중앙로 국제업무단지 CP2앞(보조1)37.5634126.827112022-12-01
4강서구(교체예정)C181026(SC106) - 마곡서1로 8단지 공원부지앞 삼거리37.5651126.819312022-12-01
5강서구(교체예정)C181046(SC212) - 공항대로 국제업무단지 C6 앞37.5594126.832112022-12-01
6강서구(교체예정)P183019(SC공원22) - 공항대로 마곡역 우측 연결녹지22호 내(보조1줌)37.5602126.828312022-12-01
7강서구(노후교체예정)I116001_가양동 97-8 (CJ한길자동차 매매단지)37.5662126.84512022-12-01
8강서구(대체카메라)C161021_등촌2동 532-837.5496126.861712022-12-01
9강서구(분기점철거)C231014_염창동 279-12(고정1) - 공항대로59다길 방향37.549126.871612022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
3200강서구쉼터188001_양천향교역 7번출구_고정2_외부_감시용(녹화)37.5672126.840812022-12-01
3201강서구쉼터228001 내부 사회적 거리(방화동 855 방화근린공원) (라이브)37.5819126.813612022-12-01
3202강서구쉼터228001 사회적거리등_고정1_(방화동 855 방화근린공원) (녹화)37.5819126.813612022-12-01
3203강서구쉼터228001_방화근린공원_고정2_외부 감시용 (방화동 855 방화근린공원) (녹화)37.5819126.813612022-12-01
3204강서구쉼터318001 사회적거리등(화곡동 56-3한글어린이공원) (녹화)37.5386126.850312022-12-01
3205강서구쉼터318001 사회적거리등(화곡동 56-3한글어린이공원) (라이브)37.5386126.850312022-12-01
3206강서구어린이체험관 - 카메라 137.5706126.817212022-12-01
3207강서구어린이체험관(2F)37.5706126.817112022-12-01
3208강서구어린이체험관(4F)37.5707126.817112022-12-01
3209강서구철거됨_S232010(A6038)_염창동 271(염창초등학교)37.553126.866512022-12-01