Overview

Dataset statistics

Number of variables6
Number of observations3223
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory160.6 KiB
Average record size in memory51.0 B

Variable types

Categorical2
Text1
Numeric2
DateTime1

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-20936/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
수정 일시 has constant value ""Constant
CCTV 수량 is highly imbalanced (99.6%)Imbalance
안심 주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 13:39:20.519123
Analysis finished2024-03-13 13:39:21.491383
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
서대문구
3223 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서대문구 3223
100.0%

Length

2024-03-13T22:39:21.553963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:39:21.647006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서대문구 3223
100.0%

안심 주소
Text

UNIQUE 

Distinct3223
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
2024-03-13T22:39:21.853655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length26.775675
Min length4

Characters and Unicode

Total characters86298
Distinct characters316
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3223 ?
Unique (%)100.0%

Sample

1st row(광역감시01) 서05-703 안산철탑_회전_서북
2nd row(광역감시02) 서05-703-1 안산철탑_회전_동남
3rd row(광역감시03) 서05-703-2 안산철탑_고정_서
4th row(광역감시04) 서05-703-3 안산철탑_고정_북
5th row(광역감시05) 서05-703-4 안산철탑_고정_동
ValueCountFrequency (%)
앞 57
 
0.7%
홍은동 37
 
0.5%
연희동 35
 
0.4%
옆 29
 
0.4%
224-190 28
 
0.4%
갈매연어린이공원(남가좌동 28
 
0.4%
홍제동 24
 
0.3%
연희로39길 24
 
0.3%
맞은편 20
 
0.3%
갈매연어린이공원1(남가좌동 19
 
0.2%
Other values (4694) 7555
96.2%
2024-03-13T22:39:22.332251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9402
 
10.9%
- 8324
 
9.6%
2 5919
 
6.9%
0 5148
 
6.0%
4643
 
5.4%
3 4209
 
4.9%
4 3820
 
4.4%
서 3293
 
3.8%
5 2577
 
3.0%
( 2531
 
2.9%
Other values (306) 36432
42.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38298
44.4%
Other Letter 29864
34.6%
Dash Punctuation 8324
 
9.6%
Space Separator 4643
 
5.4%
Open Punctuation 2531
 
2.9%
Close Punctuation 2525
 
2.9%
Uppercase Letter 81
 
0.1%
Connector Punctuation 12
 
< 0.1%
Other Punctuation 10
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 3293
 
11.0%
동 2384
 
8.0%
로 2053
 
6.9%
길 1947
 
6.5%
가 1207
 
4.0%
홍 1162
 
3.9%
연 1014
 
3.4%
은 902
 
3.0%
북 846
 
2.8%
희 745
 
2.5%
Other values (278) 14311
47.9%
Decimal Number
ValueCountFrequency (%)
1 9402
24.5%
2 5919
15.5%
0 5148
13.4%
3 4209
11.0%
4 3820
10.0%
5 2577
 
6.7%
6 1992
 
5.2%
8 1873
 
4.9%
7 1764
 
4.6%
9 1594
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
C 27
33.3%
M 21
25.9%
D 21
25.9%
T 4
 
4.9%
U 4
 
4.9%
K 1
 
1.2%
N 1
 
1.2%
S 1
 
1.2%
H 1
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
e 4
40.0%
u 3
30.0%
c 3
30.0%
Dash Punctuation
ValueCountFrequency (%)
- 8324
100.0%
Space Separator
ValueCountFrequency (%)
4643
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2531
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2525
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56343
65.3%
Hangul 29864
34.6%
Latin 91
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 3293
 
11.0%
동 2384
 
8.0%
로 2053
 
6.9%
길 1947
 
6.5%
가 1207
 
4.0%
홍 1162
 
3.9%
연 1014
 
3.4%
은 902
 
3.0%
북 846
 
2.8%
희 745
 
2.5%
Other values (278) 14311
47.9%
Common
ValueCountFrequency (%)
1 9402
16.7%
- 8324
14.8%
2 5919
10.5%
0 5148
9.1%
4643
8.2%
3 4209
7.5%
4 3820
6.8%
5 2577
 
4.6%
( 2531
 
4.5%
) 2525
 
4.5%
Other values (6) 7245
12.9%
Latin
ValueCountFrequency (%)
C 27
29.7%
M 21
23.1%
D 21
23.1%
T 4
 
4.4%
e 4
 
4.4%
U 4
 
4.4%
u 3
 
3.3%
c 3
 
3.3%
K 1
 
1.1%
N 1
 
1.1%
Other values (2) 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56434
65.4%
Hangul 29864
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9402
16.7%
- 8324
14.7%
2 5919
10.5%
0 5148
9.1%
4643
8.2%
3 4209
7.5%
4 3820
6.8%
5 2577
 
4.6%
( 2531
 
4.5%
) 2525
 
4.5%
Other values (18) 7336
13.0%
Hangul
ValueCountFrequency (%)
서 3293
 
11.0%
동 2384
 
8.0%
로 2053
 
6.9%
길 1947
 
6.5%
가 1207
 
4.0%
홍 1162
 
3.9%
연 1014
 
3.4%
은 902
 
3.0%
북 846
 
2.8%
희 745
 
2.5%
Other values (278) 14311
47.9%

위도
Real number (ℝ)

Distinct396
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.577088
Minimum37.5558
Maximum37.6058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.5 KiB
2024-03-13T22:39:22.479638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.5558
5-th percentile37.5582
Q137.5673
median37.578
Q337.585
95-th percentile37.598
Maximum37.6058
Range0.05
Interquartile range (IQR)0.0177

Descriptive statistics

Standard deviation0.012110064
Coefficient of variation (CV)0.00032227256
Kurtosis-0.77632107
Mean37.577088
Median Absolute Deviation (MAD)0.0087
Skewness0.10134131
Sum121110.95
Variance0.00014665365
MonotonicityNot monotonic
2024-03-13T22:39:22.631394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5789 39
 
1.2%
37.5782 31
 
1.0%
37.5795 29
 
0.9%
37.5867 27
 
0.8%
37.5741 27
 
0.8%
37.5803 27
 
0.8%
37.5582 26
 
0.8%
37.5594 26
 
0.8%
37.578 25
 
0.8%
37.5619 24
 
0.7%
Other values (386) 2942
91.3%
ValueCountFrequency (%)
37.5558 2
 
0.1%
37.556 4
 
0.1%
37.5561 2
 
0.1%
37.5563 5
 
0.2%
37.5566 1
 
< 0.1%
37.5567 2
 
0.1%
37.5569 15
0.5%
37.557 10
0.3%
37.5572 8
0.2%
37.5573 3
 
0.1%
ValueCountFrequency (%)
37.6058 2
 
0.1%
37.6054 3
0.1%
37.6052 4
0.1%
37.6038 7
0.2%
37.6035 5
0.2%
37.6033 5
0.2%
37.6031 4
0.1%
37.603 4
0.1%
37.6026 3
0.1%
37.6024 5
0.2%

경도
Real number (ℝ)

Distinct458
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.93592
Minimum126.8915
Maximum126.9669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.5 KiB
2024-03-13T22:39:22.781136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.8915
5-th percentile126.91101
Q1126.92445
median126.9354
Q3126.9475
95-th percentile126.9599
Maximum126.9669
Range0.0754
Interquartile range (IQR)0.02305

Descriptive statistics

Standard deviation0.014936601
Coefficient of variation (CV)0.0001176704
Kurtosis-0.84603871
Mean126.93592
Median Absolute Deviation (MAD)0.0115
Skewness-0.092014344
Sum409114.48
Variance0.00022310204
MonotonicityNot monotonic
2024-03-13T22:39:22.974221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9178 38
 
1.2%
126.9194 28
 
0.9%
126.9506 24
 
0.7%
126.9234 24
 
0.7%
126.9172 22
 
0.7%
126.9549 21
 
0.7%
126.9353 21
 
0.7%
126.9326 21
 
0.7%
126.9278 20
 
0.6%
126.9463 20
 
0.6%
Other values (448) 2984
92.6%
ValueCountFrequency (%)
126.8915 2
 
0.1%
126.9035 1
 
< 0.1%
126.9039 3
 
0.1%
126.9048 2
 
0.1%
126.905 2
 
0.1%
126.9053 9
0.3%
126.9054 4
0.1%
126.9055 3
 
0.1%
126.906 4
0.1%
126.9061 4
0.1%
ValueCountFrequency (%)
126.9669 3
 
0.1%
126.9668 4
 
0.1%
126.9662 2
 
0.1%
126.966 3
 
0.1%
126.9659 5
0.2%
126.9652 7
0.2%
126.9651 3
 
0.1%
126.9644 12
0.4%
126.9642 1
 
< 0.1%
126.9641 7
0.2%

CCTV 수량
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
1
3222 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 3222
> 99.9%
2 1
 
< 0.1%

Length

2024-03-13T22:39:23.143192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:39:23.262692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3222
> 99.9%
2 1
 
< 0.1%

수정 일시
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
Minimum2022-12-01 00:00:00
Maximum2022-12-01 00:00:00
2024-03-13T22:39:23.341728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:39:23.432000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-13T22:39:21.076657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:39:20.870315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:39:21.177073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:39:20.957347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:39:23.497226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV 수량
위도1.0000.7770.045
경도0.7771.0000.000
CCTV 수량0.0450.0001.000
2024-03-13T22:39:23.578415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV 수량
위도1.000-0.0630.034
경도-0.0631.0000.000
CCTV 수량0.0340.0001.000

Missing values

2024-03-13T22:39:21.316570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:39:21.451457image/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
0서대문구(광역감시01) 서05-703 안산철탑_회전_서북37.577126.945712022-12-01
1서대문구(광역감시02) 서05-703-1 안산철탑_회전_동남37.5769126.94612022-12-01
2서대문구(광역감시03) 서05-703-2 안산철탑_고정_서37.577126.945512022-12-01
3서대문구(광역감시04) 서05-703-3 안산철탑_고정_북37.5771126.945912022-12-01
4서대문구(광역감시05) 서05-703-4 안산철탑_고정_동37.577126.946212022-12-01
5서대문구(광역감시06) 서05-703-5 안산철탑_고정_남37.5768126.945912022-12-01
6서대문구(스마트주차01) 서05-701-1 구청제1부설(북)구청광장37.5794126.936612022-12-01
7서대문구(스마트주차02) 서05-701-2구청제1부설(남)구청광장37.5789126.936612022-12-01
8서대문구(스마트주차03) 서05-702-1 구청제2부설(북)동신병원뒤37.5823126.937412022-12-01
9서대문구(스마트주차04) 서05-702-2 구청제2부설(남)동신병원뒤37.5817126.937512022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
3213서대문구서15-864 연흥장로교회 앞(남가좌동 386-1)37.5723126.922112022-12-01
3214서대문구서15-865 그린손세차장 앞(남가좌동 318-22)37.5758126.926512022-12-01
3215서대문구서15-866 서대문구청직장어린이집 앞(연희동 735)37.5785126.932912022-12-01
3216서대문구서15-867 SK광호주유소 앞(홍은동 275-70)37.5804126.936512022-12-01
3217서대문구서15-868 문화촌어린이공원 앞(홍제동 277-67)37.5945126.947212022-12-01
3218서대문구서15-868-1 간호대로1길4837.5945126.947212022-12-01
3219서대문구서15-869 수정쉐르빌 103동 앞(홍제동 287-198)37.5974126.946712022-12-01
3220서대문구서15-870 홍제천 유지용수 방류구(홍제동 4-4번지)37.5977126.956412022-12-01
3221서대문구서99-999 관제센터37.5791126.936812022-12-01
3222서대문구키오스크37.5791126.936812022-12-01