Overview

Dataset statistics

Number of variables6
Number of observations4036
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory201.1 KiB
Average record size in memory51.0 B

Variable types

Categorical3
Text1
Numeric2

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-20927/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
CCTV 수량 has constant value ""Constant
수정 일시 has constant value ""Constant
안심 주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 10:17:18.043616
Analysis finished2024-03-13 10:17:19.214963
Duration1.17 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
성동구
4036 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성동구 4036
100.0%

Length

2024-03-13T19:17:19.298263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T19:17:19.419430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성동구 4036
100.0%

안심 주소
Text

UNIQUE 

Distinct4036
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
2024-03-13T19:17:19.967981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length22.733647
Min length9

Characters and Unicode

Total characters91753
Distinct characters528
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4036 ?
Unique (%)100.0%

Sample

1st rowB010_(고정1)7_뚝섬역 7번출구 주변
2nd rowB012_(고정1)3_뚝섬역 2번출구 주변
3rd rowB012_(고정2)7_뚝섬역 2번출구 주변
4th rowB013_(고정1)3_성수역 4번출구 아래
5th rowB013_(고정2)7_성수역 4번출구 아래
ValueCountFrequency (%)
방향 376
 
5.0%
주변 77
 
1.0%
주정차 52
 
0.7%
7 37
 
0.5%
14 35
 
0.5%
분기 34
 
0.5%
교차로 31
 
0.4%
6 29
 
0.4%
15 28
 
0.4%
2 25
 
0.3%
Other values (5403) 6805
90.4%
2024-03-13T19:17:20.530060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 9171
 
10.0%
1 5243
 
5.7%
) 4484
 
4.9%
( 4482
 
4.9%
2 4067
 
4.4%
3508
 
3.8%
정 3393
 
3.7%
고 3137
 
3.4%
3 3037
 
3.3%
C 2932
 
3.2%
Other values (518) 48299
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37380
40.7%
Decimal Number 26956
29.4%
Connector Punctuation 9171
 
10.0%
Close Punctuation 4484
 
4.9%
Open Punctuation 4482
 
4.9%
Uppercase Letter 4267
 
4.7%
Space Separator 3508
 
3.8%
Dash Punctuation 1020
 
1.1%
Lowercase Letter 425
 
0.5%
Other Punctuation 57
 
0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 3393
 
9.1%
고 3137
 
8.4%
동 1375
 
3.7%
길 1274
 
3.4%
로 1021
 
2.7%
회 989
 
2.6%
전 918
 
2.5%
성 795
 
2.1%
수 689
 
1.8%
리 587
 
1.6%
Other values (473) 23202
62.1%
Uppercase Letter
ValueCountFrequency (%)
C 2932
68.7%
P 453
 
10.6%
F 219
 
5.1%
W 186
 
4.4%
G 162
 
3.8%
S 160
 
3.7%
D 43
 
1.0%
B 30
 
0.7%
A 25
 
0.6%
K 19
 
0.4%
Other values (9) 38
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 5243
19.5%
2 4067
15.1%
3 3037
11.3%
0 2739
10.2%
4 2287
8.5%
6 1970
 
7.3%
7 1970
 
7.3%
8 1940
 
7.2%
5 1878
 
7.0%
9 1825
 
6.8%
Lowercase Letter
ValueCountFrequency (%)
c 210
49.4%
v 105
24.7%
t 105
24.7%
e 3
 
0.7%
n 1
 
0.2%
k 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 44
77.2%
# 10
 
17.5%
@ 3
 
5.3%
Connector Punctuation
ValueCountFrequency (%)
_ 9171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4484
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4482
100.0%
Space Separator
ValueCountFrequency (%)
3508
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1020
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈈ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49680
54.1%
Hangul 37377
40.7%
Latin 4692
 
5.1%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 3393
 
9.1%
고 3137
 
8.4%
동 1375
 
3.7%
길 1274
 
3.4%
로 1021
 
2.7%
회 989
 
2.6%
전 918
 
2.5%
성 795
 
2.1%
수 689
 
1.8%
리 587
 
1.6%
Other values (472) 23199
62.1%
Latin
ValueCountFrequency (%)
C 2932
62.5%
P 453
 
9.7%
F 219
 
4.7%
c 210
 
4.5%
W 186
 
4.0%
G 162
 
3.5%
S 160
 
3.4%
v 105
 
2.2%
t 105
 
2.2%
D 43
 
0.9%
Other values (15) 117
 
2.5%
Common
ValueCountFrequency (%)
_ 9171
18.5%
1 5243
10.6%
) 4484
9.0%
( 4482
9.0%
2 4067
8.2%
3508
 
7.1%
3 3037
 
6.1%
0 2739
 
5.5%
4 2287
 
4.6%
6 1970
 
4.0%
Other values (9) 8692
17.5%
Han
ValueCountFrequency (%)
乍 3
75.0%
麗 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54372
59.3%
Hangul 37376
40.7%
CJK 3
 
< 0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 9171
16.9%
1 5243
9.6%
) 4484
 
8.2%
( 4482
 
8.2%
2 4067
 
7.5%
3508
 
6.5%
3 3037
 
5.6%
C 2932
 
5.4%
0 2739
 
5.0%
4 2287
 
4.2%
Other values (34) 12422
22.8%
Hangul
ValueCountFrequency (%)
정 3393
 
9.1%
고 3137
 
8.4%
동 1375
 
3.7%
길 1274
 
3.4%
로 1021
 
2.7%
회 989
 
2.6%
전 918
 
2.5%
성 795
 
2.1%
수 689
 
1.8%
리 587
 
1.6%
Other values (471) 23198
62.1%
CJK
ValueCountFrequency (%)
乍 3
100.0%
None
ValueCountFrequency (%)
㈈ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
麗 1
100.0%

위도
Real number (ℝ)

Distinct360
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.553689
Minimum37.5344
Maximum37.5719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-03-13T19:17:20.680451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.5344
5-th percentile37.5382
Q137.5468
median37.553
Q337.5616
95-th percentile37.568
Maximum37.5719
Range0.0375
Interquartile range (IQR)0.0148

Descriptive statistics

Standard deviation0.0092970355
Coefficient of variation (CV)0.0002475665
Kurtosis-1.0702815
Mean37.553689
Median Absolute Deviation (MAD)0.0078
Skewness-0.039979556
Sum151566.69
Variance8.6434869 × 10-5
MonotonicityNot monotonic
2024-03-13T19:17:20.835310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5486 45
 
1.1%
37.5612 42
 
1.0%
37.5488 37
 
0.9%
37.5482 34
 
0.8%
37.5613 30
 
0.7%
37.5642 30
 
0.7%
37.5602 29
 
0.7%
37.542 29
 
0.7%
37.55 29
 
0.7%
37.5483 28
 
0.7%
Other values (350) 3703
91.7%
ValueCountFrequency (%)
37.5344 1
 
< 0.1%
37.5345 4
0.1%
37.5346 3
0.1%
37.5347 3
0.1%
37.535 3
0.1%
37.5352 2
 
< 0.1%
37.5353 3
0.1%
37.5354 6
0.1%
37.5355 1
 
< 0.1%
37.5357 4
0.1%
ValueCountFrequency (%)
37.5719 1
 
< 0.1%
37.5717 1
 
< 0.1%
37.5716 2
 
< 0.1%
37.5713 3
 
0.1%
37.5712 7
0.2%
37.571 6
 
0.1%
37.5709 16
0.4%
37.5708 5
 
0.1%
37.5707 1
 
< 0.1%
37.5706 13
0.3%

경도
Real number (ℝ)

Distinct535
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04103
Minimum127.0087
Maximum127.0734
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-03-13T19:17:20.975272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0087
5-th percentile127.01718
Q1127.0301
median127.0409
Q3127.0525
95-th percentile127.0665
Maximum127.0734
Range0.0647
Interquartile range (IQR)0.0224

Descriptive statistics

Standard deviation0.014786288
Coefficient of variation (CV)0.00011638987
Kurtosis-0.84277529
Mean127.04103
Median Absolute Deviation (MAD)0.0111
Skewness0.045213045
Sum512737.6
Variance0.00021863432
MonotonicityNot monotonic
2024-03-13T19:17:21.119263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0393 38
 
0.9%
127.0331 24
 
0.6%
127.0467 24
 
0.6%
127.0518 23
 
0.6%
127.0357 23
 
0.6%
127.0454 23
 
0.6%
127.0337 23
 
0.6%
127.0304 23
 
0.6%
127.0324 22
 
0.5%
127.0461 22
 
0.5%
Other values (525) 3791
93.9%
ValueCountFrequency (%)
127.0087 1
 
< 0.1%
127.009 1
 
< 0.1%
127.0096 1
 
< 0.1%
127.0097 2
< 0.1%
127.0098 2
< 0.1%
127.0101 4
0.1%
127.0103 1
 
< 0.1%
127.0105 1
 
< 0.1%
127.0106 3
0.1%
127.0107 3
0.1%
ValueCountFrequency (%)
127.0734 3
0.1%
127.0727 2
 
< 0.1%
127.0726 1
 
< 0.1%
127.0725 1
 
< 0.1%
127.0723 2
 
< 0.1%
127.072 3
0.1%
127.0719 3
0.1%
127.0717 2
 
< 0.1%
127.0715 3
0.1%
127.0712 6
0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
1
4036 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 4036
100.0%

Length

2024-03-13T19:17:21.237140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T19:17:21.327825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4036
100.0%

수정 일시
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
2022-12-01
4036 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-01
2nd row2022-12-01
3rd row2022-12-01
4th row2022-12-01
5th row2022-12-01

Common Values

ValueCountFrequency (%)
2022-12-01 4036
100.0%

Length

2024-03-13T19:17:21.435501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T19:17:21.528898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 4036
100.0%

Interactions

2024-03-13T19:17:18.677114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T19:17:18.440778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T19:17:18.796024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T19:17:18.542634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T19:17:21.588892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.704
경도0.7041.000
2024-03-13T19:17:21.661896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.171
경도-0.1711.000

Missing values

2024-03-13T19:17:18.999592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T19:17:19.149879image/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
0성동구B010_(고정1)7_뚝섬역 7번출구 주변37.5474127.046512022-12-01
1성동구B012_(고정1)3_뚝섬역 2번출구 주변37.5476127.046812022-12-01
2성동구B012_(고정2)7_뚝섬역 2번출구 주변37.5476127.046812022-12-01
3성동구B013_(고정1)3_성수역 4번출구 아래37.5448127.054812022-12-01
4성동구B013_(고정2)7_성수역 4번출구 아래37.5448127.054812022-12-01
5성동구B014_(고정1)3_성수역 4번출구 건너37.5445127.055812022-12-01
6성동구B014_(고정2)7_성수역 4번출구 건너37.5445127.055812022-12-01
7성동구B015_(고정1)7_성수동2가 315-109 (분기)37.5442127.056812022-12-01
8성동구B015_(고정2)8_성수역 3번출구 아래37.5442127.056812022-12-01
9성동구B015_(고정3)3_성수동2가 315-109 (분기)37.5442127.056812022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
4026성동구W150_(고정2)1_송정12나길 2237.5506127.066712022-12-01
4027성동구W151_(고정1)3_둘레7길 1237.5378127.04912022-12-01
4028성동구W152_(고정)_둘레11길 1337.5368127.052112022-12-01
4029성동구W153_(고정1)3_금호산9나길 1937.5517127.018912022-12-01
4030성동구W154_(고정1)3_송정8길 1437.5492127.066112022-12-01
4031성동구관제센터 내부_137.5631127.036712022-12-01
4032성동구관제센터 내부_237.5631127.036712022-12-01
4033성동구관제센터 서버실_137.5631127.036712022-12-01
4034성동구관제센터 서버실_237.5631127.036712022-12-01
4035성동구관제센터카메라_(회전)37.5631127.036712022-12-01