Overview

Dataset statistics

Number of variables6
Number of observations2336
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.5 KiB
Average record size in memory51.1 B

Variable types

Categorical2
Text1
Numeric2
DateTime1

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-20925/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 14:33:01.305327
Analysis finished2024-03-13 14:33:02.125311
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
중구
2336 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 2336
100.0%

Length

2024-03-13T23:33:02.179103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:33:02.251008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 2336
100.0%

안심 주소
Text

UNIQUE 

Distinct2336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
2024-03-13T23:33:02.410047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length32.00214
Min length3

Characters and Unicode

Total characters74757
Distinct characters467
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

Unique2336 ?
Unique (%)100.0%

Sample

1st row02 정문
2nd row13 실내야구장 뒤
3rd row16 본관 뒤 주차장
4th row16 학교후문
5th row공002(손기정로 101_손기정체육공원 체육생활관)
ValueCountFrequency (%)
앞 489
 
6.1%
옆 142
 
1.8%
사거리 124
 
1.6%
삼거리 99
 
1.2%
앞)1 70
 
0.9%
골목 51
 
0.6%
정문 46
 
0.6%
후문 37
 
0.5%
뒤 32
 
0.4%
입구 27
 
0.3%
Other values (4102) 6857
86.0%
2024-03-13T23:33:02.794324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5642
 
7.5%
1 5404
 
7.2%
2 3816
 
5.1%
, 3426
 
4.6%
3 3068
 
4.1%
로 2446
 
3.3%
( 2337
 
3.1%
) 2252
 
3.0%
동 2252
 
3.0%
0 2243
 
3.0%
Other values (457) 41871
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33954
45.4%
Decimal Number 23896
32.0%
Space Separator 5642
 
7.5%
Other Punctuation 3429
 
4.6%
Open Punctuation 2337
 
3.1%
Close Punctuation 2252
 
3.0%
Dash Punctuation 1864
 
2.5%
Uppercase Letter 859
 
1.1%
Connector Punctuation 524
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 2446
 
7.2%
동 2252
 
6.6%
길 1659
 
4.9%
보 1457
 
4.3%
중 1424
 
4.2%
가 1121
 
3.3%
앞 858
 
2.5%
남 759
 
2.2%
산 678
 
2.0%
리 569
 
1.7%
Other values (418) 20731
61.1%
Uppercase Letter
ValueCountFrequency (%)
B 142
16.5%
G 101
11.8%
A 63
 
7.3%
J 53
 
6.2%
I 53
 
6.2%
O 52
 
6.1%
M 51
 
5.9%
D 47
 
5.5%
E 45
 
5.2%
L 42
 
4.9%
Other values (12) 210
24.4%
Decimal Number
ValueCountFrequency (%)
1 5404
22.6%
2 3816
16.0%
3 3068
12.8%
0 2243
9.4%
4 2006
 
8.4%
5 1998
 
8.4%
6 1657
 
6.9%
8 1368
 
5.7%
7 1320
 
5.5%
9 1016
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 3426
99.9%
. 3
 
0.1%
Space Separator
ValueCountFrequency (%)
5642
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2337
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2252
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1864
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 524
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39944
53.4%
Hangul 33954
45.4%
Latin 859
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 2446
 
7.2%
동 2252
 
6.6%
길 1659
 
4.9%
보 1457
 
4.3%
중 1424
 
4.2%
가 1121
 
3.3%
앞 858
 
2.5%
남 759
 
2.2%
산 678
 
2.0%
리 569
 
1.7%
Other values (418) 20731
61.1%
Latin
ValueCountFrequency (%)
B 142
16.5%
G 101
11.8%
A 63
 
7.3%
J 53
 
6.2%
I 53
 
6.2%
O 52
 
6.1%
M 51
 
5.9%
D 47
 
5.5%
E 45
 
5.2%
L 42
 
4.9%
Other values (12) 210
24.4%
Common
ValueCountFrequency (%)
5642
14.1%
1 5404
13.5%
2 3816
9.6%
, 3426
8.6%
3 3068
 
7.7%
( 2337
 
5.9%
) 2252
 
5.6%
0 2243
 
5.6%
4 2006
 
5.0%
5 1998
 
5.0%
Other values (7) 7752
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40803
54.6%
Hangul 33954
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5642
13.8%
1 5404
13.2%
2 3816
9.4%
, 3426
 
8.4%
3 3068
 
7.5%
( 2337
 
5.7%
) 2252
 
5.5%
0 2243
 
5.5%
4 2006
 
4.9%
5 1998
 
4.9%
Other values (29) 8611
21.1%
Hangul
ValueCountFrequency (%)
로 2446
 
7.2%
동 2252
 
6.6%
길 1659
 
4.9%
보 1457
 
4.3%
중 1424
 
4.2%
가 1121
 
3.3%
앞 858
 
2.5%
남 759
 
2.2%
산 678
 
2.0%
리 569
 
1.7%
Other values (418) 20731
61.1%

위도
Real number (ℝ)

Distinct205
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.560933
Minimum37.545
Maximum37.5708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.7 KiB
2024-03-13T23:33:02.953669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.545
5-th percentile37.5521
Q137.5576
median37.5613
Q337.5645
95-th percentile37.5681
Maximum37.5708
Range0.0258
Interquartile range (IQR)0.0069

Descriptive statistics

Standard deviation0.0048224528
Coefficient of variation (CV)0.00012839012
Kurtosis-0.42487452
Mean37.560933
Median Absolute Deviation (MAD)0.0035
Skewness-0.34987594
Sum87742.34
Variance2.3256051 × 10-5
MonotonicityNot monotonic
2024-03-13T23:33:03.209135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5576 34
 
1.5%
37.563 32
 
1.4%
37.5644 31
 
1.3%
37.5634 30
 
1.3%
37.5639 28
 
1.2%
37.5609 28
 
1.2%
37.5645 27
 
1.2%
37.5586 26
 
1.1%
37.5648 25
 
1.1%
37.5575 25
 
1.1%
Other values (195) 2050
87.8%
ValueCountFrequency (%)
37.545 1
 
< 0.1%
37.5464 3
0.1%
37.548 4
0.2%
37.5481 1
 
< 0.1%
37.5488 5
0.2%
37.5489 2
 
0.1%
37.5491 1
 
< 0.1%
37.5492 3
0.1%
37.5495 3
0.1%
37.5496 5
0.2%
ValueCountFrequency (%)
37.5708 2
 
0.1%
37.5705 4
 
0.2%
37.5704 4
 
0.2%
37.5702 8
0.3%
37.5697 2
 
0.1%
37.5695 8
0.3%
37.5693 3
 
0.1%
37.5692 9
0.4%
37.5691 3
 
0.1%
37.569 11
0.5%

경도
Real number (ℝ)

Distinct445
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99961
Minimum126.9621
Maximum127.0265
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.7 KiB
2024-03-13T23:33:03.442108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.9621
5-th percentile126.9683
Q1126.9849
median127.0048
Q3127.0136
95-th percentile127.0213
Maximum127.0265
Range0.0644
Interquartile range (IQR)0.0287

Descriptive statistics

Standard deviation0.017009952
Coefficient of variation (CV)0.00013393704
Kurtosis-0.93061677
Mean126.99961
Median Absolute Deviation (MAD)0.01165
Skewness-0.52035547
Sum296671.1
Variance0.00028933848
MonotonicityNot monotonic
2024-03-13T23:33:03.573796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0189 19
 
0.8%
126.9773 18
 
0.8%
127.0132 17
 
0.7%
127.0112 17
 
0.7%
127.0122 16
 
0.7%
126.9954 15
 
0.6%
127.0196 14
 
0.6%
127.0142 14
 
0.6%
126.9844 14
 
0.6%
127.0183 14
 
0.6%
Other values (435) 2178
93.2%
ValueCountFrequency (%)
126.9621 2
 
0.1%
126.9623 1
 
< 0.1%
126.9626 1
 
< 0.1%
126.9628 4
0.2%
126.9629 3
0.1%
126.963 2
 
0.1%
126.9632 3
0.1%
126.9633 1
 
< 0.1%
126.9634 7
0.3%
126.9635 4
0.2%
ValueCountFrequency (%)
127.0265 1
 
< 0.1%
127.0259 4
 
0.2%
127.0258 3
 
0.1%
127.0251 2
 
0.1%
127.025 2
 
0.1%
127.0248 3
 
0.1%
127.0245 2
 
0.1%
127.0242 3
 
0.1%
127.0239 3
 
0.1%
127.0238 14
0.6%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
1
2336 

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 2336
100.0%

Length

2024-03-13T23:33:03.688690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:33:03.769441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2336
100.0%

수정 일시
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
Minimum2022-12-01 00:00:00
Maximum2022-12-01 00:00:00
2024-03-13T23:33:03.827030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:33:03.897109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-13T23:33:01.767132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:33:01.589588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:33:01.848524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:33:01.684444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T23:33:03.948360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.596
경도0.5961.000
2024-03-13T23:33:04.014281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.201
경도0.2011.000

Missing values

2024-03-13T23:33:01.970238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T23:33:02.086811image/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
0중구02 정문37.5564127.017112022-12-01
1중구13 실내야구장 뒤37.5584127.014212022-12-01
2중구16 본관 뒤 주차장37.5563126.96412022-12-01
3중구16 학교후문37.5686126.974512022-12-01
4중구공002(손기정로 101_손기정체육공원 체육생활관)37.5558126.964112022-12-01
5중구공005(매봉18길 79,약수동 333-771,응봉근린공원-동산초교부근)37.5545127.01712022-12-01
6중구공006(칠패로 27,순화동 9-5,순화공원 광장뒤)37.5603126.971712022-12-01
7중구공007(칠패로 27,순화동 9-5,순화공원 펜스옆)37.56126.971612022-12-01
8중구공008(매봉18길 11,약수동 산55,응봉공원-약수지구대뒤편)37.5504127.013712022-12-01
9중구공009(매봉18길 11,약수동 844-10,응봉공원)37.5488127.010412022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
2326중구차141(을지로45길 46_동대문 한국산업단지공단)37.5663127.011912022-12-01
2327중구차142(퇴계로352_광희문 건너편)37.5646127.010412022-12-01
2328중구차143(필동로 42_필동어린이집)37.5578126.995612022-12-01
2329중구차144(황학동 697_미담어린이집)37.5657127.021212022-12-01
2330중구차145(다산로 96_약수어린이집)37.5526127.009212022-12-01
2331중구차146(명동8나길 34-1_중앙우체국뒤 사거리)37.5613126.983112022-12-01
2332중구차147(동호로10길 79_아이엠카페앞사거리)37.5573127.013412022-12-01
2333중구파고라37.562127.001812022-12-01
2334중구후관동 입구37.562127.001812022-12-01
2335중구흥인초교00(정문)37.5605127.014312022-12-01