Overview

Dataset statistics

Number of variables6
Number of observations2858
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory142.5 KiB
Average record size in memory51.0 B

Variable types

Categorical2
Text1
Numeric2
DateTime1

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-20932/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 19:09:37.927015
Analysis finished2024-03-13 19:09:38.530052
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
강북구
2858 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강북구 2858
100.0%

Length

2024-03-14T04:09:38.587600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T04:09:38.659036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강북구 2858
100.0%

안심 주소
Text

UNIQUE 

Distinct2858
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
2024-03-14T04:09:38.818800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length22.991253
Min length4

Characters and Unicode

Total characters65709
Distinct characters76
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

Unique2858 ?
Unique (%)100.0%

Sample

1st rowtest
2nd row[1001][어린이학습체험관](고정)
3rd row[1002][방범-미아-005](회전M)
4th row[1003][방범-미아-009](회전M)
5th row[1004][어린이-미아-011](회전)
ValueCountFrequency (%)
test 1
 
< 0.1%
3160][방범-우이-130](고정,북 1
 
< 0.1%
3156][방범-수유3-101](어안m 1
 
< 0.1%
3158][방범-수유3-110](어안m 1
 
< 0.1%
3156][방범-수유3-102](회전,동 1
 
< 0.1%
3156][방범-수유3-103](고정,서 1
 
< 0.1%
3156][방범-수유3-104](고정,남 1
 
< 0.1%
3156][방범-수유3-105](고정,북 1
 
< 0.1%
3157][방범-수유3-106](어안m 1
 
< 0.1%
3157][방범-수유3-107](회전,남 1
 
< 0.1%
Other values (2850) 2850
99.7%
2024-03-14T04:09:39.123412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5710
 
8.7%
[ 5652
 
8.6%
] 5652
 
8.6%
1 4587
 
7.0%
3 3447
 
5.2%
0 2917
 
4.4%
) 2858
 
4.3%
( 2858
 
4.3%
2 2621
 
4.0%
범 2213
 
3.4%
Other values (66) 27194
41.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20878
31.8%
Other Letter 19396
29.5%
Open Punctuation 8510
13.0%
Close Punctuation 8510
13.0%
Dash Punctuation 5710
 
8.7%
Other Punctuation 1575
 
2.4%
Uppercase Letter 1121
 
1.7%
Lowercase Letter 4
 
< 0.1%
Math Symbol 3
 
< 0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
범 2213
 
11.4%
방 2213
 
11.4%
정 1304
 
6.7%
고 1202
 
6.2%
전 1119
 
5.8%
회 1119
 
5.8%
수 949
 
4.9%
어 874
 
4.5%
유 649
 
3.3%
이 625
 
3.2%
Other values (43) 7129
36.8%
Decimal Number
ValueCountFrequency (%)
1 4587
22.0%
3 3447
16.5%
0 2917
14.0%
2 2621
12.6%
4 1368
 
6.6%
5 1356
 
6.5%
6 1328
 
6.4%
7 1124
 
5.4%
8 1068
 
5.1%
9 1062
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
t 2
50.0%
s 1
25.0%
e 1
25.0%
Open Punctuation
ValueCountFrequency (%)
[ 5652
66.4%
( 2858
33.6%
Close Punctuation
ValueCountFrequency (%)
] 5652
66.4%
) 2858
33.6%
Other Punctuation
ValueCountFrequency (%)
, 1571
99.7%
. 4
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 5710
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1121
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45188
68.8%
Hangul 19396
29.5%
Latin 1125
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
범 2213
 
11.4%
방 2213
 
11.4%
정 1304
 
6.7%
고 1202
 
6.2%
전 1119
 
5.8%
회 1119
 
5.8%
수 949
 
4.9%
어 874
 
4.5%
유 649
 
3.3%
이 625
 
3.2%
Other values (43) 7129
36.8%
Common
ValueCountFrequency (%)
- 5710
12.6%
[ 5652
12.5%
] 5652
12.5%
1 4587
10.2%
3 3447
7.6%
0 2917
 
6.5%
) 2858
 
6.3%
( 2858
 
6.3%
2 2621
 
5.8%
, 1571
 
3.5%
Other values (9) 7315
16.2%
Latin
ValueCountFrequency (%)
M 1121
99.6%
t 2
 
0.2%
s 1
 
0.1%
e 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46313
70.5%
Hangul 19396
29.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5710
12.3%
[ 5652
12.2%
] 5652
12.2%
1 4587
9.9%
3 3447
7.4%
0 2917
 
6.3%
) 2858
 
6.2%
( 2858
 
6.2%
2 2621
 
5.7%
, 1571
 
3.4%
Other values (13) 8440
18.2%
Hangul
ValueCountFrequency (%)
범 2213
 
11.4%
방 2213
 
11.4%
정 1304
 
6.7%
고 1202
 
6.2%
전 1119
 
5.8%
회 1119
 
5.8%
수 949
 
4.9%
어 874
 
4.5%
유 649
 
3.3%
이 625
 
3.2%
Other values (43) 7129
36.8%

위도
Real number (ℝ)

Distinct411
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.635253
Minimum37.6106
Maximum37.6657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.2 KiB
2024-03-14T04:09:39.230170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.6106
5-th percentile37.6167
Q137.6282
median37.6398
Q337.6398
95-th percentile37.646915
Maximum37.6657
Range0.0551
Interquartile range (IQR)0.0116

Descriptive statistics

Standard deviation0.0096122573
Coefficient of variation (CV)0.00025540567
Kurtosis0.32885203
Mean37.635253
Median Absolute Deviation (MAD)0.0024
Skewness-0.37132354
Sum107561.55
Variance9.239549 × 10-5
MonotonicityNot monotonic
2024-03-14T04:09:39.331859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6398 1225
42.9%
37.6236 13
 
0.5%
37.6208 11
 
0.4%
37.6279 10
 
0.3%
37.6378 10
 
0.3%
37.6302 10
 
0.3%
37.6265 10
 
0.3%
37.626 10
 
0.3%
37.6368 10
 
0.3%
37.6251 10
 
0.3%
Other values (401) 1539
53.8%
ValueCountFrequency (%)
37.6106 3
0.1%
37.6112 2
0.1%
37.6113 1
 
< 0.1%
37.6117 1
 
< 0.1%
37.6118 2
0.1%
37.6119 1
 
< 0.1%
37.612 1
 
< 0.1%
37.6121 2
0.1%
37.6122 1
 
< 0.1%
37.6123 1
 
< 0.1%
ValueCountFrequency (%)
37.6657 2
0.1%
37.6635 4
0.1%
37.6631 1
 
< 0.1%
37.6625 1
 
< 0.1%
37.6624 2
0.1%
37.6623 2
0.1%
37.6621 2
0.1%
37.662 3
0.1%
37.6619 1
 
< 0.1%
37.6618 2
0.1%

경도
Real number (ℝ)

Distinct359
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02357
Minimum127.0036
Maximum127.0482
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.2 KiB
2024-03-14T04:09:39.440228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0036
5-th percentile127.0108
Q1127.0196
median127.0255
Q3127.0255
95-th percentile127.0345
Maximum127.0482
Range0.0446
Interquartile range (IQR)0.0059

Descriptive statistics

Standard deviation0.0069600571
Coefficient of variation (CV)5.4793429 × 10-5
Kurtosis0.6096517
Mean127.02357
Median Absolute Deviation (MAD)0.0022
Skewness-0.18687986
Sum363033.37
Variance4.8442395 × 10-5
MonotonicityNot monotonic
2024-03-14T04:09:39.566647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0255 1226
42.9%
127.0172 13
 
0.5%
127.0308 12
 
0.4%
127.0125 12
 
0.4%
127.0238 11
 
0.4%
127.0195 11
 
0.4%
127.009 11
 
0.4%
127.0201 11
 
0.4%
127.0126 11
 
0.4%
127.0132 11
 
0.4%
Other values (349) 1529
53.5%
ValueCountFrequency (%)
127.0036 1
< 0.1%
127.0039 1
< 0.1%
127.004 1
< 0.1%
127.0046 2
0.1%
127.0047 1
< 0.1%
127.0049 1
< 0.1%
127.0053 1
< 0.1%
127.0054 1
< 0.1%
127.0055 2
0.1%
127.0057 1
< 0.1%
ValueCountFrequency (%)
127.0482 2
0.1%
127.0478 2
0.1%
127.0471 1
 
< 0.1%
127.0465 2
0.1%
127.0463 1
 
< 0.1%
127.0462 2
0.1%
127.0461 3
0.1%
127.0452 1
 
< 0.1%
127.0445 2
0.1%
127.0444 1
 
< 0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
1
2858 

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 2858
100.0%

Length

2024-03-14T04:09:39.666679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T04:09:39.735682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2858
100.0%

수정 일시
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
Minimum2022-12-01 00:00:00
Maximum2022-12-01 00:00:00
2024-03-14T04:09:39.792201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T04:09:39.859917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T04:09:38.223891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T04:09:38.087117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T04:09:38.293482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T04:09:38.157560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T04:09:39.910582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.770
경도0.7701.000
2024-03-14T04:09:39.969345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.218
경도-0.2181.000

Missing values

2024-03-14T04:09:38.383409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T04:09:38.482032image/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
0강북구test37.6398127.025512022-12-01
1강북구[1001][어린이학습체험관](고정)37.627127.02712022-12-01
2강북구[1002][방범-미아-005](회전M)37.6275127.023712022-12-01
3강북구[1003][방범-미아-009](회전M)37.6285127.031212022-12-01
4강북구[1004][어린이-미아-011](회전)37.6256127.027812022-12-01
5강북구[1004][어린이-미아-090](고정,북)37.6398127.025512022-12-01
6강북구[1004][어린이-미아-117](어안M)37.6256127.027712022-12-01
7강북구[1006][방범-인수-006](회전M)37.6435127.004612022-12-01
8강북구[1007][방범-인수-029](회전M)37.6438127.005412022-12-01
9강북구[1007][방범-인수-117](고정,남서)37.6398127.025512022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
2848강북구[주정차-수유1-120](회전)37.6295127.016312022-12-01
2849강북구[주정차-수유1-207](회전M)37.6278127.011112022-12-01
2850강북구[주정차-수유3-034](회전M)37.6421127.023712022-12-01
2851강북구[주정차-수유3-035](회전M)37.6411127.02512022-12-01
2852강북구[주정차-수유3-036](회전M)37.6401127.026512022-12-01
2853강북구[주정차-수유3-129](회전M)37.6406127.017112022-12-01
2854강북구[주정차-우이-200](회전M)37.6517127.011912022-12-01
2855강북구[주정차-우이-279](회전M)37.6398127.025512022-12-01
2856강북구[주정차-인수-265](회전M)37.6383127.013812022-12-01
2857강북구관제센터 장비실(고정)37.6398127.025512022-12-01