Overview

Dataset statistics

Number of variables12
Number of observations105
Missing cells111
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.5 KiB
Average record size in memory102.3 B

Variable types

Categorical3
Text2
Unsupported1
Numeric4
Boolean1
DateTime1

Dataset

Description파일 다운로드
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-15013/S/1/datasetView.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
CCTV설치대수 is highly overall correlated with CCTV설치여부High correlation
관할경찰서명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
CCTV설치여부 is highly overall correlated with CCTV설치대수High correlation
CCTV설치여부 is highly imbalanced (86.4%)Imbalance
소재지지번주소 has 105 (100.0%) missing valuesMissing
CCTV설치대수 has 3 (2.9%) missing valuesMissing
보호구역도로폭 has 3 (2.9%) missing valuesMissing
대상시설명 has unique valuesUnique
소재지지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 09:06:03.575703
Analysis finished2023-12-11 09:06:05.949238
Duration2.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류
Categorical

Distinct4
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size972.0 B
어린이집
45 
초등학교
33 
유치원
24 
특수학교
 
3

Length

Max length4
Median length4
Mean length3.7714286
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 45
42.9%
초등학교 33
31.4%
유치원 24
22.9%
특수학교 3
 
2.9%

Length

2023-12-11T18:06:06.021904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:06.161720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 45
42.9%
초등학교 33
31.4%
유치원 24
22.9%
특수학교 3
 
2.9%

대상시설명
Text

UNIQUE 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
2023-12-11T18:06:06.442848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length6.3904762
Min length4

Characters and Unicode

Total characters671
Distinct characters134
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)100.0%

Sample

1st row돌샘유치원
2nd row신양유치원
3rd row이화유치원
4th row영동제일유치원
5th row소망유치원
ValueCountFrequency (%)
돌샘유치원 1
 
1.0%
양전초등학교 1
 
1.0%
구민회관어린이집 1
 
1.0%
강남구청어린이집 1
 
1.0%
튼튼영재어린이집 1
 
1.0%
청수어린이집 1
 
1.0%
성아어린이집 1
 
1.0%
선재어린이집 1
 
1.0%
킹스키즈어린이집 1
 
1.0%
한티어린이집 1
 
1.0%
Other values (95) 95
90.5%
2023-12-11T18:06:06.887925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 49
 
7.3%
집 45
 
6.7%
린 45
 
6.7%
어 45
 
6.7%
학 40
 
6.0%
교 39
 
5.8%
초 38
 
5.7%
등 37
 
5.5%
원 28
 
4.2%
치 26
 
3.9%
Other values (124) 279
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 669
99.7%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 49
 
7.3%
집 45
 
6.7%
린 45
 
6.7%
어 45
 
6.7%
학 40
 
6.0%
교 39
 
5.8%
초 38
 
5.7%
등 37
 
5.5%
원 28
 
4.2%
치 26
 
3.9%
Other values (122) 277
41.4%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 669
99.7%
Common 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 49
 
7.3%
집 45
 
6.7%
린 45
 
6.7%
어 45
 
6.7%
학 40
 
6.0%
교 39
 
5.8%
초 38
 
5.7%
등 37
 
5.5%
원 28
 
4.2%
치 26
 
3.9%
Other values (122) 277
41.4%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 669
99.7%
ASCII 2
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 49
 
7.3%
집 45
 
6.7%
린 45
 
6.7%
어 45
 
6.7%
학 40
 
6.0%
교 39
 
5.8%
초 38
 
5.7%
등 37
 
5.5%
원 28
 
4.2%
치 26
 
3.9%
Other values (122) 277
41.4%
ASCII
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

소재지도로명주소
Text

Distinct99
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size972.0 B
2023-12-11T18:06:07.236297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length19.161905
Min length16

Characters and Unicode

Total characters2012
Distinct characters74
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)88.6%

Sample

1st row서울특별시 강남구 개포로 516
2nd row서울특별시 강남구 선릉로10길 18-6
3rd row서울특별시 강남구 개포로109길 9
4th row서울특별시 강남구 삼성로120길 28
5th row서울특별시 강남구 광평로56길 11
ValueCountFrequency (%)
서울특별시 105
24.7%
강남구 105
24.7%
개포로 6
 
1.4%
16 5
 
1.2%
9 5
 
1.2%
17 4
 
0.9%
일원로 4
 
0.9%
29 3
 
0.7%
선릉로 3
 
0.7%
27 3
 
0.7%
Other values (140) 182
42.8%
2023-12-11T18:06:07.740202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
320
15.9%
남 111
 
5.5%
구 111
 
5.5%
강 109
 
5.4%
서 105
 
5.2%
로 105
 
5.2%
특 105
 
5.2%
별 105
 
5.2%
시 105
 
5.2%
울 105
 
5.2%
Other values (64) 731
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1285
63.9%
Decimal Number 397
 
19.7%
Space Separator 320
 
15.9%
Dash Punctuation 8
 
0.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 111
8.6%
구 111
8.6%
강 109
8.5%
서 105
8.2%
로 105
8.2%
특 105
8.2%
별 105
8.2%
시 105
8.2%
울 105
8.2%
길 79
 
6.1%
Other values (51) 245
19.1%
Decimal Number
ValueCountFrequency (%)
1 82
20.7%
2 58
14.6%
3 42
10.6%
6 41
10.3%
5 39
9.8%
4 34
8.6%
7 30
 
7.6%
8 25
 
6.3%
0 24
 
6.0%
9 22
 
5.5%
Space Separator
ValueCountFrequency (%)
320
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1285
63.9%
Common 727
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 111
8.6%
구 111
8.6%
강 109
8.5%
서 105
8.2%
로 105
8.2%
특 105
8.2%
별 105
8.2%
시 105
8.2%
울 105
8.2%
길 79
 
6.1%
Other values (51) 245
19.1%
Common
ValueCountFrequency (%)
320
44.0%
1 82
 
11.3%
2 58
 
8.0%
3 42
 
5.8%
6 41
 
5.6%
5 39
 
5.4%
4 34
 
4.7%
7 30
 
4.1%
8 25
 
3.4%
0 24
 
3.3%
Other values (3) 32
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1285
63.9%
ASCII 727
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
320
44.0%
1 82
 
11.3%
2 58
 
8.0%
3 42
 
5.8%
6 41
 
5.6%
5 39
 
5.4%
4 34
 
4.7%
7 30
 
4.1%
8 25
 
3.4%
0 24
 
3.3%
Other values (3) 32
 
4.4%
Hangul
ValueCountFrequency (%)
남 111
8.6%
구 111
8.6%
강 109
8.5%
서 105
8.2%
로 105
8.2%
특 105
8.2%
별 105
8.2%
시 105
8.2%
울 105
8.2%
길 79
 
6.1%
Other values (51) 245
19.1%

소재지지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing105
Missing (%)100.0%
Memory size1.1 KiB

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.497584
Minimum37.464621
Maximum37.531739
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T18:06:07.895454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.464621
5-th percentile37.47353
Q137.486214
median37.494321
Q337.511421
95-th percentile37.525254
Maximum37.531739
Range0.067117667
Interquartile range (IQR)0.025207216

Descriptive statistics

Standard deviation0.016502733
Coefficient of variation (CV)0.00044010122
Kurtosis-0.74558652
Mean37.497584
Median Absolute Deviation (MAD)0.01089024
Skewness0.28650778
Sum3937.2463
Variance0.00027234018
MonotonicityNot monotonic
2023-12-11T18:06:08.072877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.495751 2
 
1.9%
37.5221207444 2
 
1.9%
37.4911505764 2
 
1.9%
37.503722762 2
 
1.9%
37.4868054401 2
 
1.9%
37.4931611542 2
 
1.9%
37.4891403199 1
 
1.0%
37.499834126 1
 
1.0%
37.4938869965 1
 
1.0%
37.5179663586 1
 
1.0%
Other values (89) 89
84.8%
ValueCountFrequency (%)
37.4646213557 1
1.0%
37.4668200316 1
1.0%
37.468857 1
1.0%
37.4699201969 1
1.0%
37.472191 1
1.0%
37.4735223605 1
1.0%
37.4735607837 1
1.0%
37.474559 1
1.0%
37.475292873 1
1.0%
37.475915 1
1.0%
ValueCountFrequency (%)
37.5317390226 1
1.0%
37.5315339928 1
1.0%
37.5293482238 1
1.0%
37.5282817801 1
1.0%
37.5262731393 1
1.0%
37.525305 1
1.0%
37.525052 1
1.0%
37.523923 1
1.0%
37.5233612951 1
1.0%
37.5226241543 1
1.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06151
Minimum127.02399
Maximum127.11161
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T18:06:08.234425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02399
5-th percentile127.03113
Q1127.04515
median127.05636
Q3127.07808
95-th percentile127.10155
Maximum127.11161
Range0.087619477
Interquartile range (IQR)0.032925115

Descriptive statistics

Standard deviation0.022275249
Coefficient of variation (CV)0.00017531075
Kurtosis-0.69346795
Mean127.06151
Median Absolute Deviation (MAD)0.016242513
Skewness0.48669037
Sum13341.459
Variance0.00049618671
MonotonicityNot monotonic
2023-12-11T18:06:08.389484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.075096 2
 
1.9%
127.0401134152 2
 
1.9%
127.101549 2
 
1.9%
127.0635640432 2
 
1.9%
127.0699765891 2
 
1.9%
127.0326030259 2
 
1.9%
127.070869784 1
 
1.0%
127.056227 1
 
1.0%
127.0642703746 1
 
1.0%
127.0470610826 1
 
1.0%
Other values (89) 89
84.8%
ValueCountFrequency (%)
127.023991523 1
1.0%
127.0262216669 1
1.0%
127.026898 1
1.0%
127.0285346272 1
1.0%
127.0292753857 1
1.0%
127.0308412892 1
1.0%
127.0322634719 1
1.0%
127.0326030259 2
1.9%
127.035354 1
1.0%
127.0356145558 1
1.0%
ValueCountFrequency (%)
127.111611 1
1.0%
127.108267 1
1.0%
127.1056313773 1
1.0%
127.1055894642 1
1.0%
127.104503 1
1.0%
127.101549 2
1.9%
127.0998274586 1
1.0%
127.0995995421 1
1.0%
127.099054 1
1.0%
127.0981866623 1
1.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
서울특별시 강남구청
105 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 강남구청
2nd row서울특별시 강남구청
3rd row서울특별시 강남구청
4th row서울특별시 강남구청
5th row서울특별시 강남구청

Common Values

ValueCountFrequency (%)
서울특별시 강남구청 105
100.0%

Length

2023-12-11T18:06:08.522336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:08.634650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 105
50.0%
강남구청 105
50.0%

관할경찰서명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size972.0 B
수서경찰서
73 
강남경찰서
32 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수서경찰서
2nd row수서경찰서
3rd row수서경찰서
4th row강남경찰서
5th row수서경찰서

Common Values

ValueCountFrequency (%)
수서경찰서 73
69.5%
강남경찰서 32
30.5%

Length

2023-12-11T18:06:08.765895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:08.879305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수서경찰서 73
69.5%
강남경찰서 32
30.5%

CCTV설치여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size237.0 B
True
103 
False
 
2
ValueCountFrequency (%)
True 103
98.1%
False 2
 
1.9%
2023-12-11T18:06:09.003585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CCTV설치대수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)8.8%
Missing3
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean2.2058824
Minimum0
Maximum8
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T18:06:09.130753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile6
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7311259
Coefficient of variation (CV)0.78477706
Kurtosis3.0780554
Mean2.2058824
Median Absolute Deviation (MAD)1
Skewness1.8360286
Sum225
Variance2.9967967
MonotonicityNot monotonic
2023-12-11T18:06:09.281117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 46
43.8%
2 28
26.7%
3 11
 
10.5%
4 5
 
4.8%
5 4
 
3.8%
8 3
 
2.9%
6 2
 
1.9%
7 2
 
1.9%
0 1
 
1.0%
(Missing) 3
 
2.9%
ValueCountFrequency (%)
0 1
 
1.0%
1 46
43.8%
2 28
26.7%
3 11
 
10.5%
4 5
 
4.8%
5 4
 
3.8%
6 2
 
1.9%
7 2
 
1.9%
8 3
 
2.9%
ValueCountFrequency (%)
8 3
 
2.9%
7 2
 
1.9%
6 2
 
1.9%
5 4
 
3.8%
4 5
 
4.8%
3 11
 
10.5%
2 28
26.7%
1 46
43.8%
0 1
 
1.0%

보호구역도로폭
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)39.2%
Missing3
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean10.833333
Minimum4
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T18:06:09.452347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5.5
Q16
median8
Q312
95-th percentile25
Maximum40
Range36
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.1566259
Coefficient of variation (CV)0.66061162
Kurtosis4.9962223
Mean10.833333
Median Absolute Deviation (MAD)2
Skewness2.1499341
Sum1105
Variance51.217294
MonotonicityNot monotonic
2023-12-11T18:06:09.601622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
6.0 26
24.8%
8.0 13
 
12.4%
12.0 7
 
6.7%
15.0 4
 
3.8%
5.5 4
 
3.8%
20.0 3
 
2.9%
25.0 3
 
2.9%
5.9 2
 
1.9%
6.5 2
 
1.9%
9.0 2
 
1.9%
Other values (30) 36
34.3%
(Missing) 3
 
2.9%
ValueCountFrequency (%)
4.0 1
 
1.0%
5.3 1
 
1.0%
5.4 1
 
1.0%
5.5 4
 
3.8%
5.7 1
 
1.0%
5.8 1
 
1.0%
5.9 2
 
1.9%
6.0 26
24.8%
6.1 1
 
1.0%
6.5 2
 
1.9%
ValueCountFrequency (%)
40.0 2
1.9%
30.0 2
1.9%
28.7 1
 
1.0%
25.0 3
2.9%
23.1 1
 
1.0%
20.0 3
2.9%
19.7 1
 
1.0%
15.2 1
 
1.0%
15.0 4
3.8%
14.7 1
 
1.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
Minimum2019-12-20 00:00:00
Maximum2019-12-20 00:00:00
2023-12-11T18:06:10.021468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:10.121803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T18:06:05.064693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:03.960785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.341226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.672648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:05.177324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.051552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.419766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.761915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:05.279304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.150590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.503609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.850036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:05.387407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.258233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.587787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:04.951094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:06:10.222959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류소재지도로명주소위도경도관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭
시설종류1.0000.6150.0000.0000.1150.0000.5140.121
소재지도로명주소0.6151.0001.0001.0001.0001.0000.4050.951
위도0.0001.0001.0000.7070.9990.1330.0000.286
경도0.0001.0000.7071.0000.7110.3350.0360.432
관할경찰서명0.1151.0000.9990.7111.0000.0000.1690.376
CCTV설치여부0.0001.0000.1330.3350.0001.0001.0000.000
CCTV설치대수0.5140.4050.0000.0360.1691.0001.0000.000
보호구역도로폭0.1210.9510.2860.4320.3760.0000.0001.000
2023-12-11T18:06:10.365283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할경찰서명CCTV설치여부시설종류
관할경찰서명1.0000.0000.074
CCTV설치여부0.0001.0000.000
시설종류0.0740.0001.000
2023-12-11T18:06:10.488978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV설치대수보호구역도로폭시설종류관할경찰서명CCTV설치여부
위도1.000-0.6310.136-0.4420.0000.9390.094
경도-0.6311.000-0.1280.3670.0000.5330.246
CCTV설치대수0.136-0.1281.000-0.1060.3450.1600.964
보호구역도로폭-0.4420.367-0.1061.0000.0730.3470.000
시설종류0.0000.0000.3450.0731.0000.0740.000
관할경찰서명0.9390.5330.1600.3470.0741.0000.000
CCTV설치여부0.0940.2460.9640.0000.0000.0001.000

Missing values

2023-12-11T18:06:05.512147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:06:05.715044image/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.
2023-12-11T18:06:05.892250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
0유치원돌샘유치원서울특별시 강남구 개포로 516<NA>37.48914127.07087서울특별시 강남구청수서경찰서Y112.62019-12-20
1유치원신양유치원서울특별시 강남구 선릉로10길 18-6<NA>37.483431127.061678서울특별시 강남구청수서경찰서Y26.02019-12-20
2유치원이화유치원서울특별시 강남구 개포로109길 9<NA>37.495751127.075096서울특별시 강남구청수서경찰서Y215.02019-12-20
3유치원영동제일유치원서울특별시 강남구 삼성로120길 28<NA>37.517579127.053437서울특별시 강남구청강남경찰서Y25.82019-12-20
4유치원소망유치원서울특별시 강남구 광평로56길 11<NA>37.487979127.105631서울특별시 강남구청수서경찰서Y111.02019-12-20
5유치원청운유치원서울특별시 강남구 언주로65길 5<NA>37.495049127.045531서울특별시 강남구청수서경찰서Y111.52019-12-20
6유치원묘동유치원서울특별시 강남구 도곡로78길 8<NA>37.497407127.058723서울특별시 강남구청수서경찰서Y55.52019-12-20
7유치원푸른유치원서울특별시 강남구 일원로14길 25<NA>37.484798127.0811서울특별시 강남구청수서경찰서Y115.22019-12-20
8유치원성요셉유치원서울특별시 강남구 도산대로83길 27<NA>37.526273127.048211서울특별시 강남구청강남경찰서Y25.92019-12-20
9유치원강남유치원서울특별시 강남구 선릉로129길 31<NA>37.515448127.039009서울특별시 강남구청강남경찰서Y28.62019-12-20
시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
95어린이집바롬어린이집서울특별시 강남구 언주로164길 36<NA>37.525305127.036309서울특별시 강남구청강남경찰서Y16.02019-12-20
96어린이집역삼가애어린이집서울특별시 강남구 도곡로37길 15<NA>37.494809127.044725서울특별시 강남구청수서경찰서Y212.02019-12-20
97어린이집아이뜰어린이집서울특별시 강남구 개포로22길 39-11<NA>37.477164127.050117서울특별시 강남구청수서경찰서Y18.02019-12-20
98어린이집해맑은어린이집서울특별시 강남구 개포로36길 14<NA>37.478521127.051305서울특별시 강남구청수서경찰서Y16.02019-12-20
99어린이집대청어린이집서울특별시 강남구 양재대로37길 19<NA>37.490853127.083513서울특별시 강남구청수서경찰서Y16.02019-12-20
100어린이집충현어린이집서울특별시 강남구 테헤란로27길 40<NA>37.505327127.037616서울특별시 강남구청수서경찰서Y212.02019-12-20
101어린이집세곡햇빛어린이집서울특별시 강남구 자곡로 260<NA>37.476549127.111611서울특별시 강남구청수서경찰서N08.02019-12-20
102어린이집한울어린이집서울특별시 강남구 삼성로51길 25<NA>37.495907127.061002서울특별시 강남구청수서경찰서Y18.02019-12-20
103어린이집미담어린이집서울특별시 강남구 일원로 115<NA>37.484021127.08446서울특별시 강남구청수서경찰서Y<NA><NA>2019-12-20
104어린이집아이앤어린이집서울특별시 강남구 봉은사로68길 35-2<NA>37.510028127.051843서울특별시 강남구청강남경찰서Y<NA><NA>2019-12-20