Overview

Dataset statistics

Number of variables12
Number of observations97
Missing cells97
Missing cells (%)8.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory102.4 B

Variable types

Categorical4
Text2
Unsupported1
Numeric4
Boolean1

Dataset

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

Alerts

관리기관명 has constant value ""Constant
CCTV설치여부 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
관할경찰서명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
소재지지번주소 has 97 (100.0%) missing valuesMissing
대상시설명 has unique valuesUnique
소재지지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 09:06:28.485041
Analysis finished2023-12-11 09:06:30.909916
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류
Categorical

Distinct4
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
어린이집
42 
초등학교
32 
유치원
20 
특수학교
 
3

Length

Max length4
Median length4
Mean length3.7938144
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 42
43.3%
초등학교 32
33.0%
유치원 20
20.6%
특수학교 3
 
3.1%

Length

2023-12-11T18:06:30.992235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:31.130974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 42
43.3%
초등학교 32
33.0%
유치원 20
20.6%
특수학교 3
 
3.1%

대상시설명
Text

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-11T18:06:31.404313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length6.443299
Min length4

Characters and Unicode

Total characters625
Distinct characters127
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)100.0%

Sample

1st row돌샘유치원
2nd row이화유치원
3rd row영동제일유치원
4th row소망유치원
5th row묘동유치원
ValueCountFrequency (%)
돌샘유치원 1
 
1.0%
세명초등학교 1
 
1.0%
신사어린이집 1
 
1.0%
구민회관어린이집 1
 
1.0%
강남구청어린이집 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 (87) 87
89.7%
2023-12-11T18:06:31.889597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 45
 
7.2%
학 41
 
6.6%
집 41
 
6.6%
린 41
 
6.6%
어 41
 
6.6%
교 39
 
6.2%
초 38
 
6.1%
등 37
 
5.9%
원 25
 
4.0%
치 23
 
3.7%
Other values (117) 254
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 620
99.2%
Uppercase Letter 3
 
0.5%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 45
 
7.3%
학 41
 
6.6%
집 41
 
6.6%
린 41
 
6.6%
어 41
 
6.6%
교 39
 
6.3%
초 38
 
6.1%
등 37
 
6.0%
원 25
 
4.0%
치 23
 
3.7%
Other values (112) 249
40.2%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
K 1
33.3%
G 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 620
99.2%
Latin 3
 
0.5%
Common 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 45
 
7.3%
학 41
 
6.6%
집 41
 
6.6%
린 41
 
6.6%
어 41
 
6.6%
교 39
 
6.3%
초 38
 
6.1%
등 37
 
6.0%
원 25
 
4.0%
치 23
 
3.7%
Other values (112) 249
40.2%
Latin
ValueCountFrequency (%)
L 1
33.3%
K 1
33.3%
G 1
33.3%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 620
99.2%
ASCII 5
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 45
 
7.3%
학 41
 
6.6%
집 41
 
6.6%
린 41
 
6.6%
어 41
 
6.6%
교 39
 
6.3%
초 38
 
6.1%
등 37
 
6.0%
원 25
 
4.0%
치 23
 
3.7%
Other values (112) 249
40.2%
ASCII
ValueCountFrequency (%)
L 1
20.0%
K 1
20.0%
G 1
20.0%
( 1
20.0%
) 1
20.0%

소재지도로명주소
Text

Distinct91
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-11T18:06:32.255291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length22
Mean length19.134021
Min length16

Characters and Unicode

Total characters1856
Distinct characters71
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

Unique85 ?
Unique (%)87.6%

Sample

1st row서울특별시 강남구 개포로 516
2nd row서울특별시 강남구 개포로109길 9
3rd row서울특별시 강남구 삼성로120길 28
4th row서울특별시 강남구 광평로56길 11
5th row서울특별시 강남구 도곡로78길 8
ValueCountFrequency (%)
서울특별시 97
24.7%
강남구 97
24.7%
개포로 5
 
1.3%
16 5
 
1.3%
9 5
 
1.3%
21 4
 
1.0%
17 4
 
1.0%
일원로 4
 
1.0%
19 3
 
0.8%
학동로 3
 
0.8%
Other values (130) 166
42.2%
2023-12-11T18:06:32.769989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
296
15.9%
남 104
 
5.6%
구 102
 
5.5%
강 101
 
5.4%
서 97
 
5.2%
특 97
 
5.2%
별 97
 
5.2%
시 97
 
5.2%
울 97
 
5.2%
로 97
 
5.2%
Other values (61) 671
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1184
63.8%
Decimal Number 368
 
19.8%
Space Separator 296
 
15.9%
Dash Punctuation 7
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 104
8.8%
구 102
8.6%
강 101
8.5%
서 97
8.2%
특 97
8.2%
별 97
8.2%
시 97
8.2%
울 97
8.2%
로 97
8.2%
길 73
 
6.2%
Other values (48) 222
18.8%
Decimal Number
ValueCountFrequency (%)
1 75
20.4%
2 55
14.9%
3 39
10.6%
6 37
10.1%
5 33
9.0%
4 32
8.7%
7 31
8.4%
9 24
 
6.5%
8 22
 
6.0%
0 20
 
5.4%
Space Separator
ValueCountFrequency (%)
296
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1184
63.8%
Common 672
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 104
8.8%
구 102
8.6%
강 101
8.5%
서 97
8.2%
특 97
8.2%
별 97
8.2%
시 97
8.2%
울 97
8.2%
로 97
8.2%
길 73
 
6.2%
Other values (48) 222
18.8%
Common
ValueCountFrequency (%)
296
44.0%
1 75
 
11.2%
2 55
 
8.2%
3 39
 
5.8%
6 37
 
5.5%
5 33
 
4.9%
4 32
 
4.8%
7 31
 
4.6%
9 24
 
3.6%
8 22
 
3.3%
Other values (3) 28
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1184
63.8%
ASCII 672
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
296
44.0%
1 75
 
11.2%
2 55
 
8.2%
3 39
 
5.8%
6 37
 
5.5%
5 33
 
4.9%
4 32
 
4.8%
7 31
 
4.6%
9 24
 
3.6%
8 22
 
3.3%
Other values (3) 28
 
4.2%
Hangul
ValueCountFrequency (%)
남 104
8.8%
구 102
8.6%
강 101
8.5%
서 97
8.2%
특 97
8.2%
별 97
8.2%
시 97
8.2%
울 97
8.2%
로 97
8.2%
길 73
 
6.2%
Other values (48) 222
18.8%

소재지지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing97
Missing (%)100.0%
Memory size1005.0 B

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.49744
Minimum37.464621
Maximum37.531739
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-11T18:06:32.936068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.464621
5-th percentile37.473256
Q137.486323
median37.494712
Q337.511028
95-th percentile37.525103
Maximum37.531739
Range0.06711766
Interquartile range (IQR)0.02470465

Descriptive statistics

Standard deviation0.016130488
Coefficient of variation (CV)0.0004301757
Kurtosis-0.67524086
Mean37.49744
Median Absolute Deviation (MAD)0.01066991
Skewness0.21765393
Sum3637.2517
Variance0.00026019263
MonotonicityNot monotonic
2023-12-11T18:06:33.127071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.50372276 2
 
2.1%
37.495751 2
 
2.1%
37.52212074 2
 
2.1%
37.49230166 2
 
2.1%
37.49316115 2
 
2.1%
37.49115058 2
 
2.1%
37.48914032 1
 
1.0%
37.51150308 1
 
1.0%
37.493887 1
 
1.0%
37.51796636 1
 
1.0%
Other values (81) 81
83.5%
ValueCountFrequency (%)
37.46462136 1
1.0%
37.46682003 1
1.0%
37.468857 1
1.0%
37.4699202 1
1.0%
37.472191 1
1.0%
37.47352236 1
1.0%
37.47356078 1
1.0%
37.474559 1
1.0%
37.475915 1
1.0%
37.47591562 1
1.0%
ValueCountFrequency (%)
37.53173902 1
1.0%
37.52934822 1
1.0%
37.52828178 1
1.0%
37.52627314 1
1.0%
37.525305 1
1.0%
37.525052 1
1.0%
37.523923 1
1.0%
37.5233613 1
1.0%
37.52212074 2
2.1%
37.52012607 1
1.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06197
Minimum127.02399
Maximum127.11161
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-11T18:06:33.321926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02399
5-th percentile127.03198
Q1127.04651
median127.05636
Q3127.07825
95-th percentile127.10214
Maximum127.11161
Range0.0876195
Interquartile range (IQR)0.031743

Descriptive statistics

Standard deviation0.022423039
Coefficient of variation (CV)0.00017647325
Kurtosis-0.70061262
Mean127.06197
Median Absolute Deviation (MAD)0.0162425
Skewness0.47759626
Sum12325.011
Variance0.00050279269
MonotonicityNot monotonic
2023-12-11T18:06:33.478629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.063564 2
 
2.1%
127.075096 2
 
2.1%
127.0401134 2
 
2.1%
127.0811312 2
 
2.1%
127.032603 2
 
2.1%
127.101549 2
 
2.1%
127.0708698 1
 
1.0%
127.0285346 1
 
1.0%
127.0642704 1
 
1.0%
127.0470611 1
 
1.0%
Other values (81) 81
83.5%
ValueCountFrequency (%)
127.0239915 1
1.0%
127.0262217 1
1.0%
127.026898 1
1.0%
127.0285346 1
1.0%
127.0308413 1
1.0%
127.0322635 1
1.0%
127.032603 2
2.1%
127.035354 1
1.0%
127.0356146 1
1.0%
127.035679 1
1.0%
ValueCountFrequency (%)
127.111611 1
1.0%
127.108267 1
1.0%
127.1056314 1
1.0%
127.1055895 1
1.0%
127.104503 1
1.0%
127.101549 2
2.1%
127.0998275 1
1.0%
127.0996009 1
1.0%
127.099054 1
1.0%
127.0981867 1
1.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
서울특별시 강남구청
97 

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 97
100.0%

Length

2023-12-11T18:06:33.615864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:33.700323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 97
50.0%
강남구청 97
50.0%

관할경찰서명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
수서경찰서
68 
강남경찰서
29 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수서경찰서 68
70.1%
강남경찰서 29
29.9%

Length

2023-12-11T18:06:33.788444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:33.880474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수서경찰서 68
70.1%
강남경찰서 29
29.9%

CCTV설치여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size229.0 B
True
97 
ValueCountFrequency (%)
True 97
100.0%
2023-12-11T18:06:33.965912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CCTV설치대수
Real number (ℝ)

Distinct11
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9484536
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-11T18:06:34.057317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile8
Maximum46
Range45
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.9315547
Coefficient of variation (CV)1.6725902
Kurtosis61.60587
Mean2.9484536
Median Absolute Deviation (MAD)1
Skewness7.2231624
Sum286
Variance24.320232
MonotonicityNot monotonic
2023-12-11T18:06:34.164946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 41
42.3%
2 26
26.8%
3 10
 
10.3%
4 6
 
6.2%
5 4
 
4.1%
8 3
 
3.1%
6 2
 
2.1%
7 2
 
2.1%
46 1
 
1.0%
13 1
 
1.0%
ValueCountFrequency (%)
1 41
42.3%
2 26
26.8%
3 10
 
10.3%
4 6
 
6.2%
5 4
 
4.1%
6 2
 
2.1%
7 2
 
2.1%
8 3
 
3.1%
10 1
 
1.0%
13 1
 
1.0%
ValueCountFrequency (%)
46 1
 
1.0%
13 1
 
1.0%
10 1
 
1.0%
8 3
 
3.1%
7 2
 
2.1%
6 2
 
2.1%
5 4
 
4.1%
4 6
 
6.2%
3 10
 
10.3%
2 26
26.8%

보호구역도로폭
Real number (ℝ)

Distinct40
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.160825
Minimum5.3
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-11T18:06:34.318150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.3
5-th percentile5.5
Q16
median8
Q314
95-th percentile25.74
Maximum40
Range34.7
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.2573319
Coefficient of variation (CV)0.6502505
Kurtosis3.4472362
Mean11.160825
Median Absolute Deviation (MAD)2
Skewness1.8887618
Sum1082.6
Variance52.668866
MonotonicityNot monotonic
2023-12-11T18:06:34.469394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
6.0 22
22.7%
8.0 15
15.5%
12.0 6
 
6.2%
20.0 4
 
4.1%
5.5 4
 
4.1%
15.0 3
 
3.1%
25.0 3
 
3.1%
9.0 2
 
2.1%
6.5 2
 
2.1%
14.0 2
 
2.1%
Other values (30) 34
35.1%
ValueCountFrequency (%)
5.3 1
 
1.0%
5.4 1
 
1.0%
5.5 4
 
4.1%
5.7 1
 
1.0%
5.8 1
 
1.0%
5.9 2
 
2.1%
6.0 22
22.7%
6.1 1
 
1.0%
6.5 2
 
2.1%
6.9 1
 
1.0%
ValueCountFrequency (%)
40.0 1
 
1.0%
36.0 1
 
1.0%
30.0 2
2.1%
28.7 1
 
1.0%
25.0 3
3.1%
24.0 1
 
1.0%
23.1 1
 
1.0%
20.0 4
4.1%
19.7 1
 
1.0%
15.2 1
 
1.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-05-31
97 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-31
2nd row2023-05-31
3rd row2023-05-31
4th row2023-05-31
5th row2023-05-31

Common Values

ValueCountFrequency (%)
2023-05-31 97
100.0%

Length

2023-12-11T18:06:34.619949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:34.740196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-31 97
100.0%

Interactions

2023-12-11T18:06:30.099222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:28.881268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.275659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.725710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:30.206478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:28.987772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.403491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.833070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:30.318083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.075541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.493752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.917550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:30.424753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.159519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.606032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:29.998628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:06:34.803583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류대상시설명소재지도로명주소위도경도관할경찰서명CCTV설치대수보호구역도로폭
시설종류1.0001.0000.5210.0000.0000.0000.4930.211
대상시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소0.5211.0001.0001.0001.0001.0000.8060.937
위도0.0001.0001.0001.0000.7090.9990.0590.000
경도0.0001.0001.0000.7091.0000.7160.3610.191
관할경찰서명0.0001.0001.0000.9990.7161.0000.3190.307
CCTV설치대수0.4931.0000.8060.0590.3610.3191.0000.096
보호구역도로폭0.2111.0000.9370.0000.1910.3070.0961.000
2023-12-11T18:06:34.930813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할경찰서명시설종류
관할경찰서명1.0000.000
시설종류0.0001.000
2023-12-11T18:06:35.046265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV설치대수보호구역도로폭시설종류관할경찰서명
위도1.000-0.6470.060-0.3960.0000.934
경도-0.6471.000-0.0590.3490.0000.535
CCTV설치대수0.060-0.0591.000-0.0170.1650.148
보호구역도로폭-0.3960.349-0.0171.0000.1290.294
시설종류0.0000.0000.1650.1291.0000.000
관할경찰서명0.9340.5350.1480.2940.0001.000

Missing values

2023-12-11T18:06:30.601370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:06:30.835927image/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

시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
0유치원돌샘유치원서울특별시 강남구 개포로 516<NA>37.48914127.07087서울특별시 강남구청수서경찰서Y112.62023-05-31
1유치원이화유치원서울특별시 강남구 개포로109길 9<NA>37.495751127.075096서울특별시 강남구청수서경찰서Y215.02023-05-31
2유치원영동제일유치원서울특별시 강남구 삼성로120길 28<NA>37.517579127.053437서울특별시 강남구청강남경찰서Y25.82023-05-31
3유치원소망유치원서울특별시 강남구 광평로56길 11<NA>37.487979127.105631서울특별시 강남구청수서경찰서Y111.02023-05-31
4유치원묘동유치원서울특별시 강남구 도곡로78길 8<NA>37.497407127.058723서울특별시 강남구청수서경찰서Y55.52023-05-31
5유치원푸른유치원서울특별시 강남구 일원로14길 25<NA>37.484798127.081101서울특별시 강남구청수서경찰서Y115.22023-05-31
6유치원성요셉유치원서울특별시 강남구 도산대로83길 27<NA>37.526273127.048211서울특별시 강남구청강남경찰서Y25.92023-05-31
7유치원강남유치원서울특별시 강남구 선릉로129길 31<NA>37.515448127.039009서울특별시 강남구청강남경찰서Y28.62023-05-31
8유치원반디유치원서울특별시 강남구 광평로47길 17<NA>37.48791127.098187서울특별시 강남구청수서경찰서Y29.62023-05-31
9유치원초원유치원서울특별시 강남구 논현로14길 17<NA>37.475915127.048578서울특별시 강남구청수서경찰서Y29.42023-05-31
시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
87어린이집아이뜰어린이집서울특별시 강남구 개포로22길 39-11<NA>37.477164127.050117서울특별시 강남구청수서경찰서Y18.02023-05-31
88어린이집해맑은어린이집서울특별시 강남구 개포로36길 14<NA>37.478521127.051305서울특별시 강남구청수서경찰서Y16.02023-05-31
89어린이집대청어린이집서울특별시 강남구 양재대로37길 19<NA>37.490853127.083513서울특별시 강남구청수서경찰서Y16.02023-05-31
90어린이집충현어린이집서울특별시 강남구 테헤란로27길 40<NA>37.505327127.037616서울특별시 강남구청수서경찰서Y212.02023-05-31
91어린이집세곡햇빛어린이집서울특별시 강남구 자곡로 260<NA>37.476549127.111611서울특별시 강남구청수서경찰서Y138.02023-05-31
92어린이집한울어린이집서울특별시 강남구 삼성로51길 25<NA>37.495907127.061서울특별시 강남구청수서경찰서Y18.02023-05-31
93어린이집미담어린이집서울특별시 강남구 일원로 115<NA>37.484021127.08446서울특별시 강남구청수서경찰서Y18.02023-05-31
94어린이집아이앤어린이집서울특별시 강남구 봉은사로68길 35-2<NA>37.510028127.051843서울특별시 강남구청강남경찰서Y18.02023-05-31
95어린이집보람어린이집서울특별시 강남구 남부순환로397길 19<NA>37.494385127.06134서울특별시 강남구청수서경찰서Y1014.02023-05-31
96어린이집대치동학원가서울특별시 강남구 도곡로 407-2<NA>37.497088127.054896서울특별시 강남구청수서경찰서Y436.02023-05-31