Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells4058
Missing cells (%)2.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory148.0 B

Variable types

Text6
Categorical6
Numeric3
Boolean2

Dataset

Description시설번호,시설유형코드,시도명,시군구명,시군구코드,소재지도로명주소,소재지지번주소,위도,경도,상세위치,안전센터명,보호틀유무,사용가능여부,설치연도,관할소방서명,관할소방서전화번호,데이터기준일자
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21306/S/1/datasetView.do

Alerts

시도명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시군구명 is highly overall correlated with 시군구코드 and 2 other fieldsHigh correlation
관할소방서명 is highly overall correlated with 시군구코드 and 2 other fieldsHigh correlation
관할소방서전화번호 is highly overall correlated with 시군구코드 and 2 other fieldsHigh correlation
시군구코드 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 시군구코드High correlation
시설유형코드 is highly imbalanced (59.5%)Imbalance
보호틀유무 is highly imbalanced (98.5%)Imbalance
사용가능여부 is highly imbalanced (84.3%)Imbalance
상세위치 has 4035 (40.4%) missing valuesMissing

Reproduction

Analysis started2023-12-11 06:55:50.603762
Analysis finished2023-12-11 06:55:55.889321
Duration5.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설번호
Text

Distinct9249
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:55:56.228054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.4748
Min length1

Characters and Unicode

Total characters64748
Distinct characters47
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

Unique8620 ?
Unique (%)86.2%

Sample

1st row중부-3282
2nd row현장대응단-1464
3rd row현장대응단-1098
4th row4265
5th row동대문-001499
ValueCountFrequency (%)
1561 5
 
< 0.1%
1134 4
 
< 0.1%
2611 4
 
< 0.1%
1197 4
 
< 0.1%
1067 4
 
< 0.1%
1383 4
 
< 0.1%
1328 4
 
< 0.1%
1280 4
 
< 0.1%
3015 4
 
< 0.1%
2044 4
 
< 0.1%
Other values (9239) 9959
99.6%
2023-12-11T15:55:56.728927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11323
17.5%
1 6461
10.0%
2 5664
 
8.7%
- 5167
 
8.0%
3 4877
 
7.5%
4 3777
 
5.8%
6 3646
 
5.6%
5 3480
 
5.4%
7 3442
 
5.3%
8 2502
 
3.9%
Other values (37) 14409
22.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47576
73.5%
Other Letter 11991
 
18.5%
Dash Punctuation 5167
 
8.0%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 2339
19.5%
강 1598
13.3%
남 945
 
7.9%
울 846
 
7.1%
초 846
 
7.1%
중 634
 
5.3%
부 634
 
5.3%
포 632
 
5.3%
마 632
 
5.3%
대 452
 
3.8%
Other values (24) 2433
20.3%
Decimal Number
ValueCountFrequency (%)
0 11323
23.8%
1 6461
13.6%
2 5664
11.9%
3 4877
10.3%
4 3777
 
7.9%
6 3646
 
7.7%
5 3480
 
7.3%
7 3442
 
7.2%
8 2502
 
5.3%
9 2404
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 5167
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52757
81.5%
Hangul 11991
 
18.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 2339
19.5%
강 1598
13.3%
남 945
 
7.9%
울 846
 
7.1%
초 846
 
7.1%
중 634
 
5.3%
부 634
 
5.3%
포 632
 
5.3%
마 632
 
5.3%
대 452
 
3.8%
Other values (24) 2433
20.3%
Common
ValueCountFrequency (%)
0 11323
21.5%
1 6461
12.2%
2 5664
10.7%
- 5167
9.8%
3 4877
9.2%
4 3777
 
7.2%
6 3646
 
6.9%
5 3480
 
6.6%
7 3442
 
6.5%
8 2502
 
4.7%
Other values (3) 2418
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52757
81.5%
Hangul 11991
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11323
21.5%
1 6461
12.2%
2 5664
10.7%
- 5167
9.8%
3 4877
9.2%
4 3777
 
7.2%
6 3646
 
6.9%
5 3480
 
6.6%
7 3442
 
6.5%
8 2502
 
4.7%
Other values (3) 2418
 
4.6%
Hangul
ValueCountFrequency (%)
서 2339
19.5%
강 1598
13.3%
남 945
 
7.9%
울 846
 
7.1%
초 846
 
7.1%
중 634
 
5.3%
부 634
 
5.3%
포 632
 
5.3%
마 632
 
5.3%
대 452
 
3.8%
Other values (24) 2433
20.3%

시설유형코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
6933 
1
3001 
4
 
52
3
 
10
5
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 6933
69.3%
1 3001
30.0%
4 52
 
0.5%
3 10
 
0.1%
5 4
 
< 0.1%

Length

2023-12-11T15:55:56.875399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:55:56.990881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6933
69.3%
1 3001
30.0%
4 52
 
0.5%
3 10
 
0.1%
5 4
 
< 0.1%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
서울특별시
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 10000
100.0%

Length

2023-12-11T15:55:57.102433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:55:57.201991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 10000
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강남구
945 
서초구
846 
영등포구
817 
종로구
710 
성북구
667 
Other values (13)
6015 

Length

Max length4
Median length3
Mean length3.0728
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row중구
2nd row도봉구
3rd row도봉구
4th row성북구
5th row동대문구

Common Values

ValueCountFrequency (%)
강남구 945
 
9.4%
서초구 846
 
8.5%
영등포구 817
 
8.2%
종로구 710
 
7.1%
성북구 667
 
6.7%
강서구 647
 
6.5%
중구 634
 
6.3%
강동구 633
 
6.3%
마포구 632
 
6.3%
용산구 613
 
6.1%
Other values (8) 2856
28.6%

Length

2023-12-11T15:55:57.299995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 945
 
9.4%
서초구 846
 
8.5%
영등포구 817
 
8.2%
종로구 710
 
7.1%
성북구 667
 
6.7%
강서구 647
 
6.5%
중구 634
 
6.3%
강동구 633
 
6.3%
마포구 632
 
6.3%
용산구 613
 
6.1%
Other values (8) 2856
28.6%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11413.177
Minimum11110
Maximum11740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T15:55:57.456675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11110
Q111230
median11380
Q311560
95-th percentile11740
Maximum11740
Range630
Interquartile range (IQR)330

Descriptive statistics

Standard deviation203.90116
Coefficient of variation (CV)0.017865417
Kurtosis-1.3530457
Mean11413.177
Median Absolute Deviation (MAD)180
Skewness0.051263736
Sum1.1413177 × 108
Variance41575.684
MonotonicityNot monotonic
2023-12-11T15:55:57.567029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
11680 945
 
9.4%
11650 846
 
8.5%
11560 817
 
8.2%
11110 710
 
7.1%
11230 688
 
6.9%
11290 667
 
6.7%
11500 647
 
6.5%
11140 634
 
6.3%
11740 633
 
6.3%
11440 632
 
6.3%
Other values (7) 2781
27.8%
ValueCountFrequency (%)
11110 710
7.1%
11140 634
6.3%
11170 613
6.1%
11215 420
4.2%
11230 688
6.9%
11290 667
6.7%
11320 411
4.1%
11350 352
3.5%
11380 521
5.2%
11440 632
6.3%
ValueCountFrequency (%)
11740 633
6.3%
11680 945
9.4%
11650 846
8.5%
11620 1
 
< 0.1%
11560 817
8.2%
11530 463
4.6%
11500 647
6.5%
11440 632
6.3%
11380 521
5.2%
11350 352
 
3.5%

소재지도로명주소
Text

Distinct9809
Distinct (%)98.3%
Missing23
Missing (%)0.2%
Memory size156.2 KiB
2023-12-11T15:55:57.955957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length22.444723
Min length6

Characters and Unicode

Total characters223931
Distinct characters732
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9663 ?
Unique (%)96.9%

Sample

1st row서울특별시 중구 서애로 15-6 삼진빌딩
2nd row서울특별시 도봉구 해등로16길 52-18
3rd row서울특별시 도봉구 도당로2길 59
4th row서울특별시 성북구 장위로8길 6
5th row서울특별시 동대문구 휘경로 28 외대역앞역 5번출구앞
ValueCountFrequency (%)
서울특별시 8995
 
20.8%
강남구 945
 
2.2%
서초구 832
 
1.9%
영등포구 817
 
1.9%
서울시 817
 
1.9%
종로구 708
 
1.6%
동대문구 688
 
1.6%
성북구 666
 
1.5%
강서구 651
 
1.5%
강동구 633
 
1.5%
Other values (10433) 27448
63.5%
2023-12-11T15:55:58.678358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43251
19.3%
서 11978
 
5.3%
로 10848
 
4.8%
구 10789
 
4.8%
시 10011
 
4.5%
울 9946
 
4.4%
별 9004
 
4.0%
특 9001
 
4.0%
1 8133
 
3.6%
길 6768
 
3.0%
Other values (722) 94202
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139339
62.2%
Space Separator 43251
 
19.3%
Decimal Number 37723
 
16.8%
Dash Punctuation 2991
 
1.3%
Uppercase Letter 360
 
0.2%
Lowercase Letter 118
 
0.1%
Close Punctuation 74
 
< 0.1%
Open Punctuation 50
 
< 0.1%
Other Punctuation 19
 
< 0.1%
Letter Number 3
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 11978
 
8.6%
로 10848
 
7.8%
구 10789
 
7.7%
시 10011
 
7.2%
울 9946
 
7.1%
별 9004
 
6.5%
특 9001
 
6.5%
길 6768
 
4.9%
강 2623
 
1.9%
동 2464
 
1.8%
Other values (654) 55907
40.1%
Uppercase Letter
ValueCountFrequency (%)
S 42
 
11.7%
C 35
 
9.7%
G 31
 
8.6%
A 25
 
6.9%
I 21
 
5.8%
M 20
 
5.6%
K 19
 
5.3%
T 19
 
5.3%
O 18
 
5.0%
L 17
 
4.7%
Other values (14) 113
31.4%
Lowercase Letter
ValueCountFrequency (%)
m 15
12.7%
e 15
12.7%
c 10
 
8.5%
a 9
 
7.6%
o 9
 
7.6%
r 9
 
7.6%
l 7
 
5.9%
i 6
 
5.1%
s 5
 
4.2%
g 4
 
3.4%
Other values (12) 29
24.6%
Decimal Number
ValueCountFrequency (%)
1 8133
21.6%
2 5450
14.4%
3 4336
11.5%
4 3567
9.5%
5 3178
 
8.4%
0 3178
 
8.4%
6 2805
 
7.4%
7 2548
 
6.8%
8 2313
 
6.1%
9 2215
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 8
42.1%
& 6
31.6%
/ 2
 
10.5%
@ 2
 
10.5%
? 1
 
5.3%
Space Separator
ValueCountFrequency (%)
43251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2991
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139339
62.2%
Common 84111
37.6%
Latin 481
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 11978
 
8.6%
로 10848
 
7.8%
구 10789
 
7.7%
시 10011
 
7.2%
울 9946
 
7.1%
별 9004
 
6.5%
특 9001
 
6.5%
길 6768
 
4.9%
강 2623
 
1.9%
동 2464
 
1.8%
Other values (654) 55907
40.1%
Latin
ValueCountFrequency (%)
S 42
 
8.7%
C 35
 
7.3%
G 31
 
6.4%
A 25
 
5.2%
I 21
 
4.4%
M 20
 
4.2%
K 19
 
4.0%
T 19
 
4.0%
O 18
 
3.7%
L 17
 
3.5%
Other values (37) 234
48.6%
Common
ValueCountFrequency (%)
43251
51.4%
1 8133
 
9.7%
2 5450
 
6.5%
3 4336
 
5.2%
4 3567
 
4.2%
5 3178
 
3.8%
0 3178
 
3.8%
- 2991
 
3.6%
6 2805
 
3.3%
7 2548
 
3.0%
Other values (11) 4674
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139339
62.2%
ASCII 84589
37.8%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43251
51.1%
1 8133
 
9.6%
2 5450
 
6.4%
3 4336
 
5.1%
4 3567
 
4.2%
5 3178
 
3.8%
0 3178
 
3.8%
- 2991
 
3.5%
6 2805
 
3.3%
7 2548
 
3.0%
Other values (57) 5152
 
6.1%
Hangul
ValueCountFrequency (%)
서 11978
 
8.6%
로 10848
 
7.8%
구 10789
 
7.7%
시 10011
 
7.2%
울 9946
 
7.1%
별 9004
 
6.5%
특 9001
 
6.5%
길 6768
 
4.9%
강 2623
 
1.9%
동 2464
 
1.8%
Other values (654) 55907
40.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

소재지지번주소
Text

Distinct9823
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:55:59.102618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length41
Mean length22.6206
Min length13

Characters and Unicode

Total characters226206
Distinct characters750
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9671 ?
Unique (%)96.7%

Sample

1st row서울특별시 중구 필동3가 20-14 삼진빌딩
2nd row서울특별시 도봉구 창동 291-17
3rd row서울특별시 도봉구 쌍문동 712-26
4th row서울특별시 성북구 장위동 231-218
5th row서울특별시 동대문구 이문동 306-14 외대역앞역 5번출구앞
ValueCountFrequency (%)
서울특별시 9150
 
20.3%
강남구 945
 
2.1%
서초구 846
 
1.9%
영등포구 817
 
1.8%
서울시 817
 
1.8%
종로구 710
 
1.6%
동대문구 683
 
1.5%
성북구 667
 
1.5%
강서구 651
 
1.4%
중구 634
 
1.4%
Other values (12180) 29172
64.7%
2023-12-11T15:56:00.329909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40823
18.0%
서 12047
 
5.3%
동 11610
 
5.1%
구 10950
 
4.8%
시 10083
 
4.5%
울 10069
 
4.5%
별 9166
 
4.1%
특 9158
 
4.0%
1 8432
 
3.7%
- 8392
 
3.7%
Other values (740) 95476
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133422
59.0%
Decimal Number 42739
 
18.9%
Space Separator 40823
 
18.0%
Dash Punctuation 8392
 
3.7%
Uppercase Letter 475
 
0.2%
Lowercase Letter 158
 
0.1%
Close Punctuation 93
 
< 0.1%
Open Punctuation 65
 
< 0.1%
Other Punctuation 32
 
< 0.1%
Letter Number 3
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 12047
 
9.0%
동 11610
 
8.7%
구 10950
 
8.2%
시 10083
 
7.6%
울 10069
 
7.5%
별 9166
 
6.9%
특 9158
 
6.9%
강 2436
 
1.8%
포 1803
 
1.4%
로 1768
 
1.3%
Other values (671) 54332
40.7%
Uppercase Letter
ValueCountFrequency (%)
S 57
 
12.0%
C 47
 
9.9%
G 39
 
8.2%
A 32
 
6.7%
T 29
 
6.1%
K 27
 
5.7%
M 25
 
5.3%
I 25
 
5.3%
E 23
 
4.8%
O 21
 
4.4%
Other values (14) 150
31.6%
Lowercase Letter
ValueCountFrequency (%)
e 20
12.7%
c 16
 
10.1%
m 16
 
10.1%
a 15
 
9.5%
o 11
 
7.0%
r 10
 
6.3%
l 9
 
5.7%
b 7
 
4.4%
k 7
 
4.4%
i 6
 
3.8%
Other values (13) 41
25.9%
Decimal Number
ValueCountFrequency (%)
1 8432
19.7%
2 5948
13.9%
3 4917
11.5%
4 4299
10.1%
5 3914
9.2%
6 3742
8.8%
7 3114
 
7.3%
0 2911
 
6.8%
8 2811
 
6.6%
9 2651
 
6.2%
Other Punctuation
ValueCountFrequency (%)
? 12
37.5%
. 9
28.1%
& 6
18.8%
@ 3
 
9.4%
/ 2
 
6.2%
Space Separator
ValueCountFrequency (%)
40823
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8392
100.0%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133422
59.0%
Common 92148
40.7%
Latin 636
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 12047
 
9.0%
동 11610
 
8.7%
구 10950
 
8.2%
시 10083
 
7.6%
울 10069
 
7.5%
별 9166
 
6.9%
특 9158
 
6.9%
강 2436
 
1.8%
포 1803
 
1.4%
로 1768
 
1.3%
Other values (671) 54332
40.7%
Latin
ValueCountFrequency (%)
S 57
 
9.0%
C 47
 
7.4%
G 39
 
6.1%
A 32
 
5.0%
T 29
 
4.6%
K 27
 
4.2%
M 25
 
3.9%
I 25
 
3.9%
E 23
 
3.6%
O 21
 
3.3%
Other values (38) 311
48.9%
Common
ValueCountFrequency (%)
40823
44.3%
1 8432
 
9.2%
- 8392
 
9.1%
2 5948
 
6.5%
3 4917
 
5.3%
4 4299
 
4.7%
5 3914
 
4.2%
6 3742
 
4.1%
7 3114
 
3.4%
0 2911
 
3.2%
Other values (11) 5656
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133422
59.0%
ASCII 92781
41.0%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40823
44.0%
1 8432
 
9.1%
- 8392
 
9.0%
2 5948
 
6.4%
3 4917
 
5.3%
4 4299
 
4.6%
5 3914
 
4.2%
6 3742
 
4.0%
7 3114
 
3.4%
0 2911
 
3.1%
Other values (58) 6289
 
6.8%
Hangul
ValueCountFrequency (%)
서 12047
 
9.0%
동 11610
 
8.7%
구 10950
 
8.2%
시 10083
 
7.6%
울 10069
 
7.5%
별 9166
 
6.9%
특 9158
 
6.9%
강 2436
 
1.8%
포 1803
 
1.4%
로 1768
 
1.3%
Other values (671) 54332
40.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct9958
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.803679
Minimum37.0677
Maximum127.04558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T15:56:00.569026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.0677
5-th percentile37.482053
Q137.517846
median37.551823
Q337.581351
95-th percentile37.649361
Maximum127.04558
Range89.977883
Interquartile range (IQR)0.063504462

Descriptive statistics

Standard deviation4.7290907
Coefficient of variation (CV)0.12509605
Kurtosis352.24955
Mean37.803679
Median Absolute Deviation (MAD)0.031843045
Skewness18.818671
Sum378036.79
Variance22.364299
MonotonicityNot monotonic
2023-12-11T15:56:00.745978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.55624851 10
 
0.1%
37.53463 3
 
< 0.1%
37.51983204 2
 
< 0.1%
37.66655143 2
 
< 0.1%
37.559462 2
 
< 0.1%
37.557594 2
 
< 0.1%
37.58258 2
 
< 0.1%
37.652212 2
 
< 0.1%
37.53357625 2
 
< 0.1%
37.5369 2
 
< 0.1%
Other values (9948) 9971
99.7%
ValueCountFrequency (%)
37.0677 1
< 0.1%
37.43494384 1
< 0.1%
37.43545951 1
< 0.1%
37.44292472 1
< 0.1%
37.44389044 1
< 0.1%
37.44623202 1
< 0.1%
37.44645992 1
< 0.1%
37.44658585 1
< 0.1%
37.4471965 1
< 0.1%
37.44737873 1
< 0.1%
ValueCountFrequency (%)
127.0455829 1
< 0.1%
127.0447165 1
< 0.1%
127.0445074 1
< 0.1%
127.0444273 1
< 0.1%
127.0443182 1
< 0.1%
127.0441397 1
< 0.1%
127.0440485 1
< 0.1%
127.0434469 1
< 0.1%
127.0433384 1
< 0.1%
127.0432219 1
< 0.1%

경도
Real number (ℝ)

Distinct9944
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.7421
Minimum37.665896
Maximum127.18266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T15:56:00.921394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.665896
5-th percentile126.8445
Q1126.92232
median127.00522
Q3127.04737
95-th percentile127.12886
Maximum127.18266
Range89.516767
Interquartile range (IQR)0.12504867

Descriptive statistics

Standard deviation4.720561
Coefficient of variation (CV)0.037245407
Kurtosis352.11697
Mean126.7421
Median Absolute Deviation (MAD)0.05221875
Skewness-18.813375
Sum1267421
Variance22.283696
MonotonicityNot monotonic
2023-12-11T15:56:01.111337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.996127 10
 
0.1%
126.98303 3
 
< 0.1%
127.00179 2
 
< 0.1%
126.9977984 2
 
< 0.1%
126.97903 2
 
< 0.1%
127.0258085 2
 
< 0.1%
126.96718 2
 
< 0.1%
127.0193782 2
 
< 0.1%
127.00165 2
 
< 0.1%
126.973503 2
 
< 0.1%
Other values (9934) 9971
99.7%
ValueCountFrequency (%)
37.66589572 1
< 0.1%
37.66697325 1
< 0.1%
37.66714459 1
< 0.1%
37.66730008 1
< 0.1%
37.66787982 1
< 0.1%
37.668638 1
< 0.1%
37.6687497 1
< 0.1%
37.66882401 1
< 0.1%
37.66916496 1
< 0.1%
37.66926646 1
< 0.1%
ValueCountFrequency (%)
127.1826626 1
< 0.1%
127.1818034 1
< 0.1%
127.1802605 1
< 0.1%
127.1794324 1
< 0.1%
127.1792207 1
< 0.1%
127.1790756 1
< 0.1%
127.1781261 1
< 0.1%
127.1778635 1
< 0.1%
127.1764983 1
< 0.1%
127.1762957 1
< 0.1%

상세위치
Text

MISSING 

Distinct3955
Distinct (%)66.3%
Missing4035
Missing (%)40.4%
Memory size156.2 KiB
2023-12-11T15:56:01.492974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length21
Mean length5.4477787
Min length1

Characters and Unicode

Total characters32496
Distinct characters754
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3746 ?
Unique (%)62.8%

Sample

1st row지번앞
2nd row지번앞
3rd row지번 앞
4th row한길교회
5th row삼성동아이파크타워
ValueCountFrequency (%)
앞 865
 
12.0%
지번 623
 
8.7%
지번앞 614
 
8.5%
일반주택 68
 
0.9%
주택 65
 
0.9%
옆 40
 
0.6%
주택앞 31
 
0.4%
일반가 25
 
0.3%
입구 18
 
0.3%
인도 16
 
0.2%
Other values (4170) 4825
67.1%
2023-12-11T15:56:02.112784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2939
 
9.0%
앞 1775
 
5.5%
지 1488
 
4.6%
번 1289
 
4.0%
빌 989
 
3.0%
딩 559
 
1.7%
동 544
 
1.7%
아 491
 
1.5%
트 466
 
1.4%
주 452
 
1.4%
Other values (744) 21504
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27941
86.0%
Space Separator 2939
 
9.0%
Decimal Number 809
 
2.5%
Uppercase Letter 435
 
1.3%
Lowercase Letter 167
 
0.5%
Close Punctuation 77
 
0.2%
Open Punctuation 54
 
0.2%
Dash Punctuation 36
 
0.1%
Other Punctuation 31
 
0.1%
Letter Number 3
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 1775
 
6.4%
지 1488
 
5.3%
번 1289
 
4.6%
빌 989
 
3.5%
딩 559
 
2.0%
동 544
 
1.9%
아 491
 
1.8%
트 466
 
1.7%
주 452
 
1.6%
파 372
 
1.3%
Other values (670) 19516
69.8%
Uppercase Letter
ValueCountFrequency (%)
S 44
 
10.1%
G 43
 
9.9%
C 43
 
9.9%
L 34
 
7.8%
A 31
 
7.1%
B 31
 
7.1%
K 23
 
5.3%
I 20
 
4.6%
T 20
 
4.6%
E 19
 
4.4%
Other values (15) 127
29.2%
Lowercase Letter
ValueCountFrequency (%)
e 19
 
11.4%
a 17
 
10.2%
s 12
 
7.2%
l 12
 
7.2%
m 11
 
6.6%
c 11
 
6.6%
o 10
 
6.0%
u 9
 
5.4%
i 9
 
5.4%
r 8
 
4.8%
Other values (14) 49
29.3%
Decimal Number
ValueCountFrequency (%)
1 229
28.3%
2 130
16.1%
0 81
 
10.0%
3 81
 
10.0%
5 67
 
8.3%
4 56
 
6.9%
9 55
 
6.8%
7 43
 
5.3%
6 36
 
4.4%
8 31
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 7
22.6%
@ 7
22.6%
? 5
16.1%
& 5
16.1%
/ 4
12.9%
' 2
 
6.5%
: 1
 
3.2%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
+ 1
33.3%
Space Separator
ValueCountFrequency (%)
2939
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27942
86.0%
Common 3949
 
12.2%
Latin 605
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 1775
 
6.4%
지 1488
 
5.3%
번 1289
 
4.6%
빌 989
 
3.5%
딩 559
 
2.0%
동 544
 
1.9%
아 491
 
1.8%
트 466
 
1.7%
주 452
 
1.6%
파 372
 
1.3%
Other values (671) 19517
69.8%
Latin
ValueCountFrequency (%)
S 44
 
7.3%
G 43
 
7.1%
C 43
 
7.1%
L 34
 
5.6%
A 31
 
5.1%
B 31
 
5.1%
K 23
 
3.8%
I 20
 
3.3%
T 20
 
3.3%
E 19
 
3.1%
Other values (40) 297
49.1%
Common
ValueCountFrequency (%)
2939
74.4%
1 229
 
5.8%
2 130
 
3.3%
0 81
 
2.1%
3 81
 
2.1%
) 77
 
1.9%
5 67
 
1.7%
4 56
 
1.4%
9 55
 
1.4%
( 54
 
1.4%
Other values (13) 180
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27939
86.0%
ASCII 4551
 
14.0%
Number Forms 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2939
64.6%
1 229
 
5.0%
2 130
 
2.9%
0 81
 
1.8%
3 81
 
1.8%
) 77
 
1.7%
5 67
 
1.5%
4 56
 
1.2%
9 55
 
1.2%
( 54
 
1.2%
Other values (62) 782
 
17.2%
Hangul
ValueCountFrequency (%)
앞 1775
 
6.4%
지 1488
 
5.3%
번 1289
 
4.6%
빌 989
 
3.5%
딩 559
 
2.0%
동 544
 
1.9%
아 491
 
1.8%
트 466
 
1.7%
주 452
 
1.6%
파 372
 
1.3%
Other values (668) 19514
69.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅍ 1
50.0%
ㅠ 1
50.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

안전센터명
Text

Distinct67
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:56:02.414343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.0663
Min length5

Characters and Unicode

Total characters80663
Distinct characters97
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row신당119안전센터
2nd row현장대응단
3rd row현장대응단
4th row장위119안전센터
5th row청량리119안전센터
ValueCountFrequency (%)
현장대응단 2496
25.0%
영동119안전센터 265
 
2.6%
용두119안전센터 199
 
2.0%
역삼119안전센터 197
 
2.0%
돈암119안전센터 197
 
2.0%
대림119안전센터 195
 
1.9%
양재119안전센터 191
 
1.9%
서초119안전센터 174
 
1.7%
서교119안전센터 172
 
1.7%
당산119안전센터 171
 
1.7%
Other values (57) 5743
57.4%
2023-12-11T15:56:02.941963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15008
18.6%
전 7640
9.5%
안 7504
9.3%
터 7504
9.3%
센 7504
9.3%
9 7504
9.3%
대 2691
 
3.3%
장 2636
 
3.3%
현 2634
 
3.3%
단 2554
 
3.2%
Other values (87) 17484
21.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58151
72.1%
Decimal Number 22512
 
27.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 7640
13.1%
안 7504
12.9%
터 7504
12.9%
센 7504
12.9%
대 2691
 
4.6%
장 2636
 
4.5%
현 2634
 
4.5%
단 2554
 
4.4%
응 2496
 
4.3%
동 606
 
1.0%
Other values (85) 14382
24.7%
Decimal Number
ValueCountFrequency (%)
1 15008
66.7%
9 7504
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58151
72.1%
Common 22512
 
27.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 7640
13.1%
안 7504
12.9%
터 7504
12.9%
센 7504
12.9%
대 2691
 
4.6%
장 2636
 
4.5%
현 2634
 
4.5%
단 2554
 
4.4%
응 2496
 
4.3%
동 606
 
1.0%
Other values (85) 14382
24.7%
Common
ValueCountFrequency (%)
1 15008
66.7%
9 7504
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58151
72.1%
ASCII 22512
 
27.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15008
66.7%
9 7504
33.3%
Hangul
ValueCountFrequency (%)
전 7640
13.1%
안 7504
12.9%
터 7504
12.9%
센 7504
12.9%
대 2691
 
4.6%
장 2636
 
4.5%
현 2634
 
4.5%
단 2554
 
4.4%
응 2496
 
4.3%
동 606
 
1.0%
Other values (85) 14382
24.7%

보호틀유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9986 
True
 
14
ValueCountFrequency (%)
False 9986
99.9%
True 14
 
0.1%
2023-12-11T15:56:03.086692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

사용가능여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
9771 
False
 
229
ValueCountFrequency (%)
True 9771
97.7%
False 229
 
2.3%
2023-12-11T15:56:03.170617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

설치연도
Text

Distinct62
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:56:03.431863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters40000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2008
2nd row2001
3rd row1996
4th row1997
5th row1992
ValueCountFrequency (%)
1996 828
 
8.3%
1997 700
 
7.0%
1993 655
 
6.6%
1992 576
 
5.8%
1995 542
 
5.4%
1994 526
 
5.3%
1998 523
 
5.2%
2001 393
 
3.9%
1989 340
 
3.4%
1991 333
 
3.3%
Other values (51) 4577
45.8%
2023-12-11T15:56:03.881242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 12576
31.4%
1 8756
21.9%
0 6198
15.5%
2 4118
 
10.3%
8 2502
 
6.3%
7 1466
 
3.7%
6 1380
 
3.5%
3 1051
 
2.6%
4 1027
 
2.6%
5 898
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39972
99.9%
Space Separator 28
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 12576
31.5%
1 8756
21.9%
0 6198
15.5%
2 4118
 
10.3%
8 2502
 
6.3%
7 1466
 
3.7%
6 1380
 
3.5%
3 1051
 
2.6%
4 1027
 
2.6%
5 898
 
2.2%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 12576
31.4%
1 8756
21.9%
0 6198
15.5%
2 4118
 
10.3%
8 2502
 
6.3%
7 1466
 
3.7%
6 1380
 
3.5%
3 1051
 
2.6%
4 1027
 
2.6%
5 898
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 12576
31.4%
1 8756
21.9%
0 6198
15.5%
2 4118
 
10.3%
8 2502
 
6.3%
7 1466
 
3.7%
6 1380
 
3.5%
3 1051
 
2.6%
4 1027
 
2.6%
5 898
 
2.2%

관할소방서명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강남소방서
945 
서초소방서
846 
영등포소방서
817 
종로소방서
710 
동대문소방서
688 
Other values (13)
5994 

Length

Max length18
Median length18
Mean length18
Min length18

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row중부소방서
2nd row도봉소방서
3rd row도봉소방서
4th row성북소방서
5th row동대문소방서

Common Values

ValueCountFrequency (%)
강남소방서 945
 
9.4%
서초소방서 846
 
8.5%
영등포소방서 817
 
8.2%
종로소방서 710
 
7.1%
동대문소방서 688
 
6.9%
성북소방서 667
 
6.7%
강서소방서 647
 
6.5%
중부소방서 634
 
6.3%
마포소방서 632
 
6.3%
강동소방서 627
 
6.3%
Other values (8) 2787
27.9%

Length

2023-12-11T15:56:04.071735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남소방서 945
 
9.5%
서초소방서 846
 
8.5%
영등포소방서 817
 
8.2%
종로소방서 710
 
7.1%
동대문소방서 688
 
6.9%
성북소방서 667
 
6.7%
강서소방서 647
 
6.5%
중부소방서 634
 
6.3%
마포소방서 632
 
6.3%
강동소방서 627
 
6.3%
Other values (7) 2781
27.8%

관할소방서전화번호
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
02-6981-7475
945 
02-6981-5843
846 
02-6981-7043
817 
02-6981-5700
710 
02-6942-1243
688 
Other values (14)
5994 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row02-2253-0119
2nd row02-6981-8043
3rd row02-6981-8043
4th row02-6981-7243
5th row02-6942-1243

Common Values

ValueCountFrequency (%)
02-6981-7475 945
 
9.4%
02-6981-5843 846
 
8.5%
02-6981-7043 817
 
8.2%
02-6981-5700 710
 
7.1%
02-6942-1243 688
 
6.9%
02-6981-7243 667
 
6.7%
02-6981-5043 647
 
6.5%
02-2253-0119 634
 
6.3%
02-6981-7843 632
 
6.3%
02-6981-7643 627
 
6.3%
Other values (9) 2787
27.9%

Length

2023-12-11T15:56:04.225474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02-6981-7475 945
 
9.5%
02-6981-5843 846
 
8.5%
02-6981-7043 817
 
8.2%
02-6981-5700 710
 
7.1%
02-6942-1243 688
 
6.9%
02-6981-7243 667
 
6.7%
02-6981-5043 647
 
6.5%
02-2253-0119 634
 
6.3%
02-6981-7843 632
 
6.3%
02-6981-7643 627
 
6.3%
Other values (8) 2781
27.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-06-30
10000 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-06-30
2nd row2022-06-30
3rd row2022-06-30
4th row2022-06-30
5th row2022-06-30

Common Values

ValueCountFrequency (%)
2022-06-30 10000
100.0%

Length

2023-12-11T15:56:04.380844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:56:04.495424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06-30 10000
100.0%

Interactions

2023-12-11T15:55:55.126680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:55:54.564417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:55:54.876224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:55:55.216136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:55:54.679784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:55:54.964641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:55:55.294504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:55:54.770156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:55:55.045713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T15:56:04.566883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형코드시군구명시군구코드위도경도안전센터명보호틀유무사용가능여부설치연도관할소방서명관할소방서전화번호
시설유형코드1.0000.0890.0680.0000.0000.3940.0390.0610.4270.0870.164
시군구명0.0891.0001.0000.3210.3210.9900.0490.1330.5491.0000.997
시군구코드0.0681.0001.0000.2360.2360.9840.0490.1080.5021.0001.000
위도0.0000.3210.2361.0001.0000.5280.0000.0000.0590.3210.285
경도0.0000.3210.2361.0001.0000.5280.0000.0000.0590.3210.285
안전센터명0.3940.9900.9840.5280.5281.0000.1130.1910.6240.9870.985
보호틀유무0.0390.0490.0490.0000.0000.1131.0000.0000.2510.0490.042
사용가능여부0.0610.1330.1080.0000.0000.1910.0001.0000.2000.2440.217
설치연도0.4270.5490.5020.0590.0590.6240.2510.2001.0000.7450.742
관할소방서명0.0871.0001.0000.3210.3210.9870.0490.2440.7451.0001.000
관할소방서전화번호0.1640.9971.0000.2850.2850.9850.0420.2170.7421.0001.000
2023-12-11T15:56:04.710401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명관할소방서명사용가능여부시설유형코드관할소방서전화번호보호틀유무
시군구명1.0000.9700.1050.0450.9700.038
관할소방서명0.9701.0000.1920.0441.0000.038
사용가능여부0.1050.1921.0000.0750.1920.000
시설유형코드0.0450.0440.0751.0000.0820.047
관할소방서전화번호0.9701.0000.1920.0821.0000.037
보호틀유무0.0380.0380.0000.0470.0371.000
2023-12-11T15:56:04.836767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드위도경도시설유형코드시군구명보호틀유무사용가능여부관할소방서명관할소방서전화번호
시군구코드1.000-0.6040.0800.0321.0000.0370.0871.0001.000
위도-0.6041.0000.1290.0000.2530.0000.0000.2530.253
경도0.0800.1291.0000.0000.2530.0000.0000.2530.253
시설유형코드0.0320.0000.0001.0000.0450.0470.0750.0440.082
시군구명1.0000.2530.2530.0451.0000.0380.1050.9700.970
보호틀유무0.0370.0000.0000.0470.0381.0000.0000.0380.037
사용가능여부0.0870.0000.0000.0750.1050.0001.0000.1920.192
관할소방서명1.0000.2530.2530.0440.9700.0380.1921.0001.000
관할소방서전화번호1.0000.2530.2530.0820.9700.0370.1921.0001.000

Missing values

2023-12-11T15:55:55.429608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:55:55.688990image/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.
2023-12-11T15:55:55.817903image/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

시설번호시설유형코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도상세위치안전센터명보호틀유무사용가능여부설치연도관할소방서명관할소방서전화번호데이터기준일자
5383중부-32822서울특별시중구11140서울특별시 중구 서애로 15-6 삼진빌딩서울특별시 중구 필동3가 20-14 삼진빌딩37.560581126.998012<NA>신당119안전센터NY2008중부소방서02-2253-01192022-06-30
35291현장대응단-14642서울특별시도봉구11320서울특별시 도봉구 해등로16길 52-18서울특별시 도봉구 창동 291-1737.654729127.042769지번앞현장대응단NY2001도봉소방서02-6981-80432022-06-30
35145현장대응단-10982서울특별시도봉구11320서울특별시 도봉구 도당로2길 59서울특별시 도봉구 쌍문동 712-2637.659372127.038434지번앞현장대응단NY1996도봉소방서02-6981-80432022-06-30
1799442652서울특별시성북구11290서울특별시 성북구 장위로8길 6서울특별시 성북구 장위동 231-21837.613037127.038847지번 앞장위119안전센터NY1997성북소방서02-6981-72432022-06-30
9665동대문-0014992서울특별시동대문구11230서울특별시 동대문구 휘경로 28 외대역앞역 5번출구앞서울특별시 동대문구 이문동 306-14 외대역앞역 5번출구앞37.595596127.060606한길교회청량리119안전센터NY1992동대문소방서02-6942-12432022-06-30
21955강남-0016661서울특별시강남구11680서울특별시 강남구 영동대로 520 삼성동아이파크타워서울특별시 강남구 삼성동 160 삼성동아이파크타워37.51417127.060963삼성동아이파크타워현장대응단NY1993강남소방서02-6981-74752022-06-30
24719서울서초-0018001서울특별시서초구11650서울특별시 서초구 남부순환로340길 29 서울특별시소방학교서울특별시 서초구 서초동 391 서울특별시소방학교37.481598127.023762소방학교우면119안전센터NY1993서초소방서02-6981-58432022-06-30
4316중부-28672서울특별시중구11140청계천로 100서울특별시 중구 수표동 9937.567815126.988688<NA>충무로119안전센터NY1984중부소방서02-2253-01192022-06-30
27261서울서초-307022서울특별시서초구11650서울특별시 서초구 효령로 165서울특별시 서초구 서초동 1490-4937.482509127.002113<NA>서초119안전센터NY2010서초소방서02-6981-58432022-06-30
34711마포-0051872서울특별시마포구11440서울특별시 마포구 임정로 59-6서울특별시 마포구 신공덕동 2-9437.544952126.917742공덕119안전센터NY1990마포소방서02-6981-78432022-06-30
시설번호시설유형코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도상세위치안전센터명보호틀유무사용가능여부설치연도관할소방서명관할소방서전화번호데이터기준일자
7282용산-0002232서울특별시용산구11170서울특별시 용산구 서빙고로 50-12서울특별시 용산구 한강로3가 65-31337.52303126.969552지번앞이촌119안전센터NY1986용산소방서02-6943-14432022-06-30
10348동대문-0012442서울특별시동대문11230서울특별시 동대문구 황물로 147서울특별시 동대문구 답십리동 490-1637.566713127.054814지번 앞전농119안전센터NY1991동대문소방서02-6942-12432022-06-30
33836마포-14441서울특별시마포구11440서울특별시 마포구 대흥로 122서울특별시 마포구 대흥동 38-2237.550168126.93509현장대응단NY1997마포소방서02-6981-78432022-06-30
26803서울서초-302432서울특별시서초구11650서울특별시 서초구 서초대로25길 80서울특별시 서초구 방배동 838-137.491025126.992402<NA>현장대응단NY2007서초소방서02-6981-58432022-06-30
28995강서-1300532서울특별시강서구11500서울특별시 강서구 까치산로18라길 6 세븐일레븐 화곡하늘점서울특별시 강서구 화곡동 42-48 세븐일레븐 화곡하늘점37.546957126.851742<NA>발산119안전센터NY1998강서소방서02-6981-50432022-06-30
24243서울서초-0002262서울특별시서초구11650서울특별시 서초구 서초대로27길 30서울특별시 서초구 방배동 877-137.489285126.994305<NA>현장대응단NY1992서초소방서02-6981-58432022-06-30
9655동대문-0004362서울특별시동대문구11230서울특별시 동대문구 휘경로2가길 16-9서울특별시 동대문구 이문동 305-11237.595964127.060852부흥슈퍼청량리119안전센터NY1986동대문소방서02-6942-12432022-06-30
152297624342서울특별시영등포구11560서울시 영등포구 영신로39길14-1서울시 영등포구 당산동1가 155-237.521696126.899588<NA>당산119안전센터NY1991영등포소방서02-6981-70432022-06-30
26539서울서초-205012서울특별시서초구11650서울특별시 서초구 바우뫼로 135-4 두범빌딩서울특별시 서초구 양재동 70-6 두범빌딩37.476402127.035413두범빌딩우면119안전센터NY2002서초소방서02-6981-58432022-06-30
617숭-1472서울특별시종로구11110서울특별시 종로구 난계로27길 34서울특별시 종로구 숭인동 202-3437.572934127.021177<NA>숭인119안전센터NY1995종로소방서02-6981-57002022-06-30