Overview

Dataset statistics

Number of variables11
Number of observations134
Missing cells135
Missing cells (%)9.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.0 KiB
Average record size in memory92.0 B

Variable types

Numeric3
Categorical5
Text3

Dataset

Description대전광역시 비상소화장치 설치 현황으로서 비상소화장치 위치(위도, 경도), 자체관리번호, 관할소방서, 소화전형식, 설치연도 등 제공하고 있습니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15080771/fileData.do

Alerts

시도 has constant value ""Constant
연번 is highly overall correlated with 소방서High correlation
위도 is highly overall correlated with 소방서High correlation
경도 is highly overall correlated with 소방서High correlation
소방서 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
소화전 연결방식(일체형 및 분리형) is highly overall correlated with 설치연도High correlation
소화전 형식 is highly overall correlated with 설치연도High correlation
설치연도 is highly overall correlated with 소화전 연결방식(일체형 및 분리형) and 1 other fieldsHigh correlation
위도 has 2 (1.5%) missing valuesMissing
경도 has 2 (1.5%) missing valuesMissing
비고 has 131 (97.8%) missing valuesMissing
연번 has unique valuesUnique
자체 관리번호 has unique valuesUnique
비상소화장치 위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:53:45.297399
Analysis finished2023-12-12 10:53:48.566914
Duration3.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct134
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.5
Minimum1
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T19:53:48.709955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.65
Q134.25
median67.5
Q3100.75
95-th percentile127.35
Maximum134
Range133
Interquartile range (IQR)66.5

Descriptive statistics

Standard deviation38.826537
Coefficient of variation (CV)0.57520796
Kurtosis-1.2
Mean67.5
Median Absolute Deviation (MAD)33.5
Skewness0
Sum9045
Variance1507.5
MonotonicityStrictly increasing
2023-12-12T19:53:48.976659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
86 1
 
0.7%
100 1
 
0.7%
99 1
 
0.7%
98 1
 
0.7%
97 1
 
0.7%
96 1
 
0.7%
95 1
 
0.7%
94 1
 
0.7%
93 1
 
0.7%
Other values (124) 124
92.5%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%
128 1
0.7%
127 1
0.7%
126 1
0.7%
125 1
0.7%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
대전
134 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전 134
100.0%

Length

2023-12-12T19:53:49.258547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:53:49.437907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전 134
100.0%

소방서
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
동부
37 
대덕
37 
서부
25 
둔산
19 
유성
16 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동부
2nd row서부
3rd row서부
4th row서부
5th row유성

Common Values

ValueCountFrequency (%)
동부 37
27.6%
대덕 37
27.6%
서부 25
18.7%
둔산 19
14.2%
유성 16
11.9%

Length

2023-12-12T19:53:49.666322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:53:49.977020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동부 37
27.6%
대덕 37
27.6%
서부 25
18.7%
둔산 19
14.2%
유성 16
11.9%

자체 관리번호
Text

UNIQUE 

Distinct134
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T19:53:50.530636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.3059701
Min length5

Characters and Unicode

Total characters845
Distinct characters53
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

Unique134 ?
Unique (%)100.0%

Sample

1st row가양비상-12
2nd row산성비상-2
3rd row가수원비상-2
4th row가수원비상-1
5th row노은센터-10
ValueCountFrequency (%)
가양비상-12 1
 
0.7%
원동비상-3 1
 
0.7%
산내비상-36 1
 
0.7%
송촌센터-4 1
 
0.7%
가양비상-33 1
 
0.7%
가양비상-9 1
 
0.7%
부사비상-19 1
 
0.7%
덕암센터-1 1
 
0.7%
원동비상-20 1
 
0.7%
가양비상-26 1
 
0.7%
Other values (124) 124
92.5%
2023-12-12T19:53:51.301444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 133
15.7%
비 68
 
8.0%
상 68
 
8.0%
센 66
 
7.8%
터 66
 
7.8%
1 40
 
4.7%
동 35
 
4.1%
2 32
 
3.8%
3 28
 
3.3%
원 25
 
3.0%
Other values (43) 284
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 542
64.1%
Decimal Number 170
 
20.1%
Dash Punctuation 133
 
15.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 68
12.5%
상 68
12.5%
센 66
12.2%
터 66
12.2%
동 35
 
6.5%
원 25
 
4.6%
평 17
 
3.1%
문 14
 
2.6%
수 13
 
2.4%
법 12
 
2.2%
Other values (32) 158
29.2%
Decimal Number
ValueCountFrequency (%)
1 40
23.5%
2 32
18.8%
3 28
16.5%
4 17
10.0%
5 14
 
8.2%
6 12
 
7.1%
7 9
 
5.3%
8 8
 
4.7%
9 6
 
3.5%
0 4
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 542
64.1%
Common 303
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 68
12.5%
상 68
12.5%
센 66
12.2%
터 66
12.2%
동 35
 
6.5%
원 25
 
4.6%
평 17
 
3.1%
문 14
 
2.6%
수 13
 
2.4%
법 12
 
2.2%
Other values (32) 158
29.2%
Common
ValueCountFrequency (%)
- 133
43.9%
1 40
 
13.2%
2 32
 
10.6%
3 28
 
9.2%
4 17
 
5.6%
5 14
 
4.6%
6 12
 
4.0%
7 9
 
3.0%
8 8
 
2.6%
9 6
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 542
64.1%
ASCII 303
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 133
43.9%
1 40
 
13.2%
2 32
 
10.6%
3 28
 
9.2%
4 17
 
5.6%
5 14
 
4.6%
6 12
 
4.0%
7 9
 
3.0%
8 8
 
2.6%
9 6
 
2.0%
Hangul
ValueCountFrequency (%)
비 68
12.5%
상 68
12.5%
센 66
12.2%
터 66
12.2%
동 35
 
6.5%
원 25
 
4.6%
평 17
 
3.1%
문 14
 
2.6%
수 13
 
2.4%
법 12
 
2.2%
Other values (32) 158
29.2%

비상소화장치 위치
Text

UNIQUE 

Distinct134
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T19:53:51.820932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length28
Mean length19.835821
Min length14

Characters and Unicode

Total characters2658
Distinct characters153
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)100.0%

Sample

1st row대전광역시 동구 미래길 73 계룡철물점 우측
2nd row대전광역시 중구 대둔산로346번길41
3rd row대전광역시 서구 무도리길247
4th row대전광역시 서구 방앗간길379
5th row대전광역시 유성구 외삼동178-3
ValueCountFrequency (%)
대전광역시 131
28.2%
동구 33
 
7.1%
대덕구 31
 
6.7%
서구 26
 
5.6%
중구 21
 
4.5%
유성구 16
 
3.4%
대전로 5
 
1.1%
대전로791번길 3
 
0.6%
동대전로 2
 
0.4%
110번길 2
 
0.4%
Other values (184) 194
41.8%
2023-12-12T19:53:52.592093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
344
 
12.9%
대 203
 
7.6%
전 152
 
5.7%
구 136
 
5.1%
광 135
 
5.1%
시 135
 
5.1%
역 134
 
5.0%
길 114
 
4.3%
1 111
 
4.2%
로 102
 
3.8%
Other values (143) 1092
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1709
64.3%
Decimal Number 549
 
20.7%
Space Separator 344
 
12.9%
Dash Punctuation 20
 
0.8%
Close Punctuation 17
 
0.6%
Open Punctuation 17
 
0.6%
Lowercase Letter 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 203
11.9%
전 152
 
8.9%
구 136
 
8.0%
광 135
 
7.9%
시 135
 
7.9%
역 134
 
7.8%
길 114
 
6.7%
로 102
 
6.0%
번 84
 
4.9%
동 59
 
3.5%
Other values (127) 455
26.6%
Decimal Number
ValueCountFrequency (%)
1 111
20.2%
2 70
12.8%
3 67
12.2%
4 59
10.7%
7 59
10.7%
5 57
10.4%
8 36
 
6.6%
0 34
 
6.2%
6 28
 
5.1%
9 28
 
5.1%
Space Separator
ValueCountFrequency (%)
344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1709
64.3%
Common 948
35.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 203
11.9%
전 152
 
8.9%
구 136
 
8.0%
광 135
 
7.9%
시 135
 
7.9%
역 134
 
7.8%
길 114
 
6.7%
로 102
 
6.0%
번 84
 
4.9%
동 59
 
3.5%
Other values (127) 455
26.6%
Common
ValueCountFrequency (%)
344
36.3%
1 111
 
11.7%
2 70
 
7.4%
3 67
 
7.1%
4 59
 
6.2%
7 59
 
6.2%
5 57
 
6.0%
8 36
 
3.8%
0 34
 
3.6%
6 28
 
3.0%
Other values (5) 83
 
8.8%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1709
64.3%
ASCII 949
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
344
36.2%
1 111
 
11.7%
2 70
 
7.4%
3 67
 
7.1%
4 59
 
6.2%
7 59
 
6.2%
5 57
 
6.0%
8 36
 
3.8%
0 34
 
3.6%
6 28
 
3.0%
Other values (6) 84
 
8.9%
Hangul
ValueCountFrequency (%)
대 203
11.9%
전 152
 
8.9%
구 136
 
8.0%
광 135
 
7.9%
시 135
 
7.9%
역 134
 
7.8%
길 114
 
6.7%
로 102
 
6.0%
번 84
 
4.9%
동 59
 
3.5%
Other values (127) 455
26.6%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct132
Distinct (%)100.0%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean36.351897
Minimum36.200024
Maximum36.493383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T19:53:52.876423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.200024
5-th percentile36.303002
Q136.324317
median36.33547
Q336.367158
95-th percentile36.449086
Maximum36.493383
Range0.2933591
Interquartile range (IQR)0.0428412

Descriptive statistics

Standard deviation0.04852124
Coefficient of variation (CV)0.001334765
Kurtosis0.80179065
Mean36.351897
Median Absolute Deviation (MAD)0.0208405
Skewness0.50174222
Sum4798.4504
Variance0.0023543107
MonotonicityNot monotonic
2023-12-12T19:53:53.181435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.34126 1
 
0.7%
36.3180044 1
 
0.7%
36.311987 1
 
0.7%
36.359769 1
 
0.7%
36.3366048 1
 
0.7%
36.327898 1
 
0.7%
36.314897 1
 
0.7%
36.4375523 1
 
0.7%
36.322544 1
 
0.7%
36.3441285 1
 
0.7%
Other values (122) 122
91.0%
(Missing) 2
 
1.5%
ValueCountFrequency (%)
36.2000243 1
0.7%
36.243776 1
0.7%
36.248811 1
0.7%
36.255476 1
0.7%
36.258348 1
0.7%
36.295271 1
0.7%
36.301445 1
0.7%
36.304275 1
0.7%
36.306956 1
0.7%
36.309609 1
0.7%
ValueCountFrequency (%)
36.4933834 1
0.7%
36.452528 1
0.7%
36.450324 1
0.7%
36.450168 1
0.7%
36.449496 1
0.7%
36.449478 1
0.7%
36.44947 1
0.7%
36.448771 1
0.7%
36.448132 1
0.7%
36.443592 1
0.7%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct132
Distinct (%)100.0%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean127.40352
Minimum127.26274
Maximum127.50641
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T19:53:53.482073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.26274
5-th percentile127.31976
Q1127.38375
median127.41773
Q3127.43198
95-th percentile127.44979
Maximum127.50641
Range0.243675
Interquartile range (IQR)0.048229675

Descriptive statistics

Standard deviation0.042184953
Coefficient of variation (CV)0.00033111294
Kurtosis1.5003299
Mean127.40352
Median Absolute Deviation (MAD)0.0185868
Skewness-1.2027121
Sum16817.265
Variance0.0017795703
MonotonicityNot monotonic
2023-12-12T19:53:53.770236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.434161 1
 
0.7%
127.4472062 1
 
0.7%
127.4450249 1
 
0.7%
127.443153 1
 
0.7%
127.4384218 1
 
0.7%
127.437859 1
 
0.7%
127.437248 1
 
0.7%
127.4369722 1
 
0.7%
127.436388 1
 
0.7%
127.4362541 1
 
0.7%
Other values (122) 122
91.0%
(Missing) 2
 
1.5%
ValueCountFrequency (%)
127.262735 1
0.7%
127.26823 1
0.7%
127.287042 1
0.7%
127.289967 1
0.7%
127.293856 1
0.7%
127.312896 1
0.7%
127.316966 1
0.7%
127.322054 1
0.7%
127.324021 1
0.7%
127.333589 1
0.7%
ValueCountFrequency (%)
127.50641 1
0.7%
127.462536 1
0.7%
127.460024 1
0.7%
127.453038 1
0.7%
127.4515225 1
0.7%
127.450979 1
0.7%
127.4508591 1
0.7%
127.448914 1
0.7%
127.4472062 1
0.7%
127.4450249 1
0.7%

소화전 연결방식(일체형 및 분리형)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
일체형
71 
분리형
63 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row분리형
2nd row일체형
3rd row분리형
4th row분리형
5th row일체형

Common Values

ValueCountFrequency (%)
일체형 71
53.0%
분리형 63
47.0%

Length

2023-12-12T19:53:53.997676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:53:54.743721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일체형 71
53.0%
분리형 63
47.0%

소화전 형식
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
지상식
72 
지하식
62 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지상식
2nd row지상식
3rd row지상식
4th row지하식
5th row지상식

Common Values

ValueCountFrequency (%)
지상식 72
53.7%
지하식 62
46.3%

Length

2023-12-12T19:53:54.922064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:53:55.116663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상식 72
53.7%
지하식 62
46.3%

설치연도
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2013
15 
2015
14 
2019
13 
2014
12 
2003
10 
Other values (16)
70 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique4 ?
Unique (%)3.0%

Sample

1st row1998
2nd row2016
3rd row2017
4th row2002
5th row2016

Common Values

ValueCountFrequency (%)
2013 15
11.2%
2015 14
10.4%
2019 13
9.7%
2014 12
 
9.0%
2003 10
 
7.5%
2017 9
 
6.7%
2016 9
 
6.7%
2020 8
 
6.0%
2011 6
 
4.5%
2006 6
 
4.5%
Other values (11) 32
23.9%

Length

2023-12-12T19:53:55.323566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2013 15
11.2%
2015 14
10.4%
2019 13
9.7%
2014 12
 
9.0%
2003 10
 
7.5%
2017 9
 
6.7%
2016 9
 
6.7%
2020 8
 
6.0%
2006 6
 
4.5%
2018 6
 
4.5%
Other values (11) 32
23.9%

비고
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing131
Missing (%)97.8%
Memory size1.2 KiB
2023-12-12T19:53:55.581086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length16.666667
Min length10

Characters and Unicode

Total characters50
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row현재 소화전 이설중
2nd row공사중 2024.6.30까지 센터보관
3rd row공사중 2024.6.30까지 센터보관
ValueCountFrequency (%)
공사중 2
22.2%
2024.6.30까지 2
22.2%
센터보관 2
22.2%
현재 1
11.1%
소화전 1
11.1%
이설중 1
11.1%
2023-12-12T19:53:56.142135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
12.0%
2 4
 
8.0%
0 4
 
8.0%
. 4
 
8.0%
중 3
 
6.0%
공 2
 
4.0%
사 2
 
4.0%
관 2
 
4.0%
보 2
 
4.0%
터 2
 
4.0%
Other values (13) 19
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26
52.0%
Decimal Number 14
28.0%
Space Separator 6
 
12.0%
Other Punctuation 4
 
8.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 3
11.5%
공 2
 
7.7%
사 2
 
7.7%
관 2
 
7.7%
보 2
 
7.7%
터 2
 
7.7%
센 2
 
7.7%
지 2
 
7.7%
까 2
 
7.7%
현 1
 
3.8%
Other values (6) 6
23.1%
Decimal Number
ValueCountFrequency (%)
2 4
28.6%
0 4
28.6%
3 2
14.3%
6 2
14.3%
4 2
14.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26
52.0%
Common 24
48.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 3
11.5%
공 2
 
7.7%
사 2
 
7.7%
관 2
 
7.7%
보 2
 
7.7%
터 2
 
7.7%
센 2
 
7.7%
지 2
 
7.7%
까 2
 
7.7%
현 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
6
25.0%
2 4
16.7%
0 4
16.7%
. 4
16.7%
3 2
 
8.3%
6 2
 
8.3%
4 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26
52.0%
ASCII 24
48.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
25.0%
2 4
16.7%
0 4
16.7%
. 4
16.7%
3 2
 
8.3%
6 2
 
8.3%
4 2
 
8.3%
Hangul
ValueCountFrequency (%)
중 3
11.5%
공 2
 
7.7%
사 2
 
7.7%
관 2
 
7.7%
보 2
 
7.7%
터 2
 
7.7%
센 2
 
7.7%
지 2
 
7.7%
까 2
 
7.7%
현 1
 
3.8%
Other values (6) 6
23.1%

Interactions

2023-12-12T19:53:47.280717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:53:46.212353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:53:46.740274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:53:47.452808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:53:46.381171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:53:46.944812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:53:47.647601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:53:46.564752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:53:47.117734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:53:56.332006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소방서위도경도소화전 연결방식(일체형 및 분리형)소화전 형식설치연도비고
연번1.0000.9550.6130.9190.5480.3920.6950.000
소방서0.9551.0000.7810.8870.3020.1720.5550.000
위도0.6130.7811.0000.5660.0000.0000.765NaN
경도0.9190.8870.5661.0000.4710.2880.163NaN
소화전 연결방식(일체형 및 분리형)0.5480.3020.0000.4711.0000.6900.7600.000
소화전 형식0.3920.1720.0000.2880.6901.0000.6470.000
설치연도0.6950.5550.7650.1630.7600.6471.0001.000
비고0.0000.000NaNNaN0.0000.0001.0001.000
2023-12-12T19:53:56.598790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도소화전 형식소방서소화전 연결방식(일체형 및 분리형)
설치연도1.0000.5320.2890.636
소화전 형식0.5321.0000.2080.484
소방서0.2890.2081.0000.365
소화전 연결방식(일체형 및 분리형)0.6360.4840.3651.000
2023-12-12T19:53:56.818205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도소방서소화전 연결방식(일체형 및 분리형)소화전 형식설치연도
연번1.000-0.4160.4490.6960.4090.2910.323
위도-0.4161.0000.1140.5900.0000.0000.401
경도0.4490.1141.0000.5550.3510.2130.046
소방서0.6960.5900.5551.0000.3650.2080.289
소화전 연결방식(일체형 및 분리형)0.4090.0000.3510.3651.0000.4840.636
소화전 형식0.2910.0000.2130.2080.4841.0000.532
설치연도0.3230.4010.0460.2890.6360.5321.000

Missing values

2023-12-12T19:53:47.909708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:53:48.231578image/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.
2023-12-12T19:53:48.458550image/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

연번시도소방서자체 관리번호비상소화장치 위치위도경도소화전 연결방식(일체형 및 분리형)소화전 형식설치연도비고
01대전동부가양비상-12대전광역시 동구 미래길 73 계룡철물점 우측36.200024127.262735분리형지상식1998<NA>
12대전서부산성비상-2대전광역시 중구 대둔산로346번길4136.311974127.26823일체형지상식2016<NA>
23대전서부가수원비상-2대전광역시 서구 무도리길24736.258348127.287042분리형지상식2017<NA>
34대전서부가수원비상-1대전광역시 서구 방앗간길37936.248811127.312896분리형지하식2002<NA>
45대전유성노은센터-10대전광역시 유성구 외삼동178-336.39969127.316966일체형지상식2016<NA>
56대전유성구암센터-9대전광역시 유성구 박산로104번길709(구암동)36.350452127.322054일체형지상식2016<NA>
67대전유성궁동센터-3대전광역시 유성구 유성대로720번길3036.35716127.333589일체형지상식2013<NA>
78대전유성궁동센터-1대전광역시 유성구유성대로730번길2436.357918127.333605분리형지하식확인불가<NA>
89대전유성궁동센터-2대전광역시 유성구 유성대로720번길4136.357322127.33427분리형지하식2013<NA>
910대전유성궁동센터-4대전광역시 유성구 유성대로720번길4036.357947127.334935일체형지상식2013<NA>
연번시도소방서자체 관리번호비상소화장치 위치위도경도소화전 연결방식(일체형 및 분리형)소화전 형식설치연도비고
124125대전서부문화비상-3대전광역시 중구 보문로125번길1636.31458127.426905분리형지하식2001<NA>
125126대전동부원동비상-4대전광역시 동구 마을회관3길 9<NA><NA>분리형지하식2015공사중 2024.6.30까지 센터보관
126127대전동부원동비상-25대전광역시 동구 마을회관길 109<NA><NA>분리형지하식2013공사중 2024.6.30까지 센터보관
127128대전둔산태평센터-5대전광역시 서구 유천로 142번길 3136.325467127.396772일체형지하식2020<NA>
128129대전둔산태평센터-6대전광역시 서구 유천로 142번길 1336.325255127.395832일체형지하식2020<NA>
129130대전대덕법동센터-시민2대전광역시 대덕구 중리북로37번길 5 / 중리시장36.365912127.425905일체형지하식2020<NA>
130131대전서부산성비상3대전광역시 중구 금동길54-436.243776127.426533일체형지상식2020<NA>
131132대전서부가수원센터-3대전광역시 서구 계백로1158번길 1136.304275127.352271분리형지상식2020<NA>
132133대전서부가수원센터-4대전광역시 서구 야실길 5536.255476127.324021분리형지상식2020<NA>
133134대전둔산갈마센터-6대전광역시 서구 가장로 94번길36.334479127.384286일체형지하식2020<NA>