Overview

Dataset statistics

Number of variables16
Number of observations234
Missing cells258
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.8 KiB
Average record size in memory130.6 B

Variable types

Numeric2
Categorical8
DateTime4
Text2

Dataset

Description세종소방본부에서 제공하는 2020년 차량화재종별 신고 정보로서 접수경로명, 접수일시, 상황종료일시, 관할서명, 서센터명, 긴급구조 종별, 분류, 규모명 등의 정보를 제공하는 데이터임
Author소방청
URLhttps://www.data.go.kr/data/15080971/fileData.do

Alerts

긴급구조 종별명 has constant value ""Constant
긴급구조 분류명 has constant value ""Constant
긴급구조 규모명 has constant value ""Constant
일련번호 is highly overall correlated with 관할서명High correlation
긴급구조 우편번호 is highly overall correlated with 서센터명High correlation
긴급구조 동명 is highly overall correlated with 관할서명 and 1 other fieldsHigh correlation
관할서명 is highly overall correlated with 일련번호 and 2 other fieldsHigh correlation
서센터명 is highly overall correlated with 긴급구조 우편번호 and 2 other fieldsHigh correlation
접수경로명 is highly imbalanced (65.8%)Imbalance
타시도신고여부 is highly imbalanced (92.9%)Imbalance
긴급구조 우편번호 has 12 (5.1%) missing valuesMissing
긴급구조 리명 has 60 (25.6%) missing valuesMissing
도로명 has 186 (79.5%) missing valuesMissing
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:41:51.525303
Analysis finished2023-12-12 06:41:53.316994
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct234
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.51282
Minimum1
Maximum254
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T15:41:53.393758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.65
Q159.25
median121.5
Q3185.75
95-th percentile240.35
Maximum254
Range253
Interquartile range (IQR)126.5

Descriptive statistics

Standard deviation73.131913
Coefficient of variation (CV)0.59693273
Kurtosis-1.1902888
Mean122.51282
Median Absolute Deviation (MAD)63.5
Skewness0.082966219
Sum28668
Variance5348.2767
MonotonicityStrictly increasing
2023-12-12T15:41:53.551953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
169 1
 
0.4%
155 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
Other values (224) 224
95.7%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%
246 1
0.4%
244 1
0.4%
243 1
0.4%

접수경로명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
이동전화
206 
기타
 
13
일반전화
 
13
사후각지
 
2

Length

Max length4
Median length4
Mean length3.8888889
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row일반전화
3rd row기타
4th row이동전화
5th row이동전화

Common Values

ValueCountFrequency (%)
이동전화 206
88.0%
기타 13
 
5.6%
일반전화 13
 
5.6%
사후각지 2
 
0.9%

Length

2023-12-12T15:41:53.730329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:41:53.881490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이동전화 206
88.0%
기타 13
 
5.6%
일반전화 13
 
5.6%
사후각지 2
 
0.9%

접수일시
Date

Distinct228
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2012-07-20 00:00:00
Maximum2021-09-09 00:00:00
2023-12-12T15:41:54.021493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:41:54.183240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

접수일시(상세)
Date

Distinct233
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2023-12-12 00:05:46
Maximum2023-12-12 23:55:59
2023-12-12T15:41:54.374111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:41:54.558532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

타시도신고여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
아니오
232 
예
 
2

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아니오 232
99.1%
예 2
 
0.9%

Length

2023-12-12T15:41:54.686963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:41:54.787423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아니오 232
99.1%
예 2
 
0.9%

긴급구조 우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct110
Distinct (%)49.5%
Missing12
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean78842.347
Minimum71007
Maximum80191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T15:41:54.908299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum71007
5-th percentile71093.5
Q180013
median80085.5
Q380147
95-th percentile80181
Maximum80191
Range9184
Interquartile range (IQR)134

Descriptive statistics

Standard deviation3122.311
Coefficient of variation (CV)0.039601954
Kurtosis2.4024604
Mean78842.347
Median Absolute Deviation (MAD)71.5
Skewness-2.0923001
Sum17503001
Variance9748825.7
MonotonicityNot monotonic
2023-12-12T15:41:55.033812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80012 7
 
3.0%
80078 7
 
3.0%
80006 7
 
3.0%
80022 7
 
3.0%
80143 6
 
2.6%
80097 6
 
2.6%
80013 5
 
2.1%
80086 5
 
2.1%
80080 4
 
1.7%
80165 4
 
1.7%
Other values (100) 164
70.1%
(Missing) 12
 
5.1%
ValueCountFrequency (%)
71007 2
0.9%
71022 2
0.9%
71036 1
0.4%
71046 2
0.9%
71048 1
0.4%
71052 1
0.4%
71077 1
0.4%
71093 2
0.9%
71103 1
0.4%
71105 1
0.4%
ValueCountFrequency (%)
80191 1
 
0.4%
80189 2
0.9%
80188 1
 
0.4%
80187 1
 
0.4%
80186 1
 
0.4%
80185 3
1.3%
80183 1
 
0.4%
80182 1
 
0.4%
80181 3
1.3%
80179 2
0.9%

긴급구조 동명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
조치원읍
32 
금남면
32 
장군면
21 
전의면
15 
연서면
14 
Other values (19)
120 

Length

Max length4
Median length3
Mean length3.1367521
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row소정면
2nd row금남면
3rd row부강면
4th row전의면
5th row부강면

Common Values

ValueCountFrequency (%)
조치원읍 32
13.7%
금남면 32
13.7%
장군면 21
 
9.0%
전의면 15
 
6.4%
연서면 14
 
6.0%
부강면 14
 
6.0%
연기면 13
 
5.6%
전동면 13
 
5.6%
소정면 11
 
4.7%
연동면 11
 
4.7%
Other values (14) 58
24.8%

Length

2023-12-12T15:41:55.147206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조치원읍 32
13.7%
금남면 32
13.7%
장군면 21
 
9.0%
전의면 15
 
6.4%
연서면 14
 
6.0%
부강면 14
 
6.0%
연기면 13
 
5.6%
전동면 13
 
5.6%
소정면 11
 
4.7%
연동면 11
 
4.7%
Other values (14) 58
24.8%

긴급구조 리명
Text

MISSING 

Distinct77
Distinct (%)44.3%
Missing60
Missing (%)25.6%
Memory size2.0 KiB
2023-12-12T15:41:55.414011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9482759
Min length2

Characters and Unicode

Total characters513
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)19.5%

Sample

1st row운당리
2nd row용포리
3rd row부강리
4th row신방리
5th row부강리
ValueCountFrequency (%)
봉암리 7
 
4.0%
운당리 7
 
4.0%
부강리 7
 
4.0%
동교리 6
 
3.4%
두만리 6
 
3.4%
죽림리 5
 
2.9%
산울리 5
 
2.9%
용담리 5
 
2.9%
세종리 5
 
2.9%
하봉리 5
 
2.9%
Other values (67) 116
66.7%
2023-12-12T15:41:55.781992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 174
33.9%
봉 19
 
3.7%
용 17
 
3.3%
암 17
 
3.3%
산 16
 
3.1%
곡 11
 
2.1%
신 10
 
1.9%
강 9
 
1.8%
교 8
 
1.6%
하 8
 
1.6%
Other values (77) 224
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 513
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 174
33.9%
봉 19
 
3.7%
용 17
 
3.3%
암 17
 
3.3%
산 16
 
3.1%
곡 11
 
2.1%
신 10
 
1.9%
강 9
 
1.8%
교 8
 
1.6%
하 8
 
1.6%
Other values (77) 224
43.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 513
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 174
33.9%
봉 19
 
3.7%
용 17
 
3.3%
암 17
 
3.3%
산 16
 
3.1%
곡 11
 
2.1%
신 10
 
1.9%
강 9
 
1.8%
교 8
 
1.6%
하 8
 
1.6%
Other values (77) 224
43.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 513
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 174
33.9%
봉 19
 
3.7%
용 17
 
3.3%
암 17
 
3.3%
산 16
 
3.1%
곡 11
 
2.1%
신 10
 
1.9%
강 9
 
1.8%
교 8
 
1.6%
하 8
 
1.6%
Other values (77) 224
43.7%

긴급구조 종별명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
화재
234 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화재 234
100.0%

Length

2023-12-12T15:41:55.900969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:41:55.988008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화재 234
100.0%

긴급구조 분류명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
일반화재(차량)
234 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반화재(차량)
2nd row일반화재(차량)
3rd row일반화재(차량)
4th row일반화재(차량)
5th row일반화재(차량)

Common Values

ValueCountFrequency (%)
일반화재(차량) 234
100.0%

Length

2023-12-12T15:41:56.068863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:41:56.145217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반화재(차량 234
100.0%

긴급구조 규모명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
1차출동
234 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1차출동
2nd row1차출동
3rd row1차출동
4th row1차출동
5th row1차출동

Common Values

ValueCountFrequency (%)
1차출동 234
100.0%

Length

2023-12-12T15:41:56.229203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:41:56.326167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1차출동 234
100.0%

상황종료일시
Date

Distinct226
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2012-07-21 00:00:00
Maximum2021-09-11 00:00:00
2023-12-12T15:41:56.431201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:41:56.839581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상황종료일시(상세)
Date

Distinct233
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2023-12-12 00:11:28
Maximum2023-12-12 23:45:40
2023-12-12T15:41:56.989810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:41:57.210873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관할서명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
조치원소방서
124 
세종소방서
75 
세종소방본부
31 
<NA>
 
4

Length

Max length6
Median length6
Mean length5.6452991
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
조치원소방서 124
53.0%
세종소방서 75
32.1%
세종소방본부 31
 
13.2%
<NA> 4
 
1.7%

Length

2023-12-12T15:41:57.357146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:41:57.500787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조치원소방서 124
53.0%
세종소방서 75
32.1%
세종소방본부 31
 
13.2%
na 4
 
1.7%

서센터명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
조치원119안전센터
41 
보람119안전센터
36 
한솔119안전센터
34 
전의119안전센터
33 
아름119안전센터
32 
Other values (7)
58 

Length

Max length10
Median length9
Mean length9.1239316
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전의119안전센터
2nd row조치원119구조대
3rd row부강119안전센터
4th row전의119안전센터
5th row부강119안전센터

Common Values

ValueCountFrequency (%)
조치원119안전센터 41
17.5%
보람119안전센터 36
15.4%
한솔119안전센터 34
14.5%
전의119안전센터 33
14.1%
아름119안전센터 32
13.7%
부강119안전센터 25
10.7%
연서119안전센터 10
 
4.3%
첫마을119안전센터 8
 
3.4%
조치원119구조대 7
 
3.0%
<NA> 4
 
1.7%
Other values (2) 4
 
1.7%

Length

2023-12-12T15:41:57.668790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조치원119안전센터 41
17.5%
보람119안전센터 36
15.4%
한솔119안전센터 34
14.5%
전의119안전센터 33
14.1%
아름119안전센터 32
13.7%
부강119안전센터 25
10.7%
연서119안전센터 10
 
4.3%
첫마을119안전센터 8
 
3.4%
조치원119구조대 7
 
3.0%
na 4
 
1.7%
Other values (2) 4
 
1.7%

도로명
Text

MISSING 

Distinct37
Distinct (%)77.1%
Missing186
Missing (%)79.5%
Memory size2.0 KiB
2023-12-12T15:41:57.952350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.8958333
Min length3

Characters and Unicode

Total characters187
Distinct characters75
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

Unique28 ?
Unique (%)58.3%

Sample

1st row신송로
2nd row조치원로
3rd row갈매로
4th row운주산로
5th row운당양촌불당골길
ValueCountFrequency (%)
당산로 3
 
6.2%
운당양촌불당골길 3
 
6.2%
조치원로 2
 
4.2%
신송로 2
 
4.2%
용연로 2
 
4.2%
청연로 2
 
4.2%
세종로 2
 
4.2%
갈운2길 2
 
4.2%
달빛로 2
 
4.2%
무넘이길 1
 
2.1%
Other values (27) 27
56.2%
2023-12-12T15:41:58.394401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 29
 
15.5%
길 19
 
10.2%
당 10
 
5.3%
운 6
 
3.2%
산 6
 
3.2%
2 5
 
2.7%
연 5
 
2.7%
용 4
 
2.1%
골 4
 
2.1%
부 4
 
2.1%
Other values (65) 95
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 176
94.1%
Decimal Number 11
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 29
 
16.5%
길 19
 
10.8%
당 10
 
5.7%
운 6
 
3.4%
산 6
 
3.4%
연 5
 
2.8%
용 4
 
2.3%
골 4
 
2.3%
부 4
 
2.3%
갈 3
 
1.7%
Other values (61) 86
48.9%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
1 3
27.3%
3 2
 
18.2%
6 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 176
94.1%
Common 11
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 29
 
16.5%
길 19
 
10.8%
당 10
 
5.7%
운 6
 
3.4%
산 6
 
3.4%
연 5
 
2.8%
용 4
 
2.3%
골 4
 
2.3%
부 4
 
2.3%
갈 3
 
1.7%
Other values (61) 86
48.9%
Common
ValueCountFrequency (%)
2 5
45.5%
1 3
27.3%
3 2
 
18.2%
6 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 176
94.1%
ASCII 11
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 29
 
16.5%
길 19
 
10.8%
당 10
 
5.7%
운 6
 
3.4%
산 6
 
3.4%
연 5
 
2.8%
용 4
 
2.3%
골 4
 
2.3%
부 4
 
2.3%
갈 3
 
1.7%
Other values (61) 86
48.9%
ASCII
ValueCountFrequency (%)
2 5
45.5%
1 3
27.3%
3 2
 
18.2%
6 1
 
9.1%

Interactions

2023-12-12T15:41:52.535955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:41:52.293115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:41:52.652590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:41:52.428851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:41:58.506677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호접수경로명타시도신고여부긴급구조 우편번호긴급구조 동명긴급구조 리명관할서명서센터명도로명
일련번호1.0000.0000.0000.9850.3670.6120.6900.5210.889
접수경로명0.0001.0000.5390.2780.0000.0000.1280.0000.000
타시도신고여부0.0000.5391.0000.0000.0000.6050.0000.000NaN
긴급구조 우편번호0.9850.2780.0001.0000.0000.3150.2180.664NaN
긴급구조 동명0.3670.0000.0000.0001.0001.0000.9160.9251.000
긴급구조 리명0.6120.0000.6050.3151.0001.0000.8530.9530.995
관할서명0.6900.1280.0000.2180.9160.8531.0000.8791.000
서센터명0.5210.0000.0000.6640.9250.9530.8791.0000.959
도로명0.8890.000NaNNaN1.0000.9951.0000.9591.000
2023-12-12T15:41:58.675084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할서명접수경로명서센터명타시도신고여부긴급구조 동명
관할서명1.0000.1200.7860.0000.673
접수경로명0.1201.0000.0000.3660.000
서센터명0.7860.0001.0000.0000.645
타시도신고여부0.0000.3660.0001.0000.000
긴급구조 동명0.6730.0000.6450.0001.000
2023-12-12T15:41:58.813762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호긴급구조 우편번호접수경로명타시도신고여부긴급구조 동명관할서명서센터명
일련번호1.0000.3090.0000.0000.1370.5370.251
긴급구조 우편번호0.3091.0000.2320.0000.0000.3660.621
접수경로명0.0000.2321.0000.3660.0000.1200.000
타시도신고여부0.0000.0000.3661.0000.0000.0000.000
긴급구조 동명0.1370.0000.0000.0001.0000.6730.645
관할서명0.5370.3660.1200.0000.6731.0000.786
서센터명0.2510.6210.0000.0000.6450.7861.000

Missing values

2023-12-12T15:41:52.781294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:41:53.049278image/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.
2023-12-12T15:41:53.224858image/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

일련번호접수경로명접수일시접수일시(상세)타시도신고여부긴급구조 우편번호긴급구조 동명긴급구조 리명긴급구조 종별명긴급구조 분류명긴급구조 규모명상황종료일시상황종료일시(상세)관할서명서센터명도로명
01기타2012-09-0521:10:15아니오71148소정면운당리화재일반화재(차량)1차출동2012-09-0522:28:29조치원소방서전의119안전센터<NA>
12일반전화2012-07-2023:22:05아니오71105금남면용포리화재일반화재(차량)1차출동2012-07-213:00:21조치원소방서조치원119구조대<NA>
23기타2012-08-0212:05:00아니오71007부강면부강리화재일반화재(차량)1차출동2012-08-0213:14:35조치원소방서부강119안전센터<NA>
34이동전화2012-08-1618:18:01아니오<NA>전의면신방리화재일반화재(차량)1차출동2012-08-1619:45:59조치원소방서전의119안전센터<NA>
45이동전화2012-07-2617:42:37아니오71022부강면부강리화재일반화재(차량)1차출동2012-07-2619:26:23조치원소방서부강119안전센터<NA>
56이동전화2012-08-260:16:38아니오71048조치원읍신흥리화재일반화재(차량)1차출동2012-08-261:25:02조치원소방서조치원119안전센터<NA>
67이동전화2012-11-080:32:48아니오71120전의면유천리화재일반화재(차량)1차출동2012-11-081:49:57조치원소방서전의119안전센터<NA>
78이동전화2012-09-2618:25:55아니오<NA>부강면금호리화재일반화재(차량)1차출동2012-09-2622:09:15조치원소방서부강119안전센터<NA>
89이동전화2012-09-1012:36:30아니오71135연동면내판리화재일반화재(차량)1차출동2012-09-1013:38:02조치원소방서부강119안전센터<NA>
910일반전화2012-10-0516:21:44예71132전의면읍내리화재일반화재(차량)1차출동2012-10-0516:53:55조치원소방서전의119안전센터<NA>
일련번호접수경로명접수일시접수일시(상세)타시도신고여부긴급구조 우편번호긴급구조 동명긴급구조 리명긴급구조 종별명긴급구조 분류명긴급구조 규모명상황종료일시상황종료일시(상세)관할서명서센터명도로명
224243이동전화2020-08-0914:15:02아니오80136전의면달전리화재일반화재(차량)1차출동2020-08-1119:29:29조치원소방서전의119안전센터윗다락골길
225244이동전화2020-08-198:46:35아니오80173장군면송문리화재일반화재(차량)1차출동2020-08-2114:43:56세종소방서장군119안전센터<NA>
226246이동전화2021-03-2620:18:08아니오80005가람동<NA>화재일반화재(차량)1차출동2021-03-3018:10:29세종소방서한솔119안전센터<NA>
227248이동전화2021-07-016:12:47아니오80014소담동<NA>화재일반화재(차량)1차출동2021-07-0221:03:21세종소방서보람119안전센터<NA>
228249이동전화2021-02-072:32:59아니오80158소정면고등리화재일반화재(차량)1차출동2021-02-0815:26:50조치원소방서전의119안전센터<NA>
229250이동전화2021-02-2015:21:16아니오80011반곡동<NA>화재일반화재(차량)1차출동2021-02-2216:52:50세종소방서보람119안전센터<NA>
230251이동전화2021-01-098:59:03아니오80106금남면발산리화재일반화재(차량)1차출동2021-01-1117:26:03세종소방서보람119안전센터<NA>
231252이동전화2021-03-0712:44:13아니오80063조치원읍신흥리화재일반화재(차량)1차출동2021-03-0918:00:17조치원소방서조치원119안전센터<NA>
232253일반전화2021-03-0213:50:49아니오80165조치원읍죽림리화재일반화재(차량)1차출동2021-03-0310:38:57조치원소방서조치원119안전센터<NA>
233254이동전화2020-08-2913:42:14아니오80058조치원읍남리화재일반화재(차량)1차출동2020-09-0117:53:31조치원소방서조치원119안전센터<NA>