Overview

Dataset statistics

Number of variables14
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory124.0 B

Variable types

Categorical8
Text2
Numeric4

Dataset

Description제주특별자치도 소방서세부현황에 대한 데이터로 소방서의 관할구역 세대수, 인구수, 펌프/물탱크 등 차량보유 대수와 같은 세부 현황 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15056013/fileData.do

Alerts

담당부서 has constant value ""Constant
데이터기준일자 has constant value ""Constant
관할구역 세대수 is highly overall correlated with 관할구역 인구수High correlation
관할구역 인구수 is highly overall correlated with 관할구역 세대수High correlation
관할면적(제곱킬로미터) is highly overall correlated with 기타차 and 2 other fieldsHigh correlation
기타차 is highly overall correlated with 관할면적(제곱킬로미터) and 1 other fieldsHigh correlation
소속 is highly overall correlated with 관할구역 읍면동수High correlation
관할구역 읍면동수 is highly overall correlated with 관할면적(제곱킬로미터) and 2 other fieldsHigh correlation
펌프차 is highly overall correlated with 물탱크차 and 1 other fieldsHigh correlation
물탱크차 is highly overall correlated with 관할면적(제곱킬로미터) and 2 other fieldsHigh correlation
구급차 is highly overall correlated with 기타차 and 1 other fieldsHigh correlation
관할구역 세대수 has 4 (12.1%) zerosZeros
관할구역 인구수 has 4 (12.1%) zerosZeros
기타차 has 9 (27.3%) zerosZeros

Reproduction

Analysis started2023-12-12 16:13:20.805176
Analysis finished2023-12-12 16:13:23.773620
Duration2.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소속
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
제주소방서
12 
서부소방서
8 
동부소방서
7 
서귀포소방서
6 

Length

Max length6
Median length5
Mean length5.1818182
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주소방서 12
36.4%
서부소방서 8
24.2%
동부소방서 7
21.2%
서귀포소방서 6
18.2%

Length

2023-12-13T01:13:23.851365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:13:23.980213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주소방서 12
36.4%
서부소방서 8
24.2%
동부소방서 7
21.2%
서귀포소방서 6
18.2%

구분
Text

Distinct28
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T01:13:24.186320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.3333333
Min length2

Characters and Unicode

Total characters77
Distinct characters50
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

Unique26 ?
Unique (%)78.8%

Sample

1st row본서
2nd row이도
3rd row삼도
4th row오라
5th row연동
ValueCountFrequency (%)
구조대 4
 
12.1%
본서 4
 
12.1%
효돈 1
 
3.0%
중문 1
 
3.0%
남원 1
 
3.0%
조천 1
 
3.0%
구좌 1
 
3.0%
성산 1
 
3.0%
영어교육도시 1
 
3.0%
안덕 1
 
3.0%
Other values (17) 17
51.5%
2023-12-13T01:13:24.597888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 6
 
7.8%
구 5
 
6.5%
조 5
 
6.5%
본 4
 
5.2%
서 4
 
5.2%
도 4
 
5.2%
3
 
3.9%
동 2
 
2.6%
라 2
 
2.6%
한 2
 
2.6%
Other values (40) 40
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
96.1%
Space Separator 3
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 6
 
8.1%
구 5
 
6.8%
조 5
 
6.8%
본 4
 
5.4%
서 4
 
5.4%
도 4
 
5.4%
동 2
 
2.7%
라 2
 
2.7%
한 2
 
2.7%
시 1
 
1.4%
Other values (39) 39
52.7%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74
96.1%
Common 3
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 6
 
8.1%
구 5
 
6.8%
조 5
 
6.8%
본 4
 
5.4%
서 4
 
5.4%
도 4
 
5.4%
동 2
 
2.7%
라 2
 
2.7%
한 2
 
2.7%
시 1
 
1.4%
Other values (39) 39
52.7%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74
96.1%
ASCII 3
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 6
 
8.1%
구 5
 
6.8%
조 5
 
6.8%
본 4
 
5.4%
서 4
 
5.4%
도 4
 
5.4%
동 2
 
2.7%
라 2
 
2.7%
한 2
 
2.7%
시 1
 
1.4%
Other values (39) 39
52.7%
ASCII
ValueCountFrequency (%)
3
100.0%

관할구역 세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18748.848
Minimum0
Maximum167763
Zeros4
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T01:13:24.781791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15731
median11882
Q321308
95-th percentile48901.6
Maximum167763
Range167763
Interquartile range (IQR)15577

Descriptive statistics

Standard deviation29737.546
Coefficient of variation (CV)1.5860998
Kurtosis20.609077
Mean18748.848
Median Absolute Deviation (MAD)7068
Skewness4.2107654
Sum618712
Variance8.8432162 × 108
MonotonicityNot monotonic
2023-12-13T01:13:25.029498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 4
 
12.1%
167763 1
 
3.0%
4932 1
 
3.0%
6294 1
 
3.0%
8811 1
 
3.0%
11882 1
 
3.0%
7994 1
 
3.0%
8228 1
 
3.0%
43209 1
 
3.0%
4415 1
 
3.0%
Other values (20) 20
60.6%
ValueCountFrequency (%)
0 4
12.1%
947 1
 
3.0%
4415 1
 
3.0%
4537 1
 
3.0%
4932 1
 
3.0%
5731 1
 
3.0%
6294 1
 
3.0%
7527 1
 
3.0%
7975 1
 
3.0%
7994 1
 
3.0%
ValueCountFrequency (%)
167763 1
3.0%
50194 1
3.0%
48040 1
3.0%
43209 1
3.0%
29339 1
3.0%
23618 1
3.0%
21811 1
3.0%
21635 1
3.0%
21308 1
3.0%
18950 1
3.0%

관할구역 인구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41730.606
Minimum0
Maximum390609
Zeros4
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T01:13:25.175189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111129
median25788
Q344277
95-th percentile104118.6
Maximum390609
Range390609
Interquartile range (IQR)33148

Descriptive statistics

Standard deviation68694.732
Coefficient of variation (CV)1.6461475
Kurtosis21.878673
Mean41730.606
Median Absolute Deviation (MAD)16553
Skewness4.3596974
Sum1377110
Variance4.7189662 × 109
MonotonicityNot monotonic
2023-12-13T01:13:25.323432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 4
 
12.1%
30669 2
 
6.1%
390609 1
 
3.0%
102627 1
 
3.0%
12913 1
 
3.0%
19137 1
 
3.0%
25788 1
 
3.0%
15381 1
 
3.0%
16776 1
 
3.0%
89995 1
 
3.0%
Other values (19) 19
57.6%
ValueCountFrequency (%)
0 4
12.1%
1586 1
 
3.0%
8380 1
 
3.0%
9235 1
 
3.0%
10807 1
 
3.0%
11129 1
 
3.0%
12913 1
 
3.0%
15152 1
 
3.0%
15381 1
 
3.0%
16672 1
 
3.0%
ValueCountFrequency (%)
390609 1
3.0%
106356 1
3.0%
102627 1
3.0%
89995 1
3.0%
66296 1
3.0%
57493 1
3.0%
54277 1
3.0%
49068 1
3.0%
44277 1
3.0%
43945 1
3.0%

관할구역 읍면동수
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Memory size396.0 B
3개동
6 
1읍
5 
2개동
4 
19개동+1면
2 
1개동
2 
Other values (10)
14 

Length

Max length10
Median length7
Mean length4.0606061
Min length2

Unique

Unique6 ?
Unique (%)18.2%

Sample

1st row19개동+1면
2nd row3개동
3rd row3개동
4th row2개동
5th row1개동

Common Values

ValueCountFrequency (%)
3개동 6
18.2%
1읍 5
15.2%
2개동 4
12.1%
19개동+1면 2
 
6.1%
1개동 2
 
6.1%
12개동 2
 
6.1%
3읍+2면 2
 
6.1%
1면(1개리 제외) 2
 
6.1%
4읍+2면 2
 
6.1%
1개면 1
 
3.0%
Other values (5) 5
15.2%

Length

2023-12-13T01:13:25.488743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3개동 6
16.7%
1읍 5
13.9%
2개동 4
11.1%
제외 3
8.3%
19개동+1면 2
 
5.6%
1개동 2
 
5.6%
12개동 2
 
5.6%
3읍+2면 2
 
5.6%
1면(1개리 2
 
5.6%
4읍+2면 2
 
5.6%
Other values (6) 6
16.7%

관할면적(제곱킬로미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.03061
Minimum5.03
Maximum774.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T01:13:25.631878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.03
5-th percentile6.824
Q144.86
median91.09
Q3202.16
95-th percentile643.614
Maximum774.27
Range769.24
Interquartile range (IQR)157.3

Descriptive statistics

Standard deviation207.4104
Coefficient of variation (CV)1.2343608
Kurtosis3.2490886
Mean168.03061
Median Absolute Deviation (MAD)61.48
Skewness1.9583915
Sum5545.01
Variance43019.074
MonotonicityNot monotonic
2023-12-13T01:13:25.782086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
262.54 2
 
6.1%
556.51 2
 
6.1%
774.27 2
 
6.1%
254.89 2
 
6.1%
135.17 1
 
3.0%
189.08 1
 
3.0%
150.68 1
 
3.0%
192.11 1
 
3.0%
107.61 1
 
3.0%
44.86 1
 
3.0%
Other values (19) 19
57.6%
ValueCountFrequency (%)
5.03 1
3.0%
6.38 1
3.0%
7.12 1
3.0%
12.33 1
3.0%
14.98 1
3.0%
29.61 1
3.0%
30.19 1
3.0%
34.93 1
3.0%
44.86 1
3.0%
45.2 1
3.0%
ValueCountFrequency (%)
774.27 2
6.1%
556.51 2
6.1%
262.54 2
6.1%
254.89 2
6.1%
202.16 1
3.0%
192.11 1
3.0%
189.08 1
3.0%
150.68 1
3.0%
135.17 1
3.0%
107.61 1
3.0%

관할구역 읍면동 상세
Text

Distinct26
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T01:13:25.985488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length31
Mean length9.1515152
Min length2

Characters and Unicode

Total characters302
Distinct characters84
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row해당없음
2nd row이도1동+이도2동+아라동(오등동)
3rd row삼도2동+용담1동+용담2동
4th row오라동+삼도1동
5th row연동
ValueCountFrequency (%)
해당없음 8
21.1%
제외 4
 
10.5%
예례동+중문동 1
 
2.6%
남원읍 1
 
2.6%
조천읍 1
 
2.6%
구좌읍+우도면 1
 
2.6%
성산읍 1
 
2.6%
대정읍(구억리+보성리+신평리+안성리+인성리)+안덕면(서광서리)+한경면(청수리 1
 
2.6%
안덕면(서광서리 1
 
2.6%
한경면(청수리 1
 
2.6%
Other values (18) 18
47.4%
2023-12-13T01:13:26.322487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 39
 
12.9%
+ 29
 
9.6%
( 11
 
3.6%
리 11
 
3.6%
) 11
 
3.6%
도 9
 
3.0%
해 8
 
2.6%
읍 8
 
2.6%
면 8
 
2.6%
당 8
 
2.6%
Other values (74) 160
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
78.8%
Math Symbol 29
 
9.6%
Open Punctuation 11
 
3.6%
Close Punctuation 11
 
3.6%
Decimal Number 8
 
2.6%
Space Separator 5
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 39
 
16.4%
리 11
 
4.6%
도 9
 
3.8%
해 8
 
3.4%
읍 8
 
3.4%
면 8
 
3.4%
당 8
 
3.4%
음 8
 
3.4%
없 8
 
3.4%
외 6
 
2.5%
Other values (68) 125
52.5%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%
Math Symbol
ValueCountFrequency (%)
+ 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 238
78.8%
Common 64
 
21.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 39
 
16.4%
리 11
 
4.6%
도 9
 
3.8%
해 8
 
3.4%
읍 8
 
3.4%
면 8
 
3.4%
당 8
 
3.4%
음 8
 
3.4%
없 8
 
3.4%
외 6
 
2.5%
Other values (68) 125
52.5%
Common
ValueCountFrequency (%)
+ 29
45.3%
( 11
 
17.2%
) 11
 
17.2%
5
 
7.8%
2 4
 
6.2%
1 4
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
78.8%
ASCII 64
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 39
 
16.4%
리 11
 
4.6%
도 9
 
3.8%
해 8
 
3.4%
읍 8
 
3.4%
면 8
 
3.4%
당 8
 
3.4%
음 8
 
3.4%
없 8
 
3.4%
외 6
 
2.5%
Other values (68) 125
52.5%
ASCII
ValueCountFrequency (%)
+ 29
45.3%
( 11
 
17.2%
) 11
 
17.2%
5
 
7.8%
2 4
 
6.2%
1 4
 
6.2%

펌프차
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
1
17 
0
8 
2
4 
3
2 
4
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row3
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 17
51.5%
0 8
24.2%
2 4
 
12.1%
3 2
 
6.1%
4 2
 
6.1%

Length

2023-12-13T01:13:26.470871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:13:26.585470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 17
51.5%
0 8
24.2%
2 4
 
12.1%
3 2
 
6.1%
4 2
 
6.1%

물탱크차
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
1
22 
0
10 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 22
66.7%
0 10
30.3%
2 1
 
3.0%

Length

2023-12-13T01:13:26.696688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:13:26.830260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
66.7%
0 10
30.3%
2 1
 
3.0%

사다리차
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
0
23 
1
9 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23
69.7%
1 9
 
27.3%
2 1
 
3.0%

Length

2023-12-13T01:13:26.942848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:13:27.050407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
69.7%
1 9
 
27.3%
2 1
 
3.0%

구급차
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
1
22 
2
6 
0
4 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row1
2nd row2
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 22
66.7%
2 6
 
18.2%
0 4
 
12.1%
3 1
 
3.0%

Length

2023-12-13T01:13:27.172443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:13:27.291837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
66.7%
2 6
 
18.2%
0 4
 
12.1%
3 1
 
3.0%

기타차
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6363636
Minimum0
Maximum16
Zeros9
Zeros (%)27.3%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T01:13:27.400831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile10.4
Maximum16
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.8634358
Coefficient of variation (CV)1.4654412
Kurtosis3.8414867
Mean2.6363636
Median Absolute Deviation (MAD)1
Skewness2.0217393
Sum87
Variance14.926136
MonotonicityNot monotonic
2023-12-13T01:13:27.521237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 14
42.4%
0 9
27.3%
6 2
 
6.1%
5 2
 
6.1%
16 1
 
3.0%
11 1
 
3.0%
9 1
 
3.0%
2 1
 
3.0%
10 1
 
3.0%
3 1
 
3.0%
ValueCountFrequency (%)
0 9
27.3%
1 14
42.4%
2 1
 
3.0%
3 1
 
3.0%
5 2
 
6.1%
6 2
 
6.1%
9 1
 
3.0%
10 1
 
3.0%
11 1
 
3.0%
16 1
 
3.0%
ValueCountFrequency (%)
16 1
 
3.0%
11 1
 
3.0%
10 1
 
3.0%
9 1
 
3.0%
6 2
 
6.1%
5 2
 
6.1%
3 1
 
3.0%
2 1
 
3.0%
1 14
42.4%
0 9
27.3%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
소방정책과
33 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소방정책과 33
100.0%

Length

2023-12-13T01:13:27.674667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:13:27.821357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소방정책과 33
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2022-12-31
33 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 33
100.0%

Length

2023-12-13T01:13:27.934564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:13:28.039871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 33
100.0%

Interactions

2023-12-13T01:13:22.786524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:21.424005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:21.826763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:22.296781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:22.883861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:21.516256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:21.930308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:22.429362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:23.233441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:21.620285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:22.032031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:22.581411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:23.330931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:21.726967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:22.148129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:22.685324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:13:28.126266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소속구분관할구역 세대수관할구역 인구수관할구역 읍면동수관할면적(제곱킬로미터)관할구역 읍면동 상세펌프차물탱크차사다리차구급차기타차
소속1.0000.0000.0000.3810.8880.6460.0000.0000.0000.1710.0000.000
구분0.0001.0000.0000.0000.4080.0001.0001.0001.0001.0001.0000.000
관할구역 세대수0.0000.0001.0000.9990.5480.4910.0000.3460.3030.4150.0000.913
관할구역 인구수0.3810.0000.9991.0000.6530.5230.0000.3330.2960.3390.0000.910
관할구역 읍면동수0.8880.4080.5480.6531.0000.9580.7590.8940.9980.0000.7440.531
관할면적(제곱킬로미터)0.6460.0000.4910.5230.9581.0000.0000.5920.8750.0000.5910.881
관할구역 읍면동 상세0.0001.0000.0000.0000.7590.0001.0001.0001.0001.0000.0000.000
펌프차0.0001.0000.3460.3330.8940.5921.0001.0000.5980.3340.6240.599
물탱크차0.0001.0000.3030.2960.9980.8751.0000.5981.0000.0000.4010.823
사다리차0.1711.0000.4150.3390.0000.0001.0000.3340.0001.0000.2280.766
구급차0.0001.0000.0000.0000.7440.5910.0000.6240.4010.2281.0000.755
기타차0.0000.0000.9130.9100.5310.8810.0000.5990.8230.7660.7551.000
2023-12-13T01:13:28.302584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
물탱크차소속펌프차관할구역 읍면동수구급차사다리차
물탱크차1.0000.0000.5290.7320.3820.000
소속0.0001.0000.0000.5780.0000.150
펌프차0.5290.0001.0000.4730.5400.251
관할구역 읍면동수0.7320.5780.4731.0000.4050.000
구급차0.3820.0000.5400.4051.0000.207
사다리차0.0000.1500.2510.0000.2071.000
2023-12-13T01:13:28.462515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할구역 세대수관할구역 인구수관할면적(제곱킬로미터)기타차소속관할구역 읍면동수펌프차물탱크차사다리차구급차
관할구역 세대수1.0000.992-0.123-0.0470.0000.2450.2770.2810.3970.000
관할구역 인구수0.9921.000-0.119-0.0360.1460.3240.2650.2750.3180.000
관할면적(제곱킬로미터)-0.123-0.1191.0000.6910.4540.6760.4390.5470.0000.402
기타차-0.047-0.0360.6911.0000.0000.1950.4460.4790.4170.570
소속0.0000.1460.4540.0001.0000.5780.0000.0000.1500.000
관할구역 읍면동수0.2450.3240.6760.1950.5781.0000.4730.7320.0000.405
펌프차0.2770.2650.4390.4460.0000.4731.0000.5290.2510.540
물탱크차0.2810.2750.5470.4790.0000.7320.5291.0000.0000.382
사다리차0.3970.3180.0000.4170.1500.0000.2510.0001.0000.207
구급차0.0000.0000.4020.5700.0000.4050.5400.3820.2071.000

Missing values

2023-12-13T01:13:23.460707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:13:23.693248image/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

소속구분관할구역 세대수관할구역 인구수관할구역 읍면동수관할면적(제곱킬로미터)관할구역 읍면동 상세펌프차물탱크차사다리차구급차기타차담당부서데이터기준일자
0제주소방서본서16776339060919개동+1면262.54해당없음000116소방정책과2022-12-31
1제주소방서이도29339662963개동30.19이도1동+이도2동+아라동(오등동)31121소방정책과2022-12-31
2제주소방서삼도14005296293개동6.38삼도2동+용담1동+용담2동11010소방정책과2022-12-31
3제주소방서오라12385297042개동29.61오라동+삼도1동11010소방정책과2022-12-31
4제주소방서연동21811439451개동12.33연동11010소방정책과2022-12-31
5제주소방서항만18950442773개동5.03일도1동+일도2동+건입동+추자면10111소방정책과2022-12-31
6제주소방서추자94715861개면7.12추자면20011소방정책과2022-12-31
7제주소방서화북21308542773개동54.05화북동+삼양동+봉개동(용강동 제외)11110소방정책과2022-12-31
8제주소방서노형23618574931개동45.2노형동11110소방정책과2022-12-31
9제주소방서외도12391306693개동14.98이호동+외도동+도두동11011소방정책과2022-12-31
소속구분관할구역 세대수관할구역 인구수관할구역 읍면동수관할면적(제곱킬로미터)관할구역 읍면동 상세펌프차물탱크차사다리차구급차기타차담당부서데이터기준일자
23서부소방서안덕5731111291면(1개리 제외)98.7안덕면(서광서리 제외)11011소방정책과2022-12-31
24서부소방서영어교육도시441592357개리44.86대정읍(구억리+보성리+신평리+안성리+인성리)+안덕면(서광서리)+한경면(청수리)11011소방정책과2022-12-31
25서부소방서구조대003읍+2면556.51해당없음00006소방정책과2022-12-31
26동부소방서본서43209899954읍+2면774.27해당없음000110소방정책과2022-12-31
27동부소방서성산8228167761읍107.61성산읍21223소방정책과2022-12-31
28동부소방서구좌7994153811읍+1면192.11구좌읍+우도면41031소방정책과2022-12-31
29동부소방서조천11882257881읍150.68조천읍21011소방정책과2022-12-31
30동부소방서남원8811191371읍189.08남원읍11011소방정책과2022-12-31
31동부소방서표선6294129131면135.17표선면12021소방정책과2022-12-31
32동부소방서구조대004읍+2면774.27해당없음00005소방정책과2022-12-31