Overview

Dataset statistics

Number of variables5
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory44.5 B

Variable types

Numeric1
Categorical3
Text1

Dataset

Description이 파일은 대구광역시 소방안전본부 소속 8개 소방서에 배치된 구긥차 수를 나타낸 자료이며 대구소방본부는 구급대 운영으로 모든 구급차는 구급대 소속으로 자료에 표시된 배치 센터는 실제 구급차가 배치된 119안전센터입니다.
Author대구광역시
URLhttps://www.data.go.kr/data/15112361/fileData.do

Alerts

부서 has constant value ""Constant
연번 is highly overall correlated with 소방서High correlation
소방서 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
배치센터 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:05:15.035441
Analysis finished2023-12-12 08:05:15.529143
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T17:05:15.610294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2023-12-12T17:05:15.754122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

소방서
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size548.0 B
서부
8 
수성
8 
중부
7 
동부
7 
북부
7 
Other values (3)
15 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서부 8
15.4%
수성 8
15.4%
중부 7
13.5%
동부 7
13.5%
북부 7
13.5%
달서 6
11.5%
달성 5
9.6%
강서 4
7.7%

Length

2023-12-12T17:05:15.929625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:05:16.103246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서부 8
15.4%
수성 8
15.4%
중부 7
13.5%
동부 7
13.5%
북부 7
13.5%
달서 6
11.5%
달성 5
9.6%
강서 4
7.7%

부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
119구급대
52 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row119구급대
2nd row119구급대
3rd row119구급대
4th row119구급대
5th row119구급대

Common Values

ValueCountFrequency (%)
119구급대 52
100.0%

Length

2023-12-12T17:05:16.274273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:05:16.421273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
119구급대 52
100.0%

배치센터
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T17:05:16.730692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0961538
Min length2

Characters and Unicode

Total characters109
Distinct characters68
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

Unique52 ?
Unique (%)100.0%

Sample

1st row남산
2nd row서문로
3rd row봉덕
4th row삼덕
5th row대명
ValueCountFrequency (%)
남산 1
 
1.9%
서문로 1
 
1.9%
월서 1
 
1.9%
복현지역대 1
 
1.9%
범물 1
 
1.9%
만촌 1
 
1.9%
황금 1
 
1.9%
상동 1
 
1.9%
수성 1
 
1.9%
고산 1
 
1.9%
Other values (42) 42
80.8%
2023-12-12T17:05:17.277821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 6
 
5.5%
현 5
 
4.6%
성 5
 
4.6%
대 4
 
3.7%
덕 3
 
2.8%
동 3
 
2.8%
천 3
 
2.8%
명 3
 
2.8%
원 3
 
2.8%
로 3
 
2.8%
Other values (58) 71
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 6
 
5.5%
현 5
 
4.6%
성 5
 
4.6%
대 4
 
3.7%
덕 3
 
2.8%
동 3
 
2.8%
천 3
 
2.8%
명 3
 
2.8%
원 3
 
2.8%
로 3
 
2.8%
Other values (58) 71
65.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 6
 
5.5%
현 5
 
4.6%
성 5
 
4.6%
대 4
 
3.7%
덕 3
 
2.8%
동 3
 
2.8%
천 3
 
2.8%
명 3
 
2.8%
원 3
 
2.8%
로 3
 
2.8%
Other values (58) 71
65.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 6
 
5.5%
현 5
 
4.6%
성 5
 
4.6%
대 4
 
3.7%
덕 3
 
2.8%
동 3
 
2.8%
천 3
 
2.8%
명 3
 
2.8%
원 3
 
2.8%
로 3
 
2.8%
Other values (58) 71
65.1%

대수
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
1
45 
2
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 45
86.5%
2 7
 
13.5%

Length

2023-12-12T17:05:17.470533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:05:17.617055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 45
86.5%
2 7
 
13.5%

Interactions

2023-12-12T17:05:15.210479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:05:17.694571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소방서배치센터대수
연번1.0000.9201.0000.000
소방서0.9201.0001.0000.000
배치센터1.0001.0001.0001.000
대수0.0000.0001.0001.000
2023-12-12T17:05:17.821484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소방서대수
소방서1.0000.000
대수0.0001.000
2023-12-12T17:05:17.947195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소방서대수
연번1.0000.7510.000
소방서0.7511.0000.000
대수0.0000.0001.000

Missing values

2023-12-12T17:05:15.352916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:05:15.487779image/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

연번소방서부서배치센터대수
01중부119구급대남산2
12중부119구급대서문로1
23중부119구급대봉덕1
34중부119구급대삼덕1
45중부119구급대대명1
56중부119구급대명덕1
67중부119구급대성명1
78동부119구급대신천2
89동부119구급대동촌1
910동부119구급대안심1
연번소방서부서배치센터대수
4243달서119구급대죽전1
4344달성119구급대현풍2
4445달성119구급대논공1
4546달성119구급대화원1
4647달성119구급대구지1
4748달성119구급대옥포1
4849강서119구급대다사2
4950강서119구급대성서1
5051강서119구급대대천1
5152강서119구급대매곡1