Overview

Dataset statistics

Number of variables3
Number of observations31
Missing cells3
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory938.0 B
Average record size in memory30.3 B

Variable types

Numeric2
Text1

Dataset

Description광주광역시 서부소방서에서 보유하고있는 수난구조장비 보유현황의 장비명, 수량 등의 데이터 파일을 제공하고 표시합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15071678/fileData.do

Alerts

계 has 3 (9.7%) missing valuesMissing
연번 has unique valuesUnique
장비명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:42:30.930890
Analysis finished2023-12-12 05:42:31.586497
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T14:42:31.664640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2023-12-12T14:42:31.784510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

장비명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T14:42:31.993688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.3870968
Min length6

Characters and Unicode

Total characters291
Distinct characters92
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

Unique31 ?
Unique (%)100.0%

Sample

1st row급류구조자켓(01)
2nd row급류구조용 헬멧(05)
3rd row드로우백(06)
4th row스쿠버 공기통(01)
5th row다이브컴퓨터(02)
ValueCountFrequency (%)
급류구조자켓(01 1
 
2.8%
급류구조용 1
 
2.8%
잠수장비(15 1
 
2.8%
수중리프트백(16 1
 
2.8%
마커부이(17 1
 
2.8%
긴급잠수장비(18 1
 
2.8%
수중통신장비(19 1
 
2.8%
구명조끼(01 1
 
2.8%
구명부환(02 1
 
2.8%
수난구조용튜브(03 1
 
2.8%
Other values (26) 26
72.2%
2023-12-12T14:42:32.293534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 31
 
10.7%
) 31
 
10.7%
0 22
 
7.6%
수 16
 
5.5%
1 15
 
5.2%
조 8
 
2.7%
구 7
 
2.4%
잠 6
 
2.1%
중 5
 
1.7%
용 5
 
1.7%
Other values (82) 145
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
55.7%
Decimal Number 62
 
21.3%
Open Punctuation 31
 
10.7%
Close Punctuation 31
 
10.7%
Space Separator 5
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 16
 
9.9%
조 8
 
4.9%
구 7
 
4.3%
잠 6
 
3.7%
중 5
 
3.1%
용 5
 
3.1%
기 5
 
3.1%
장 5
 
3.1%
스 4
 
2.5%
트 4
 
2.5%
Other values (69) 97
59.9%
Decimal Number
ValueCountFrequency (%)
0 22
35.5%
1 15
24.2%
3 4
 
6.5%
4 4
 
6.5%
5 4
 
6.5%
2 4
 
6.5%
6 3
 
4.8%
9 2
 
3.2%
8 2
 
3.2%
7 2
 
3.2%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
55.7%
Common 129
44.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 16
 
9.9%
조 8
 
4.9%
구 7
 
4.3%
잠 6
 
3.7%
중 5
 
3.1%
용 5
 
3.1%
기 5
 
3.1%
장 5
 
3.1%
스 4
 
2.5%
트 4
 
2.5%
Other values (69) 97
59.9%
Common
ValueCountFrequency (%)
( 31
24.0%
) 31
24.0%
0 22
17.1%
1 15
11.6%
5
 
3.9%
3 4
 
3.1%
4 4
 
3.1%
5 4
 
3.1%
2 4
 
3.1%
6 3
 
2.3%
Other values (3) 6
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
55.7%
ASCII 129
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 31
24.0%
) 31
24.0%
0 22
17.1%
1 15
11.6%
5
 
3.9%
3 4
 
3.1%
4 4
 
3.1%
5 4
 
3.1%
2 4
 
3.1%
6 3
 
2.3%
Other values (3) 6
 
4.7%
Hangul
ValueCountFrequency (%)
수 16
 
9.9%
조 8
 
4.9%
구 7
 
4.3%
잠 6
 
3.7%
중 5
 
3.1%
용 5
 
3.1%
기 5
 
3.1%
장 5
 
3.1%
스 4
 
2.5%
트 4
 
2.5%
Other values (69) 97
59.9%

계
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)53.6%
Missing3
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean8
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T14:42:32.396915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.75
median5.5
Q39.25
95-th percentile19.65
Maximum40
Range39
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation8.1876149
Coefficient of variation (CV)1.0234519
Kurtosis8.0457504
Mean8
Median Absolute Deviation (MAD)3.5
Skewness2.514926
Sum224
Variance67.037037
MonotonicityNot monotonic
2023-12-12T14:42:32.496214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 4
12.9%
8 4
12.9%
5 3
9.7%
4 3
9.7%
1 3
9.7%
10 2
 
6.5%
3 1
 
3.2%
19 1
 
3.2%
40 1
 
3.2%
9 1
 
3.2%
Other values (5) 5
16.1%
(Missing) 3
9.7%
ValueCountFrequency (%)
1 3
9.7%
2 4
12.9%
3 1
 
3.2%
4 3
9.7%
5 3
9.7%
6 1
 
3.2%
7 1
 
3.2%
8 4
12.9%
9 1
 
3.2%
10 2
6.5%
ValueCountFrequency (%)
40 1
 
3.2%
20 1
 
3.2%
19 1
 
3.2%
18 1
 
3.2%
12 1
 
3.2%
10 2
6.5%
9 1
 
3.2%
8 4
12.9%
7 1
 
3.2%
6 1
 
3.2%

Interactions

2023-12-12T14:42:31.233260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:42:31.035629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:42:31.332944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:42:31.135176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:42:32.563595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번장비명계
연번1.0001.0000.472
장비명1.0001.0001.000
계0.4721.0001.000
2023-12-12T14:42:32.629615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번계
연번1.000-0.361
계-0.3611.000

Missing values

2023-12-12T14:42:31.461317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:42:31.553728image/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

연번장비명계
01급류구조자켓(01)5
12급류구조용 헬멧(05)2
23드로우백(06)5
34스쿠버 공기통(01)3
45다이브컴퓨터(02)<NA>
56잠수호흡기세트(03)19
67부력조절기(04)4
78스킨핀(05)40
89스쿠버핀(06)10
910중량밸트(07)9
연번장비명계
2122수중통신장비(19)4
2223구명조끼(01)1
2324구명부환(02)<NA>
2425수난구조용튜브(03)18
2526수난구조용 로프(04)2
2627수심측정기(05)2
2728수난용 들것(01)5
2829선외기(02)1
2930수난구조용서프보드(03)<NA>
3031분리형장대세트(04)1