Overview

Dataset statistics

Number of variables10
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory93.3 B

Variable types

Numeric2
Text1
Categorical7

Dataset

Description예금보험공사 층별 소화설비 보유 현황에 대한 데이터로, 층별 소화기 세부항목 및 대수, 층별 소화전 대수, 층별 기타 소화설비 종류에 관하여 제공합니다.
Author예금보험공사
URLhttps://www.data.go.kr/data/15126817/fileData.do

Alerts

소화전 is highly overall correlated with 일반 분말 소화기 and 2 other fieldsHigh correlation
주방용 소화기 is highly overall correlated with 일반 분말 소화기 and 5 other fieldsHigh correlation
기타 소화설비 is highly overall correlated with 일반 분말 소화기 and 5 other fieldsHigh correlation
할론 소화기 is highly overall correlated with 일반 분말 소화기 and 4 other fieldsHigh correlation
자동확산 소화기 is highly overall correlated with 주방용 소화기 and 1 other fieldsHigh correlation
청정 소화기 is highly overall correlated with 일반 분말 소화기 and 5 other fieldsHigh correlation
일반 분말 소화기 is highly overall correlated with 대형 분말 소화기 and 5 other fieldsHigh correlation
대형 분말 소화기 is highly overall correlated with 일반 분말 소화기 and 3 other fieldsHigh correlation
할론 소화기 is highly imbalanced (58.6%)Imbalance
청정 소화기 is highly imbalanced (62.9%)Imbalance
자동확산 소화기 is highly imbalanced (75.0%)Imbalance
주방용 소화기 is highly imbalanced (68.6%)Imbalance
소화전 is highly imbalanced (75.0%)Imbalance
연번 has unique valuesUnique
설비위치 has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:16:46.021124
Analysis finished2024-03-14 14:16:48.746364
Duration2.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T23:16:48.921465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2024-03-14T23:16:49.311130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

설비위치
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T23:16:49.883214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1666667
Min length2

Characters and Unicode

Total characters76
Distinct characters16
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

Unique24 ?
Unique (%)100.0%

Sample

1st row지하 6층
2nd row지하 5층
3rd row지하 4층
4th row지하 3층
5th row지하 2층
ValueCountFrequency (%)
지하 6
20.0%
3층 2
 
6.7%
2층 2
 
6.7%
1층 2
 
6.7%
6층 2
 
6.7%
13층 1
 
3.3%
19층 1
 
3.3%
18층 1
 
3.3%
17층 1
 
3.3%
16층 1
 
3.3%
Other values (11) 11
36.7%
2024-03-14T23:16:50.877962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
층 23
30.3%
1 13
17.1%
지 6
 
7.9%
하 6
 
7.9%
6
 
7.9%
6 3
 
3.9%
3 3
 
3.9%
2 3
 
3.9%
5 2
 
2.6%
4 2
 
2.6%
Other values (6) 9
 
11.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37
48.7%
Decimal Number 33
43.4%
Space Separator 6
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
39.4%
6 3
 
9.1%
3 3
 
9.1%
2 3
 
9.1%
5 2
 
6.1%
4 2
 
6.1%
7 2
 
6.1%
8 2
 
6.1%
9 2
 
6.1%
0 1
 
3.0%
Other Letter
ValueCountFrequency (%)
층 23
62.2%
지 6
 
16.2%
하 6
 
16.2%
옥 1
 
2.7%
상 1
 
2.7%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39
51.3%
Hangul 37
48.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
33.3%
6
15.4%
6 3
 
7.7%
3 3
 
7.7%
2 3
 
7.7%
5 2
 
5.1%
4 2
 
5.1%
7 2
 
5.1%
8 2
 
5.1%
9 2
 
5.1%
Hangul
ValueCountFrequency (%)
층 23
62.2%
지 6
 
16.2%
하 6
 
16.2%
옥 1
 
2.7%
상 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
51.3%
Hangul 37
48.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
층 23
62.2%
지 6
 
16.2%
하 6
 
16.2%
옥 1
 
2.7%
상 1
 
2.7%
ASCII
ValueCountFrequency (%)
1 13
33.3%
6
15.4%
6 3
 
7.7%
3 3
 
7.7%
2 3
 
7.7%
5 2
 
5.1%
4 2
 
5.1%
7 2
 
5.1%
8 2
 
5.1%
9 2
 
5.1%

일반 분말 소화기
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.2916667
Minimum3
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T23:16:51.231252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q14
median6
Q38
95-th percentile16.95
Maximum22
Range19
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.6107546
Coefficient of variation (CV)0.63233206
Kurtosis4.2823259
Mean7.2916667
Median Absolute Deviation (MAD)2
Skewness2.0287317
Sum175
Variance21.259058
MonotonicityNot monotonic
2024-03-14T23:16:51.604044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 7
29.2%
11 3
12.5%
6 3
12.5%
8 3
12.5%
5 3
12.5%
7 2
 
8.3%
18 1
 
4.2%
22 1
 
4.2%
3 1
 
4.2%
ValueCountFrequency (%)
3 1
 
4.2%
4 7
29.2%
5 3
12.5%
6 3
12.5%
7 2
 
8.3%
8 3
12.5%
11 3
12.5%
18 1
 
4.2%
22 1
 
4.2%
ValueCountFrequency (%)
22 1
 
4.2%
18 1
 
4.2%
11 3
12.5%
8 3
12.5%
7 2
 
8.3%
6 3
12.5%
5 3
12.5%
4 7
29.2%
3 1
 
4.2%

대형 분말 소화기
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size320.0 B
0
19 
1
4 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 19
79.2%
1 4
 
16.7%
3 1
 
4.2%

Length

2024-03-14T23:16:52.009589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:52.313191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 19
79.2%
1 4
 
16.7%
3 1
 
4.2%

할론 소화기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size320.0 B
0
22 
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22
91.7%
2 2
 
8.3%

Length

2024-03-14T23:16:52.654225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:52.967829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 22
91.7%
2 2
 
8.3%

청정 소화기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size320.0 B
0
21 
4
 
1
3
 
1
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)12.5%

Sample

1st row4
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21
87.5%
4 1
 
4.2%
3 1
 
4.2%
1 1
 
4.2%

Length

2024-03-14T23:16:53.285409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:53.595339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
87.5%
4 1
 
4.2%
3 1
 
4.2%
1 1
 
4.2%

자동확산 소화기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size320.0 B
0
23 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 23
95.8%
2 1
 
4.2%

Length

2024-03-14T23:16:53.860010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:54.021190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
95.8%
2 1
 
4.2%

주방용 소화기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size320.0 B
0
22 
3
 
1
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)8.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 22
91.7%
3 1
 
4.2%
1 1
 
4.2%

Length

2024-03-14T23:16:54.188053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:54.351194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 22
91.7%
3 1
 
4.2%
1 1
 
4.2%

소화전
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size320.0 B
2
23 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
2 23
95.8%
4 1
 
4.2%

Length

2024-03-14T23:16:54.526793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:54.685579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 23
95.8%
4 1
 
4.2%

기타 소화설비
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size320.0 B
스프링쿨러
18 
할로겐 화합물, 스프링쿨러
4 
이산화탄소, 할로겐 화합물, 스프링쿨러
 
1
간이소화용구, 이산화탄소, 스프링쿨러
 
1

Length

Max length21
Median length5
Mean length7.7916667
Min length5

Unique

Unique2 ?
Unique (%)8.3%

Sample

1st row이산화탄소, 할로겐 화합물, 스프링쿨러
2nd row스프링쿨러
3rd row스프링쿨러
4th row스프링쿨러
5th row스프링쿨러

Common Values

ValueCountFrequency (%)
스프링쿨러 18
75.0%
할로겐 화합물, 스프링쿨러 4
 
16.7%
이산화탄소, 할로겐 화합물, 스프링쿨러 1
 
4.2%
간이소화용구, 이산화탄소, 스프링쿨러 1
 
4.2%

Length

2024-03-14T23:16:54.964386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:55.162849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
스프링쿨러 24
64.9%
할로겐 5
 
13.5%
화합물 5
 
13.5%
이산화탄소 2
 
5.4%
간이소화용구 1
 
2.7%

Interactions

2024-03-14T23:16:47.237377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:46.739373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:47.487934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:46.976925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:16:55.302596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비위치일반 분말 소화기대형 분말 소화기할론 소화기청정 소화기자동확산 소화기주방용 소화기소화전기타 소화설비
연번1.0001.0000.0000.7160.0000.0000.0000.2530.5270.000
설비위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
일반 분말 소화기0.0001.0001.0000.9451.0000.9090.4820.9571.0000.775
대형 분말 소화기0.7161.0000.9451.0000.4220.6410.0000.0000.0000.654
할론 소화기0.0001.0001.0000.4221.0001.0000.0000.4200.3740.911
청정 소화기0.0001.0000.9090.6411.0001.0000.0000.6351.0000.926
자동확산 소화기0.0001.0000.4820.0000.0000.0001.0001.0000.0001.000
주방용 소화기0.2531.0000.9570.0000.4200.6351.0001.0001.0000.705
소화전0.5271.0001.0000.0000.3741.0000.0001.0001.0000.480
기타 소화설비0.0001.0000.7750.6540.9110.9261.0000.7050.4801.000
2024-03-14T23:16:55.525813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소화전주방용 소화기기타 소화설비할론 소화기대형 분말 소화기자동확산 소화기청정 소화기
소화전1.0000.9770.3020.2410.0000.0000.953
주방용 소화기0.9771.0000.7230.6400.0000.9770.638
기타 소화설비0.3020.7231.0000.6940.6610.9530.638
할론 소화기0.2410.6400.6941.0000.6440.0000.953
대형 분말 소화기0.0000.0000.6610.6441.0000.0000.645
자동확산 소화기0.0000.9770.9530.0000.0001.0000.000
청정 소화기0.9530.6380.6380.9530.6450.0001.000
2024-03-14T23:16:55.723697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번일반 분말 소화기대형 분말 소화기할론 소화기청정 소화기자동확산 소화기주방용 소화기소화전기타 소화설비
연번1.000-0.3540.4590.0000.0000.0000.0000.3020.000
일반 분말 소화기-0.3541.0000.6600.9050.7520.3020.6900.9050.580
대형 분말 소화기0.4590.6601.0000.6440.6450.0000.0000.0000.661
할론 소화기0.0000.9050.6441.0000.9530.0000.6400.2410.694
청정 소화기0.0000.7520.6450.9531.0000.0000.6380.9530.638
자동확산 소화기0.0000.3020.0000.0000.0001.0000.9770.0000.953
주방용 소화기0.0000.6900.0000.6400.6380.9771.0000.9770.723
소화전0.3020.9050.0000.2410.9530.0000.9771.0000.302
기타 소화설비0.0000.5800.6610.6940.6380.9530.7230.3021.000

Missing values

2024-03-14T23:16:48.085397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:16:48.559331image/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

연번설비위치일반 분말 소화기대형 분말 소화기할론 소화기청정 소화기자동확산 소화기주방용 소화기소화전기타 소화설비
01지하 6층18324002이산화탄소, 할로겐 화합물, 스프링쿨러
12지하 5층4100002스프링쿨러
23지하 4층4100002스프링쿨러
34지하 3층4100002스프링쿨러
45지하 2층11100002스프링쿨러
56지하 1층22023034할로겐 화합물, 스프링쿨러
671층11000002스프링쿨러
782층11000212간이소화용구, 이산화탄소, 스프링쿨러
893층6000002스프링쿨러
9106층8000002스프링쿨러
연번설비위치일반 분말 소화기대형 분말 소화기할론 소화기청정 소화기자동확산 소화기주방용 소화기소화전기타 소화설비
141511층6001002할로겐 화합물, 스프링쿨러
151612층7000002할로겐 화합물, 스프링쿨러
161713층4000002스프링쿨러
171814층4000002스프링쿨러
181915층8000002스프링쿨러
192016층4000002스프링쿨러
202117층5000002스프링쿨러
212218층5000002스프링쿨러
222319층6000002스프링쿨러
2324옥상3000002할로겐 화합물, 스프링쿨러