Overview

Dataset statistics

Number of variables4
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory37.3 B

Variable types

Numeric1
Text1
Categorical2

Dataset

Description광주광역시 남부소방서 관내 소방시설업체 현황- 상세내용: 관내 소방시설업체(시설업,관리업,점검업,공사업) 상호, 업종, 분야 등 정보 데이터 제공
Author광주광역시
URLhttps://www.data.go.kr/data/15052636/fileData.do

Alerts

연번 is highly overall correlated with 업종 and 1 other fieldsHigh correlation
업종 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
분야 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:40:56.925507
Analysis finished2023-12-12 10:40:57.348125
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  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
2023-12-12T19:40:57.417872image/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
2023-12-12T19:40:57.587682image/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%

상호
Text

Distinct27
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:40:57.836878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length9.1612903
Min length5

Characters and Unicode

Total characters284
Distinct characters81
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)74.2%

Sample

1st row대하산업개발(주)
2nd row(주)유림
3rd row주식회사 승진일렉콤
4th row(주)성신전력
5th row(주)서경이엔엘
ValueCountFrequency (%)
주식회사 14
28.6%
화성 2
 
4.1%
주)상현이앤지 2
 
4.1%
덕양소방 2
 
4.1%
호남소방 2
 
4.1%
엔지니어링 2
 
4.1%
유)빛고을엔지니어링 1
 
2.0%
케이엠로지스 1
 
2.0%
동광전기 1
 
2.0%
오션이앤지 1
 
2.0%
Other values (21) 21
42.9%
2023-12-12T19:40:58.250013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 24
 
8.5%
사 18
 
6.3%
18
 
6.3%
회 15
 
5.3%
식 14
 
4.9%
지 11
 
3.9%
( 11
 
3.9%
) 11
 
3.9%
방 10
 
3.5%
소 10
 
3.5%
Other values (71) 142
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
85.6%
Space Separator 18
 
6.3%
Open Punctuation 11
 
3.9%
Close Punctuation 11
 
3.9%
Other Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 24
 
9.9%
사 18
 
7.4%
회 15
 
6.2%
식 14
 
5.8%
지 11
 
4.5%
방 10
 
4.1%
소 10
 
4.1%
이 10
 
4.1%
엔 7
 
2.9%
전 6
 
2.5%
Other values (67) 118
48.6%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 244
85.9%
Common 40
 
14.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 24
 
9.8%
사 18
 
7.4%
회 15
 
6.1%
식 14
 
5.7%
지 11
 
4.5%
방 10
 
4.1%
소 10
 
4.1%
이 10
 
4.1%
엔 7
 
2.9%
전 6
 
2.5%
Other values (68) 119
48.8%
Common
ValueCountFrequency (%)
18
45.0%
( 11
27.5%
) 11
27.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
85.6%
ASCII 40
 
14.1%
None 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 24
 
9.9%
사 18
 
7.4%
회 15
 
6.2%
식 14
 
5.8%
지 11
 
4.5%
방 10
 
4.1%
소 10
 
4.1%
이 10
 
4.1%
엔 7
 
2.9%
전 6
 
2.5%
Other values (67) 118
48.6%
ASCII
ValueCountFrequency (%)
18
45.0%
( 11
27.5%
) 11
27.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업종
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
공사업
20 
설계업
4 
관리업
4 
감리업
 
2
방염업
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
공사업 20
64.5%
설계업 4
 
12.9%
관리업 4
 
12.9%
감리업 2
 
6.5%
방염업 1
 
3.2%

Length

2023-12-12T19:40:58.423822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:58.565783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공사업 20
64.5%
설계업 4
 
12.9%
관리업 4
 
12.9%
감리업 2
 
6.5%
방염업 1
 
3.2%

분야
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
전문
21 
기계,전기
4 
<NA>
4 
전기
 
1
합판목재류
 
1

Length

Max length5
Median length2
Mean length2.7419355
Min length2

Unique

Unique2 ?
Unique (%)6.5%

Sample

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

Common Values

ValueCountFrequency (%)
전문 21
67.7%
기계,전기 4
 
12.9%
<NA> 4
 
12.9%
전기 1
 
3.2%
합판목재류 1
 
3.2%

Length

2023-12-12T19:40:58.724331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:58.873768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문 21
67.7%
기계,전기 4
 
12.9%
na 4
 
12.9%
전기 1
 
3.2%
합판목재류 1
 
3.2%

Interactions

2023-12-12T19:40:57.096789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:40:58.963396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호업종분야
연번1.0000.7370.9700.469
상호0.7371.0000.4950.556
업종0.9700.4951.0000.971
분야0.4690.5560.9711.000
2023-12-12T19:40:59.058559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종분야
업종1.0000.769
분야0.7691.000
2023-12-12T19:40:59.170934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종분야
연번1.0000.5190.509
업종0.5191.0000.769
분야0.5090.7691.000

Missing values

2023-12-12T19:40:57.220741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:40:57.311003image/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

연번상호업종분야
01대하산업개발(주)공사업전문
12(주)유림공사업전문
23주식회사 승진일렉콤공사업전문
34(주)성신전력공사업전문
45(주)서경이엔엘공사업전문
56(주)시온이엔지공사업전문
67(주)국제소방공사공사업전문
78(주)지엠이앤씨공사업전문
89(주)상현이앤지공사업전문
910주식회사 라인산업공사업전문
연번상호업종분야
2122(주)전원기술단설계업전기
2223(유)빛고을엔지니어링설계업기계,전기
2324화성 엔지니어링설계업기계,전기
2425진성이앤씨감리업기계,전기
2526주식회사 미드엔지니어링건축사사무소감리업전문
2627인트로 방재산업방염업합판목재류
2728㈜국제소방안전점검관리업<NA>
2829주식회사 국민안전소방관리업<NA>
2930주식회사 덕양소방관리업<NA>
3031호남소방 주식회사관리업<NA>