Overview

Dataset statistics

Number of variables6
Number of observations510
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.5 KiB
Average record size in memory49.3 B

Variable types

Numeric1
Categorical4
Text1

Dataset

Description소방시설업(공사업,관리업,설계업,방염업) : 소방시설을 설치하고자 할 때 설계,공사,감리 등 업체현황소방시설관리업 : 자체점검(종합정밀점검, 작동기능점검)을 대행하는 업체 현황
Author대구광역시
URLhttps://www.data.go.kr/data/15125360/fileData.do

Alerts

지역 has constant value ""Constant
업종 is highly overall correlated with 분야High correlation
분야 is highly overall correlated with 업종High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:38:55.999945
Analysis finished2023-12-12 17:38:56.647463
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct510
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean255.5
Minimum1
Maximum510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T02:38:56.746037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.45
Q1128.25
median255.5
Q3382.75
95-th percentile484.55
Maximum510
Range509
Interquartile range (IQR)254.5

Descriptive statistics

Standard deviation147.36859
Coefficient of variation (CV)0.57678507
Kurtosis-1.2
Mean255.5
Median Absolute Deviation (MAD)127.5
Skewness0
Sum130305
Variance21717.5
MonotonicityStrictly increasing
2023-12-13T02:38:56.929229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
337 1
 
0.2%
350 1
 
0.2%
349 1
 
0.2%
348 1
 
0.2%
347 1
 
0.2%
346 1
 
0.2%
345 1
 
0.2%
344 1
 
0.2%
343 1
 
0.2%
Other values (500) 500
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
510 1
0.2%
509 1
0.2%
508 1
0.2%
507 1
0.2%
506 1
0.2%
505 1
0.2%
504 1
0.2%
503 1
0.2%
502 1
0.2%
501 1
0.2%

지역
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
대구
510 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구 510
100.0%

Length

2023-12-13T02:38:57.046513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:38:57.425015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구 510
100.0%

세부지역
Categorical

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
수성구
103 
북구
93 
달서구
93 
동구
67 
서구
46 
Other values (5)
108 

Length

Max length4
Median length2
Mean length2.4686275
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row동구
2nd row수성구
3rd row수성구
4th row수성구
5th row수성구

Common Values

ValueCountFrequency (%)
수성구 103
20.2%
북구 93
18.2%
달서구 93
18.2%
동구 67
13.1%
서구 46
9.0%
달성군 36
 
7.1%
중구 33
 
6.5%
남구 33
 
6.5%
군위군 5
 
1.0%
<NA> 1
 
0.2%

Length

2023-12-13T02:38:57.552661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:38:57.747362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수성구 103
20.2%
북구 93
18.2%
달서구 93
18.2%
동구 67
13.1%
서구 46
9.0%
달성군 36
 
7.1%
중구 33
 
6.5%
남구 33
 
6.5%
군위군 5
 
1.0%
na 1
 
0.2%

상호
Text

Distinct412
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T02:38:58.051949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length8.2235294
Min length3

Characters and Unicode

Total characters4194
Distinct characters227
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)69.2%

Sample

1st row(자)대한소방
2nd row화성산업(주)
3rd row(주)서한
4th row(합자)세명소방
5th row(주)경일소방
ValueCountFrequency (%)
주식회사 134
 
20.6%
다온이엔지 5
 
0.8%
세이프소방방재 5
 
0.8%
주)새솔enc 4
 
0.6%
주)가람기술단 4
 
0.6%
지이에스 4
 
0.6%
주)제일소방방재 4
 
0.6%
대영소방기술(주 4
 
0.6%
주)덕원기술사 4
 
0.6%
주)한양이엔씨 4
 
0.6%
Other values (408) 479
73.6%
2023-12-13T02:38:58.516241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 425
 
10.1%
) 293
 
7.0%
( 293
 
7.0%
사 162
 
3.9%
141
 
3.4%
회 140
 
3.3%
식 135
 
3.2%
이 130
 
3.1%
방 126
 
3.0%
엔 112
 
2.7%
Other values (217) 2237
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3410
81.3%
Close Punctuation 293
 
7.0%
Open Punctuation 293
 
7.0%
Space Separator 141
 
3.4%
Uppercase Letter 43
 
1.0%
Decimal Number 12
 
0.3%
Lowercase Letter 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 425
 
12.5%
사 162
 
4.8%
회 140
 
4.1%
식 135
 
4.0%
이 130
 
3.8%
방 126
 
3.7%
엔 112
 
3.3%
지 100
 
2.9%
소 95
 
2.8%
전 91
 
2.7%
Other values (204) 1894
55.5%
Uppercase Letter
ValueCountFrequency (%)
E 14
32.6%
N 12
27.9%
G 9
20.9%
C 6
14.0%
A 1
 
2.3%
I 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 8
66.7%
9 4
33.3%
Close Punctuation
ValueCountFrequency (%)
) 293
100.0%
Open Punctuation
ValueCountFrequency (%)
( 293
100.0%
Space Separator
ValueCountFrequency (%)
141
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3410
81.3%
Common 740
 
17.6%
Latin 44
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 425
 
12.5%
사 162
 
4.8%
회 140
 
4.1%
식 135
 
4.0%
이 130
 
3.8%
방 126
 
3.7%
엔 112
 
3.3%
지 100
 
2.9%
소 95
 
2.8%
전 91
 
2.7%
Other values (204) 1894
55.5%
Latin
ValueCountFrequency (%)
E 14
31.8%
N 12
27.3%
G 9
20.5%
C 6
13.6%
A 1
 
2.3%
n 1
 
2.3%
I 1
 
2.3%
Common
ValueCountFrequency (%)
) 293
39.6%
( 293
39.6%
141
19.1%
1 8
 
1.1%
9 4
 
0.5%
. 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3410
81.3%
ASCII 784
 
18.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 425
 
12.5%
사 162
 
4.8%
회 140
 
4.1%
식 135
 
4.0%
이 130
 
3.8%
방 126
 
3.7%
엔 112
 
3.3%
지 100
 
2.9%
소 95
 
2.8%
전 91
 
2.7%
Other values (204) 1894
55.5%
ASCII
ValueCountFrequency (%)
) 293
37.4%
( 293
37.4%
141
18.0%
E 14
 
1.8%
N 12
 
1.5%
G 9
 
1.1%
1 8
 
1.0%
C 6
 
0.8%
9 4
 
0.5%
A 1
 
0.1%
Other values (3) 3
 
0.4%

업종
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
공사업
308 
설계업
90 
감리업
62 
방염업
50 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공사업 308
60.4%
설계업 90
 
17.6%
감리업 62
 
12.2%
방염업 50
 
9.8%

Length

2023-12-13T02:38:58.711580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:38:58.865238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공사업 308
60.4%
설계업 90
 
17.6%
감리업 62
 
12.2%
방염업 50
 
9.8%

분야
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
전문
315 
일반(기계)
76 
일반(전기)
69 
합판목재류
 
26
섬유류
 
15

Length

Max length6
Median length2
Mean length3.372549
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전문 315
61.8%
일반(기계) 76
 
14.9%
일반(전기) 69
 
13.5%
합판목재류 26
 
5.1%
섬유류 15
 
2.9%
합성수지류 9
 
1.8%

Length

2023-12-13T02:38:59.084242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:38:59.253412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문 315
61.8%
일반(기계 76
 
14.9%
일반(전기 69
 
13.5%
합판목재류 26
 
5.1%
섬유류 15
 
2.9%
합성수지류 9
 
1.8%

Interactions

2023-12-13T02:38:56.334839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:38:59.339039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번세부지역업종분야
순번1.0000.3260.5320.373
세부지역0.3261.0000.2380.263
업종0.5320.2381.0000.875
분야0.3730.2630.8751.000
2023-12-13T02:38:59.447293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종분야세부지역
업종1.0000.7470.154
분야0.7471.0000.133
세부지역0.1540.1331.000
2023-12-13T02:38:59.562140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번세부지역업종분야
순번1.0000.1540.3450.206
세부지역0.1541.0000.1540.133
업종0.3450.1541.0000.747
분야0.2060.1330.7471.000

Missing values

2023-12-13T02:38:56.477981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:38:56.604746image/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

순번지역세부지역상호업종분야
01대구동구(자)대한소방공사업전문
12대구수성구화성산업(주)공사업전문
23대구수성구(주)서한공사업전문
34대구수성구(합자)세명소방공사업전문
45대구수성구(주)경일소방공사업전문
56대구서구(주)합동소방설비공사업전문
67대구수성구(주)라산전공공사업전문
78대구수성구(주)삼진씨앤씨공사업전문
89대구북구(주)우방공사업전문
910대구수성구주식회사 남영전설공사업전문
순번지역세부지역상호업종분야
500501대구수성구이에스설비 주식회사설계업일반(기계)
501502대구수성구이에스설비 주식회사설계업일반(전기)
502503대구서구주식회사 대현소방공사업전문
503504대구달서구주식회사 태림전력공사업전문
504505대구수성구주식회사 가야산업개발공사업일반(기계)
505506대구수성구주식회사 이응공사업전문
506507대구중구새솔이엔지설계업일반(기계)
507508대구북구주식회사 아승이엔지공사업전문
508509대구동구주식회사 풍림건설공사업전문
509510대구서구창문애아트블라인드방염업합판목재류