Overview

Dataset statistics

Number of variables6
Number of observations159
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.7 KiB
Average record size in memory49.8 B

Variable types

Numeric1
Text3
Categorical1
DateTime1

Dataset

Description대구광역시 남구 관내 전문건설업 등록현황에 대한 데이터로 업체명, 업종, 주소, 전화번호에 대한 정보를 제공합니다.
Author대구광역시 남구
URLhttps://www.data.go.kr/data/15126652/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:00:00.287937
Analysis finished2024-03-14 15:00:01.281615
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80
Minimum1
Maximum159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-15T00:00:01.500101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.9
Q140.5
median80
Q3119.5
95-th percentile151.1
Maximum159
Range158
Interquartile range (IQR)79

Descriptive statistics

Standard deviation46.043458
Coefficient of variation (CV)0.57554322
Kurtosis-1.2
Mean80
Median Absolute Deviation (MAD)40
Skewness0
Sum12720
Variance2120
MonotonicityStrictly increasing
2024-03-15T00:00:01.984497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
2 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
Other values (149) 149
93.7%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
159 1
0.6%
158 1
0.6%
157 1
0.6%
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%

업체명
Text

Distinct158
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T00:00:03.060335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.754717
Min length4

Characters and Unicode

Total characters1074
Distinct characters165
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)98.7%

Sample

1st row(주)가인건설디자인
2nd row(주)강산씨앤씨
3rd row(주)광양건설
4th row(주)국제피스코
5th row(주)노수테크
ValueCountFrequency (%)
우진설비 2
 
1.3%
신천기전 1
 
0.6%
신택건설(주 1
 
0.6%
안동설비 1
 
0.6%
세현설비 1
 
0.6%
센스튜디오 1
 
0.6%
수성설비 1
 
0.6%
승백건설(주 1
 
0.6%
신아건설(주 1
 
0.6%
엘지종합건축 1
 
0.6%
Other values (148) 148
93.1%
2024-03-15T00:00:04.540813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 95
 
8.8%
설 70
 
6.5%
( 64
 
6.0%
) 64
 
6.0%
비 45
 
4.2%
건 45
 
4.2%
사 36
 
3.4%
식 29
 
2.7%
회 27
 
2.5%
이 21
 
2.0%
Other values (155) 578
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 934
87.0%
Open Punctuation 64
 
6.0%
Close Punctuation 64
 
6.0%
Uppercase Letter 9
 
0.8%
Decimal Number 2
 
0.2%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 95
 
10.2%
설 70
 
7.5%
비 45
 
4.8%
건 45
 
4.8%
사 36
 
3.9%
식 29
 
3.1%
회 27
 
2.9%
이 21
 
2.2%
디 19
 
2.0%
성 17
 
1.8%
Other values (147) 530
56.7%
Uppercase Letter
ValueCountFrequency (%)
E 3
33.3%
N 3
33.3%
G 3
33.3%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 935
87.1%
Common 130
 
12.1%
Latin 9
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 95
 
10.2%
설 70
 
7.5%
비 45
 
4.8%
건 45
 
4.8%
사 36
 
3.9%
식 29
 
3.1%
회 27
 
2.9%
이 21
 
2.2%
디 19
 
2.0%
성 17
 
1.8%
Other values (148) 531
56.8%
Common
ValueCountFrequency (%)
( 64
49.2%
) 64
49.2%
4 1
 
0.8%
2 1
 
0.8%
Latin
ValueCountFrequency (%)
E 3
33.3%
N 3
33.3%
G 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 934
87.0%
ASCII 139
 
12.9%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 95
 
10.2%
설 70
 
7.5%
비 45
 
4.8%
건 45
 
4.8%
사 36
 
3.9%
식 29
 
3.1%
회 27
 
2.9%
이 21
 
2.2%
디 19
 
2.0%
성 17
 
1.8%
Other values (147) 530
56.7%
ASCII
ValueCountFrequency (%)
( 64
46.0%
) 64
46.0%
E 3
 
2.2%
N 3
 
2.2%
G 3
 
2.2%
4 1
 
0.7%
2 1
 
0.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업종
Categorical

Distinct34
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
가스ㆍ난방공사업
66 
실내건축공사업
20 
기계설비ㆍ가스공사업
13 
도장ㆍ습식ㆍ방수ㆍ석공사업
9 
실내건축공사업
 
6
Other values (29)
45 

Length

Max length45
Median length40
Mean length11.672956
Min length7

Unique

Unique21 ?
Unique (%)13.2%

Sample

1st row실내건축공사업 금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업
2nd row조경식재ㆍ시설물공사업 철근ㆍ콘크리트공사업
3rd row지반조성ㆍ포장공사업
4th row상ㆍ하수도설비공사업
5th row기계설비ㆍ가스공사업

Common Values

ValueCountFrequency (%)
가스ㆍ난방공사업 66
41.5%
실내건축공사업 20
 
12.6%
기계설비ㆍ가스공사업 13
 
8.2%
도장ㆍ습식ㆍ방수ㆍ석공사업 9
 
5.7%
실내건축공사업 6
 
3.8%
지반조성ㆍ포장공사업 5
 
3.1%
상ㆍ하수도설비공사업 4
 
2.5%
상ㆍ하수도설비공사업 3
 
1.9%
철근ㆍ콘크리트공사업 3
 
1.9%
금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 3
 
1.9%
Other values (24) 27
17.0%

Length

2024-03-15T00:00:05.038950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가스ㆍ난방공사업 66
36.5%
실내건축공사업 32
17.7%
기계설비ㆍ가스공사업 15
 
8.3%
도장ㆍ습식ㆍ방수ㆍ석공사업 14
 
7.7%
지반조성ㆍ포장공사업 14
 
7.7%
상ㆍ하수도설비공사업 12
 
6.6%
철근ㆍ콘크리트공사업 11
 
6.1%
금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 10
 
5.5%
조경식재ㆍ시설물공사업 3
 
1.7%
구조물해체ㆍ비계공사업 2
 
1.1%
Other values (2) 2
 
1.1%

도로명주소
Text

Distinct157
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T00:00:06.356009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length25.465409
Min length18

Characters and Unicode

Total characters4049
Distinct characters96
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

Unique155 ?
Unique (%)97.5%

Sample

1st row대구광역시 남구 현충로 133 202호 1호실 (대명동)
2nd row대구광역시 남구 대명로36길 23-1 2층 201호 (대명동)
3rd row대구광역시 남구 장전1길 34 (대명동)
4th row대구광역시 남구 대명남로 171 (대명동)
5th row대구광역시 남구 앞산순환로 561 (대명동)
ValueCountFrequency (%)
대구광역시 159
18.2%
남구 158
18.1%
대명동 115
 
13.1%
봉덕동 27
 
3.1%
2층 17
 
1.9%
대명남로 16
 
1.8%
1층 12
 
1.4%
이천동 11
 
1.3%
성당로 10
 
1.1%
4층 7
 
0.8%
Other values (244) 343
39.2%
2024-03-15T00:00:08.033831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
716
17.7%
대 329
 
8.1%
구 319
 
7.9%
남 175
 
4.3%
시 163
 
4.0%
동 163
 
4.0%
명 161
 
4.0%
역 159
 
3.9%
광 159
 
3.9%
) 156
 
3.9%
Other values (86) 1549
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2315
57.2%
Space Separator 716
 
17.7%
Decimal Number 649
 
16.0%
Close Punctuation 156
 
3.9%
Open Punctuation 156
 
3.9%
Dash Punctuation 45
 
1.1%
Other Punctuation 11
 
0.3%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 329
14.2%
구 319
13.8%
남 175
 
7.6%
시 163
 
7.0%
동 163
 
7.0%
명 161
 
7.0%
역 159
 
6.9%
광 159
 
6.9%
로 114
 
4.9%
길 101
 
4.4%
Other values (70) 472
20.4%
Decimal Number
ValueCountFrequency (%)
1 150
23.1%
2 127
19.6%
3 72
11.1%
0 64
9.9%
4 61
9.4%
6 44
 
6.8%
5 41
 
6.3%
9 37
 
5.7%
8 27
 
4.2%
7 26
 
4.0%
Space Separator
ValueCountFrequency (%)
716
100.0%
Close Punctuation
ValueCountFrequency (%)
) 156
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2315
57.2%
Common 1733
42.8%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 329
14.2%
구 319
13.8%
남 175
 
7.6%
시 163
 
7.0%
동 163
 
7.0%
명 161
 
7.0%
역 159
 
6.9%
광 159
 
6.9%
로 114
 
4.9%
길 101
 
4.4%
Other values (70) 472
20.4%
Common
ValueCountFrequency (%)
716
41.3%
) 156
 
9.0%
( 156
 
9.0%
1 150
 
8.7%
2 127
 
7.3%
3 72
 
4.2%
0 64
 
3.7%
4 61
 
3.5%
- 45
 
2.6%
6 44
 
2.5%
Other values (5) 142
 
8.2%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2315
57.2%
ASCII 1734
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
716
41.3%
) 156
 
9.0%
( 156
 
9.0%
1 150
 
8.7%
2 127
 
7.3%
3 72
 
4.2%
0 64
 
3.7%
4 61
 
3.5%
- 45
 
2.6%
6 44
 
2.5%
Other values (6) 143
 
8.2%
Hangul
ValueCountFrequency (%)
대 329
14.2%
구 319
13.8%
남 175
 
7.6%
시 163
 
7.0%
동 163
 
7.0%
명 161
 
7.0%
역 159
 
6.9%
광 159
 
6.9%
로 114
 
4.9%
길 101
 
4.4%
Other values (70) 472
20.4%

전화번호
Text

Distinct146
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T00:00:08.969386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.943396
Min length11

Characters and Unicode

Total characters1899
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)91.2%

Sample

1st row053-286-2100
2nd row053-656-6888
3rd row070-4109-8084
4th row053-653-7958
5th row053-627-3088
ValueCountFrequency (%)
00-000-0000 14
 
8.8%
053-622-0461 1
 
0.6%
053-655-1505 1
 
0.6%
053-567-0606 1
 
0.6%
053-624-4010 1
 
0.6%
053-622-0684 1
 
0.6%
053-710-9381 1
 
0.6%
053-625-1819 1
 
0.6%
053-657-5065 1
 
0.6%
053-653-8804 1
 
0.6%
Other values (136) 136
85.5%
2024-03-15T00:00:10.331733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 364
19.2%
- 318
16.7%
5 273
14.4%
3 226
11.9%
6 164
8.6%
2 132
 
7.0%
4 104
 
5.5%
7 99
 
5.2%
8 76
 
4.0%
1 75
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1581
83.3%
Dash Punctuation 318
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 364
23.0%
5 273
17.3%
3 226
14.3%
6 164
10.4%
2 132
 
8.3%
4 104
 
6.6%
7 99
 
6.3%
8 76
 
4.8%
1 75
 
4.7%
9 68
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1899
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 364
19.2%
- 318
16.7%
5 273
14.4%
3 226
11.9%
6 164
8.6%
2 132
 
7.0%
4 104
 
5.5%
7 99
 
5.2%
8 76
 
4.0%
1 75
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 364
19.2%
- 318
16.7%
5 273
14.4%
3 226
11.9%
6 164
8.6%
2 132
 
7.0%
4 104
 
5.5%
7 99
 
5.2%
8 76
 
4.0%
1 75
 
3.9%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2024-02-08 00:00:00
Maximum2024-02-08 00:00:00
2024-03-15T00:00:10.684488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:00:10.987780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T00:00:00.667580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:00:11.208791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종
번호1.0000.593
업종0.5931.000
2024-03-15T00:00:11.428852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종
번호1.0000.232
업종0.2321.000

Missing values

2024-03-15T00:00:00.957502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:00:01.141532image/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

번호업체명업종도로명주소전화번호데이터 기준일자
01(주)가인건설디자인실내건축공사업 금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업대구광역시 남구 현충로 133 202호 1호실 (대명동)053-286-21002024-02-08
12(주)강산씨앤씨조경식재ㆍ시설물공사업 철근ㆍ콘크리트공사업대구광역시 남구 대명로36길 23-1 2층 201호 (대명동)053-656-68882024-02-08
23(주)광양건설지반조성ㆍ포장공사업대구광역시 남구 장전1길 34 (대명동)070-4109-80842024-02-08
34(주)국제피스코상ㆍ하수도설비공사업대구광역시 남구 대명남로 171 (대명동)053-653-79582024-02-08
45(주)노수테크기계설비ㆍ가스공사업대구광역시 남구 앞산순환로 561 (대명동)053-627-30882024-02-08
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