Overview

Dataset statistics

Number of variables3
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory27.7 B

Variable types

Numeric1
Text2

Alerts

연번 has unique valuesUnique
등록번호 has unique valuesUnique
업 체 명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:29:03.654516
Analysis finished2024-03-14 00:29:03.930499
Duration0.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25
Minimum1
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-03-14T09:29:03.991764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.4
Q113
median25
Q337
95-th percentile46.6
Maximum49
Range48
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.28869
Coefficient of variation (CV)0.57154761
Kurtosis-1.2
Mean25
Median Absolute Deviation (MAD)12
Skewness0
Sum1225
Variance204.16667
MonotonicityStrictly increasing
2024-03-14T09:29:04.129925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 1
 
2.0%
38 1
 
2.0%
28 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%
40 1
2.0%

등록번호
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-14T09:29:04.323320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9
Min length6

Characters and Unicode

Total characters441
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

Unique49 ?
Unique (%)100.0%

Sample

1st row03-000746
2nd row05-03-1034
3rd row05-1088
4th row05-03-1025
5th row05-03-1019
ValueCountFrequency (%)
03-000746 1
 
2.0%
05-03-1017 1
 
2.0%
05-03-1037 1
 
2.0%
03-000632 1
 
2.0%
05-03-1038 1
 
2.0%
05-03-1032 1
 
2.0%
05-03-1107 1
 
2.0%
03-000749 1
 
2.0%
05-03-1028 1
 
2.0%
05-1103 1
 
2.0%
Other values (39) 39
79.6%
2024-03-14T09:29:04.619788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 159
36.1%
- 66
15.0%
3 56
 
12.7%
1 56
 
12.7%
5 47
 
10.7%
7 14
 
3.2%
2 13
 
2.9%
4 8
 
1.8%
6 8
 
1.8%
8 8
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 375
85.0%
Dash Punctuation 66
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 159
42.4%
3 56
 
14.9%
1 56
 
14.9%
5 47
 
12.5%
7 14
 
3.7%
2 13
 
3.5%
4 8
 
2.1%
6 8
 
2.1%
8 8
 
2.1%
9 6
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 441
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 159
36.1%
- 66
15.0%
3 56
 
12.7%
1 56
 
12.7%
5 47
 
10.7%
7 14
 
3.2%
2 13
 
2.9%
4 8
 
1.8%
6 8
 
1.8%
8 8
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 159
36.1%
- 66
15.0%
3 56
 
12.7%
1 56
 
12.7%
5 47
 
10.7%
7 14
 
3.2%
2 13
 
2.9%
4 8
 
1.8%
6 8
 
1.8%
8 8
 
1.8%

업 체 명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-14T09:29:04.814584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length9.244898
Min length5

Characters and Unicode

Total characters453
Distinct characters89
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row(유) 세종건설기술
2nd row(유)대도엔지니어링
3rd row(유)백제기술공사
4th row(유)승우엔지니어링
5th row(유)신우엔지니어링
ValueCountFrequency (%)
주식회사 5
 
8.3%
엔지니어링 3
 
5.0%
유 1
 
1.7%
주)항도엔지니어링 1
 
1.7%
주)유건앤지리정보센터 1
 
1.7%
주)유앤디엔지니어링건축사사무소 1
 
1.7%
주)유일종합기술단 1
 
1.7%
주)인우 1
 
1.7%
주)조화엔지니어링 1
 
1.7%
주)주한건설기술단 1
 
1.7%
Other values (44) 44
73.3%
2024-03-14T09:29:05.130039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 42
 
9.3%
) 42
 
9.3%
주 34
 
7.5%
엔 21
 
4.6%
지 21
 
4.6%
유 19
 
4.2%
링 17
 
3.8%
어 17
 
3.8%
니 17
 
3.8%
사 13
 
2.9%
Other values (79) 210
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 358
79.0%
Open Punctuation 42
 
9.3%
Close Punctuation 42
 
9.3%
Space Separator 11
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 34
 
9.5%
엔 21
 
5.9%
지 21
 
5.9%
유 19
 
5.3%
링 17
 
4.7%
어 17
 
4.7%
니 17
 
4.7%
사 13
 
3.6%
기 13
 
3.6%
술 13
 
3.6%
Other values (76) 173
48.3%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 358
79.0%
Common 95
 
21.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 34
 
9.5%
엔 21
 
5.9%
지 21
 
5.9%
유 19
 
5.3%
링 17
 
4.7%
어 17
 
4.7%
니 17
 
4.7%
사 13
 
3.6%
기 13
 
3.6%
술 13
 
3.6%
Other values (76) 173
48.3%
Common
ValueCountFrequency (%)
( 42
44.2%
) 42
44.2%
11
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 358
79.0%
ASCII 95
 
21.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 42
44.2%
) 42
44.2%
11
 
11.6%
Hangul
ValueCountFrequency (%)
주 34
 
9.5%
엔 21
 
5.9%
지 21
 
5.9%
유 19
 
5.3%
링 17
 
4.7%
어 17
 
4.7%
니 17
 
4.7%
사 13
 
3.6%
기 13
 
3.6%
술 13
 
3.6%
Other values (76) 173
48.3%

Interactions

2024-03-14T09:29:03.767504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:29:05.244248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번등록번호업 체 명
연번1.0001.0001.000
등록번호1.0001.0001.000
업 체 명1.0001.0001.000

Missing values

2024-03-14T09:29:03.851221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:29:03.906020image/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

연번등록번호업 체 명
0103-000746(유) 세종건설기술
1205-03-1034(유)대도엔지니어링
2305-1088(유)백제기술공사
3405-03-1025(유)승우엔지니어링
4505-03-1019(유)신우엔지니어링
5605-1093(유)신한개발기술단
6705-03-1018(유)여울건설엔지니어링
7805-03-1024(유)이지이앤씨
8905-1054(유)장흥건설기술공사
91005-03-1013(유)케이티 엔지니어링
연번등록번호업 체 명
394005031011(주)현성 엔지니어링
404105031010성원기술개발(주)
414203-000752유한회사 새움
424303-000729유한회사일등엔지니어링
4344051057제이씨엔(주)
444503-000731주식회사 성광
454603-000704주식회사 씨앤에스 비전
464705031021주식회사 천우
4748051050주식회사 한아
484905031006주식회사 현산이엔씨