Overview

Dataset statistics

Number of variables3
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory26.8 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 02:53:04.359415
Analysis finished2024-03-14 02:53:04.702790
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.5
Minimum1
Maximum72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-03-14T11:53:04.760224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.55
Q118.75
median36.5
Q354.25
95-th percentile68.45
Maximum72
Range71
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation20.92845
Coefficient of variation (CV)0.57338218
Kurtosis-1.2
Mean36.5
Median Absolute Deviation (MAD)18
Skewness0
Sum2628
Variance438
MonotonicityStrictly increasing
2024-03-14T11:53:04.874958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
38 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%

등록번호
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-03-14T11:53:05.091286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.6805556
Min length6

Characters and Unicode

Total characters553
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

Unique72 ?
Unique (%)100.0%

Sample

1st row05032027
2nd row04-002763
3rd row05032084
4th row05032083
5th row052133
ValueCountFrequency (%)
05032027 1
 
1.4%
04-002763 1
 
1.4%
05032089 1
 
1.4%
05032051 1
 
1.4%
05032057 1
 
1.4%
05032067 1
 
1.4%
05032061 1
 
1.4%
05032065 1
 
1.4%
04-002853 1
 
1.4%
052116 1
 
1.4%
Other values (62) 62
86.1%
2024-03-14T11:53:05.408528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 188
34.0%
2 79
14.3%
5 77
13.9%
3 61
 
11.0%
1 33
 
6.0%
4 27
 
4.9%
8 23
 
4.2%
7 18
 
3.3%
6 18
 
3.3%
9 18
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 542
98.0%
Dash Punctuation 11
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 188
34.7%
2 79
14.6%
5 77
14.2%
3 61
 
11.3%
1 33
 
6.1%
4 27
 
5.0%
8 23
 
4.2%
7 18
 
3.3%
6 18
 
3.3%
9 18
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 188
34.0%
2 79
14.3%
5 77
13.9%
3 61
 
11.0%
1 33
 
6.0%
4 27
 
4.9%
8 23
 
4.2%
7 18
 
3.3%
6 18
 
3.3%
9 18
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 188
34.0%
2 79
14.3%
5 77
13.9%
3 61
 
11.0%
1 33
 
6.0%
4 27
 
4.9%
8 23
 
4.2%
7 18
 
3.3%
6 18
 
3.3%
9 18
 
3.3%

업 체 명
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-03-14T11:53:05.599739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8.8472222
Min length3

Characters and Unicode

Total characters637
Distinct characters111
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

Unique72 ?
Unique (%)100.0%

Sample

1st row(유)공간건설엔지니어링
2nd row(유)대건엔지니어링
3rd row(유)대성이엔씨
4th row(유)동방엔지니어링
5th row(유)미래에스엔씨
ValueCountFrequency (%)
유한회사 8
 
9.5%
주식회사 3
 
3.6%
거성건설 1
 
1.2%
강성엔지니어링 1
 
1.2%
우리측량토목설계 1
 
1.2%
송하측량토목설계공사 1
 
1.2%
새터이엔지 1
 
1.2%
삼일토목기술단 1
 
1.2%
부경주식회사 1
 
1.2%
유)공간건설엔지니어링 1
 
1.2%
Other values (65) 65
77.4%
2024-03-14T11:53:05.982304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
설 35
 
5.5%
( 34
 
5.3%
) 34
 
5.3%
사 33
 
5.2%
유 28
 
4.4%
엔 24
 
3.8%
지 22
 
3.5%
계 21
 
3.3%
량 21
 
3.3%
측 21
 
3.3%
Other values (101) 364
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 553
86.8%
Open Punctuation 34
 
5.3%
Close Punctuation 34
 
5.3%
Space Separator 12
 
1.9%
Uppercase Letter 3
 
0.5%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 35
 
6.3%
사 33
 
6.0%
유 28
 
5.1%
엔 24
 
4.3%
지 22
 
4.0%
계 21
 
3.8%
량 21
 
3.8%
측 21
 
3.8%
주 19
 
3.4%
링 15
 
2.7%
Other values (94) 314
56.8%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
E 1
33.3%
N 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 554
87.0%
Common 80
 
12.6%
Latin 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 35
 
6.3%
사 33
 
6.0%
유 28
 
5.1%
엔 24
 
4.3%
지 22
 
4.0%
계 21
 
3.8%
량 21
 
3.8%
측 21
 
3.8%
주 19
 
3.4%
링 15
 
2.7%
Other values (95) 315
56.9%
Common
ValueCountFrequency (%)
( 34
42.5%
) 34
42.5%
12
 
15.0%
Latin
ValueCountFrequency (%)
G 1
33.3%
E 1
33.3%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 553
86.8%
ASCII 83
 
13.0%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
설 35
 
6.3%
사 33
 
6.0%
유 28
 
5.1%
엔 24
 
4.3%
지 22
 
4.0%
계 21
 
3.8%
량 21
 
3.8%
측 21
 
3.8%
주 19
 
3.4%
링 15
 
2.7%
Other values (94) 314
56.8%
ASCII
ValueCountFrequency (%)
( 34
41.0%
) 34
41.0%
12
 
14.5%
G 1
 
1.2%
E 1
 
1.2%
N 1
 
1.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

Interactions

2024-03-14T11:53:04.479887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:53:06.061052image/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

2024-03-14T11:53:04.598892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:53:04.678154image/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
0105032027(유)공간건설엔지니어링
1204-002763(유)대건엔지니어링
2305032084(유)대성이엔씨
3405032083(유)동방엔지니어링
45052133(유)미래에스엔씨
5605032063(유)백두엔지니어링
67052182(유)범한
7805032076(유)삼교건설엔지니어링
8905032055(유)삼안엔지니어링
910052020(유)삼오기술사
연번등록번호업 체 명
6263052123제일측량설계공사
636404-002914주식회사 고산
646504-003103주식회사 고원
656604-002964주식회사 지유엔지니어링
666705032196지오측량설계사무소
6768052048청구토목측량설계공사
6869052176토지측량설계공사
697005032185하늘측량토목설계
7071052094현대측량설계공사
7172052145호남측량설계공사