Overview

Dataset statistics

Number of variables4
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory35.6 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description대구광역시_국제물류주선업 현황_20231208
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15101517&dataSetDetailId=151015171c8b58be320bc&provdMethod=FILE

Alerts

법인구분 is highly imbalanced (76.1%)Imbalance
연번 has unique valuesUnique
상 호 has unique valuesUnique

Reproduction

Analysis started2023-12-22 21:17:58.652068
Analysis finished2023-12-22 21:18:01.311238
Duration2.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-22T21:18:01.659523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2023-12-22T21:18:02.671492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 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%
36 1
 
2.0%
Other values (41) 41
80.4%
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 (%)
51 1
2.0%
50 1
2.0%
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%

법인구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
법인
49 
개인
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 49
96.1%
개인 2
 
3.9%

Length

2023-12-22T21:18:03.392073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:18:03.753233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 49
96.1%
개인 2
 
3.9%

상 호
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-22T21:18:04.441174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.5686275
Min length4

Characters and Unicode

Total characters437
Distinct characters97
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row해륙물류(주)
2nd row(주)삼화국제물류
3rd row그랜드해운항공(주)
4th row(주)삼원토탈로지스틱
5th row제일항공해운(주)
ValueCountFrequency (%)
해륙물류(주 1
 
2.0%
주)디에이치씨앤에어 1
 
2.0%
주)명도물류 1
 
2.0%
수석해운(주 1
 
2.0%
주)지앤프레이트 1
 
2.0%
씨아이엘(주 1
 
2.0%
주)정명운수 1
 
2.0%
주)아이디씨국제운송 1
 
2.0%
주)스타로지스 1
 
2.0%
주)제일사 1
 
2.0%
Other values (41) 41
80.4%
2023-12-22T21:18:05.786889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 49
 
11.2%
주 49
 
11.2%
) 49
 
11.2%
스 24
 
5.5%
이 17
 
3.9%
로 16
 
3.7%
지 15
 
3.4%
운 14
 
3.2%
제 12
 
2.7%
해 11
 
2.5%
Other values (87) 181
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 337
77.1%
Open Punctuation 49
 
11.2%
Close Punctuation 49
 
11.2%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 49
 
14.5%
스 24
 
7.1%
이 17
 
5.0%
로 16
 
4.7%
지 15
 
4.5%
운 14
 
4.2%
제 12
 
3.6%
해 11
 
3.3%
물 10
 
3.0%
류 9
 
2.7%
Other values (83) 160
47.5%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
F 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 337
77.1%
Common 98
 
22.4%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 49
 
14.5%
스 24
 
7.1%
이 17
 
5.0%
로 16
 
4.7%
지 15
 
4.5%
운 14
 
4.2%
제 12
 
3.6%
해 11
 
3.3%
물 10
 
3.0%
류 9
 
2.7%
Other values (83) 160
47.5%
Common
ValueCountFrequency (%)
( 49
50.0%
) 49
50.0%
Latin
ValueCountFrequency (%)
G 1
50.0%
F 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 337
77.1%
ASCII 100
 
22.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 49
49.0%
) 49
49.0%
G 1
 
1.0%
F 1
 
1.0%
Hangul
ValueCountFrequency (%)
주 49
 
14.5%
스 24
 
7.1%
이 17
 
5.0%
로 16
 
4.7%
지 15
 
4.5%
운 14
 
4.2%
제 12
 
3.6%
해 11
 
3.3%
물 10
 
3.0%
류 9
 
2.7%
Other values (83) 160
47.5%

주사무소
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-22T21:18:06.811225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length31
Mean length27.019608
Min length16

Characters and Unicode

Total characters1378
Distinct characters110
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

Unique49 ?
Unique (%)96.1%

Sample

1st row대구광역시 동구 동대구로 495(신천3동)
2nd row대구광역시 동구 동대구로85길 17(신천동)
3rd row대구광역시 남구 이천로 54, 비이동 101호(봉덕동)
4th row대구광역시 동구 동대구로 85길 7-2 (신천3동)
5th row대구광역시 동구 신천동 350-1 비즈빌딩5층
ValueCountFrequency (%)
대구광역시 51
 
19.5%
동구 22
 
8.4%
북구 8
 
3.1%
달서구 7
 
2.7%
수성구 6
 
2.3%
동대구로 4
 
1.5%
3층 4
 
1.5%
48 3
 
1.1%
2층 3
 
1.1%
노원로 3
 
1.1%
Other values (131) 150
57.5%
2023-12-22T21:18:09.849400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
213
 
15.5%
구 108
 
7.8%
동 80
 
5.8%
대 65
 
4.7%
시 52
 
3.8%
광 51
 
3.7%
역 51
 
3.7%
로 50
 
3.6%
1 44
 
3.2%
0 44
 
3.2%
Other values (100) 620
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 770
55.9%
Decimal Number 271
 
19.7%
Space Separator 213
 
15.5%
Other Punctuation 40
 
2.9%
Open Punctuation 35
 
2.5%
Close Punctuation 35
 
2.5%
Dash Punctuation 12
 
0.9%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 108
14.0%
동 80
 
10.4%
대 65
 
8.4%
시 52
 
6.8%
광 51
 
6.6%
역 51
 
6.6%
로 50
 
6.5%
층 22
 
2.9%
호 21
 
2.7%
길 21
 
2.7%
Other values (83) 249
32.3%
Decimal Number
ValueCountFrequency (%)
1 44
16.2%
0 44
16.2%
2 39
14.4%
3 34
12.5%
4 28
10.3%
5 26
9.6%
7 18
6.6%
8 18
6.6%
9 10
 
3.7%
6 10
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
213
100.0%
Other Punctuation
ValueCountFrequency (%)
, 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 770
55.9%
Common 606
44.0%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 108
14.0%
동 80
 
10.4%
대 65
 
8.4%
시 52
 
6.8%
광 51
 
6.6%
역 51
 
6.6%
로 50
 
6.5%
층 22
 
2.9%
호 21
 
2.7%
길 21
 
2.7%
Other values (83) 249
32.3%
Common
ValueCountFrequency (%)
213
35.1%
1 44
 
7.3%
0 44
 
7.3%
, 40
 
6.6%
2 39
 
6.4%
( 35
 
5.8%
) 35
 
5.8%
3 34
 
5.6%
4 28
 
4.6%
5 26
 
4.3%
Other values (5) 68
 
11.2%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 770
55.9%
ASCII 608
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
213
35.0%
1 44
 
7.2%
0 44
 
7.2%
, 40
 
6.6%
2 39
 
6.4%
( 35
 
5.8%
) 35
 
5.8%
3 34
 
5.6%
4 28
 
4.6%
5 26
 
4.3%
Other values (7) 70
 
11.5%
Hangul
ValueCountFrequency (%)
구 108
14.0%
동 80
 
10.4%
대 65
 
8.4%
시 52
 
6.8%
광 51
 
6.6%
역 51
 
6.6%
로 50
 
6.5%
층 22
 
2.9%
호 21
 
2.7%
길 21
 
2.7%
Other values (83) 249
32.3%

Interactions

2023-12-22T21:17:59.796869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-22T21:18:10.291263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법인구분상 호주사무소
연번1.0000.0001.0000.945
법인구분0.0001.0001.0001.000
상 호1.0001.0001.0001.000
주사무소0.9451.0001.0001.000
2023-12-22T21:18:10.951975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법인구분
연번1.0000.000
법인구분0.0001.000

Missing values

2023-12-22T21:18:00.411973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-22T21:18:01.061213image/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

연번법인구분상 호주사무소
01법인해륙물류(주)대구광역시 동구 동대구로 495(신천3동)
12법인(주)삼화국제물류대구광역시 동구 동대구로85길 17(신천동)
23법인그랜드해운항공(주)대구광역시 남구 이천로 54, 비이동 101호(봉덕동)
34법인(주)삼원토탈로지스틱대구광역시 동구 동대구로 85길 7-2 (신천3동)
45법인제일항공해운(주)대구광역시 동구 신천동 350-1 비즈빌딩5층
56법인대구로지스틱스(주)대구광역시 동구 동대구로85길 7-2(신천동)
67법인(주)세이프로지스대구광역시 북구 노원로 169, 405호(노원동3가)
78법인태화로지스틱(주)대구광역시 북구 노원로 116, 205호(노원동3가)
89법인(주)성원해운항공대구광역시 달서구 달서대로 555, 108호(신당동)
910법인(주)GF해운대구광역시 수성구 신천동로 94-7(상동)
연번법인구분상 호주사무소
4142법인(주)와이엔케이서비스대구광역시 동구 동부로22길 48, 302호(신천동)
4243법인(주)엘위즈대구광역시 중구 대봉로 257, 2층
4344법인(주)일상로지스대구광역시 서구 북비산로 48
4445법인(주)제이엔엘로지스대구광역시 동구 반야월로 311-11, 4층(신서동)
4546법인신성로지스(주)대구광역시 동구 안심로51길 7-2(서호동)
4647법인(주)두리종합물류대구광역시 북구 서재로 540, 201호
4748법인(주)다올해운항공대구광역시 동구 동부로22길 9, 1동 603호
4849개인메탈박스대구광역시 북구 성북로 70, 1008동 3409호(침산동, 화성파크드림)
4950법인(주)아이엠로지스대구광역시 수성구 무학로35길 108, 1층(지산동)
5051법인건영화물(주)대구광역시 북구 노원로 125(노원동3가)