Overview

Dataset statistics

Number of variables5
Number of observations62
Missing cells36
Missing cells (%)11.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory43.1 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 미추홀구 내에 있는 고물상에 대한 데이터입니다. 상호명, 도로명주소, 전화번호 등의 항목으로 구성되어있습니다.
URLhttps://www.data.go.kr/data/15086997/fileData.do

Alerts

도로명주소 has 7 (11.3%) missing valuesMissing
전화번호 has 29 (46.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:54:11.048459
Analysis finished2023-12-12 21:54:11.822471
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.5
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-13T06:54:11.916382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.05
Q116.25
median31.5
Q346.75
95-th percentile58.95
Maximum62
Range61
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation18.041619
Coefficient of variation (CV)0.5727498
Kurtosis-1.2
Mean31.5
Median Absolute Deviation (MAD)15.5
Skewness0
Sum1953
Variance325.5
MonotonicityStrictly increasing
2023-12-13T06:54:12.046772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
48 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (52) 52
83.9%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%

상호명
Text

Distinct57
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-13T06:54:12.293372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length4
Mean length4.5483871
Min length3

Characters and Unicode

Total characters282
Distinct characters94
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)85.5%

Sample

1st row오뚜기자원
2nd row주안자원
3rd row항만자원
4th row인하자원
5th row명진비철
ValueCountFrequency (%)
금강자원 3
 
4.8%
그린자원 2
 
3.2%
우리자원 2
 
3.2%
당진자원 2
 
3.2%
신의철강 1
 
1.6%
대아자원 1
 
1.6%
오뚜기자원 1
 
1.6%
금성고물상 1
 
1.6%
대성비철 1
 
1.6%
그린고물상 1
 
1.6%
Other values (47) 47
75.8%
2023-12-13T06:54:12.687729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 49
 
17.4%
자 47
 
16.7%
물 9
 
3.2%
고 8
 
2.8%
상 8
 
2.8%
성 7
 
2.5%
철 6
 
2.1%
대 6
 
2.1%
우 6
 
2.1%
금 5
 
1.8%
Other values (84) 131
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 282
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 49
 
17.4%
자 47
 
16.7%
물 9
 
3.2%
고 8
 
2.8%
상 8
 
2.8%
성 7
 
2.5%
철 6
 
2.1%
대 6
 
2.1%
우 6
 
2.1%
금 5
 
1.8%
Other values (84) 131
46.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 282
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 49
 
17.4%
자 47
 
16.7%
물 9
 
3.2%
고 8
 
2.8%
상 8
 
2.8%
성 7
 
2.5%
철 6
 
2.1%
대 6
 
2.1%
우 6
 
2.1%
금 5
 
1.8%
Other values (84) 131
46.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 282
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 49
 
17.4%
자 47
 
16.7%
물 9
 
3.2%
고 8
 
2.8%
상 8
 
2.8%
성 7
 
2.5%
철 6
 
2.1%
대 6
 
2.1%
우 6
 
2.1%
금 5
 
1.8%
Other values (84) 131
46.5%

지번주소
Text

Distinct61
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-13T06:54:12.905371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.33871
Min length14

Characters and Unicode

Total characters1261
Distinct characters38
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

Unique60 ?
Unique (%)96.8%

Sample

1st row인천광역시 미추홀구 주안동 180-1
2nd row인천광역시 미추홀구 주안동 116-12
3rd row인천광역시 미추홀구 숭의동 432-22 항만자원
4th row인천광역시 미추홀구 용현동 187-46
5th row인천광역시 미추홀구 주안동 832-12
ValueCountFrequency (%)
인천광역시 62
25.0%
미추홀구 62
25.0%
도화동 18
 
7.3%
주안동 13
 
5.2%
용현동 11
 
4.4%
학익동 9
 
3.6%
숭의동 9
 
3.6%
문학동 2
 
0.8%
203-18 2
 
0.8%
640-8 2
 
0.8%
Other values (58) 58
23.4%
2023-12-13T06:54:13.271671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
 
14.9%
인 62
 
4.9%
추 62
 
4.9%
동 62
 
4.9%
천 62
 
4.9%
홀 62
 
4.9%
구 62
 
4.9%
미 62
 
4.9%
시 62
 
4.9%
역 62
 
4.9%
Other values (28) 515
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 752
59.6%
Decimal Number 266
 
21.1%
Space Separator 188
 
14.9%
Dash Punctuation 55
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 62
8.2%
추 62
8.2%
동 62
8.2%
천 62
8.2%
홀 62
8.2%
구 62
8.2%
미 62
8.2%
시 62
8.2%
역 62
8.2%
광 62
8.2%
Other values (16) 132
17.6%
Decimal Number
ValueCountFrequency (%)
1 51
19.2%
2 45
16.9%
0 26
9.8%
3 24
9.0%
6 22
8.3%
8 22
8.3%
7 21
7.9%
4 21
7.9%
5 20
 
7.5%
9 14
 
5.3%
Space Separator
ValueCountFrequency (%)
188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 752
59.6%
Common 509
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 62
8.2%
추 62
8.2%
동 62
8.2%
천 62
8.2%
홀 62
8.2%
구 62
8.2%
미 62
8.2%
시 62
8.2%
역 62
8.2%
광 62
8.2%
Other values (16) 132
17.6%
Common
ValueCountFrequency (%)
188
36.9%
- 55
 
10.8%
1 51
 
10.0%
2 45
 
8.8%
0 26
 
5.1%
3 24
 
4.7%
6 22
 
4.3%
8 22
 
4.3%
7 21
 
4.1%
4 21
 
4.1%
Other values (2) 34
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 752
59.6%
ASCII 509
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
36.9%
- 55
 
10.8%
1 51
 
10.0%
2 45
 
8.8%
0 26
 
5.1%
3 24
 
4.7%
6 22
 
4.3%
8 22
 
4.3%
7 21
 
4.1%
4 21
 
4.1%
Other values (2) 34
 
6.7%
Hangul
ValueCountFrequency (%)
인 62
8.2%
추 62
8.2%
동 62
8.2%
천 62
8.2%
홀 62
8.2%
구 62
8.2%
미 62
8.2%
시 62
8.2%
역 62
8.2%
광 62
8.2%
Other values (16) 132
17.6%

도로명주소
Text

MISSING 

Distinct54
Distinct (%)98.2%
Missing7
Missing (%)11.3%
Memory size628.0 B
2023-12-13T06:54:13.517438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length20.4
Min length17

Characters and Unicode

Total characters1122
Distinct characters80
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

Unique53 ?
Unique (%)96.4%

Sample

1st row인천광역시 미추홀구 주안중로 9
2nd row인천광역시 미추홀구 주안동로 59
3rd row인천광역시 미추홀구 인중로16번길 18 항만자원
4th row인천광역시 미추홀구 인하로 215
5th row인천광역시 미추홀구 한나루로599번길 2
ValueCountFrequency (%)
인천광역시 55
24.3%
미추홀구 55
24.3%
인주대로 7
 
3.1%
경인로 4
 
1.8%
한나루로341번길 4
 
1.8%
경인북길 3
 
1.3%
석정로301번길 3
 
1.3%
매소홀로 2
 
0.9%
5 2
 
0.9%
52 2
 
0.9%
Other values (81) 89
39.4%
2023-12-13T06:54:13.937537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
171
 
15.2%
인 74
 
6.6%
홀 59
 
5.3%
천 57
 
5.1%
광 55
 
4.9%
역 55
 
4.9%
시 55
 
4.9%
미 55
 
4.9%
추 55
 
4.9%
구 55
 
4.9%
Other values (70) 431
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 763
68.0%
Decimal Number 183
 
16.3%
Space Separator 171
 
15.2%
Dash Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 74
 
9.7%
홀 59
 
7.7%
천 57
 
7.5%
광 55
 
7.2%
역 55
 
7.2%
시 55
 
7.2%
미 55
 
7.2%
추 55
 
7.2%
구 55
 
7.2%
로 50
 
6.6%
Other values (58) 193
25.3%
Decimal Number
ValueCountFrequency (%)
1 34
18.6%
2 27
14.8%
3 25
13.7%
5 19
10.4%
4 19
10.4%
6 18
9.8%
0 14
7.7%
9 11
 
6.0%
7 9
 
4.9%
8 7
 
3.8%
Space Separator
ValueCountFrequency (%)
171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 763
68.0%
Common 359
32.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 74
 
9.7%
홀 59
 
7.7%
천 57
 
7.5%
광 55
 
7.2%
역 55
 
7.2%
시 55
 
7.2%
미 55
 
7.2%
추 55
 
7.2%
구 55
 
7.2%
로 50
 
6.6%
Other values (58) 193
25.3%
Common
ValueCountFrequency (%)
171
47.6%
1 34
 
9.5%
2 27
 
7.5%
3 25
 
7.0%
5 19
 
5.3%
4 19
 
5.3%
6 18
 
5.0%
0 14
 
3.9%
9 11
 
3.1%
7 9
 
2.5%
Other values (2) 12
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 763
68.0%
ASCII 359
32.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
171
47.6%
1 34
 
9.5%
2 27
 
7.5%
3 25
 
7.0%
5 19
 
5.3%
4 19
 
5.3%
6 18
 
5.0%
0 14
 
3.9%
9 11
 
3.1%
7 9
 
2.5%
Other values (2) 12
 
3.3%
Hangul
ValueCountFrequency (%)
인 74
 
9.7%
홀 59
 
7.7%
천 57
 
7.5%
광 55
 
7.2%
역 55
 
7.2%
시 55
 
7.2%
미 55
 
7.2%
추 55
 
7.2%
구 55
 
7.2%
로 50
 
6.6%
Other values (58) 193
25.3%

전화번호
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing29
Missing (%)46.8%
Memory size628.0 B
2023-12-13T06:54:14.148391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.454545
Min length12

Characters and Unicode

Total characters411
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

Unique33 ?
Unique (%)100.0%

Sample

1st row0507-1302-5711
2nd row0507-1394-8230
3rd row032-873-0828
4th row032-876-4037
5th row0507-1313-9745
ValueCountFrequency (%)
032-863-2600 1
 
3.0%
032-862-0673 1
 
3.0%
032-424-7407 1
 
3.0%
032-434-6960 1
 
3.0%
0507-1331-5946 1
 
3.0%
032-872-0677 1
 
3.0%
032-868-1235 1
 
3.0%
032-874-2848 1
 
3.0%
070-4553-2942 1
 
3.0%
0507-1302-5711 1
 
3.0%
Other values (23) 23
69.7%
2023-12-13T06:54:14.498652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 66
16.1%
0 60
14.6%
3 57
13.9%
2 46
11.2%
7 40
9.7%
8 39
9.5%
6 24
 
5.8%
4 22
 
5.4%
5 20
 
4.9%
1 20
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 345
83.9%
Dash Punctuation 66
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60
17.4%
3 57
16.5%
2 46
13.3%
7 40
11.6%
8 39
11.3%
6 24
 
7.0%
4 22
 
6.4%
5 20
 
5.8%
1 20
 
5.8%
9 17
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 411
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 66
16.1%
0 60
14.6%
3 57
13.9%
2 46
11.2%
7 40
9.7%
8 39
9.5%
6 24
 
5.8%
4 22
 
5.4%
5 20
 
4.9%
1 20
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 66
16.1%
0 60
14.6%
3 57
13.9%
2 46
11.2%
7 40
9.7%
8 39
9.5%
6 24
 
5.8%
4 22
 
5.4%
5 20
 
4.9%
1 20
 
4.9%

Interactions

2023-12-13T06:54:11.445066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:54:14.599072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명지번주소도로명주소전화번호
연번1.0000.5990.9320.9451.000
상호명0.5991.0000.9910.9891.000
지번주소0.9320.9911.0001.0001.000
도로명주소0.9450.9891.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2023-12-13T06:54:11.555258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:54:11.654109image/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.
2023-12-13T06:54:11.762750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번상호명지번주소도로명주소전화번호
01오뚜기자원인천광역시 미추홀구 주안동 180-1인천광역시 미추홀구 주안중로 9<NA>
12주안자원인천광역시 미추홀구 주안동 116-12인천광역시 미추홀구 주안동로 59<NA>
23항만자원인천광역시 미추홀구 숭의동 432-22 항만자원인천광역시 미추홀구 인중로16번길 18 항만자원0507-1302-5711
34인하자원인천광역시 미추홀구 용현동 187-46<NA>0507-1394-8230
45명진비철인천광역시 미추홀구 주안동 832-12인천광역시 미추홀구 인하로 215<NA>
56대명자원인천광역시 미추홀구 도화동 440-13인천광역시 미추홀구 한나루로599번길 2<NA>
67신비자원인천광역시 미추홀구 주안동 1586-1인천광역시 미추홀구 경인로 460<NA>
78희망자원인천광역시 미추홀구 주안동 1447-7인천광역시 미추홀구 인주대로366번길 10032-873-0828
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