Overview

Dataset statistics

Number of variables5
Number of observations32
Missing cells25
Missing cells (%)15.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory45.1 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 미추홀구의 중고가전 판매장 현황에 대한 데이터로 업소명, 도로명주소, 전화번호,위도,경도 등의 정보를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15087067/fileData.do

Alerts

도로명주소 has 7 (21.9%) missing valuesMissing
전화번호 has 18 (56.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:25:56.628180
Analysis finished2023-12-12 20:25:57.457218
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T05:25:57.555060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2023-12-13T05:25:57.754157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

상호명
Text

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T05:25:58.023315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length18
Mean length9.8125
Min length4

Characters and Unicode

Total characters314
Distinct characters94
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)93.8%

Sample

1st row한길물산
2nd row가전종합알뜰매장
3rd row중고가전냉장고세탁기에어컨매입가구폐기가
4th row중고가전가구알뜰매장
5th row동일중고가전
ValueCountFrequency (%)
예본알뜰매장 2
 
6.2%
한길물산 1
 
3.1%
우리나눔중고생활용품 1
 
3.1%
대형폐기물처리인테리어철거상가철거욕실철거유품정리화환수거 1
 
3.1%
중고가구가전사무용리퍼브고가매입판매 1
 
3.1%
업소용중고냉장고판매.식당폐업정리.식당집기매입.식당철거 1
 
3.1%
하나전자 1
 
3.1%
행복알뜰매장 1
 
3.1%
하림엔지니어링 1
 
3.1%
종합알뜰매장신세계 1
 
3.1%
Other values (21) 21
65.6%
2023-12-13T05:25:58.453234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 24
 
7.6%
매 22
 
7.0%
가 20
 
6.4%
중 19
 
6.1%
장 18
 
5.7%
전 17
 
5.4%
알 12
 
3.8%
뜰 12
 
3.8%
기 7
 
2.2%
리 6
 
1.9%
Other values (84) 157
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
98.4%
Other Punctuation 3
 
1.0%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 24
 
7.8%
매 22
 
7.1%
가 20
 
6.5%
중 19
 
6.1%
장 18
 
5.8%
전 17
 
5.5%
알 12
 
3.9%
뜰 12
 
3.9%
기 7
 
2.3%
리 6
 
1.9%
Other values (81) 152
49.2%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
98.4%
Common 3
 
1.0%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 24
 
7.8%
매 22
 
7.1%
가 20
 
6.5%
중 19
 
6.1%
장 18
 
5.8%
전 17
 
5.5%
알 12
 
3.9%
뜰 12
 
3.9%
기 7
 
2.3%
리 6
 
1.9%
Other values (81) 152
49.2%
Latin
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%
Common
ValueCountFrequency (%)
. 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
98.4%
ASCII 5
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 24
 
7.8%
매 22
 
7.1%
가 20
 
6.5%
중 19
 
6.1%
장 18
 
5.8%
전 17
 
5.5%
알 12
 
3.9%
뜰 12
 
3.9%
기 7
 
2.3%
리 6
 
1.9%
Other values (81) 152
49.2%
ASCII
ValueCountFrequency (%)
. 3
60.0%
G 1
 
20.0%
S 1
 
20.0%

지번주소
Text

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T05:25:58.712059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length19.34375
Min length14

Characters and Unicode

Total characters619
Distinct characters33
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

Unique28 ?
Unique (%)87.5%

Sample

1st row인천광역시 미추홀구 도화동 389-16
2nd row인천광역시 미추홀구 주안동 799-4
3rd row인천광역시 미추홀구 주안동
4th row인천광역시 미추홀구 용현동 463-31
5th row인천광역시 미추홀구 도화1동 624-30
ValueCountFrequency (%)
인천광역시 32
26.4%
미추홀구 32
26.4%
용현동 9
 
7.4%
주안동 8
 
6.6%
도화동 4
 
3.3%
숭의동 4
 
3.3%
문학동 2
 
1.7%
학익동 2
 
1.7%
606-26 1
 
0.8%
666-3 1
 
0.8%
Other values (26) 26
21.5%
2023-12-13T05:25:59.131710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
 
14.9%
인 32
 
5.2%
동 32
 
5.2%
광 32
 
5.2%
역 32
 
5.2%
시 32
 
5.2%
미 32
 
5.2%
추 32
 
5.2%
홀 32
 
5.2%
구 32
 
5.2%
Other values (23) 239
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 384
62.0%
Decimal Number 119
 
19.2%
Space Separator 92
 
14.9%
Dash Punctuation 24
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 32
8.3%
동 32
8.3%
광 32
8.3%
역 32
8.3%
시 32
8.3%
미 32
8.3%
추 32
8.3%
홀 32
8.3%
구 32
8.3%
천 32
8.3%
Other values (11) 64
16.7%
Decimal Number
ValueCountFrequency (%)
1 26
21.8%
6 16
13.4%
3 15
12.6%
2 14
11.8%
7 11
9.2%
5 10
 
8.4%
4 10
 
8.4%
9 7
 
5.9%
0 6
 
5.0%
8 4
 
3.4%
Space Separator
ValueCountFrequency (%)
92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 384
62.0%
Common 235
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 32
8.3%
동 32
8.3%
광 32
8.3%
역 32
8.3%
시 32
8.3%
미 32
8.3%
추 32
8.3%
홀 32
8.3%
구 32
8.3%
천 32
8.3%
Other values (11) 64
16.7%
Common
ValueCountFrequency (%)
92
39.1%
1 26
 
11.1%
- 24
 
10.2%
6 16
 
6.8%
3 15
 
6.4%
2 14
 
6.0%
7 11
 
4.7%
5 10
 
4.3%
4 10
 
4.3%
9 7
 
3.0%
Other values (2) 10
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 384
62.0%
ASCII 235
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
39.1%
1 26
 
11.1%
- 24
 
10.2%
6 16
 
6.8%
3 15
 
6.4%
2 14
 
6.0%
7 11
 
4.7%
5 10
 
4.3%
4 10
 
4.3%
9 7
 
3.0%
Other values (2) 10
 
4.3%
Hangul
ValueCountFrequency (%)
인 32
8.3%
동 32
8.3%
광 32
8.3%
역 32
8.3%
시 32
8.3%
미 32
8.3%
추 32
8.3%
홀 32
8.3%
구 32
8.3%
천 32
8.3%
Other values (11) 64
16.7%

도로명주소
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing7
Missing (%)21.9%
Memory size388.0 B
2023-12-13T05:25:59.406937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length20.08
Min length17

Characters and Unicode

Total characters502
Distinct characters60
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

Unique25 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 경인로 303
2nd row인천광역시 미추홀구 인주대로 296
3rd row인천광역시 미추홀구 인주대로 93
4th row인천광역시 미추홀구 수봉북로 14
5th row인천광역시 미추홀구 인주대로 327
ValueCountFrequency (%)
인천광역시 25
24.3%
미추홀구 25
24.3%
인주대로 5
 
4.9%
5 2
 
1.9%
매소홀로 2
 
1.9%
104 2
 
1.9%
한나루로 2
 
1.9%
토금북로 2
 
1.9%
석정로 2
 
1.9%
71 2
 
1.9%
Other values (34) 34
33.0%
2023-12-13T05:25:59.892679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
15.5%
인 35
 
7.0%
홀 27
 
5.4%
추 25
 
5.0%
로 25
 
5.0%
구 25
 
5.0%
천 25
 
5.0%
미 25
 
5.0%
시 25
 
5.0%
역 25
 
5.0%
Other values (50) 187
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 344
68.5%
Decimal Number 79
 
15.7%
Space Separator 78
 
15.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 35
10.2%
홀 27
 
7.8%
추 25
 
7.3%
로 25
 
7.3%
구 25
 
7.3%
천 25
 
7.3%
미 25
 
7.3%
시 25
 
7.3%
역 25
 
7.3%
광 25
 
7.3%
Other values (38) 82
23.8%
Decimal Number
ValueCountFrequency (%)
4 11
13.9%
2 11
13.9%
1 11
13.9%
5 9
11.4%
3 8
10.1%
9 7
8.9%
6 6
7.6%
7 6
7.6%
0 6
7.6%
8 4
 
5.1%
Space Separator
ValueCountFrequency (%)
78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 344
68.5%
Common 158
31.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 35
10.2%
홀 27
 
7.8%
추 25
 
7.3%
로 25
 
7.3%
구 25
 
7.3%
천 25
 
7.3%
미 25
 
7.3%
시 25
 
7.3%
역 25
 
7.3%
광 25
 
7.3%
Other values (38) 82
23.8%
Common
ValueCountFrequency (%)
78
49.4%
4 11
 
7.0%
2 11
 
7.0%
1 11
 
7.0%
5 9
 
5.7%
3 8
 
5.1%
9 7
 
4.4%
6 6
 
3.8%
7 6
 
3.8%
0 6
 
3.8%
Other values (2) 5
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 344
68.5%
ASCII 158
31.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
49.4%
4 11
 
7.0%
2 11
 
7.0%
1 11
 
7.0%
5 9
 
5.7%
3 8
 
5.1%
9 7
 
4.4%
6 6
 
3.8%
7 6
 
3.8%
0 6
 
3.8%
Other values (2) 5
 
3.2%
Hangul
ValueCountFrequency (%)
인 35
10.2%
홀 27
 
7.8%
추 25
 
7.3%
로 25
 
7.3%
구 25
 
7.3%
천 25
 
7.3%
미 25
 
7.3%
시 25
 
7.3%
역 25
 
7.3%
광 25
 
7.3%
Other values (38) 82
23.8%

전화번호
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing18
Missing (%)56.2%
Memory size388.0 B
2023-12-13T05:26:00.144770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13.5
Mean length12.571429
Min length12

Characters and Unicode

Total characters176
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

Unique14 ?
Unique (%)100.0%

Sample

1st row032-437-4998
2nd row070-4528-9809
3rd row0507-1422-6005
4th row032-432-5005
5th row070-8916-9312
ValueCountFrequency (%)
032-437-4998 1
 
7.1%
070-4528-9809 1
 
7.1%
0507-1422-6005 1
 
7.1%
032-432-5005 1
 
7.1%
070-8916-9312 1
 
7.1%
032-862-0813 1
 
7.1%
032-710-4306 1
 
7.1%
032-873-4944 1
 
7.1%
032-863-7945 1
 
7.1%
032-246-5005 1
 
7.1%
Other values (4) 4
28.6%
2023-12-13T05:26:00.560609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
19.3%
- 28
15.9%
2 18
10.2%
3 16
9.1%
4 15
8.5%
9 13
 
7.4%
8 13
 
7.4%
7 12
 
6.8%
5 10
 
5.7%
6 9
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148
84.1%
Dash Punctuation 28
 
15.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
23.0%
2 18
12.2%
3 16
10.8%
4 15
10.1%
9 13
 
8.8%
8 13
 
8.8%
7 12
 
8.1%
5 10
 
6.8%
6 9
 
6.1%
1 8
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 176
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
19.3%
- 28
15.9%
2 18
10.2%
3 16
9.1%
4 15
8.5%
9 13
 
7.4%
8 13
 
7.4%
7 12
 
6.8%
5 10
 
5.7%
6 9
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
19.3%
- 28
15.9%
2 18
10.2%
3 16
9.1%
4 15
8.5%
9 13
 
7.4%
8 13
 
7.4%
7 12
 
6.8%
5 10
 
5.7%
6 9
 
5.1%

Interactions

2023-12-13T05:25:56.946386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:26:00.657301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명지번주소도로명주소전화번호
연번1.0000.9170.9071.0001.000
상호명0.9171.0000.9861.0001.000
지번주소0.9070.9861.0001.0001.000
도로명주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2023-12-13T05:25:57.133537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:25:57.283262image/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.
2023-12-13T05:25:57.399539image/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
01한길물산인천광역시 미추홀구 도화동 389-16인천광역시 미추홀구 경인로 303032-437-4998
12가전종합알뜰매장인천광역시 미추홀구 주안동 799-4인천광역시 미추홀구 인주대로 296<NA>
23중고가전냉장고세탁기에어컨매입가구폐기가인천광역시 미추홀구 주안동<NA>070-4528-9809
34중고가전가구알뜰매장인천광역시 미추홀구 용현동 463-31인천광역시 미추홀구 인주대로 930507-1422-6005
45동일중고가전인천광역시 미추홀구 도화1동 624-30인천광역시 미추홀구 수봉북로 14<NA>
56종합중고전자인천광역시 미추홀구 주안2동 1417-63인천광역시 미추홀구 인주대로 327<NA>
67서광중고가전인천광역시 미추홀구 주안동 169인천광역시 미추홀구 주안중로 25<NA>
78예본알뜰매장인천광역시 미추홀구 숭의동 111-21인천광역시 미추홀구 석정로 95032-432-5005
89중고가전에어컨세탁기냉장고매입판매건조기인천광역시 미추홀구 도화동<NA>070-8916-9312
910종합가전알뜰매장인천광역시 미추홀구 용현동 104-6인천광역시 미추홀구 인주대로 247032-862-0813
연번상호명지번주소도로명주소전화번호
2223중고사랑인천광역시 미추홀구 주안동 606-26인천광역시 미추홀구 한나루로550번길 5<NA>
2324종합알뜰매장신세계인천광역시 미추홀구 용현동 453-65인천광역시 미추홀구 인주대로 137<NA>
2425하림엔지니어링인천광역시 미추홀구 주안7동 1461-3인천광역시 미추홀구 인하로267번길 28<NA>
2526행복알뜰매장인천광역시 미추홀구 용현동 177-34인천광역시 미추홀구 인주대로224번길 36032-863-7945
2627하나전자인천광역시 미추홀구 주안동 801-23인천광역시 미추홀구 한나루로490번길 5<NA>
2728예본알뜰매장인천광역시 미추홀구 주안동<NA>032-246-5005
2829업소용중고냉장고판매.식당폐업정리.식당집기매입.식당철거인천광역시 미추홀구 학익동<NA>070-8935-6414
2930중고가구가전사무용리퍼브고가매입판매인천광역시 미추홀구 숭의동<NA>070-8932-2040
3031대형폐기물처리인테리어철거상가철거욕실철거유품정리화환수거인천광역시 미추홀구 문학동<NA>070-7912-8462
3132인천중고가전매장가구매입냉장고세탁기에어인천광역시 미추홀구 도화동<NA>070-8916-9058