Overview

Dataset statistics

Number of variables4
Number of observations107
Missing cells5
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory34.2 B

Variable types

Numeric1
Text3

Dataset

Description대구광역시 서구 관내 세탁업 현황에 대한 데이터로 업소명, 소재지, 업소전화번호 등의 항목을 제공합니다.*코인세탁업은 자유업으로 취급하지 않는 데이터입니다.
Author대구광역시 서구
URLhttps://www.data.go.kr/data/15054532/fileData.do

Alerts

소재지전화 has 5 (4.7%) missing valuesMissing
연번 has unique valuesUnique
영업소 주소(도로명) has unique valuesUnique

Reproduction

Analysis started2024-03-14 17:24:21.482698
Analysis finished2024-03-14 17:24:22.771042
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54
Minimum1
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-15T02:24:23.023625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.3
Q127.5
median54
Q380.5
95-th percentile101.7
Maximum107
Range106
Interquartile range (IQR)53

Descriptive statistics

Standard deviation31.032241
Coefficient of variation (CV)0.57467114
Kurtosis-1.2
Mean54
Median Absolute Deviation (MAD)27
Skewness0
Sum5778
Variance963
MonotonicityStrictly increasing
2024-03-15T02:24:23.466936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
69 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
Other values (97) 97
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%

업소명
Text

Distinct96
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size984.0 B
2024-03-15T02:24:24.499432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length5
Mean length5.4018692
Min length2

Characters and Unicode

Total characters578
Distinct characters136
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)82.2%

Sample

1st row현대
2nd row월성세탁소
3rd row미조사세탁소
4th row서대구세탁소
5th row크린세탁소
ValueCountFrequency (%)
백광세탁소 4
 
3.6%
현대세탁소 3
 
2.7%
세화컴퓨터크리닝 2
 
1.8%
백양세탁소 2
 
1.8%
경북세탁소 2
 
1.8%
대현세탁소 2
 
1.8%
서부세탁소 2
 
1.8%
신우세탁소 2
 
1.8%
한아름컴퓨터세탁 1
 
0.9%
청우세탁소 1
 
0.9%
Other values (90) 90
81.1%
2024-03-15T02:24:25.893986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 91
 
15.7%
탁 88
 
15.2%
소 80
 
13.8%
크 13
 
2.2%
리 13
 
2.2%
대 12
 
2.1%
백 12
 
2.1%
닝 10
 
1.7%
성 8
 
1.4%
동 8
 
1.4%
Other values (126) 243
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 574
99.3%
Space Separator 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 91
 
15.9%
탁 88
 
15.3%
소 80
 
13.9%
크 13
 
2.3%
리 13
 
2.3%
대 12
 
2.1%
백 12
 
2.1%
닝 10
 
1.7%
성 8
 
1.4%
동 8
 
1.4%
Other values (125) 239
41.6%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 574
99.3%
Common 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 91
 
15.9%
탁 88
 
15.3%
소 80
 
13.9%
크 13
 
2.3%
리 13
 
2.3%
대 12
 
2.1%
백 12
 
2.1%
닝 10
 
1.7%
성 8
 
1.4%
동 8
 
1.4%
Other values (125) 239
41.6%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 574
99.3%
ASCII 4
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 91
 
15.9%
탁 88
 
15.3%
소 80
 
13.9%
크 13
 
2.3%
리 13
 
2.3%
대 12
 
2.1%
백 12
 
2.1%
닝 10
 
1.7%
성 8
 
1.4%
동 8
 
1.4%
Other values (125) 239
41.6%
ASCII
ValueCountFrequency (%)
4
100.0%

영업소 주소(도로명)
Text

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size984.0 B
2024-03-15T02:24:27.075023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40
Mean length26.336449
Min length22

Characters and Unicode

Total characters2818
Distinct characters72
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

Unique107 ?
Unique (%)100.0%

Sample

1st row대구광역시 서구 당산로45길 46, 1층
2nd row대구광역시 서구 북비산로31길 11 (평리동)
3rd row대구광역시 서구 국채보상로50길 47 (평리동)
4th row대구광역시 서구 서대구로44길 25 (평리동)
5th row대구광역시 서구 북비산로50길 12 (평리동)
ValueCountFrequency (%)
대구광역시 107
19.1%
서구 107
19.1%
평리동 40
 
7.1%
비산동 26
 
4.6%
내당동 24
 
4.3%
1층 15
 
2.7%
중리동 6
 
1.1%
27 4
 
0.7%
원대동3가 4
 
0.7%
12 4
 
0.7%
Other values (170) 223
39.8%
2024-03-15T02:24:28.884226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
453
 
16.1%
구 232
 
8.2%
서 135
 
4.8%
대 135
 
4.8%
1 111
 
3.9%
동 109
 
3.9%
시 108
 
3.8%
광 107
 
3.8%
로 107
 
3.8%
역 107
 
3.8%
Other values (62) 1214
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1634
58.0%
Decimal Number 468
 
16.6%
Space Separator 453
 
16.1%
Close Punctuation 106
 
3.8%
Open Punctuation 106
 
3.8%
Dash Punctuation 29
 
1.0%
Other Punctuation 21
 
0.7%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 232
14.2%
서 135
 
8.3%
대 135
 
8.3%
동 109
 
6.7%
시 108
 
6.6%
광 107
 
6.5%
로 107
 
6.5%
역 107
 
6.5%
길 99
 
6.1%
리 56
 
3.4%
Other values (46) 439
26.9%
Decimal Number
ValueCountFrequency (%)
1 111
23.7%
3 60
12.8%
2 59
12.6%
5 54
11.5%
4 51
10.9%
7 37
 
7.9%
6 36
 
7.7%
8 26
 
5.6%
0 20
 
4.3%
9 14
 
3.0%
Space Separator
ValueCountFrequency (%)
453
100.0%
Close Punctuation
ValueCountFrequency (%)
) 106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1634
58.0%
Common 1183
42.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 232
14.2%
서 135
 
8.3%
대 135
 
8.3%
동 109
 
6.7%
시 108
 
6.6%
광 107
 
6.5%
로 107
 
6.5%
역 107
 
6.5%
길 99
 
6.1%
리 56
 
3.4%
Other values (46) 439
26.9%
Common
ValueCountFrequency (%)
453
38.3%
1 111
 
9.4%
) 106
 
9.0%
( 106
 
9.0%
3 60
 
5.1%
2 59
 
5.0%
5 54
 
4.6%
4 51
 
4.3%
7 37
 
3.1%
6 36
 
3.0%
Other values (5) 110
 
9.3%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1634
58.0%
ASCII 1184
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
453
38.3%
1 111
 
9.4%
) 106
 
9.0%
( 106
 
9.0%
3 60
 
5.1%
2 59
 
5.0%
5 54
 
4.6%
4 51
 
4.3%
7 37
 
3.1%
6 36
 
3.0%
Other values (6) 111
 
9.4%
Hangul
ValueCountFrequency (%)
구 232
14.2%
서 135
 
8.3%
대 135
 
8.3%
동 109
 
6.7%
시 108
 
6.6%
광 107
 
6.5%
로 107
 
6.5%
역 107
 
6.5%
길 99
 
6.1%
리 56
 
3.4%
Other values (46) 439
26.9%

소재지전화
Text

MISSING 

Distinct102
Distinct (%)100.0%
Missing5
Missing (%)4.7%
Memory size984.0 B
2024-03-15T02:24:29.971418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.970588
Min length9

Characters and Unicode

Total characters1221
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

Unique102 ?
Unique (%)100.0%

Sample

1st row053-557-3457
2nd row053-555-2530
3rd row053-558-1815
4th row053-554-9010
5th row053-562-5125
ValueCountFrequency (%)
053-567-8587 1
 
1.0%
053-358-7326 1
 
1.0%
053-566-4207 1
 
1.0%
053-566-2364 1
 
1.0%
053-566-3007 1
 
1.0%
053-566-7180 1
 
1.0%
053-522-7258 1
 
1.0%
053-555-2950 1
 
1.0%
053-553-4152 1
 
1.0%
053-555-0785 1
 
1.0%
Other values (92) 92
90.2%
2024-03-15T02:24:31.164524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 303
24.8%
- 204
16.7%
3 172
14.1%
0 148
12.1%
6 77
 
6.3%
2 64
 
5.2%
7 63
 
5.2%
4 53
 
4.3%
8 52
 
4.3%
1 46
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1017
83.3%
Dash Punctuation 204
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 303
29.8%
3 172
16.9%
0 148
14.6%
6 77
 
7.6%
2 64
 
6.3%
7 63
 
6.2%
4 53
 
5.2%
8 52
 
5.1%
1 46
 
4.5%
9 39
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1221
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 303
24.8%
- 204
16.7%
3 172
14.1%
0 148
12.1%
6 77
 
6.3%
2 64
 
5.2%
7 63
 
5.2%
4 53
 
4.3%
8 52
 
4.3%
1 46
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 303
24.8%
- 204
16.7%
3 172
14.1%
0 148
12.1%
6 77
 
6.3%
2 64
 
5.2%
7 63
 
5.2%
4 53
 
4.3%
8 52
 
4.3%
1 46
 
3.8%

Interactions

2024-03-15T02:24:22.001207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:24:31.331667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명
연번1.0000.394
업소명0.3941.000

Missing values

2024-03-15T02:24:22.311090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:24:22.639876image/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

연번업소명영업소 주소(도로명)소재지전화
01현대대구광역시 서구 당산로45길 46, 1층053-557-3457
12월성세탁소대구광역시 서구 북비산로31길 11 (평리동)053-555-2530
23미조사세탁소대구광역시 서구 국채보상로50길 47 (평리동)053-558-1815
34서대구세탁소대구광역시 서구 서대구로44길 25 (평리동)053-554-9010
45크린세탁소대구광역시 서구 북비산로50길 12 (평리동)053-562-5125
56금스세탁소대구광역시 서구 문화로49길 18 (평리동)053-552-4249
67동일컴퓨터세탁소대구광역시 서구 평리로50길 40, 1층 (내당동)053-558-3463
78대진세탁소대구광역시 서구 서대구로21길 24 (평리동)053-558-8362
89황제세탁소대구광역시 서구 통학로 39, 상가동 101호 (내당동,홍실 2차)053-563-1150
910비룡세탁소대구광역시 서구 북비산로67길 4 (비산동)053-561-7256
연번업소명영업소 주소(도로명)소재지전화
9798태양세탁소대구광역시 서구 국채보상로48길 54 (평리동)<NA>
9899금수세탁소대구광역시 서구 국채보상로36길 41-16, 1층 (중리동)053-552-6542
99100윤일세탁소대구광역시 서구 달서로25길 15 (비산동)566-0088-
100101롯데명품세탁대구광역시 서구 국채보상로 316, 304동 지하 1층 102호 (평리동)053-567-0044
101102빨래장이대구광역시 서구 달서천로 395, 1층 (원대동1가)053-522-7883
102103시장명품세탁대구광역시 서구 원대로13길 54 (원대동3가)053-353-1327
103104동해세탁소대구광역시 서구 문화로69길 7, 1층 (비산동)<NA>
104105운동화빨래방대구광역시 서구 통학로23길 12, 1층 (평리동)<NA>
105106서부세탁소대구광역시 서구 통학로49길 55, 1층 (평리동)053-561-9390
106107호돌이크리닝대구광역시 서구 통학로 111-1 (평리동)<NA>