Overview

Dataset statistics

Number of variables4
Number of observations318
Missing cells204
Missing cells (%)16.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory32.4 B

Variable types

Text4

Dataset

Description대구광역시 서구 관내의 의료기기판매업소 및 수리업소 현황 데이터이며 영업소명, 주소, 전화번호의 데이터를 포함합니다.
Author대구광역시 서구
URLhttps://www.data.go.kr/data/15103408/fileData.do

Alerts

전화번호 has 204 (64.2%) missing valuesMissing

Reproduction

Analysis started2024-03-14 19:12:33.801356
Analysis finished2024-03-14 19:12:34.875335
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Text

Distinct309
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-15T04:12:36.486017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.6006289
Min length1

Characters and Unicode

Total characters827
Distinct characters12
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

Unique300 ?
Unique (%)94.3%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
1 2
 
0.6%
3 2
 
0.6%
9 2
 
0.6%
8 2
 
0.6%
7 2
 
0.6%
2 2
 
0.6%
5 2
 
0.6%
4 2
 
0.6%
6 2
 
0.6%
202 1
 
0.3%
Other values (299) 299
94.0%
2024-03-15T04:12:38.750859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 162
19.6%
2 162
19.6%
3 71
8.6%
6 62
 
7.5%
4 62
 
7.5%
5 62
 
7.5%
7 62
 
7.5%
8 62
 
7.5%
9 61
 
7.4%
0 59
 
7.1%
Other values (2) 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 825
99.8%
Other Letter 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 162
19.6%
2 162
19.6%
3 71
8.6%
6 62
 
7.5%
4 62
 
7.5%
5 62
 
7.5%
7 62
 
7.5%
8 62
 
7.5%
9 61
 
7.4%
0 59
 
7.2%
Other Letter
ValueCountFrequency (%)
순 1
50.0%
번 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 825
99.8%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 162
19.6%
2 162
19.6%
3 71
8.6%
6 62
 
7.5%
4 62
 
7.5%
5 62
 
7.5%
7 62
 
7.5%
8 62
 
7.5%
9 61
 
7.4%
0 59
 
7.2%
Hangul
ValueCountFrequency (%)
순 1
50.0%
번 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 825
99.8%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 162
19.6%
2 162
19.6%
3 71
8.6%
6 62
 
7.5%
4 62
 
7.5%
5 62
 
7.5%
7 62
 
7.5%
8 62
 
7.5%
9 61
 
7.4%
0 59
 
7.2%
Hangul
ValueCountFrequency (%)
순 1
50.0%
번 1
50.0%

영업소명
Text

Distinct310
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-15T04:12:39.835701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.9591195
Min length2

Characters and Unicode

Total characters2531
Distinct characters320
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302 ?
Unique (%)95.0%

Sample

1st row유투프로
2nd row씨유화성파크드림서대구점
3rd row강고랑
4th row씨유 서대구센트럴자이원대점
5th row메인 메디
ValueCountFrequency (%)
세븐일레븐 21
 
4.7%
씨유 18
 
4.1%
주식회사 13
 
2.9%
gs25 11
 
2.5%
지에스(gs)25 7
 
1.6%
내당점 5
 
1.1%
대구점 3
 
0.7%
이마트24 3
 
0.7%
cu 3
 
0.7%
주)코리아세븐 3
 
0.7%
Other values (335) 357
80.4%
2024-03-15T04:12:41.245594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
5.0%
점 110
 
4.3%
대 90
 
3.6%
구 83
 
3.3%
메 65
 
2.6%
디 65
 
2.6%
리 62
 
2.4%
스 62
 
2.4%
이 49
 
1.9%
븐 45
 
1.8%
Other values (310) 1774
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2097
82.9%
Uppercase Letter 128
 
5.1%
Space Separator 126
 
5.0%
Decimal Number 75
 
3.0%
Close Punctuation 44
 
1.7%
Open Punctuation 44
 
1.7%
Lowercase Letter 10
 
0.4%
Other Punctuation 5
 
0.2%
Other Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 110
 
5.2%
대 90
 
4.3%
구 83
 
4.0%
메 65
 
3.1%
디 65
 
3.1%
리 62
 
3.0%
스 62
 
3.0%
이 49
 
2.3%
븐 45
 
2.1%
주 42
 
2.0%
Other values (269) 1424
67.9%
Uppercase Letter
ValueCountFrequency (%)
S 34
26.6%
G 29
22.7%
C 12
 
9.4%
U 8
 
6.2%
H 6
 
4.7%
O 5
 
3.9%
K 5
 
3.9%
A 4
 
3.1%
T 4
 
3.1%
E 3
 
2.3%
Other values (9) 18
14.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
20.0%
r 2
20.0%
g 1
10.0%
i 1
10.0%
c 1
10.0%
u 1
10.0%
e 1
10.0%
h 1
10.0%
Decimal Number
ValueCountFrequency (%)
2 36
48.0%
5 32
42.7%
4 4
 
5.3%
3 2
 
2.7%
1 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
& 2
40.0%
. 1
20.0%
· 1
20.0%
, 1
20.0%
Space Separator
ValueCountFrequency (%)
126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2098
82.9%
Common 295
 
11.7%
Latin 138
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 110
 
5.2%
대 90
 
4.3%
구 83
 
4.0%
메 65
 
3.1%
디 65
 
3.1%
리 62
 
3.0%
스 62
 
3.0%
이 49
 
2.3%
븐 45
 
2.1%
주 42
 
2.0%
Other values (270) 1425
67.9%
Latin
ValueCountFrequency (%)
S 34
24.6%
G 29
21.0%
C 12
 
8.7%
U 8
 
5.8%
H 6
 
4.3%
O 5
 
3.6%
K 5
 
3.6%
A 4
 
2.9%
T 4
 
2.9%
E 3
 
2.2%
Other values (17) 28
20.3%
Common
ValueCountFrequency (%)
126
42.7%
) 44
 
14.9%
( 44
 
14.9%
2 36
 
12.2%
5 32
 
10.8%
4 4
 
1.4%
& 2
 
0.7%
3 2
 
0.7%
. 1
 
0.3%
1 1
 
0.3%
Other values (3) 3
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2097
82.9%
ASCII 432
 
17.1%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
29.2%
) 44
 
10.2%
( 44
 
10.2%
2 36
 
8.3%
S 34
 
7.9%
5 32
 
7.4%
G 29
 
6.7%
C 12
 
2.8%
U 8
 
1.9%
H 6
 
1.4%
Other values (29) 61
14.1%
Hangul
ValueCountFrequency (%)
점 110
 
5.2%
대 90
 
4.3%
구 83
 
4.0%
메 65
 
3.1%
디 65
 
3.1%
리 62
 
3.0%
스 62
 
3.0%
이 49
 
2.3%
븐 45
 
2.1%
주 42
 
2.0%
Other values (269) 1424
67.9%
None
ValueCountFrequency (%)
㈜ 1
50.0%
· 1
50.0%

영업소소재지(도로명)
Text

Distinct301
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-15T04:12:42.535978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length45
Mean length28.918239
Min length11

Characters and Unicode

Total characters9196
Distinct characters148
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)89.3%

Sample

1st row대구광역시 서구 서대구로7길 11, 3층 (내당동)
2nd row대구광역시 서구 서대구로29길 30, 7111동 2호 (평리동, 서대구역화성파크드림)
3rd row대구광역시 서구 서대구로8길 49, 2동 101호 (내당동, 내당보성홍실아파트)
4th row대구광역시 서구 고성로 33, 상가동402동 1층 108호 (원대동3가, 서대구센트럴자이)
5th row대구광역시 서구 국채보상로61길 32, 1층 (평리동)
ValueCountFrequency (%)
대구광역시 317
 
16.9%
서구 316
 
16.9%
1층 111
 
5.9%
평리동 79
 
4.2%
비산동 66
 
3.5%
내당동 66
 
3.5%
중리동 41
 
2.2%
2층 32
 
1.7%
국채보상로 31
 
1.7%
달구벌대로 20
 
1.1%
Other values (424) 793
42.4%
2024-03-15T04:12:44.303578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1554
 
16.9%
구 717
 
7.8%
대 423
 
4.6%
1 416
 
4.5%
서 399
 
4.3%
동 343
 
3.7%
광 321
 
3.5%
역 321
 
3.5%
시 318
 
3.5%
) 317
 
3.4%
Other values (138) 4067
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5126
55.7%
Decimal Number 1567
 
17.0%
Space Separator 1554
 
16.9%
Close Punctuation 317
 
3.4%
Open Punctuation 317
 
3.4%
Other Punctuation 255
 
2.8%
Dash Punctuation 55
 
0.6%
Uppercase Letter 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 717
14.0%
대 423
 
8.3%
서 399
 
7.8%
동 343
 
6.7%
광 321
 
6.3%
역 321
 
6.3%
시 318
 
6.2%
로 317
 
6.2%
리 186
 
3.6%
층 182
 
3.6%
Other values (120) 1599
31.2%
Decimal Number
ValueCountFrequency (%)
1 416
26.5%
2 229
14.6%
3 209
13.3%
0 119
 
7.6%
4 118
 
7.5%
5 116
 
7.4%
7 113
 
7.2%
6 103
 
6.6%
8 79
 
5.0%
9 65
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 3
75.0%
B 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1554
100.0%
Close Punctuation
ValueCountFrequency (%)
) 317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 317
100.0%
Other Punctuation
ValueCountFrequency (%)
, 255
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5126
55.7%
Common 4065
44.2%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 717
14.0%
대 423
 
8.3%
서 399
 
7.8%
동 343
 
6.7%
광 321
 
6.3%
역 321
 
6.3%
시 318
 
6.2%
로 317
 
6.2%
리 186
 
3.6%
층 182
 
3.6%
Other values (120) 1599
31.2%
Common
ValueCountFrequency (%)
1554
38.2%
1 416
 
10.2%
) 317
 
7.8%
( 317
 
7.8%
, 255
 
6.3%
2 229
 
5.6%
3 209
 
5.1%
0 119
 
2.9%
4 118
 
2.9%
5 116
 
2.9%
Other values (5) 415
 
10.2%
Latin
ValueCountFrequency (%)
A 3
60.0%
c 1
 
20.0%
B 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5126
55.7%
ASCII 4070
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1554
38.2%
1 416
 
10.2%
) 317
 
7.8%
( 317
 
7.8%
, 255
 
6.3%
2 229
 
5.6%
3 209
 
5.1%
0 119
 
2.9%
4 118
 
2.9%
5 116
 
2.9%
Other values (8) 420
 
10.3%
Hangul
ValueCountFrequency (%)
구 717
14.0%
대 423
 
8.3%
서 399
 
7.8%
동 343
 
6.7%
광 321
 
6.3%
역 321
 
6.3%
시 318
 
6.2%
로 317
 
6.2%
리 186
 
3.6%
층 182
 
3.6%
Other values (120) 1599
31.2%

전화번호
Text

MISSING 

Distinct110
Distinct (%)96.5%
Missing204
Missing (%)64.2%
Memory size2.6 KiB
2024-03-15T04:12:45.255095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.894737
Min length4

Characters and Unicode

Total characters1356
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)93.0%

Sample

1st row1577-0711
2nd row053-524-8789
3rd row053-527-4082
4th row053-572-6675
5th row053-421-9755
ValueCountFrequency (%)
053-581-5114 2
 
1.8%
053-558-2605 2
 
1.8%
053-573-8248 2
 
1.8%
053-561-0220 2
 
1.8%
053-573-1110 1
 
0.9%
053-954-0674 1
 
0.9%
055-553-1445 1
 
0.9%
053-571-0119 1
 
0.9%
053-526-2417 1
 
0.9%
053-635-2556 1
 
0.9%
Other values (100) 100
87.7%
2024-03-15T04:12:46.416670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 289
21.3%
- 224
16.5%
3 185
13.6%
0 169
12.5%
2 95
 
7.0%
6 80
 
5.9%
1 75
 
5.5%
4 67
 
4.9%
8 63
 
4.6%
7 57
 
4.2%
Other values (5) 52
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1128
83.2%
Dash Punctuation 224
 
16.5%
Other Letter 4
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 289
25.6%
3 185
16.4%
0 169
15.0%
2 95
 
8.4%
6 80
 
7.1%
1 75
 
6.6%
4 67
 
5.9%
8 63
 
5.6%
7 57
 
5.1%
9 48
 
4.3%
Other Letter
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 224
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1352
99.7%
Hangul 4
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
5 289
21.4%
- 224
16.6%
3 185
13.7%
0 169
12.5%
2 95
 
7.0%
6 80
 
5.9%
1 75
 
5.5%
4 67
 
5.0%
8 63
 
4.7%
7 57
 
4.2%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1352
99.7%
Hangul 4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 289
21.4%
- 224
16.6%
3 185
13.7%
0 169
12.5%
2 95
 
7.0%
6 80
 
5.9%
1 75
 
5.5%
4 67
 
5.0%
8 63
 
4.7%
7 57
 
4.2%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Missing values

2024-03-15T04:12:34.468488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:12:34.756880image/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

순번영업소명영업소소재지(도로명)전화번호
01유투프로대구광역시 서구 서대구로7길 11, 3층 (내당동)<NA>
12씨유화성파크드림서대구점대구광역시 서구 서대구로29길 30, 7111동 2호 (평리동, 서대구역화성파크드림)<NA>
23강고랑대구광역시 서구 서대구로8길 49, 2동 101호 (내당동, 내당보성홍실아파트)<NA>
34씨유 서대구센트럴자이원대점대구광역시 서구 고성로 33, 상가동402동 1층 108호 (원대동3가, 서대구센트럴자이)<NA>
45메인 메디대구광역시 서구 국채보상로61길 32, 1층 (평리동)<NA>
56GS25 서대구서한퍼스트점대구광역시 서구 국채보상로37길 38, 10호 (평리동, 서대구역서한이다음더퍼스트)<NA>
67카포포대구광역시 서구 서대구로40길 3-1, 1층 (평리동)<NA>
78세븐일레븐 대구내당뉴타운점대구광역시 서구 서대구로5길 71, 1층 (내당동)<NA>
89세븐일레븐 대구이현공단점대구광역시 서구 와룡로 377, 1층 (중리동)<NA>
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