Overview

Dataset statistics

Number of variables9
Number of observations45
Missing cells2
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory74.9 B

Variable types

Text6
Categorical2
DateTime1

Dataset

Description경상북도 구미시에서 지정한 착한가격업소의 업소명, 주소, 전화번호, 품목, 가격등의 현황 데이터를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/3071693/fileData.do

Alerts

관리기관전화번호 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연락처 has 2 (4.4%) missing valuesMissing
업소명 has unique valuesUnique
도로명 주소 has unique valuesUnique
지번 주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:11:13.414295
Analysis finished2023-12-12 03:11:14.169179
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:11:14.367085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.8666667
Min length3

Characters and Unicode

Total characters264
Distinct characters146
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

Unique45 ?
Unique (%)100.0%

Sample

1st row어촌마을1호점
2nd row봉가네식당
3rd row거송순대식당
4th row자갈마당
5th row도리산암소한마리광평점
ValueCountFrequency (%)
어촌마을1호점 1
 
1.9%
옛날산골통닭 1
 
1.9%
럭키미용실 1
 
1.9%
돌곱창 1
 
1.9%
지산골잔치국수인동점 1
 
1.9%
실비회식당 1
 
1.9%
황상동닭한마리 1
 
1.9%
학천국수 1
 
1.9%
상모점 1
 
1.9%
여수동 1
 
1.9%
Other values (44) 44
81.5%
2023-12-12T12:11:14.883049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
3.4%
수 8
 
3.0%
식 8
 
3.0%
당 7
 
2.7%
국 7
 
2.7%
점 7
 
2.7%
리 5
 
1.9%
마 4
 
1.5%
산 4
 
1.5%
실 4
 
1.5%
Other values (136) 201
76.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 249
94.3%
Space Separator 9
 
3.4%
Decimal Number 6
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 8
 
3.2%
식 8
 
3.2%
당 7
 
2.8%
국 7
 
2.8%
점 7
 
2.8%
리 5
 
2.0%
마 4
 
1.6%
산 4
 
1.6%
실 4
 
1.6%
한 4
 
1.6%
Other values (132) 191
76.7%
Decimal Number
ValueCountFrequency (%)
0 4
66.7%
1 1
 
16.7%
2 1
 
16.7%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 249
94.3%
Common 15
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 8
 
3.2%
식 8
 
3.2%
당 7
 
2.8%
국 7
 
2.8%
점 7
 
2.8%
리 5
 
2.0%
마 4
 
1.6%
산 4
 
1.6%
실 4
 
1.6%
한 4
 
1.6%
Other values (132) 191
76.7%
Common
ValueCountFrequency (%)
9
60.0%
0 4
26.7%
1 1
 
6.7%
2 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 249
94.3%
ASCII 15
 
5.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
60.0%
0 4
26.7%
1 1
 
6.7%
2 1
 
6.7%
Hangul
ValueCountFrequency (%)
수 8
 
3.2%
식 8
 
3.2%
당 7
 
2.8%
국 7
 
2.8%
점 7
 
2.8%
리 5
 
2.0%
마 4
 
1.6%
산 4
 
1.6%
실 4
 
1.6%
한 4
 
1.6%
Other values (132) 191
76.7%

도로명 주소
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:11:15.275996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.622222
Min length15

Characters and Unicode

Total characters838
Distinct characters64
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row경상북도 구미시 형곡서로 42
2nd row경상북도 구미시 신시로26길 25
3rd row경상북도 구미시 백산로5길 17
4th row경상북도 구미시 선산읍 단계서길 39
5th row경상북도 구미시 구미대로18길 21
ValueCountFrequency (%)
경상북도 45
24.5%
구미시 45
24.5%
17 2
 
1.1%
30 2
 
1.1%
상사서로22길 2
 
1.1%
41 2
 
1.1%
39 2
 
1.1%
10 2
 
1.1%
25 2
 
1.1%
형곡서로 2
 
1.1%
Other values (78) 78
42.4%
2023-12-12T12:11:15.797435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
16.7%
상 50
 
6.0%
시 49
 
5.8%
구 48
 
5.7%
미 48
 
5.7%
도 46
 
5.5%
경 45
 
5.4%
북 45
 
5.4%
로 39
 
4.7%
1 38
 
4.5%
Other values (54) 290
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 516
61.6%
Decimal Number 161
 
19.2%
Space Separator 140
 
16.7%
Dash Punctuation 16
 
1.9%
Other Punctuation 4
 
0.5%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 50
9.7%
시 49
9.5%
구 48
9.3%
미 48
9.3%
도 46
8.9%
경 45
8.7%
북 45
8.7%
로 39
 
7.6%
길 35
 
6.8%
산 11
 
2.1%
Other values (40) 100
19.4%
Decimal Number
ValueCountFrequency (%)
1 38
23.6%
2 35
21.7%
4 22
13.7%
5 14
 
8.7%
3 13
 
8.1%
0 9
 
5.6%
7 9
 
5.6%
6 8
 
5.0%
9 7
 
4.3%
8 6
 
3.7%
Space Separator
ValueCountFrequency (%)
140
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 516
61.6%
Common 321
38.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 50
9.7%
시 49
9.5%
구 48
9.3%
미 48
9.3%
도 46
8.9%
경 45
8.7%
북 45
8.7%
로 39
 
7.6%
길 35
 
6.8%
산 11
 
2.1%
Other values (40) 100
19.4%
Common
ValueCountFrequency (%)
140
43.6%
1 38
 
11.8%
2 35
 
10.9%
4 22
 
6.9%
- 16
 
5.0%
5 14
 
4.4%
3 13
 
4.0%
0 9
 
2.8%
7 9
 
2.8%
6 8
 
2.5%
Other values (3) 17
 
5.3%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 516
61.6%
ASCII 322
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
43.5%
1 38
 
11.8%
2 35
 
10.9%
4 22
 
6.8%
- 16
 
5.0%
5 14
 
4.3%
3 13
 
4.0%
0 9
 
2.8%
7 9
 
2.8%
6 8
 
2.5%
Other values (4) 18
 
5.6%
Hangul
ValueCountFrequency (%)
상 50
9.7%
시 49
9.5%
구 48
9.3%
미 48
9.3%
도 46
8.9%
경 45
8.7%
북 45
8.7%
로 39
 
7.6%
길 35
 
6.8%
산 11
 
2.1%
Other values (40) 100
19.4%

지번 주소
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:11:16.139767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length18.066667
Min length16

Characters and Unicode

Total characters813
Distinct characters49
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

Unique45 ?
Unique (%)100.0%

Sample

1st row경상북도 구미시 형곡동 314-10
2nd row경상북도 구미시 송정동 10-6
3rd row경상북도 구미시 송정동 39-1
4th row경상북도 구미시 선산읍 완전리 155
5th row경상북도 구미시 광평동 66-1
ValueCountFrequency (%)
경상북도 45
24.6%
구미시 45
24.6%
송정동 7
 
3.8%
원평동 6
 
3.3%
형곡동 4
 
2.2%
사곡동 4
 
2.2%
도량동 4
 
2.2%
광평동 3
 
1.6%
황상동 2
 
1.1%
진평동 2
 
1.1%
Other values (57) 61
33.3%
2023-12-12T12:11:17.033901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
139
17.1%
도 49
 
6.0%
상 47
 
5.8%
경 45
 
5.5%
북 45
 
5.5%
구 45
 
5.5%
미 45
 
5.5%
시 45
 
5.5%
동 42
 
5.2%
- 38
 
4.7%
Other values (39) 273
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 459
56.5%
Decimal Number 177
 
21.8%
Space Separator 139
 
17.1%
Dash Punctuation 38
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 49
10.7%
상 47
10.2%
경 45
9.8%
북 45
9.8%
구 45
9.8%
미 45
9.8%
시 45
9.8%
동 42
9.2%
평 12
 
2.6%
곡 10
 
2.2%
Other values (27) 74
16.1%
Decimal Number
ValueCountFrequency (%)
1 27
15.3%
4 25
14.1%
6 21
11.9%
5 19
10.7%
2 17
9.6%
9 16
9.0%
0 15
8.5%
3 15
8.5%
8 13
7.3%
7 9
 
5.1%
Space Separator
ValueCountFrequency (%)
139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 459
56.5%
Common 354
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 49
10.7%
상 47
10.2%
경 45
9.8%
북 45
9.8%
구 45
9.8%
미 45
9.8%
시 45
9.8%
동 42
9.2%
평 12
 
2.6%
곡 10
 
2.2%
Other values (27) 74
16.1%
Common
ValueCountFrequency (%)
139
39.3%
- 38
 
10.7%
1 27
 
7.6%
4 25
 
7.1%
6 21
 
5.9%
5 19
 
5.4%
2 17
 
4.8%
9 16
 
4.5%
0 15
 
4.2%
3 15
 
4.2%
Other values (2) 22
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 459
56.5%
ASCII 354
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
139
39.3%
- 38
 
10.7%
1 27
 
7.6%
4 25
 
7.1%
6 21
 
5.9%
5 19
 
5.4%
2 17
 
4.8%
9 16
 
4.5%
0 15
 
4.2%
3 15
 
4.2%
Other values (2) 22
 
6.2%
Hangul
ValueCountFrequency (%)
도 49
10.7%
상 47
10.2%
경 45
9.8%
북 45
9.8%
구 45
9.8%
미 45
9.8%
시 45
9.8%
동 42
9.2%
평 12
 
2.6%
곡 10
 
2.2%
Other values (27) 74
16.1%

연락처
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing2
Missing (%)4.4%
Memory size492.0 B
2023-12-12T12:11:17.373897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.023256
Min length12

Characters and Unicode

Total characters517
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

Unique43 ?
Unique (%)100.0%

Sample

1st row054-454-2008
2nd row054-456-7809
3rd row054-457-8012
4th row054-482-3792
5th row054-462-9298
ValueCountFrequency (%)
054-457-5745 1
 
2.3%
054-454-2008 1
 
2.3%
054-462-3366 1
 
2.3%
054-456-4641 1
 
2.3%
054-451-3944 1
 
2.3%
054-456-3751 1
 
2.3%
054-482-4829 1
 
2.3%
054-471-4339 1
 
2.3%
054-461-8558 1
 
2.3%
054-472-3622 1
 
2.3%
Other values (33) 33
76.7%
2023-12-12T12:11:17.834256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 101
19.5%
5 91
17.6%
- 86
16.6%
0 65
12.6%
6 35
 
6.8%
8 29
 
5.6%
2 26
 
5.0%
3 26
 
5.0%
1 24
 
4.6%
7 18
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 431
83.4%
Dash Punctuation 86
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 101
23.4%
5 91
21.1%
0 65
15.1%
6 35
 
8.1%
8 29
 
6.7%
2 26
 
6.0%
3 26
 
6.0%
1 24
 
5.6%
7 18
 
4.2%
9 16
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 517
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 101
19.5%
5 91
17.6%
- 86
16.6%
0 65
12.6%
6 35
 
6.8%
8 29
 
5.6%
2 26
 
5.0%
3 26
 
5.0%
1 24
 
4.6%
7 18
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 101
19.5%
5 91
17.6%
- 86
16.6%
0 65
12.6%
6 35
 
6.8%
8 29
 
5.6%
2 26
 
5.0%
3 26
 
5.0%
1 24
 
4.6%
7 18
 
3.5%

품목
Text

Distinct40
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:11:18.175829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length16
Mean length10.866667
Min length2

Characters and Unicode

Total characters489
Distinct characters118
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

Unique36 ?
Unique (%)80.0%

Sample

1st row모듬회(중)+우럭(중)
2nd row돼지찌개+김치찌개
3rd row순대국밥+김치찌개
4th row칼국수+콩국수
5th row소고기국밥+곰탕
ValueCountFrequency (%)
잔치국수+칼국수 3
 
6.4%
목욕료 2
 
4.3%
아메리카노+카페라떼+카푸치노 2
 
4.3%
짜장면+짬뽕 2
 
4.3%
보리밥+국수 1
 
2.1%
모듬회(중)+우럭(중 1
 
2.1%
칼국수+칼제비 1
 
2.1%
커트(성인)+염색/펌 1
 
2.1%
된장+비빔밥+잔치국수 1
 
2.1%
광어(1kg)+우럭(1kg)+모듬회(소 1
 
2.1%
Other values (32) 32
68.1%
2023-12-12T12:11:18.774028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 54
 
11.0%
국 25
 
5.1%
( 23
 
4.7%
) 23
 
4.7%
수 22
 
4.5%
치 14
 
2.9%
0 13
 
2.7%
1 11
 
2.2%
g 11
 
2.2%
비 9
 
1.8%
Other values (108) 284
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
69.9%
Math Symbol 54
 
11.0%
Decimal Number 30
 
6.1%
Open Punctuation 23
 
4.7%
Close Punctuation 23
 
4.7%
Lowercase Letter 13
 
2.7%
Space Separator 2
 
0.4%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 25
 
7.3%
수 22
 
6.4%
치 14
 
4.1%
비 9
 
2.6%
칼 8
 
2.3%
리 8
 
2.3%
개 8
 
2.3%
밥 8
 
2.3%
장 8
 
2.3%
잔 7
 
2.0%
Other values (96) 225
65.8%
Decimal Number
ValueCountFrequency (%)
0 13
43.3%
1 11
36.7%
5 4
 
13.3%
3 1
 
3.3%
2 1
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
g 11
84.6%
k 2
 
15.4%
Math Symbol
ValueCountFrequency (%)
+ 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
69.9%
Common 134
 
27.4%
Latin 13
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 25
 
7.3%
수 22
 
6.4%
치 14
 
4.1%
비 9
 
2.6%
칼 8
 
2.3%
리 8
 
2.3%
개 8
 
2.3%
밥 8
 
2.3%
장 8
 
2.3%
잔 7
 
2.0%
Other values (96) 225
65.8%
Common
ValueCountFrequency (%)
+ 54
40.3%
( 23
17.2%
) 23
17.2%
0 13
 
9.7%
1 11
 
8.2%
5 4
 
3.0%
2
 
1.5%
/ 2
 
1.5%
3 1
 
0.7%
2 1
 
0.7%
Latin
ValueCountFrequency (%)
g 11
84.6%
k 2
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
69.9%
ASCII 147
30.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 54
36.7%
( 23
15.6%
) 23
15.6%
0 13
 
8.8%
1 11
 
7.5%
g 11
 
7.5%
5 4
 
2.7%
k 2
 
1.4%
2
 
1.4%
/ 2
 
1.4%
Other values (2) 2
 
1.4%
Hangul
ValueCountFrequency (%)
국 25
 
7.3%
수 22
 
6.4%
치 14
 
4.1%
비 9
 
2.6%
칼 8
 
2.3%
리 8
 
2.3%
개 8
 
2.3%
밥 8
 
2.3%
장 8
 
2.3%
잔 7
 
2.0%
Other values (96) 225
65.8%

가격
Text

Distinct32
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:11:19.089694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length9.8
Min length4

Characters and Unicode

Total characters441
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)53.3%

Sample

1st row30000
2nd row7000+7000
3rd row7000+7000
4th row5000+7000
5th row6000+6000
ValueCountFrequency (%)
6000 5
 
10.2%
5000+6000 4
 
8.2%
5000 3
 
6.1%
7000 3
 
6.1%
7000+7000 2
 
4.1%
5000+6000+6000 2
 
4.1%
23000 2
 
4.1%
6000+6000 2
 
4.1%
10000+30000 2
 
4.1%
2000+3000+3000 2
 
4.1%
Other values (22) 22
44.9%
2023-12-12T12:11:19.601995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 282
63.9%
+ 48
 
10.9%
5 29
 
6.6%
6 25
 
5.7%
3 18
 
4.1%
7 10
 
2.3%
2 8
 
1.8%
4 6
 
1.4%
1 5
 
1.1%
8 5
 
1.1%
Other values (2) 5
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 389
88.2%
Math Symbol 48
 
10.9%
Space Separator 4
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 282
72.5%
5 29
 
7.5%
6 25
 
6.4%
3 18
 
4.6%
7 10
 
2.6%
2 8
 
2.1%
4 6
 
1.5%
1 5
 
1.3%
8 5
 
1.3%
9 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
+ 48
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 441
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 282
63.9%
+ 48
 
10.9%
5 29
 
6.6%
6 25
 
5.7%
3 18
 
4.1%
7 10
 
2.3%
2 8
 
1.8%
4 6
 
1.4%
1 5
 
1.1%
8 5
 
1.1%
Other values (2) 5
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 282
63.9%
+ 48
 
10.9%
5 29
 
6.6%
6 25
 
5.7%
3 18
 
4.1%
7 10
 
2.3%
2 8
 
1.8%
4 6
 
1.4%
1 5
 
1.1%
8 5
 
1.1%
Other values (2) 5
 
1.1%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
054-480-2624
45 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row054-480-2624
2nd row054-480-2624
3rd row054-480-2624
4th row054-480-2624
5th row054-480-2624

Common Values

ValueCountFrequency (%)
054-480-2624 45
100.0%

Length

2023-12-12T12:11:19.786687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:19.912247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
054-480-2624 45
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
경상북도 구미시청
45 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도 구미시청
2nd row경상북도 구미시청
3rd row경상북도 구미시청
4th row경상북도 구미시청
5th row경상북도 구미시청

Common Values

ValueCountFrequency (%)
경상북도 구미시청 45
100.0%

Length

2023-12-12T12:11:20.032103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:20.170590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 45
50.0%
구미시청 45
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum2023-06-27 00:00:00
Maximum2023-06-27 00:00:00
2023-12-12T12:11:20.300194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:20.429621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T12:11:20.537419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명도로명 주소지번 주소연락처품목가격
업소명1.0001.0001.0001.0001.0001.000
도로명 주소1.0001.0001.0001.0001.0001.000
지번 주소1.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.000
품목1.0001.0001.0001.0001.0000.998
가격1.0001.0001.0001.0000.9981.000

Missing values

2023-12-12T12:11:13.937672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:11:14.090014image/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

업소명도로명 주소지번 주소연락처품목가격관리기관전화번호관리기관명데이터기준일자
0어촌마을1호점경상북도 구미시 형곡서로 42경상북도 구미시 형곡동 314-10054-454-2008모듬회(중)+우럭(중)30000054-480-2624경상북도 구미시청2023-06-27
1봉가네식당경상북도 구미시 신시로26길 25경상북도 구미시 송정동 10-6054-456-7809돼지찌개+김치찌개7000+7000054-480-2624경상북도 구미시청2023-06-27
2거송순대식당경상북도 구미시 백산로5길 17경상북도 구미시 송정동 39-1054-457-8012순대국밥+김치찌개7000+7000054-480-2624경상북도 구미시청2023-06-27
3자갈마당경상북도 구미시 선산읍 단계서길 39경상북도 구미시 선산읍 완전리 155054-482-3792칼국수+콩국수5000+7000054-480-2624경상북도 구미시청2023-06-27
4도리산암소한마리광평점경상북도 구미시 구미대로18길 21경상북도 구미시 광평동 66-1054-462-9298소고기국밥+곰탕6000+6000054-480-2624경상북도 구미시청2023-06-27
5원조일품국수경상북도 구미시 금오산로22길 13-2경상북도 구미시 원평동 409-19054-457-0362잔치국수+칼국수5000+6000054-480-2624경상북도 구미시청2023-06-27
6씨티클럽경상북도 구미시 금오대로14길 15-4경상북도 구미시 오태동 753-4054-465-6425커트6000054-480-2624경상북도 구미시청2023-06-27
7준헤어클럽경상북도 구미시 형곡로29길 24경상북도 구미시 형곡동 254054-453-3313커트+학생커트8000+7000054-480-2624경상북도 구미시청2023-06-27
8착한이발소경상북도 구미시 흥안로1길 4,D동 105호경상북도 구미시 옥계동 560-4054-475-8383이발+염색5000054-480-2624경상북도 구미시청2023-06-27
9궁전목욕탕경상북도 구미시 송정대로 102경상북도 구미시 송정동 456-4054-451-2902목욕료5000054-480-2624경상북도 구미시청2023-06-27
업소명도로명 주소지번 주소연락처품목가격관리기관전화번호관리기관명데이터기준일자
35할매기사식당경상북도 구미시 구미중앙로 30경상북도 구미시 원평동 59-9054-456-48151인분 뷔페6000054-480-2624경상북도 구미시청2023-06-27
36옛날산골통닭 봉곡점경상북도 구미시 봉곡서로 48경상북도 구미시 봉곡동 146-15054-454-7792한마리+닭똥집튀김8000+8000054-480-2624경상북도 구미시청2023-06-27
37남경회 만오천냥경상북도 구미시 들성로 27경상북도 구미시 원호리 393054-454-0788광어(소)+우럭(소)20000+20000054-480-2624경상북도 구미시청2023-06-27
38카페 낭랑경상북도 구미시 신시로16길 67경상북도 구미시 송정동 458-1054-455-3690아메리카노+카페라떼+카푸치노2000+3000+3000054-480-2624경상북도 구미시청2023-06-27
39다온국수경상북도 구미시 도봉로 5안길 6-1경상북도 구미시 도량동 325-3054-455-4808잔치국수+비빔국수+칼국수5000+6000+6000054-480-2624경상북도 구미시청2023-06-27
40가정식백반경상북도 구미시 구미대로 384-1경상북도 구미시 신평동 168-9054-461-4956백반+잔치국수+칼국수5000+4000+5000054-480-2624경상북도 구미시청2023-06-27
41사곡맛깔뷔페경상북도 구미시 상사동로22길 8경상북도 구미시 사곡동 686-2054-464-9125보리밥뷔페4000054-480-2624경상북도 구미시청2023-06-27
42알밥국시경상북도 구미시 상사동로27길 25경상북도 구미시 사곡동 664-9054-461-6656잔치국수+비빔국수+수제돈가스(150g)5000+6000+6000054-480-2624경상북도 구미시청2023-06-27
43둥실원식당경상북도 구미시 금오산로12길 5-1경상북도 구미시 원평동 429-21054-453-1461짜장면+짬뽕+짬뽕밥+탕수육3500+4500+5000+9000054-480-2624경상북도 구미시청2023-06-27
44철수와 영희 미용실경상북도 구미시 송동로7길 33경상북도 구미시 도량동 99-4054-456-6287커트(남/여)+전체염색10000+30000054-480-2624경상북도 구미시청2023-06-27