Overview

Dataset statistics

Number of variables7
Number of observations1246
Missing cells125
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory68.3 KiB
Average record size in memory56.1 B

Variable types

Categorical2
Text5

Dataset

Description전라남도 나주시 나주사랑상품권 가맹점(가맹점명, 소재지주소, 주요 상품, 전화번호 등) 정보
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15050386/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
주요상품 has 31 (2.5%) missing valuesMissing
전화번호 has 93 (7.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 00:56:23.397080
Analysis finished2023-12-12 00:56:24.579418
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
도소매업
608 
음식업
424 
주유소.충전소 등
110 
개인서비스업
 
42
병의원.약국
 
41
Other values (2)
 
21

Length

Max length9
Median length6
Mean length4.20626
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주유소.충전소 등
2nd row주유소.충전소 등
3rd row도소매업
4th row도소매업
5th row도소매업

Common Values

ValueCountFrequency (%)
도소매업 608
48.8%
음식업 424
34.0%
주유소.충전소 등 110
 
8.8%
개인서비스업 42
 
3.4%
병의원.약국 41
 
3.3%
학원 14
 
1.1%
숙박업 7
 
0.6%

Length

2023-12-12T09:56:24.671406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:56:24.840368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도소매업 608
44.8%
음식업 424
31.3%
주유소.충전소 110
 
8.1%
등 110
 
8.1%
개인서비스업 42
 
3.1%
병의원.약국 41
 
3.0%
학원 14
 
1.0%
숙박업 7
 
0.5%

업소명
Text

Distinct1223
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2023-12-12T09:56:25.201960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length5.8491172
Min length2

Characters and Unicode

Total characters7288
Distinct characters610
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

Unique1204 ?
Unique (%)96.6%

Sample

1st row(유)산포자동차공업사
2nd row(유)예향에너지
3rd row(유)한일상사
4th row(유)합동상사
5th row(자)신성가축약품
ValueCountFrequency (%)
나주혁신점 20
 
1.4%
하나로마트 13
 
0.9%
나주점 11
 
0.8%
주식회사 9
 
0.6%
어물 4
 
0.3%
빛가람점 4
 
0.3%
나주혁신도시점 3
 
0.2%
파리바게뜨 3
 
0.2%
농업회사법인 3
 
0.2%
유한회사 3
 
0.2%
Other values (1328) 1366
94.9%
2023-12-12T09:56:25.831309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 226
 
3.1%
193
 
2.6%
나 184
 
2.5%
점 143
 
2.0%
식 117
 
1.6%
이 109
 
1.5%
리 99
 
1.4%
회 99
 
1.4%
산 96
 
1.3%
원 92
 
1.3%
Other values (600) 5930
81.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6774
92.9%
Space Separator 193
 
2.6%
Decimal Number 92
 
1.3%
Uppercase Letter 90
 
1.2%
Close Punctuation 44
 
0.6%
Open Punctuation 44
 
0.6%
Lowercase Letter 36
 
0.5%
Other Punctuation 11
 
0.2%
Other Symbol 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 226
 
3.3%
나 184
 
2.7%
점 143
 
2.1%
식 117
 
1.7%
이 109
 
1.6%
리 99
 
1.5%
회 99
 
1.5%
산 96
 
1.4%
원 92
 
1.4%
사 91
 
1.3%
Other values (547) 5518
81.5%
Uppercase Letter
ValueCountFrequency (%)
G 10
 
11.1%
L 8
 
8.9%
S 8
 
8.9%
C 7
 
7.8%
O 7
 
7.8%
E 6
 
6.7%
M 6
 
6.7%
P 4
 
4.4%
J 4
 
4.4%
I 4
 
4.4%
Other values (12) 26
28.9%
Lowercase Letter
ValueCountFrequency (%)
o 7
19.4%
r 5
13.9%
e 4
11.1%
k 4
11.1%
t 3
8.3%
y 3
8.3%
s 2
 
5.6%
v 2
 
5.6%
a 2
 
5.6%
c 2
 
5.6%
Other values (2) 2
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 17
18.5%
5 16
17.4%
0 15
16.3%
2 12
13.0%
3 10
10.9%
6 7
7.6%
4 6
 
6.5%
8 4
 
4.3%
9 3
 
3.3%
7 2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
& 6
54.5%
, 2
 
18.2%
. 2
 
18.2%
' 1
 
9.1%
Space Separator
ValueCountFrequency (%)
193
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6776
93.0%
Common 386
 
5.3%
Latin 126
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 226
 
3.3%
나 184
 
2.7%
점 143
 
2.1%
식 117
 
1.7%
이 109
 
1.6%
리 99
 
1.5%
회 99
 
1.5%
산 96
 
1.4%
원 92
 
1.4%
사 91
 
1.3%
Other values (548) 5520
81.5%
Latin
ValueCountFrequency (%)
G 10
 
7.9%
L 8
 
6.3%
S 8
 
6.3%
C 7
 
5.6%
o 7
 
5.6%
O 7
 
5.6%
E 6
 
4.8%
M 6
 
4.8%
r 5
 
4.0%
e 4
 
3.2%
Other values (24) 58
46.0%
Common
ValueCountFrequency (%)
193
50.0%
) 44
 
11.4%
( 44
 
11.4%
1 17
 
4.4%
5 16
 
4.1%
0 15
 
3.9%
2 12
 
3.1%
3 10
 
2.6%
6 7
 
1.8%
& 6
 
1.6%
Other values (8) 22
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6774
92.9%
ASCII 512
 
7.0%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 226
 
3.3%
나 184
 
2.7%
점 143
 
2.1%
식 117
 
1.7%
이 109
 
1.6%
리 99
 
1.5%
회 99
 
1.5%
산 96
 
1.4%
원 92
 
1.4%
사 91
 
1.3%
Other values (547) 5518
81.5%
ASCII
ValueCountFrequency (%)
193
37.7%
) 44
 
8.6%
( 44
 
8.6%
1 17
 
3.3%
5 16
 
3.1%
0 15
 
2.9%
2 12
 
2.3%
3 10
 
2.0%
G 10
 
2.0%
L 8
 
1.6%
Other values (42) 143
27.9%
None
ValueCountFrequency (%)
㈜ 2
100.0%

대표자
Text

Distinct1175
Distinct (%)94.4%
Missing1
Missing (%)0.1%
Memory size9.9 KiB
2023-12-12T09:56:26.295878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9911647
Min length1

Characters and Unicode

Total characters3724
Distinct characters225
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1112 ?
Unique (%)89.3%

Sample

1st row박정남
2nd row박종태
3rd row송영일
4th row노재액
5th row김영식
ValueCountFrequency (%)
최공섭 4
 
0.3%
이계익 3
 
0.2%
박창기 3
 
0.2%
김창용 3
 
0.2%
우대봉 3
 
0.2%
김옥기 3
 
0.2%
임선택 2
 
0.2%
김영선 2
 
0.2%
남일수 2
 
0.2%
김상언 2
 
0.2%
Other values (1166) 1219
97.8%
2023-12-12T09:56:26.941019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 274
 
7.4%
정 180
 
4.8%
이 171
 
4.6%
영 116
 
3.1%
박 107
 
2.9%
순 89
 
2.4%
자 68
 
1.8%
경 68
 
1.8%
최 68
 
1.8%
숙 68
 
1.8%
Other values (215) 2515
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3719
99.9%
Decimal Number 2
 
0.1%
Dash Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 274
 
7.4%
정 180
 
4.8%
이 171
 
4.6%
영 116
 
3.1%
박 107
 
2.9%
순 89
 
2.4%
자 68
 
1.8%
경 68
 
1.8%
최 68
 
1.8%
숙 68
 
1.8%
Other values (211) 2510
67.5%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3719
99.9%
Common 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 274
 
7.4%
정 180
 
4.8%
이 171
 
4.6%
영 116
 
3.1%
박 107
 
2.9%
순 89
 
2.4%
자 68
 
1.8%
경 68
 
1.8%
최 68
 
1.8%
숙 68
 
1.8%
Other values (211) 2510
67.5%
Common
ValueCountFrequency (%)
1 2
40.0%
- 1
20.0%
1
20.0%
, 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3719
99.9%
ASCII 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 274
 
7.4%
정 180
 
4.8%
이 171
 
4.6%
영 116
 
3.1%
박 107
 
2.9%
순 89
 
2.4%
자 68
 
1.8%
경 68
 
1.8%
최 68
 
1.8%
숙 68
 
1.8%
Other values (211) 2510
67.5%
ASCII
ValueCountFrequency (%)
1 2
40.0%
- 1
20.0%
1
20.0%
, 1
20.0%

주요상품
Text

MISSING 

Distinct516
Distinct (%)42.5%
Missing31
Missing (%)2.5%
Memory size9.9 KiB
2023-12-12T09:56:27.377442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length3.8049383
Min length1

Characters and Unicode

Total characters4623
Distinct characters331
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique393 ?
Unique (%)32.3%

Sample

1st row자동차종합수리
2nd rowLPG
3rd row주류
4th row주류도매
5th row가축약품
ValueCountFrequency (%)
한식 169
 
12.8%
일반음식점 53
 
4.0%
주유소 48
 
3.6%
의류 38
 
2.9%
어물 37
 
2.8%
잡화 28
 
2.1%
홍어 18
 
1.4%
중식 17
 
1.3%
치킨 16
 
1.2%
식육 13
 
1.0%
Other values (516) 885
66.9%
2023-12-12T09:56:27.991853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 359
 
7.8%
, 278
 
6.0%
한 191
 
4.1%
품 133
 
2.9%
107
 
2.3%
물 106
 
2.3%
어 98
 
2.1%
의 94
 
2.0%
류 92
 
2.0%
화 90
 
1.9%
Other values (321) 3075
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4093
88.5%
Other Punctuation 296
 
6.4%
Space Separator 107
 
2.3%
Uppercase Letter 74
 
1.6%
Open Punctuation 23
 
0.5%
Close Punctuation 23
 
0.5%
Dash Punctuation 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 359
 
8.8%
한 191
 
4.7%
품 133
 
3.2%
물 106
 
2.6%
어 98
 
2.4%
의 94
 
2.3%
류 92
 
2.2%
화 90
 
2.2%
일 80
 
2.0%
점 74
 
1.8%
Other values (306) 2776
67.8%
Uppercase Letter
ValueCountFrequency (%)
L 16
21.6%
S 16
21.6%
G 12
16.2%
P 10
13.5%
I 7
9.5%
O 7
9.5%
K 4
 
5.4%
C 1
 
1.4%
V 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 278
93.9%
. 18
 
6.1%
Space Separator
ValueCountFrequency (%)
107
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4093
88.5%
Common 456
 
9.9%
Latin 74
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 359
 
8.8%
한 191
 
4.7%
품 133
 
3.2%
물 106
 
2.6%
어 98
 
2.4%
의 94
 
2.3%
류 92
 
2.2%
화 90
 
2.2%
일 80
 
2.0%
점 74
 
1.8%
Other values (306) 2776
67.8%
Latin
ValueCountFrequency (%)
L 16
21.6%
S 16
21.6%
G 12
16.2%
P 10
13.5%
I 7
9.5%
O 7
9.5%
K 4
 
5.4%
C 1
 
1.4%
V 1
 
1.4%
Common
ValueCountFrequency (%)
, 278
61.0%
107
 
23.5%
( 23
 
5.0%
) 23
 
5.0%
. 18
 
3.9%
- 7
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4093
88.5%
ASCII 530
 
11.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 359
 
8.8%
한 191
 
4.7%
품 133
 
3.2%
물 106
 
2.6%
어 98
 
2.4%
의 94
 
2.3%
류 92
 
2.2%
화 90
 
2.2%
일 80
 
2.0%
점 74
 
1.8%
Other values (306) 2776
67.8%
ASCII
ValueCountFrequency (%)
, 278
52.5%
107
 
20.2%
( 23
 
4.3%
) 23
 
4.3%
. 18
 
3.4%
L 16
 
3.0%
S 16
 
3.0%
G 12
 
2.3%
P 10
 
1.9%
- 7
 
1.3%
Other values (5) 20
 
3.8%

소재지도로명주소
Text

Distinct1045
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2023-12-12T09:56:28.428440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length23.294543
Min length12

Characters and Unicode

Total characters29025
Distinct characters237
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique964 ?
Unique (%)77.4%

Sample

1st row전라남도 나주시 산포면 산포로 468-3
2nd row전라남도 나주시 이창동 34-1
3rd row전라남도 나주시 나주천2길 42 (금계동)
4th row전라남도 나주시 삼영1길 18 (삼영동)
5th row전라남도 나주시 남고문로 124 (죽림동)
ValueCountFrequency (%)
전라남도 1245
20.4%
나주시 1245
20.4%
나주로 123
 
2.0%
중앙동 84
 
1.4%
이창동 72
 
1.2%
풍물시장2길 66
 
1.1%
12-14 64
 
1.1%
영산포풍물시장 64
 
1.1%
남평읍 56
 
0.9%
청동길 55
 
0.9%
Other values (1155) 3016
49.5%
2023-12-12T09:56:29.030013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4863
 
16.8%
시 1517
 
5.2%
1 1501
 
5.2%
남 1436
 
4.9%
주 1428
 
4.9%
나 1425
 
4.9%
도 1284
 
4.4%
라 1261
 
4.3%
전 1259
 
4.3%
2 713
 
2.5%
Other values (227) 12338
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17050
58.7%
Decimal Number 5043
 
17.4%
Space Separator 4863
 
16.8%
Close Punctuation 573
 
2.0%
Open Punctuation 573
 
2.0%
Dash Punctuation 501
 
1.7%
Other Punctuation 291
 
1.0%
Uppercase Letter 117
 
0.4%
Lowercase Letter 8
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1517
 
8.9%
남 1436
 
8.4%
주 1428
 
8.4%
나 1425
 
8.4%
도 1284
 
7.5%
라 1261
 
7.4%
전 1259
 
7.4%
동 621
 
3.6%
로 617
 
3.6%
길 475
 
2.8%
Other values (201) 5727
33.6%
Decimal Number
ValueCountFrequency (%)
1 1501
29.8%
2 713
14.1%
4 523
 
10.4%
3 436
 
8.6%
0 406
 
8.1%
5 382
 
7.6%
6 333
 
6.6%
7 269
 
5.3%
8 264
 
5.2%
9 216
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 49
41.9%
A 28
23.9%
T 23
19.7%
B 12
 
10.3%
M 1
 
0.9%
H 1
 
0.9%
L 1
 
0.9%
G 1
 
0.9%
S 1
 
0.9%
Space Separator
ValueCountFrequency (%)
4863
100.0%
Close Punctuation
ValueCountFrequency (%)
) 573
100.0%
Open Punctuation
ValueCountFrequency (%)
( 573
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 501
100.0%
Other Punctuation
ValueCountFrequency (%)
, 291
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17050
58.7%
Common 11850
40.8%
Latin 125
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1517
 
8.9%
남 1436
 
8.4%
주 1428
 
8.4%
나 1425
 
8.4%
도 1284
 
7.5%
라 1261
 
7.4%
전 1259
 
7.4%
동 621
 
3.6%
로 617
 
3.6%
길 475
 
2.8%
Other values (201) 5727
33.6%
Common
ValueCountFrequency (%)
4863
41.0%
1 1501
 
12.7%
2 713
 
6.0%
) 573
 
4.8%
( 573
 
4.8%
4 523
 
4.4%
- 501
 
4.2%
3 436
 
3.7%
0 406
 
3.4%
5 382
 
3.2%
Other values (6) 1379
 
11.6%
Latin
ValueCountFrequency (%)
C 49
39.2%
A 28
22.4%
T 23
18.4%
B 12
 
9.6%
s 8
 
6.4%
M 1
 
0.8%
H 1
 
0.8%
L 1
 
0.8%
G 1
 
0.8%
S 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17050
58.7%
ASCII 11975
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4863
40.6%
1 1501
 
12.5%
2 713
 
6.0%
) 573
 
4.8%
( 573
 
4.8%
4 523
 
4.4%
- 501
 
4.2%
3 436
 
3.6%
0 406
 
3.4%
5 382
 
3.2%
Other values (16) 1504
 
12.6%
Hangul
ValueCountFrequency (%)
시 1517
 
8.9%
남 1436
 
8.4%
주 1428
 
8.4%
나 1425
 
8.4%
도 1284
 
7.5%
라 1261
 
7.4%
전 1259
 
7.4%
동 621
 
3.6%
로 617
 
3.6%
길 475
 
2.8%
Other values (201) 5727
33.6%

전화번호
Text

MISSING 

Distinct1124
Distinct (%)97.5%
Missing93
Missing (%)7.5%
Memory size9.9 KiB
2023-12-12T09:56:29.620368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.005204
Min length9

Characters and Unicode

Total characters13842
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

Unique1096 ?
Unique (%)95.1%

Sample

1st row061-337-1474
2nd row061-332-1141
3rd row061-332-8924
4th row061-334-3370
5th row061-332-6458
ValueCountFrequency (%)
061-334-4682 3
 
0.3%
061-337-3007 2
 
0.2%
070-7576-3252 2
 
0.2%
061-334-5035 2
 
0.2%
061-336-4646 2
 
0.2%
061-335-9101 2
 
0.2%
061-334-7726 2
 
0.2%
061-334-2936 2
 
0.2%
061-333-6060 2
 
0.2%
061-332-4693 2
 
0.2%
Other values (1114) 1132
98.2%
2023-12-12T09:56:30.076567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 3012
21.8%
- 2304
16.6%
0 1821
13.2%
1 1689
12.2%
6 1654
11.9%
2 735
 
5.3%
5 610
 
4.4%
4 597
 
4.3%
7 501
 
3.6%
9 471
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11538
83.4%
Dash Punctuation 2304
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 3012
26.1%
0 1821
15.8%
1 1689
14.6%
6 1654
14.3%
2 735
 
6.4%
5 610
 
5.3%
4 597
 
5.2%
7 501
 
4.3%
9 471
 
4.1%
8 448
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 2304
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13842
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 3012
21.8%
- 2304
16.6%
0 1821
13.2%
1 1689
12.2%
6 1654
11.9%
2 735
 
5.3%
5 610
 
4.4%
4 597
 
4.3%
7 501
 
3.6%
9 471
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13842
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 3012
21.8%
- 2304
16.6%
0 1821
13.2%
1 1689
12.2%
6 1654
11.9%
2 735
 
5.3%
5 610
 
4.4%
4 597
 
4.3%
7 501
 
3.6%
9 471
 
3.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2019-10-08
1246 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-10-08
2nd row2019-10-08
3rd row2019-10-08
4th row2019-10-08
5th row2019-10-08

Common Values

ValueCountFrequency (%)
2019-10-08 1246
100.0%

Length

2023-12-12T09:56:30.230569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:56:30.328225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-10-08 1246
100.0%

Missing values

2023-12-12T09:56:24.269993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:56:24.391537image/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.
2023-12-12T09:56:24.507980image/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

구분업소명대표자주요상품소재지도로명주소전화번호데이터기준일자
0주유소.충전소 등(유)산포자동차공업사박정남자동차종합수리전라남도 나주시 산포면 산포로 468-3061-337-14742019-10-08
1주유소.충전소 등(유)예향에너지박종태LPG전라남도 나주시 이창동 34-1061-332-11412019-10-08
2도소매업(유)한일상사송영일주류전라남도 나주시 나주천2길 42 (금계동)061-332-89242019-10-08
3도소매업(유)합동상사노재액주류도매전라남도 나주시 삼영1길 18 (삼영동)061-334-33702019-10-08
4도소매업(자)신성가축약품김영식가축약품전라남도 나주시 남고문로 124 (죽림동)061-332-64582019-10-08
5도소매업(주)광주식자재나주점김쌍섭종합식품센터, 식자재전라남도 나주시 나주로 65061-331-05002019-10-08
6도소매업(주)나주가스박철선부탕,프로판가스전라남도 나주시 문평면 다시로 86061-335-45002019-10-08
7도소매업(주)부농원송행숙농약,종자,비료,농자재전라남도 나주시 동점문길 15-1 (중앙동)061-334-72942019-10-08
8도소매업(주)사조화인코리아장운덕삼계, 오리, 가공품전라남도 나주시 금천면 금영로 792061-330-45722019-10-08
9도소매업(주)와이마트 나주혁신중흥점조양구슈퍼,부동산임대업전라남도 나주시 상야2길 7, 117,118호(중흥s클래스메가티움1차)061-335-90062019-10-08
구분업소명대표자주요상품소재지도로명주소전화번호데이터기준일자
1236음식업후포리 대게박순자한식전라남도 나주시 빛가람로 747, 1층 106호(메디칼빌딩)<NA>2019-10-08
1237음식업훈이네집임문자갈치,병어조림전라남도 나주시 나주로 134 (금성동)061-332-35792019-10-08
1238숙박업휠모텔양진용여관업전라남도 나주시 완사천길 3 시티힐모텔061-332-50462019-10-08
1239주유소.충전소 등흥국주유소최정옥주유소전라남도 나주시 건재로 330061-333-80082019-10-08
1240개인서비스업흥미이발관임정채이미용전라남도 나주시 영산포로 255(삼영동)061-334-30352019-10-08
1241음식업흥부네 감자탕김수경한식전라남도 나주시 나주로 83-4061-334-23102019-10-08
1242도소매업흥부원예사정일남농약,씨앗,농자재전라남도 나주시 이창동 752-8번지061-334-33382019-10-08
1243음식업흥신수산박경수홍어전라남도 나주시 영산포로 195(영산동)061-334-31182019-10-08
1244도소매업흥일방앗간윤순희떡,식품전라남도 나주시 남내1길 17(남내동)061-333-40402019-10-08
1245음식업히트(HIT)김선영한식전라남도 나주시 청동길 14, 매일동 A20호(나주목사고을시장)061-333-62952019-10-08