Overview

Dataset statistics

Number of variables10
Number of observations281
Missing cells127
Missing cells (%)4.5%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory22.1 KiB
Average record size in memory80.5 B

Variable types

Categorical4
Text4
DateTime2

Dataset

Description경상남도 창녕군 관내 담배소매인 지정 현황 정보(시군명, 소매인구분, 업소명, 지번주소, 도로명주소, 영업상태, 지정일자, 데이터기준일자)
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15035661

Alerts

시군명 has constant value ""Constant
민원구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 1 (0.4%) duplicate rowsDuplicates
소매인구분 is highly overall correlated with 영업상태High correlation
영업상태 is highly overall correlated with 소매인구분High correlation
업소명 has 20 (7.1%) missing valuesMissing
전화번호 has 107 (38.1%) missing valuesMissing

Reproduction

Analysis started2023-12-11 00:17:36.021016
Analysis finished2023-12-11 00:17:36.873682
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
경상남도 창녕군
281 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 창녕군
2nd row경상남도 창녕군
3rd row경상남도 창녕군
4th row경상남도 창녕군
5th row경상남도 창녕군

Common Values

ValueCountFrequency (%)
경상남도 창녕군 281
100.0%

Length

2023-12-11T09:17:36.950921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:37.054730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 281
50.0%
창녕군 281
50.0%

민원구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
일반
281 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row일반
3rd row일반
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 281
100.0%

Length

2023-12-11T09:17:37.161490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:37.269039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 281
100.0%

업소명
Text

MISSING 

Distinct234
Distinct (%)89.7%
Missing20
Missing (%)7.1%
Memory size2.3 KiB
2023-12-11T09:17:37.477976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length6.4904215
Min length1

Characters and Unicode

Total characters1694
Distinct characters288
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

Unique227 ?
Unique (%)87.0%

Sample

1st row타올백화점
2nd row이마트24 창녕봉산점
3rd row세븐일레븐 창녕터미널점
4th row세븐일레븐 부곡온천점
5th row이마트24 창녕대지점
ValueCountFrequency (%)
일용잡화 16
 
4.8%
세븐일레븐 11
 
3.3%
씨유 11
 
3.3%
이마트24 9
 
2.7%
잡화 8
 
2.4%
gs25 8
 
2.4%
창녕점 4
 
1.2%
성원c마트 2
 
0.6%
농협연쇄점 2
 
0.6%
남지상회 2
 
0.6%
Other values (251) 258
77.9%
2023-12-11T09:17:37.895174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 85
 
5.0%
71
 
4.2%
창 62
 
3.7%
녕 57
 
3.4%
마 51
 
3.0%
트 45
 
2.7%
지 39
 
2.3%
일 38
 
2.2%
븐 30
 
1.8%
화 29
 
1.7%
Other values (278) 1187
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1488
87.8%
Space Separator 71
 
4.2%
Decimal Number 64
 
3.8%
Uppercase Letter 43
 
2.5%
Close Punctuation 10
 
0.6%
Open Punctuation 10
 
0.6%
Lowercase Letter 6
 
0.4%
Dash Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 85
 
5.7%
창 62
 
4.2%
녕 57
 
3.8%
마 51
 
3.4%
트 45
 
3.0%
지 39
 
2.6%
일 38
 
2.6%
븐 30
 
2.0%
화 29
 
1.9%
잡 25
 
1.7%
Other values (249) 1027
69.0%
Uppercase Letter
ValueCountFrequency (%)
G 14
32.6%
S 12
27.9%
C 7
16.3%
U 3
 
7.0%
I 1
 
2.3%
A 1
 
2.3%
N 1
 
2.3%
M 1
 
2.3%
D 1
 
2.3%
R 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
2 26
40.6%
5 15
23.4%
4 10
 
15.6%
1 6
 
9.4%
6 2
 
3.1%
8 2
 
3.1%
9 2
 
3.1%
3 1
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
a 2
33.3%
t 1
16.7%
s 1
16.7%
i 1
16.7%
r 1
16.7%
Space Separator
ValueCountFrequency (%)
71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1488
87.8%
Common 157
 
9.3%
Latin 49
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 85
 
5.7%
창 62
 
4.2%
녕 57
 
3.8%
마 51
 
3.4%
트 45
 
3.0%
지 39
 
2.6%
일 38
 
2.6%
븐 30
 
2.0%
화 29
 
1.9%
잡 25
 
1.7%
Other values (249) 1027
69.0%
Latin
ValueCountFrequency (%)
G 14
28.6%
S 12
24.5%
C 7
14.3%
U 3
 
6.1%
a 2
 
4.1%
t 1
 
2.0%
I 1
 
2.0%
A 1
 
2.0%
s 1
 
2.0%
N 1
 
2.0%
Other values (6) 6
12.2%
Common
ValueCountFrequency (%)
71
45.2%
2 26
 
16.6%
5 15
 
9.6%
) 10
 
6.4%
( 10
 
6.4%
4 10
 
6.4%
1 6
 
3.8%
6 2
 
1.3%
8 2
 
1.3%
9 2
 
1.3%
Other values (3) 3
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1488
87.8%
ASCII 206
 
12.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 85
 
5.7%
창 62
 
4.2%
녕 57
 
3.8%
마 51
 
3.4%
트 45
 
3.0%
지 39
 
2.6%
일 38
 
2.6%
븐 30
 
2.0%
화 29
 
1.9%
잡 25
 
1.7%
Other values (249) 1027
69.0%
ASCII
ValueCountFrequency (%)
71
34.5%
2 26
 
12.6%
5 15
 
7.3%
G 14
 
6.8%
S 12
 
5.8%
) 10
 
4.9%
( 10
 
4.9%
4 10
 
4.9%
C 7
 
3.4%
1 6
 
2.9%
Other values (19) 25
 
12.1%

소재지지번주소
Text

Distinct266
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T09:17:38.150255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length38
Mean length23.782918
Min length1

Characters and Unicode

Total characters6683
Distinct characters152
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

Unique261 ?
Unique (%)92.9%

Sample

1st row경상남도 창녕군 부곡면 거문리 215-12
2nd row경상남도 창녕군 계성면 봉산리 24-9
3rd row경상남도 창녕군 창녕읍 교리 1040-1
4th row경상남도 창녕군 부곡면 거문리 224-1
5th row경상남도 창녕군 대지면 왕산리 24
ValueCountFrequency (%)
경상남도 270
 
17.1%
창녕군 270
 
17.1%
창녕읍 65
 
4.1%
남지읍 47
 
3.0%
1호 42
 
2.7%
부곡면 38
 
2.4%
남지리 36
 
2.3%
영산면 32
 
2.0%
거문리 24
 
1.5%
대합면 20
 
1.3%
Other values (383) 732
46.4%
2023-12-11T09:17:38.520299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1348
20.2%
남 355
 
5.3%
창 338
 
5.1%
녕 338
 
5.1%
지 323
 
4.8%
도 285
 
4.3%
상 275
 
4.1%
군 271
 
4.1%
경 270
 
4.0%
리 267
 
4.0%
Other values (142) 2613
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4193
62.7%
Space Separator 1348
 
20.2%
Decimal Number 1097
 
16.4%
Dash Punctuation 38
 
0.6%
Other Punctuation 3
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 355
 
8.5%
창 338
 
8.1%
녕 338
 
8.1%
지 323
 
7.7%
도 285
 
6.8%
상 275
 
6.6%
군 271
 
6.5%
경 270
 
6.4%
리 267
 
6.4%
번 227
 
5.4%
Other values (126) 1244
29.7%
Decimal Number
ValueCountFrequency (%)
1 214
19.5%
2 166
15.1%
3 128
11.7%
5 110
10.0%
6 88
8.0%
4 83
 
7.6%
9 83
 
7.6%
0 80
 
7.3%
8 73
 
6.7%
7 72
 
6.6%
Space Separator
ValueCountFrequency (%)
1348
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4193
62.7%
Common 2488
37.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 355
 
8.5%
창 338
 
8.1%
녕 338
 
8.1%
지 323
 
7.7%
도 285
 
6.8%
상 275
 
6.6%
군 271
 
6.5%
경 270
 
6.4%
리 267
 
6.4%
번 227
 
5.4%
Other values (126) 1244
29.7%
Common
ValueCountFrequency (%)
1348
54.2%
1 214
 
8.6%
2 166
 
6.7%
3 128
 
5.1%
5 110
 
4.4%
6 88
 
3.5%
4 83
 
3.3%
9 83
 
3.3%
0 80
 
3.2%
8 73
 
2.9%
Other values (5) 115
 
4.6%
Latin
ValueCountFrequency (%)
C 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4193
62.7%
ASCII 2490
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1348
54.1%
1 214
 
8.6%
2 166
 
6.7%
3 128
 
5.1%
5 110
 
4.4%
6 88
 
3.5%
4 83
 
3.3%
9 83
 
3.3%
0 80
 
3.2%
8 73
 
2.9%
Other values (6) 117
 
4.7%
Hangul
ValueCountFrequency (%)
남 355
 
8.5%
창 338
 
8.1%
녕 338
 
8.1%
지 323
 
7.7%
도 285
 
6.8%
상 275
 
6.6%
군 271
 
6.5%
경 270
 
6.4%
리 267
 
6.4%
번 227
 
5.4%
Other values (126) 1244
29.7%

소재지도로명주소
Text

Distinct273
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T09:17:38.736675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length21.366548
Min length1

Characters and Unicode

Total characters6004
Distinct characters171
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

Unique267 ?
Unique (%)95.0%

Sample

1st row경상남도 창녕군 부곡면 온천중앙로 15. 108호
2nd row경상남도 창녕군 계성면 영산장마로 644
3rd row경상남도 창녕군 창녕읍 창녕대로 11
4th row경상남도 창녕군 부곡면 온천중앙로 52
5th row경상남도 창녕군 대지면 억만미산로 43
ValueCountFrequency (%)
경상남도 278
19.4%
창녕군 278
19.4%
창녕읍 71
 
5.0%
남지읍 49
 
3.4%
부곡면 39
 
2.7%
영산면 32
 
2.2%
대합면 20
 
1.4%
계성면 12
 
0.8%
명덕로 11
 
0.8%
창녕대로 11
 
0.8%
Other values (356) 630
44.0%
2023-12-11T09:17:39.080686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1154
19.2%
창 378
 
6.3%
녕 367
 
6.1%
남 351
 
5.8%
도 293
 
4.9%
경 283
 
4.7%
상 283
 
4.7%
군 281
 
4.7%
1 207
 
3.4%
로 159
 
2.6%
Other values (161) 2248
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3952
65.8%
Space Separator 1154
 
19.2%
Decimal Number 813
 
13.5%
Dash Punctuation 47
 
0.8%
Other Punctuation 21
 
0.3%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
창 378
 
9.6%
녕 367
 
9.3%
남 351
 
8.9%
도 293
 
7.4%
경 283
 
7.2%
상 283
 
7.2%
군 281
 
7.1%
로 159
 
4.0%
면 158
 
4.0%
길 129
 
3.3%
Other values (145) 1270
32.1%
Decimal Number
ValueCountFrequency (%)
1 207
25.5%
2 105
12.9%
4 86
10.6%
3 74
 
9.1%
0 67
 
8.2%
5 67
 
8.2%
9 58
 
7.1%
6 55
 
6.8%
7 50
 
6.2%
8 44
 
5.4%
Space Separator
ValueCountFrequency (%)
1154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Other Punctuation
ValueCountFrequency (%)
. 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3952
65.8%
Common 2051
34.2%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
창 378
 
9.6%
녕 367
 
9.3%
남 351
 
8.9%
도 293
 
7.4%
경 283
 
7.2%
상 283
 
7.2%
군 281
 
7.1%
로 159
 
4.0%
면 158
 
4.0%
길 129
 
3.3%
Other values (145) 1270
32.1%
Common
ValueCountFrequency (%)
1154
56.3%
1 207
 
10.1%
2 105
 
5.1%
4 86
 
4.2%
3 74
 
3.6%
0 67
 
3.3%
5 67
 
3.3%
9 58
 
2.8%
6 55
 
2.7%
7 50
 
2.4%
Other values (5) 128
 
6.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3952
65.8%
ASCII 2052
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1154
56.2%
1 207
 
10.1%
2 105
 
5.1%
4 86
 
4.2%
3 74
 
3.6%
0 67
 
3.3%
5 67
 
3.3%
9 58
 
2.8%
6 55
 
2.7%
7 50
 
2.4%
Other values (6) 129
 
6.3%
Hangul
ValueCountFrequency (%)
창 378
 
9.6%
녕 367
 
9.3%
남 351
 
8.9%
도 293
 
7.4%
경 283
 
7.2%
상 283
 
7.2%
군 281
 
7.1%
로 159
 
4.0%
면 158
 
4.0%
길 129
 
3.3%
Other values (145) 1270
32.1%

소매인구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
제7조의3제2항에따른경우
142 
일반소매인
105 
제7조의3제3항에따른경우
20 
구내소매인
 
13
 
1

Length

Max length13
Median length13
Mean length9.5978648
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row제7조의3제2항에따른경우
2nd row제7조의3제2항에따른경우
3rd row제7조의3제2항에따른경우
4th row제7조의3제2항에따른경우
5th row제7조의3제2항에따른경우

Common Values

ValueCountFrequency (%)
제7조의3제2항에따른경우 142
50.5%
일반소매인 105
37.4%
제7조의3제3항에따른경우 20
 
7.1%
구내소매인 13
 
4.6%
1
 
0.4%

Length

2023-12-11T09:17:39.198862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:39.292353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제7조의3제2항에따른경우 142
50.7%
일반소매인 105
37.5%
제7조의3제3항에따른경우 20
 
7.1%
구내소매인 13
 
4.6%

영업상태
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
정상영업
249 
<NA>
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정상영업
2nd row정상영업
3rd row정상영업
4th row정상영업
5th row정상영업

Common Values

ValueCountFrequency (%)
정상영업 249
88.6%
<NA> 32
 
11.4%

Length

2023-12-11T09:17:39.400247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:39.480156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 249
88.6%
na 32
 
11.4%

지정일자
Date

Distinct233
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum1980-08-29 00:00:00
Maximum2021-10-06 00:00:00
2023-12-11T09:17:39.569633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:17:39.683775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct127
Distinct (%)73.0%
Missing107
Missing (%)38.1%
Memory size2.3 KiB
2023-12-11T09:17:39.893981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length9.091954
Min length1

Characters and Unicode

Total characters1582
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

Unique124 ?
Unique (%)71.3%

Sample

1st row055-532-7986
2nd row055-521-0460
3rd row055-526-3708
4th row055-526-1329
5th row055-533-6949
ValueCountFrequency (%)
055-526-3981 2
 
1.6%
055-533-0065 2
 
1.6%
055-533-2330 1
 
0.8%
055-526-1428 1
 
0.8%
055-536-6236 1
 
0.8%
055-533-7420 1
 
0.8%
055-526-1544 1
 
0.8%
055-536-6867 1
 
0.8%
055-536-5391 1
 
0.8%
055-533-0140 1
 
0.8%
Other values (116) 116
90.6%
2023-12-11T09:17:40.245377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 440
27.8%
- 256
16.2%
0 189
11.9%
3 164
 
10.4%
2 119
 
7.5%
6 105
 
6.6%
1 77
 
4.9%
8 50
 
3.2%
4 50
 
3.2%
46
 
2.9%
Other values (2) 86
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1280
80.9%
Dash Punctuation 256
 
16.2%
Space Separator 46
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 440
34.4%
0 189
14.8%
3 164
 
12.8%
2 119
 
9.3%
6 105
 
8.2%
1 77
 
6.0%
8 50
 
3.9%
4 50
 
3.9%
7 44
 
3.4%
9 42
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 256
100.0%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1582
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 440
27.8%
- 256
16.2%
0 189
11.9%
3 164
 
10.4%
2 119
 
7.5%
6 105
 
6.6%
1 77
 
4.9%
8 50
 
3.2%
4 50
 
3.2%
46
 
2.9%
Other values (2) 86
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 440
27.8%
- 256
16.2%
0 189
11.9%
3 164
 
10.4%
2 119
 
7.5%
6 105
 
6.6%
1 77
 
4.9%
8 50
 
3.2%
4 50
 
3.2%
46
 
2.9%
Other values (2) 86
 
5.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2021-10-07 00:00:00
Maximum2021-10-07 00:00:00
2023-12-11T09:17:40.369239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:17:40.457134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-11T09:17:40.515854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소매인구분
소매인구분1.000
2023-12-11T09:17:40.584856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소매인구분영업상태
소매인구분1.0001.000
영업상태1.0001.000
2023-12-11T09:17:40.653260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소매인구분영업상태
소매인구분1.0001.000
영업상태1.0001.000

Missing values

2023-12-11T09:17:36.513431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:17:36.684197image/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.
2023-12-11T09:17:36.795629image/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

시군명민원구분업소명소재지지번주소소재지도로명주소소매인구분영업상태지정일자전화번호데이터기준일자
0경상남도 창녕군일반타올백화점경상남도 창녕군 부곡면 거문리 215-12경상남도 창녕군 부곡면 온천중앙로 15. 108호제7조의3제2항에따른경우정상영업2021-10-06<NA>2021-10-07
1경상남도 창녕군일반이마트24 창녕봉산점경상남도 창녕군 계성면 봉산리 24-9경상남도 창녕군 계성면 영산장마로 644제7조의3제2항에따른경우정상영업2021-09-29<NA>2021-10-07
2경상남도 창녕군일반세븐일레븐 창녕터미널점경상남도 창녕군 창녕읍 교리 1040-1경상남도 창녕군 창녕읍 창녕대로 11제7조의3제2항에따른경우정상영업2021-08-05<NA>2021-10-07
3경상남도 창녕군일반세븐일레븐 부곡온천점경상남도 창녕군 부곡면 거문리 224-1경상남도 창녕군 부곡면 온천중앙로 52제7조의3제2항에따른경우정상영업2021-07-29<NA>2021-10-07
4경상남도 창녕군일반이마트24 창녕대지점경상남도 창녕군 대지면 왕산리 24경상남도 창녕군 대지면 억만미산로 43제7조의3제2항에따른경우정상영업2021-07-28<NA>2021-10-07
5경상남도 창녕군일반낙동강 휴게소경상남도 창녕군 부곡면 노리 710-4 소매경상남도 창녕군 부곡면 낙동로 2153제7조의3제2항에따른경우정상영업2021-07-26<NA>2021-10-07
6경상남도 창녕군일반GS25 영산드림점경상남도 창녕군 영산면 성내리 612-1경상남도 창녕군 영산면 삼시랑길 4제7조의3제2항에따른경우정상영업2021-07-02<NA>2021-10-07
7경상남도 창녕군일반성원C마트경상남도 창녕군 대합면 십이리 240-10경상남도 창녕군 대합면 창한로 97-1제7조의3제2항에따른경우정상영업2021-06-22<NA>2021-10-07
8경상남도 창녕군일반세븐일레븐 창녕신라점경상남도 창녕군 창녕읍 말흘리 177-2경상남도 창녕군 창녕읍 척경비로 21제7조의3제2항에따른경우정상영업2021-04-30<NA>2021-10-07
9경상남도 창녕군일반세븐일레븐 창녕종로점경상남도 창녕군 창녕읍 말흘리 186-1경상남도 창녕군 창녕읍 말흘2길 2제7조의3제2항에따른경우정상영업2021-04-23<NA>2021-10-07
시군명민원구분업소명소재지지번주소소재지도로명주소소매인구분영업상태지정일자전화번호데이터기준일자
271경상남도 창녕군일반학우사경상남도 창녕군 영산면 서리 223번지 4호경상남도 창녕군 영산면 영산새싹길 30일반소매인<NA>1989-04-202021-10-07
272경상남도 창녕군일반일용잡화경상남도 창녕군 영산면 월령리 990번지경상남도 창녕군 영산면 월령윗길 9일반소매인<NA>1989-04-202021-10-07
273경상남도 창녕군일반잡화경상남도 창녕군 장마면 강리 806번지 7호경상남도 창녕군 장마면 강리길 27일반소매인<NA>1989-04-202021-10-07
274경상남도 창녕군일반일용잡화경상남도 창녕군 도천면 일리 552번지 4호경상남도 창녕군 도천면 도천중앙로 21일반소매인<NA>1989-10-062021-10-07
275경상남도 창녕군일반잡화경상남도 창녕군 창녕읍 송현리 261번지 21호경상남도 창녕군 창녕읍 창녕대동길 42일반소매인<NA>1989-04-202021-10-07
276경상남도 창녕군일반<NA>경상남도 창녕군 창녕읍 교리 259-1번지경상남도 창녕군 창녕읍 명덕로 70-1일반소매인<NA>1989-04-20<NA>2021-10-07
277경상남도 창녕군일반일용잡화경상남도 창녕군 창녕읍 교하리 223번지 2호경상남도 창녕군 창녕읍 화왕산1로 11일반소매인<NA>1989-04-202021-10-07
278경상남도 창녕군일반부곡파크호텔숙박업경상남도 창녕군 부곡면 거문리 216번지 1호경상남도 창녕군 부곡면 온천2길 26구내소매인<NA>1988-07-11055-536-62112021-10-07
279경상남도 창녕군일반담배소매경상남도 창녕군 부곡면 수다리 601호경상남도 창녕군 부곡면 수다길 42-5일반소매인<NA>1985-06-302021-10-07
280경상남도 창녕군일반일용잡화경상남도 창녕군 길곡면 오호리 330호경상남도 창녕군 길곡면 내동길 145일반소매인<NA>1980-08-292021-10-07

Duplicate rows

Most frequently occurring

시군명민원구분업소명소재지지번주소소재지도로명주소소매인구분영업상태지정일자전화번호데이터기준일자# duplicates
0경상남도 창녕군일반<NA>경상남도 창녕군 남지읍 고곡리 575번지 4호경상남도 창녕군 남지읍 수개시남길 3일반소매인<NA>1989-04-20<NA>2021-10-073