Overview

Dataset statistics

Number of variables7
Number of observations657
Missing cells4
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.7 KiB
Average record size in memory57.2 B

Variable types

Numeric1
Categorical2
Text4

Dataset

Description부산광역시북구_담배소매인지정현황_20230418
Author부산광역시 북구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3070064

Alerts

영업구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
민원구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 민원구분 and 1 other fieldsHigh correlation
영업구분 is highly imbalanced (98.4%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:27:23.068210
Analysis finished2023-12-10 16:27:24.047993
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct657
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean329
Minimum1
Maximum657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2023-12-11T01:27:24.152240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile33.8
Q1165
median329
Q3493
95-th percentile624.2
Maximum657
Range656
Interquartile range (IQR)328

Descriptive statistics

Standard deviation189.80385
Coefficient of variation (CV)0.57691139
Kurtosis-1.2
Mean329
Median Absolute Deviation (MAD)164
Skewness0
Sum216153
Variance36025.5
MonotonicityStrictly increasing
2023-12-11T01:27:24.325838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
433 1
 
0.2%
435 1
 
0.2%
436 1
 
0.2%
437 1
 
0.2%
438 1
 
0.2%
439 1
 
0.2%
440 1
 
0.2%
441 1
 
0.2%
442 1
 
0.2%
Other values (647) 647
98.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
657 1
0.2%
656 1
0.2%
655 1
0.2%
654 1
0.2%
653 1
0.2%
652 1
0.2%
651 1
0.2%
650 1
0.2%
649 1
0.2%
648 1
0.2%

민원구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
제7조의3제2항에따른경우
385 
242 
제7조의3제3항에따른경우
 
29
<NA>
 
1

Length

Max length13
Median length13
Mean length8.56621
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
제7조의3제2항에따른경우 385
58.6%
242
36.8%
제7조의3제3항에따른경우 29
 
4.4%
<NA> 1
 
0.2%

Length

2023-12-11T01:27:24.476139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:27:24.591826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제7조의3제2항에따른경우 385
92.8%
제7조의3제3항에따른경우 29
 
7.0%
na 1
 
0.2%

업소명
Text

Distinct607
Distinct (%)92.5%
Missing1
Missing (%)0.2%
Memory size5.3 KiB
2023-12-11T01:27:25.011015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length7.1082317
Min length1

Characters and Unicode

Total characters4663
Distinct characters424
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique587 ?
Unique (%)89.5%

Sample

1st row씨유 부산폴리텍이레점
2nd row미진식품
3rd row대우마트
4th row화명동전자담배샤크베이퍼
5th row뚱이네 대박슈퍼
ValueCountFrequency (%)
씨유 45
 
5.2%
지에스(gs)25 24
 
2.8%
세븐일레븐 19
 
2.2%
gs25 18
 
2.1%
이마트24 13
 
1.5%
화명점 7
 
0.8%
전자담배 7
 
0.8%
지에스25 6
 
0.7%
주)코리아세븐 6
 
0.7%
덕천점 5
 
0.6%
Other values (656) 714
82.6%
2023-12-11T01:27:25.609849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
271
 
5.8%
점 232
 
5.0%
마 135
 
2.9%
트 122
 
2.6%
스 90
 
1.9%
퍼 90
 
1.9%
2 89
 
1.9%
슈 86
 
1.8%
덕 86
 
1.8%
) 82
 
1.8%
Other values (414) 3380
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3818
81.9%
Space Separator 271
 
5.8%
Decimal Number 188
 
4.0%
Uppercase Letter 159
 
3.4%
Close Punctuation 82
 
1.8%
Open Punctuation 82
 
1.8%
Lowercase Letter 52
 
1.1%
Other Punctuation 8
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 232
 
6.1%
마 135
 
3.5%
트 122
 
3.2%
스 90
 
2.4%
퍼 90
 
2.4%
슈 86
 
2.3%
덕 86
 
2.3%
화 77
 
2.0%
구 76
 
2.0%
유 73
 
1.9%
Other values (366) 2751
72.1%
Lowercase Letter
ValueCountFrequency (%)
o 7
13.5%
e 5
9.6%
r 5
9.6%
n 5
9.6%
a 4
7.7%
t 4
7.7%
i 4
7.7%
s 4
7.7%
p 3
 
5.8%
d 2
 
3.8%
Other values (7) 9
17.3%
Uppercase Letter
ValueCountFrequency (%)
S 57
35.8%
G 56
35.2%
C 14
 
8.8%
U 9
 
5.7%
E 4
 
2.5%
P 4
 
2.5%
A 3
 
1.9%
N 2
 
1.3%
F 2
 
1.3%
L 2
 
1.3%
Other values (6) 6
 
3.8%
Decimal Number
ValueCountFrequency (%)
2 89
47.3%
5 68
36.2%
4 19
 
10.1%
1 8
 
4.3%
9 1
 
0.5%
6 1
 
0.5%
7 1
 
0.5%
3 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 6
75.0%
/ 1
 
12.5%
· 1
 
12.5%
Space Separator
ValueCountFrequency (%)
271
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3818
81.9%
Common 634
 
13.6%
Latin 211
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 232
 
6.1%
마 135
 
3.5%
트 122
 
3.2%
스 90
 
2.4%
퍼 90
 
2.4%
슈 86
 
2.3%
덕 86
 
2.3%
화 77
 
2.0%
구 76
 
2.0%
유 73
 
1.9%
Other values (366) 2751
72.1%
Latin
ValueCountFrequency (%)
S 57
27.0%
G 56
26.5%
C 14
 
6.6%
U 9
 
4.3%
o 7
 
3.3%
e 5
 
2.4%
r 5
 
2.4%
n 5
 
2.4%
a 4
 
1.9%
t 4
 
1.9%
Other values (23) 45
21.3%
Common
ValueCountFrequency (%)
271
42.7%
2 89
 
14.0%
) 82
 
12.9%
( 82
 
12.9%
5 68
 
10.7%
4 19
 
3.0%
1 8
 
1.3%
. 6
 
0.9%
- 3
 
0.5%
9 1
 
0.2%
Other values (5) 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3818
81.9%
ASCII 844
 
18.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
271
32.1%
2 89
 
10.5%
) 82
 
9.7%
( 82
 
9.7%
5 68
 
8.1%
S 57
 
6.8%
G 56
 
6.6%
4 19
 
2.3%
C 14
 
1.7%
U 9
 
1.1%
Other values (37) 97
 
11.5%
Hangul
ValueCountFrequency (%)
점 232
 
6.1%
마 135
 
3.5%
트 122
 
3.2%
스 90
 
2.4%
퍼 90
 
2.4%
슈 86
 
2.3%
덕 86
 
2.3%
화 77
 
2.0%
구 76
 
2.0%
유 73
 
1.9%
Other values (366) 2751
72.1%
None
ValueCountFrequency (%)
· 1
100.0%

업소지번주소
Text

Distinct558
Distinct (%)85.2%
Missing2
Missing (%)0.3%
Memory size5.3 KiB
2023-12-11T01:27:25.871058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length22.141985
Min length1

Characters and Unicode

Total characters14503
Distinct characters227
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

Unique545 ?
Unique (%)83.2%

Sample

1st row부산광역시 북구 덕천동 365-14
2nd row부산광역시 북구 덕천동 404-13
3rd row부산광역시 북구 화명동 377-9
4th row부산광역시 북구 화명동 1470-16
5th row부산광역시 북구 구포동 1154-5
ValueCountFrequency (%)
부산광역시 570
18.6%
북구 569
18.6%
구포동 166
 
5.4%
호 118
 
3.8%
덕천동 113
 
3.7%
만덕동 87
 
2.8%
화명동 86
 
2.8%
금곡동 54
 
1.8%
1호 44
 
1.4%
2호 21
 
0.7%
Other values (798) 1237
40.4%
2023-12-11T01:27:26.336562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3278
22.6%
구 757
 
5.2%
1 689
 
4.8%
동 593
 
4.1%
산 589
 
4.1%
시 576
 
4.0%
역 575
 
4.0%
부 573
 
4.0%
광 570
 
3.9%
북 569
 
3.9%
Other values (217) 5734
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8177
56.4%
Space Separator 3278
22.6%
Decimal Number 2882
 
19.9%
Dash Punctuation 128
 
0.9%
Other Punctuation 25
 
0.2%
Uppercase Letter 10
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 757
 
9.3%
동 593
 
7.3%
산 589
 
7.2%
시 576
 
7.0%
역 575
 
7.0%
부 573
 
7.0%
광 570
 
7.0%
북 569
 
7.0%
호 442
 
5.4%
지 418
 
5.1%
Other values (196) 2515
30.8%
Decimal Number
ValueCountFrequency (%)
1 689
23.9%
2 416
14.4%
3 319
11.1%
0 272
 
9.4%
4 232
 
8.0%
8 213
 
7.4%
5 194
 
6.7%
9 189
 
6.6%
7 187
 
6.5%
6 171
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
40.0%
H 2
20.0%
A 2
20.0%
L 2
20.0%
Other Punctuation
ValueCountFrequency (%)
. 12
48.0%
@ 11
44.0%
/ 2
 
8.0%
Space Separator
ValueCountFrequency (%)
3278
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8177
56.4%
Common 6315
43.5%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 757
 
9.3%
동 593
 
7.3%
산 589
 
7.2%
시 576
 
7.0%
역 575
 
7.0%
부 573
 
7.0%
광 570
 
7.0%
북 569
 
7.0%
호 442
 
5.4%
지 418
 
5.1%
Other values (196) 2515
30.8%
Common
ValueCountFrequency (%)
3278
51.9%
1 689
 
10.9%
2 416
 
6.6%
3 319
 
5.1%
0 272
 
4.3%
4 232
 
3.7%
8 213
 
3.4%
5 194
 
3.1%
9 189
 
3.0%
7 187
 
3.0%
Other values (6) 326
 
5.2%
Latin
ValueCountFrequency (%)
B 4
36.4%
H 2
18.2%
A 2
18.2%
L 2
18.2%
b 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8177
56.4%
ASCII 6326
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3278
51.8%
1 689
 
10.9%
2 416
 
6.6%
3 319
 
5.0%
0 272
 
4.3%
4 232
 
3.7%
8 213
 
3.4%
5 194
 
3.1%
9 189
 
3.0%
7 187
 
3.0%
Other values (11) 337
 
5.3%
Hangul
ValueCountFrequency (%)
구 757
 
9.3%
동 593
 
7.3%
산 589
 
7.2%
시 576
 
7.0%
역 575
 
7.0%
부 573
 
7.0%
광 570
 
7.0%
북 569
 
7.0%
호 442
 
5.4%
지 418
 
5.1%
Other values (196) 2515
30.8%

업소도로명주소
Text

Distinct577
Distinct (%)88.0%
Missing1
Missing (%)0.2%
Memory size5.3 KiB
2023-12-11T01:27:26.751086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length50
Mean length26.903963
Min length1

Characters and Unicode

Total characters17649
Distinct characters265
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

Unique574 ?
Unique (%)87.5%

Sample

1st row부산광역시 북구 만덕대로155번길 60 (덕천동)
2nd row부산광역시 북구 만덕대로168번길 14 (덕천동)
3rd row부산광역시 북구 산성로47번길 1. 1층 103호 (화명동)
4th row부산광역시 북구 와석장터로 1 (화명동)
5th row부산광역시 북구 구포만세길 167. 1층 일부 (구포동)
ValueCountFrequency (%)
부산광역시 580
 
16.8%
북구 578
 
16.7%
구포동 185
 
5.3%
덕천동 125
 
3.6%
1층 114
 
3.3%
만덕동 92
 
2.7%
화명동 89
 
2.6%
금곡동 50
 
1.4%
금곡대로 45
 
1.3%
101호 31
 
0.9%
Other values (719) 1571
45.4%
2023-12-11T01:27:27.307806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3145
 
17.8%
1 804
 
4.6%
구 800
 
4.5%
동 717
 
4.1%
시 656
 
3.7%
산 616
 
3.5%
북 587
 
3.3%
역 586
 
3.3%
부 586
 
3.3%
광 581
 
3.3%
Other values (255) 8571
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10112
57.3%
Space Separator 3145
 
17.8%
Decimal Number 2783
 
15.8%
Open Punctuation 578
 
3.3%
Close Punctuation 578
 
3.3%
Other Punctuation 381
 
2.2%
Dash Punctuation 48
 
0.3%
Uppercase Letter 16
 
0.1%
Math Symbol 6
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 800
 
7.9%
동 717
 
7.1%
시 656
 
6.5%
산 616
 
6.1%
북 587
 
5.8%
역 586
 
5.8%
부 586
 
5.8%
광 581
 
5.7%
로 555
 
5.5%
덕 399
 
3.9%
Other values (227) 4029
39.8%
Decimal Number
ValueCountFrequency (%)
1 804
28.9%
2 370
13.3%
0 313
 
11.2%
3 261
 
9.4%
6 205
 
7.4%
4 200
 
7.2%
5 182
 
6.5%
7 182
 
6.5%
8 152
 
5.5%
9 114
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 5
31.2%
B 4
25.0%
L 2
 
12.5%
H 2
 
12.5%
E 1
 
6.2%
F 1
 
6.2%
D 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 372
97.6%
@ 6
 
1.6%
， 2
 
0.5%
/ 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
3145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 578
100.0%
Close Punctuation
ValueCountFrequency (%)
) 578
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10112
57.3%
Common 7519
42.6%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 800
 
7.9%
동 717
 
7.1%
시 656
 
6.5%
산 616
 
6.1%
북 587
 
5.8%
역 586
 
5.8%
부 586
 
5.8%
광 581
 
5.7%
로 555
 
5.5%
덕 399
 
3.9%
Other values (227) 4029
39.8%
Common
ValueCountFrequency (%)
3145
41.8%
1 804
 
10.7%
( 578
 
7.7%
) 578
 
7.7%
. 372
 
4.9%
2 370
 
4.9%
0 313
 
4.2%
3 261
 
3.5%
6 205
 
2.7%
4 200
 
2.7%
Other values (9) 693
 
9.2%
Latin
ValueCountFrequency (%)
A 5
27.8%
B 4
22.2%
L 2
 
11.1%
H 2
 
11.1%
E 1
 
5.6%
b 1
 
5.6%
e 1
 
5.6%
F 1
 
5.6%
D 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10112
57.3%
ASCII 7535
42.7%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3145
41.7%
1 804
 
10.7%
( 578
 
7.7%
) 578
 
7.7%
. 372
 
4.9%
2 370
 
4.9%
0 313
 
4.2%
3 261
 
3.5%
6 205
 
2.7%
4 200
 
2.7%
Other values (17) 709
 
9.4%
Hangul
ValueCountFrequency (%)
구 800
 
7.9%
동 717
 
7.1%
시 656
 
6.5%
산 616
 
6.1%
북 587
 
5.8%
역 586
 
5.8%
부 586
 
5.8%
광 581
 
5.7%
로 555
 
5.5%
덕 399
 
3.9%
Other values (227) 4029
39.8%
None
ValueCountFrequency (%)
， 2
100.0%

지정일자
Text

Distinct595
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2023-12-11T01:27:27.618763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9863014
Min length1

Characters and Unicode

Total characters6561
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

Unique542 ?
Unique (%)82.5%

Sample

1st row2023-03-20
2nd row2023-03-15
3rd row2023-03-13
4th row2023-03-09
5th row2023-02-27
ValueCountFrequency (%)
2020-07-20 4
 
0.6%
2020-10-16 3
 
0.5%
2021-04-29 3
 
0.5%
2018-11-19 3
 
0.5%
2019-09-25 3
 
0.5%
2022-09-01 3
 
0.5%
2019-08-06 3
 
0.5%
1998-12-14 3
 
0.5%
2021-05-10 2
 
0.3%
2022-03-24 2
 
0.3%
Other values (584) 627
95.6%
2023-12-11T01:27:28.119023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1532
23.4%
- 1312
20.0%
2 1153
17.6%
1 1038
15.8%
9 437
 
6.7%
3 224
 
3.4%
8 217
 
3.3%
7 187
 
2.9%
4 161
 
2.5%
6 151
 
2.3%
Other values (2) 149
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5248
80.0%
Dash Punctuation 1312
 
20.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1532
29.2%
2 1153
22.0%
1 1038
19.8%
9 437
 
8.3%
3 224
 
4.3%
8 217
 
4.1%
7 187
 
3.6%
4 161
 
3.1%
6 151
 
2.9%
5 148
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 1312
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1532
23.4%
- 1312
20.0%
2 1153
17.6%
1 1038
15.8%
9 437
 
6.7%
3 224
 
3.4%
8 217
 
3.3%
7 187
 
2.9%
4 161
 
2.5%
6 151
 
2.3%
Other values (2) 149
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1532
23.4%
- 1312
20.0%
2 1153
17.6%
1 1038
15.8%
9 437
 
6.7%
3 224
 
3.4%
8 217
 
3.3%
7 187
 
2.9%
4 161
 
2.5%
6 151
 
2.3%
Other values (2) 149
 
2.3%

영업구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
정상영업
656 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 656
99.8%
<NA> 1
 
0.2%

Length

2023-12-11T01:27:28.295023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:27:28.459554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 656
99.8%
na 1
 
0.2%

Interactions

2023-12-11T01:27:23.614973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:27:28.537400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번민원구분
연번1.0000.791
민원구분0.7911.000
2023-12-11T01:27:28.677320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업구분민원구분
영업구분1.0001.000
민원구분1.0001.000
2023-12-11T01:27:28.810120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번민원구분영업구분
연번1.0000.6751.000
민원구분0.6751.0001.000
영업구분1.0001.0001.000

Missing values

2023-12-11T01:27:23.767831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:27:23.883242image/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.
2023-12-11T01:27:23.982475image/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

연번민원구분업소명업소지번주소업소도로명주소지정일자영업구분
01제7조의3제2항에따른경우씨유 부산폴리텍이레점부산광역시 북구 덕천동 365-14부산광역시 북구 만덕대로155번길 60 (덕천동)2023-03-20정상영업
12제7조의3제2항에따른경우미진식품부산광역시 북구 덕천동 404-13부산광역시 북구 만덕대로168번길 14 (덕천동)2023-03-15정상영업
23제7조의3제2항에따른경우대우마트부산광역시 북구 화명동 377-9부산광역시 북구 산성로47번길 1. 1층 103호 (화명동)2023-03-13정상영업
34제7조의3제2항에따른경우화명동전자담배샤크베이퍼부산광역시 북구 화명동 1470-16부산광역시 북구 와석장터로 1 (화명동)2023-03-09정상영업
45제7조의3제2항에따른경우뚱이네 대박슈퍼부산광역시 북구 구포동 1154-5부산광역시 북구 구포만세길 167. 1층 일부 (구포동)2023-02-27정상영업
56제7조의3제2항에따른경우후크전자담배 부산 화명점부산광역시 북구 화명동 898-20 해창빌딩부산광역시 북구 금곡대로 180. 해창빌딩 102호 (화명동)2023-02-22정상영업
67제7조의3제2항에따른경우(주)영도우리마트 만덕점부산광역시 북구 만덕동 308부산광역시 북구 만덕2로 28 (만덕동)2023-02-22정상영업
78제7조의3제2항에따른경우(주)베이프마스터 덕천점부산광역시 북구 덕천동 415-1부산광역시 북구 의성로122번길 66 (덕천동)2023-02-20정상영업
89제7조의3제2항에따른경우아이스크림할인점(만덕점)부산광역시 북구 만덕동 962 이편한세상 금정산부산광역시 북구 상학로 36. 상가1동 101호 (만덕동. 이편한세상 금정산)2023-02-13정상영업
910제7조의3제2항에따른경우다마트(대림)부산광역시 북구 화명동 1170-1 화명동대림타운부산광역시 북구 금곡대로 270. 화명동대림타운 제분산상가동 101~104호 (화명동)2023-02-03정상영업
연번민원구분업소명업소지번주소업소도로명주소지정일자영업구분
647648부산광역시 북구 덕천동 383번지 12 호부산광역시 북구 만덕대로28번길 9 (덕천동)1990-05-15정상영업
648649부산광역시 북구 구포동 1184번지 12 호부산광역시 북구 낙동대로1570번길 3 (구포동)1990-04-02정상영업
649650부산광역시 북구 만덕동 732번지 2 호부산광역시 북구 만덕1로102번길 12 (만덕동)1990-03-19정상영업
650651부산광역시 북구 만덕동 828번지 33 호1990-03-16정상영업
651652부산광역시 북구 만덕동 818호1989-12-09정상영업
652653은하슈퍼부산광역시 북구 덕천동 424번지 5 호부산광역시 북구 만덕대로128번길 38 (덕천동)1989-12-01정상영업
653654덕경부산광역시 북구 화명동 1310번지 5 호부산광역시 북구 화명대로80번길 4-8 (화명동)1989-12-15정상영업
654655잡화부산광역시 북구 구포동 1129번지 8 호부산광역시 북구 사상로558번길 33 (구포동)1989-12-01정상영업
655656영선슈퍼부산광역시 북구 구포동 709호1989-12-05정상영업
656657팔공슈퍼부산광역시 북구 구포동 592번지 8 호1989-12-04정상영업