Overview

Dataset statistics

Number of variables11
Number of observations671
Missing cells184
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.1 KiB
Average record size in memory90.2 B

Variable types

Text5
Categorical4
Numeric2

Dataset

Description김해시 식품제조가공업 현황(사업장명, 소재지전화, 소재지면적, 지번주소, 도로명주소, 위생업태명, 급수시설구분 등)에 대한 데이터를 제공합니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033408/fileData.do

Alerts

시설총규모 is highly overall correlated with 급수시설구분명High correlation
급수시설구분명 is highly overall correlated with 시설총규모High correlation
위생업태명 is highly imbalanced (52.6%)Imbalance
소재지전화 has 130 (19.4%) missing valuesMissing
소재지면적 has 35 (5.2%) missing valuesMissing
도로명주소 has 19 (2.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:33:44.813462
Analysis finished2023-12-12 09:33:47.147539
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct638
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-12T18:33:47.404503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length20
Mean length6.1743666
Min length2

Characters and Unicode

Total characters4143
Distinct characters435
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

Unique609 ?
Unique (%)90.8%

Sample

1st row도우
2nd row만복쏠트
3rd row참그린
4th row주식회사씨엠지바이오팜
5th row(주)마이크로파우더
ValueCountFrequency (%)
주식회사 17
 
2.4%
농업회사법인 5
 
0.7%
푸드클럽 3
 
0.4%
아세아식품 3
 
0.4%
만나식품 3
 
0.4%
태양식품 3
 
0.4%
상원식품 2
 
0.3%
주)신광식품 2
 
0.3%
주)고려종합 2
 
0.3%
주)참사리 2
 
0.3%
Other values (652) 678
94.2%
2023-12-12T18:33:47.897249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 277
 
6.7%
품 245
 
5.9%
주 204
 
4.9%
) 188
 
4.5%
( 188
 
4.5%
드 85
 
2.1%
푸 75
 
1.8%
이 67
 
1.6%
사 67
 
1.6%
스 60
 
1.4%
Other values (425) 2687
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3524
85.1%
Close Punctuation 188
 
4.5%
Open Punctuation 188
 
4.5%
Uppercase Letter 100
 
2.4%
Lowercase Letter 61
 
1.5%
Space Separator 49
 
1.2%
Other Punctuation 17
 
0.4%
Decimal Number 15
 
0.4%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 277
 
7.9%
품 245
 
7.0%
주 204
 
5.8%
드 85
 
2.4%
푸 75
 
2.1%
이 67
 
1.9%
사 67
 
1.9%
스 60
 
1.7%
산 60
 
1.7%
회 45
 
1.3%
Other values (374) 2339
66.4%
Uppercase Letter
ValueCountFrequency (%)
F 17
17.0%
O 10
10.0%
R 9
9.0%
B 8
 
8.0%
D 7
 
7.0%
S 7
 
7.0%
E 6
 
6.0%
C 5
 
5.0%
M 5
 
5.0%
A 5
 
5.0%
Other values (9) 21
21.0%
Lowercase Letter
ValueCountFrequency (%)
o 9
14.8%
e 9
14.8%
a 8
13.1%
f 7
11.5%
d 5
8.2%
s 3
 
4.9%
i 2
 
3.3%
n 2
 
3.3%
h 2
 
3.3%
u 2
 
3.3%
Other values (8) 12
19.7%
Other Punctuation
ValueCountFrequency (%)
& 12
70.6%
. 2
 
11.8%
! 1
 
5.9%
/ 1
 
5.9%
' 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 8
53.3%
1 2
 
13.3%
4 2
 
13.3%
0 2
 
13.3%
9 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 188
100.0%
Open Punctuation
ValueCountFrequency (%)
( 188
100.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3525
85.1%
Common 457
 
11.0%
Latin 161
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 277
 
7.9%
품 245
 
7.0%
주 204
 
5.8%
드 85
 
2.4%
푸 75
 
2.1%
이 67
 
1.9%
사 67
 
1.9%
스 60
 
1.7%
산 60
 
1.7%
회 45
 
1.3%
Other values (375) 2340
66.4%
Latin
ValueCountFrequency (%)
F 17
 
10.6%
O 10
 
6.2%
R 9
 
5.6%
o 9
 
5.6%
e 9
 
5.6%
a 8
 
5.0%
B 8
 
5.0%
D 7
 
4.3%
S 7
 
4.3%
f 7
 
4.3%
Other values (27) 70
43.5%
Common
ValueCountFrequency (%)
) 188
41.1%
( 188
41.1%
49
 
10.7%
& 12
 
2.6%
2 8
 
1.8%
. 2
 
0.4%
1 2
 
0.4%
4 2
 
0.4%
0 2
 
0.4%
! 1
 
0.2%
Other values (3) 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3524
85.1%
ASCII 618
 
14.9%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 277
 
7.9%
품 245
 
7.0%
주 204
 
5.8%
드 85
 
2.4%
푸 75
 
2.1%
이 67
 
1.9%
사 67
 
1.9%
스 60
 
1.7%
산 60
 
1.7%
회 45
 
1.3%
Other values (374) 2339
66.4%
ASCII
ValueCountFrequency (%)
) 188
30.4%
( 188
30.4%
49
 
7.9%
F 17
 
2.8%
& 12
 
1.9%
O 10
 
1.6%
R 9
 
1.5%
o 9
 
1.5%
e 9
 
1.5%
2 8
 
1.3%
Other values (40) 119
19.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지전화
Text

MISSING 

Distinct512
Distinct (%)94.6%
Missing130
Missing (%)19.4%
Memory size5.4 KiB
2023-12-12T18:33:48.208778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.983364
Min length9

Characters and Unicode

Total characters6483
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

Unique487 ?
Unique (%)90.0%

Sample

1st row055-331-5553
2nd row055-337-3789
3rd row055-310-7115
4th row055-325-5520
5th row055-312-7413
ValueCountFrequency (%)
055-328-2911 4
 
0.7%
055-323-9912 3
 
0.6%
055-329-2218 3
 
0.6%
055-331-1613 2
 
0.4%
055-323-1181 2
 
0.4%
055-346-5374 2
 
0.4%
055-329-4339 2
 
0.4%
055-339-7749 2
 
0.4%
055-324-0053 2
 
0.4%
055-325-9920 2
 
0.4%
Other values (502) 517
95.6%
2023-12-12T18:33:48.769534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1315
20.3%
- 1063
16.4%
3 943
14.5%
0 846
13.0%
2 544
8.4%
1 358
 
5.5%
4 320
 
4.9%
8 312
 
4.8%
6 265
 
4.1%
9 262
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5420
83.6%
Dash Punctuation 1063
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1315
24.3%
3 943
17.4%
0 846
15.6%
2 544
10.0%
1 358
 
6.6%
4 320
 
5.9%
8 312
 
5.8%
6 265
 
4.9%
9 262
 
4.8%
7 255
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 1063
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6483
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1315
20.3%
- 1063
16.4%
3 943
14.5%
0 846
13.0%
2 544
8.4%
1 358
 
5.5%
4 320
 
4.9%
8 312
 
4.8%
6 265
 
4.1%
9 262
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6483
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1315
20.3%
- 1063
16.4%
3 943
14.5%
0 846
13.0%
2 544
8.4%
1 358
 
5.5%
4 320
 
4.9%
8 312
 
4.8%
6 265
 
4.1%
9 262
 
4.0%

소재지면적
Text

MISSING 

Distinct562
Distinct (%)88.4%
Missing35
Missing (%)5.2%
Memory size5.4 KiB
2023-12-12T18:33:49.360935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.7955975
Min length1

Characters and Unicode

Total characters3050
Distinct characters12
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

Unique508 ?
Unique (%)79.9%

Sample

1st row301
2nd row15.12
3rd row296
4th row100.11
5th row277.87
ValueCountFrequency (%)
0 6
 
0.9%
212.62 4
 
0.6%
360 4
 
0.6%
66 4
 
0.6%
77.22 4
 
0.6%
198 4
 
0.6%
480 4
 
0.6%
330 3
 
0.5%
35 3
 
0.5%
165 3
 
0.5%
Other values (552) 597
93.9%
2023-12-12T18:33:50.068806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 471
15.4%
1 328
10.8%
2 310
10.2%
4 293
9.6%
3 250
8.2%
5 242
7.9%
6 233
7.6%
9 225
7.4%
0 219
7.2%
8 216
7.1%
Other values (2) 263
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2524
82.8%
Other Punctuation 526
 
17.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 328
13.0%
2 310
12.3%
4 293
11.6%
3 250
9.9%
5 242
9.6%
6 233
9.2%
9 225
8.9%
0 219
8.7%
8 216
8.6%
7 208
8.2%
Other Punctuation
ValueCountFrequency (%)
. 471
89.5%
, 55
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3050
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 471
15.4%
1 328
10.8%
2 310
10.2%
4 293
9.6%
3 250
8.2%
5 242
7.9%
6 233
7.6%
9 225
7.4%
0 219
7.2%
8 216
7.1%
Other values (2) 263
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 471
15.4%
1 328
10.8%
2 310
10.2%
4 293
9.6%
3 250
8.2%
5 242
7.9%
6 233
7.6%
9 225
7.4%
0 219
7.2%
8 216
7.1%
Other values (2) 263
8.6%

지번주소
Text

Distinct619
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-12T18:33:50.469255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length22.432191
Min length14

Characters and Unicode

Total characters15052
Distinct characters166
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

Unique577 ?
Unique (%)86.0%

Sample

1st row경상남도 김해시 화목동 587-5번지
2nd row경상남도 김해시 대청동 315-2번지 재영프라자122호
3rd row경상남도 김해시 진례면 초전리 816-5번지
4th row경상남도 김해시 주촌면 원지리 477-1번지
5th row경상남도 김해시 주촌면 선지리 750-6
ValueCountFrequency (%)
경상남도 671
21.0%
김해시 671
21.0%
주촌면 112
 
3.5%
진례면 56
 
1.8%
진영읍 56
 
1.8%
어방동 51
 
1.6%
내삼리 47
 
1.5%
한림면 41
 
1.3%
상동면 41
 
1.3%
지내동 35
 
1.1%
Other values (765) 1408
44.2%
2023-12-12T18:33:51.036802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2518
 
16.7%
상 733
 
4.9%
1 709
 
4.7%
시 677
 
4.5%
도 673
 
4.5%
김 672
 
4.5%
해 672
 
4.5%
경 671
 
4.5%
남 671
 
4.5%
지 608
 
4.0%
Other values (156) 6448
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9071
60.3%
Decimal Number 2909
 
19.3%
Space Separator 2518
 
16.7%
Dash Punctuation 508
 
3.4%
Uppercase Letter 19
 
0.1%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%
Other Punctuation 8
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 733
 
8.1%
시 677
 
7.5%
도 673
 
7.4%
김 672
 
7.4%
해 672
 
7.4%
경 671
 
7.4%
남 671
 
7.4%
지 608
 
6.7%
번 527
 
5.8%
동 444
 
4.9%
Other values (135) 2723
30.0%
Decimal Number
ValueCountFrequency (%)
1 709
24.4%
2 361
12.4%
3 298
10.2%
0 273
 
9.4%
5 244
 
8.4%
6 242
 
8.3%
4 230
 
7.9%
9 199
 
6.8%
7 197
 
6.8%
8 156
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 6
31.6%
A 5
26.3%
L 4
21.1%
C 3
15.8%
F 1
 
5.3%
Space Separator
ValueCountFrequency (%)
2518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 508
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9071
60.3%
Common 5961
39.6%
Latin 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 733
 
8.1%
시 677
 
7.5%
도 673
 
7.4%
김 672
 
7.4%
해 672
 
7.4%
경 671
 
7.4%
남 671
 
7.4%
지 608
 
6.7%
번 527
 
5.8%
동 444
 
4.9%
Other values (135) 2723
30.0%
Common
ValueCountFrequency (%)
2518
42.2%
1 709
 
11.9%
- 508
 
8.5%
2 361
 
6.1%
3 298
 
5.0%
0 273
 
4.6%
5 244
 
4.1%
6 242
 
4.1%
4 230
 
3.9%
9 199
 
3.3%
Other values (5) 379
 
6.4%
Latin
ValueCountFrequency (%)
B 6
30.0%
A 5
25.0%
L 4
20.0%
C 3
15.0%
e 1
 
5.0%
F 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9071
60.3%
ASCII 5981
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2518
42.1%
1 709
 
11.9%
- 508
 
8.5%
2 361
 
6.0%
3 298
 
5.0%
0 273
 
4.6%
5 244
 
4.1%
6 242
 
4.0%
4 230
 
3.8%
9 199
 
3.3%
Other values (11) 399
 
6.7%
Hangul
ValueCountFrequency (%)
상 733
 
8.1%
시 677
 
7.5%
도 673
 
7.4%
김 672
 
7.4%
해 672
 
7.4%
경 671
 
7.4%
남 671
 
7.4%
지 608
 
6.7%
번 527
 
5.8%
동 444
 
4.9%
Other values (135) 2723
30.0%

도로명주소
Text

MISSING 

Distinct586
Distinct (%)89.9%
Missing19
Missing (%)2.8%
Memory size5.4 KiB
2023-12-12T18:33:51.369790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length49
Mean length26.865031
Min length16

Characters and Unicode

Total characters17516
Distinct characters179
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

Unique539 ?
Unique (%)82.7%

Sample

1st row경상남도 김해시 칠산로179번길 124 (화목동)
2nd row경상남도 김해시 삼문로 26, 122호 (대청동, 재영프라자)
3rd row경상남도 김해시 진례면 진례로 103, B동
4th row경상남도 김해시 주촌면 서부로1701번안길 186, 2층
5th row경상남도 김해시 주촌면 선천로 63-4
ValueCountFrequency (%)
경상남도 652
 
18.8%
김해시 652
 
18.8%
주촌면 108
 
3.1%
1층 59
 
1.7%
진례면 56
 
1.6%
진영읍 56
 
1.6%
어방동 48
 
1.4%
한림면 41
 
1.2%
상동면 40
 
1.2%
지내동 31
 
0.9%
Other values (797) 1734
49.9%
2023-12-12T18:33:51.889495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2825
 
16.1%
1 795
 
4.5%
상 747
 
4.3%
해 720
 
4.1%
김 718
 
4.1%
시 658
 
3.8%
도 656
 
3.7%
경 653
 
3.7%
남 652
 
3.7%
로 644
 
3.7%
Other values (169) 8448
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9914
56.6%
Decimal Number 3645
 
20.8%
Space Separator 2825
 
16.1%
Close Punctuation 328
 
1.9%
Open Punctuation 328
 
1.9%
Dash Punctuation 276
 
1.6%
Other Punctuation 178
 
1.0%
Uppercase Letter 21
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 747
 
7.5%
해 720
 
7.3%
김 718
 
7.2%
시 658
 
6.6%
도 656
 
6.6%
경 653
 
6.6%
남 652
 
6.6%
로 644
 
6.5%
길 467
 
4.7%
번 465
 
4.7%
Other values (148) 3534
35.6%
Decimal Number
ValueCountFrequency (%)
1 795
21.8%
2 517
14.2%
3 390
10.7%
4 354
9.7%
5 337
9.2%
6 293
 
8.0%
0 271
 
7.4%
9 252
 
6.9%
7 246
 
6.7%
8 190
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
A 12
57.1%
B 4
 
19.0%
C 3
 
14.3%
F 1
 
4.8%
D 1
 
4.8%
Space Separator
ValueCountFrequency (%)
2825
100.0%
Close Punctuation
ValueCountFrequency (%)
) 328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 328
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%
Other Punctuation
ValueCountFrequency (%)
, 178
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9914
56.6%
Common 7581
43.3%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 747
 
7.5%
해 720
 
7.3%
김 718
 
7.2%
시 658
 
6.6%
도 656
 
6.6%
경 653
 
6.6%
남 652
 
6.6%
로 644
 
6.5%
길 467
 
4.7%
번 465
 
4.7%
Other values (148) 3534
35.6%
Common
ValueCountFrequency (%)
2825
37.3%
1 795
 
10.5%
2 517
 
6.8%
3 390
 
5.1%
4 354
 
4.7%
5 337
 
4.4%
) 328
 
4.3%
( 328
 
4.3%
6 293
 
3.9%
- 276
 
3.6%
Other values (6) 1138
15.0%
Latin
ValueCountFrequency (%)
A 12
57.1%
B 4
 
19.0%
C 3
 
14.3%
F 1
 
4.8%
D 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9914
56.6%
ASCII 7602
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2825
37.2%
1 795
 
10.5%
2 517
 
6.8%
3 390
 
5.1%
4 354
 
4.7%
5 337
 
4.4%
) 328
 
4.3%
( 328
 
4.3%
6 293
 
3.9%
- 276
 
3.6%
Other values (11) 1159
15.2%
Hangul
ValueCountFrequency (%)
상 747
 
7.5%
해 720
 
7.3%
김 718
 
7.2%
시 658
 
6.6%
도 656
 
6.6%
경 653
 
6.6%
남 652
 
6.6%
로 644
 
6.5%
길 467
 
4.7%
번 465
 
4.7%
Other values (148) 3534
35.6%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
식품제조가공업
531 
기타 식품제조가공업
139 
도시락제조업
 
1

Length

Max length10
Median length7
Mean length7.6199702
Min length6

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row기타 식품제조가공업
2nd row기타 식품제조가공업
3rd row기타 식품제조가공업
4th row기타 식품제조가공업
5th row기타 식품제조가공업

Common Values

ValueCountFrequency (%)
식품제조가공업 531
79.1%
기타 식품제조가공업 139
 
20.7%
도시락제조업 1
 
0.1%

Length

2023-12-12T18:33:52.044267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:33:52.147154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 670
82.7%
기타 139
 
17.2%
도시락제조업 1
 
0.1%

급수시설구분명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
상수도전용
382 
<NA>
204 
지하수전용
70 
상수도(음용)지하수(주방용)겸용
 
8
간이상수도
 
5

Length

Max length19
Median length5
Mean length4.880775
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상수도전용
2nd row지하수전용
3rd row상수도전용
4th row상수도전용
5th row상수도전용

Common Values

ValueCountFrequency (%)
상수도전용 382
56.9%
<NA> 204
30.4%
지하수전용 70
 
10.4%
상수도(음용)지하수(주방용)겸용 8
 
1.2%
간이상수도 5
 
0.7%
전용상수도(특정시설의 자가용 수도) 2
 
0.3%

Length

2023-12-12T18:33:52.248529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:33:52.349424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 382
56.6%
na 204
30.2%
지하수전용 70
 
10.4%
상수도(음용)지하수(주방용)겸용 8
 
1.2%
간이상수도 5
 
0.7%
전용상수도(특정시설의 2
 
0.3%
자가용 2
 
0.3%
수도 2
 
0.3%

시설총규모
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
상수도전용
382 
<NA>
204 
지하수전용
70 
상수도(음용)지하수(주방용)겸용
 
8
간이상수도
 
5

Length

Max length19
Median length5
Mean length4.880775
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상수도전용
2nd row지하수전용
3rd row상수도전용
4th row상수도전용
5th row상수도전용

Common Values

ValueCountFrequency (%)
상수도전용 382
56.9%
<NA> 204
30.4%
지하수전용 70
 
10.4%
상수도(음용)지하수(주방용)겸용 8
 
1.2%
간이상수도 5
 
0.7%
전용상수도(특정시설의 자가용 수도) 2
 
0.3%

Length

2023-12-12T18:33:52.465930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:33:52.575865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 382
56.6%
na 204
30.2%
지하수전용 70
 
10.4%
상수도(음용)지하수(주방용)겸용 8
 
1.2%
간이상수도 5
 
0.7%
전용상수도(특정시설의 2
 
0.3%
자가용 2
 
0.3%
수도 2
 
0.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
폐업
410 
영업/정상
261 

Length

Max length5
Median length2
Mean length3.1669151
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 410
61.1%
영업/정상 261
38.9%

Length

2023-12-12T18:33:52.705556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:33:52.809613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 410
61.1%
영업/정상 261
38.9%

위도
Real number (ℝ)

Distinct569
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.249366
Minimum35.171997
Maximum35.374304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2023-12-12T18:33:52.909827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.171997
5-th percentile35.194366
Q135.227771
median35.236369
Q335.272771
95-th percentile35.322681
Maximum35.374304
Range0.20230712
Interquartile range (IQR)0.045000017

Descriptive statistics

Standard deviation0.038425021
Coefficient of variation (CV)0.0010900911
Kurtosis-0.21464347
Mean35.249366
Median Absolute Deviation (MAD)0.014444548
Skewness0.70542396
Sum23652.325
Variance0.0014764822
MonotonicityNot monotonic
2023-12-12T18:33:53.047578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.2261402281 8
 
1.2%
35.2647857521 6
 
0.9%
35.2344525871 4
 
0.6%
35.322203178 4
 
0.6%
35.2396629514 4
 
0.6%
35.2499147259 4
 
0.6%
35.2270492503 4
 
0.6%
35.32276283 3
 
0.4%
35.2349365293 3
 
0.4%
35.2363685835 3
 
0.4%
Other values (559) 628
93.6%
ValueCountFrequency (%)
35.1719973331 1
0.1%
35.1729579967 1
0.1%
35.1756900423 1
0.1%
35.1772274223 1
0.1%
35.1781647861 1
0.1%
35.182945911 1
0.1%
35.1850671136 1
0.1%
35.1850970435 1
0.1%
35.1853033989 1
0.1%
35.18549719 2
0.3%
ValueCountFrequency (%)
35.3743044483 1
0.1%
35.3667542795 1
0.1%
35.3641454372 1
0.1%
35.3496214252 1
0.1%
35.3424542848 1
0.1%
35.3348691591 1
0.1%
35.334468661 1
0.1%
35.3334748487 1
0.1%
35.3330368504 1
0.1%
35.3315281486 1
0.1%

경도
Real number (ℝ)

Distinct569
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.84317
Minimum128.70719
Maximum128.97969
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2023-12-12T18:33:53.188439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70719
5-th percentile128.74923
Q1128.80327
median128.84322
Q3128.89635
95-th percentile128.9232
Maximum128.97969
Range0.27250069
Interquartile range (IQR)0.093076824

Descriptive statistics

Standard deviation0.057081284
Coefficient of variation (CV)0.00044302919
Kurtosis-0.84284061
Mean128.84317
Median Absolute Deviation (MAD)0.042492788
Skewness-0.089769
Sum86453.766
Variance0.003258273
MonotonicityNot monotonic
2023-12-12T18:33:53.323729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8129186564 8
 
1.2%
128.823101157 6
 
0.9%
128.9058060215 4
 
0.6%
128.9420377071 4
 
0.6%
128.900652145 4
 
0.6%
128.828280567 4
 
0.6%
128.8140444908 4
 
0.6%
128.7497769283 3
 
0.4%
128.9013542634 3
 
0.4%
128.9077927199 3
 
0.4%
Other values (559) 628
93.6%
ValueCountFrequency (%)
128.7071909253 1
0.1%
128.7187754984 1
0.1%
128.718973881 1
0.1%
128.7240276487 1
0.1%
128.7257408328 1
0.1%
128.7259828441 1
0.1%
128.7262089686 1
0.1%
128.7264345817 1
0.1%
128.7277172308 1
0.1%
128.7285720533 1
0.1%
ValueCountFrequency (%)
128.9796916147 1
 
0.1%
128.979509997 1
 
0.1%
128.9759086893 1
 
0.1%
128.9674288179 1
 
0.1%
128.9559449712 1
 
0.1%
128.9513671083 1
 
0.1%
128.9503320903 2
0.3%
128.9496978814 2
0.3%
128.9420377071 4
0.6%
128.9418184277 1
 
0.1%

Interactions

2023-12-12T18:33:46.058364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:33:45.754000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:33:46.176029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:33:45.897060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:33:53.411502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위생업태명급수시설구분명시설총규모영업상태명위도경도
위생업태명1.0000.3320.3320.2190.1250.000
급수시설구분명0.3321.0001.0000.1350.1470.193
시설총규모0.3321.0001.0000.1350.1470.193
영업상태명0.2190.1350.1351.0000.2140.068
위도0.1250.1470.1470.2141.0000.747
경도0.0000.1930.1930.0680.7471.000
2023-12-12T18:33:53.514965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위생업태명시설총규모영업상태명급수시설구분명
위생업태명1.0000.2660.3580.266
시설총규모0.2661.0000.1651.000
영업상태명0.3580.1651.0000.165
급수시설구분명0.2661.0000.1651.000
2023-12-12T18:33:53.614415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도위생업태명급수시설구분명시설총규모영업상태명
위도1.000-0.0810.0740.0610.0610.163
경도-0.0811.0000.0000.0820.0820.041
위생업태명0.0740.0001.0000.2660.2660.358
급수시설구분명0.0610.0820.2661.0001.0000.165
시설총규모0.0610.0820.2661.0001.0000.165
영업상태명0.1630.0410.3580.1650.1651.000

Missing values

2023-12-12T18:33:46.675886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:33:46.874797image/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.
2023-12-12T18:33:47.049367image/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

사업장명소재지전화소재지면적지번주소도로명주소위생업태명급수시설구분명시설총규모영업상태명위도경도
0도우055-331-5553301경상남도 김해시 화목동 587-5번지경상남도 김해시 칠산로179번길 124 (화목동)기타 식품제조가공업상수도전용상수도전용영업/정상35.197184128.843392
1만복쏠트055-337-378915.12경상남도 김해시 대청동 315-2번지 재영프라자122호경상남도 김해시 삼문로 26, 122호 (대청동, 재영프라자)기타 식품제조가공업지하수전용지하수전용영업/정상35.19248128.803571
2참그린<NA>296경상남도 김해시 진례면 초전리 816-5번지경상남도 김해시 진례면 진례로 103, B동기타 식품제조가공업상수도전용상수도전용영업/정상35.237147128.751125
3주식회사씨엠지바이오팜<NA>100.11경상남도 김해시 주촌면 원지리 477-1번지경상남도 김해시 주촌면 서부로1701번안길 186, 2층기타 식품제조가공업상수도전용상수도전용영업/정상35.24978128.836774
4(주)마이크로파우더<NA>277.87경상남도 김해시 주촌면 선지리 750-6경상남도 김해시 주촌면 선천로 63-4기타 식품제조가공업상수도전용상수도전용영업/정상35.236471128.840324
5농협김해유통센터055-310-7115316.2경상남도 김해시 신문동 1421번지 김해농수산물종합유통센타경상남도 김해시 칠산로 128, 김해농수산물종합유통센타 (신문동)기타 식품제조가공업상수도전용상수도전용영업/정상35.185097128.835401
6고운동커피로스터스055-325-552069경상남도 김해시 화목동 392-13번지경상남도 김해시 칠산로335번길 2 (화목동)기타 식품제조가공업상수도전용상수도전용영업/정상35.202449128.850382
7로스코프(Roascoff)055-312-741325.14경상남도 김해시 흥동 30-1번지경상남도 김해시 흥동로 38, 1층 (흥동)기타 식품제조가공업상수도전용상수도전용영업/정상35.222141128.852783
8동양식품<NA>792경상남도 김해시 한림면 장방리 799-1번지경상남도 김해시 한림면 장방로 250, 1층기타 식품제조가공업상수도전용상수도전용영업/정상35.328854128.780207
9(주)빙그레055-340-220011,251.35경상남도 김해시 한림면 1078-1번지경상남도 김해시 한림면 고모로 768식품제조가공업상수도전용상수도전용영업/정상35.298193128.801397
사업장명소재지전화소재지면적지번주소도로명주소위생업태명급수시설구분명시설총규모영업상태명위도경도
661나눔유통055-326-038446.2경상남도 김해시 부원동 170-14번지경상남도 김해시 활천로5번길 4 (부원동)식품제조가공업<NA><NA>폐업35.228231128.893779
662예가F&B<NA>68.82경상남도 김해시 화목동 442-12경상남도 김해시 칠산로347번길 6-3, 1층 (화목동)기타 식품제조가공업상수도전용상수도전용폐업35.203797128.850387
663(주)만만요리연구소055-326-6218146.97경상남도 김해시 어방동 1049-9경상남도 김해시 분성로 575, 2층 (어방동)기타 식품제조가공업상수도전용상수도전용폐업35.236087128.909067
664서부커피로스터스<NA>23.95경상남도 김해시 봉황동 6-2번지 1층경상남도 김해시 봉황대길 63, 1층 (봉황동)기타 식품제조가공업상수도전용상수도전용폐업35.230006128.880011
665삼천리F&B<NA>63.96경상남도 김해시 풍유동 393-2경상남도 김해시 칠산로387번길 70, A동 (풍유동)기타 식품제조가공업지하수전용지하수전용폐업35.209981128.848652
666릴리로스터즈<NA>49.5경상남도 김해시 봉황동 223-10번지 1층경상남도 김해시 봉황대길 46, 1층 (봉황동)기타 식품제조가공업상수도전용상수도전용폐업35.228924128.878717
667내고장식품055-331-0711124.09경상남도 김해시 삼계동 524번지경상남도 김해시 가야로51번길 10-20 (삼계동)식품제조가공업<NA><NA>폐업35.270367128.866777
668극동식품055-342-638270경상남도 김해시 한림면 장방리 839-10번지경상남도 김해시 한림면 장방로 327식품제조가공업<NA><NA>폐업35.333037128.785539
669세운식품055-338-66881,899.68경상남도 김해시 주촌면 천곡리 503번지경상남도 김해시 주촌면 서부로 1629식품제조가공업<NA><NA>폐업35.237377128.829959
670한아름도시락055-334-6204341.61경상남도 김해시 삼계동 1104-3번지경상남도 김해시 안곡로 27 (삼계동)식품제조가공업<NA><NA>폐업35.271241128.857867