Overview

Dataset statistics

Number of variables7
Number of observations243
Missing cells297
Missing cells (%)17.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.4 KiB
Average record size in memory56.5 B

Variable types

Categorical2
Text5

Dataset

Description부산광역시 도시재생종합정보관리시스템의 데이터로 구분,사업관리번호,주요사업내용,주소,연락처,제품명,수정일자 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15122135/fileData.do

Alerts

구분 is highly overall correlated with 수정일자High correlation
수정일자 is highly overall correlated with 구분High correlation
주요사업내용 has 15 (6.2%) missing valuesMissing
연락처 has 108 (44.4%) missing valuesMissing
제품명 has 174 (71.6%) missing valuesMissing
사업관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:50:33.484899
Analysis finished2023-12-12 21:50:34.257757
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
마을공동체
174 
마을기업
69 

Length

Max length5
Median length5
Mean length4.7160494
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
마을공동체 174
71.6%
마을기업 69
 
28.4%

Length

2023-12-13T06:50:34.333213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:50:34.420402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을공동체 174
71.6%
마을기업 69
 
28.4%

사업관리번호
Text

UNIQUE 

Distinct243
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T06:50:34.666564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2430
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique243 ?
Unique (%)100.0%

Sample

1st rowTCP0000160
2nd rowTCP0000159
3rd rowTCP0000158
4th rowTCP0000157
5th rowTCP0000156
ValueCountFrequency (%)
tcp0000160 1
 
0.4%
tcu0000135 1
 
0.4%
tcu0000088 1
 
0.4%
tcu0000101 1
 
0.4%
tcu0000100 1
 
0.4%
tcu0000099 1
 
0.4%
tcu0000098 1
 
0.4%
tcu0000097 1
 
0.4%
tcu0000095 1
 
0.4%
tcu0000094 1
 
0.4%
Other values (233) 233
95.9%
2023-12-13T06:50:35.044256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1116
45.9%
T 243
 
10.0%
C 243
 
10.0%
1 198
 
8.1%
U 174
 
7.2%
P 69
 
2.8%
9 52
 
2.1%
4 51
 
2.1%
3 51
 
2.1%
2 50
 
2.1%
Other values (4) 183
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1701
70.0%
Uppercase Letter 729
30.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1116
65.6%
1 198
 
11.6%
9 52
 
3.1%
4 51
 
3.0%
3 51
 
3.0%
2 50
 
2.9%
5 47
 
2.8%
7 46
 
2.7%
6 45
 
2.6%
8 45
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
T 243
33.3%
C 243
33.3%
U 174
23.9%
P 69
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1701
70.0%
Latin 729
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1116
65.6%
1 198
 
11.6%
9 52
 
3.1%
4 51
 
3.0%
3 51
 
3.0%
2 50
 
2.9%
5 47
 
2.8%
7 46
 
2.7%
6 45
 
2.6%
8 45
 
2.6%
Latin
ValueCountFrequency (%)
T 243
33.3%
C 243
33.3%
U 174
23.9%
P 69
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2430
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1116
45.9%
T 243
 
10.0%
C 243
 
10.0%
1 198
 
8.1%
U 174
 
7.2%
P 69
 
2.8%
9 52
 
2.1%
4 51
 
2.1%
3 51
 
2.1%
2 50
 
2.1%
Other values (4) 183
 
7.5%

주요사업내용
Text

MISSING 

Distinct217
Distinct (%)95.2%
Missing15
Missing (%)6.2%
Memory size2.0 KiB
2023-12-13T06:50:35.340710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length284
Median length50
Mean length24.807018
Min length3

Characters and Unicode

Total characters5656
Distinct characters449
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique212 ?
Unique (%)93.0%

Sample

1st row중장비 실습교육 및 운용
2nd row곰국 제조 및 판매+지역특산물 판매
3rd row두부+메주 가공 판매
4th row지역특산품(미역+다시마 등) 판매
5th row돌봄사업
ValueCountFrequency (%)
운영 83
 
6.6%
등 54
 
4.3%
및 46
 
3.6%
판매 31
 
2.5%
마을 24
 
1.9%
프로그램 16
 
1.3%
사업 12
 
0.9%
체험 12
 
0.9%
환경개선사업 9
 
0.7%
활동 9
 
0.7%
Other values (720) 968
76.6%
2023-12-13T06:50:35.841312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1050
 
18.6%
, 239
 
4.2%
마 116
 
2.1%
을 116
 
2.1%
사 107
 
1.9%
업 107
 
1.9%
영 99
 
1.8%
운 99
 
1.8%
기 75
 
1.3%
동 69
 
1.2%
Other values (439) 3579
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4220
74.6%
Space Separator 1050
 
18.6%
Other Punctuation 272
 
4.8%
Decimal Number 42
 
0.7%
Close Punctuation 22
 
0.4%
Open Punctuation 22
 
0.4%
Uppercase Letter 11
 
0.2%
Math Symbol 7
 
0.1%
Dash Punctuation 4
 
0.1%
Final Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 116
 
2.7%
을 116
 
2.7%
사 107
 
2.5%
업 107
 
2.5%
영 99
 
2.3%
운 99
 
2.3%
기 75
 
1.8%
동 69
 
1.6%
공 63
 
1.5%
화 58
 
1.4%
Other values (406) 3311
78.5%
Decimal Number
ValueCountFrequency (%)
1 8
19.0%
2 7
16.7%
0 6
14.3%
7 4
9.5%
8 4
9.5%
3 3
 
7.1%
6 3
 
7.1%
5 3
 
7.1%
4 3
 
7.1%
9 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
M 2
18.2%
E 2
18.2%
I 1
9.1%
Y 1
9.1%
B 1
9.1%
N 1
9.1%
D 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 239
87.9%
. 19
 
7.0%
· 7
 
2.6%
: 4
 
1.5%
" 2
 
0.7%
/ 1
 
0.4%
Final Punctuation
ValueCountFrequency (%)
’ 2
66.7%
” 1
33.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
66.7%
“ 1
33.3%
Space Separator
ValueCountFrequency (%)
1050
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Math Symbol
ValueCountFrequency (%)
+ 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4220
74.6%
Common 1425
 
25.2%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 116
 
2.7%
을 116
 
2.7%
사 107
 
2.5%
업 107
 
2.5%
영 99
 
2.3%
운 99
 
2.3%
기 75
 
1.8%
동 69
 
1.6%
공 63
 
1.5%
화 58
 
1.4%
Other values (406) 3311
78.5%
Common
ValueCountFrequency (%)
1050
73.7%
, 239
 
16.8%
) 22
 
1.5%
( 22
 
1.5%
. 19
 
1.3%
1 8
 
0.6%
· 7
 
0.5%
+ 7
 
0.5%
2 7
 
0.5%
0 6
 
0.4%
Other values (15) 38
 
2.7%
Latin
ValueCountFrequency (%)
S 2
18.2%
M 2
18.2%
E 2
18.2%
I 1
9.1%
Y 1
9.1%
B 1
9.1%
N 1
9.1%
D 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4220
74.6%
ASCII 1423
 
25.2%
None 7
 
0.1%
Punctuation 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1050
73.8%
, 239
 
16.8%
) 22
 
1.5%
( 22
 
1.5%
. 19
 
1.3%
1 8
 
0.6%
+ 7
 
0.5%
2 7
 
0.5%
0 6
 
0.4%
7 4
 
0.3%
Other values (18) 39
 
2.7%
Hangul
ValueCountFrequency (%)
마 116
 
2.7%
을 116
 
2.7%
사 107
 
2.5%
업 107
 
2.5%
영 99
 
2.3%
운 99
 
2.3%
기 75
 
1.8%
동 69
 
1.6%
공 63
 
1.5%
화 58
 
1.4%
Other values (406) 3311
78.5%
None
ValueCountFrequency (%)
· 7
100.0%
Punctuation
ValueCountFrequency (%)
’ 2
33.3%
‘ 2
33.3%
“ 1
16.7%
” 1
16.7%

주소
Text

Distinct239
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-13T06:50:36.222930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length36
Mean length26.765432
Min length13

Characters and Unicode

Total characters6504
Distinct characters205
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

Unique235 ?
Unique (%)96.7%

Sample

1st row부산광역시 기장군 일광면 이천10길 18-1
2nd row부산광역시 기장군 철마면 철마로 450
3rd row부산광역시 기장군 철마면 곰내길 261
4th row부산광역시 기장군 일광면 문오성길 319
5th row부산광역시 사상구 낙동대로 776번길 40(엄궁동)
ValueCountFrequency (%)
부산광역시 243
 
19.7%
서구 33
 
2.7%
사상구 33
 
2.7%
부산진구 25
 
2.0%
동구 24
 
1.9%
금정구 21
 
1.7%
사하구 17
 
1.4%
해운대구 17
 
1.4%
영도구 14
 
1.1%
일원 13
 
1.1%
Other values (588) 792
64.3%
2023-12-13T06:50:36.807593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
994
 
15.3%
산 291
 
4.5%
1 283
 
4.4%
부 279
 
4.3%
동 268
 
4.1%
광 252
 
3.9%
시 250
 
3.8%
구 250
 
3.8%
역 243
 
3.7%
2 228
 
3.5%
Other values (195) 3166
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3747
57.6%
Decimal Number 1328
 
20.4%
Space Separator 994
 
15.3%
Close Punctuation 149
 
2.3%
Open Punctuation 149
 
2.3%
Dash Punctuation 103
 
1.6%
Other Punctuation 32
 
0.5%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 291
 
7.8%
부 279
 
7.4%
동 268
 
7.2%
광 252
 
6.7%
시 250
 
6.7%
구 250
 
6.7%
역 243
 
6.5%
로 196
 
5.2%
길 134
 
3.6%
번 122
 
3.3%
Other values (178) 1462
39.0%
Decimal Number
ValueCountFrequency (%)
1 283
21.3%
2 228
17.2%
3 156
11.7%
4 115
8.7%
5 113
 
8.5%
6 96
 
7.2%
0 89
 
6.7%
7 88
 
6.6%
9 83
 
6.2%
8 77
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
994
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Other Punctuation
ValueCountFrequency (%)
, 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3747
57.6%
Common 2755
42.4%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 291
 
7.8%
부 279
 
7.4%
동 268
 
7.2%
광 252
 
6.7%
시 250
 
6.7%
구 250
 
6.7%
역 243
 
6.5%
로 196
 
5.2%
길 134
 
3.6%
번 122
 
3.3%
Other values (178) 1462
39.0%
Common
ValueCountFrequency (%)
994
36.1%
1 283
 
10.3%
2 228
 
8.3%
3 156
 
5.7%
) 149
 
5.4%
( 149
 
5.4%
4 115
 
4.2%
5 113
 
4.1%
- 103
 
3.7%
6 96
 
3.5%
Other values (5) 369
 
13.4%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3747
57.6%
ASCII 2757
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
994
36.1%
1 283
 
10.3%
2 228
 
8.3%
3 156
 
5.7%
) 149
 
5.4%
( 149
 
5.4%
4 115
 
4.2%
5 113
 
4.1%
- 103
 
3.7%
6 96
 
3.5%
Other values (7) 371
 
13.5%
Hangul
ValueCountFrequency (%)
산 291
 
7.8%
부 279
 
7.4%
동 268
 
7.2%
광 252
 
6.7%
시 250
 
6.7%
구 250
 
6.7%
역 243
 
6.5%
로 196
 
5.2%
길 134
 
3.6%
번 122
 
3.3%
Other values (178) 1462
39.0%

연락처
Text

MISSING 

Distinct111
Distinct (%)82.2%
Missing108
Missing (%)44.4%
Memory size2.0 KiB
2023-12-13T06:50:37.111720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.088889
Min length12

Characters and Unicode

Total characters1632
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

Unique100 ?
Unique (%)74.1%

Sample

1st row051-723-5525
2nd row051-751-8114
3rd row051-721-9255
4th row051-723-0905
5th row051-328-0284
ValueCountFrequency (%)
051-440-4285 6
 
4.4%
051-440-4286 6
 
4.4%
051-440-4284 5
 
3.7%
051-309-2075 4
 
3.0%
051-749-2906 2
 
1.5%
051-256-4788 2
 
1.5%
051-462-5200 2
 
1.5%
051-959-0012 2
 
1.5%
051-896-2320 2
 
1.5%
051-749-6882 2
 
1.5%
Other values (101) 102
75.6%
2023-12-13T06:50:37.534552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 270
16.5%
0 269
16.5%
5 240
14.7%
1 209
12.8%
4 139
8.5%
2 117
7.2%
8 101
 
6.2%
7 78
 
4.8%
3 72
 
4.4%
6 69
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1362
83.5%
Dash Punctuation 270
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 269
19.8%
5 240
17.6%
1 209
15.3%
4 139
10.2%
2 117
8.6%
8 101
 
7.4%
7 78
 
5.7%
3 72
 
5.3%
6 69
 
5.1%
9 68
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1632
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 270
16.5%
0 269
16.5%
5 240
14.7%
1 209
12.8%
4 139
8.5%
2 117
7.2%
8 101
 
6.2%
7 78
 
4.8%
3 72
 
4.4%
6 69
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 270
16.5%
0 269
16.5%
5 240
14.7%
1 209
12.8%
4 139
8.5%
2 117
7.2%
8 101
 
6.2%
7 78
 
4.8%
3 72
 
4.4%
6 69
 
4.2%

제품명
Text

MISSING 

Distinct67
Distinct (%)97.1%
Missing174
Missing (%)71.6%
Memory size2.0 KiB
2023-12-13T06:50:37.857422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length19
Mean length9.3043478
Min length1

Characters and Unicode

Total characters642
Distinct characters214
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

Unique66 ?
Unique (%)95.7%

Sample

1st row중장비 실습교육
2nd row곰국+지역특산물
3rd row두부+메주
4th row지역특산품
5th row돌봄교육
ValueCountFrequency (%)
및 9
 
6.2%
판매 6
 
4.1%
커피 4
 
2.8%
체험 3
 
2.1%
등 2
 
1.4%
무조청 1
 
0.7%
조청유과 1
 
0.7%
쌀조청 1
 
0.7%
카페 1
 
0.7%
국수체험 1
 
0.7%
Other values (116) 116
80.0%
2023-12-13T06:50:38.283300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
 
11.8%
, 24
 
3.7%
품 17
 
2.6%
+ 15
 
2.3%
체 10
 
1.6%
및 10
 
1.6%
마 9
 
1.4%
험 9
 
1.4%
기 9
 
1.4%
공 9
 
1.4%
Other values (204) 454
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 517
80.5%
Space Separator 76
 
11.8%
Other Punctuation 24
 
3.7%
Math Symbol 15
 
2.3%
Uppercase Letter 4
 
0.6%
Close Punctuation 3
 
0.5%
Open Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 17
 
3.3%
체 10
 
1.9%
및 10
 
1.9%
마 9
 
1.7%
험 9
 
1.7%
기 9
 
1.7%
공 9
 
1.7%
매 9
 
1.7%
리 8
 
1.5%
판 8
 
1.5%
Other values (197) 419
81.0%
Uppercase Letter
ValueCountFrequency (%)
E 2
50.0%
M 2
50.0%
Space Separator
ValueCountFrequency (%)
76
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Math Symbol
ValueCountFrequency (%)
+ 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 517
80.5%
Common 121
 
18.8%
Latin 4
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 17
 
3.3%
체 10
 
1.9%
및 10
 
1.9%
마 9
 
1.7%
험 9
 
1.7%
기 9
 
1.7%
공 9
 
1.7%
매 9
 
1.7%
리 8
 
1.5%
판 8
 
1.5%
Other values (197) 419
81.0%
Common
ValueCountFrequency (%)
76
62.8%
, 24
 
19.8%
+ 15
 
12.4%
) 3
 
2.5%
( 3
 
2.5%
Latin
ValueCountFrequency (%)
E 2
50.0%
M 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 517
80.5%
ASCII 125
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
60.8%
, 24
 
19.2%
+ 15
 
12.0%
) 3
 
2.4%
( 3
 
2.4%
E 2
 
1.6%
M 2
 
1.6%
Hangul
ValueCountFrequency (%)
품 17
 
3.3%
체 10
 
1.9%
및 10
 
1.9%
마 9
 
1.7%
험 9
 
1.7%
기 9
 
1.7%
공 9
 
1.7%
매 9
 
1.7%
리 8
 
1.5%
판 8
 
1.5%
Other values (197) 419
81.0%

수정일자
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-05-04
56 
2020-02-03
37 
<NA>
35 
2020-09-23
25 
2020-09-29
21 
Other values (8)
69 

Length

Max length10
Median length10
Mean length9.1358025
Min length4

Unique

Unique2 ?
Unique (%)0.8%

Sample

1st row2023-05-04
2nd row2023-05-04
3rd row2023-05-04
4th row2023-05-04
5th row2023-05-04

Common Values

ValueCountFrequency (%)
2023-05-04 56
23.0%
2020-02-03 37
15.2%
<NA> 35
14.4%
2020-09-23 25
10.3%
2020-09-29 21
 
8.6%
2020-09-22 18
 
7.4%
2020-01-30 15
 
6.2%
2023-05-09 12
 
4.9%
2020-01-31 8
 
3.3%
2020-09-28 8
 
3.3%
Other values (3) 8
 
3.3%

Length

2023-12-13T06:50:38.459269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-05-04 56
23.0%
2020-02-03 37
15.2%
na 35
14.4%
2020-09-23 25
10.3%
2020-09-29 21
 
8.6%
2020-09-22 18
 
7.4%
2020-01-30 15
 
6.2%
2023-05-09 12
 
4.9%
2020-01-31 8
 
3.3%
2020-09-28 8
 
3.3%
Other values (3) 8
 
3.3%

Correlations

2023-12-13T06:50:38.546895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분제품명수정일자
구분1.000NaN1.000
제품명NaN1.0001.000
수정일자1.0001.0001.000
2023-12-13T06:50:38.667692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분수정일자
구분1.0000.975
수정일자0.9751.000
2023-12-13T06:50:38.766020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분수정일자
구분1.0000.975
수정일자0.9751.000

Missing values

2023-12-13T06:50:34.014541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:50:34.117206image/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.
2023-12-13T06:50:34.206952image/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

구분사업관리번호주요사업내용주소연락처제품명수정일자
0마을기업TCP0000160중장비 실습교육 및 운용부산광역시 기장군 일광면 이천10길 18-1051-723-5525중장비 실습교육2023-05-04
1마을기업TCP0000159곰국 제조 및 판매+지역특산물 판매부산광역시 기장군 철마면 철마로 450051-751-8114곰국+지역특산물2023-05-04
2마을기업TCP0000158두부+메주 가공 판매부산광역시 기장군 철마면 곰내길 261051-721-9255두부+메주2023-05-04
3마을기업TCP0000157지역특산품(미역+다시마 등) 판매부산광역시 기장군 일광면 문오성길 319051-723-0905지역특산품2023-05-04
4마을기업TCP0000156돌봄사업부산광역시 사상구 낙동대로 776번길 40(엄궁동)051-328-0284돌봄교육2023-05-04
5마을기업TCP0000155음악다방 식음료 및 전통다과부산광역시 사상구 새벽로 194번길 55051-959-0012음악다방 식음료 및 전통다과2023-05-04
6마을기업TCP0000154원예체험부산광역시 사상구 강변대로 512(엄궁동, 농협화훼공판장)051-313-9569원예체험2023-05-04
7마을기업TCP0000153전통식품 제조부산광역시 사상구 가야대로405번길 7-22051-323-3211된장+고추장2023-05-04
8마을기업TCP0000152숲 생태교육부산광역시 사상구 대동로 115번길 13051-325-0347숲 탐방+자연물만들기2023-05-04
9마을기업TCP0000151불용컴퓨터 리싸이클링 사업부산광역시 사상구 낙동대로 910, 제에이동 317호(감전동, 마트월드)070-7677-8388컴퓨터용품2023-05-04
구분사업관리번호주요사업내용주소연락처제품명수정일자
233마을공동체TCU00000118090 생일상, 행복담은 밑반찬, 전통음식 만들기부산광역시 사상구 강선로13번길 32(덕포동)<NA><NA>2020-09-29
234마을공동체TCU0000010바리스타, 마을소식지발간, 전통혼례예식진행부산광역시 사상구 사상로 277번길 22-10070-7583-2650<NA>2020-09-29
235마을공동체TCU0000009부산시 행복마을만들기사업부산광역시 사상구 모라로110번길 85<NA><NA>2020-09-29
236마을공동체TCU0000008마을 내 청소활동부산광역시 사상구 모라로 192번길 21051-302-5523<NA>2020-09-29
237마을공동체TCU0000007수공예(가죽, 비즈, 한지, 리본, 천 등)부산광역시 사상구 모라로 192번길 20-83 나동 104호<NA><NA>2020-09-29
238마을공동체TCU0000006놀이터활성화사업, 마을환경정화부산광역시 사상구 모라3동 (모라로110번길129)051-304-9876<NA>2020-09-29
239마을공동체TCU0000005부산시 행복마을만들기사업부산광역시 사상구 사상로 483<NA><NA>2020-09-29
240마을공동체TCU0000004도서관 대출 업무부산광역시 사상구 모라로110번길 29(모라동, 3층)051-312-1391<NA>2020-09-29
241마을공동체TCU0000003부산시 행복마을만들기사업부산광역시 사상구 삼덕로46번안길 17-6<NA><NA>2020-09-29
242마을공동체TCU0000002삼락이 있는 신나는 마을축제, 우리마을 팸투어부산광역시 사상구 낙동대로 1258번길 36(삼락동)<NA><NA>2020-09-29