Overview

Dataset statistics

Number of variables7
Number of observations576
Missing cells284
Missing cells (%)7.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.6 KiB
Average record size in memory56.2 B

Variable types

Text4
Categorical3

Dataset

Description경상북도 구미시 관내에 신고된 민간 체육시설 현황으로 상호, 주소, 전화번호, 업종등의 데이터를 제공하고 있습니다.
Author경상북도 구미시
URLhttps://www.data.go.kr/data/3071419/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업종 is highly overall correlated with 실내구분High correlation
실내구분 is highly overall correlated with 업종High correlation
실내구분 is highly imbalanced (96.7%)Imbalance
도로명주소 has 7 (1.2%) missing valuesMissing
전화번호 has 277 (48.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 07:43:39.232055
Analysis finished2023-12-12 07:43:39.948446
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct562
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T16:43:40.135058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length7.5868056
Min length2

Characters and Unicode

Total characters4370
Distinct characters414
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

Unique548 ?
Unique (%)95.1%

Sample

1st row새천년사우나스포츠
2nd row구미시 선산청소년수련관
3rd rowAQUA schule(아쿠아 슐레)
4th row스윔슐레 구미캠퍼스
5th row제이원 스파랜드
ValueCountFrequency (%)
태권도장 29
 
3.4%
골프 13
 
1.5%
당구장 11
 
1.3%
스크린골프 11
 
1.3%
당구클럽 10
 
1.2%
스크린 10
 
1.2%
스트라이크존 6
 
0.7%
gym 6
 
0.7%
휘트니스 6
 
0.7%
아카데미 5
 
0.6%
Other values (640) 734
87.3%
2023-12-12T16:43:40.585299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
 
6.1%
스 221
 
5.1%
장 193
 
4.4%
구 158
 
3.6%
도 139
 
3.2%
프 122
 
2.8%
태 121
 
2.8%
권 120
 
2.7%
당 115
 
2.6%
골 112
 
2.6%
Other values (404) 2804
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3747
85.7%
Space Separator 265
 
6.1%
Uppercase Letter 236
 
5.4%
Lowercase Letter 68
 
1.6%
Decimal Number 25
 
0.6%
Other Punctuation 9
 
0.2%
Close Punctuation 8
 
0.2%
Open Punctuation 8
 
0.2%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 221
 
5.9%
장 193
 
5.2%
구 158
 
4.2%
도 139
 
3.7%
프 122
 
3.3%
태 121
 
3.2%
권 120
 
3.2%
당 115
 
3.1%
골 112
 
3.0%
클 87
 
2.3%
Other values (342) 2359
63.0%
Uppercase Letter
ValueCountFrequency (%)
M 32
13.6%
S 21
 
8.9%
K 20
 
8.5%
A 18
 
7.6%
G 18
 
7.6%
T 18
 
7.6%
J 14
 
5.9%
P 12
 
5.1%
B 12
 
5.1%
Y 11
 
4.7%
Other values (15) 60
25.4%
Lowercase Letter
ValueCountFrequency (%)
e 6
 
8.8%
y 6
 
8.8%
s 6
 
8.8%
o 5
 
7.4%
m 5
 
7.4%
a 5
 
7.4%
r 4
 
5.9%
i 4
 
5.9%
d 3
 
4.4%
t 3
 
4.4%
Other values (10) 21
30.9%
Decimal Number
ValueCountFrequency (%)
2 13
52.0%
1 3
 
12.0%
0 3
 
12.0%
7 2
 
8.0%
4 2
 
8.0%
8 1
 
4.0%
3 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
& 4
44.4%
. 3
33.3%
′ 1
 
11.1%
＆ 1
 
11.1%
Space Separator
ValueCountFrequency (%)
265
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3747
85.7%
Common 319
 
7.3%
Latin 304
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 221
 
5.9%
장 193
 
5.2%
구 158
 
4.2%
도 139
 
3.7%
프 122
 
3.3%
태 121
 
3.2%
권 120
 
3.2%
당 115
 
3.1%
골 112
 
3.0%
클 87
 
2.3%
Other values (342) 2359
63.0%
Latin
ValueCountFrequency (%)
M 32
 
10.5%
S 21
 
6.9%
K 20
 
6.6%
A 18
 
5.9%
G 18
 
5.9%
T 18
 
5.9%
J 14
 
4.6%
P 12
 
3.9%
B 12
 
3.9%
Y 11
 
3.6%
Other values (35) 128
42.1%
Common
ValueCountFrequency (%)
265
83.1%
2 13
 
4.1%
) 8
 
2.5%
( 8
 
2.5%
& 4
 
1.3%
. 3
 
0.9%
1 3
 
0.9%
0 3
 
0.9%
7 2
 
0.6%
4 2
 
0.6%
Other values (7) 8
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3747
85.7%
ASCII 620
 
14.2%
Punctuation 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
42.7%
M 32
 
5.2%
S 21
 
3.4%
K 20
 
3.2%
A 18
 
2.9%
G 18
 
2.9%
T 18
 
2.9%
J 14
 
2.3%
2 13
 
2.1%
P 12
 
1.9%
Other values (49) 189
30.5%
Hangul
ValueCountFrequency (%)
스 221
 
5.9%
장 193
 
5.2%
구 158
 
4.2%
도 139
 
3.7%
프 122
 
3.3%
태 121
 
3.2%
권 120
 
3.2%
당 115
 
3.1%
골 112
 
3.0%
클 87
 
2.3%
Other values (342) 2359
63.0%
Punctuation
ValueCountFrequency (%)
′ 1
50.0%
’ 1
50.0%
None
ValueCountFrequency (%)
＆ 1
100.0%

지번주소
Text

Distinct526
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T16:43:40.939935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length44
Mean length21.206597
Min length13

Characters and Unicode

Total characters12215
Distinct characters181
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

Unique483 ?
Unique (%)83.9%

Sample

1st row경상북도 구미시 인의동 701-8
2nd row경상북도 구미시 선산읍 노상리 333-2
3rd row경상북도 구미시 부곡동 322-1
4th row경상북도 구미시 산동읍 신당리 1458
5th row경상북도 구미시 산동읍 신당리 1167-11
ValueCountFrequency (%)
경상북도 576
21.8%
구미시 576
21.8%
산동읍 54
 
2.0%
옥계동 48
 
1.8%
봉곡동 46
 
1.7%
형곡동 46
 
1.7%
고아읍 42
 
1.6%
신당리 37
 
1.4%
사곡동 30
 
1.1%
인의동 30
 
1.1%
Other values (657) 1154
43.7%
2023-12-12T16:43:41.447715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2612
21.4%
상 648
 
5.3%
구 610
 
5.0%
도 598
 
4.9%
미 584
 
4.8%
시 579
 
4.7%
경 578
 
4.7%
북 576
 
4.7%
동 542
 
4.4%
1 460
 
3.8%
Other values (171) 4428
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6715
55.0%
Space Separator 2612
 
21.4%
Decimal Number 2436
 
19.9%
Dash Punctuation 428
 
3.5%
Other Punctuation 18
 
0.1%
Uppercase Letter 3
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 648
 
9.7%
구 610
 
9.1%
도 598
 
8.9%
미 584
 
8.7%
시 579
 
8.6%
경 578
 
8.6%
북 576
 
8.6%
동 542
 
8.1%
곡 126
 
1.9%
리 117
 
1.7%
Other values (154) 1757
26.2%
Decimal Number
ValueCountFrequency (%)
1 460
18.9%
3 313
12.8%
4 310
12.7%
2 299
12.3%
6 207
8.5%
5 198
8.1%
0 185
7.6%
7 167
 
6.9%
8 160
 
6.6%
9 137
 
5.6%
Space Separator
ValueCountFrequency (%)
2612
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 428
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6715
55.0%
Common 5496
45.0%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 648
 
9.7%
구 610
 
9.1%
도 598
 
8.9%
미 584
 
8.7%
시 579
 
8.6%
경 578
 
8.6%
북 576
 
8.6%
동 542
 
8.1%
곡 126
 
1.9%
리 117
 
1.7%
Other values (154) 1757
26.2%
Common
ValueCountFrequency (%)
2612
47.5%
1 460
 
8.4%
- 428
 
7.8%
3 313
 
5.7%
4 310
 
5.6%
2 299
 
5.4%
6 207
 
3.8%
5 198
 
3.6%
0 185
 
3.4%
7 167
 
3.0%
Other values (5) 317
 
5.8%
Latin
ValueCountFrequency (%)
A 3
75.0%
e 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6715
55.0%
ASCII 5500
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2612
47.5%
1 460
 
8.4%
- 428
 
7.8%
3 313
 
5.7%
4 310
 
5.6%
2 299
 
5.4%
6 207
 
3.8%
5 198
 
3.6%
0 185
 
3.4%
7 167
 
3.0%
Other values (7) 321
 
5.8%
Hangul
ValueCountFrequency (%)
상 648
 
9.7%
구 610
 
9.1%
도 598
 
8.9%
미 584
 
8.7%
시 579
 
8.6%
경 578
 
8.6%
북 576
 
8.6%
동 542
 
8.1%
곡 126
 
1.9%
리 117
 
1.7%
Other values (154) 1757
26.2%

도로명주소
Text

MISSING 

Distinct549
Distinct (%)96.5%
Missing7
Missing (%)1.2%
Memory size4.6 KiB
2023-12-12T16:43:41.834919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length49
Mean length27.926186
Min length19

Characters and Unicode

Total characters15890
Distinct characters215
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

Unique529 ?
Unique (%)93.0%

Sample

1st row경상북도 구미시 인동북길 117 (인의동)
2nd row경상북도 구미시 선산읍 단계동길 270, 지하2층
3rd row경상북도 구미시 부곡길 90-4 (부곡동)
4th row경상북도 구미시 산동읍 신당1로 24, 바젤파크 5층 501호
5th row경상북도 구미시 산동읍 강동로 1159-57, B2층
ValueCountFrequency (%)
경상북도 569
 
16.9%
구미시 569
 
16.9%
2층 109
 
3.2%
3층 52
 
1.5%
산동읍 51
 
1.5%
옥계동 47
 
1.4%
형곡동 46
 
1.4%
봉곡동 45
 
1.3%
고아읍 42
 
1.2%
4층 36
 
1.1%
Other values (718) 1801
53.5%
2023-12-12T16:43:42.376393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2798
 
17.6%
상 695
 
4.4%
동 691
 
4.3%
구 628
 
4.0%
미 603
 
3.8%
도 600
 
3.8%
북 597
 
3.8%
시 595
 
3.7%
경 573
 
3.6%
1 569
 
3.6%
Other values (205) 7541
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8944
56.3%
Space Separator 2798
 
17.6%
Decimal Number 2614
 
16.5%
Open Punctuation 459
 
2.9%
Close Punctuation 459
 
2.9%
Other Punctuation 418
 
2.6%
Dash Punctuation 178
 
1.1%
Uppercase Letter 10
 
0.1%
Math Symbol 8
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 695
 
7.8%
동 691
 
7.7%
구 628
 
7.0%
미 603
 
6.7%
도 600
 
6.7%
북 597
 
6.7%
시 595
 
6.7%
경 573
 
6.4%
로 482
 
5.4%
층 289
 
3.2%
Other values (181) 3191
35.7%
Decimal Number
ValueCountFrequency (%)
1 569
21.8%
2 482
18.4%
3 363
13.9%
4 238
9.1%
0 215
 
8.2%
5 169
 
6.5%
7 161
 
6.2%
6 153
 
5.9%
8 135
 
5.2%
9 129
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
A 3
30.0%
D 1
 
10.0%
K 1
 
10.0%
C 1
 
10.0%
S 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 416
99.5%
. 2
 
0.5%
Space Separator
ValueCountFrequency (%)
2798
100.0%
Open Punctuation
ValueCountFrequency (%)
( 459
100.0%
Close Punctuation
ValueCountFrequency (%)
) 459
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8944
56.3%
Common 6934
43.6%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 695
 
7.8%
동 691
 
7.7%
구 628
 
7.0%
미 603
 
6.7%
도 600
 
6.7%
북 597
 
6.7%
시 595
 
6.7%
경 573
 
6.4%
로 482
 
5.4%
층 289
 
3.2%
Other values (181) 3191
35.7%
Common
ValueCountFrequency (%)
2798
40.4%
1 569
 
8.2%
2 482
 
7.0%
( 459
 
6.6%
) 459
 
6.6%
, 416
 
6.0%
3 363
 
5.2%
4 238
 
3.4%
0 215
 
3.1%
- 178
 
2.6%
Other values (7) 757
 
10.9%
Latin
ValueCountFrequency (%)
B 3
25.0%
A 3
25.0%
e 2
16.7%
D 1
 
8.3%
K 1
 
8.3%
C 1
 
8.3%
S 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8944
56.3%
ASCII 6946
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2798
40.3%
1 569
 
8.2%
2 482
 
6.9%
( 459
 
6.6%
) 459
 
6.6%
, 416
 
6.0%
3 363
 
5.2%
4 238
 
3.4%
0 215
 
3.1%
- 178
 
2.6%
Other values (14) 769
 
11.1%
Hangul
ValueCountFrequency (%)
상 695
 
7.8%
동 691
 
7.7%
구 628
 
7.0%
미 603
 
6.7%
도 600
 
6.7%
북 597
 
6.7%
시 595
 
6.7%
경 573
 
6.4%
로 482
 
5.4%
층 289
 
3.2%
Other values (181) 3191
35.7%

전화번호
Text

MISSING 

Distinct294
Distinct (%)98.3%
Missing277
Missing (%)48.1%
Memory size4.6 KiB
2023-12-12T16:43:42.712543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3588
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

Unique289 ?
Unique (%)96.7%

Sample

1st row054-473-6300
2nd row054-480-6003
3rd row054-453-2600
4th row054-473-0165
5th row054-475-8655
ValueCountFrequency (%)
054-444-3705 2
 
0.7%
054-465-7878 2
 
0.7%
054-457-4545 2
 
0.7%
054-442-5900 2
 
0.7%
054-475-3737 2
 
0.7%
054-473-7227 1
 
0.3%
054-456-3020 1
 
0.3%
054-458-8296 1
 
0.3%
054-482-5531 1
 
0.3%
054-453-9682 1
 
0.3%
Other values (284) 284
95.0%
2023-12-12T16:43:43.135811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 775
21.6%
- 598
16.7%
5 543
15.1%
0 504
14.0%
7 243
 
6.8%
6 198
 
5.5%
8 158
 
4.4%
1 156
 
4.3%
3 154
 
4.3%
2 149
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2990
83.3%
Dash Punctuation 598
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 775
25.9%
5 543
18.2%
0 504
16.9%
7 243
 
8.1%
6 198
 
6.6%
8 158
 
5.3%
1 156
 
5.2%
3 154
 
5.2%
2 149
 
5.0%
9 110
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 598
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 775
21.6%
- 598
16.7%
5 543
15.1%
0 504
14.0%
7 243
 
6.8%
6 198
 
5.5%
8 158
 
4.4%
1 156
 
4.3%
3 154
 
4.3%
2 149
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 775
21.6%
- 598
16.7%
5 543
15.1%
0 504
14.0%
7 243
 
6.8%
6 198
 
5.5%
8 158
 
4.4%
1 156
 
4.3%
3 154
 
4.3%
2 149
 
4.2%

업종
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
체육도장업
159 
당구장업
122 
체력단련장업
95 
골프연습장업
86 
가상체험 체육시설업
46 
Other values (10)
68 

Length

Max length10
Median length7
Mean length5.4635417
Min length4

Unique

Unique4 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
체육도장업 159
27.6%
당구장업 122
21.2%
체력단련장업 95
16.5%
골프연습장업 86
14.9%
가상체험 체육시설업 46
 
8.0%
체육교습업 22
 
3.8%
<NA> 19
 
3.3%
무도학원업 13
 
2.3%
수영장업 5
 
0.9%
종합체육시설업 3
 
0.5%
Other values (5) 6
 
1.0%

Length

2023-12-12T16:43:43.335723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
체육도장업 159
25.6%
당구장업 122
19.6%
체력단련장업 95
15.3%
골프연습장업 86
13.8%
가상체험 46
 
7.4%
체육시설업 46
 
7.4%
체육교습업 22
 
3.5%
na 19
 
3.1%
무도학원업 13
 
2.1%
수영장업 5
 
0.8%
Other values (6) 9
 
1.4%

실내구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
실내
574 
실외
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실내 574
99.7%
실외 2
 
0.3%

Length

2023-12-12T16:43:43.488163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:43:43.606840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 574
99.7%
실외 2
 
0.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-06-30
576 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-30
2nd row2023-06-30
3rd row2023-06-30
4th row2023-06-30
5th row2023-06-30

Common Values

ValueCountFrequency (%)
2023-06-30 576
100.0%

Length

2023-12-12T16:43:43.726820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:43:43.823505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-30 576
100.0%

Correlations

2023-12-12T16:43:43.881205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종실내구분
업종1.0000.865
실내구분0.8651.000
2023-12-12T16:43:43.958767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실내구분업종
실내구분1.0000.706
업종0.7061.000
2023-12-12T16:43:44.061748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종실내구분
업종1.0000.706
실내구분0.7061.000

Missing values

2023-12-12T16:43:39.736614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:43:39.823843image/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.
2023-12-12T16:43:39.904927image/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

상호지번주소도로명주소전화번호업종실내구분데이터기준일자
0새천년사우나스포츠경상북도 구미시 인의동 701-8경상북도 구미시 인동북길 117 (인의동)054-473-6300수영장업실내2023-06-30
1구미시 선산청소년수련관경상북도 구미시 선산읍 노상리 333-2경상북도 구미시 선산읍 단계동길 270, 지하2층054-480-6003수영장업실내2023-06-30
2AQUA schule(아쿠아 슐레)경상북도 구미시 부곡동 322-1경상북도 구미시 부곡길 90-4 (부곡동)054-453-2600수영장업실내2023-06-30
3스윔슐레 구미캠퍼스경상북도 구미시 산동읍 신당리 1458경상북도 구미시 산동읍 신당1로 24, 바젤파크 5층 501호<NA>수영장업실내2023-06-30
4제이원 스파랜드경상북도 구미시 산동읍 신당리 1167-11경상북도 구미시 산동읍 강동로 1159-57, B2층<NA>수영장업실내2023-06-30
5황상체육관경상북도 구미시 황상동 199-1경상북도 구미시 검성로 90-1 (황상동)054-473-0165체육도장업실내2023-06-30
6한일태권도장경상북도 구미시 도량동 639 도량 롯데캐슬 골드파크경상북도 구미시 문장로 111, 401~404호 (도량동, 도량 롯데캐슬 골드파크)<NA>체육도장업실내2023-06-30
7경일태권도경상북도 구미시 옥계동 543경상북도 구미시 흥안로 48, 209동 (옥계동)054-475-8655체육도장업실내2023-06-30
8중앙키즈태권도체육관경상북도 구미시 형곡동 151-9경상북도 구미시 형곡중앙로 24 (형곡동)054-452-8733체육도장업실내2023-06-30
9금호무술(권투)경상북도 구미시 사곡동 267-53경상북도 구미시 상사동로18길 16-5 (사곡동)054-462-1744체육도장업실내2023-06-30
상호지번주소도로명주소전화번호업종실내구분데이터기준일자
566스피드풋살구장경상북도 구미시 봉곡동 178경상북도 구미시 봉곡남로25길 31 (봉곡동)<NA>체육교습업실내2023-06-30
567피닉스 키즈 스포츠경상북도 구미시 봉곡동 106-3경상북도 구미시 봉곡북로13길 24 (봉곡동)<NA>체육교습업실내2023-06-30
568샬롬 코리아 사커스쿨경상북도 구미시 구평동 451-3경상북도 구미시 인동38길 15-6, 5층 (구평동)<NA>체육교습업실내2023-06-30
569샬롬코리아사커스쿨경상북도 구미시 산동읍 신당리 0경상북도 구미시 산동읍 신당4로1길 57, 203호<NA>체육교습업실내2023-06-30
570남구미풋살장경상북도 구미시 오태동 594-14경상북도 구미시 오태1길 9 (오태동)<NA>체육교습업실내2023-06-30
571몬스터 아카데미경상북도 구미시 산동읍 신당리 0경상북도 구미시 산동읍 신당4로1길 57, 202호<NA>체육교습업실내2023-06-30
572칠드런경상북도 구미시 옥계동 834-2경상북도 구미시 옥계북로 40, 9층 (옥계동)<NA>체육교습업실내2023-06-30
573점프윙스 줄넘기클럽 구미사곡점경상북도 구미시 사곡동 818경상북도 구미시 새마을로3길 17, 2층 (사곡동)<NA>체육교습업실내2023-06-30
574레브 유소년 축구 클럽경상북도 구미시 고아읍 문성리 1158경상북도 구미시 고아읍 들성로9길 25-7<NA>체육교습업실내2023-06-30
575산동포시즌 클라이밍경상북도 구미시 산동읍 신당리 1458 바젤-파크시티 제1동경상북도 구미시 산동읍 신당1로 24, 바젤-파크시티 제1동 5층<NA>인공암벽장업실내2023-06-30