Overview

Dataset statistics

Number of variables7
Number of observations1043
Missing cells657
Missing cells (%)9.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.2 KiB
Average record size in memory56.1 B

Variable types

Categorical3
Text4

Dataset

Description대구광역시_동구_휴게음식점현황_20190513
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15052655&dataSetDetailId=150526552e5f46acc2ba8&provdMethod=FILE

Alerts

업종명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지(도로명) has 11 (1.1%) missing valuesMissing
연락처 has 646 (61.9%) missing valuesMissing

Reproduction

Analysis started2024-04-16 17:23:25.879699
Analysis finished2024-04-16 17:23:26.730123
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
휴게음식점
1043 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴게음식점 1043
100.0%

Length

2024-04-17T02:23:26.785062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:23:26.885304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 1043
100.0%

업태명
Categorical

Distinct13
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
기타 휴게음식점
465 
커피숍
227 
편의점
113 
일반조리판매
92 
다방
79 
Other values (8)
67 

Length

Max length8
Median length6
Mean length5.5158198
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 휴게음식점 465
44.6%
커피숍 227
21.8%
편의점 113
 
10.8%
일반조리판매 92
 
8.8%
다방 79
 
7.6%
패스트푸드 32
 
3.1%
전통찻집 10
 
1.0%
키즈카페 7
 
0.7%
아이스크림 5
 
0.5%
푸드트럭 5
 
0.5%
Other values (3) 8
 
0.8%

Length

2024-04-17T02:23:26.984068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 465
30.8%
휴게음식점 465
30.8%
커피숍 227
15.1%
편의점 113
 
7.5%
일반조리판매 92
 
6.1%
다방 79
 
5.2%
패스트푸드 32
 
2.1%
전통찻집 10
 
0.7%
키즈카페 7
 
0.5%
아이스크림 5
 
0.3%
Other values (4) 13
 
0.9%

업소명
Text

Distinct1029
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
2024-04-17T02:23:27.191778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length26
Mean length8.2627037
Min length1

Characters and Unicode

Total characters8618
Distinct characters622
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

Unique1018 ?
Unique (%)97.6%

Sample

1st row영남다방
2nd row동광다방
3rd row대화다방
4th row양지다방
5th row7.7다방
ValueCountFrequency (%)
gs25 16
 
1.2%
coffee 13
 
0.9%
세븐일레븐 10
 
0.7%
주)코리아세븐 10
 
0.7%
롯데리아 9
 
0.7%
투썸플레이스 8
 
0.6%
공차 7
 
0.5%
이시아폴리스점 7
 
0.5%
파스쿠찌 7
 
0.5%
씨유 7
 
0.5%
Other values (1146) 1278
93.1%
2024-04-17T02:23:27.575211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 383
 
4.4%
329
 
3.8%
스 251
 
2.9%
구 224
 
2.6%
대 210
 
2.4%
( 187
 
2.2%
) 187
 
2.2%
피 171
 
2.0%
이 167
 
1.9%
리 149
 
1.7%
Other values (612) 6360
73.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6839
79.4%
Uppercase Letter 465
 
5.4%
Lowercase Letter 431
 
5.0%
Space Separator 329
 
3.8%
Open Punctuation 187
 
2.2%
Close Punctuation 187
 
2.2%
Decimal Number 158
 
1.8%
Other Punctuation 22
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 383
 
5.6%
스 251
 
3.7%
구 224
 
3.3%
대 210
 
3.1%
피 171
 
2.5%
이 167
 
2.4%
리 149
 
2.2%
커 126
 
1.8%
신 124
 
1.8%
아 117
 
1.7%
Other values (546) 4917
71.9%
Lowercase Letter
ValueCountFrequency (%)
e 79
18.3%
o 50
11.6%
f 40
9.3%
c 31
 
7.2%
n 28
 
6.5%
a 28
 
6.5%
i 23
 
5.3%
r 20
 
4.6%
s 19
 
4.4%
u 16
 
3.7%
Other values (14) 97
22.5%
Uppercase Letter
ValueCountFrequency (%)
C 72
15.5%
S 48
 
10.3%
G 42
 
9.0%
P 35
 
7.5%
O 31
 
6.7%
F 27
 
5.8%
E 27
 
5.8%
U 20
 
4.3%
A 19
 
4.1%
D 17
 
3.7%
Other values (14) 127
27.3%
Decimal Number
ValueCountFrequency (%)
2 58
36.7%
5 49
31.0%
1 12
 
7.6%
0 8
 
5.1%
9 8
 
5.1%
8 7
 
4.4%
3 7
 
4.4%
4 4
 
2.5%
7 4
 
2.5%
6 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 8
36.4%
. 7
31.8%
& 4
18.2%
' 2
 
9.1%
? 1
 
4.5%
Space Separator
ValueCountFrequency (%)
329
100.0%
Open Punctuation
ValueCountFrequency (%)
( 187
100.0%
Close Punctuation
ValueCountFrequency (%)
) 187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6839
79.4%
Latin 896
 
10.4%
Common 883
 
10.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 383
 
5.6%
스 251
 
3.7%
구 224
 
3.3%
대 210
 
3.1%
피 171
 
2.5%
이 167
 
2.4%
리 149
 
2.2%
커 126
 
1.8%
신 124
 
1.8%
아 117
 
1.7%
Other values (546) 4917
71.9%
Latin
ValueCountFrequency (%)
e 79
 
8.8%
C 72
 
8.0%
o 50
 
5.6%
S 48
 
5.4%
G 42
 
4.7%
f 40
 
4.5%
P 35
 
3.9%
O 31
 
3.5%
c 31
 
3.5%
n 28
 
3.1%
Other values (38) 440
49.1%
Common
ValueCountFrequency (%)
329
37.3%
( 187
21.2%
) 187
21.2%
2 58
 
6.6%
5 49
 
5.5%
1 12
 
1.4%
, 8
 
0.9%
0 8
 
0.9%
9 8
 
0.9%
8 7
 
0.8%
Other values (8) 30
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6839
79.4%
ASCII 1779
 
20.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 383
 
5.6%
스 251
 
3.7%
구 224
 
3.3%
대 210
 
3.1%
피 171
 
2.5%
이 167
 
2.4%
리 149
 
2.2%
커 126
 
1.8%
신 124
 
1.8%
아 117
 
1.7%
Other values (546) 4917
71.9%
ASCII
ValueCountFrequency (%)
329
18.5%
( 187
 
10.5%
) 187
 
10.5%
e 79
 
4.4%
C 72
 
4.0%
2 58
 
3.3%
o 50
 
2.8%
5 49
 
2.8%
S 48
 
2.7%
G 42
 
2.4%
Other values (56) 678
38.1%

소재지(도로명)
Text

MISSING 

Distinct940
Distinct (%)91.1%
Missing11
Missing (%)1.1%
Memory size8.3 KiB
2024-04-17T02:23:27.889894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length51
Mean length30.339147
Min length20

Characters and Unicode

Total characters31310
Distinct characters315
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

Unique910 ?
Unique (%)88.2%

Sample

1st row대구광역시 동구 동부로 119 (신천동)
2nd row대구광역시 동구 송라로32길 25 (신암동)
3rd row대구광역시 동구 반야월로 116 (신기동)
4th row대구광역시 동구 송라로 19 (신천동)
5th row대구광역시 동구 아양로 141-1 (신암동)
ValueCountFrequency (%)
동구 1033
 
16.0%
대구광역시 1032
 
16.0%
1층 380
 
5.9%
신천동 214
 
3.3%
신암동 141
 
2.2%
동부로 107
 
1.7%
율하동 85
 
1.3%
149 84
 
1.3%
신서동 83
 
1.3%
효목동 63
 
1.0%
Other values (1001) 3224
50.0%
2024-04-17T02:23:28.381899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5414
17.3%
동 2654
 
8.5%
구 2253
 
7.2%
1 1542
 
4.9%
대 1262
 
4.0%
역 1070
 
3.4%
시 1061
 
3.4%
, 1057
 
3.4%
로 1050
 
3.4%
( 1037
 
3.3%
Other values (305) 12910
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17612
56.3%
Space Separator 5414
 
17.3%
Decimal Number 4915
 
15.7%
Other Punctuation 1066
 
3.4%
Open Punctuation 1037
 
3.3%
Close Punctuation 1037
 
3.3%
Dash Punctuation 149
 
0.5%
Uppercase Letter 48
 
0.2%
Lowercase Letter 21
 
0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2654
15.1%
구 2253
12.8%
대 1262
 
7.2%
역 1070
 
6.1%
시 1061
 
6.0%
로 1050
 
6.0%
광 1035
 
5.9%
신 637
 
3.6%
층 636
 
3.6%
길 408
 
2.3%
Other values (264) 5546
31.5%
Lowercase Letter
ValueCountFrequency (%)
e 4
19.0%
l 3
14.3%
w 2
9.5%
i 2
9.5%
p 2
9.5%
s 2
9.5%
h 1
 
4.8%
o 1
 
4.8%
u 1
 
4.8%
t 1
 
4.8%
Other values (2) 2
9.5%
Uppercase Letter
ValueCountFrequency (%)
A 20
41.7%
B 13
27.1%
C 5
 
10.4%
G 3
 
6.2%
S 1
 
2.1%
D 1
 
2.1%
H 1
 
2.1%
J 1
 
2.1%
V 1
 
2.1%
L 1
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 1542
31.4%
2 656
13.3%
0 465
 
9.5%
4 450
 
9.2%
3 393
 
8.0%
5 375
 
7.6%
6 300
 
6.1%
9 282
 
5.7%
8 230
 
4.7%
7 222
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 1057
99.2%
. 9
 
0.8%
Math Symbol
ValueCountFrequency (%)
~ 10
90.9%
→ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
5414
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1037
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1037
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17612
56.3%
Common 13629
43.5%
Latin 69
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2654
15.1%
구 2253
12.8%
대 1262
 
7.2%
역 1070
 
6.1%
시 1061
 
6.0%
로 1050
 
6.0%
광 1035
 
5.9%
신 637
 
3.6%
층 636
 
3.6%
길 408
 
2.3%
Other values (264) 5546
31.5%
Latin
ValueCountFrequency (%)
A 20
29.0%
B 13
18.8%
C 5
 
7.2%
e 4
 
5.8%
l 3
 
4.3%
G 3
 
4.3%
w 2
 
2.9%
i 2
 
2.9%
p 2
 
2.9%
s 2
 
2.9%
Other values (13) 13
18.8%
Common
ValueCountFrequency (%)
5414
39.7%
1 1542
 
11.3%
, 1057
 
7.8%
( 1037
 
7.6%
) 1037
 
7.6%
2 656
 
4.8%
0 465
 
3.4%
4 450
 
3.3%
3 393
 
2.9%
5 375
 
2.8%
Other values (8) 1203
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17612
56.3%
ASCII 13697
43.7%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5414
39.5%
1 1542
 
11.3%
, 1057
 
7.7%
( 1037
 
7.6%
) 1037
 
7.6%
2 656
 
4.8%
0 465
 
3.4%
4 450
 
3.3%
3 393
 
2.9%
5 375
 
2.7%
Other values (30) 1271
 
9.3%
Hangul
ValueCountFrequency (%)
동 2654
15.1%
구 2253
12.8%
대 1262
 
7.2%
역 1070
 
6.1%
시 1061
 
6.0%
로 1050
 
6.0%
광 1035
 
5.9%
신 637
 
3.6%
층 636
 
3.6%
길 408
 
2.3%
Other values (264) 5546
31.5%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

소재지(지번)
Text

Distinct836
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
2024-04-17T02:23:28.695633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length44
Mean length23.958773
Min length4

Characters and Unicode

Total characters24989
Distinct characters238
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

Unique756 ?
Unique (%)72.5%

Sample

1st row대구광역시 동구 신천동 70번지 4호
2nd row대구광역시 동구 신암동 166번지 23호
3rd row대구광역시 동구 신기동 158번지 8호
4th row대구광역시 동구 신천동 782번지 10호
5th row대구광역시 동구 신암동 148번지 3호
ValueCountFrequency (%)
대구광역시 1042
20.1%
동구 1041
20.1%
신천동 219
 
4.2%
신암동 150
 
2.9%
1호 119
 
2.3%
신서동 93
 
1.8%
율하동 92
 
1.8%
3호 85
 
1.6%
2호 68
 
1.3%
효목동 67
 
1.3%
Other values (783) 2205
42.6%
2024-04-17T02:23:29.183065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6039
24.2%
동 2162
 
8.7%
구 2122
 
8.5%
지 1139
 
4.6%
대 1111
 
4.4%
역 1056
 
4.2%
번 1050
 
4.2%
시 1048
 
4.2%
광 1043
 
4.2%
1 1040
 
4.2%
Other values (228) 7179
28.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14294
57.2%
Space Separator 6039
24.2%
Decimal Number 4609
 
18.4%
Other Punctuation 17
 
0.1%
Uppercase Letter 11
 
< 0.1%
Dash Punctuation 9
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2162
15.1%
구 2122
14.8%
지 1139
8.0%
대 1111
7.8%
역 1056
7.4%
번 1050
7.3%
시 1048
7.3%
광 1043
7.3%
호 789
 
5.5%
신 519
 
3.6%
Other values (203) 2255
15.8%
Decimal Number
ValueCountFrequency (%)
1 1040
22.6%
3 502
10.9%
5 499
10.8%
2 461
10.0%
4 416
 
9.0%
0 394
 
8.5%
8 355
 
7.7%
9 334
 
7.2%
6 332
 
7.2%
7 276
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
36.4%
G 2
18.2%
A 1
 
9.1%
V 1
 
9.1%
C 1
 
9.1%
L 1
 
9.1%
S 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 9
52.9%
, 8
47.1%
Space Separator
ValueCountFrequency (%)
6039
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Math Symbol
ValueCountFrequency (%)
→ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14294
57.2%
Common 10683
42.8%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2162
15.1%
구 2122
14.8%
지 1139
8.0%
대 1111
7.8%
역 1056
7.4%
번 1050
7.3%
시 1048
7.3%
광 1043
7.3%
호 789
 
5.5%
신 519
 
3.6%
Other values (203) 2255
15.8%
Common
ValueCountFrequency (%)
6039
56.5%
1 1040
 
9.7%
3 502
 
4.7%
5 499
 
4.7%
2 461
 
4.3%
4 416
 
3.9%
0 394
 
3.7%
8 355
 
3.3%
9 334
 
3.1%
6 332
 
3.1%
Other values (7) 311
 
2.9%
Latin
ValueCountFrequency (%)
B 4
33.3%
G 2
16.7%
e 1
 
8.3%
A 1
 
8.3%
V 1
 
8.3%
C 1
 
8.3%
L 1
 
8.3%
S 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14294
57.2%
ASCII 10694
42.8%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6039
56.5%
1 1040
 
9.7%
3 502
 
4.7%
5 499
 
4.7%
2 461
 
4.3%
4 416
 
3.9%
0 394
 
3.7%
8 355
 
3.3%
9 334
 
3.1%
6 332
 
3.1%
Other values (14) 322
 
3.0%
Hangul
ValueCountFrequency (%)
동 2162
15.1%
구 2122
14.8%
지 1139
8.0%
대 1111
7.8%
역 1056
7.4%
번 1050
7.3%
시 1048
7.3%
광 1043
7.3%
호 789
 
5.5%
신 519
 
3.6%
Other values (203) 2255
15.8%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

연락처
Text

MISSING 

Distinct371
Distinct (%)93.5%
Missing646
Missing (%)61.9%
Memory size8.3 KiB
2024-04-17T02:23:29.448795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.030227
Min length12

Characters and Unicode

Total characters4776
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

Unique363 ?
Unique (%)91.4%

Sample

1st row053-755-2556
2nd row053-941-2569
3rd row053-962-5335
4th row053-424-9939
5th row053-955-8777
ValueCountFrequency (%)
053-941-0019 13
 
3.3%
053-661-1209 6
 
1.5%
053-742-2631 4
 
1.0%
053-665-1052 3
 
0.8%
053-559-2080 2
 
0.5%
053-959-2277 2
 
0.5%
053-741-8772 2
 
0.5%
070-7092-7065 2
 
0.5%
053-964-0783 1
 
0.3%
053-961-4123 1
 
0.3%
Other values (361) 361
90.9%
2024-04-17T02:23:29.828557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 794
16.6%
5 699
14.6%
0 647
13.5%
3 631
13.2%
9 453
9.5%
8 284
 
5.9%
1 268
 
5.6%
6 264
 
5.5%
2 258
 
5.4%
7 247
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3982
83.4%
Dash Punctuation 794
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 699
17.6%
0 647
16.2%
3 631
15.8%
9 453
11.4%
8 284
7.1%
1 268
 
6.7%
6 264
 
6.6%
2 258
 
6.5%
7 247
 
6.2%
4 231
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 794
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4776
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 794
16.6%
5 699
14.6%
0 647
13.5%
3 631
13.2%
9 453
9.5%
8 284
 
5.9%
1 268
 
5.6%
6 264
 
5.5%
2 258
 
5.4%
7 247
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4776
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 794
16.6%
5 699
14.6%
0 647
13.5%
3 631
13.2%
9 453
9.5%
8 284
 
5.9%
1 268
 
5.6%
6 264
 
5.5%
2 258
 
5.4%
7 247
 
5.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
2019-05-13
1043 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-05-13
2nd row2019-05-13
3rd row2019-05-13
4th row2019-05-13
5th row2019-05-13

Common Values

ValueCountFrequency (%)
2019-05-13 1043
100.0%

Length

2024-04-17T02:23:29.961982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:23:30.054493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-05-13 1043
100.0%

Missing values

2024-04-17T02:23:26.467429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T02:23:26.576980image/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.
2024-04-17T02:23:26.666107image/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

업종명업태명업소명소재지(도로명)소재지(지번)연락처데이터기준일자
0휴게음식점다방영남다방대구광역시 동구 동부로 119 (신천동)대구광역시 동구 신천동 70번지 4호053-755-25562019-05-13
1휴게음식점다방동광다방대구광역시 동구 송라로32길 25 (신암동)대구광역시 동구 신암동 166번지 23호053-941-25692019-05-13
2휴게음식점다방대화다방대구광역시 동구 반야월로 116 (신기동)대구광역시 동구 신기동 158번지 8호053-962-53352019-05-13
3휴게음식점다방양지다방대구광역시 동구 송라로 19 (신천동)대구광역시 동구 신천동 782번지 10호053-424-99392019-05-13
4휴게음식점다방7.7다방대구광역시 동구 아양로 141-1 (신암동)대구광역시 동구 신암동 148번지 3호053-955-87772019-05-13
5휴게음식점다방승지다방대구광역시 동구 팔공산로 1676 (백안동)대구광역시 동구 백안동 510번지 1호053-982-05082019-05-13
6휴게음식점다방선화다방대구광역시 동구 송라로 141 (신암동)대구광역시 동구 신암동 485번지 22호053-956-89602019-05-13
7휴게음식점다방궁전다방대구광역시 동구 화랑로 189 (효목동)대구광역시 동구 효목동 197번지 5호053-959-62202019-05-13
8휴게음식점다방동신다방대구광역시 동구 동촌로16길 2, 지하1층 (검사동)대구광역시 동구 검사동 990번지 60호053-983-88782019-05-13
9휴게음식점다방팔공다방대구광역시 동구 팔공로 144 (불로동)대구광역시 동구 불로동 460번지 44호053-983-58882019-05-13
업종명업태명업소명소재지(도로명)소재지(지번)연락처데이터기준일자
1033휴게음식점기타 휴게음식점씨유(CU)동촌역점대구광역시 동구 동촌로16길 36, 1층 (검사동)대구광역시 동구 검사동 991번지 39호053-981-32772019-05-13
1034휴게음식점기타 휴게음식점흑화당 대구신세계점대구광역시 동구 동부로 149, 신세계동대구복합환승센터 지하1층 (신천동)대구광역시 동구 신천동 1506번지 신세계동대구복합환승센터<NA>2019-05-13
1035휴게음식점기타 휴게음식점조코만 삼겹떡볶이대구광역시 동구 평화로 14, 1층 (신암동)대구광역시 동구 신암동 784번지 51호<NA>2019-05-13
1036휴게음식점기타 휴게음식점스토리떡볶이대구광역시 동구 송라로2길 15, 1층 (신천동)대구광역시 동구 신천동 173번지 6호<NA>2019-05-13
1037휴게음식점기타 휴게음식점별에서 온 꼬치대구광역시 동구 경안로 808, 1층 (각산동)대구광역시 동구 각산동 383번지 15호<NA>2019-05-13
1038휴게음식점기타 휴게음식점카페플래닛대구광역시 동구 동부로 14-1, 1층 (신천동)대구광역시 동구 신천동 600번지 46호<NA>2019-05-13
1039휴게음식점기타 휴게음식점호텔앙코르대구광역시 동구 이노밸리로 7, 1층 (상매동)대구광역시 동구 상매동 505번지 9호<NA>2019-05-13
1040휴게음식점기타 휴게음식점라포렛대구광역시 동구 도평로51길 3, 1층 (도동)대구광역시 동구 도동 474번지<NA>2019-05-13
1041휴게음식점기타 휴게음식점커피공식대구광역시 동구 신암로 132, 1층 점포4호 (신암동, 신흥아파트)대구광역시 동구 신암동 484번지 3호 신흥아파트<NA>2019-05-13
1042휴게음식점기타 휴게음식점자미당대구광역시 동구 메디밸리로8길 12, 1층 (사복동)대구광역시 동구 사복동 847번지<NA>2019-05-13