Overview

Dataset statistics

Number of variables7
Number of observations925
Missing cells521
Missing cells (%)8.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.7 KiB
Average record size in memory56.1 B

Variable types

Text4
DateTime1
Categorical2

Dataset

Description대구광역시_동구_담배소매인지정현황_20230323
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15035585&dataSetDetailId=150355851e7d374d34c5d&provdMethod=FILE

Alerts

영업구분 has constant value ""Constant
법인구분 is highly imbalanced (61.7%)Imbalance
업소전화번호 has 513 (55.5%) missing valuesMissing

Reproduction

Analysis started2024-04-21 02:59:12.805392
Analysis finished2024-04-21 02:59:14.638695
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct835
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2024-04-21T11:59:15.433027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length7.9891892
Min length1

Characters and Unicode

Total characters7390
Distinct characters460
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique813 ?
Unique (%)87.9%

Sample

1st row지에스(GS)25 방촌우방점
2nd row필수장터
3rd row씨유 대구율원점
4th row세븐일레븐 대구청아람점
5th row진로할인마트
ValueCountFrequency (%)
세븐일레븐 56
 
4.4%
씨유 52
 
4.1%
지에스(gs)25 48
 
3.8%
48
 
3.8%
이마트24 26
 
2.0%
gs25 13
 
1.0%
주)코리아세븐 13
 
1.0%
주식회사 12
 
0.9%
나이스마트 10
 
0.8%
홈마트 8
 
0.6%
Other values (885) 990
77.6%
2024-04-21T11:59:16.870149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 387
 
5.2%
355
 
4.8%
대 246
 
3.3%
트 225
 
3.0%
구 225
 
3.0%
마 223
 
3.0%
동 146
 
2.0%
스 142
 
1.9%
신 140
 
1.9%
븐 139
 
1.9%
Other values (450) 5162
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6202
83.9%
Space Separator 355
 
4.8%
Decimal Number 276
 
3.7%
Uppercase Letter 236
 
3.2%
Close Punctuation 132
 
1.8%
Open Punctuation 129
 
1.7%
Dash Punctuation 53
 
0.7%
Other Punctuation 5
 
0.1%
Math Symbol 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 387
 
6.2%
대 246
 
4.0%
트 225
 
3.6%
구 225
 
3.6%
마 223
 
3.6%
동 146
 
2.4%
스 142
 
2.3%
신 140
 
2.3%
븐 139
 
2.2%
유 125
 
2.0%
Other values (414) 4204
67.8%
Uppercase Letter
ValueCountFrequency (%)
S 85
36.0%
G 83
35.2%
C 14
 
5.9%
U 8
 
3.4%
K 6
 
2.5%
L 6
 
2.5%
O 5
 
2.1%
D 5
 
2.1%
E 5
 
2.1%
R 3
 
1.3%
Other values (9) 16
 
6.8%
Decimal Number
ValueCountFrequency (%)
2 124
44.9%
5 90
32.6%
4 32
 
11.6%
1 9
 
3.3%
6 7
 
2.5%
3 6
 
2.2%
0 3
 
1.1%
9 3
 
1.1%
7 2
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 4
80.0%
& 1
 
20.0%
Space Separator
ValueCountFrequency (%)
355
100.0%
Close Punctuation
ValueCountFrequency (%)
) 132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Math Symbol
ValueCountFrequency (%)
∥ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6202
83.9%
Common 951
 
12.9%
Latin 237
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 387
 
6.2%
대 246
 
4.0%
트 225
 
3.6%
구 225
 
3.6%
마 223
 
3.6%
동 146
 
2.4%
스 142
 
2.3%
신 140
 
2.3%
븐 139
 
2.2%
유 125
 
2.0%
Other values (414) 4204
67.8%
Latin
ValueCountFrequency (%)
S 85
35.9%
G 83
35.0%
C 14
 
5.9%
U 8
 
3.4%
K 6
 
2.5%
L 6
 
2.5%
O 5
 
2.1%
D 5
 
2.1%
E 5
 
2.1%
R 3
 
1.3%
Other values (10) 17
 
7.2%
Common
ValueCountFrequency (%)
355
37.3%
) 132
 
13.9%
( 129
 
13.6%
2 124
 
13.0%
5 90
 
9.5%
- 53
 
5.6%
4 32
 
3.4%
1 9
 
0.9%
6 7
 
0.7%
3 6
 
0.6%
Other values (6) 14
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6199
83.9%
ASCII 1187
 
16.1%
Compat Jamo 3
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 387
 
6.2%
대 246
 
4.0%
트 225
 
3.6%
구 225
 
3.6%
마 223
 
3.6%
동 146
 
2.4%
스 142
 
2.3%
신 140
 
2.3%
븐 139
 
2.2%
유 125
 
2.0%
Other values (412) 4201
67.8%
ASCII
ValueCountFrequency (%)
355
29.9%
) 132
 
11.1%
( 129
 
10.9%
2 124
 
10.4%
5 90
 
7.6%
S 85
 
7.2%
G 83
 
7.0%
- 53
 
4.5%
4 32
 
2.7%
C 14
 
1.2%
Other values (25) 90
 
7.6%
Compat Jamo
ValueCountFrequency (%)
ㅇ 2
66.7%
ㅅ 1
33.3%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%

업소지번주소
Text

Distinct827
Distinct (%)89.9%
Missing5
Missing (%)0.5%
Memory size7.4 KiB
2024-04-21T11:59:17.826891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length21.527174
Min length1

Characters and Unicode

Total characters19805
Distinct characters282
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique811 ?
Unique (%)88.2%

Sample

1st row대구광역시 동구 방촌동 1119-77
2nd row대구광역시 동구 신서동 1011-2
3rd row대구광역시 동구 율하동 1492
4th row대구광역시 동구 신암동 1189-6
5th row대구광역시 동구 효목동 55 진로이스트타운
ValueCountFrequency (%)
대구광역시 839
 
18.8%
동구 838
 
18.7%
호 139
 
3.1%
신암동 118
 
2.6%
신천동 117
 
2.6%
효목동 67
 
1.5%
방촌동 63
 
1.4%
1호 62
 
1.4%
신서동 52
 
1.2%
1층 50
 
1.1%
Other values (1130) 2125
47.5%
2024-04-21T11:59:19.017572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3916
19.8%
동 1777
 
9.0%
구 1708
 
8.6%
1 1006
 
5.1%
대 883
 
4.5%
역 859
 
4.3%
시 859
 
4.3%
광 840
 
4.2%
지 654
 
3.3%
호 647
 
3.3%
Other values (272) 6656
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11568
58.4%
Decimal Number 4094
 
20.7%
Space Separator 3916
 
19.8%
Dash Punctuation 158
 
0.8%
Other Punctuation 27
 
0.1%
Uppercase Letter 24
 
0.1%
Lowercase Letter 10
 
0.1%
Math Symbol 3
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1777
15.4%
구 1708
14.8%
대 883
 
7.6%
역 859
 
7.4%
시 859
 
7.4%
광 840
 
7.3%
지 654
 
5.7%
호 647
 
5.6%
번 581
 
5.0%
신 372
 
3.2%
Other values (237) 2388
20.6%
Decimal Number
ValueCountFrequency (%)
1 1006
24.6%
2 436
10.6%
3 409
10.0%
5 393
 
9.6%
0 374
 
9.1%
6 335
 
8.2%
4 330
 
8.1%
9 273
 
6.7%
7 270
 
6.6%
8 268
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
H 5
20.8%
B 4
16.7%
A 4
16.7%
L 3
12.5%
C 2
 
8.3%
D 2
 
8.3%
M 1
 
4.2%
G 1
 
4.2%
T 1
 
4.2%
K 1
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 3
30.0%
a 2
20.0%
k 1
 
10.0%
s 1
 
10.0%
d 1
 
10.0%
n 1
 
10.0%
i 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 24
88.9%
/ 3
 
11.1%
Space Separator
ValueCountFrequency (%)
3916
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11568
58.4%
Common 8203
41.4%
Latin 34
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1777
15.4%
구 1708
14.8%
대 883
 
7.6%
역 859
 
7.4%
시 859
 
7.4%
광 840
 
7.3%
지 654
 
5.7%
호 647
 
5.6%
번 581
 
5.0%
신 372
 
3.2%
Other values (237) 2388
20.6%
Common
ValueCountFrequency (%)
3916
47.7%
1 1006
 
12.3%
2 436
 
5.3%
3 409
 
5.0%
5 393
 
4.8%
0 374
 
4.6%
6 335
 
4.1%
4 330
 
4.0%
9 273
 
3.3%
7 270
 
3.3%
Other values (8) 461
 
5.6%
Latin
ValueCountFrequency (%)
H 5
14.7%
B 4
11.8%
A 4
11.8%
L 3
8.8%
e 3
8.8%
a 2
 
5.9%
C 2
 
5.9%
D 2
 
5.9%
k 1
 
2.9%
M 1
 
2.9%
Other values (7) 7
20.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11568
58.4%
ASCII 8236
41.6%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3916
47.5%
1 1006
 
12.2%
2 436
 
5.3%
3 409
 
5.0%
5 393
 
4.8%
0 374
 
4.5%
6 335
 
4.1%
4 330
 
4.0%
9 273
 
3.3%
7 270
 
3.3%
Other values (24) 494
 
6.0%
Hangul
ValueCountFrequency (%)
동 1777
15.4%
구 1708
14.8%
대 883
 
7.6%
역 859
 
7.4%
시 859
 
7.4%
광 840
 
7.3%
지 654
 
5.7%
호 647
 
5.6%
번 581
 
5.0%
신 372
 
3.2%
Other values (237) 2388
20.6%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

업소도로명주소
Text

Distinct897
Distinct (%)97.3%
Missing3
Missing (%)0.3%
Memory size7.4 KiB
2024-04-21T11:59:20.066287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length55
Mean length27.90564
Min length1

Characters and Unicode

Total characters25729
Distinct characters302
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique890 ?
Unique (%)96.5%

Sample

1st row대구광역시 동구 화랑로80길 7-24. 1층 (방촌동)
2nd row대구광역시 동구 신서로 77 (신서동)
3rd row대구광역시 동구 율하동로10길 3-6. 1층 (율하동)
4th row대구광역시 동구 신성로 49-1 (신암동)
5th row대구광역시 동구 아양로 218. 303동 101.102.103.104.107호 (효목동. 진로이스트타운)
ValueCountFrequency (%)
대구광역시 902
 
17.0%
동구 902
 
17.0%
1층 204
 
3.8%
신암동 141
 
2.7%
신천동 130
 
2.5%
효목동 77
 
1.5%
방촌동 58
 
1.1%
율하동 53
 
1.0%
신서동 49
 
0.9%
동촌로 39
 
0.7%
Other values (1046) 2751
51.8%
2024-04-21T11:59:21.409590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4491
17.5%
동 2290
 
8.9%
구 1861
 
7.2%
1 1218
 
4.7%
대 981
 
3.8%
로 937
 
3.6%
역 928
 
3.6%
시 927
 
3.6%
) 904
 
3.5%
( 904
 
3.5%
Other values (292) 10288
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14542
56.5%
Space Separator 4491
 
17.5%
Decimal Number 4127
 
16.0%
Close Punctuation 904
 
3.5%
Open Punctuation 904
 
3.5%
Other Punctuation 607
 
2.4%
Dash Punctuation 105
 
0.4%
Uppercase Letter 33
 
0.1%
Lowercase Letter 9
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2290
15.7%
구 1861
12.8%
대 981
 
6.7%
로 937
 
6.4%
역 928
 
6.4%
시 927
 
6.4%
광 903
 
6.2%
신 483
 
3.3%
길 433
 
3.0%
호 276
 
1.9%
Other values (257) 4523
31.1%
Uppercase Letter
ValueCountFrequency (%)
B 8
24.2%
A 6
18.2%
H 5
15.2%
L 3
 
9.1%
C 3
 
9.1%
D 3
 
9.1%
M 1
 
3.0%
T 1
 
3.0%
K 1
 
3.0%
F 1
 
3.0%
Decimal Number
ValueCountFrequency (%)
1 1218
29.5%
2 550
13.3%
0 471
 
11.4%
3 367
 
8.9%
5 341
 
8.3%
4 330
 
8.0%
6 265
 
6.4%
7 212
 
5.1%
9 196
 
4.7%
8 177
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 3
33.3%
a 2
22.2%
s 1
 
11.1%
d 1
 
11.1%
n 1
 
11.1%
i 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 605
99.7%
/ 2
 
0.3%
Space Separator
ValueCountFrequency (%)
4491
100.0%
Close Punctuation
ValueCountFrequency (%)
) 904
100.0%
Open Punctuation
ValueCountFrequency (%)
( 904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14542
56.5%
Common 11145
43.3%
Latin 42
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2290
15.7%
구 1861
12.8%
대 981
 
6.7%
로 937
 
6.4%
역 928
 
6.4%
시 927
 
6.4%
광 903
 
6.2%
신 483
 
3.3%
길 433
 
3.0%
호 276
 
1.9%
Other values (257) 4523
31.1%
Common
ValueCountFrequency (%)
4491
40.3%
1 1218
 
10.9%
) 904
 
8.1%
( 904
 
8.1%
. 605
 
5.4%
2 550
 
4.9%
0 471
 
4.2%
3 367
 
3.3%
5 341
 
3.1%
4 330
 
3.0%
Other values (8) 964
 
8.6%
Latin
ValueCountFrequency (%)
B 8
19.0%
A 6
14.3%
H 5
11.9%
e 3
 
7.1%
L 3
 
7.1%
C 3
 
7.1%
D 3
 
7.1%
a 2
 
4.8%
s 1
 
2.4%
M 1
 
2.4%
Other values (7) 7
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14542
56.5%
ASCII 11186
43.5%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4491
40.1%
1 1218
 
10.9%
) 904
 
8.1%
( 904
 
8.1%
. 605
 
5.4%
2 550
 
4.9%
0 471
 
4.2%
3 367
 
3.3%
5 341
 
3.0%
4 330
 
3.0%
Other values (24) 1005
 
9.0%
Hangul
ValueCountFrequency (%)
동 2290
15.7%
구 1861
12.8%
대 981
 
6.7%
로 937
 
6.4%
역 928
 
6.4%
시 927
 
6.4%
광 903
 
6.2%
신 483
 
3.3%
길 433
 
3.0%
호 276
 
1.9%
Other values (257) 4523
31.1%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

업소전화번호
Text

MISSING 

Distinct396
Distinct (%)96.1%
Missing513
Missing (%)55.5%
Memory size7.4 KiB
2024-04-21T11:59:22.180864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.966019
Min length1

Characters and Unicode

Total characters4930
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

Unique385 ?
Unique (%)93.4%

Sample

1st row053-985-0750
2nd row053-981-9763
3rd row053-959-9210
4th row053-753-0133
5th row053-965-5602
ValueCountFrequency (%)
053-742-2631 5
 
1.2%
053-750-4482 3
 
0.7%
053-961-0448 3
 
0.7%
053-961-2776 2
 
0.5%
053-952-5166 2
 
0.5%
053-665-1052 2
 
0.5%
053-751-4511 2
 
0.5%
053-425-0551 2
 
0.5%
053-985-0111 2
 
0.5%
053-941-0019 2
 
0.5%
Other values (385) 386
93.9%
2024-04-21T11:59:23.374514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 821
16.7%
5 740
15.0%
0 658
13.3%
3 624
12.7%
9 458
9.3%
4 306
 
6.2%
8 302
 
6.1%
1 300
 
6.1%
2 276
 
5.6%
6 235
 
4.8%
Other values (2) 210
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4108
83.3%
Dash Punctuation 821
 
16.7%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 740
18.0%
0 658
16.0%
3 624
15.2%
9 458
11.1%
4 306
7.4%
8 302
7.4%
1 300
7.3%
2 276
 
6.7%
6 235
 
5.7%
7 209
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 821
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 821
16.7%
5 740
15.0%
0 658
13.3%
3 624
12.7%
9 458
9.3%
4 306
 
6.2%
8 302
 
6.1%
1 300
 
6.1%
2 276
 
5.6%
6 235
 
4.8%
Other values (2) 210
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 821
16.7%
5 740
15.0%
0 658
13.3%
3 624
12.7%
9 458
9.3%
4 306
 
6.2%
8 302
 
6.1%
1 300
 
6.1%
2 276
 
5.6%
6 235
 
4.8%
Other values (2) 210
 
4.3%

지정일자
Date

Distinct789
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
Minimum1962-01-01 00:00:00
Maximum2023-03-02 00:00:00
2024-04-21T11:59:23.776785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:59:24.217646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

법인구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
개인
856 
법인
 
69

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 856
92.5%
법인 69
 
7.5%

Length

2024-04-21T11:59:24.629291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:59:24.912054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 856
92.5%
법인 69
 
7.5%

영업구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
정상영업
925 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 925
100.0%

Length

2024-04-21T11:59:25.126254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:59:25.326695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 925
100.0%

Missing values

2024-04-21T11:59:13.806562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:59:14.189371image/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.
2024-04-21T11:59:14.493554image/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

업소명업소지번주소업소도로명주소업소전화번호지정일자법인구분영업구분
0지에스(GS)25 방촌우방점대구광역시 동구 방촌동 1119-77대구광역시 동구 화랑로80길 7-24. 1층 (방촌동)<NA>2023-03-02개인정상영업
1필수장터대구광역시 동구 신서동 1011-2대구광역시 동구 신서로 77 (신서동)<NA>2023-03-02개인정상영업
2씨유 대구율원점대구광역시 동구 율하동 1492대구광역시 동구 율하동로10길 3-6. 1층 (율하동)<NA>2023-02-28개인정상영업
3세븐일레븐 대구청아람점대구광역시 동구 신암동 1189-6대구광역시 동구 신성로 49-1 (신암동)<NA>2023-02-27개인정상영업
4진로할인마트대구광역시 동구 효목동 55 진로이스트타운대구광역시 동구 아양로 218. 303동 101.102.103.104.107호 (효목동. 진로이스트타운)<NA>2023-02-27개인정상영업
5신우유통대구광역시 동구 신천동 633 동신우방아파트대구광역시 동구 송라로11길 86. 상가동 1층 106호 (신천동. 동신우방아파트)<NA>2023-02-10개인정상영업
6씨유 동대구역 아펠리체점대구광역시 동구 신천동 327-3 동대구역 아펠리체대구광역시 동구 동부로22길 9. 동대구역 아펠리체 109호 (신천동)<NA>2023-02-02개인정상영업
7씨유 율하선수촌점대구광역시 동구 율하동 1313대구광역시 동구 율하서로 82. 1층 (율하동)<NA>2023-01-27개인정상영업
8온리포유플라워대구광역시 동구 신암동 229-25대구광역시 동구 신암남로15길 33. 1층 (신암동)<NA>2023-01-20개인정상영업
9지에스(GS)25 동대구화성센터점대구광역시 동구 신암동 258-1 동원맨션대구광역시 동구 신암남로23길 17. 1층 103호 (신암동. 동원맨션)<NA>2023-01-18개인정상영업
업소명업소지번주소업소도로명주소업소전화번호지정일자법인구분영업구분
915언덕슈퍼대구광역시 동구 신암동 329번지 16호 18통 1반대구광역시 동구 아양로34길 26 (신암동)053-942-61111987-04-30개인정상영업
916명진마트 명진정보대구광역시 동구 신암4동 246번지 3호대구광역시 동구 동대구로 596 (신암동)053-941-12911981-11-18개인정상영업
917동대구윤업사대구광역시 동구 아양로 164-1 (신암동)053-941-35591964-01-01개인정상영업
918-대구광역시 동구 신암동 221번지 16 호대구광역시 동구 동대구로99길 18 (신암동)053-958-15011984-12-27개인정상영업
919-대구광역시 동구 신암동 106번지 54호대구광역시 동구 동북로 417-1 (신암동)053-942-41881980-12-22개인정상영업
920-대구광역시 동구 신암동 67호 보성2차상가 113 1대구광역시 동구 아양로49길 77. 113동 1호 (신암동.보성2차상가)053-957-94241988-12-26개인정상영업
921한빛의료기대구광역시 동구 효목동 526번지 1호대구광역시 동구 화랑로 105 (효목동)053-742-29222000-06-09개인정상영업
922대구축산업협동조합대구광역시 동구 신암동 645번지 4 호대구광역시 동구 동북로 296 (신암동)053-950-12722000-03-30법인정상영업
923-대구광역시 동구 각산동 861번지 1호대구광역시 동구 반야월북로11길 42 (각산동)053-962-14842000-03-17개인정상영업
924영남슈퍼대구광역시 동구 신암동 625번지 117 호대구광역시 동구 아양로15길 90-48 (신암동)053-942-52822000-02-10개인정상영업