Overview

Dataset statistics

Number of variables6
Number of observations1462
Missing cells1100
Missing cells (%)12.5%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory68.7 KiB
Average record size in memory48.1 B

Variable types

Categorical2
Text4

Dataset

Description대구광역시 동구 소재 카페, 편의점, 다방 등 휴게음식점현황 데이터입니다. 이 데이터는 업종명, 업태명, 업소명, 주소, 연락처 등의 항목을 포함합니다.
Author대구광역시 동구
URLhttps://www.data.go.kr/data/15052655/fileData.do

Alerts

업종명 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
업태명 is highly imbalanced (52.4%)Imbalance
연락처 has 1100 (75.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:32:25.047708
Analysis finished2023-12-12 18:32:26.116460
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
휴게음식점
1462 

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 1462
100.0%

Length

2023-12-13T03:32:26.196626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:26.334280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 1462
100.0%

업태명
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
기타 휴게음식점
977 
커피숍
206 
편의점
 
95
일반조리판매
 
73
다방
 
56
Other values (7)
 
55

Length

Max length8
Median length8
Mean length6.5068399
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타 휴게음식점
2nd row커피숍
3rd row기타 휴게음식점
4th row기타 휴게음식점
5th row패스트푸드

Common Values

ValueCountFrequency (%)
기타 휴게음식점 977
66.8%
커피숍 206
 
14.1%
편의점 95
 
6.5%
일반조리판매 73
 
5.0%
다방 56
 
3.8%
패스트푸드 23
 
1.6%
전통찻집 10
 
0.7%
키즈카페 8
 
0.5%
푸드트럭 5
 
0.3%
과자점 4
 
0.3%
Other values (2) 5
 
0.3%

Length

2023-12-13T03:32:26.469399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 977
40.1%
휴게음식점 977
40.1%
커피숍 206
 
8.4%
편의점 95
 
3.9%
일반조리판매 73
 
3.0%
다방 56
 
2.3%
패스트푸드 23
 
0.9%
전통찻집 10
 
0.4%
키즈카페 8
 
0.3%
푸드트럭 5
 
0.2%
Other values (3) 9
 
0.4%

업소명
Text

Distinct1441
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2023-12-13T03:32:26.795832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length8.9569083
Min length1

Characters and Unicode

Total characters13095
Distinct characters686
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1423 ?
Unique (%)97.3%

Sample

1st row본죽송라시장점
2nd row스타벅스동대구터미널점
3rd row엠에이치커피(MH커피)
4th row시네델리(Cine delly)
5th row롯데리아 아양교점
ValueCountFrequency (%)
세븐일레븐 38
 
1.8%
씨유 34
 
1.6%
지에스(gs)25 28
 
1.3%
카페 24
 
1.1%
coffee 19
 
0.9%
gs25 16
 
0.7%
이시아폴리스점 13
 
0.6%
율하점 10
 
0.5%
투썸플레이스 10
 
0.5%
동대구점 10
 
0.5%
Other values (1608) 1932
90.5%
2023-12-13T03:32:27.672174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
672
 
5.1%
점 628
 
4.8%
구 365
 
2.8%
대 340
 
2.6%
스 334
 
2.6%
) 302
 
2.3%
( 302
 
2.3%
이 278
 
2.1%
피 226
 
1.7%
신 193
 
1.5%
Other values (676) 9455
72.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10027
76.6%
Uppercase Letter 756
 
5.8%
Lowercase Letter 716
 
5.5%
Space Separator 672
 
5.1%
Close Punctuation 302
 
2.3%
Open Punctuation 302
 
2.3%
Decimal Number 279
 
2.1%
Other Punctuation 38
 
0.3%
Modifier Symbol 1
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 628
 
6.3%
구 365
 
3.6%
대 340
 
3.4%
스 334
 
3.3%
이 278
 
2.8%
피 226
 
2.3%
신 193
 
1.9%
동 189
 
1.9%
리 186
 
1.9%
커 183
 
1.8%
Other values (602) 7105
70.9%
Uppercase Letter
ValueCountFrequency (%)
S 92
12.2%
G 90
11.9%
C 86
 
11.4%
E 68
 
9.0%
P 45
 
6.0%
O 38
 
5.0%
T 31
 
4.1%
A 30
 
4.0%
U 29
 
3.8%
F 29
 
3.8%
Other values (16) 218
28.8%
Lowercase Letter
ValueCountFrequency (%)
e 123
17.2%
o 71
9.9%
a 68
 
9.5%
f 61
 
8.5%
n 53
 
7.4%
c 37
 
5.2%
i 36
 
5.0%
l 35
 
4.9%
s 34
 
4.7%
r 26
 
3.6%
Other values (14) 172
24.0%
Decimal Number
ValueCountFrequency (%)
2 117
41.9%
5 81
29.0%
4 23
 
8.2%
1 16
 
5.7%
9 14
 
5.0%
0 10
 
3.6%
8 9
 
3.2%
3 5
 
1.8%
6 2
 
0.7%
7 2
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 12
31.6%
& 12
31.6%
. 8
21.1%
' 2
 
5.3%
! 1
 
2.6%
# 1
 
2.6%
: 1
 
2.6%
% 1
 
2.6%
Space Separator
ValueCountFrequency (%)
672
100.0%
Close Punctuation
ValueCountFrequency (%)
) 302
100.0%
Open Punctuation
ValueCountFrequency (%)
( 302
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10025
76.6%
Common 1596
 
12.2%
Latin 1472
 
11.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 628
 
6.3%
구 365
 
3.6%
대 340
 
3.4%
스 334
 
3.3%
이 278
 
2.8%
피 226
 
2.3%
신 193
 
1.9%
동 189
 
1.9%
리 186
 
1.9%
커 183
 
1.8%
Other values (600) 7103
70.9%
Latin
ValueCountFrequency (%)
e 123
 
8.4%
S 92
 
6.2%
G 90
 
6.1%
C 86
 
5.8%
o 71
 
4.8%
E 68
 
4.6%
a 68
 
4.6%
f 61
 
4.1%
n 53
 
3.6%
P 45
 
3.1%
Other values (40) 715
48.6%
Common
ValueCountFrequency (%)
672
42.1%
) 302
18.9%
( 302
18.9%
2 117
 
7.3%
5 81
 
5.1%
4 23
 
1.4%
1 16
 
1.0%
9 14
 
0.9%
, 12
 
0.8%
& 12
 
0.8%
Other values (14) 45
 
2.8%
Han
ValueCountFrequency (%)
辛 1
50.0%
茶 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10025
76.6%
ASCII 3068
 
23.4%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
672
21.9%
) 302
 
9.8%
( 302
 
9.8%
e 123
 
4.0%
2 117
 
3.8%
S 92
 
3.0%
G 90
 
2.9%
C 86
 
2.8%
5 81
 
2.6%
o 71
 
2.3%
Other values (64) 1132
36.9%
Hangul
ValueCountFrequency (%)
점 628
 
6.3%
구 365
 
3.6%
대 340
 
3.4%
스 334
 
3.3%
이 278
 
2.8%
피 226
 
2.3%
신 193
 
1.9%
동 189
 
1.9%
리 186
 
1.9%
커 183
 
1.8%
Other values (600) 7103
70.9%
CJK
ValueCountFrequency (%)
辛 1
50.0%
茶 1
50.0%

소재지(도로명)
Text

Distinct1356
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2023-12-13T03:32:28.051606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length56
Mean length31.677839
Min length9

Characters and Unicode

Total characters46313
Distinct characters349
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

Unique1308 ?
Unique (%)89.5%

Sample

1st row대구광역시 동구 동부로 19 (신천동)
2nd row대구광역시 동구 동부로30길 12 (신천동,번지외1필지 보광빌딩 가동 1,2층)
3rd row대구광역시 동구 동대구로 418 (신천동)
4th row대구광역시 동구 팔공로49길 16 (봉무동)
5th row대구광역시 동구 아양로 240 (효목동)
ValueCountFrequency (%)
동구 1456
 
15.1%
대구광역시 1455
 
15.1%
1층 830
 
8.6%
신천동 258
 
2.7%
신암동 209
 
2.2%
율하동 140
 
1.5%
신서동 136
 
1.4%
동부로 99
 
1.0%
효목동 93
 
1.0%
방촌동 83
 
0.9%
Other values (1293) 4858
50.5%
2023-12-13T03:32:28.659835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8156
17.6%
동 3787
 
8.2%
구 3143
 
6.8%
1 2544
 
5.5%
대 1748
 
3.8%
, 1638
 
3.5%
역 1523
 
3.3%
시 1514
 
3.3%
로 1490
 
3.2%
) 1462
 
3.2%
Other values (339) 19308
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25553
55.2%
Space Separator 8156
 
17.6%
Decimal Number 7633
 
16.5%
Other Punctuation 1644
 
3.5%
Close Punctuation 1462
 
3.2%
Open Punctuation 1462
 
3.2%
Dash Punctuation 226
 
0.5%
Uppercase Letter 132
 
0.3%
Math Symbol 26
 
0.1%
Lowercase Letter 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3787
14.8%
구 3143
 
12.3%
대 1748
 
6.8%
역 1523
 
6.0%
시 1514
 
5.9%
로 1490
 
5.8%
광 1459
 
5.7%
층 1136
 
4.4%
신 859
 
3.4%
길 655
 
2.6%
Other values (297) 8239
32.2%
Uppercase Letter
ValueCountFrequency (%)
A 37
28.0%
B 19
14.4%
E 14
 
10.6%
D 12
 
9.1%
C 11
 
8.3%
L 10
 
7.6%
H 7
 
5.3%
P 6
 
4.5%
R 6
 
4.5%
G 5
 
3.8%
Other values (5) 5
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 2544
33.3%
2 1026
13.4%
0 798
 
10.5%
3 666
 
8.7%
5 564
 
7.4%
4 553
 
7.2%
6 415
 
5.4%
9 373
 
4.9%
7 357
 
4.7%
8 337
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
p 4
22.2%
e 4
22.2%
s 3
16.7%
a 2
11.1%
t 2
11.1%
l 2
11.1%
d 1
 
5.6%
Math Symbol
ValueCountFrequency (%)
~ 14
53.8%
< 6
23.1%
> 6
23.1%
Other Punctuation
ValueCountFrequency (%)
, 1638
99.6%
. 6
 
0.4%
Space Separator
ValueCountFrequency (%)
8156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1462
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1462
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 226
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25553
55.2%
Common 20609
44.5%
Latin 151
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3787
14.8%
구 3143
 
12.3%
대 1748
 
6.8%
역 1523
 
6.0%
시 1514
 
5.9%
로 1490
 
5.8%
광 1459
 
5.7%
층 1136
 
4.4%
신 859
 
3.4%
길 655
 
2.6%
Other values (297) 8239
32.2%
Latin
ValueCountFrequency (%)
A 37
24.5%
B 19
12.6%
E 14
 
9.3%
D 12
 
7.9%
C 11
 
7.3%
L 10
 
6.6%
H 7
 
4.6%
P 6
 
4.0%
R 6
 
4.0%
G 5
 
3.3%
Other values (13) 24
15.9%
Common
ValueCountFrequency (%)
8156
39.6%
1 2544
 
12.3%
, 1638
 
7.9%
) 1462
 
7.1%
( 1462
 
7.1%
2 1026
 
5.0%
0 798
 
3.9%
3 666
 
3.2%
5 564
 
2.7%
4 553
 
2.7%
Other values (9) 1740
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25553
55.2%
ASCII 20759
44.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8156
39.3%
1 2544
 
12.3%
, 1638
 
7.9%
) 1462
 
7.0%
( 1462
 
7.0%
2 1026
 
4.9%
0 798
 
3.8%
3 666
 
3.2%
5 564
 
2.7%
4 553
 
2.7%
Other values (31) 1890
 
9.1%
Hangul
ValueCountFrequency (%)
동 3787
14.8%
구 3143
 
12.3%
대 1748
 
6.8%
역 1523
 
6.0%
시 1514
 
5.9%
로 1490
 
5.8%
광 1459
 
5.7%
층 1136
 
4.4%
신 859
 
3.4%
길 655
 
2.6%
Other values (297) 8239
32.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

소재지(지번)
Text

Distinct1144
Distinct (%)78.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2023-12-13T03:32:29.002368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length39
Mean length21.24829
Min length16

Characters and Unicode

Total characters31065
Distinct characters310
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

Unique993 ?
Unique (%)67.9%

Sample

1st row대구광역시 동구 신천동 541-32
2nd row대구광역시 동구 신천동 330-6 번지외1필지 보광빌딩 가동 1,2층
3rd row대구광역시 동구 신천동 300-4
4th row대구광역시 동구 봉무동 1545
5th row대구광역시 동구 효목동 80-2
ValueCountFrequency (%)
대구광역시 1462
22.9%
동구 1462
22.9%
신천동 262
 
4.1%
신암동 216
 
3.4%
율하동 144
 
2.3%
신서동 142
 
2.2%
효목동 95
 
1.5%
방촌동 86
 
1.3%
봉무동 85
 
1.3%
각산동 61
 
1.0%
Other values (1386) 2374
37.2%
2023-12-13T03:32:29.506980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6378
20.5%
동 3073
 
9.9%
구 3019
 
9.7%
대 1596
 
5.1%
역 1506
 
4.8%
시 1497
 
4.8%
광 1465
 
4.7%
1 1440
 
4.6%
- 1029
 
3.3%
신 733
 
2.4%
Other values (300) 9329
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17247
55.5%
Space Separator 6378
 
20.5%
Decimal Number 6357
 
20.5%
Dash Punctuation 1029
 
3.3%
Uppercase Letter 33
 
0.1%
Other Punctuation 10
 
< 0.1%
Lowercase Letter 4
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3073
17.8%
구 3019
17.5%
대 1596
9.3%
역 1506
8.7%
시 1497
8.7%
광 1465
 
8.5%
신 733
 
4.3%
천 282
 
1.6%
암 222
 
1.3%
서 168
 
1.0%
Other values (270) 3686
21.4%
Decimal Number
ValueCountFrequency (%)
1 1440
22.7%
5 719
11.3%
3 691
10.9%
2 684
10.8%
4 546
 
8.6%
0 516
 
8.1%
6 467
 
7.3%
8 464
 
7.3%
9 428
 
6.7%
7 402
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
D 11
33.3%
H 6
18.2%
L 4
 
12.1%
B 3
 
9.1%
G 3
 
9.1%
C 2
 
6.1%
A 1
 
3.0%
T 1
 
3.0%
K 1
 
3.0%
V 1
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
d 1
25.0%
s 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 6
60.0%
, 4
40.0%
Space Separator
ValueCountFrequency (%)
6378
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1029
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17247
55.5%
Common 13780
44.4%
Latin 38
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3073
17.8%
구 3019
17.5%
대 1596
9.3%
역 1506
8.7%
시 1497
8.7%
광 1465
 
8.5%
신 733
 
4.3%
천 282
 
1.6%
암 222
 
1.3%
서 168
 
1.0%
Other values (270) 3686
21.4%
Common
ValueCountFrequency (%)
6378
46.3%
1 1440
 
10.4%
- 1029
 
7.5%
5 719
 
5.2%
3 691
 
5.0%
2 684
 
5.0%
4 546
 
4.0%
0 516
 
3.7%
6 467
 
3.4%
8 464
 
3.4%
Other values (6) 846
 
6.1%
Latin
ValueCountFrequency (%)
D 11
28.9%
H 6
15.8%
L 4
 
10.5%
B 3
 
7.9%
G 3
 
7.9%
e 2
 
5.3%
C 2
 
5.3%
d 1
 
2.6%
s 1
 
2.6%
A 1
 
2.6%
Other values (4) 4
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17247
55.5%
ASCII 13817
44.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6378
46.2%
1 1440
 
10.4%
- 1029
 
7.4%
5 719
 
5.2%
3 691
 
5.0%
2 684
 
5.0%
4 546
 
4.0%
0 516
 
3.7%
6 467
 
3.4%
8 464
 
3.4%
Other values (19) 883
 
6.4%
Hangul
ValueCountFrequency (%)
동 3073
17.8%
구 3019
17.5%
대 1596
9.3%
역 1506
8.7%
시 1497
8.7%
광 1465
 
8.5%
신 733
 
4.3%
천 282
 
1.6%
암 222
 
1.3%
서 168
 
1.0%
Other values (270) 3686
21.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

연락처
Text

MISSING 

Distinct337
Distinct (%)93.1%
Missing1100
Missing (%)75.2%
Memory size11.6 KiB
2023-12-13T03:32:29.835226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.033149
Min length11

Characters and Unicode

Total characters4356
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

Unique325 ?
Unique (%)89.8%

Sample

1st row053-256-6288
2nd row053-742-8417
3rd row053-756-1100
4th row053-794-7590
5th row053-956-3377
ValueCountFrequency (%)
053-941-0019 13
 
3.6%
053-607-2500 3
 
0.8%
053-665-1052 3
 
0.8%
070-7801-7552 2
 
0.6%
053-959-2277 2
 
0.6%
070-7092-7065 2
 
0.6%
070-7092-7145 2
 
0.6%
053-962-0999 2
 
0.6%
053-742-2631 2
 
0.6%
053-661-1760 2
 
0.6%
Other values (327) 329
90.9%
2023-12-13T03:32:30.341822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 724
16.6%
0 648
14.9%
5 605
13.9%
3 538
12.4%
9 422
9.7%
8 265
 
6.1%
2 242
 
5.6%
7 239
 
5.5%
6 236
 
5.4%
1 234
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3632
83.4%
Dash Punctuation 724
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 648
17.8%
5 605
16.7%
3 538
14.8%
9 422
11.6%
8 265
7.3%
2 242
 
6.7%
7 239
 
6.6%
6 236
 
6.5%
1 234
 
6.4%
4 203
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 724
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4356
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 724
16.6%
0 648
14.9%
5 605
13.9%
3 538
12.4%
9 422
9.7%
8 265
 
6.1%
2 242
 
5.6%
7 239
 
5.5%
6 236
 
5.4%
1 234
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4356
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 724
16.6%
0 648
14.9%
5 605
13.9%
3 538
12.4%
9 422
9.7%
8 265
 
6.1%
2 242
 
5.6%
7 239
 
5.5%
6 236
 
5.4%
1 234
 
5.4%

Missing values

2023-12-13T03:32:25.921537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:32:26.065501image/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.

Sample

업종명업태명업소명소재지(도로명)소재지(지번)연락처
0휴게음식점기타 휴게음식점본죽송라시장점대구광역시 동구 동부로 19 (신천동)대구광역시 동구 신천동 541-32053-256-6288
1휴게음식점커피숍스타벅스동대구터미널점대구광역시 동구 동부로30길 12 (신천동,번지외1필지 보광빌딩 가동 1,2층)대구광역시 동구 신천동 330-6 번지외1필지 보광빌딩 가동 1,2층053-742-8417
2휴게음식점기타 휴게음식점엠에이치커피(MH커피)대구광역시 동구 동대구로 418 (신천동)대구광역시 동구 신천동 300-4053-756-1100
3휴게음식점기타 휴게음식점시네델리(Cine delly)대구광역시 동구 팔공로49길 16 (봉무동)대구광역시 동구 봉무동 1545053-794-7590
4휴게음식점패스트푸드롯데리아 아양교점대구광역시 동구 아양로 240 (효목동)대구광역시 동구 효목동 80-2053-956-3377
5휴게음식점기타 휴게음식점개구쟁이대구광역시 동구 율하동로17길 2 (율하동)대구광역시 동구 율하동 953-7053-963-1932
6휴게음식점다방시즌대구광역시 동구 방촌로1길 116 (방촌동)대구광역시 동구 방촌동 902-25053-982-3530
7휴게음식점커피숍파이데이아북카페대구광역시 동구 파계로138길 15, B동 (중대동)대구광역시 동구 중대동 38-17 B동053-982-7063
8휴게음식점기타 휴게음식점메리포핀스대구광역시 동구 국채보상로159길 12, 1층 (신천동)대구광역시 동구 신천동 825-2053-243-7371
9휴게음식점일반조리판매신바람찐빵집대구광역시 동구 안심로 456, 2층 (괴전동)대구광역시 동구 괴전동 162-5053-294-9191
업종명업태명업소명소재지(도로명)소재지(지번)연락처
1452휴게음식점기타 휴게음식점더리터 동대구역아펠리체점대구광역시 동구 동부로22길 9, 동대구역 아펠리체 1층 108호 (신천동)대구광역시 동구 신천동 327-3 동대구역 아펠리체<NA>
1453휴게음식점기타 휴게음식점리은푸드대구광역시 동구 동부로 149, 신세계동대구복합환승센터 지하1층 (신천동)대구광역시 동구 신천동 1506 신세계동대구복합환승센터<NA>
1454휴게음식점기타 휴게음식점카페첼대구광역시 동구 반야월북로53길 6-4, 1층 (신서동)대구광역시 동구 신서동 885-15<NA>
1455휴게음식점기타 휴게음식점과일콕 반야월점대구광역시 동구 안심로49길 55, 1층 (서호동)대구광역시 동구 서호동 95-6<NA>
1456휴게음식점기타 휴게음식점씨유 신천광장점대구광역시 동구 동부로15길 11, 1층 (신천동)대구광역시 동구 신천동 25-2<NA>
1457휴게음식점기타 휴게음식점주식회사 서로대구광역시 동구 아양로 99, 파티마병원 G동 1층 (신암동)대구광역시 동구 신암동 576-31 파티마병원<NA>
1458휴게음식점기타 휴게음식점나리꼬모대구광역시 동구 동부로 149, 신세계동대구복합환승센터 지하1층 (신천동)대구광역시 동구 신천동 1506 신세계동대구복합환승센터<NA>
1459휴게음식점기타 휴게음식점베키아에누보 다이아몬드라운지대구광역시 동구 동부로 149, 신세계동대구복합환승센터 5층 (신천동)대구광역시 동구 신천동 1506 신세계동대구복합환승센터<NA>
1460휴게음식점기타 휴게음식점헤븐대구광역시 동구 율하동로10길 13, 1층 (율하동)대구광역시 동구 율하동 1494<NA>
1461휴게음식점기타 휴게음식점(주)지오에프앤씨대구광역시 동구 동부로 149, 신세계동대구복합환승센터 지하1층 (신천동)대구광역시 동구 신천동 1506 신세계동대구복합환승센터<NA>

Duplicate rows

Most frequently occurring

업종명업태명업소명소재지(도로명)소재지(지번)연락처# duplicates
0휴게음식점기타 휴게음식점나리꼬모대구광역시 동구 동부로 149, 신세계동대구복합환승센터 지하1층 (신천동)대구광역시 동구 신천동 1506 신세계동대구복합환승센터<NA>2