Overview

Dataset statistics

Number of variables8
Number of observations918
Missing cells637
Missing cells (%)8.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.3 KiB
Average record size in memory66.1 B

Variable types

Numeric2
Categorical2
Text4

Dataset

Description대구광역시 수성구 관내에 있는 데이터로 카페 업소명, 소재지, 영업장 면적, 소재지 전화 등에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15038007/fileData.do

Alerts

업태명 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
업종명 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 업종명 and 1 other fieldsHigh correlation
소재지전화 has 635 (69.2%) missing valuesMissing
연번 has unique valuesUnique
영업장면적 has 17 (1.9%) zerosZeros

Reproduction

Analysis started2023-12-12 22:07:58.957723
Analysis finished2023-12-12 22:08:00.790441
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct918
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean459.5
Minimum1
Maximum918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2023-12-13T07:08:00.857977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile46.85
Q1230.25
median459.5
Q3688.75
95-th percentile872.15
Maximum918
Range917
Interquartile range (IQR)458.5

Descriptive statistics

Standard deviation265.14807
Coefficient of variation (CV)0.57703606
Kurtosis-1.2
Mean459.5
Median Absolute Deviation (MAD)229.5
Skewness0
Sum421821
Variance70303.5
MonotonicityStrictly increasing
2023-12-13T07:08:00.983402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
605 1
 
0.1%
607 1
 
0.1%
608 1
 
0.1%
609 1
 
0.1%
610 1
 
0.1%
611 1
 
0.1%
612 1
 
0.1%
613 1
 
0.1%
614 1
 
0.1%
Other values (908) 908
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
918 1
0.1%
917 1
0.1%
916 1
0.1%
915 1
0.1%
914 1
0.1%
913 1
0.1%
912 1
0.1%
911 1
0.1%
910 1
0.1%
909 1
0.1%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
휴게음식점
815 
일반음식점
103 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴게음식점 815
88.8%
일반음식점 103
 
11.2%

Length

2023-12-13T07:08:01.100763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:08:01.182673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 815
88.8%
일반음식점 103
 
11.2%

업소명
Text

Distinct904
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2023-12-13T07:08:01.396493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length21
Mean length7.6840959
Min length1

Characters and Unicode

Total characters7054
Distinct characters608
Distinct categories8 ?
Distinct scripts5 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique890 ?
Unique (%)96.9%

Sample

1st row아담브릿지
2nd row브랜치식당
3rd row바비네카페(BOB'S CAFE)
4th row씨엘(Ciel)
5th row중국전통요리상해관
ValueCountFrequency (%)
coffee 11
 
1.1%
투썸플레이스 6
 
0.6%
시지점 4
 
0.4%
더 3
 
0.3%
cafe 3
 
0.3%
스타벅스 3
 
0.3%
팔레트(대산 2
 
0.2%
빽다방 2
 
0.2%
대구범어역점 2
 
0.2%
대구범어점 2
 
0.2%
Other values (953) 971
96.2%
2023-12-13T07:08:01.802443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 285
 
4.0%
스 211
 
3.0%
커 200
 
2.8%
피 200
 
2.8%
( 182
 
2.6%
) 182
 
2.6%
카 152
 
2.2%
페 147
 
2.1%
이 141
 
2.0%
구 130
 
1.8%
Other values (598) 5224
74.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5385
76.3%
Lowercase Letter 624
 
8.8%
Uppercase Letter 469
 
6.6%
Open Punctuation 182
 
2.6%
Close Punctuation 182
 
2.6%
Decimal Number 100
 
1.4%
Space Separator 91
 
1.3%
Other Punctuation 21
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 285
 
5.3%
스 211
 
3.9%
커 200
 
3.7%
피 200
 
3.7%
카 152
 
2.8%
페 147
 
2.7%
이 141
 
2.6%
구 130
 
2.4%
대 116
 
2.2%
리 107
 
2.0%
Other values (528) 3696
68.6%
Lowercase Letter
ValueCountFrequency (%)
e 105
16.8%
a 65
10.4%
o 64
10.3%
f 55
 
8.8%
c 41
 
6.6%
t 37
 
5.9%
r 28
 
4.5%
n 27
 
4.3%
l 27
 
4.3%
i 25
 
4.0%
Other values (15) 150
24.0%
Uppercase Letter
ValueCountFrequency (%)
E 47
 
10.0%
C 42
 
9.0%
A 36
 
7.7%
O 36
 
7.7%
D 33
 
7.0%
R 29
 
6.2%
F 29
 
6.2%
T 28
 
6.0%
S 24
 
5.1%
B 23
 
4.9%
Other values (15) 142
30.3%
Decimal Number
ValueCountFrequency (%)
1 22
22.0%
2 15
15.0%
9 13
13.0%
5 11
11.0%
4 10
10.0%
0 9
9.0%
8 6
 
6.0%
3 5
 
5.0%
6 5
 
5.0%
7 4
 
4.0%
Other Punctuation
ValueCountFrequency (%)
& 7
33.3%
. 7
33.3%
' 3
14.3%
, 1
 
4.8%
! 1
 
4.8%
# 1
 
4.8%
; 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 182
100.0%
Space Separator
ValueCountFrequency (%)
91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5384
76.3%
Latin 1092
 
15.5%
Common 576
 
8.2%
Han 1
 
< 0.1%
Cyrillic 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 285
 
5.3%
스 211
 
3.9%
커 200
 
3.7%
피 200
 
3.7%
카 152
 
2.8%
페 147
 
2.7%
이 141
 
2.6%
구 130
 
2.4%
대 116
 
2.2%
리 107
 
2.0%
Other values (527) 3695
68.6%
Latin
ValueCountFrequency (%)
e 105
 
9.6%
a 65
 
6.0%
o 64
 
5.9%
f 55
 
5.0%
E 47
 
4.3%
C 42
 
3.8%
c 41
 
3.8%
t 37
 
3.4%
A 36
 
3.3%
O 36
 
3.3%
Other values (39) 564
51.6%
Common
ValueCountFrequency (%)
( 182
31.6%
) 182
31.6%
91
15.8%
1 22
 
3.8%
2 15
 
2.6%
9 13
 
2.3%
5 11
 
1.9%
4 10
 
1.7%
0 9
 
1.6%
& 7
 
1.2%
Other values (10) 34
 
5.9%
Han
ValueCountFrequency (%)
休 1
100.0%
Cyrillic
ValueCountFrequency (%)
Ё 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5384
76.3%
ASCII 1668
 
23.6%
CJK 1
 
< 0.1%
Cyrillic 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 285
 
5.3%
스 211
 
3.9%
커 200
 
3.7%
피 200
 
3.7%
카 152
 
2.8%
페 147
 
2.7%
이 141
 
2.6%
구 130
 
2.4%
대 116
 
2.2%
리 107
 
2.0%
Other values (527) 3695
68.6%
ASCII
ValueCountFrequency (%)
( 182
 
10.9%
) 182
 
10.9%
e 105
 
6.3%
91
 
5.5%
a 65
 
3.9%
o 64
 
3.8%
f 55
 
3.3%
E 47
 
2.8%
C 42
 
2.5%
c 41
 
2.5%
Other values (59) 794
47.6%
CJK
ValueCountFrequency (%)
休 1
100.0%
Cyrillic
ValueCountFrequency (%)
Ё 1
100.0%

소재지(도로명)
Text

Distinct905
Distinct (%)98.8%
Missing2
Missing (%)0.2%
Memory size7.3 KiB
2023-12-13T07:08:02.065911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length53
Mean length31.255459
Min length21

Characters and Unicode

Total characters28630
Distinct characters264
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

Unique898 ?
Unique (%)98.0%

Sample

1st row대구광역시 수성구 수성로15길 46 (상동)
2nd row대구광역시 수성구 상록로 37 (범어동,(지상2층))
3rd row대구광역시 수성구 동대구로 358-26 (범어동)
4th row대구광역시 수성구 범어천로 128 (범어동)
5th row대구광역시 수성구 상록로 24 (범어동)
ValueCountFrequency (%)
대구광역시 916
 
16.1%
수성구 916
 
16.1%
1층 477
 
8.4%
범어동 196
 
3.4%
지산동 97
 
1.7%
만촌동 94
 
1.7%
달구벌대로 69
 
1.2%
두산동 67
 
1.2%
신매동 64
 
1.1%
황금동 60
 
1.1%
Other values (1026) 2739
48.1%
2023-12-13T07:08:02.500039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4780
 
16.7%
구 2098
 
7.3%
1 1454
 
5.1%
대 1204
 
4.2%
동 1160
 
4.1%
수 1158
 
4.0%
성 1129
 
3.9%
시 1022
 
3.6%
) 935
 
3.3%
( 935
 
3.3%
Other values (254) 12755
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16169
56.5%
Space Separator 4780
 
16.7%
Decimal Number 4751
 
16.6%
Close Punctuation 935
 
3.3%
Open Punctuation 935
 
3.3%
Other Punctuation 868
 
3.0%
Dash Punctuation 142
 
0.5%
Uppercase Letter 47
 
0.2%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2098
13.0%
대 1204
 
7.4%
동 1160
 
7.2%
수 1158
 
7.2%
성 1129
 
7.0%
시 1022
 
6.3%
역 921
 
5.7%
광 919
 
5.7%
로 914
 
5.7%
층 642
 
4.0%
Other values (223) 5002
30.9%
Uppercase Letter
ValueCountFrequency (%)
S 7
14.9%
B 7
14.9%
T 5
10.6%
A 4
 
8.5%
E 3
 
6.4%
H 3
 
6.4%
J 2
 
4.3%
M 2
 
4.3%
F 2
 
4.3%
I 2
 
4.3%
Other values (5) 10
21.3%
Decimal Number
ValueCountFrequency (%)
1 1454
30.6%
2 704
14.8%
3 434
 
9.1%
0 425
 
8.9%
4 419
 
8.8%
6 328
 
6.9%
5 306
 
6.4%
9 237
 
5.0%
8 226
 
4.8%
7 218
 
4.6%
Space Separator
ValueCountFrequency (%)
4780
100.0%
Close Punctuation
ValueCountFrequency (%)
) 935
100.0%
Open Punctuation
ValueCountFrequency (%)
( 935
100.0%
Other Punctuation
ValueCountFrequency (%)
, 868
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16169
56.5%
Common 12414
43.4%
Latin 47
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2098
13.0%
대 1204
 
7.4%
동 1160
 
7.2%
수 1158
 
7.2%
성 1129
 
7.0%
시 1022
 
6.3%
역 921
 
5.7%
광 919
 
5.7%
로 914
 
5.7%
층 642
 
4.0%
Other values (223) 5002
30.9%
Common
ValueCountFrequency (%)
4780
38.5%
1 1454
 
11.7%
) 935
 
7.5%
( 935
 
7.5%
, 868
 
7.0%
2 704
 
5.7%
3 434
 
3.5%
0 425
 
3.4%
4 419
 
3.4%
6 328
 
2.6%
Other values (6) 1132
 
9.1%
Latin
ValueCountFrequency (%)
S 7
14.9%
B 7
14.9%
T 5
10.6%
A 4
 
8.5%
E 3
 
6.4%
H 3
 
6.4%
J 2
 
4.3%
M 2
 
4.3%
F 2
 
4.3%
I 2
 
4.3%
Other values (5) 10
21.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16169
56.5%
ASCII 12461
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4780
38.4%
1 1454
 
11.7%
) 935
 
7.5%
( 935
 
7.5%
, 868
 
7.0%
2 704
 
5.6%
3 434
 
3.5%
0 425
 
3.4%
4 419
 
3.4%
6 328
 
2.6%
Other values (21) 1179
 
9.5%
Hangul
ValueCountFrequency (%)
구 2098
13.0%
대 1204
 
7.4%
동 1160
 
7.2%
수 1158
 
7.2%
성 1129
 
7.0%
시 1022
 
6.3%
역 921
 
5.7%
광 919
 
5.7%
로 914
 
5.7%
층 642
 
4.0%
Other values (223) 5002
30.9%

소재지(지번)
Text

Distinct906
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2023-12-13T07:08:02.750089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length24.75817
Min length17

Characters and Unicode

Total characters22728
Distinct characters242
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

Unique897 ?
Unique (%)97.7%

Sample

1st row대구광역시 수성구 상동 221
2nd row대구광역시 수성구 범어동 479-41 (지상2층)
3rd row대구광역시 수성구 범어동 175-5
4th row대구광역시 수성구 범어동 792-2
5th row대구광역시 수성구 범어동 27-13
ValueCountFrequency (%)
대구광역시 918
19.7%
수성구 918
19.7%
1층 400
 
8.6%
범어동 201
 
4.3%
지산동 99
 
2.1%
만촌동 97
 
2.1%
두산동 73
 
1.6%
신매동 69
 
1.5%
황금동 61
 
1.3%
범물동 44
 
0.9%
Other values (1145) 1782
38.2%
2023-12-13T07:08:03.321213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4531
19.9%
구 1847
 
8.1%
1 1523
 
6.7%
성 1056
 
4.6%
수 1042
 
4.6%
동 1034
 
4.5%
시 977
 
4.3%
대 951
 
4.2%
광 921
 
4.1%
역 921
 
4.1%
Other values (232) 7925
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12154
53.5%
Decimal Number 5128
22.6%
Space Separator 4531
 
19.9%
Dash Punctuation 743
 
3.3%
Other Punctuation 72
 
0.3%
Uppercase Letter 46
 
0.2%
Close Punctuation 25
 
0.1%
Open Punctuation 25
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1847
15.2%
성 1056
8.7%
수 1042
 
8.6%
동 1034
 
8.5%
시 977
 
8.0%
대 951
 
7.8%
광 921
 
7.6%
역 921
 
7.6%
층 525
 
4.3%
범 270
 
2.2%
Other values (201) 2610
21.5%
Uppercase Letter
ValueCountFrequency (%)
S 7
15.2%
B 6
13.0%
T 5
10.9%
A 4
 
8.7%
E 3
 
6.5%
H 3
 
6.5%
M 2
 
4.3%
J 2
 
4.3%
F 2
 
4.3%
I 2
 
4.3%
Other values (5) 10
21.7%
Decimal Number
ValueCountFrequency (%)
1 1523
29.7%
2 588
 
11.5%
3 483
 
9.4%
0 460
 
9.0%
5 406
 
7.9%
7 380
 
7.4%
4 349
 
6.8%
6 346
 
6.7%
8 320
 
6.2%
9 273
 
5.3%
Space Separator
ValueCountFrequency (%)
4531
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 743
100.0%
Other Punctuation
ValueCountFrequency (%)
, 72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12154
53.5%
Common 10528
46.3%
Latin 46
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1847
15.2%
성 1056
8.7%
수 1042
 
8.6%
동 1034
 
8.5%
시 977
 
8.0%
대 951
 
7.8%
광 921
 
7.6%
역 921
 
7.6%
층 525
 
4.3%
범 270
 
2.2%
Other values (201) 2610
21.5%
Common
ValueCountFrequency (%)
4531
43.0%
1 1523
 
14.5%
- 743
 
7.1%
2 588
 
5.6%
3 483
 
4.6%
0 460
 
4.4%
5 406
 
3.9%
7 380
 
3.6%
4 349
 
3.3%
6 346
 
3.3%
Other values (6) 719
 
6.8%
Latin
ValueCountFrequency (%)
S 7
15.2%
B 6
13.0%
T 5
10.9%
A 4
 
8.7%
E 3
 
6.5%
H 3
 
6.5%
M 2
 
4.3%
J 2
 
4.3%
F 2
 
4.3%
I 2
 
4.3%
Other values (5) 10
21.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12154
53.5%
ASCII 10574
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4531
42.9%
1 1523
 
14.4%
- 743
 
7.0%
2 588
 
5.6%
3 483
 
4.6%
0 460
 
4.4%
5 406
 
3.8%
7 380
 
3.6%
4 349
 
3.3%
6 346
 
3.3%
Other values (21) 765
 
7.2%
Hangul
ValueCountFrequency (%)
구 1847
15.2%
성 1056
8.7%
수 1042
 
8.6%
동 1034
 
8.5%
시 977
 
8.0%
대 951
 
7.8%
광 921
 
7.6%
역 921
 
7.6%
층 525
 
4.3%
범 270
 
2.2%
Other values (201) 2610
21.5%

영업장면적
Real number (ℝ)

ZEROS 

Distinct736
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.321492
Minimum0
Maximum1227.18
Zeros17
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2023-12-13T07:08:03.488703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.328
Q134
median54.55
Q394.14
95-th percentile279.7975
Maximum1227.18
Range1227.18
Interquartile range (IQR)60.14

Descriptive statistics

Standard deviation107.63576
Coefficient of variation (CV)1.2326377
Kurtosis29.865459
Mean87.321492
Median Absolute Deviation (MAD)24.885
Skewness4.4285866
Sum80161.13
Variance11585.458
MonotonicityNot monotonic
2023-12-13T07:08:03.627127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 17
 
1.9%
33.0 12
 
1.3%
66.0 10
 
1.1%
50.0 8
 
0.9%
49.5 8
 
0.9%
40.0 7
 
0.8%
45.0 6
 
0.7%
60.0 6
 
0.7%
36.0 5
 
0.5%
39.6 4
 
0.4%
Other values (726) 835
91.0%
ValueCountFrequency (%)
0.0 17
1.9%
3.06 1
 
0.1%
3.1 1
 
0.1%
3.3 2
 
0.2%
6.6 3
 
0.3%
7.42 1
 
0.1%
7.54 1
 
0.1%
7.92 1
 
0.1%
8.0 1
 
0.1%
9.0 1
 
0.1%
ValueCountFrequency (%)
1227.18 1
0.1%
1080.41 1
0.1%
830.4 1
0.1%
818.36 1
0.1%
676.15 1
0.1%
640.96 1
0.1%
618.0 1
0.1%
612.74 1
0.1%
552.19 1
0.1%
550.68 1
0.1%

소재지전화
Text

MISSING 

Distinct280
Distinct (%)98.9%
Missing635
Missing (%)69.2%
Memory size7.3 KiB
2023-12-13T07:08:03.862896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3396
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

Unique277 ?
Unique (%)97.9%

Sample

1st row053-292-0000
2nd row053-424-0022
3rd row053-741-4820
4th row053-743-3313
5th row053-745-1890
ValueCountFrequency (%)
053-754-0910 2
 
0.7%
053-784-6080 2
 
0.7%
053-765-5632 2
 
0.7%
053-958-2041 1
 
0.4%
053-763-7429 1
 
0.4%
053-763-8427 1
 
0.4%
053-763-8030 1
 
0.4%
053-763-7999 1
 
0.4%
053-292-0000 1
 
0.4%
053-762-6008 1
 
0.4%
Other values (270) 270
95.4%
2023-12-13T07:08:04.219164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 566
16.7%
5 476
14.0%
0 458
13.5%
3 440
13.0%
7 363
10.7%
2 215
 
6.3%
4 192
 
5.7%
6 192
 
5.7%
1 169
 
5.0%
8 168
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2830
83.3%
Dash Punctuation 566
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 476
16.8%
0 458
16.2%
3 440
15.5%
7 363
12.8%
2 215
7.6%
4 192
6.8%
6 192
6.8%
1 169
 
6.0%
8 168
 
5.9%
9 157
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 566
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 566
16.7%
5 476
14.0%
0 458
13.5%
3 440
13.0%
7 363
10.7%
2 215
 
6.3%
4 192
 
5.7%
6 192
 
5.7%
1 169
 
5.0%
8 168
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 566
16.7%
5 476
14.0%
0 458
13.5%
3 440
13.0%
7 363
10.7%
2 215
 
6.3%
4 192
 
5.7%
6 192
 
5.7%
1 169
 
5.0%
8 168
 
4.9%

업태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
커피숍
815 
까페
103 

Length

Max length3
Median length3
Mean length2.8877996
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 815
88.8%
까페 103
 
11.2%

Length

2023-12-13T07:08:04.351433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:08:04.431978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
커피숍 815
88.8%
까페 103
 
11.2%

Interactions

2023-12-13T07:07:59.906118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:59.661026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:08:00.028046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:59.780320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:08:04.502963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명영업장면적업태명
연번1.0000.9960.2770.996
업종명0.9961.0000.2401.000
영업장면적0.2770.2401.0000.240
업태명0.9961.0000.2401.000
2023-12-13T07:08:04.608328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태명업종명
업태명1.0000.995
업종명0.9951.000
2023-12-13T07:08:04.691483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번영업장면적업종명업태명
연번1.000-0.3260.9410.941
영업장면적-0.3261.0000.2390.239
업종명0.9410.2391.0000.995
업태명0.9410.2390.9951.000

Missing values

2023-12-13T07:08:00.202981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:08:00.369027image/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.
2023-12-13T07:08:00.743985image/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

연번업종명업소명소재지(도로명)소재지(지번)영업장면적소재지전화업태명
01일반음식점아담브릿지대구광역시 수성구 수성로15길 46 (상동)대구광역시 수성구 상동 221173.51053-292-0000까페
12일반음식점브랜치식당대구광역시 수성구 상록로 37 (범어동,(지상2층))대구광역시 수성구 범어동 479-41 (지상2층)116.2053-424-0022까페
23일반음식점바비네카페(BOB'S CAFE)대구광역시 수성구 동대구로 358-26 (범어동)대구광역시 수성구 범어동 175-5125.8053-741-4820까페
34일반음식점씨엘(Ciel)대구광역시 수성구 범어천로 128 (범어동)대구광역시 수성구 범어동 792-2119.67053-743-3313까페
45일반음식점중국전통요리상해관대구광역시 수성구 상록로 24 (범어동)대구광역시 수성구 범어동 27-13122.68053-745-1890까페
56일반음식점시카고(chicago)대구광역시 수성구 달구벌대로 2354 (수성동3가)대구광역시 수성구 수성동3가 10162.0053-745-7703까페
67일반음식점더샐러드(THE SALAD)대구광역시 수성구 동대구로 214 (범어동)대구광역시 수성구 범어동 711-517.8053-746-8788까페
78일반음식점한신포차 수성못점대구광역시 수성구 수성못2길 53 (두산동)대구광역시 수성구 두산동 665220.41053-751-0202까페
89일반음식점부메랑대구광역시 수성구 달구벌대로 2546, 지하1층 (범어동)대구광역시 수성구 범어동 217-3 지하1층111.02053-753-0425까페
910일반음식점크라운대구광역시 수성구 동대구로73길 10 (범어동)대구광역시 수성구 범어동 17-622.4053-754-0515까페
연번업종명업소명소재지(도로명)소재지(지번)영업장면적소재지전화업태명
908909휴게음식점유아이유커피대구광역시 수성구 수성로 211, B동 1층 (중동)대구광역시 수성구 중동 261-5 1층, B동28.0<NA>커피숍
909910휴게음식점샌드리아담티역점대구광역시 수성구 달구벌대로 2674, 1층 (만촌동)대구광역시 수성구 만촌동 860-6 1층66.0<NA>커피숍
910911휴게음식점머뭇대구광역시 수성구 신천동로96길 35-12, 1층 (수성동4가)대구광역시 수성구 수성동4가 1124-16 1층30.6<NA>커피숍
911912휴게음식점베오메오황금점대구광역시 수성구 들안로28길 24-6, 1층 (황금동)대구광역시 수성구 황금동 874-10 1층0.0<NA>커피숍
912913휴게음식점마고커피대구광역시 수성구 고모로33길 105-1, 1층 101호 (연호동)대구광역시 수성구 연호동 52-1 1층 101호0.0<NA>커피숍
913914휴게음식점켑트커피대구광역시 수성구 청솔로14길 28, 1층 (범어동)대구광역시 수성구 범어동 805-164 1층88.19<NA>커피숍
914915휴게음식점아틀리에빈사월점대구광역시 수성구 달구벌대로 3300-5, 공서빌딩 A동 1층 (신매동)대구광역시 수성구 신매동 10-11 공서빌딩, 1층 A동0.0<NA>커피숍
915916휴게음식점더리터지산목련점대구광역시 수성구 용학로 210, 1층 (지산동)대구광역시 수성구 지산동 1194-4 1층0.0<NA>커피숍
916917휴게음식점태백(TAEBAEK)1975대구광역시 수성구 동대구로12길 24, 1층 (지산동)대구광역시 수성구 지산동 1003-3 1층0.0<NA>커피숍
917918휴게음식점하삼동커피대구범어점대구광역시 수성구 동대구로 346, 지하1층 3-4호 (범어동, 범어서한포레스트)대구광역시 수성구 범어동 177-1 범어서한포레스트 지하1층 3-4호0.0<NA>커피숍