Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory390.6 KiB
Average record size in memory40.0 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description대구광역시_음식점 등록현황_20231204
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3056779&dataSetDetailId=30567791f77ff9339e2d&provdMethod=FILE

Alerts

연번 is highly overall correlated with 업태High correlation
업태 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 20:19:09.239017
Analysis finished2023-12-10 20:21:06.365671
Duration1 minute and 57.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15594.068
Minimum1
Maximum31383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:21:06.448415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1530.8
Q17806.75
median15541
Q323378.75
95-th percentile29814.2
Maximum31383
Range31382
Interquartile range (IQR)15572

Descriptive statistics

Standard deviation9040.8552
Coefficient of variation (CV)0.57976246
Kurtosis-1.1885829
Mean15594.068
Median Absolute Deviation (MAD)7797.5
Skewness0.011015689
Sum1.5594068 × 108
Variance81737064
MonotonicityNot monotonic
2023-12-11T05:21:06.664365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29685 1
 
< 0.1%
23735 1
 
< 0.1%
4349 1
 
< 0.1%
1874 1
 
< 0.1%
8203 1
 
< 0.1%
5950 1
 
< 0.1%
25608 1
 
< 0.1%
21991 1
 
< 0.1%
30428 1
 
< 0.1%
17374 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
15 1
< 0.1%
18 1
< 0.1%
21 1
< 0.1%
30 1
< 0.1%
31 1
< 0.1%
34 1
< 0.1%
35 1
< 0.1%
ValueCountFrequency (%)
31383 1
< 0.1%
31382 1
< 0.1%
31381 1
< 0.1%
31378 1
< 0.1%
31376 1
< 0.1%
31368 1
< 0.1%
31367 1
< 0.1%
31365 1
< 0.1%
31362 1
< 0.1%
31359 1
< 0.1%

업소명
Text

Distinct9282
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T05:21:07.039252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length33
Mean length6.3961
Min length1

Characters and Unicode

Total characters63961
Distinct characters1087
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8800 ?
Unique (%)88.0%

Sample

1st row아빠찜닭
2nd row소와 나무
3rd row짬뽕칼국수
4th row노비아갈라
5th row다이와스시
ValueCountFrequency (%)
다사점 26
 
0.2%
동성로점 21
 
0.2%
식당 17
 
0.1%
대구 16
 
0.1%
칠곡점 16
 
0.1%
성서점 14
 
0.1%
본점 14
 
0.1%
상인점 14
 
0.1%
서재점 13
 
0.1%
대구점 13
 
0.1%
Other values (9890) 11655
98.6%
2023-12-11T05:21:07.682246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 2025
 
3.2%
1821
 
2.8%
식 1347
 
2.1%
이 1209
 
1.9%
당 1167
 
1.8%
대 1144
 
1.8%
구 913
 
1.4%
) 860
 
1.3%
( 860
 
1.3%
리 802
 
1.3%
Other values (1077) 51813
81.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56530
88.4%
Space Separator 1821
 
2.8%
Lowercase Letter 1609
 
2.5%
Uppercase Letter 1348
 
2.1%
Close Punctuation 860
 
1.3%
Open Punctuation 860
 
1.3%
Decimal Number 708
 
1.1%
Other Punctuation 211
 
0.3%
Dash Punctuation 10
 
< 0.1%
Connector Punctuation 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 2025
 
3.6%
식 1347
 
2.4%
이 1209
 
2.1%
당 1167
 
2.1%
대 1144
 
2.0%
구 913
 
1.6%
리 802
 
1.4%
국 673
 
1.2%
수 639
 
1.1%
스 638
 
1.1%
Other values (999) 45973
81.3%
Uppercase Letter
ValueCountFrequency (%)
B 116
 
8.6%
A 105
 
7.8%
O 97
 
7.2%
E 93
 
6.9%
T 83
 
6.2%
C 82
 
6.1%
R 77
 
5.7%
H 65
 
4.8%
L 64
 
4.7%
D 62
 
4.6%
Other values (16) 504
37.4%
Lowercase Letter
ValueCountFrequency (%)
e 214
13.3%
o 174
 
10.8%
a 158
 
9.8%
r 102
 
6.3%
i 100
 
6.2%
n 99
 
6.2%
s 84
 
5.2%
l 71
 
4.4%
c 70
 
4.4%
t 64
 
4.0%
Other values (15) 473
29.4%
Decimal Number
ValueCountFrequency (%)
1 125
17.7%
0 117
16.5%
3 98
13.8%
2 96
13.6%
9 64
9.0%
5 53
7.5%
8 44
 
6.2%
7 41
 
5.8%
4 35
 
4.9%
6 35
 
4.9%
Other Punctuation
ValueCountFrequency (%)
& 92
43.6%
. 52
24.6%
, 27
 
12.8%
' 17
 
8.1%
· 8
 
3.8%
; 5
 
2.4%
! 5
 
2.4%
: 3
 
1.4%
? 1
 
0.5%
# 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1821
100.0%
Close Punctuation
ValueCountFrequency (%)
) 860
100.0%
Open Punctuation
ValueCountFrequency (%)
( 860
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56484
88.3%
Common 4473
 
7.0%
Latin 2958
 
4.6%
Han 42
 
0.1%
Hiragana 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 2025
 
3.6%
식 1347
 
2.4%
이 1209
 
2.1%
당 1167
 
2.1%
대 1144
 
2.0%
구 913
 
1.6%
리 802
 
1.4%
국 673
 
1.2%
수 639
 
1.1%
스 638
 
1.1%
Other values (966) 45927
81.3%
Latin
ValueCountFrequency (%)
e 214
 
7.2%
o 174
 
5.9%
a 158
 
5.3%
B 116
 
3.9%
A 105
 
3.5%
r 102
 
3.4%
i 100
 
3.4%
n 99
 
3.3%
O 97
 
3.3%
E 93
 
3.1%
Other values (42) 1700
57.5%
Han
ValueCountFrequency (%)
家 5
 
11.9%
愛 4
 
9.5%
酒 3
 
7.1%
人 2
 
4.8%
味 2
 
4.8%
姜 1
 
2.4%
火 1
 
2.4%
美 1
 
2.4%
集 1
 
2.4%
珍 1
 
2.4%
Other values (21) 21
50.0%
Common
ValueCountFrequency (%)
1821
40.7%
) 860
19.2%
( 860
19.2%
1 125
 
2.8%
0 117
 
2.6%
3 98
 
2.2%
2 96
 
2.1%
& 92
 
2.1%
9 64
 
1.4%
5 53
 
1.2%
Other values (16) 287
 
6.4%
Hiragana
ValueCountFrequency (%)
ど 2
50.0%
ん 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56484
88.3%
ASCII 7422
 
11.6%
CJK 40
 
0.1%
None 8
 
< 0.1%
Hiragana 4
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 2025
 
3.6%
식 1347
 
2.4%
이 1209
 
2.1%
당 1167
 
2.1%
대 1144
 
2.0%
구 913
 
1.6%
리 802
 
1.4%
국 673
 
1.2%
수 639
 
1.1%
스 638
 
1.1%
Other values (966) 45927
81.3%
ASCII
ValueCountFrequency (%)
1821
24.5%
) 860
 
11.6%
( 860
 
11.6%
e 214
 
2.9%
o 174
 
2.3%
a 158
 
2.1%
1 125
 
1.7%
0 117
 
1.6%
B 116
 
1.6%
A 105
 
1.4%
Other values (66) 2872
38.7%
None
ValueCountFrequency (%)
· 8
100.0%
CJK
ValueCountFrequency (%)
家 5
 
12.5%
愛 4
 
10.0%
酒 3
 
7.5%
人 2
 
5.0%
味 2
 
5.0%
姜 1
 
2.5%
火 1
 
2.5%
美 1
 
2.5%
集 1
 
2.5%
珍 1
 
2.5%
Other values (19) 19
47.5%
Hiragana
ValueCountFrequency (%)
ど 2
50.0%
ん 2
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
林 1
50.0%
女 1
50.0%

업태
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4088 
기타
1662 
호프/통닭
1001 
식육(숯불구이)
877 
경양식
510 
Other values (16)
1862 

Length

Max length15
Median length2
Mean length3.264
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row식육(숯불구이)
3rd row한식
4th row뷔페식
5th row일식

Common Values

ValueCountFrequency (%)
한식 4088
40.9%
기타 1662
16.6%
호프/통닭 1001
 
10.0%
식육(숯불구이) 877
 
8.8%
경양식 510
 
5.1%
중국식 395
 
4.0%
분식 367
 
3.7%
일식 289
 
2.9%
정종/대포집/소주방 216
 
2.2%
회집 215
 
2.1%
Other values (11) 380
 
3.8%

Length

2023-12-11T05:21:07.904405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4088
40.9%
기타 1662
16.6%
호프/통닭 1001
 
10.0%
식육(숯불구이 877
 
8.8%
경양식 510
 
5.1%
중국식 395
 
4.0%
분식 367
 
3.7%
일식 289
 
2.9%
정종/대포집/소주방 216
 
2.2%
회집 215
 
2.1%
Other values (11) 380
 
3.8%

업소주소
Text

Distinct9709
Distinct (%)97.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-11T05:21:08.448646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length54
Mean length27.60046
Min length2

Characters and Unicode

Total characters275977
Distinct characters479
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

Unique9458 ?
Unique (%)94.6%

Sample

1st row대구광역시 달성군 화원읍 사문진로 349-51(1층)
2nd row대구광역시 중구 대봉로 241(대봉동, 지상1층)
3rd row대구광역시 달성군 화원읍 성암로 16-71
4th row대구광역시 동구 동촌로 87(3층, 4층 검사동, 노비아갈라웨딩)
5th row대구광역시 달서구 달구벌대로332길 82(1층 감삼동)
ValueCountFrequency (%)
대구광역시 9995
 
20.1%
달서구 2003
 
4.0%
북구 1606
 
3.2%
수성구 1467
 
3.0%
동구 1439
 
2.9%
중구 977
 
2.0%
달성군 953
 
1.9%
서구 748
 
1.5%
남구 683
 
1.4%
1층 597
 
1.2%
Other values (9529) 29193
58.8%
2023-12-11T05:21:09.370367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39670
 
14.4%
구 20341
 
7.4%
1 14949
 
5.4%
대 12984
 
4.7%
동 12894
 
4.7%
시 10317
 
3.7%
역 10118
 
3.7%
광 10025
 
3.6%
로 9583
 
3.5%
) 9579
 
3.5%
Other values (469) 125517
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165069
59.8%
Decimal Number 47407
 
17.2%
Space Separator 39670
 
14.4%
Close Punctuation 9579
 
3.5%
Open Punctuation 9579
 
3.5%
Dash Punctuation 2351
 
0.9%
Other Punctuation 1822
 
0.7%
Uppercase Letter 414
 
0.2%
Math Symbol 51
 
< 0.1%
Lowercase Letter 35
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 20341
 
12.3%
대 12984
 
7.9%
동 12894
 
7.8%
시 10317
 
6.3%
역 10118
 
6.1%
광 10025
 
6.1%
로 9583
 
5.8%
층 5837
 
3.5%
길 5481
 
3.3%
성 3951
 
2.4%
Other values (412) 63538
38.5%
Uppercase Letter
ValueCountFrequency (%)
A 127
30.7%
B 96
23.2%
S 23
 
5.6%
C 23
 
5.6%
D 16
 
3.9%
M 16
 
3.9%
T 15
 
3.6%
L 13
 
3.1%
E 12
 
2.9%
O 11
 
2.7%
Other values (13) 62
15.0%
Lowercase Letter
ValueCountFrequency (%)
e 15
42.9%
c 3
 
8.6%
l 3
 
8.6%
o 2
 
5.7%
r 2
 
5.7%
d 2
 
5.7%
i 2
 
5.7%
w 2
 
5.7%
t 1
 
2.9%
a 1
 
2.9%
Other values (2) 2
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 14949
31.5%
2 6729
14.2%
3 4717
 
10.0%
4 3755
 
7.9%
0 3724
 
7.9%
5 3353
 
7.1%
6 3055
 
6.4%
7 2628
 
5.5%
9 2253
 
4.8%
8 2244
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 1800
98.8%
. 10
 
0.5%
/ 4
 
0.2%
· 3
 
0.2%
@ 2
 
0.1%
& 2
 
0.1%
？ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
39670
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9579
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9579
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2351
100.0%
Math Symbol
ValueCountFrequency (%)
~ 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165069
59.8%
Common 110459
40.0%
Latin 449
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 20341
 
12.3%
대 12984
 
7.9%
동 12894
 
7.8%
시 10317
 
6.3%
역 10118
 
6.1%
광 10025
 
6.1%
로 9583
 
5.8%
층 5837
 
3.5%
길 5481
 
3.3%
성 3951
 
2.4%
Other values (412) 63538
38.5%
Latin
ValueCountFrequency (%)
A 127
28.3%
B 96
21.4%
S 23
 
5.1%
C 23
 
5.1%
D 16
 
3.6%
M 16
 
3.6%
e 15
 
3.3%
T 15
 
3.3%
L 13
 
2.9%
E 12
 
2.7%
Other values (25) 93
20.7%
Common
ValueCountFrequency (%)
39670
35.9%
1 14949
 
13.5%
) 9579
 
8.7%
( 9579
 
8.7%
2 6729
 
6.1%
3 4717
 
4.3%
4 3755
 
3.4%
0 3724
 
3.4%
5 3353
 
3.0%
6 3055
 
2.8%
Other values (12) 11349
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165069
59.8%
ASCII 110904
40.2%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39670
35.8%
1 14949
 
13.5%
) 9579
 
8.6%
( 9579
 
8.6%
2 6729
 
6.1%
3 4717
 
4.3%
4 3755
 
3.4%
0 3724
 
3.4%
5 3353
 
3.0%
6 3055
 
2.8%
Other values (45) 11794
 
10.6%
Hangul
ValueCountFrequency (%)
구 20341
 
12.3%
대 12984
 
7.9%
동 12894
 
7.8%
시 10317
 
6.3%
역 10118
 
6.1%
광 10025
 
6.1%
로 9583
 
5.8%
층 5837
 
3.5%
길 5481
 
3.3%
성 3951
 
2.4%
Other values (412) 63538
38.5%
None
ValueCountFrequency (%)
· 3
75.0%
？ 1
 
25.0%

Interactions

2023-12-11T05:19:11.942935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T05:21:09.546098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업태
연번1.0000.401
업태0.4011.000
2023-12-11T05:21:09.691895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업태
연번1.0001.000
업태1.0001.000

Missing values

2023-12-11T05:21:06.165140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T05:21:06.304787image/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

연번업소명업태업소주소
2968529685아빠찜닭한식대구광역시 달성군 화원읍 사문진로 349-51(1층)
15151516소와 나무식육(숯불구이)대구광역시 중구 대봉로 241(대봉동, 지상1층)
3035330353짬뽕칼국수한식대구광역시 달성군 화원읍 성암로 16-71
36033604노비아갈라뷔페식대구광역시 동구 동촌로 87(3층, 4층 검사동, 노비아갈라웨딩)
2253022531다이와스시일식대구광역시 달서구 달구벌대로332길 82(1층 감삼동)
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