Overview

Dataset statistics

Number of variables9
Number of observations334
Missing cells36
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.9 KiB
Average record size in memory73.4 B

Variable types

Numeric1
Categorical2
Text6

Dataset

Description대구광역시_착한가격업소 현황_20240401
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15126761&dataSetDetailId=151267611f3124ce021aa&provdMethod=FILE

Alerts

연번 is highly overall correlated with 구군High correlation
구군 is highly overall correlated with 연번High correlation
업종 is highly imbalanced (51.6%)Imbalance
연락처 has 36 (10.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-20 17:21:20.124129
Analysis finished2024-04-20 17:21:22.218421
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct334
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167.5
Minimum1
Maximum334
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-21T02:21:22.281819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.65
Q184.25
median167.5
Q3250.75
95-th percentile317.35
Maximum334
Range333
Interquartile range (IQR)166.5

Descriptive statistics

Standard deviation96.561725
Coefficient of variation (CV)0.57648791
Kurtosis-1.2
Mean167.5
Median Absolute Deviation (MAD)83.5
Skewness0
Sum55945
Variance9324.1667
MonotonicityStrictly increasing
2024-04-21T02:21:22.401137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
231 1
 
0.3%
229 1
 
0.3%
228 1
 
0.3%
227 1
 
0.3%
226 1
 
0.3%
225 1
 
0.3%
224 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
Other values (324) 324
97.0%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
334 1
0.3%
333 1
0.3%
332 1
0.3%
331 1
0.3%
330 1
0.3%
329 1
0.3%
328 1
0.3%
327 1
0.3%
326 1
0.3%
325 1
0.3%

업종
Categorical

IMBALANCE 

Distinct19
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
한식
210 
이미용업
35 
중식
29 
미용업
24 
세탁업
 
8
Other values (14)
28 

Length

Max length12
Median length2
Mean length2.4730539
Min length2

Unique

Unique8 ?
Unique (%)2.4%

Sample

1st row이미용업
2nd row한식
3rd row이미용업
4th row한식
5th row중식

Common Values

ValueCountFrequency (%)
한식 210
62.9%
이미용업 35
 
10.5%
중식 29
 
8.7%
미용업 24
 
7.2%
세탁업 8
 
2.4%
일식 7
 
2.1%
목욕업 4
 
1.2%
기타요식업 3
 
0.9%
양식 2
 
0.6%
한식_일반 2
 
0.6%
Other values (9) 10
 
3.0%

Length

2024-04-21T02:21:22.545591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 210
62.7%
이미용업 36
 
10.7%
중식 29
 
8.7%
미용업 24
 
7.2%
세탁업 8
 
2.4%
일식 7
 
2.1%
목욕업 4
 
1.2%
기타요식업 3
 
0.9%
기타(외식 2
 
0.6%
기타 2
 
0.6%
Other values (8) 10
 
3.0%

업소명
Text

Distinct330
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-21T02:21:22.800859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length5.2904192
Min length2

Characters and Unicode

Total characters1767
Distinct characters368
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

Unique326 ?
Unique (%)97.6%

Sample

1st row현대이용소
2nd row춘사김밥
3rd row영생이용소
4th row마산설렁탕
5th row중해반점
ValueCountFrequency (%)
시골밥상 3
 
0.8%
별미국수 2
 
0.6%
현대이용소 2
 
0.6%
우당탕반점 2
 
0.6%
민머리방 1
 
0.3%
청도시골밥상 1
 
0.3%
보배루 1
 
0.3%
차오 1
 
0.3%
중화반점 1
 
0.3%
국수둥지 1
 
0.3%
Other values (348) 348
95.9%
2024-04-21T02:21:23.155241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 51
 
2.9%
국 51
 
2.9%
수 50
 
2.8%
미 45
 
2.5%
당 41
 
2.3%
이 35
 
2.0%
용 35
 
2.0%
어 29
 
1.6%
29
 
1.6%
밥 27
 
1.5%
Other values (358) 1374
77.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1714
97.0%
Space Separator 29
 
1.6%
Decimal Number 9
 
0.5%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%
Lowercase Letter 3
 
0.2%
Uppercase Letter 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 51
 
3.0%
국 51
 
3.0%
수 50
 
2.9%
미 45
 
2.6%
당 41
 
2.4%
이 35
 
2.0%
용 35
 
2.0%
어 29
 
1.7%
밥 27
 
1.6%
장 25
 
1.5%
Other values (342) 1325
77.3%
Decimal Number
ValueCountFrequency (%)
0 3
33.3%
5 2
22.2%
2 1
 
11.1%
4 1
 
11.1%
3 1
 
11.1%
6 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
m 1
33.3%
i 1
33.3%
s 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
S 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1714
97.0%
Common 47
 
2.7%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 51
 
3.0%
국 51
 
3.0%
수 50
 
2.9%
미 45
 
2.6%
당 41
 
2.4%
이 35
 
2.0%
용 35
 
2.0%
어 29
 
1.7%
밥 27
 
1.6%
장 25
 
1.5%
Other values (342) 1325
77.3%
Common
ValueCountFrequency (%)
29
61.7%
( 4
 
8.5%
) 4
 
8.5%
0 3
 
6.4%
5 2
 
4.3%
2 1
 
2.1%
' 1
 
2.1%
4 1
 
2.1%
3 1
 
2.1%
6 1
 
2.1%
Latin
ValueCountFrequency (%)
m 1
16.7%
K 1
16.7%
i 1
16.7%
s 1
16.7%
S 1
16.7%
G 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1714
97.0%
ASCII 53
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 51
 
3.0%
국 51
 
3.0%
수 50
 
2.9%
미 45
 
2.6%
당 41
 
2.4%
이 35
 
2.0%
용 35
 
2.0%
어 29
 
1.7%
밥 27
 
1.6%
장 25
 
1.5%
Other values (342) 1325
77.3%
ASCII
ValueCountFrequency (%)
29
54.7%
( 4
 
7.5%
) 4
 
7.5%
0 3
 
5.7%
5 2
 
3.8%
2 1
 
1.9%
m 1
 
1.9%
' 1
 
1.9%
K 1
 
1.9%
i 1
 
1.9%
Other values (6) 6
 
11.3%

업주명
Text

Distinct324
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-21T02:21:23.449777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0149701
Min length3

Characters and Unicode

Total characters1007
Distinct characters153
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique316 ?
Unique (%)94.6%

Sample

1st row이수길
2nd row이춘자
3rd row김상국
4th row조웅제
5th row우려원
ValueCountFrequency (%)
김정희 3
 
0.9%
김병학 3
 
0.9%
박금희 2
 
0.6%
김영숙 2
 
0.6%
박영희 2
 
0.6%
김금희 2
 
0.6%
김명순 2
 
0.6%
이경희 2
 
0.6%
시미연 1
 
0.3%
김윤권 1
 
0.3%
Other values (314) 314
94.0%
2024-04-21T02:21:23.854920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 79
 
7.8%
이 59
 
5.9%
희 49
 
4.9%
영 36
 
3.6%
순 36
 
3.6%
정 34
 
3.4%
경 33
 
3.3%
숙 30
 
3.0%
박 28
 
2.8%
자 19
 
1.9%
Other values (143) 604
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1005
99.8%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 79
 
7.9%
이 59
 
5.9%
희 49
 
4.9%
영 36
 
3.6%
순 36
 
3.6%
정 34
 
3.4%
경 33
 
3.3%
숙 30
 
3.0%
박 28
 
2.8%
자 19
 
1.9%
Other values (141) 602
59.9%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1005
99.8%
Common 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 79
 
7.9%
이 59
 
5.9%
희 49
 
4.9%
영 36
 
3.6%
순 36
 
3.6%
정 34
 
3.4%
경 33
 
3.3%
숙 30
 
3.0%
박 28
 
2.8%
자 19
 
1.9%
Other values (141) 602
59.9%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1005
99.8%
ASCII 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 79
 
7.9%
이 59
 
5.9%
희 49
 
4.9%
영 36
 
3.6%
순 36
 
3.6%
정 34
 
3.4%
경 33
 
3.3%
숙 30
 
3.0%
박 28
 
2.8%
자 19
 
1.9%
Other values (141) 602
59.9%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

구군
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
달서구
105 
수성구
45 
서구
40 
동구
33 
달성군
31 
Other values (4)
80 

Length

Max length3
Median length3
Mean length2.6017964
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
달서구 105
31.4%
수성구 45
13.5%
서구 40
 
12.0%
동구 33
 
9.9%
달성군 31
 
9.3%
북구 25
 
7.5%
중구 22
 
6.6%
군위군 20
 
6.0%
남구 13
 
3.9%

Length

2024-04-21T02:21:23.980278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:21:24.098256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달서구 105
31.4%
수성구 45
13.5%
서구 40
 
12.0%
동구 33
 
9.9%
달성군 31
 
9.3%
북구 25
 
7.5%
중구 22
 
6.6%
군위군 20
 
6.0%
남구 13
 
3.9%

주소
Text

Distinct331
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-21T02:21:24.360791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length16.353293
Min length5

Characters and Unicode

Total characters5462
Distinct characters210
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

Unique328 ?
Unique (%)98.2%

Sample

1st row동덕로36길 60
2nd row중앙대로 282
3rd row이천로 184-8
4th row경상감영1길 41
5th row명륜로 63
ValueCountFrequency (%)
대구광역시 21
 
2.3%
군위군 20
 
2.2%
서구 14
 
1.5%
군위읍 12
 
1.3%
다사읍 10
 
1.1%
1층 9
 
1.0%
120 8
 
0.9%
화원읍 8
 
0.9%
파동로 6
 
0.6%
중앙길 6
 
0.6%
Other values (666) 812
87.7%
2024-04-21T02:21:24.773981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
615
 
11.3%
1 380
 
7.0%
로 310
 
5.7%
동 268
 
4.9%
2 223
 
4.1%
( 222
 
4.1%
) 222
 
4.1%
길 201
 
3.7%
3 181
 
3.3%
4 152
 
2.8%
Other values (200) 2688
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2603
47.7%
Decimal Number 1619
29.6%
Space Separator 615
 
11.3%
Open Punctuation 222
 
4.1%
Close Punctuation 222
 
4.1%
Dash Punctuation 121
 
2.2%
Other Punctuation 59
 
1.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 310
 
11.9%
동 268
 
10.3%
길 201
 
7.7%
대 69
 
2.7%
구 61
 
2.3%
상 60
 
2.3%
군 54
 
2.1%
산 54
 
2.1%
서 47
 
1.8%
당 44
 
1.7%
Other values (181) 1435
55.1%
Decimal Number
ValueCountFrequency (%)
1 380
23.5%
2 223
13.8%
3 181
11.2%
4 152
 
9.4%
5 145
 
9.0%
6 137
 
8.5%
0 113
 
7.0%
7 110
 
6.8%
8 94
 
5.8%
9 84
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 55
93.2%
/ 2
 
3.4%
? 1
 
1.7%
@ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
615
100.0%
Open Punctuation
ValueCountFrequency (%)
( 222
100.0%
Close Punctuation
ValueCountFrequency (%)
) 222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2858
52.3%
Hangul 2603
47.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 310
 
11.9%
동 268
 
10.3%
길 201
 
7.7%
대 69
 
2.7%
구 61
 
2.3%
상 60
 
2.3%
군 54
 
2.1%
산 54
 
2.1%
서 47
 
1.8%
당 44
 
1.7%
Other values (181) 1435
55.1%
Common
ValueCountFrequency (%)
615
21.5%
1 380
13.3%
2 223
 
7.8%
( 222
 
7.8%
) 222
 
7.8%
3 181
 
6.3%
4 152
 
5.3%
5 145
 
5.1%
6 137
 
4.8%
- 121
 
4.2%
Other values (8) 460
16.1%
Latin
ValueCountFrequency (%)
a 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2859
52.3%
Hangul 2603
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
615
21.5%
1 380
13.3%
2 223
 
7.8%
( 222
 
7.8%
) 222
 
7.8%
3 181
 
6.3%
4 152
 
5.3%
5 145
 
5.1%
6 137
 
4.8%
- 121
 
4.2%
Other values (9) 461
16.1%
Hangul
ValueCountFrequency (%)
로 310
 
11.9%
동 268
 
10.3%
길 201
 
7.7%
대 69
 
2.7%
구 61
 
2.3%
상 60
 
2.3%
군 54
 
2.1%
산 54
 
2.1%
서 47
 
1.8%
당 44
 
1.7%
Other values (181) 1435
55.1%

연락처
Text

MISSING 

Distinct297
Distinct (%)99.7%
Missing36
Missing (%)10.8%
Memory size2.7 KiB
2024-04-21T02:21:24.972852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.077181
Min length12

Characters and Unicode

Total characters3599
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)99.3%

Sample

1st row053-423-1473
2nd row053-423-7827
3rd row053-425-9732
4th row053-254-4317
5th row053-255-8555
ValueCountFrequency (%)
054-382-5308 2
 
0.7%
053-587-3331 1
 
0.3%
053-627-8860 1
 
0.3%
053-656-1002 1
 
0.3%
053-636-0207 1
 
0.3%
053-588-1147 1
 
0.3%
070-7535-8282 1
 
0.3%
053-291-6184 1
 
0.3%
053-591-2020 1
 
0.3%
053-423-1473 1
 
0.3%
Other values (287) 287
96.3%
2024-04-21T02:21:25.307610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 597
16.6%
- 596
16.6%
3 521
14.5%
0 445
12.4%
2 253
7.0%
6 237
 
6.6%
8 224
 
6.2%
7 198
 
5.5%
4 177
 
4.9%
1 171
 
4.8%
Other values (3) 180
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2982
82.9%
Dash Punctuation 596
 
16.6%
Space Separator 20
 
0.6%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 597
20.0%
3 521
17.5%
0 445
14.9%
2 253
8.5%
6 237
 
7.9%
8 224
 
7.5%
7 198
 
6.6%
4 177
 
5.9%
1 171
 
5.7%
9 159
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 596
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 597
16.6%
- 596
16.6%
3 521
14.5%
0 445
12.4%
2 253
7.0%
6 237
 
6.6%
8 224
 
6.2%
7 198
 
5.5%
4 177
 
4.9%
1 171
 
4.8%
Other values (3) 180
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 597
16.6%
- 596
16.6%
3 521
14.5%
0 445
12.4%
2 253
7.0%
6 237
 
6.6%
8 224
 
6.2%
7 198
 
5.5%
4 177
 
4.9%
1 171
 
4.8%
Other values (3) 180
 
5.0%

대표메뉴
Text

Distinct189
Distinct (%)56.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-21T02:21:25.562878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length5.4341317
Min length1

Characters and Unicode

Total characters1815
Distinct characters220
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)45.5%

Sample

1st row커트일반
2nd row참치김밥
3rd row커트
4th row설렁탕
5th row자장면
ValueCountFrequency (%)
칼국수 26
 
7.2%
커트 20
 
5.5%
자장면 18
 
5.0%
잔치국수 14
 
3.9%
컷트 11
 
3.0%
된장찌개 10
 
2.8%
짜장면 9
 
2.5%
정식 6
 
1.7%
돼지국밥 6
 
1.7%
파마 5
 
1.4%
Other values (188) 237
65.5%
2024-04-21T02:21:25.907112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
 
6.8%
국 97
 
5.3%
수 75
 
4.1%
장 54
 
3.0%
) 54
 
3.0%
( 53
 
2.9%
트 48
 
2.6%
0 43
 
2.4%
밥 42
 
2.3%
칼 41
 
2.3%
Other values (210) 1185
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1440
79.3%
Space Separator 123
 
6.8%
Decimal Number 96
 
5.3%
Close Punctuation 54
 
3.0%
Open Punctuation 53
 
2.9%
Lowercase Letter 28
 
1.5%
Other Punctuation 14
 
0.8%
Math Symbol 5
 
0.3%
Dash Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 97
 
6.7%
수 75
 
5.2%
장 54
 
3.8%
트 48
 
3.3%
밥 42
 
2.9%
칼 41
 
2.8%
비 35
 
2.4%
커 33
 
2.3%
치 32
 
2.2%
면 31
 
2.2%
Other values (195) 952
66.1%
Decimal Number
ValueCountFrequency (%)
0 43
44.8%
1 24
25.0%
2 12
 
12.5%
5 10
 
10.4%
4 4
 
4.2%
8 3
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 13
92.9%
/ 1
 
7.1%
Space Separator
ValueCountFrequency (%)
123
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 28
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1436
79.1%
Common 346
 
19.1%
Latin 29
 
1.6%
Han 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 97
 
6.8%
수 75
 
5.2%
장 54
 
3.8%
트 48
 
3.3%
밥 42
 
2.9%
칼 41
 
2.9%
비 35
 
2.4%
커 33
 
2.3%
치 32
 
2.2%
면 31
 
2.2%
Other values (192) 948
66.0%
Common
ValueCountFrequency (%)
123
35.5%
) 54
15.6%
( 53
15.3%
0 43
 
12.4%
1 24
 
6.9%
, 13
 
3.8%
2 12
 
3.5%
5 10
 
2.9%
+ 5
 
1.4%
4 4
 
1.2%
Other values (3) 5
 
1.4%
Han
ValueCountFrequency (%)
大 2
50.0%
中 1
25.0%
小 1
25.0%
Latin
ValueCountFrequency (%)
g 28
96.6%
A 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1436
79.1%
ASCII 375
 
20.7%
CJK 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
32.8%
) 54
14.4%
( 53
14.1%
0 43
 
11.5%
g 28
 
7.5%
1 24
 
6.4%
, 13
 
3.5%
2 12
 
3.2%
5 10
 
2.7%
+ 5
 
1.3%
Other values (5) 10
 
2.7%
Hangul
ValueCountFrequency (%)
국 97
 
6.8%
수 75
 
5.2%
장 54
 
3.8%
트 48
 
3.3%
밥 42
 
2.9%
칼 41
 
2.9%
비 35
 
2.4%
커 33
 
2.3%
치 32
 
2.2%
면 31
 
2.2%
Other values (192) 948
66.0%
CJK
ValueCountFrequency (%)
大 2
50.0%
中 1
25.0%
小 1
25.0%

대표메뉴가격
Text

Distinct78
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-21T02:21:26.063522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length4
Mean length5.1467066
Min length4

Characters and Unicode

Total characters1719
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)15.3%

Sample

1st row10000
2nd row2500
3rd row8000
4th row12000
5th row6000
ValueCountFrequency (%)
7000 53
13.5%
6000 53
13.5%
5000 44
11.2%
8000 43
10.9%
10000 28
 
7.1%
9000 17
 
4.3%
5500 13
 
3.3%
12000 12
 
3.1%
25000 12
 
3.1%
4000 12
 
3.1%
Other values (39) 106
27.0%
2024-04-21T02:21:26.337079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1143
66.5%
5 135
 
7.9%
1 77
 
4.5%
6 71
 
4.1%
7 63
 
3.7%
59
 
3.4%
8 49
 
2.9%
2 43
 
2.5%
9 27
 
1.6%
3 26
 
1.5%
Other values (6) 26
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1655
96.3%
Space Separator 59
 
3.4%
Other Letter 4
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1143
69.1%
5 135
 
8.2%
1 77
 
4.7%
6 71
 
4.3%
7 63
 
3.8%
8 49
 
3.0%
2 43
 
2.6%
9 27
 
1.6%
3 26
 
1.6%
4 21
 
1.3%
Other Letter
ValueCountFrequency (%)
포 1
25.0%
장 1
25.0%
남 1
25.0%
여 1
25.0%
Space Separator
ValueCountFrequency (%)
59
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1715
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1143
66.6%
5 135
 
7.9%
1 77
 
4.5%
6 71
 
4.1%
7 63
 
3.7%
59
 
3.4%
8 49
 
2.9%
2 43
 
2.5%
9 27
 
1.6%
3 26
 
1.5%
Other values (2) 22
 
1.3%
Hangul
ValueCountFrequency (%)
포 1
25.0%
장 1
25.0%
남 1
25.0%
여 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1715
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1143
66.6%
5 135
 
7.9%
1 77
 
4.5%
6 71
 
4.1%
7 63
 
3.7%
59
 
3.4%
8 49
 
2.9%
2 43
 
2.5%
9 27
 
1.6%
3 26
 
1.5%
Other values (2) 22
 
1.3%
Hangul
ValueCountFrequency (%)
포 1
25.0%
장 1
25.0%
남 1
25.0%
여 1
25.0%

Interactions

2024-04-21T02:21:21.900148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T02:21:26.420150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종구군대표메뉴가격
연번1.0000.3880.9200.495
업종0.3881.0000.3950.949
구군0.9200.3951.0000.651
대표메뉴가격0.4950.9490.6511.000
2024-04-21T02:21:26.508486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종구군
업종1.0000.163
구군0.1631.000
2024-04-21T02:21:26.589888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종구군
연번1.0000.1530.745
업종0.1531.0000.163
구군0.7450.1631.000

Missing values

2024-04-21T02:21:22.063957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T02:21:22.172642image/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

연번업종업소명업주명구군주소연락처대표메뉴대표메뉴가격
01이미용업현대이용소이수길중구동덕로36길 60053-423-1473커트일반10000
12한식춘사김밥이춘자중구중앙대로 282053-423-7827참치김밥2500
23이미용업영생이용소김상국중구이천로 184-8053-425-9732커트8000
34한식마산설렁탕조웅제중구경상감영1길 41053-254-4317설렁탕12000
45중식중해반점우려원중구명륜로 63053-255-8555자장면6000
56중식만리향반점전은숙중구명덕로35길 112053-255-9380자장면5000
67이미용업은혜이용소성기환중구명륜로 98053-427-2021커트13000
78한식한우장김여옥중구국채보상로 567053-257-1125설렁탕10000
89한식단아정권기화중구동덕로 177053-256-9292갈비탕8000
910한식옛날국수공희영중구중앙대로 439053-256-1221잔치국수2000
연번업종업소명업주명구군주소연락처대표메뉴대표메뉴가격
324325한식한마음식당손필경군위군대구광역시 군위군 군위읍 중앙길 56-16054-382-8675김치찌개7000
325326한식자연산민물시래기매운탕이병우군위군대구광역시 군위군 효령면 효우로 83054-382-5308메기매운탕(소)25000
326327세탁업소보세탁소정태재군위군대구광역시 군위군 소보면 송원3길 19054-382-5308드라이클리닝6000
327328세탁업군위크리닝김태중군위군대구광역시 군위군 군위읍 중앙길 53054-383-3777드라이클리닝6000
328329미용업우아미미용실박맹희군위군대구광역시 군위군 군위읍 중앙길 112-2054-382-5158커트15000
329330미용업장근희헤어장근희군위군대구광역시 군위군 군위읍 중앙길 141054-383-6832커트15000
330331미용업박현주미용실박현주군위군대구광역시 군위군 군위읍 중앙4길 16-6054-383-6777커트15000
331332한식우리분식강석진군위군대구광역시 군위군 우보면 이화길 120054-915-9915김밥3000
332333한식우리칼국수전옥자군위군대구광역시 군위군 삼국유사면 삼국유사로 5054-383-9980칼국수7000
333334한식하림꼬꼬불고기식당김순자군위군대구광역시 군위군 의흥면 읍내5길 13-1054-382-7900닭목살불고기8000