Overview

Dataset statistics

Number of variables10
Number of observations76
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory83.7 B

Variable types

Categorical3
Text5
Numeric2

Dataset

Description경상남도 김해시의 착한가격업소 현황에 대한 데이터로 상호, 업종, 사업장주소, 전화번호, 가격 등에 대한 데이터를 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033316

Alerts

구분 is highly overall correlated with 비고High correlation
업종 is highly overall correlated with 비고High correlation
비고 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 비고High correlation
경도 is highly overall correlated with 비고High correlation
업종 is highly imbalanced (53.9%)Imbalance
상호 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:53:20.683526
Analysis finished2023-12-11 00:53:22.315206
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
착한가격업소
66 
10인이상 할인업소
10 

Length

Max length10
Median length6
Mean length6.5263158
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
착한가격업소 66
86.8%
10인이상 할인업소 10
 
13.2%

Length

2023-12-11T09:53:22.404890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:53:22.513653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
착한가격업소 66
76.7%
10인이상 10
 
11.6%
할인업소 10
 
11.6%

업종
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
음식업
61 
이미용업
7 
기타
 
4
세탁업
 
2
목욕업
 
2

Length

Max length4
Median length3
Mean length3.0394737
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row세탁업
2nd row세탁업
3rd row목욕업
4th row이미용업
5th row이미용업

Common Values

ValueCountFrequency (%)
음식업 61
80.3%
이미용업 7
 
9.2%
기타 4
 
5.3%
세탁업 2
 
2.6%
목욕업 2
 
2.6%

Length

2023-12-11T09:53:22.648384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:53:22.809673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식업 61
80.3%
이미용업 7
 
9.2%
기타 4
 
5.3%
세탁업 2
 
2.6%
목욕업 2
 
2.6%

상호
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T09:53:23.080322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length5.5131579
Min length2

Characters and Unicode

Total characters419
Distinct characters209
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

Unique76 ?
Unique (%)100.0%

Sample

1st row하이크리닝
2nd row미크리링삽
3rd row청수탕
4th row보이투맨
5th row다홍머리
ValueCountFrequency (%)
하이크리닝 1
 
1.1%
황룡 1
 
1.1%
사량도 1
 
1.1%
심술민경포차 1
 
1.1%
쌈마이 1
 
1.1%
끼니와분식 1
 
1.1%
만리장성&가야밀면 1
 
1.1%
굿모닝시락국 1
 
1.1%
삼정탕 1
 
1.1%
봉평메밀마당 1
 
1.1%
Other values (78) 78
88.6%
2023-12-11T09:53:23.501831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
2.9%
국 9
 
2.1%
장 9
 
2.1%
가 9
 
2.1%
지 8
 
1.9%
이 8
 
1.9%
밥 7
 
1.7%
리 7
 
1.7%
기 6
 
1.4%
수 6
 
1.4%
Other values (199) 338
80.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 367
87.6%
Space Separator 12
 
2.9%
Lowercase Letter 11
 
2.6%
Decimal Number 10
 
2.4%
Uppercase Letter 9
 
2.1%
Other Punctuation 4
 
1.0%
Open Punctuation 3
 
0.7%
Close Punctuation 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 9
 
2.5%
장 9
 
2.5%
가 9
 
2.5%
지 8
 
2.2%
이 8
 
2.2%
밥 7
 
1.9%
리 7
 
1.9%
기 6
 
1.6%
수 6
 
1.6%
탕 6
 
1.6%
Other values (171) 292
79.6%
Uppercase Letter
ValueCountFrequency (%)
L 1
11.1%
Y 1
11.1%
A 1
11.1%
T 1
11.1%
F 1
11.1%
B 1
11.1%
D 1
11.1%
O 1
11.1%
K 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
r 3
27.3%
a 2
18.2%
o 1
 
9.1%
y 1
 
9.1%
t 1
 
9.1%
c 1
 
9.1%
d 1
 
9.1%
e 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 4
40.0%
9 2
20.0%
3 1
 
10.0%
7 1
 
10.0%
5 1
 
10.0%
2 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
& 1
 
25.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 367
87.6%
Common 32
 
7.6%
Latin 20
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 9
 
2.5%
장 9
 
2.5%
가 9
 
2.5%
지 8
 
2.2%
이 8
 
2.2%
밥 7
 
1.9%
리 7
 
1.9%
기 6
 
1.6%
수 6
 
1.6%
탕 6
 
1.6%
Other values (171) 292
79.6%
Latin
ValueCountFrequency (%)
r 3
15.0%
a 2
 
10.0%
L 1
 
5.0%
Y 1
 
5.0%
A 1
 
5.0%
o 1
 
5.0%
y 1
 
5.0%
t 1
 
5.0%
T 1
 
5.0%
c 1
 
5.0%
Other values (7) 7
35.0%
Common
ValueCountFrequency (%)
12
37.5%
1 4
 
12.5%
( 3
 
9.4%
) 3
 
9.4%
. 3
 
9.4%
9 2
 
6.2%
3 1
 
3.1%
& 1
 
3.1%
7 1
 
3.1%
5 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 367
87.6%
ASCII 52
 
12.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
23.1%
1 4
 
7.7%
r 3
 
5.8%
( 3
 
5.8%
) 3
 
5.8%
. 3
 
5.8%
a 2
 
3.8%
9 2
 
3.8%
3 1
 
1.9%
& 1
 
1.9%
Other values (18) 18
34.6%
Hangul
ValueCountFrequency (%)
국 9
 
2.5%
장 9
 
2.5%
가 9
 
2.5%
지 8
 
2.2%
이 8
 
2.2%
밥 7
 
1.9%
리 7
 
1.9%
기 6
 
1.6%
수 6
 
1.6%
탕 6
 
1.6%
Other values (171) 292
79.6%

전화번호
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T09:53:23.737895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters912
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

Unique76 ?
Unique (%)100.0%

Sample

1st row055-328-4045
2nd row055-333-3982
3rd row055-314-7518
4th row055-311-4662
5th row055-324-1919
ValueCountFrequency (%)
055-328-4045 1
 
1.3%
055-337-0047 1
 
1.3%
055-338-9955 1
 
1.3%
055-902-6787 1
 
1.3%
055-322-2718 1
 
1.3%
055-338-3014 1
 
1.3%
055-321-9892 1
 
1.3%
055-312-9039 1
 
1.3%
055-311-6062 1
 
1.3%
055-333-3982 1
 
1.3%
Other values (66) 66
86.8%
2023-12-11T09:53:24.121197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 179
19.6%
- 152
16.7%
3 146
16.0%
0 121
13.3%
2 82
9.0%
1 52
 
5.7%
8 40
 
4.4%
4 37
 
4.1%
7 36
 
3.9%
9 36
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 760
83.3%
Dash Punctuation 152
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 179
23.6%
3 146
19.2%
0 121
15.9%
2 82
10.8%
1 52
 
6.8%
8 40
 
5.3%
4 37
 
4.9%
7 36
 
4.7%
9 36
 
4.7%
6 31
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 912
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 179
19.6%
- 152
16.7%
3 146
16.0%
0 121
13.3%
2 82
9.0%
1 52
 
5.7%
8 40
 
4.4%
4 37
 
4.1%
7 36
 
3.9%
9 36
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 179
19.6%
- 152
16.7%
3 146
16.0%
0 121
13.3%
2 82
9.0%
1 52
 
5.7%
8 40
 
4.4%
4 37
 
4.1%
7 36
 
3.9%
9 36
 
3.9%

지번주소
Text

Distinct70
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T09:53:24.395495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length19.723684
Min length15

Characters and Unicode

Total characters1499
Distinct characters88
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

Unique64 ?
Unique (%)84.2%

Sample

1st row경상남도 김해시 삼정동 608-1
2nd row경상남도 김해시 삼계동 1509-11
3rd row경상남도 김해시 대청동 72-3 풍림위너스빌딩
4th row경상남도 김해시 관동동 452-7 팔판마을4단지푸르지오아파트상가
5th row경상남도 김해시 내동 161-11
ValueCountFrequency (%)
경상남도 76
23.8%
김해시 76
23.8%
삼방동 20
 
6.3%
삼계동 8
 
2.5%
어방동 7
 
2.2%
관동동 7
 
2.2%
대청동 6
 
1.9%
내동 4
 
1.3%
구산동 4
 
1.3%
삼정동 4
 
1.3%
Other values (96) 107
33.5%
2023-12-11T09:53:24.820377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
243
16.2%
1 107
 
7.1%
동 83
 
5.5%
상 81
 
5.4%
도 79
 
5.3%
남 77
 
5.1%
시 77
 
5.1%
경 76
 
5.1%
김 76
 
5.1%
해 76
 
5.1%
Other values (78) 524
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 835
55.7%
Decimal Number 348
23.2%
Space Separator 243
 
16.2%
Dash Punctuation 73
 
4.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 83
9.9%
상 81
9.7%
도 79
9.5%
남 77
9.2%
시 77
9.2%
경 76
9.1%
김 76
9.1%
해 76
9.1%
삼 33
 
4.0%
방 27
 
3.2%
Other values (66) 150
18.0%
Decimal Number
ValueCountFrequency (%)
1 107
30.7%
6 42
 
12.1%
0 37
 
10.6%
2 33
 
9.5%
4 30
 
8.6%
3 28
 
8.0%
5 19
 
5.5%
8 19
 
5.5%
9 18
 
5.2%
7 15
 
4.3%
Space Separator
ValueCountFrequency (%)
243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 835
55.7%
Common 664
44.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 83
9.9%
상 81
9.7%
도 79
9.5%
남 77
9.2%
시 77
9.2%
경 76
9.1%
김 76
9.1%
해 76
9.1%
삼 33
 
4.0%
방 27
 
3.2%
Other values (66) 150
18.0%
Common
ValueCountFrequency (%)
243
36.6%
1 107
16.1%
- 73
 
11.0%
6 42
 
6.3%
0 37
 
5.6%
2 33
 
5.0%
4 30
 
4.5%
3 28
 
4.2%
5 19
 
2.9%
8 19
 
2.9%
Other values (2) 33
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 835
55.7%
ASCII 664
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
243
36.6%
1 107
16.1%
- 73
 
11.0%
6 42
 
6.3%
0 37
 
5.6%
2 33
 
5.0%
4 30
 
4.5%
3 28
 
4.2%
5 19
 
2.9%
8 19
 
2.9%
Other values (2) 33
 
5.0%
Hangul
ValueCountFrequency (%)
동 83
9.9%
상 81
9.7%
도 79
9.5%
남 77
9.2%
시 77
9.2%
경 76
9.1%
김 76
9.1%
해 76
9.1%
삼 33
 
4.0%
방 27
 
3.2%
Other values (66) 150
18.0%

도로명주소
Text

Distinct72
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T09:53:25.125789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length28
Mean length22.315789
Min length14

Characters and Unicode

Total characters1696
Distinct characters95
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)89.5%

Sample

1st row경상남도 김해시 활천로10번길 1
2nd row경상남도 김해시 가야로 212
3rd row경상남도 김해시 번화1로84번길 24
4th row경상남도 김해시 계동로 12
5th row경상남도 김해시 금관대로1297번길 2
ValueCountFrequency (%)
경상남도 76
23.3%
김해시 76
23.3%
인제로200번길 9
 
2.8%
인제로210번길 4
 
1.2%
1 4
 
1.2%
7 3
 
0.9%
활천로255번길 3
 
0.9%
계동로 3
 
0.9%
12 3
 
0.9%
9 3
 
0.9%
Other values (129) 142
43.6%
2023-12-11T09:53:25.976139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
250
 
14.7%
1 86
 
5.1%
해 81
 
4.8%
김 78
 
4.6%
상 78
 
4.6%
경 77
 
4.5%
남 77
 
4.5%
도 76
 
4.5%
시 76
 
4.5%
로 75
 
4.4%
Other values (85) 742
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1003
59.1%
Decimal Number 351
 
20.7%
Space Separator 250
 
14.7%
Dash Punctuation 27
 
1.6%
Open Punctuation 25
 
1.5%
Close Punctuation 25
 
1.5%
Other Punctuation 15
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 81
 
8.1%
김 78
 
7.8%
상 78
 
7.8%
경 77
 
7.7%
남 77
 
7.7%
도 76
 
7.6%
시 76
 
7.6%
로 75
 
7.5%
번 57
 
5.7%
길 56
 
5.6%
Other values (70) 272
27.1%
Decimal Number
ValueCountFrequency (%)
1 86
24.5%
2 53
15.1%
0 45
12.8%
3 36
10.3%
7 28
 
8.0%
4 27
 
7.7%
5 26
 
7.4%
8 19
 
5.4%
9 16
 
4.6%
6 15
 
4.3%
Space Separator
ValueCountFrequency (%)
250
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1003
59.1%
Common 693
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 81
 
8.1%
김 78
 
7.8%
상 78
 
7.8%
경 77
 
7.7%
남 77
 
7.7%
도 76
 
7.6%
시 76
 
7.6%
로 75
 
7.5%
번 57
 
5.7%
길 56
 
5.6%
Other values (70) 272
27.1%
Common
ValueCountFrequency (%)
250
36.1%
1 86
 
12.4%
2 53
 
7.6%
0 45
 
6.5%
3 36
 
5.2%
7 28
 
4.0%
- 27
 
3.9%
4 27
 
3.9%
5 26
 
3.8%
( 25
 
3.6%
Other values (5) 90
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1003
59.1%
ASCII 693
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
250
36.1%
1 86
 
12.4%
2 53
 
7.6%
0 45
 
6.5%
3 36
 
5.2%
7 28
 
4.0%
- 27
 
3.9%
4 27
 
3.9%
5 26
 
3.8%
( 25
 
3.6%
Other values (5) 90
 
13.0%
Hangul
ValueCountFrequency (%)
해 81
 
8.1%
김 78
 
7.8%
상 78
 
7.8%
경 77
 
7.7%
남 77
 
7.7%
도 76
 
7.6%
시 76
 
7.6%
로 75
 
7.5%
번 57
 
5.7%
길 56
 
5.6%
Other values (70) 272
27.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.231595
Minimum35.16943
Maximum35.308047
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-11T09:53:26.128917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.16943
5-th percentile35.17701
Q135.221037
median35.239826
Q335.247156
95-th percentile35.2633
Maximum35.308047
Range0.13861714
Interquartile range (IQR)0.026119122

Descriptive statistics

Standard deviation0.02946724
Coefficient of variation (CV)0.00083638678
Kurtosis0.23534271
Mean35.231595
Median Absolute Deviation (MAD)0.010220095
Skewness-0.38544939
Sum2677.6012
Variance0.00086831826
MonotonicityNot monotonic
2023-12-11T09:53:26.290449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.2455459 2
 
2.6%
35.24671789 2
 
2.6%
35.24759249 2
 
2.6%
35.25004659 2
 
2.6%
35.24679167 2
 
2.6%
35.24704424 2
 
2.6%
35.24635756 1
 
1.3%
35.20680603 1
 
1.3%
35.24654595 1
 
1.3%
35.24507742 1
 
1.3%
Other values (60) 60
78.9%
ValueCountFrequency (%)
35.16942963 1
1.3%
35.17585577 1
1.3%
35.17593669 1
1.3%
35.17659804 1
1.3%
35.17714675 1
1.3%
35.17717258 1
1.3%
35.17719254 1
1.3%
35.17948076 1
1.3%
35.185781 1
1.3%
35.18809288 1
1.3%
ValueCountFrequency (%)
35.30804677 1
1.3%
35.30730027 1
1.3%
35.26675699 1
1.3%
35.26388104 1
1.3%
35.26310676 1
1.3%
35.262848 1
1.3%
35.26124114 1
1.3%
35.26122585 1
1.3%
35.26018213 1
1.3%
35.25860628 1
1.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.86691
Minimum128.7272
Maximum128.92187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-11T09:53:26.455751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.7272
5-th percentile128.79611
Q1128.81964
median128.87581
Q3128.90438
95-th percentile128.91052
Maximum128.92187
Range0.1946649
Interquartile range (IQR)0.0847362

Descriptive statistics

Standard deviation0.045459461
Coefficient of variation (CV)0.00035276287
Kurtosis0.39152201
Mean128.86691
Median Absolute Deviation (MAD)0.02869305
Skewness-1.0648598
Sum9793.8853
Variance0.0020665626
MonotonicityNot monotonic
2023-12-11T09:53:26.626288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.9049839 2
 
2.6%
128.904504 2
 
2.6%
128.9045012 2
 
2.6%
128.9105557 2
 
2.6%
128.904269 2
 
2.6%
128.9045536 2
 
2.6%
128.9084559 1
 
1.3%
128.8198194 1
 
1.3%
128.9042717 1
 
1.3%
128.8753262 1
 
1.3%
Other values (60) 60
78.9%
ValueCountFrequency (%)
128.7272004 1
1.3%
128.7336635 1
1.3%
128.7939706 1
1.3%
128.7957439 1
1.3%
128.7962375 1
1.3%
128.7998232 1
1.3%
128.8005575 1
1.3%
128.8019871 1
1.3%
128.8020277 1
1.3%
128.8032411 1
1.3%
ValueCountFrequency (%)
128.9218653 1
1.3%
128.917816 1
1.3%
128.9105557 2
2.6%
128.9105134 1
1.3%
128.9084559 1
1.3%
128.9063403 1
1.3%
128.906284 1
1.3%
128.9061041 1
1.3%
128.9049839 2
2.6%
128.9046621 1
1.3%

대표품목
Text

Distinct73
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-11T09:53:26.846076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length29
Mean length21.276316
Min length2

Characters and Unicode

Total characters1617
Distinct characters198
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)92.1%

Sample

1st row정장3300원+와이셔츠1100원
2nd row정장3300원+와이셔츠1100원
3rd row목욕료(성인)4500원+목욕료(유아)2500원
4th row컷트(성인)5000원+컷트(학생)4000원
5th row파마(성인)30000원+컷트(성인)7000원
ValueCountFrequency (%)
정장3300원+와이셔츠1100원 2
 
2.3%
삼계탕 2
 
2.3%
자장면3000원+짬뽕4500원 2
 
2.3%
크림삼겹살스테이크 1
 
1.2%
자장면3000원+짬뽕4500원+밀면4500원 1
 
1.2%
자장면3000원+짬뽕4500원+탕수육7500원 1
 
1.2%
김밥2000원+떡볶이3000원+김치,된장찌개5500원 1
 
1.2%
한식뷔페5000원 1
 
1.2%
컷트(학생)5000원+펌(일반)30000원+염색15000원 1
 
1.2%
컷트(학생)5000원+컷트(일반)7000원+염색10000원 1
 
1.2%
Other values (73) 73
84.9%
2023-12-11T09:53:27.193345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 403
24.9%
원 141
 
8.7%
+ 79
 
4.9%
5 68
 
4.2%
1 35
 
2.2%
( 32
 
2.0%
) 32
 
2.0%
3 27
 
1.7%
장 25
 
1.5%
2 24
 
1.5%
Other values (188) 751
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 816
50.5%
Decimal Number 623
38.5%
Math Symbol 79
 
4.9%
Open Punctuation 32
 
2.0%
Close Punctuation 32
 
2.0%
Other Punctuation 13
 
0.8%
Lowercase Letter 11
 
0.7%
Space Separator 10
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 141
 
17.3%
장 25
 
3.1%
국 20
 
2.5%
면 18
 
2.2%
밥 16
 
2.0%
수 15
 
1.8%
자 15
 
1.8%
이 14
 
1.7%
뽕 12
 
1.5%
짬 12
 
1.5%
Other values (170) 528
64.7%
Decimal Number
ValueCountFrequency (%)
0 403
64.7%
5 68
 
10.9%
1 35
 
5.6%
3 27
 
4.3%
2 24
 
3.9%
4 19
 
3.0%
7 15
 
2.4%
6 13
 
2.1%
8 12
 
1.9%
9 7
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 12
92.3%
. 1
 
7.7%
Math Symbol
ValueCountFrequency (%)
+ 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 11
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 815
50.4%
Common 789
48.8%
Latin 12
 
0.7%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 141
 
17.3%
장 25
 
3.1%
국 20
 
2.5%
면 18
 
2.2%
밥 16
 
2.0%
수 15
 
1.8%
자 15
 
1.8%
이 14
 
1.7%
뽕 12
 
1.5%
짬 12
 
1.5%
Other values (169) 527
64.7%
Common
ValueCountFrequency (%)
0 403
51.1%
+ 79
 
10.0%
5 68
 
8.6%
1 35
 
4.4%
( 32
 
4.1%
) 32
 
4.1%
3 27
 
3.4%
2 24
 
3.0%
4 19
 
2.4%
7 15
 
1.9%
Other values (6) 55
 
7.0%
Latin
ValueCountFrequency (%)
g 11
91.7%
A 1
 
8.3%
Han
ValueCountFrequency (%)
小 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 815
50.4%
ASCII 801
49.5%
CJK 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 403
50.3%
+ 79
 
9.9%
5 68
 
8.5%
1 35
 
4.4%
( 32
 
4.0%
) 32
 
4.0%
3 27
 
3.4%
2 24
 
3.0%
4 19
 
2.4%
7 15
 
1.9%
Other values (8) 67
 
8.4%
Hangul
ValueCountFrequency (%)
원 141
 
17.3%
장 25
 
3.1%
국 20
 
2.5%
면 18
 
2.2%
밥 16
 
2.0%
수 15
 
1.8%
자 15
 
1.8%
이 14
 
1.7%
뽕 12
 
1.5%
짬 12
 
1.5%
Other values (169) 527
64.7%
CJK
ValueCountFrequency (%)
小 1
100.0%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
<NA>
66 
할인율 5%
10 

Length

Max length6
Median length4
Mean length4.2631579
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 66
86.8%
할인율 5% 10
 
13.2%

Length

2023-12-11T09:53:27.350131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:53:27.484191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 66
76.7%
할인율 10
 
11.6%
5 10
 
11.6%

Interactions

2023-12-11T09:53:21.826462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:53:21.529428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:53:21.938858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:53:21.686957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:53:27.608006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분업종상호전화번호지번주소도로명주소위도경도대표품목
구분1.0000.0001.0001.0001.0001.0000.3160.2401.000
업종0.0001.0001.0001.0000.9901.0000.0000.1251.000
상호1.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0000.9901.0001.0001.0001.0001.0001.0000.964
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0000.971
위도0.3160.0001.0001.0001.0001.0001.0000.8700.633
경도0.2400.1251.0001.0001.0001.0000.8701.0000.000
대표품목1.0001.0001.0001.0000.9640.9710.6330.0001.000
2023-12-11T09:53:27.772639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분업종비고
구분1.0000.0001.000
업종0.0001.0001.000
비고1.0001.0001.000
2023-12-11T09:53:27.851390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도구분업종비고
위도1.0000.4320.2990.0001.000
경도0.4321.0000.0710.0841.000
구분0.2990.0711.0000.0001.000
업종0.0000.0840.0001.0001.000
비고1.0001.0001.0001.0001.000

Missing values

2023-12-11T09:53:22.105665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:53:22.263500image/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

구분업종상호전화번호지번주소도로명주소위도경도대표품목비고
0착한가격업소세탁업하이크리닝055-328-4045경상남도 김해시 삼정동 608-1경상남도 김해시 활천로10번길 135.228704128.89445정장3300원+와이셔츠1100원<NA>
1착한가격업소세탁업미크리링삽055-333-3982경상남도 김해시 삼계동 1509-11경상남도 김해시 가야로 21235.258606128.87205정장3300원+와이셔츠1100원<NA>
2착한가격업소목욕업청수탕055-314-7518경상남도 김해시 대청동 72-3 풍림위너스빌딩경상남도 김해시 번화1로84번길 2435.195351128.801987목욕료(성인)4500원+목욕료(유아)2500원<NA>
3착한가격업소이미용업보이투맨055-311-4662경상남도 김해시 관동동 452-7 팔판마을4단지푸르지오아파트상가경상남도 김해시 계동로 1235.177147128.796237컷트(성인)5000원+컷트(학생)4000원<NA>
4착한가격업소이미용업다홍머리055-324-1919경상남도 김해시 내동 161-11경상남도 김해시 금관대로1297번길 235.240209128.861482파마(성인)30000원+컷트(성인)7000원<NA>
5착한가격업소이미용업민아헤어샾055-326-3040경상남도 김해시 부원동 63-17경상남도 김해시 호계로452번길 23-1735.230493128.88692파마(성인)20000원+컷트(성인)7000원<NA>
6착한가격업소음식업돈황055-314-1839경상남도 김해시 대청동 310-4경상남도 김해시 계동로 23035.19065128.803241자장면3000원+짬뽕4000원<NA>
7착한가격업소음식업짜장119055-313-3232경상남도 김해시 대청동 285-8경상남도 김해시 계동로 15735.188596128.795744자장면2000원+짬뽕4000원<NA>
8착한가격업소음식업천하통일055-333-3911경상남도 김해시 삼계동 1485-10경상남도 김해시 삼계중앙로 7935.261226128.873702자장면2500원+짬뽕4000원<NA>
9착한가격업소음식업황룡055-322-7892경상남도 김해시 내동 1145-2경상남도 김해시 내외로95번길 7, 106호35.235189128.867562자장면3000원+짬뽕4500원<NA>
구분업종상호전화번호지번주소도로명주소위도경도대표품목비고
6610인이상 할인업소음식업백두산삼계탕055-312-9492경상남도 김해시 삼문동 71-2경상남도 김해시 능동로7번길 7 (삼문동)35.1965128.793971삼계탕할인율 5%
6710인이상 할인업소음식업개성순대055-314-9292경상남도 김해시 대청동 1106-9경상남도 김해시 대청로104번길 82(대청동)35.188093128.806184순대전골, 모듬순대할인율 5%
6810인이상 할인업소음식업제왕갈비055-346-3392경상남도 김해시 진영읍 진영리 1622-4경상남도 김해시 진영읍 김해대로407번길 14-1235.3073128.733664모듬순대소, 돼지갈비할인율 5%
6910인이상 할인업소음식업생우림055-312-6880경상남도 김해시 삼정동 593-4경상남도 김해시 활천로36번길 34-8 (삼정동)35.232189128.89659한우할인율 5%
7010인이상 할인업소음식업밀양돼지국밥055-337-1790경상남도 김해시 어방동 1130-11경상남도 김해시 인제로 91 (어방동)35.236962128.904001돼지국밥 수육백반, 수육할인율 5%
7110인이상 할인업소음식업홍가낙지055-328-0264경상남도 김해시 어방동 1104-10경상남도 김해시 인제로51번길 4(어방동)35.233422128.904662산낙지볶음, 산낙지해물전골할인율 5%
7210인이상 할인업소음식업원조서울 녹각삼계탕055-322-4280경상남도 김해시 내동 489-3경상남도 김해시 금관대로1277번길 1-6(내동)35.238864128.859619삼계탕할인율 5%
7310인이상 할인업소음식업경포장 장어구이055-336-4742경상남도 김해시 불암동 229-34경상남도 김해시 식만로348번길 31-1(불암동)35.217923128.921865장어할인율 5%
7410인이상 할인업소음식업부부식당055-314-2366경상남도 김해시 대청동 330-11경상남도 김해시 반룡로4번길 11-15(대청동)35.185781128.799823김치찌개, 순두부찌개, 추어탕할인율 5%
7510인이상 할인업소음식업원투원(121)055-325-1211경상남도 김해시 관동동 1099-2경상남도 김해시 관동로 92, 1층(관동동)35.177173128.813406고르곤졸라피자, 까르보나라, 크림삼겹살스테이크, 나시고랭할인율 5%