Overview

Dataset statistics

Number of variables16
Number of observations69
Missing cells69
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory134.9 B

Variable types

Numeric3
Text4
Categorical2
Boolean6
Unsupported1

Dataset

Description대구 북구 전통시장 28개 중 하나인 칠성전자주방시장의 상점정보에 대한 csv 파일이다. 시장의 상점들의 주소, 상품권 사용 유무 등의 정보을 파악할 수 있다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15109915/fileData.do

Alerts

전통시장 상가번영회 가입유무 has constant value ""Constant
문화상품권 사용유무 has constant value ""Constant
전자상품권 사용유무 has constant value ""Constant
종업원 수 has constant value ""Constant
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도High correlation
온누리 상품권 사용유무 is highly overall correlated with 위도High correlation
상점업종분류 is highly imbalanced (89.1%)Imbalance
온누리 상품권 사용유무 is highly imbalanced (68.1%)Imbalance
택배서비스 유무 is highly imbalanced (52.6%)Imbalance
상점 홈페이지 주소 has 69 (100.0%) missing valuesMissing
상점코드 has unique valuesUnique
상점 홈페이지 주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 06:22:31.909098
Analysis finished2023-12-12 06:22:34.353106
Duration2.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상점코드
Real number (ℝ)

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35
Minimum1
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T15:22:34.453958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q118
median35
Q352
95-th percentile65.6
Maximum69
Range68
Interquartile range (IQR)34

Descriptive statistics

Standard deviation20.062403
Coefficient of variation (CV)0.5732115
Kurtosis-1.2
Mean35
Median Absolute Deviation (MAD)17
Skewness0
Sum2415
Variance402.5
MonotonicityStrictly increasing
2023-12-12T15:22:34.684834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
45 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
46 1
 
1.4%
44 1
 
1.4%
53 1
 
1.4%
Other values (59) 59
85.5%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%
60 1
1.4%

상점명
Text

Distinct68
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-12T15:22:34.984357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.6956522
Min length4

Characters and Unicode

Total characters393
Distinct characters122
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)97.1%

Sample

1st row가가식품기계
2nd row경남천막
3rd row경북에어컨
4th row골든주방
5th row국제냉동주방
ValueCountFrequency (%)
대경냉동 2
 
2.9%
가가식품기계 1
 
1.4%
신용전자 1
 
1.4%
신제일전자 1
 
1.4%
억조주방 1
 
1.4%
영광냉동주방 1
 
1.4%
영일전자 1
 
1.4%
재경주방 1
 
1.4%
오성카스테레오tv 1
 
1.4%
대경주방 1
 
1.4%
Other values (58) 58
84.1%
2023-12-12T15:22:35.384527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 24
 
6.1%
주 21
 
5.3%
방 20
 
5.1%
자 19
 
4.8%
동 18
 
4.6%
냉 17
 
4.3%
대 14
 
3.6%
합 14
 
3.6%
종 14
 
3.6%
성 11
 
2.8%
Other values (112) 221
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 390
99.2%
Uppercase Letter 2
 
0.5%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 24
 
6.2%
주 21
 
5.4%
방 20
 
5.1%
자 19
 
4.9%
동 18
 
4.6%
냉 17
 
4.4%
대 14
 
3.6%
합 14
 
3.6%
종 14
 
3.6%
성 11
 
2.8%
Other values (109) 218
55.9%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
V 1
50.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 390
99.2%
Latin 2
 
0.5%
Common 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 24
 
6.2%
주 21
 
5.4%
방 20
 
5.1%
자 19
 
4.9%
동 18
 
4.6%
냉 17
 
4.4%
대 14
 
3.6%
합 14
 
3.6%
종 14
 
3.6%
성 11
 
2.8%
Other values (109) 218
55.9%
Latin
ValueCountFrequency (%)
T 1
50.0%
V 1
50.0%
Common
ValueCountFrequency (%)
& 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 390
99.2%
ASCII 3
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 24
 
6.2%
주 21
 
5.4%
방 20
 
5.1%
자 19
 
4.9%
동 18
 
4.6%
냉 17
 
4.4%
대 14
 
3.6%
합 14
 
3.6%
종 14
 
3.6%
성 11
 
2.8%
Other values (109) 218
55.9%
ASCII
ValueCountFrequency (%)
T 1
33.3%
V 1
33.3%
& 1
33.3%

소재지 도로명 주소
Text

Distinct50
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-12T15:22:35.620444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length16.666667
Min length1

Characters and Unicode

Total characters1150
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)52.2%

Sample

1st row대구광역시 북구 칠성시장로 87-1
2nd row대구광역시 북구 공평로 180-1
3rd row대구광역시 북구 공평로 180-1
4th row대구광역시 북구 칠성시장로 67-7
5th row대구광역시 북구 칠성시장로 61-8
ValueCountFrequency (%)
대구광역시 67
24.7%
북구 67
24.7%
칠성시장로 31
11.4%
공평로 22
 
8.1%
칠성로 12
 
4.4%
168 4
 
1.5%
67 4
 
1.5%
115 3
 
1.1%
65 3
 
1.1%
180-1 3
 
1.1%
Other values (45) 55
20.3%
2023-12-12T15:22:36.013139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
17.6%
구 134
11.7%
시 99
 
8.6%
1 68
 
5.9%
대 67
 
5.8%
광 67
 
5.8%
역 67
 
5.8%
북 67
 
5.8%
로 67
 
5.8%
칠 45
 
3.9%
Other values (18) 267
23.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 737
64.1%
Space Separator 202
 
17.6%
Decimal Number 190
 
16.5%
Dash Punctuation 19
 
1.7%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 134
18.2%
시 99
13.4%
대 67
9.1%
광 67
9.1%
역 67
9.1%
북 67
9.1%
로 67
9.1%
칠 45
 
6.1%
성 45
 
6.1%
장 32
 
4.3%
Other values (4) 47
 
6.4%
Decimal Number
ValueCountFrequency (%)
1 68
35.8%
6 31
16.3%
7 20
 
10.5%
8 16
 
8.4%
5 12
 
6.3%
3 10
 
5.3%
4 9
 
4.7%
0 8
 
4.2%
9 8
 
4.2%
2 8
 
4.2%
Space Separator
ValueCountFrequency (%)
202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 737
64.1%
Common 413
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
202
48.9%
1 68
 
16.5%
6 31
 
7.5%
7 20
 
4.8%
- 19
 
4.6%
8 16
 
3.9%
5 12
 
2.9%
3 10
 
2.4%
4 9
 
2.2%
0 8
 
1.9%
Other values (4) 18
 
4.4%
Hangul
ValueCountFrequency (%)
구 134
18.2%
시 99
13.4%
대 67
9.1%
광 67
9.1%
역 67
9.1%
북 67
9.1%
로 67
9.1%
칠 45
 
6.1%
성 45
 
6.1%
장 32
 
4.3%
Other values (4) 47
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 737
64.1%
ASCII 413
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
48.9%
1 68
 
16.5%
6 31
 
7.5%
7 20
 
4.8%
- 19
 
4.6%
8 16
 
3.9%
5 12
 
2.9%
3 10
 
2.4%
4 9
 
2.2%
0 8
 
1.9%
Other values (4) 18
 
4.4%
Hangul
ValueCountFrequency (%)
구 134
18.2%
시 99
13.4%
대 67
9.1%
광 67
9.1%
역 67
9.1%
북 67
9.1%
로 67
9.1%
칠 45
 
6.1%
성 45
 
6.1%
장 32
 
4.3%
Other values (4) 47
 
6.4%

소재지 지번주소
Text

Distinct52
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-12T15:22:36.265393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.507246
Min length19

Characters and Unicode

Total characters1484
Distinct characters22
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

Unique40 ?
Unique (%)58.0%

Sample

1st row대구광역시 북구 칠성동2가 403-10
2nd row대구광역시 북구 칠성동2가 409-37
3rd row대구광역시 북구 칠성동2가 409-37
4th row대구광역시 북구 칠성동2가 409-664
5th row대구광역시 북구 칠성동2가 408-11
ValueCountFrequency (%)
대구광역시 69
25.0%
북구 69
25.0%
칠성동2가 66
23.9%
409-152 4
 
1.4%
409-707 3
 
1.1%
409-37 3
 
1.1%
409-270 3
 
1.1%
409-39 3
 
1.1%
칠성동1가 3
 
1.1%
409-638 2
 
0.7%
Other values (44) 51
18.5%
2023-12-12T15:22:36.677968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
 
14.0%
구 138
 
9.3%
2 86
 
5.8%
0 82
 
5.5%
4 78
 
5.3%
9 71
 
4.8%
대 69
 
4.6%
동 69
 
4.6%
- 69
 
4.6%
가 69
 
4.6%
Other values (12) 545
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 759
51.1%
Decimal Number 448
30.2%
Space Separator 208
 
14.0%
Dash Punctuation 69
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 138
18.2%
대 69
9.1%
동 69
9.1%
가 69
9.1%
성 69
9.1%
칠 69
9.1%
북 69
9.1%
시 69
9.1%
역 69
9.1%
광 69
9.1%
Decimal Number
ValueCountFrequency (%)
2 86
19.2%
0 82
18.3%
4 78
17.4%
9 71
15.8%
7 29
 
6.5%
1 24
 
5.4%
5 23
 
5.1%
3 22
 
4.9%
6 22
 
4.9%
8 11
 
2.5%
Space Separator
ValueCountFrequency (%)
208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 759
51.1%
Common 725
48.9%

Most frequent character per script

Common
ValueCountFrequency (%)
208
28.7%
2 86
11.9%
0 82
 
11.3%
4 78
 
10.8%
9 71
 
9.8%
- 69
 
9.5%
7 29
 
4.0%
1 24
 
3.3%
5 23
 
3.2%
3 22
 
3.0%
Other values (2) 33
 
4.6%
Hangul
ValueCountFrequency (%)
구 138
18.2%
대 69
9.1%
동 69
9.1%
가 69
9.1%
성 69
9.1%
칠 69
9.1%
북 69
9.1%
시 69
9.1%
역 69
9.1%
광 69
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 759
51.1%
ASCII 725
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
28.7%
2 86
11.9%
0 82
 
11.3%
4 78
 
10.8%
9 71
 
9.8%
- 69
 
9.5%
7 29
 
4.0%
1 24
 
3.3%
5 23
 
3.2%
3 22
 
3.0%
Other values (2) 33
 
4.6%
Hangul
ValueCountFrequency (%)
구 138
18.2%
대 69
9.1%
동 69
9.1%
가 69
9.1%
성 69
9.1%
칠 69
9.1%
북 69
9.1%
시 69
9.1%
역 69
9.1%
광 69
9.1%

상점업종분류
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
기타
68 
음식점
 
1

Length

Max length3
Median length2
Mean length2.0144928
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
기타 68
98.6%
음식점 1
 
1.4%

Length

2023-12-12T15:22:36.831895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:22:36.951395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 68
98.6%
음식점 1
 
1.4%

대표품목
Text

Distinct58
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-12T15:22:37.146585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length8.5797101
Min length2

Characters and Unicode

Total characters592
Distinct characters71
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)79.7%

Sample

1st row전자용품
2nd row천막제작
3rd row에어컨 판매
4th row전자용품(주방제품 판매수리)
5th row전자제품 판매 수리
ValueCountFrequency (%)
판매 18
 
12.5%
수리 17
 
11.8%
전자용품 15
 
10.4%
판매수리 11
 
7.6%
냉장고 6
 
4.2%
전자제품 5
 
3.5%
그릇 4
 
2.8%
및 4
 
2.8%
에어컨 4
 
2.8%
업소용 4
 
2.8%
Other values (45) 56
38.9%
2023-12-12T15:22:37.554624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
12.7%
매 42
 
7.1%
판 40
 
6.8%
수 38
 
6.4%
리 38
 
6.4%
전 37
 
6.2%
품 35
 
5.9%
용 33
 
5.6%
자 33
 
5.6%
기 19
 
3.2%
Other values (61) 202
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
80.9%
Space Separator 75
 
12.7%
Other Punctuation 20
 
3.4%
Close Punctuation 6
 
1.0%
Open Punctuation 6
 
1.0%
Uppercase Letter 6
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
매 42
 
8.8%
판 40
 
8.4%
수 38
 
7.9%
리 38
 
7.9%
전 37
 
7.7%
품 35
 
7.3%
용 33
 
6.9%
자 33
 
6.9%
기 19
 
4.0%
제 12
 
2.5%
Other values (54) 152
31.7%
Other Punctuation
ValueCountFrequency (%)
, 15
75.0%
. 5
 
25.0%
Uppercase Letter
ValueCountFrequency (%)
V 3
50.0%
T 3
50.0%
Space Separator
ValueCountFrequency (%)
75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
80.9%
Common 107
 
18.1%
Latin 6
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
매 42
 
8.8%
판 40
 
8.4%
수 38
 
7.9%
리 38
 
7.9%
전 37
 
7.7%
품 35
 
7.3%
용 33
 
6.9%
자 33
 
6.9%
기 19
 
4.0%
제 12
 
2.5%
Other values (54) 152
31.7%
Common
ValueCountFrequency (%)
75
70.1%
, 15
 
14.0%
) 6
 
5.6%
( 6
 
5.6%
. 5
 
4.7%
Latin
ValueCountFrequency (%)
V 3
50.0%
T 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
80.9%
ASCII 113
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
66.4%
, 15
 
13.3%
) 6
 
5.3%
( 6
 
5.3%
. 5
 
4.4%
V 3
 
2.7%
T 3
 
2.7%
Hangul
ValueCountFrequency (%)
매 42
 
8.8%
판 40
 
8.4%
수 38
 
7.9%
리 38
 
7.9%
전 37
 
7.7%
품 35
 
7.3%
용 33
 
6.9%
자 33
 
6.9%
기 19
 
4.0%
제 12
 
2.5%
Other values (54) 152
31.7%

전통시장 상가번영회 가입유무
Boolean

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size201.0 B
True
69 
ValueCountFrequency (%)
True 69
100.0%
2023-12-12T15:22:37.697231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

온누리 상품권 사용유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size201.0 B
True
65 
False
 
4
ValueCountFrequency (%)
True 65
94.2%
False 4
 
5.8%
2023-12-12T15:22:37.810770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

문화상품권 사용유무
Boolean

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size201.0 B
False
69 
ValueCountFrequency (%)
False 69
100.0%
2023-12-12T15:22:37.905697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전자상품권 사용유무
Boolean

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size201.0 B
False
69 
ValueCountFrequency (%)
False 69
100.0%
2023-12-12T15:22:37.994333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

카드단말기 유무
Boolean

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size201.0 B
True
58 
False
11 
ValueCountFrequency (%)
True 58
84.1%
False 11
 
15.9%
2023-12-12T15:22:38.088080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

택배서비스 유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size201.0 B
True
62 
False
7 
ValueCountFrequency (%)
True 62
89.9%
False 7
 
10.1%
2023-12-12T15:22:38.177215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

종업원 수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
1
69 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 69
100.0%

Length

2023-12-12T15:22:38.301836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:22:38.426187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 69
100.0%

상점 홈페이지 주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing69
Missing (%)100.0%
Memory size753.0 B

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.879342
Minimum35.874693
Maximum35.883381
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T15:22:38.549360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.874693
5-th percentile35.878236
Q135.878666
median35.879336
Q335.879906
95-th percentile35.881639
Maximum35.883381
Range0.008688
Interquartile range (IQR)0.00124

Descriptive statistics

Standard deviation0.0013154284
Coefficient of variation (CV)3.6662557 × 10-5
Kurtosis3.6637161
Mean35.879342
Median Absolute Deviation (MAD)0.000648
Skewness-0.33581143
Sum2475.6746
Variance1.730352 × 10-6
MonotonicityNot monotonic
2023-12-12T15:22:38.707344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.879019 4
 
5.8%
35.878467 3
 
4.3%
35.880111 3
 
4.3%
35.879628 3
 
4.3%
35.879309 2
 
2.9%
35.878236 2
 
2.9%
35.879984 2
 
2.9%
35.875809 2
 
2.9%
35.879647 2
 
2.9%
35.879524 2
 
2.9%
Other values (41) 44
63.8%
ValueCountFrequency (%)
35.874693 1
 
1.4%
35.875809 2
2.9%
35.878236 2
2.9%
35.878276 1
 
1.4%
35.878294 1
 
1.4%
35.878313 1
 
1.4%
35.878339 1
 
1.4%
35.878392 1
 
1.4%
35.878394 1
 
1.4%
35.878467 3
4.3%
ValueCountFrequency (%)
35.883381 1
1.4%
35.882396 1
1.4%
35.881923 1
1.4%
35.881711 1
1.4%
35.881532 1
1.4%
35.881402 1
1.4%
35.88042 1
1.4%
35.88033 2
2.9%
35.880228 1
1.4%
35.880206 1
1.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.60144
Minimum128.59056
Maximum128.60493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T15:22:38.850227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.59056
5-th percentile128.59824
Q1128.60139
median128.60156
Q3128.60214
95-th percentile128.60278
Maximum128.60493
Range0.014365
Interquartile range (IQR)0.000749

Descriptive statistics

Standard deviation0.0019822708
Coefficient of variation (CV)1.5414064 × 10-5
Kurtosis15.018297
Mean128.60144
Median Absolute Deviation (MAD)0.000318
Skewness-3.24216
Sum8873.4991
Variance3.9293975 × 10-6
MonotonicityNot monotonic
2023-12-12T15:22:39.026125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.601394 4
 
5.8%
128.601875 3
 
4.3%
128.60139 3
 
4.3%
128.601933 3
 
4.3%
128.602139 2
 
2.9%
128.602781 2
 
2.9%
128.601369 2
 
2.9%
128.604875 2
 
2.9%
128.601296 2
 
2.9%
128.602019 2
 
2.9%
Other values (41) 44
63.8%
ValueCountFrequency (%)
128.590563 1
1.4%
128.594936 1
1.4%
128.596245 1
1.4%
128.596686 1
1.4%
128.600564 1
1.4%
128.600709 1
1.4%
128.600803 1
1.4%
128.600806 1
1.4%
128.600856 1
1.4%
128.600905 1
1.4%
ValueCountFrequency (%)
128.604928 1
1.4%
128.604875 2
2.9%
128.602781 2
2.9%
128.602701 1
1.4%
128.602609 1
1.4%
128.602535 1
1.4%
128.602512 1
1.4%
128.602451 1
1.4%
128.602442 1
1.4%
128.602346 1
1.4%

Interactions

2023-12-12T15:22:33.324117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:22:32.704658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:22:33.038566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:22:33.447054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:22:32.810478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:22:33.131669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:22:33.534422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:22:32.923254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:22:33.220486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:22:39.176003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상점코드상점명소재지 도로명 주소소재지 지번주소상점업종분류대표품목온누리 상품권 사용유무카드단말기 유무택배서비스 유무위도경도
상점코드1.0001.0000.7260.6390.0000.1550.0000.0000.0000.0000.086
상점명1.0001.0001.0001.0001.0000.9891.0001.0001.0001.0001.000
소재지 도로명 주소0.7261.0001.0000.9991.0000.9901.0000.0890.7331.0001.000
소재지 지번주소0.6391.0000.9991.0001.0000.9831.0000.4000.8981.0001.000
상점업종분류0.0001.0001.0001.0001.0001.0000.0000.0000.0000.0000.000
대표품목0.1550.9890.9900.9831.0001.0001.0001.0001.0000.9910.994
온누리 상품권 사용유무0.0001.0001.0001.0000.0001.0001.0000.1310.6080.7880.000
카드단말기 유무0.0001.0000.0890.4000.0001.0000.1311.0000.2130.0000.382
택배서비스 유무0.0001.0000.7330.8980.0001.0000.6080.2131.0000.6170.532
위도0.0001.0001.0001.0000.0000.9910.7880.0000.6171.0000.807
경도0.0861.0001.0001.0000.0000.9940.0000.3820.5320.8071.000
2023-12-12T15:22:39.313596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
택배서비스 유무온누리 상품권 사용유무상점업종분류카드단말기 유무
택배서비스 유무1.0000.4160.0000.136
온누리 상품권 사용유무0.4161.0000.0000.082
상점업종분류0.0000.0001.0000.000
카드단말기 유무0.1360.0820.0001.000
2023-12-12T15:22:39.478428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상점코드위도경도상점업종분류온누리 상품권 사용유무카드단말기 유무택배서비스 유무
상점코드1.000-0.2620.1720.0000.0000.0000.000
위도-0.2621.000-0.6710.0000.5810.0000.445
경도0.172-0.6711.0000.0000.4120.3520.478
상점업종분류0.0000.0000.0001.0000.0000.0000.000
온누리 상품권 사용유무0.0000.5810.4120.0001.0000.0820.416
카드단말기 유무0.0000.0000.3520.0000.0821.0000.136
택배서비스 유무0.0000.4450.4780.0000.4160.1361.000

Missing values

2023-12-12T15:22:33.699701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:22:34.248298image/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

상점코드상점명소재지 도로명 주소소재지 지번주소상점업종분류대표품목전통시장 상가번영회 가입유무온누리 상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무종업원 수상점 홈페이지 주소위도경도
01가가식품기계대구광역시 북구 칠성시장로 87-1대구광역시 북구 칠성동2가 403-10기타전자용품YNNNYN1<NA>35.881532128.600856
12경남천막대구광역시 북구 공평로 180-1대구광역시 북구 칠성동2가 409-37기타천막제작YYNNYY1<NA>35.880111128.60139
23경북에어컨대구광역시 북구 공평로 180-1대구광역시 북구 칠성동2가 409-37기타에어컨 판매YYNNYN1<NA>35.880111128.60139
34골든주방대구광역시 북구 칠성시장로 67-7대구광역시 북구 칠성동2가 409-664기타전자용품(주방제품 판매수리)YYNNYY1<NA>35.879837128.601488
45국제냉동주방대구광역시 북구 칠성시장로 61-8대구광역시 북구 칠성동2가 408-11기타전자제품 판매 수리YYNNYY1<NA>35.879336128.601874
56그린종합가전대구광역시 북구 공평로 166대구광역시 북구 칠성동2가 409-17기타전자용품 판매수리YYNNYY1<NA>35.878887128.601425
67나눔인테리어가구대구광역시 북구 칠성시장로 65대구광역시 북구 칠성동2가 408-6기타가구판매YYNNYY1<NA>35.879524128.602019
78달구벌전자대구광역시 북구 공평로 168대구광역시 북구 칠성동2가 409-152기타전자용품 판매수리YYNNYY1<NA>35.879019128.601394
89대경냉동대구광역시 북구 칠성시장로 67대구광역시 북구 칠성동2가 409-707기타업소용 냉장고YYNNYY1<NA>35.879628128.601933
910대경냉동대구광역시 북구 칠성시장로 67대구광역시 북구 칠성동2가 409-707기타냉장고 판매YYNNYY1<NA>35.879628128.601933
상점코드상점명소재지 도로명 주소소재지 지번주소상점업종분류대표품목전통시장 상가번영회 가입유무온누리 상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무종업원 수상점 홈페이지 주소위도경도
5960제일가구대구광역시 북구 칠성로 115대구광역시 북구 칠성동2가 409-270기타탁자,의자YYNNYY1<NA>35.878467128.601875
6061태양전자대구광역시 북구 칠성시장로 67대구광역시 북구 칠성동2가 409-707기타전자용품 수리YYNNNY1<NA>35.879628128.601933
6162토탈가전냉동대구광역시 북구 공평로 164대구광역시 북구 칠성동2가 409-374기타전자용품 판매수리YYNNYY1<NA>35.878666128.601525
6263푸른주방대구광역시 북구 칠성시장로11길 3대구광역시 북구 칠성동2가 409-519기타판매 수리YYNNYY1<NA>35.878743128.602442
6364하나전자대구광역시 북구 칠성시장로 61-11대구광역시 북구 칠성동2가 409-539기타TV수리판매전문YNNNNN1<NA>35.879239128.601693
6465한국종합전자랜드대구광역시 북구 공평로 166대구광역시 북구 칠성동2가 409-17기타전자용품 판매 및 수리YYNNYY1<NA>35.878887128.601425
6566한라전기전자대구광역시 북구 칠성시장로 69-1대구광역시 북구 칠성동2가 409-660기타TV,가전YYNNYY1<NA>35.879906128.601714
6667한빛주방냉동대구광역시 북구 칠성시장로 63대구광역시 북구 칠성동2가 408-9기타전자제품 판매 수리YYNNYY1<NA>35.879309128.602139
6768현대식품기계냉동대구광역시 북구 칠성시장로 61-1대구광역시 북구 칠성동2가 409-52기타업소용 주방용품YYNNYY1<NA>35.878394128.600709
6869현대주방냉동대구광역시 북구 칠성시장로 61대구광역시 북구 칠성동2가 409-522기타전자용품 판매 수리YYNNYY1<NA>35.879124128.602247