Overview

Dataset statistics

Number of variables19
Number of observations144
Missing cells144
Missing cells (%)5.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.1 KiB
Average record size in memory156.9 B

Variable types

Numeric4
Text3
Categorical4
Boolean8

Dataset

Description대구 달서구 전통시장 중 하나인 서남신시장의 상점정보에 대한 csv 파일이다. 시장의 상점들의 주소, 상품권 사용 유무 등의 정보을 파악할 수 있다.
Author대구광역시 달서구
URLhttps://www.data.go.kr/data/15109971/fileData.do

Alerts

빈점포 유무 has constant value ""Constant
도로명주소 is highly overall correlated with 경도 and 4 other fieldsHigh correlation
지번주소 is highly overall correlated with 경도 and 4 other fieldsHigh correlation
상점코드 is highly overall correlated with 상가번영회 가입 유무 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 도로명주소 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 도로명주소 and 1 other fieldsHigh correlation
상가번영회 가입 유무 is highly overall correlated with 상점코드 and 1 other fieldsHigh correlation
온누리상품권 사용유무 is highly overall correlated with 상점코드 and 1 other fieldsHigh correlation
문화상품권 사용유무 is highly overall correlated with 도로명주소 and 1 other fieldsHigh correlation
전자상품권 사용유무 is highly overall correlated with 카드단말기 유무High correlation
카드단말기 유무 is highly overall correlated with 전자상품권 사용유무High correlation
구역 내외 유무 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
상가번영회 가입 유무 is highly imbalanced (61.1%)Imbalance
문화상품권 사용유무 is highly imbalanced (94.0%)Imbalance
구역 내외 유무 is highly imbalanced (78.2%)Imbalance
대표품목 has 7 (4.9%) missing valuesMissing
홈페이지 주소 has 137 (95.1%) missing valuesMissing
상점코드 has unique valuesUnique
상점명 has unique valuesUnique
종업원 수 has 2 (1.4%) zerosZeros

Reproduction

Analysis started2023-12-12 12:41:06.570136
Analysis finished2023-12-12 12:41:10.923448
Duration4.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상점코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.777778
Minimum1
Maximum157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T21:41:11.012757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.15
Q136.75
median76
Q3119.25
95-th percentile148.85
Maximum157
Range156
Interquartile range (IQR)82.5

Descriptive statistics

Standard deviation46.430856
Coefficient of variation (CV)0.59696815
Kurtosis-1.2715812
Mean77.777778
Median Absolute Deviation (MAD)41
Skewness0.032849476
Sum11200
Variance2155.8244
MonotonicityStrictly increasing
2023-12-12T21:41:11.205200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
78 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
106 1
 
0.7%
107 1
 
0.7%
108 1
 
0.7%
109 1
 
0.7%
111 1
 
0.7%
Other values (134) 134
93.1%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
157 1
0.7%
155 1
0.7%
154 1
0.7%
153 1
0.7%
152 1
0.7%
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%

상점명
Text

UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T21:41:11.562728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.6041667
Min length2

Characters and Unicode

Total characters807
Distinct characters256
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)100.0%

Sample

1st row1번지야채
2nd rowBYC서남점
3rd row가야떡집
4th row계영제과
5th row고령농산물
ValueCountFrequency (%)
try 2
 
1.3%
오뚜기튀김 2
 
1.3%
1번지야채 1
 
0.6%
주원김밥 1
 
0.6%
이불랜드 1
 
0.6%
이현국(의류 1
 
0.6%
인동상회 1
 
0.6%
일월산 1
 
0.6%
웰빙반찬 1
 
0.6%
장수떡집 1
 
0.6%
Other values (144) 144
92.3%
2023-12-12T21:41:12.057374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 24
 
3.0%
남 23
 
2.9%
이 19
 
2.4%
식 17
 
2.1%
( 17
 
2.1%
) 17
 
2.1%
산 16
 
2.0%
동 13
 
1.6%
점 13
 
1.6%
품 12
 
1.5%
Other values (246) 636
78.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 731
90.6%
Uppercase Letter 24
 
3.0%
Open Punctuation 17
 
2.1%
Close Punctuation 17
 
2.1%
Space Separator 12
 
1.5%
Decimal Number 4
 
0.5%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 24
 
3.3%
남 23
 
3.1%
이 19
 
2.6%
식 17
 
2.3%
산 16
 
2.2%
동 13
 
1.8%
점 13
 
1.8%
품 12
 
1.6%
떡 11
 
1.5%
주 11
 
1.5%
Other values (226) 572
78.2%
Uppercase Letter
ValueCountFrequency (%)
A 4
16.7%
R 3
12.5%
T 3
12.5%
Y 3
12.5%
I 2
8.3%
M 2
8.3%
S 2
8.3%
U 1
 
4.2%
H 1
 
4.2%
C 1
 
4.2%
Other values (2) 2
8.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
4 1
25.0%
1 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 731
90.6%
Common 52
 
6.4%
Latin 24
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 24
 
3.3%
남 23
 
3.1%
이 19
 
2.6%
식 17
 
2.3%
산 16
 
2.2%
동 13
 
1.8%
점 13
 
1.8%
품 12
 
1.6%
떡 11
 
1.5%
주 11
 
1.5%
Other values (226) 572
78.2%
Latin
ValueCountFrequency (%)
A 4
16.7%
R 3
12.5%
T 3
12.5%
Y 3
12.5%
I 2
8.3%
M 2
8.3%
S 2
8.3%
U 1
 
4.2%
H 1
 
4.2%
C 1
 
4.2%
Other values (2) 2
8.3%
Common
ValueCountFrequency (%)
( 17
32.7%
) 17
32.7%
12
23.1%
2 2
 
3.8%
4 1
 
1.9%
1 1
 
1.9%
, 1
 
1.9%
. 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 731
90.6%
ASCII 76
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 24
 
3.3%
남 23
 
3.1%
이 19
 
2.6%
식 17
 
2.3%
산 16
 
2.2%
동 13
 
1.8%
점 13
 
1.8%
품 12
 
1.6%
떡 11
 
1.5%
주 11
 
1.5%
Other values (226) 572
78.2%
ASCII
ValueCountFrequency (%)
( 17
22.4%
) 17
22.4%
12
15.8%
A 4
 
5.3%
R 3
 
3.9%
T 3
 
3.9%
Y 3
 
3.9%
I 2
 
2.6%
M 2
 
2.6%
S 2
 
2.6%
Other values (10) 11
14.5%

도로명주소
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
대구광역시 달서구 달구벌대로 1651
13 
대구광역시 달서구 달구벌대로329길 10
13 
대구광역시 달서구 달구벌대로 1651-3
12 
대구광역시 달서구 달구벌대로329길 13
 
7
대구광역시 달서구 달구벌대로329길 32
 
6
Other values (29)
93 

Length

Max length23
Median length23
Mean length21.854167
Min length18

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row대구광역시 달서구 당산로41길 51
2nd row대구광역시 달서구 달구벌대로329길 25
3rd row대구광역시 달서구 당산로41길 53
4th row대구광역시 달서구 달구벌대로 1641
5th row대구광역시 달서구 죽전4길 96

Common Values

ValueCountFrequency (%)
대구광역시 달서구 달구벌대로 1651 13
 
9.0%
대구광역시 달서구 달구벌대로329길 10 13
 
9.0%
대구광역시 달서구 달구벌대로 1651-3 12
 
8.3%
대구광역시 달서구 달구벌대로329길 13 7
 
4.9%
대구광역시 달서구 달구벌대로329길 32 6
 
4.2%
대구광역시 달서구 당산로41길 32 5
 
3.5%
대구광역시 달서구 달구벌대로329길 35 4
 
2.8%
대구광역시 달서구 달구벌대로 1641 4
 
2.8%
대구광역시 달서구 달구벌대로329길 26 4
 
2.8%
대구광역시 달서구 달구벌대로329길 7 4
 
2.8%
Other values (24) 72
50.0%

Length

2023-12-12T21:41:12.227911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대구광역시 144
25.1%
달서구 144
25.1%
달구벌대로329길 71
12.4%
달구벌대로 37
 
6.4%
당산로41길 29
 
5.1%
1651 13
 
2.3%
10 13
 
2.3%
1651-3 13
 
2.3%
32 11
 
1.9%
35 8
 
1.4%
Other values (26) 91
15.9%

지번주소
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
대구광역시 달서구 감삼동 62-3 (1층)
14 
대구광역시 달서구 감삼동 62-4 (1층)
13 
대구광역시 달서구 감삼동 61-1 (1층)
12 
대구광역시 달서구 감삼동 63-5 (1층)
 
7
대구광역시 달서구 감삼동 56-18 (1층)
 
6
Other values (32)
92 

Length

Max length26
Median length23
Mean length23.319444
Min length20

Unique

Unique7 ?
Unique (%)4.9%

Sample

1st row대구광역시 달서구 감삼동 63-19 (1층)
2nd row대구광역시 달서구 감삼동 55-16 (1층)
3rd row대구광역시 달서구 감삼동 63-18 (1층)
4th row대구광역시 달서구 감삼동 64-13 (1층)
5th row대구광역시 달서구 감삼동 56-1 (1층)

Common Values

ValueCountFrequency (%)
대구광역시 달서구 감삼동 62-3 (1층) 14
 
9.7%
대구광역시 달서구 감삼동 62-4 (1층) 13
 
9.0%
대구광역시 달서구 감삼동 61-1 (1층) 12
 
8.3%
대구광역시 달서구 감삼동 63-5 (1층) 7
 
4.9%
대구광역시 달서구 감삼동 56-18 (1층) 6
 
4.2%
대구광역시 달서구 감삼동 62-1 (1층) 5
 
3.5%
대구광역시 달서구 감삼동 57-23 (1층) 5
 
3.5%
대구광역시 달서구 감삼동 55-9 (1층) 4
 
2.8%
대구광역시 달서구 감삼동 64-13 (1층) 4
 
2.8%
대구광역시 달서구 감삼동 56-3 (1층) 4
 
2.8%
Other values (27) 70
48.6%

Length

2023-12-12T21:41:12.384601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대구광역시 144
20.0%
감삼동 144
20.0%
달서구 144
20.0%
1층 140
19.4%
62-3 15
 
2.1%
62-4 13
 
1.8%
61-1 13
 
1.8%
62-1 8
 
1.1%
63-5 7
 
1.0%
56-18 6
 
0.8%
Other values (29) 86
11.9%

업종분류
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
쇼핑시설
74 
음식점
54 
기타
16 

Length

Max length4
Median length4
Mean length3.4027778
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row쇼핑시설
2nd row쇼핑시설
3rd row음식점
4th row음식점
5th row쇼핑시설

Common Values

ValueCountFrequency (%)
쇼핑시설 74
51.4%
음식점 54
37.5%
기타 16
 
11.1%

Length

2023-12-12T21:41:12.547103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:12.698612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
쇼핑시설 74
51.4%
음식점 54
37.5%
기타 16
 
11.1%

대표품목
Text

MISSING 

Distinct71
Distinct (%)51.8%
Missing7
Missing (%)4.9%
Memory size1.3 KiB
2023-12-12T21:41:12.954573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1751825
Min length1

Characters and Unicode

Total characters298
Distinct characters108
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)33.6%

Sample

1st row야채
2nd row옷
3rd row떡
4th row제과
5th row농산물
ValueCountFrequency (%)
옷 12
 
8.7%
화장품 7
 
5.1%
떡 6
 
4.3%
육류 6
 
4.3%
반찬 6
 
4.3%
족발 4
 
2.9%
두부 4
 
2.9%
야채 4
 
2.9%
과일 4
 
2.9%
건어물 4
 
2.9%
Other values (61) 81
58.7%
2023-12-12T21:41:13.407593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
옷 12
 
4.0%
화 12
 
4.0%
떡 10
 
3.4%
품 10
 
3.4%
물 9
 
3.0%
장 7
 
2.3%
육 7
 
2.3%
식 7
 
2.3%
산 6
 
2.0%
발 6
 
2.0%
Other values (98) 212
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 297
99.7%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옷 12
 
4.0%
화 12
 
4.0%
떡 10
 
3.4%
품 10
 
3.4%
물 9
 
3.0%
장 7
 
2.4%
육 7
 
2.4%
식 7
 
2.4%
산 6
 
2.0%
발 6
 
2.0%
Other values (97) 211
71.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 297
99.7%
Common 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옷 12
 
4.0%
화 12
 
4.0%
떡 10
 
3.4%
품 10
 
3.4%
물 9
 
3.0%
장 7
 
2.4%
육 7
 
2.4%
식 7
 
2.4%
산 6
 
2.0%
발 6
 
2.0%
Other values (97) 211
71.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 297
99.7%
ASCII 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
옷 12
 
4.0%
화 12
 
4.0%
떡 10
 
3.4%
품 10
 
3.4%
물 9
 
3.0%
장 7
 
2.4%
육 7
 
2.4%
식 7
 
2.4%
산 6
 
2.0%
발 6
 
2.0%
Other values (97) 211
71.0%
ASCII
ValueCountFrequency (%)
1
100.0%

상가번영회 가입 유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size276.0 B
True
133 
False
 
11
ValueCountFrequency (%)
True 133
92.4%
False 11
 
7.6%
2023-12-12T21:41:13.536258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

온누리상품권 사용유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size276.0 B
True
126 
False
18 
ValueCountFrequency (%)
True 126
87.5%
False 18
 
12.5%
2023-12-12T21:41:13.646122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

문화상품권 사용유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size276.0 B
False
143 
True
 
1
ValueCountFrequency (%)
False 143
99.3%
True 1
 
0.7%
2023-12-12T21:41:13.761124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전자상품권 사용유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size276.0 B
True
92 
False
52 
ValueCountFrequency (%)
True 92
63.9%
False 52
36.1%
2023-12-12T21:41:13.879386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

카드단말기 유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size276.0 B
True
112 
False
32 
ValueCountFrequency (%)
True 112
77.8%
False 32
 
22.2%
2023-12-12T21:41:13.987444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

택배서비스 유무
Boolean

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size276.0 B
False
122 
True
22 
ValueCountFrequency (%)
False 122
84.7%
True 22
 
15.3%
2023-12-12T21:41:14.081750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

매출규모
Categorical

Distinct6
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0~3000만원/년
79 
3000~5000만원/년
38 
5000~1억/년
14 
1억~3억/년
 
6
<NA>
 
4

Length

Max length13
Median length10
Mean length10.340278
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000~5000만원/년
2nd row5000~1억/년
3rd row3000~5000만원/년
4th row3000~5000만원/년
5th row3000~5000만원/년

Common Values

ValueCountFrequency (%)
0~3000만원/년 79
54.9%
3000~5000만원/년 38
26.4%
5000~1억/년 14
 
9.7%
1억~3억/년 6
 
4.2%
<NA> 4
 
2.8%
3억~5억/년 3
 
2.1%

Length

2023-12-12T21:41:14.198163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:14.316391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0~3000만원/년 79
54.9%
3000~5000만원/년 38
26.4%
5000~1억/년 14
 
9.7%
1억~3억/년 6
 
4.2%
na 4
 
2.8%
3억~5억/년 3
 
2.1%

종업원 수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3263889
Minimum0
Maximum6
Zeros2
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T21:41:14.432209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.78294639
Coefficient of variation (CV)0.59028419
Kurtosis10.464105
Mean1.3263889
Median Absolute Deviation (MAD)0
Skewness2.8097025
Sum191
Variance0.61300505
MonotonicityNot monotonic
2023-12-12T21:41:14.548548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 110
76.4%
2 21
 
14.6%
3 7
 
4.9%
4 3
 
2.1%
0 2
 
1.4%
6 1
 
0.7%
ValueCountFrequency (%)
0 2
 
1.4%
1 110
76.4%
2 21
 
14.6%
3 7
 
4.9%
4 3
 
2.1%
6 1
 
0.7%
ValueCountFrequency (%)
6 1
 
0.7%
4 3
 
2.1%
3 7
 
4.9%
2 21
 
14.6%
1 110
76.4%
0 2
 
1.4%

홈페이지 주소
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing137
Missing (%)95.1%
Memory size1.3 KiB
2023-12-12T21:41:14.730702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length26
Mean length27.714286
Min length22

Characters and Unicode

Total characters194
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowhttps://www.byc.co.kr/shop/main/index.php
2nd rowhttps://www.naturerepublic.com/
3rd rowhttps://www.emart24.co.kr/
4th rowhttp://www.zishen.com/
5th rowhttps://www.ableshop.kr/
ValueCountFrequency (%)
https://www.byc.co.kr/shop/main/index.php 1
14.3%
https://www.naturerepublic.com 1
14.3%
https://www.emart24.co.kr 1
14.3%
http://www.zishen.com 1
14.3%
https://www.ableshop.kr 1
14.3%
https://www.clubclio.co.kr 1
14.3%
https://www.aritaum.com 1
14.3%
2023-12-12T21:41:15.137264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 22
 
11.3%
w 21
 
10.8%
. 18
 
9.3%
t 17
 
8.8%
p 12
 
6.2%
h 11
 
5.7%
c 10
 
5.2%
s 9
 
4.6%
o 9
 
4.6%
r 8
 
4.1%
Other values (16) 57
29.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 145
74.7%
Other Punctuation 47
 
24.2%
Decimal Number 2
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 21
14.5%
t 17
11.7%
p 12
 
8.3%
h 11
 
7.6%
c 10
 
6.9%
s 9
 
6.2%
o 9
 
6.2%
r 8
 
5.5%
m 6
 
4.1%
a 6
 
4.1%
Other values (11) 36
24.8%
Other Punctuation
ValueCountFrequency (%)
/ 22
46.8%
. 18
38.3%
: 7
 
14.9%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 145
74.7%
Common 49
 
25.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 21
14.5%
t 17
11.7%
p 12
 
8.3%
h 11
 
7.6%
c 10
 
6.9%
s 9
 
6.2%
o 9
 
6.2%
r 8
 
5.5%
m 6
 
4.1%
a 6
 
4.1%
Other values (11) 36
24.8%
Common
ValueCountFrequency (%)
/ 22
44.9%
. 18
36.7%
: 7
 
14.3%
2 1
 
2.0%
4 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 194
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 22
 
11.3%
w 21
 
10.8%
. 18
 
9.3%
t 17
 
8.8%
p 12
 
6.2%
h 11
 
5.7%
c 10
 
5.2%
s 9
 
4.6%
o 9
 
4.6%
r 8
 
4.1%
Other values (16) 57
29.4%

빈점포 유무
Boolean

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size276.0 B
False
144 
ValueCountFrequency (%)
False 144
100.0%
2023-12-12T21:41:15.246171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

구역 내외 유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size276.0 B
True
139 
False
 
5
ValueCountFrequency (%)
True 139
96.5%
False 5
 
3.5%
2023-12-12T21:41:15.329260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.5458
Minimum128.54499
Maximum128.54656
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T21:41:15.441459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.54499
5-th percentile128.54515
Q1128.54547
median128.54584
Q3128.54618
95-th percentile128.54656
Maximum128.54656
Range0.001567
Interquartile range (IQR)0.000706

Descriptive statistics

Standard deviation0.00041369021
Coefficient of variation (CV)3.218232 × 10-6
Kurtosis-0.786678
Mean128.5458
Median Absolute Deviation (MAD)0.000345
Skewness0.12228739
Sum18510.595
Variance1.7113959 × 10-7
MonotonicityNot monotonic
2023-12-12T21:41:15.579347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
128.546194 15
 
10.4%
128.546555 13
 
9.0%
128.545894 13
 
9.0%
128.545844 8
 
5.6%
128.545471 7
 
4.9%
128.54561 6
 
4.2%
128.546086 5
 
3.5%
128.545242 4
 
2.8%
128.545744 4
 
2.8%
128.545278 4
 
2.8%
Other values (21) 65
45.1%
ValueCountFrequency (%)
128.544988 3
2.1%
128.545116 3
2.1%
128.545146 3
2.1%
128.545212 2
1.4%
128.545242 4
2.8%
128.545278 4
2.8%
128.545339 3
2.1%
128.545378 3
2.1%
128.545427 3
2.1%
128.545448 4
2.8%
ValueCountFrequency (%)
128.546555 13
9.0%
128.5464 1
 
0.7%
128.546375 2
 
1.4%
128.546316 2
 
1.4%
128.546194 15
10.4%
128.546177 4
 
2.8%
128.546086 5
 
3.5%
128.546046 4
 
2.8%
128.545916 4
 
2.8%
128.545914 4
 
2.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.854399
Minimum35.853573
Maximum35.855395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T21:41:15.727252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.853573
5-th percentile35.853837
Q135.854092
median35.854191
Q335.854635
95-th percentile35.855257
Maximum35.855395
Range0.001822
Interquartile range (IQR)0.000543

Descriptive statistics

Standard deviation0.00043198141
Coefficient of variation (CV)1.2048212 × 10-5
Kurtosis-0.26850026
Mean35.854399
Median Absolute Deviation (MAD)0.000217
Skewness0.66801588
Sum5163.0334
Variance1.8660793 × 10-7
MonotonicityNot monotonic
2023-12-12T21:41:16.273677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
35.854092 17
 
11.8%
35.854191 15
 
10.4%
35.854175 13
 
9.0%
35.854302 8
 
5.6%
35.854127 7
 
4.9%
35.855072 6
 
4.2%
35.854624 5
 
3.5%
35.855395 4
 
2.8%
35.853902 4
 
2.8%
35.854509 4
 
2.8%
Other values (20) 61
42.4%
ValueCountFrequency (%)
35.853573 2
 
1.4%
35.853692 4
 
2.8%
35.853837 4
 
2.8%
35.853902 4
 
2.8%
35.853995 3
 
2.1%
35.854019 1
 
0.7%
35.854044 3
 
2.1%
35.854092 17
11.8%
35.854127 7
4.9%
35.854175 13
9.0%
ValueCountFrequency (%)
35.855395 4
2.8%
35.855288 3
2.1%
35.855257 3
2.1%
35.855127 4
2.8%
35.855072 6
4.2%
35.85495 3
2.1%
35.854878 2
 
1.4%
35.854813 3
2.1%
35.854759 4
2.8%
35.854642 3
2.1%

Interactions

2023-12-12T21:41:09.861317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:08.388154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:08.889756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:09.369672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:09.981328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:08.515584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:09.019521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:09.491163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:10.089659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:08.629037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:09.128891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:09.606516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:10.209114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:08.757823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:09.248609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:41:09.721747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:41:16.425188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상점코드도로명주소지번주소업종분류대표품목상가번영회 가입 유무온누리상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무매출규모종업원 수홈페이지 주소구역 내외 유무경도위도
상점코드1.0000.4710.0540.5100.5560.8310.6700.0000.4710.1150.0000.2910.0001.0000.0000.3410.281
도로명주소0.4711.0000.9990.4370.5700.5990.5091.0000.5560.4730.2120.5660.0001.0001.0000.9990.998
지번주소0.0540.9991.0000.4800.7880.6450.4991.0000.5440.3380.1940.6440.0001.0001.0001.0001.000
업종분류0.5100.4370.4801.0000.9850.1790.2830.0000.2340.2240.0710.1920.361NaN0.0000.3790.000
대표품목0.5560.5700.7880.9851.0000.8950.8911.0000.7040.7430.3090.3560.2391.0000.0000.0000.000
상가번영회 가입 유무0.8310.5990.6450.1790.8951.0000.9040.0000.5180.1550.0000.0000.2061.0000.0000.2700.159
온누리상품권 사용유무0.6700.5090.4990.2830.8910.9041.0000.0000.6790.4800.0000.0440.1001.0000.0000.2850.108
문화상품권 사용유무0.0001.0001.0000.0001.0000.0000.0001.0000.0000.0000.0000.3020.451NaN0.0000.0420.000
전자상품권 사용유무0.4710.5560.5440.2340.7040.5180.6790.0001.0000.8570.2460.1850.0001.0000.0000.4010.000
카드단말기 유무0.1150.4730.3380.2240.7430.1550.4800.0000.8571.0000.2890.0630.000NaN0.0000.3600.000
택배서비스 유무0.0000.2120.1940.0710.3090.0000.0000.0000.2460.2891.0000.1370.297NaN0.0000.2410.000
매출규모0.2910.5660.6440.1920.3560.0000.0440.3020.1850.0630.1371.0000.3701.0000.0000.0000.195
종업원 수0.0000.0000.0000.3610.2390.2060.1000.4510.0000.0000.2970.3701.0001.0000.0000.0000.000
홈페이지 주소1.0001.0001.000NaN1.0001.0001.000NaN1.000NaNNaN1.0001.0001.0001.0001.0001.000
구역 내외 유무0.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.7210.633
경도0.3410.9991.0000.3790.0000.2700.2850.0420.4010.3600.2410.0000.0001.0000.7211.0000.865
위도0.2810.9981.0000.0000.0000.1590.1080.0000.0000.0000.0000.1950.0001.0000.6330.8651.000
2023-12-12T21:41:16.650550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카드단말기 유무문화상품권 사용유무업종분류상가번영회 가입 유무택배서비스 유무구역 내외 유무전자상품권 사용유무매출규모도로명주소온누리상품권 사용유무지번주소
카드단말기 유무1.0000.0000.3650.0990.1860.0000.6560.0750.3300.3190.244
문화상품권 사용유무0.0001.0000.0000.0000.0000.0000.0000.3640.8800.0000.868
업종분류0.3650.0001.0000.2940.1170.0000.3810.1450.2130.4570.236
상가번영회 가입 유무0.0990.0000.2941.0000.0000.0000.3470.0000.4230.7190.477
택배서비스 유무0.1860.0000.1170.0001.0000.0000.1580.1660.1430.0000.136
구역 내외 유무0.0000.0000.0000.0000.0001.0000.0000.0000.8800.0000.868
전자상품권 사용유무0.6560.0000.3810.3470.1580.0001.0000.2230.3910.4750.399
매출규모0.0750.3640.1450.0000.1660.0000.2231.0000.2720.0520.296
도로명주소0.3300.8800.2130.4230.1430.8800.3910.2721.0000.3560.958
온누리상품권 사용유무0.3190.0000.4570.7190.0000.0000.4750.0520.3561.0000.365
지번주소0.2440.8680.2360.4770.1360.8680.3990.2960.9580.3651.000
2023-12-12T21:41:16.830171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상점코드종업원 수경도위도도로명주소지번주소업종분류상가번영회 가입 유무온누리상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무매출규모구역 내외 유무
상점코드1.000-0.2440.1400.1040.1540.0000.3420.6440.5060.0000.3460.0500.0000.1150.000
종업원 수-0.2441.0000.004-0.0060.0000.0000.1580.1450.0690.3200.0000.0000.2100.2600.000
경도0.1400.0041.000-0.1260.8990.8940.2430.2070.2200.0450.3090.2790.2450.0000.549
위도0.104-0.006-0.1261.0000.8930.8940.0000.1160.0780.0000.0000.0000.0000.0780.477
도로명주소0.1540.0000.8990.8931.0000.9580.2130.4230.3560.8800.3910.3300.1430.2720.880
지번주소0.0000.0000.8940.8940.9581.0000.2360.4770.3650.8680.3990.2440.1360.2960.868
업종분류0.3420.1580.2430.0000.2130.2361.0000.2940.4570.0000.3810.3650.1170.1450.000
상가번영회 가입 유무0.6440.1450.2070.1160.4230.4770.2941.0000.7190.0000.3470.0990.0000.0000.000
온누리상품권 사용유무0.5060.0690.2200.0780.3560.3650.4570.7191.0000.0000.4750.3190.0000.0520.000
문화상품권 사용유무0.0000.3200.0450.0000.8800.8680.0000.0000.0001.0000.0000.0000.0000.3640.000
전자상품권 사용유무0.3460.0000.3090.0000.3910.3990.3810.3470.4750.0001.0000.6560.1580.2230.000
카드단말기 유무0.0500.0000.2790.0000.3300.2440.3650.0990.3190.0000.6561.0000.1860.0750.000
택배서비스 유무0.0000.2100.2450.0000.1430.1360.1170.0000.0000.0000.1580.1861.0000.1660.000
매출규모0.1150.2600.0000.0780.2720.2960.1450.0000.0520.3640.2230.0750.1661.0000.000
구역 내외 유무0.0000.0000.5490.4770.8800.8680.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T21:41:10.399950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:41:10.698046image/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.
2023-12-12T21:41:10.858802image/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

상점코드상점명도로명주소지번주소업종분류대표품목상가번영회 가입 유무온누리상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무매출규모종업원 수홈페이지 주소빈점포 유무구역 내외 유무경도위도
011번지야채대구광역시 달서구 당산로41길 51대구광역시 달서구 감삼동 63-19 (1층)쇼핑시설야채YYNNYN3000~5000만원/년1<NA>NY128.54524235.854092
12BYC서남점대구광역시 달서구 달구벌대로329길 25대구광역시 달서구 감삼동 55-16 (1층)쇼핑시설옷YYNYYN5000~1억/년1https://www.byc.co.kr/shop/main/index.phpNY128.54537835.854813
23가야떡집대구광역시 달서구 당산로41길 53대구광역시 달서구 감삼동 63-18 (1층)음식점떡YYNYYN3000~5000만원/년1<NA>NY128.54511635.854044
34계영제과대구광역시 달서구 달구벌대로 1641대구광역시 달서구 감삼동 64-13 (1층)음식점제과YYNNYN3000~5000만원/년2<NA>NY128.54550435.853692
45고령농산물대구광역시 달서구 죽전4길 96대구광역시 달서구 감삼동 56-1 (1층)쇼핑시설농산물YYNYYY3000~5000만원/년1<NA>NY128.54544835.855395
56고령보리밥대구광역시 달서구 달구벌대로 1651-3대구광역시 달서구 감삼동 62-3 (1층)음식점보리밥YYNYYN3000~5000만원/년1<NA>NY128.54619435.854191
67영천과일대구광역시 달서구 당산로41길 55대구광역시 달서구 감삼동 63-4 (1층)쇼핑시설과일YYNYYY3000~5000만원/년1<NA>NY128.54498835.853995
78영풍식육점대구광역시 달서구 달구벌대로 1649대구광역시 달서구 감삼동 62-8 (1층)쇼핑시설식육YYYYYN1억~3억/년3<NA>NY128.546435.854019
89예실축산물대구광역시 달서구 달구벌대로329길 14대구광역시 달서구 감삼동 62-1 (1층)쇼핑시설육류YYNYYN3억~5억/년3<NA>NY128.54584435.854302
910오뚜기튀김대구광역시 달서구 달구벌대로 1651대구광역시 달서구 감삼동 61-1 (1층)음식점튀김YYNNYY3000~5000만원/년6<NA>NY128.54655535.854175
상점코드상점명도로명주소지번주소업종분류대표품목상가번영회 가입 유무온누리상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무매출규모종업원 수홈페이지 주소빈점포 유무구역 내외 유무경도위도
134147신일참기름대구광역시 달서구 당산로41길 53대구광역시 달서구 감삼동 63-18 (1층)쇼핑시설참기름YYNNYY0~3000만원/년1<NA>NY128.54511635.854044
135148서남탁구장대구광역시 달서구 달구벌대로329길 14대구광역시 달서구 감삼동 62-1 (지하 1층)기타탁구NNNNYN<NA>1<NA>NY128.54584435.854302
136149서남문화센터대구광역시 달서구 달구벌대로 1651-3대구광역시 달서구 감삼동 62-3 (2층)기타문화센터NNNNNN<NA>1<NA>NY128.54619435.854191
137150서남 고객휴게실대구광역시 달서구 달구벌대로329길 10대구광역시 달서구 감삼동 62-4 (1층)기타휴게실NNNNNN<NA>1<NA>NY128.54589435.854092
138151사랑의 교회대구광역시 달서구 달구벌대로329길 14대구광역시 달서구 감삼동 62-1 (3층)기타교회NNNNNN1억~3억/년1<NA>NY128.54584435.854302
139152태인한의원대구광역시 달서구 달구벌대로329길 14대구광역시 달서구 감삼동 62-1 (2층)기타한의원NNNNYN0~3000만원/년1<NA>NY128.54584435.854302
140153썬토스트대구광역시 달서구 달구벌대로329길 14대구광역시 달서구 감삼동 62-1 (1층)음식점토스트NNNNNN0~3000만원/년1<NA>NY128.54584435.854302
141154계림 철학원대구광역시 달서구 당산로41길 38대구광역시 달서구 감삼동 56-13 (1층)기타문화YYNNYN0~3000만원/년1<NA>NY128.54591435.854557
142155우일지짐대구광역시 달서구 달구벌대로329길 39대구광역시 달서구 감삼동 55-3 (1층)음식점전YYNNNN0~3000만원/년1<NA>NN128.54514635.855288
143157서남활어마켓대구광역시 달서구 달구벌대로329길 14대구광역시 달서구 감삼동 62-1 (1층)쇼핑시설회YYNYYY5000~1억/년2<NA>NY128.54584435.854302