Overview

Dataset statistics

Number of variables15
Number of observations1103
Missing cells1546
Missing cells (%)9.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory132.6 KiB
Average record size in memory123.1 B

Variable types

Categorical3
Numeric3
Text8
Boolean1

Dataset

Description광주광역시 지역특화거리 내 점포현황(점포명, 업종분류, 소재지지번주소, 소재지도로명주소, 전화번호, 배달서비스 여부 등)에 관한 데이터입니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15098176/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
거리명 is highly overall correlated with 점포(ID) and 3 other fieldsHigh correlation
비고 is highly overall correlated with 점포(ID) and 2 other fieldsHigh correlation
배달서비스 is highly overall correlated with 비고High correlation
점포(ID) is highly overall correlated with 거리명 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
배달서비스 is highly imbalanced (68.4%)Imbalance
비고 is highly imbalanced (79.7%)Imbalance
전화번호 has 429 (38.9%) missing valuesMissing
홈페이지 has 1026 (93.0%) missing valuesMissing
위도 has 35 (3.2%) missing valuesMissing
경도 has 35 (3.2%) missing valuesMissing
주력상품 has 17 (1.5%) missing valuesMissing
점포(ID) has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:14:06.920520
Analysis finished2023-12-12 20:14:09.759711
Duration2.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

거리명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
조대장미의거리
245 
금남로지하도상가
189 
공구의거리
177 
전자의거리
147 
자동차의거리
98 
Other values (7)
247 

Length

Max length8
Median length7
Mean length6.5512239
Min length3

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
조대장미의거리 245
22.2%
금남로지하도상가 189
17.1%
공구의거리 177
16.0%
전자의거리 147
13.3%
자동차의거리 98
 
8.9%
충금지하도상가 75
 
6.8%
용봉동패션의거리 63
 
5.7%
무등산상가거리 50
 
4.5%
무등산보리밥거리 32
 
2.9%
충장로상점가 25
 
2.3%
Other values (2) 2
 
0.2%

Length

2023-12-13T05:14:09.825838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조대장미의거리 245
22.2%
금남로지하도상가 189
17.1%
공구의거리 177
16.0%
전자의거리 147
13.3%
자동차의거리 98
 
8.9%
충금지하도상가 75
 
6.8%
용봉동패션의거리 63
 
5.7%
무등산상가거리 50
 
4.5%
무등산보리밥거리 32
 
2.9%
충장로상점가 25
 
2.3%
Other values (2) 2
 
0.2%

점포(ID)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1103
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean552.67543
Minimum1
Maximum1104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2023-12-13T05:14:09.960083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile56.1
Q1276.5
median553
Q3828.5
95-th percentile1048.9
Maximum1104
Range1103
Interquartile range (IQR)552

Descriptive statistics

Standard deviation318.93298
Coefficient of variation (CV)0.57707102
Kurtosis-1.2005519
Mean552.67543
Median Absolute Deviation (MAD)276
Skewness-0.0014501366
Sum609601
Variance101718.24
MonotonicityStrictly increasing
2023-12-13T05:14:10.089643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
736 1
 
0.1%
742 1
 
0.1%
741 1
 
0.1%
740 1
 
0.1%
739 1
 
0.1%
738 1
 
0.1%
737 1
 
0.1%
735 1
 
0.1%
727 1
 
0.1%
Other values (1093) 1093
99.1%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1104 1
0.1%
1103 1
0.1%
1102 1
0.1%
1101 1
0.1%
1100 1
0.1%
1099 1
0.1%
1098 1
0.1%
1097 1
0.1%
1096 1
0.1%
1095 1
0.1%

점포명
Text

Distinct1075
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-13T05:14:10.359135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length5.1523119
Min length1

Characters and Unicode

Total characters5683
Distinct characters628
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1047 ?
Unique (%)94.9%

Sample

1st row캐라반
2nd rowREC
3rd row삐삐네분식
4th row하나문구,하나서점
5th row도움공인중개사
ValueCountFrequency (%)
광주용봉점 16
 
1.3%
카페 9
 
0.7%
아웃도어 7
 
0.6%
용봉점 5
 
0.4%
조선대점 3
 
0.2%
세븐일레븐 3
 
0.2%
아리따움 3
 
0.2%
광주광역시 3
 
0.2%
조대점 3
 
0.2%
크로커다일 2
 
0.2%
Other values (1114) 1155
95.5%
2023-12-13T05:14:10.782503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 128
 
2.3%
이 108
 
1.9%
106
 
1.9%
리 95
 
1.7%
전 79
 
1.4%
대 76
 
1.3%
사 72
 
1.3%
점 71
 
1.2%
아 66
 
1.2%
자 66
 
1.2%
Other values (618) 4816
84.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4953
87.2%
Uppercase Letter 402
 
7.1%
Lowercase Letter 122
 
2.1%
Space Separator 106
 
1.9%
Decimal Number 66
 
1.2%
Other Punctuation 18
 
0.3%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Dash Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 128
 
2.6%
이 108
 
2.2%
리 95
 
1.9%
전 79
 
1.6%
대 76
 
1.5%
사 72
 
1.5%
점 71
 
1.4%
아 66
 
1.3%
자 66
 
1.3%
광 63
 
1.3%
Other values (551) 4129
83.4%
Uppercase Letter
ValueCountFrequency (%)
A 36
 
9.0%
O 35
 
8.7%
E 33
 
8.2%
L 31
 
7.7%
I 29
 
7.2%
C 28
 
7.0%
T 24
 
6.0%
S 22
 
5.5%
R 20
 
5.0%
P 17
 
4.2%
Other values (14) 127
31.6%
Lowercase Letter
ValueCountFrequency (%)
e 17
13.9%
o 12
 
9.8%
a 11
 
9.0%
s 9
 
7.4%
r 8
 
6.6%
c 8
 
6.6%
i 8
 
6.6%
n 6
 
4.9%
m 5
 
4.1%
b 5
 
4.1%
Other values (13) 33
27.0%
Decimal Number
ValueCountFrequency (%)
2 16
24.2%
0 12
18.2%
1 12
18.2%
3 9
13.6%
9 5
 
7.6%
5 5
 
7.6%
6 2
 
3.0%
4 2
 
3.0%
7 2
 
3.0%
8 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
& 10
55.6%
. 3
 
16.7%
, 3
 
16.7%
! 1
 
5.6%
' 1
 
5.6%
Space Separator
ValueCountFrequency (%)
106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4953
87.2%
Latin 524
 
9.2%
Common 206
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 128
 
2.6%
이 108
 
2.2%
리 95
 
1.9%
전 79
 
1.6%
대 76
 
1.5%
사 72
 
1.5%
점 71
 
1.4%
아 66
 
1.3%
자 66
 
1.3%
광 63
 
1.3%
Other values (551) 4129
83.4%
Latin
ValueCountFrequency (%)
A 36
 
6.9%
O 35
 
6.7%
E 33
 
6.3%
L 31
 
5.9%
I 29
 
5.5%
C 28
 
5.3%
T 24
 
4.6%
S 22
 
4.2%
R 20
 
3.8%
e 17
 
3.2%
Other values (37) 249
47.5%
Common
ValueCountFrequency (%)
106
51.5%
2 16
 
7.8%
0 12
 
5.8%
1 12
 
5.8%
& 10
 
4.9%
3 9
 
4.4%
( 7
 
3.4%
) 7
 
3.4%
9 5
 
2.4%
5 5
 
2.4%
Other values (10) 17
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4953
87.2%
ASCII 730
 
12.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 128
 
2.6%
이 108
 
2.2%
리 95
 
1.9%
전 79
 
1.6%
대 76
 
1.5%
사 72
 
1.5%
점 71
 
1.4%
아 66
 
1.3%
자 66
 
1.3%
광 63
 
1.3%
Other values (551) 4129
83.4%
ASCII
ValueCountFrequency (%)
106
 
14.5%
A 36
 
4.9%
O 35
 
4.8%
E 33
 
4.5%
L 31
 
4.2%
I 29
 
4.0%
C 28
 
3.8%
T 24
 
3.3%
S 22
 
3.0%
R 20
 
2.7%
Other values (57) 366
50.1%

분류
Text

Distinct93
Distinct (%)8.4%
Missing1
Missing (%)0.1%
Memory size8.7 KiB
2023-12-13T05:14:11.022142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.1107078
Min length2

Characters and Unicode

Total characters3428
Distinct characters140
Distinct categories5 ?
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 (%)5.0%

Sample

1st row노래방
2nd row카페
3rd row음식점
4th row서점
5th row부동산
ValueCountFrequency (%)
도소매 621
56.3%
음식점 156
 
14.1%
카페 43
 
3.9%
기타 37
 
3.4%
as/도소매 33
 
3.0%
휴게음식점 17
 
1.5%
미용실 15
 
1.4%
수리점 10
 
0.9%
a/s 10
 
0.9%
금은방 9
 
0.8%
Other values (82) 152
 
13.8%
2023-12-13T05:14:11.401762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 670
19.5%
도 663
19.3%
매 662
19.3%
점 216
 
6.3%
음 173
 
5.0%
식 173
 
5.0%
/ 51
 
1.5%
카 47
 
1.4%
페 45
 
1.3%
A 45
 
1.3%
Other values (130) 683
19.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3270
95.4%
Uppercase Letter 92
 
2.7%
Other Punctuation 63
 
1.8%
Lowercase Letter 2
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 670
20.5%
도 663
20.3%
매 662
20.2%
점 216
 
6.6%
음 173
 
5.3%
식 173
 
5.3%
카 47
 
1.4%
페 45
 
1.4%
타 39
 
1.2%
기 38
 
1.2%
Other values (121) 544
16.6%
Uppercase Letter
ValueCountFrequency (%)
A 45
48.9%
S 45
48.9%
T 1
 
1.1%
V 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 51
81.0%
, 12
 
19.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
p 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3270
95.4%
Latin 94
 
2.7%
Common 64
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 670
20.5%
도 663
20.3%
매 662
20.2%
점 216
 
6.6%
음 173
 
5.3%
식 173
 
5.3%
카 47
 
1.4%
페 45
 
1.4%
타 39
 
1.2%
기 38
 
1.2%
Other values (121) 544
16.6%
Latin
ValueCountFrequency (%)
A 45
47.9%
S 45
47.9%
T 1
 
1.1%
V 1
 
1.1%
c 1
 
1.1%
p 1
 
1.1%
Common
ValueCountFrequency (%)
/ 51
79.7%
, 12
 
18.8%
1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3270
95.4%
ASCII 158
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 670
20.5%
도 663
20.3%
매 662
20.2%
점 216
 
6.6%
음 173
 
5.3%
식 173
 
5.3%
카 47
 
1.4%
페 45
 
1.4%
타 39
 
1.2%
기 38
 
1.2%
Other values (121) 544
16.6%
ASCII
ValueCountFrequency (%)
/ 51
32.3%
A 45
28.5%
S 45
28.5%
, 12
 
7.6%
T 1
 
0.6%
V 1
 
0.6%
c 1
 
0.6%
1
 
0.6%
p 1
 
0.6%

소재지지번주소
Text

Distinct487
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-13T05:14:11.664258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length19.670898
Min length15

Characters and Unicode

Total characters21697
Distinct characters73
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

Unique322 ?
Unique (%)29.2%

Sample

1st row광주광역시 동구 지산동 480
2nd row광주광역시 동구 지산동 480
3rd row광주광역시 동구 지산동 488 1층
4th row광주광역시 동구 지산동 488
5th row광주광역시 동구 지산동 488
ValueCountFrequency (%)
광주광역시 1103
23.4%
동구 763
16.2%
북구 333
 
7.1%
지산동 205
 
4.4%
금남로1가 189
 
4.0%
12-7 186
 
4.0%
금남로지하상가 186
 
4.0%
운암동 167
 
3.6%
대인동 87
 
1.8%
금남로4가 75
 
1.6%
Other values (497) 1410
30.0%
2023-12-13T05:14:12.331370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3605
16.6%
광 2211
 
10.2%
동 1539
 
7.1%
1 1135
 
5.2%
시 1105
 
5.1%
구 1104
 
5.1%
주 1103
 
5.1%
역 1103
 
5.1%
- 712
 
3.3%
가 610
 
2.8%
Other values (63) 7470
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13137
60.5%
Decimal Number 4240
 
19.5%
Space Separator 3605
 
16.6%
Dash Punctuation 712
 
3.3%
Other Punctuation 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 2211
16.8%
동 1539
11.7%
시 1105
8.4%
구 1104
8.4%
주 1103
8.4%
역 1103
8.4%
가 610
 
4.6%
금 586
 
4.5%
로 535
 
4.1%
남 511
 
3.9%
Other values (48) 2730
20.8%
Decimal Number
ValueCountFrequency (%)
1 1135
26.8%
2 595
14.0%
5 522
12.3%
7 473
11.2%
4 428
 
10.1%
3 308
 
7.3%
0 210
 
5.0%
6 204
 
4.8%
9 202
 
4.8%
8 163
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
/ 1
50.0%
Space Separator
ValueCountFrequency (%)
3605
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 712
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13137
60.5%
Common 8559
39.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 2211
16.8%
동 1539
11.7%
시 1105
8.4%
구 1104
8.4%
주 1103
8.4%
역 1103
8.4%
가 610
 
4.6%
금 586
 
4.5%
로 535
 
4.1%
남 511
 
3.9%
Other values (48) 2730
20.8%
Common
ValueCountFrequency (%)
3605
42.1%
1 1135
 
13.3%
- 712
 
8.3%
2 595
 
7.0%
5 522
 
6.1%
7 473
 
5.5%
4 428
 
5.0%
3 308
 
3.6%
0 210
 
2.5%
6 204
 
2.4%
Other values (4) 367
 
4.3%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13137
60.5%
ASCII 8560
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3605
42.1%
1 1135
 
13.3%
- 712
 
8.3%
2 595
 
7.0%
5 522
 
6.1%
7 473
 
5.5%
4 428
 
5.0%
3 308
 
3.6%
0 210
 
2.5%
6 204
 
2.4%
Other values (5) 368
 
4.3%
Hangul
ValueCountFrequency (%)
광 2211
16.8%
동 1539
11.7%
시 1105
8.4%
구 1104
8.4%
주 1103
8.4%
역 1103
8.4%
가 610
 
4.6%
금 586
 
4.5%
로 535
 
4.1%
남 511
 
3.9%
Other values (48) 2730
20.8%

소재지도로명주소
Text

Distinct483
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2023-12-13T05:14:12.650359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length30
Mean length18.500453
Min length14

Characters and Unicode

Total characters20406
Distinct characters113
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique319 ?
Unique (%)28.9%

Sample

1st row광주광역시 동구 필문대로273번길
2nd row광주광역시 동구 필문대로273번길
3rd row광주광역시 동구 지산로 35
4th row광주광역시 동구 지산로 35
5th row광주광역시 동구 지산로 35
ValueCountFrequency (%)
광주광역시 1103
24.4%
동구 765
16.9%
북구 333
 
7.4%
56 191
 
4.2%
서석로 189
 
4.2%
하남대로 172
 
3.8%
독립로264번길 104
 
2.3%
필문대로287번길 99
 
2.2%
25 80
 
1.8%
필문대로273번길 80
 
1.8%
Other values (409) 1403
31.0%
2023-12-13T05:14:13.135548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3416
16.7%
광 2206
 
10.8%
시 1106
 
5.4%
구 1104
 
5.4%
역 1103
 
5.4%
주 1103
 
5.4%
로 1055
 
5.2%
동 844
 
4.1%
2 749
 
3.7%
1 586
 
2.9%
Other values (103) 7134
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12858
63.0%
Decimal Number 3901
 
19.1%
Space Separator 3416
 
16.7%
Dash Punctuation 212
 
1.0%
Uppercase Letter 10
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 2206
17.2%
시 1106
 
8.6%
구 1104
 
8.6%
역 1103
 
8.6%
주 1103
 
8.6%
로 1055
 
8.2%
동 844
 
6.6%
길 433
 
3.4%
대 387
 
3.0%
번 381
 
3.0%
Other values (78) 3136
24.4%
Decimal Number
ValueCountFrequency (%)
2 749
19.2%
1 586
15.0%
7 500
12.8%
6 439
11.3%
5 424
10.9%
8 363
9.3%
3 306
7.8%
4 216
 
5.5%
9 164
 
4.2%
0 154
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
A 3
30.0%
S 1
 
10.0%
L 1
 
10.0%
O 1
 
10.0%
N 1
 
10.0%
G 1
 
10.0%
R 1
 
10.0%
Y 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
d 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
3416
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 212
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12858
63.0%
Common 7536
36.9%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 2206
17.2%
시 1106
 
8.6%
구 1104
 
8.6%
역 1103
 
8.6%
주 1103
 
8.6%
로 1055
 
8.2%
동 844
 
6.6%
길 433
 
3.4%
대 387
 
3.0%
번 381
 
3.0%
Other values (78) 3136
24.4%
Common
ValueCountFrequency (%)
3416
45.3%
2 749
 
9.9%
1 586
 
7.8%
7 500
 
6.6%
6 439
 
5.8%
5 424
 
5.6%
8 363
 
4.8%
3 306
 
4.1%
4 216
 
2.9%
- 212
 
2.8%
Other values (5) 325
 
4.3%
Latin
ValueCountFrequency (%)
A 3
25.0%
S 1
 
8.3%
L 1
 
8.3%
O 1
 
8.3%
N 1
 
8.3%
d 1
 
8.3%
e 1
 
8.3%
G 1
 
8.3%
R 1
 
8.3%
Y 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12858
63.0%
ASCII 7548
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3416
45.3%
2 749
 
9.9%
1 586
 
7.8%
7 500
 
6.6%
6 439
 
5.8%
5 424
 
5.6%
8 363
 
4.8%
3 306
 
4.1%
4 216
 
2.9%
- 212
 
2.8%
Other values (15) 337
 
4.5%
Hangul
ValueCountFrequency (%)
광 2206
17.2%
시 1106
 
8.6%
구 1104
 
8.6%
역 1103
 
8.6%
주 1103
 
8.6%
로 1055
 
8.2%
동 844
 
6.6%
길 433
 
3.4%
대 387
 
3.0%
번 381
 
3.0%
Other values (78) 3136
24.4%

전화번호
Text

MISSING 

Distinct661
Distinct (%)98.1%
Missing429
Missing (%)38.9%
Memory size8.7 KiB
2023-12-13T05:14:13.460848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.011869
Min length12

Characters and Unicode

Total characters8096
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

Unique648 ?
Unique (%)96.1%

Sample

1st row062-222-4036
2nd row062-456-4068
3rd row062-232-0093
4th row062-234-0166
5th row062-234-9933
ValueCountFrequency (%)
062-521-2187 2
 
0.3%
062-225-1766 2
 
0.3%
062-522-9919 2
 
0.3%
070-7614-3579 2
 
0.3%
062-527-5588 2
 
0.3%
062-223-1187 2
 
0.3%
062-222-0242 2
 
0.3%
062-528-0041 2
 
0.3%
062-234-1470 2
 
0.3%
062-223-6807 2
 
0.3%
Other values (651) 654
97.0%
2023-12-13T05:14:13.989722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1889
23.3%
- 1348
16.7%
0 1077
13.3%
6 964
11.9%
5 599
 
7.4%
3 466
 
5.8%
1 451
 
5.6%
8 351
 
4.3%
7 344
 
4.2%
4 332
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6748
83.3%
Dash Punctuation 1348
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1889
28.0%
0 1077
16.0%
6 964
14.3%
5 599
 
8.9%
3 466
 
6.9%
1 451
 
6.7%
8 351
 
5.2%
7 344
 
5.1%
4 332
 
4.9%
9 275
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 1348
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8096
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1889
23.3%
- 1348
16.7%
0 1077
13.3%
6 964
11.9%
5 599
 
7.4%
3 466
 
5.8%
1 451
 
5.6%
8 351
 
4.3%
7 344
 
4.2%
4 332
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8096
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1889
23.3%
- 1348
16.7%
0 1077
13.3%
6 964
11.9%
5 599
 
7.4%
3 466
 
5.8%
1 451
 
5.6%
8 351
 
4.3%
7 344
 
4.2%
4 332
 
4.1%

홈페이지
Text

MISSING 

Distinct76
Distinct (%)98.7%
Missing1026
Missing (%)93.0%
Memory size8.7 KiB
2023-12-13T05:14:14.305220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length139
Median length57
Mean length32.818182
Min length17

Characters and Unicode

Total characters2527
Distinct characters69
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

Unique75 ?
Unique (%)97.4%

Sample

1st rowhttp://0622349933.bdp.kr
2nd rowhttps://open.kakao.com/o/sbXNCALb
3rd rowhttp://www.phonebuy.kr/shop/page_location_view.php?uid=10
4th rowhttps://blog.naver.com/expertkj
5th rowhttps://www.instagram.com/hanseokki/
ValueCountFrequency (%)
http://allforyouyb.modoo.at 2
 
2.6%
http://instagram.com/mugang_hanbok 1
 
1.3%
http://www.cuckoo.co.kr 1
 
1.3%
https://smarketyb.modoo.at 1
 
1.3%
https://smartstore.naver.com/lynxyongbong 1
 
1.3%
http://blog.naver.com/stco 1
 
1.3%
https://2xuyb.modoo.at 1
 
1.3%
http://instagram.com/ng_yongbong 1
 
1.3%
https://pf.kakao.com/_uxgqvxb 1
 
1.3%
http://www.castelbajackorea.com 1
 
1.3%
Other values (66) 66
85.7%
2023-12-13T05:14:14.763337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 219
 
8.7%
t 216
 
8.5%
o 189
 
7.5%
. 169
 
6.7%
a 137
 
5.4%
w 116
 
4.6%
m 108
 
4.3%
p 104
 
4.1%
h 102
 
4.0%
c 101
 
4.0%
Other values (59) 1066
42.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1849
73.2%
Other Punctuation 482
 
19.1%
Decimal Number 120
 
4.7%
Uppercase Letter 39
 
1.5%
Connector Punctuation 17
 
0.7%
Other Letter 9
 
0.4%
Math Symbol 8
 
0.3%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 216
 
11.7%
o 189
 
10.2%
a 137
 
7.4%
w 116
 
6.3%
m 108
 
5.8%
p 104
 
5.6%
h 102
 
5.5%
c 101
 
5.5%
r 93
 
5.0%
n 92
 
5.0%
Other values (16) 591
32.0%
Uppercase Letter
ValueCountFrequency (%)
C 9
23.1%
D 5
12.8%
B 4
10.3%
M 4
10.3%
A 3
 
7.7%
P 2
 
5.1%
N 2
 
5.1%
U 2
 
5.1%
L 2
 
5.1%
X 1
 
2.6%
Other values (5) 5
12.8%
Decimal Number
ValueCountFrequency (%)
3 25
20.8%
1 13
10.8%
0 13
10.8%
7 12
10.0%
5 12
10.0%
4 11
9.2%
2 10
 
8.3%
6 9
 
7.5%
9 8
 
6.7%
8 7
 
5.8%
Other Letter
ValueCountFrequency (%)
바 1
11.1%
스 1
11.1%
당 1
11.1%
닷 1
11.1%
탐 1
11.1%
가 1
11.1%
금 1
11.1%
대 1
11.1%
재 1
11.1%
Other Punctuation
ValueCountFrequency (%)
/ 219
45.4%
. 169
35.1%
: 77
 
16.0%
% 9
 
1.9%
? 7
 
1.5%
; 1
 
0.2%
Connector Punctuation
ValueCountFrequency (%)
_ 17
100.0%
Math Symbol
ValueCountFrequency (%)
= 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1888
74.7%
Common 630
 
24.9%
Hangul 9
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 216
 
11.4%
o 189
 
10.0%
a 137
 
7.3%
w 116
 
6.1%
m 108
 
5.7%
p 104
 
5.5%
h 102
 
5.4%
c 101
 
5.3%
r 93
 
4.9%
n 92
 
4.9%
Other values (31) 630
33.4%
Common
ValueCountFrequency (%)
/ 219
34.8%
. 169
26.8%
: 77
 
12.2%
3 25
 
4.0%
_ 17
 
2.7%
1 13
 
2.1%
0 13
 
2.1%
7 12
 
1.9%
5 12
 
1.9%
4 11
 
1.7%
Other values (9) 62
 
9.8%
Hangul
ValueCountFrequency (%)
바 1
11.1%
스 1
11.1%
당 1
11.1%
닷 1
11.1%
탐 1
11.1%
가 1
11.1%
금 1
11.1%
대 1
11.1%
재 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2518
99.6%
Hangul 9
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 219
 
8.7%
t 216
 
8.6%
o 189
 
7.5%
. 169
 
6.7%
a 137
 
5.4%
w 116
 
4.6%
m 108
 
4.3%
p 104
 
4.1%
h 102
 
4.1%
c 101
 
4.0%
Other values (50) 1057
42.0%
Hangul
ValueCountFrequency (%)
바 1
11.1%
스 1
11.1%
당 1
11.1%
닷 1
11.1%
탐 1
11.1%
가 1
11.1%
금 1
11.1%
대 1
11.1%
재 1
11.1%

배달서비스
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
False
1040 
True
 
63
ValueCountFrequency (%)
False 1040
94.3%
True 63
 
5.7%
2023-12-13T05:14:14.896276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1038
Distinct (%)97.2%
Missing35
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean35.154887
Minimum35.132524
Maximum35.215774
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2023-12-13T05:14:15.032320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.132524
5-th percentile35.144349
Q135.146408
median35.149888
Q335.164323
95-th percentile35.175779
Maximum35.215774
Range0.08324925
Interquartile range (IQR)0.01791531

Descriptive statistics

Standard deviation0.011818605
Coefficient of variation (CV)0.00033618669
Kurtosis-0.018929951
Mean35.154887
Median Absolute Deviation (MAD)0.00412117
Skewness0.67610496
Sum37545.42
Variance0.00013967943
MonotonicityNot monotonic
2023-12-13T05:14:15.215609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1712029 3
 
0.3%
35.14950391 3
 
0.3%
35.14930872 3
 
0.3%
35.14935697 2
 
0.2%
35.13426438 2
 
0.2%
35.14577245 2
 
0.2%
35.1463384 2
 
0.2%
35.14735336 2
 
0.2%
35.14672173 2
 
0.2%
35.14677437 2
 
0.2%
Other values (1028) 1045
94.7%
(Missing) 35
 
3.2%
ValueCountFrequency (%)
35.13252431 1
0.1%
35.13255502 1
0.1%
35.13260171 1
0.1%
35.13263643 1
0.1%
35.13266541 1
0.1%
35.13276791 1
0.1%
35.13278791 1
0.1%
35.13282991 1
0.1%
35.13285372 1
0.1%
35.13288256 1
0.1%
ValueCountFrequency (%)
35.21577356 1
0.1%
35.18314416 1
0.1%
35.18312005 1
0.1%
35.18311101 1
0.1%
35.18310964 1
0.1%
35.18287585 1
0.1%
35.18272917 1
0.1%
35.1823022 1
0.1%
35.18228741 1
0.1%
35.18205845 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1044
Distinct (%)97.8%
Missing35
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean126.91266
Minimum126.87133
Maximum126.95927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2023-12-13T05:14:15.380576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.87133
5-th percentile126.8771
Q1126.90045
median126.91485
Q3126.9285
95-th percentile126.94521
Maximum126.95927
Range0.0879377
Interquartile range (IQR)0.0280551

Descriptive statistics

Standard deviation0.020068983
Coefficient of variation (CV)0.00015813223
Kurtosis-0.16417572
Mean126.91266
Median Absolute Deviation (MAD)0.0139326
Skewness-0.11262741
Sum135542.73
Variance0.00040276409
MonotonicityNot monotonic
2023-12-13T05:14:15.574719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9193944 3
 
0.3%
126.8753817 2
 
0.2%
126.9303783 2
 
0.2%
126.913151 2
 
0.2%
126.9120162 2
 
0.2%
126.9121397 2
 
0.2%
126.9121322 2
 
0.2%
126.9010036 2
 
0.2%
126.9014256 2
 
0.2%
126.901746 2
 
0.2%
Other values (1034) 1047
94.9%
(Missing) 35
 
3.2%
ValueCountFrequency (%)
126.8713336 1
0.1%
126.8714713 1
0.1%
126.8716069 1
0.1%
126.8720369 1
0.1%
126.8722869 1
0.1%
126.8723204 1
0.1%
126.8725625 1
0.1%
126.872667 1
0.1%
126.8726984 1
0.1%
126.8730734 1
0.1%
ValueCountFrequency (%)
126.9592713 1
0.1%
126.9590498 1
0.1%
126.958893 1
0.1%
126.9587297 1
0.1%
126.9585487 1
0.1%
126.9585255 1
0.1%
126.9584665 1
0.1%
126.9583697 1
0.1%
126.9581992 1
0.1%
126.9581914 1
0.1%

취급품목
Text

Distinct178
Distinct (%)16.2%
Missing3
Missing (%)0.3%
Memory size8.7 KiB
2023-12-13T05:14:15.938716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.5472727
Min length1

Characters and Unicode

Total characters3902
Distinct characters227
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)10.4%

Sample

1st row노래방
2nd row카페
3rd row음식점
4th row서점
5th row부동산
ValueCountFrequency (%)
도소매 455
39.9%
음식점 90
 
7.9%
도매/패션잡화 76
 
6.7%
카페 42
 
3.7%
as/도소매 34
 
3.0%
한식 23
 
2.0%
미용실 15
 
1.3%
골프웨어 13
 
1.1%
음료 11
 
1.0%
a/s 10
 
0.9%
Other values (181) 370
32.5%
2023-12-13T05:14:16.450686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 583
 
14.9%
매 575
 
14.7%
소 506
 
13.0%
점 130
 
3.3%
/ 128
 
3.3%
식 124
 
3.2%
음 104
 
2.7%
화 81
 
2.1%
잡 77
 
2.0%
패 76
 
1.9%
Other values (217) 1518
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3585
91.9%
Other Punctuation 182
 
4.7%
Uppercase Letter 94
 
2.4%
Space Separator 39
 
1.0%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 583
16.3%
매 575
16.0%
소 506
14.1%
점 130
 
3.6%
식 124
 
3.5%
음 104
 
2.9%
화 81
 
2.3%
잡 77
 
2.1%
패 76
 
2.1%
션 76
 
2.1%
Other values (208) 1253
35.0%
Uppercase Letter
ValueCountFrequency (%)
S 46
48.9%
A 46
48.9%
V 1
 
1.1%
T 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 128
70.3%
, 54
29.7%
Lowercase Letter
ValueCountFrequency (%)
p 1
50.0%
c 1
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3585
91.9%
Common 221
 
5.7%
Latin 96
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 583
16.3%
매 575
16.0%
소 506
14.1%
점 130
 
3.6%
식 124
 
3.5%
음 104
 
2.9%
화 81
 
2.3%
잡 77
 
2.1%
패 76
 
2.1%
션 76
 
2.1%
Other values (208) 1253
35.0%
Latin
ValueCountFrequency (%)
S 46
47.9%
A 46
47.9%
V 1
 
1.0%
T 1
 
1.0%
p 1
 
1.0%
c 1
 
1.0%
Common
ValueCountFrequency (%)
/ 128
57.9%
, 54
24.4%
39
 
17.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3585
91.9%
ASCII 317
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 583
16.3%
매 575
16.0%
소 506
14.1%
점 130
 
3.6%
식 124
 
3.5%
음 104
 
2.9%
화 81
 
2.3%
잡 77
 
2.1%
패 76
 
2.1%
션 76
 
2.1%
Other values (208) 1253
35.0%
ASCII
ValueCountFrequency (%)
/ 128
40.4%
, 54
17.0%
S 46
 
14.5%
A 46
 
14.5%
39
 
12.3%
V 1
 
0.3%
T 1
 
0.3%
p 1
 
0.3%
c 1
 
0.3%

주력상품
Text

MISSING 

Distinct576
Distinct (%)53.0%
Missing17
Missing (%)1.5%
Memory size8.7 KiB
2023-12-13T05:14:16.733701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length4.674954
Min length1

Characters and Unicode

Total characters5077
Distinct characters437
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique461 ?
Unique (%)42.4%

Sample

1st row노래방
2nd row커피,아이스크림,빵
3rd row컵밥,짬뽕,짜장,튀김
4th row학습참고서
5th row원룸,상가,토지,건물
ValueCountFrequency (%)
의류 136
 
10.5%
전자제품 67
 
5.2%
커피 27
 
2.1%
아웃도어 18
 
1.4%
골프웨어 15
 
1.2%
신발 15
 
1.2%
여성의류 14
 
1.1%
미용실 13
 
1.0%
화장품 13
 
1.0%
기계공구 13
 
1.0%
Other values (625) 961
74.4%
2023-12-13T05:14:17.194156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 329
 
6.5%
208
 
4.1%
의 190
 
3.7%
류 184
 
3.6%
품 146
 
2.9%
자 130
 
2.6%
제 107
 
2.1%
전 104
 
2.0%
리 88
 
1.7%
기 81
 
1.6%
Other values (427) 3510
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4496
88.6%
Other Punctuation 337
 
6.6%
Space Separator 208
 
4.1%
Uppercase Letter 27
 
0.5%
Lowercase Letter 7
 
0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 190
 
4.2%
류 184
 
4.1%
품 146
 
3.2%
자 130
 
2.9%
제 107
 
2.4%
전 104
 
2.3%
리 88
 
2.0%
기 81
 
1.8%
스 78
 
1.7%
어 72
 
1.6%
Other values (406) 3316
73.8%
Uppercase Letter
ValueCountFrequency (%)
C 6
22.2%
S 5
18.5%
A 3
11.1%
V 3
11.1%
T 3
11.1%
P 2
 
7.4%
L 1
 
3.7%
E 1
 
3.7%
U 1
 
3.7%
B 1
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
p 2
28.6%
c 2
28.6%
v 1
14.3%
s 1
14.3%
a 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 329
97.6%
/ 7
 
2.1%
· 1
 
0.3%
Space Separator
ValueCountFrequency (%)
208
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4496
88.6%
Common 547
 
10.8%
Latin 34
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 190
 
4.2%
류 184
 
4.1%
품 146
 
3.2%
자 130
 
2.9%
제 107
 
2.4%
전 104
 
2.3%
리 88
 
2.0%
기 81
 
1.8%
스 78
 
1.7%
어 72
 
1.6%
Other values (406) 3316
73.8%
Latin
ValueCountFrequency (%)
C 6
17.6%
S 5
14.7%
A 3
8.8%
V 3
8.8%
T 3
8.8%
P 2
 
5.9%
p 2
 
5.9%
c 2
 
5.9%
v 1
 
2.9%
s 1
 
2.9%
Other values (6) 6
17.6%
Common
ValueCountFrequency (%)
, 329
60.1%
208
38.0%
/ 7
 
1.3%
1 2
 
0.4%
· 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4496
88.6%
ASCII 580
 
11.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 329
56.7%
208
35.9%
/ 7
 
1.2%
C 6
 
1.0%
S 5
 
0.9%
A 3
 
0.5%
V 3
 
0.5%
T 3
 
0.5%
P 2
 
0.3%
p 2
 
0.3%
Other values (10) 12
 
2.1%
Hangul
ValueCountFrequency (%)
의 190
 
4.2%
류 184
 
4.1%
품 146
 
3.2%
자 130
 
2.9%
제 107
 
2.4%
전 104
 
2.3%
리 88
 
2.0%
기 81
 
1.8%
스 78
 
1.7%
어 72
 
1.6%
Other values (406) 3316
73.8%
None
ValueCountFrequency (%)
· 1
100.0%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
<NA>
1068 
폐점
 
35

Length

Max length4
Median length4
Mean length3.9365367
Min length2

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> 1068
96.8%
폐점 35
 
3.2%

Length

2023-12-13T05:14:17.385481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:14:17.508539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1068
96.8%
폐점 35
 
3.2%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
2021-10-30
1103 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-10-30
2nd row2021-10-30
3rd row2021-10-30
4th row2021-10-30
5th row2021-10-30

Common Values

ValueCountFrequency (%)
2021-10-30 1103
100.0%

Length

2023-12-13T05:14:17.631314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:14:17.730261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-10-30 1103
100.0%

Interactions

2023-12-13T05:14:08.908614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:14:08.337961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:14:08.645585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:14:09.013876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:14:08.437705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:14:08.731434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:14:09.115170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:14:08.545453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:14:08.819443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:14:17.806358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거리명점포(ID)분류홈페이지배달서비스위도경도
거리명1.0000.9100.8571.0000.4560.9370.989
점포(ID)0.9101.0000.7621.0000.4890.8360.951
분류0.8570.7621.0001.0000.4670.6590.747
홈페이지1.0001.0001.0001.0000.0001.0001.000
배달서비스0.4560.4890.4670.0001.0000.3520.473
위도0.9370.8360.6591.0000.3521.0000.911
경도0.9890.9510.7471.0000.4730.9111.000
2023-12-13T05:14:17.940295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거리명비고배달서비스
거리명1.0001.0000.353
비고1.0001.0001.000
배달서비스0.3531.0001.000
2023-12-13T05:14:18.044808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
점포(ID)위도경도거리명배달서비스비고
점포(ID)1.0000.220-0.1810.6990.3751.000
위도0.2201.000-0.9180.8120.2640.000
경도-0.181-0.9181.0000.8150.3630.000
거리명0.6990.8120.8151.0000.3531.000
배달서비스0.3750.2640.3630.3531.0001.000
비고1.0000.0000.0001.0001.0001.000

Missing values

2023-12-13T05:14:09.269891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:14:09.488011image/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.
2023-12-13T05:14:09.671326image/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

거리명점포(ID)점포명분류소재지지번주소소재지도로명주소전화번호홈페이지배달서비스위도경도취급품목주력상품비고데이터 기준일자
0조대장미의거리1캐라반노래방광주광역시 동구 지산동 480광주광역시 동구 필문대로273번길<NA><NA>N35.146527126.92998노래방노래방<NA>2021-10-30
1조대장미의거리2REC카페광주광역시 동구 지산동 480광주광역시 동구 필문대로273번길<NA><NA>N35.146501126.92998카페커피,아이스크림,빵<NA>2021-10-30
2조대장미의거리3삐삐네분식음식점광주광역시 동구 지산동 488 1층광주광역시 동구 지산로 35<NA><NA>N35.147015126.931811음식점컵밥,짬뽕,짜장,튀김<NA>2021-10-30
3조대장미의거리4하나문구,하나서점서점광주광역시 동구 지산동 488광주광역시 동구 지산로 35062-222-4036<NA>N35.147017126.931805서점학습참고서<NA>2021-10-30
4조대장미의거리5도움공인중개사부동산광주광역시 동구 지산동 488광주광역시 동구 지산로 35<NA><NA>N35.147012126.931813부동산원룸,상가,토지,건물<NA>2021-10-30
5조대장미의거리6빵두카페광주광역시 동구 지산동 488-4 1층광주광역시 동구 지산로 33 1층<NA><NA>N35.146899126.931606카페커피,빵<NA>2021-10-30
6조대장미의거리7영암부동산부동산광주광역시 동구 지산동 487-8광주광역시 동구 지산동 487-8<NA><NA>N35.146646126.931559부동산원룸,상가,토지,건물<NA>2021-10-30
7조대장미의거리8돈워리비해피음식점광주광역시 동구 지산동 500광주광역시 동구 지산로 21062-456-4068<NA>N35.146085126.931181음식점수제 함박, 돈까스<NA>2021-10-30
8조대장미의거리9태현렌트카렌트카광주광역시 동구 지산동 500광주광역시 동구 지산로 21062-232-0093<NA>N35.146078126.931181렌트카자동차<NA>2021-10-30
9조대장미의거리10업텐프로피자음식점광주광역시 동구 지산동 480광주광역시 동구 필문대로273번길062-234-0166<NA>N35.146522126.929986음식점피자<NA>2021-10-30
거리명점포(ID)점포명분류소재지지번주소소재지도로명주소전화번호홈페이지배달서비스위도경도취급품목주력상품비고데이터 기준일자
1093충금지하도상가1095추억속과자도소매광주광역시 동구 금남로4가 43 충금지하상가광주광역시 동구 중앙로 187 충금지하상가<NA><NA>N<NA><NA>도매/패션잡화<NA>폐점2021-10-30
1094충금지하도상가1096수입상품도소매광주광역시 동구 금남로4가 43 충금지하상가광주광역시 동구 중앙로 187 충금지하상가<NA><NA>N<NA><NA>도매/패션잡화<NA>폐점2021-10-30
1095충금지하도상가1097비비안도소매광주광역시 동구 금남로4가 43 충금지하상가광주광역시 동구 중앙로 187 충금지하상가<NA><NA>N<NA><NA>도매/패션잡화<NA>폐점2021-10-30
1096충금지하도상가10980.99도소매광주광역시 동구 금남로4가 43 충금지하상가광주광역시 동구 중앙로 187 충금지하상가<NA><NA>N<NA><NA>도매/패션잡화<NA>폐점2021-10-30
1097충금지하도상가1099이지아(2)도소매광주광역시 동구 금남로4가 43 충금지하상가광주광역시 동구 중앙로 187 충금지하상가<NA><NA>N<NA><NA>도매/패션잡화<NA>폐점2021-10-30
1098충금지하도상가1100이지아(3)도소매광주광역시 동구 금남로4가 43 충금지하상가광주광역시 동구 중앙로 187 충금지하상가<NA><NA>N<NA><NA>도매/패션잡화<NA>폐점2021-10-30
1099금남로지하도상가1101뿌띠도소매광주광역시 동구 금남로1가 12-7 금남로지하상가광주광역시 동구 서석로 56<NA><NA>N<NA><NA>도소매<NA>폐점2021-10-30
1100금남로지하도상가1102메이커할인매장도소매광주광역시 동구 금남로1가 12-7 금남로지하상가광주광역시 동구 서석로 56<NA><NA>N<NA><NA>도소매<NA>폐점2021-10-30
1101향로정1103음식점무등산보리밥거리광주광역시 동구 지산동 116-7광주광역시 동구 지호로160번길 11062-222-7653<NA>N<NA><NA>육류, 고기요리조기매운탕, 오리로스폐점2021-10-30
1102향로봉1104음식점무등산보리밥거리광주광역시 동구 지산동 116-2광주광역시 동구 지호로160번길 17062-232-1214<NA>N<NA><NA>한식삼계탕, 오리탕폐점2021-10-30