Overview

Dataset statistics

Number of variables18
Number of observations3335
Missing cells3303
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory482.1 KiB
Average record size in memory148.0 B

Variable types

Numeric4
Categorical5
Text6
Boolean3

Dataset

Description동대문구에 존재하는 상권 내 점포에 대한 기본정보와 위치정보를 나타내는 데이터입니다. 전통시장 2,416개 대학상권 919개 총 3,335개 상권 내 점포 정보를 제공하는 입주점포 데이터입니다.
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15109936/fileData.do

Alerts

전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 아이디High correlation
경도 is highly overall correlated with 아이디High correlation
아이디 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
제로페이가능여부 is highly overall correlated with 지역상품권가능여부High correlation
지역상품권가능여부 is highly overall correlated with 아이디 and 1 other fieldsHigh correlation
스프링클러설치여부 is highly overall correlated with 아이디 and 1 other fieldsHigh correlation
화재감지시설여부 is highly overall correlated with 아이디 and 1 other fieldsHigh correlation
소화전설치여부 is highly overall correlated with 아이디High correlation
소화전설치여부 is highly imbalanced (59.2%)Imbalance
운영시간 has 965 (28.9%) missing valuesMissing
업종구분 has 136 (4.1%) missing valuesMissing
도로명주소 has 59 (1.8%) missing valuesMissing
종업원수 has 104 (3.1%) missing valuesMissing
지역상품권가능여부 has 417 (12.5%) missing valuesMissing
화재감지시설여부 has 850 (25.5%) missing valuesMissing
소화전설치여부 has 772 (23.1%) missing valuesMissing
이미지명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:17:21.811757
Analysis finished2023-12-12 07:17:26.862106
Duration5.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

Distinct559
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.62159
Minimum1
Maximum559
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.4 KiB
2023-12-12T16:17:26.951765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q137
median87
Q3192
95-th percentile392.3
Maximum559
Range558
Interquartile range (IQR)155

Descriptive statistics

Standard deviation121.63084
Coefficient of variation (CV)0.94564871
Kurtosis1.5162801
Mean128.62159
Median Absolute Deviation (MAD)61
Skewness1.3803494
Sum428953
Variance14794.061
MonotonicityNot monotonic
2023-12-12T16:17:27.099907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 24
 
0.7%
9 24
 
0.7%
2 24
 
0.7%
14 24
 
0.7%
13 24
 
0.7%
12 24
 
0.7%
10 24
 
0.7%
11 24
 
0.7%
8 24
 
0.7%
7 24
 
0.7%
Other values (549) 3095
92.8%
ValueCountFrequency (%)
1 24
0.7%
2 24
0.7%
3 24
0.7%
4 24
0.7%
5 24
0.7%
6 24
0.7%
7 24
0.7%
8 24
0.7%
9 24
0.7%
10 24
0.7%
ValueCountFrequency (%)
559 1
< 0.1%
558 1
< 0.1%
557 1
< 0.1%
556 1
< 0.1%
555 1
< 0.1%
554 1
< 0.1%
553 1
< 0.1%
552 1
< 0.1%
551 1
< 0.1%
550 1
< 0.1%

아이디
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
M11
559 
U02
322 
U04
321 
M18
315 
M10
275 
Other values (19)
1543 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM01
2nd rowM01
3rd rowM01
4th rowM01
5th rowM01

Common Values

ValueCountFrequency (%)
M11 559
16.8%
U02 322
 
9.7%
U04 321
 
9.6%
M18 315
 
9.4%
M10 275
 
8.2%
U03 153
 
4.6%
M08 149
 
4.5%
M09 142
 
4.3%
U01 123
 
3.7%
M19 121
 
3.6%
Other values (14) 855
25.6%

Length

2023-12-12T16:17:27.246890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
m11 559
16.8%
u02 322
 
9.7%
u04 321
 
9.6%
m18 315
 
9.4%
m10 275
 
8.2%
u03 153
 
4.6%
m08 149
 
4.5%
m09 142
 
4.3%
u01 123
 
3.7%
m19 121
 
3.6%
Other values (14) 855
25.6%

점포명
Text

Distinct3148
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2023-12-12T16:17:27.530205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length5.4668666
Min length1

Characters and Unicode

Total characters18232
Distinct characters774
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

Unique3000 ?
Unique (%)90.0%

Sample

1st rowchoen
2nd rowGS25회기한양점
3rd rowJB파스타
4th rowLCOC
5th rowLG가전마트
ValueCountFrequency (%)
경희대점 74
 
2.0%
외대점 39
 
1.1%
한국외대점 8
 
0.2%
충남상회 6
 
0.2%
회기점 6
 
0.2%
전농점 6
 
0.2%
서울상회 6
 
0.2%
외대본점 6
 
0.2%
본점 5
 
0.1%
대광상회 5
 
0.1%
Other values (3246) 3503
95.6%
2023-12-12T16:17:28.028495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 528
 
2.9%
회 495
 
2.7%
대 425
 
2.3%
산 368
 
2.0%
점 350
 
1.9%
329
 
1.8%
원 300
 
1.6%
이 291
 
1.6%
한 271
 
1.5%
경 271
 
1.5%
Other values (764) 14604
80.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17415
95.5%
Space Separator 329
 
1.8%
Uppercase Letter 206
 
1.1%
Decimal Number 144
 
0.8%
Lowercase Letter 77
 
0.4%
Other Punctuation 23
 
0.1%
Close Punctuation 19
 
0.1%
Open Punctuation 19
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 528
 
3.0%
회 495
 
2.8%
대 425
 
2.4%
산 368
 
2.1%
점 350
 
2.0%
원 300
 
1.7%
이 291
 
1.7%
한 271
 
1.6%
경 271
 
1.6%
동 265
 
1.5%
Other values (703) 13851
79.5%
Uppercase Letter
ValueCountFrequency (%)
C 22
 
10.7%
S 18
 
8.7%
G 18
 
8.7%
L 16
 
7.8%
E 13
 
6.3%
O 13
 
6.3%
P 10
 
4.9%
K 10
 
4.9%
N 9
 
4.4%
A 9
 
4.4%
Other values (13) 68
33.0%
Lowercase Letter
ValueCountFrequency (%)
a 8
 
10.4%
c 7
 
9.1%
e 6
 
7.8%
o 6
 
7.8%
i 5
 
6.5%
n 5
 
6.5%
d 5
 
6.5%
b 4
 
5.2%
z 4
 
5.2%
f 4
 
5.2%
Other values (10) 23
29.9%
Decimal Number
ValueCountFrequency (%)
2 35
24.3%
1 21
14.6%
5 16
11.1%
3 16
11.1%
0 15
10.4%
4 15
10.4%
8 8
 
5.6%
9 8
 
5.6%
7 6
 
4.2%
6 4
 
2.8%
Other Punctuation
ValueCountFrequency (%)
& 18
78.3%
, 4
 
17.4%
. 1
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 17
89.5%
] 2
 
10.5%
Open Punctuation
ValueCountFrequency (%)
( 17
89.5%
[ 2
 
10.5%
Space Separator
ValueCountFrequency (%)
329
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17415
95.5%
Common 534
 
2.9%
Latin 283
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 528
 
3.0%
회 495
 
2.8%
대 425
 
2.4%
산 368
 
2.1%
점 350
 
2.0%
원 300
 
1.7%
이 291
 
1.7%
한 271
 
1.6%
경 271
 
1.6%
동 265
 
1.5%
Other values (703) 13851
79.5%
Latin
ValueCountFrequency (%)
C 22
 
7.8%
S 18
 
6.4%
G 18
 
6.4%
L 16
 
5.7%
E 13
 
4.6%
O 13
 
4.6%
P 10
 
3.5%
K 10
 
3.5%
N 9
 
3.2%
A 9
 
3.2%
Other values (33) 145
51.2%
Common
ValueCountFrequency (%)
329
61.6%
2 35
 
6.6%
1 21
 
3.9%
& 18
 
3.4%
) 17
 
3.2%
( 17
 
3.2%
5 16
 
3.0%
3 16
 
3.0%
0 15
 
2.8%
4 15
 
2.8%
Other values (8) 35
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17415
95.5%
ASCII 817
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 528
 
3.0%
회 495
 
2.8%
대 425
 
2.4%
산 368
 
2.1%
점 350
 
2.0%
원 300
 
1.7%
이 291
 
1.7%
한 271
 
1.6%
경 271
 
1.6%
동 265
 
1.5%
Other values (703) 13851
79.5%
ASCII
ValueCountFrequency (%)
329
40.3%
2 35
 
4.3%
C 22
 
2.7%
1 21
 
2.6%
S 18
 
2.2%
G 18
 
2.2%
& 18
 
2.2%
) 17
 
2.1%
( 17
 
2.1%
L 16
 
2.0%
Other values (51) 306
37.5%

운영시간
Text

MISSING 

Distinct402
Distinct (%)17.0%
Missing965
Missing (%)28.9%
Memory size26.2 KiB
2023-12-12T16:17:28.292029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length33
Mean length28.703376
Min length2

Characters and Unicode

Total characters68027
Distinct characters28
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)7.6%

Sample

1st row(평일)11:00~02:00 | (주말)11:00~02:00
2nd row(평일)00:00~24:00 | (주말)00:00~24:00
3rd row(평일)11:30~21:30 | (주말)11:30~21:30
4th row(평일)10:00~23:00 | (주말)10:00~23:00
5th row(평일)10:30~21:00 | (주말)10:30~21:00
ValueCountFrequency (%)
2040
31.6%
폐업추정 311
 
4.8%
주말)09:00~18:00 106
 
1.6%
평일)09:00~18:00 106
 
1.6%
평일)00:00~24:00 68
 
1.1%
주말)00:00~24:00 68
 
1.1%
평일)07:00~18:00 62
 
1.0%
주말)07:00~18:00 62
 
1.0%
평일)06:00~18:00 59
 
0.9%
주말)06:00~18:00 59
 
0.9%
Other values (782) 3509
54.4%
2023-12-12T16:17:28.698625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19210
28.2%
: 8054
11.8%
1 4535
 
6.7%
) 4082
 
6.0%
( 4082
 
6.0%
4080
 
6.0%
~ 4023
 
5.9%
2 2488
 
3.7%
일 2042
 
3.0%
평 2042
 
3.0%
Other values (18) 13389
19.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32216
47.4%
Other Letter 9446
 
13.9%
Other Punctuation 8054
 
11.8%
Math Symbol 6063
 
8.9%
Close Punctuation 4082
 
6.0%
Open Punctuation 4082
 
6.0%
Space Separator 4080
 
6.0%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 2042
21.6%
평 2042
21.6%
주 2040
21.6%
말 2040
21.6%
업 329
 
3.5%
폐 328
 
3.5%
정 311
 
3.3%
추 311
 
3.3%
임 1
 
< 0.1%
시 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 19210
59.6%
1 4535
 
14.1%
2 2488
 
7.7%
3 1478
 
4.6%
8 1194
 
3.7%
9 1110
 
3.4%
7 676
 
2.1%
4 632
 
2.0%
6 536
 
1.7%
5 357
 
1.1%
Math Symbol
ValueCountFrequency (%)
~ 4023
66.4%
| 2040
33.6%
Other Punctuation
ValueCountFrequency (%)
: 8054
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4082
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4082
100.0%
Space Separator
ValueCountFrequency (%)
4080
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58581
86.1%
Hangul 9446
 
13.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19210
32.8%
: 8054
13.7%
1 4535
 
7.7%
) 4082
 
7.0%
( 4082
 
7.0%
4080
 
7.0%
~ 4023
 
6.9%
2 2488
 
4.2%
| 2040
 
3.5%
3 1478
 
2.5%
Other values (7) 4509
 
7.7%
Hangul
ValueCountFrequency (%)
일 2042
21.6%
평 2042
21.6%
주 2040
21.6%
말 2040
21.6%
업 329
 
3.5%
폐 328
 
3.5%
정 311
 
3.3%
추 311
 
3.3%
임 1
 
< 0.1%
시 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58581
86.1%
Hangul 9446
 
13.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19210
32.8%
: 8054
13.7%
1 4535
 
7.7%
) 4082
 
7.0%
( 4082
 
7.0%
4080
 
7.0%
~ 4023
 
6.9%
2 2488
 
4.2%
| 2040
 
3.5%
3 1478
 
2.5%
Other values (7) 4509
 
7.7%
Hangul
ValueCountFrequency (%)
일 2042
21.6%
평 2042
21.6%
주 2040
21.6%
말 2040
21.6%
업 329
 
3.5%
폐 328
 
3.5%
정 311
 
3.3%
추 311
 
3.3%
임 1
 
< 0.1%
시 1
 
< 0.1%

업종구분
Text

MISSING 

Distinct158
Distinct (%)4.9%
Missing136
Missing (%)4.1%
Memory size26.2 KiB
2023-12-12T16:17:29.049153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.302282
Min length1

Characters and Unicode

Total characters13763
Distinct characters205
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

Unique44 ?
Unique (%)1.4%

Sample

1st row식료품
2nd row편의점
3rd row양식음식점
4th row커피-음료
5th row가전제품
ValueCountFrequency (%)
청과상 403
 
12.4%
슈퍼마켓 304
 
9.3%
한식음식점 267
 
8.2%
건강기능보조식품 187
 
5.7%
수산물판매 172
 
5.3%
의약품 159
 
4.9%
기타음식점 87
 
2.7%
커피-음료 80
 
2.5%
일반의류 76
 
2.3%
식료품 75
 
2.3%
Other values (162) 1444
44.4%
2023-12-12T16:17:29.548452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 1122
 
8.2%
점 678
 
4.9%
음 528
 
3.8%
품 509
 
3.7%
과 443
 
3.2%
기 426
 
3.1%
상 417
 
3.0%
청 409
 
3.0%
의 374
 
2.7%
한 338
 
2.5%
Other values (195) 8519
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13556
98.5%
Dash Punctuation 115
 
0.8%
Space Separator 55
 
0.4%
Other Punctuation 27
 
0.2%
Uppercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 1122
 
8.3%
점 678
 
5.0%
음 528
 
3.9%
품 509
 
3.8%
과 443
 
3.3%
기 426
 
3.1%
상 417
 
3.1%
청 409
 
3.0%
의 374
 
2.8%
한 338
 
2.5%
Other values (189) 8312
61.3%
Other Punctuation
ValueCountFrequency (%)
, 24
88.9%
/ 3
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
P 5
50.0%
C 5
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 115
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13556
98.5%
Common 197
 
1.4%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 1122
 
8.3%
점 678
 
5.0%
음 528
 
3.9%
품 509
 
3.8%
과 443
 
3.3%
기 426
 
3.1%
상 417
 
3.1%
청 409
 
3.0%
의 374
 
2.8%
한 338
 
2.5%
Other values (189) 8312
61.3%
Common
ValueCountFrequency (%)
- 115
58.4%
55
27.9%
, 24
 
12.2%
/ 3
 
1.5%
Latin
ValueCountFrequency (%)
P 5
50.0%
C 5
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13556
98.5%
ASCII 207
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 1122
 
8.3%
점 678
 
5.0%
음 528
 
3.9%
품 509
 
3.8%
과 443
 
3.3%
기 426
 
3.1%
상 417
 
3.1%
청 409
 
3.0%
의 374
 
2.8%
한 338
 
2.5%
Other values (189) 8312
61.3%
ASCII
ValueCountFrequency (%)
- 115
55.6%
55
26.6%
, 24
 
11.6%
P 5
 
2.4%
C 5
 
2.4%
/ 3
 
1.4%

도로명주소
Text

MISSING 

Distinct1360
Distinct (%)41.5%
Missing59
Missing (%)1.8%
Memory size26.2 KiB
2023-12-12T16:17:29.936438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length34
Mean length17.010073
Min length13

Characters and Unicode

Total characters55725
Distinct characters155
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

Unique709 ?
Unique (%)21.6%

Sample

1st row서울 동대문구 회기로25길 3
2nd row서울 동대문구 회기로25길 23
3rd row서울 동대문구 회기로25길 18
4th row서울 동대문구 회기로25길 26
5th row서울 동대문구 이문로 41
ValueCountFrequency (%)
동대문구 3276
25.0%
서울 3275
25.0%
고산자로36길 283
 
2.2%
약령중앙로 216
 
1.6%
3 165
 
1.3%
고산자로 153
 
1.2%
이문로 148
 
1.1%
휘경로 133
 
1.0%
회기로 127
 
1.0%
경동시장로 120
 
0.9%
Other values (746) 5206
39.7%
2023-12-12T16:17:30.502818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9826
17.6%
동 3681
 
6.6%
대 3600
 
6.5%
문 3485
 
6.3%
서 3371
 
6.0%
울 3300
 
5.9%
구 3281
 
5.9%
로 3150
 
5.7%
1 2361
 
4.2%
길 1882
 
3.4%
Other values (145) 17788
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34645
62.2%
Decimal Number 10535
 
18.9%
Space Separator 9826
 
17.6%
Dash Punctuation 599
 
1.1%
Open Punctuation 55
 
0.1%
Close Punctuation 55
 
0.1%
Uppercase Letter 6
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3681
10.6%
대 3600
10.4%
문 3485
10.1%
서 3371
9.7%
울 3300
9.5%
구 3281
9.5%
로 3150
9.1%
길 1882
 
5.4%
산 935
 
2.7%
경 793
 
2.3%
Other values (124) 7167
20.7%
Decimal Number
ValueCountFrequency (%)
1 2361
22.4%
3 1790
17.0%
2 1347
12.8%
4 1147
10.9%
6 879
 
8.3%
5 748
 
7.1%
8 677
 
6.4%
0 647
 
6.1%
7 507
 
4.8%
9 432
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
K 1
 
16.7%
A 1
 
16.7%
C 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
? 1
25.0%
. 1
25.0%
Space Separator
ValueCountFrequency (%)
9826
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 599
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34645
62.2%
Common 21074
37.8%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3681
10.6%
대 3600
10.4%
문 3485
10.1%
서 3371
9.7%
울 3300
9.5%
구 3281
9.5%
로 3150
9.1%
길 1882
 
5.4%
산 935
 
2.7%
경 793
 
2.3%
Other values (124) 7167
20.7%
Common
ValueCountFrequency (%)
9826
46.6%
1 2361
 
11.2%
3 1790
 
8.5%
2 1347
 
6.4%
4 1147
 
5.4%
6 879
 
4.2%
5 748
 
3.5%
8 677
 
3.2%
0 647
 
3.1%
- 599
 
2.8%
Other values (7) 1053
 
5.0%
Latin
ValueCountFrequency (%)
B 3
50.0%
K 1
 
16.7%
A 1
 
16.7%
C 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34645
62.2%
ASCII 21080
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9826
46.6%
1 2361
 
11.2%
3 1790
 
8.5%
2 1347
 
6.4%
4 1147
 
5.4%
6 879
 
4.2%
5 748
 
3.5%
8 677
 
3.2%
0 647
 
3.1%
- 599
 
2.8%
Other values (11) 1059
 
5.0%
Hangul
ValueCountFrequency (%)
동 3681
10.6%
대 3600
10.4%
문 3485
10.1%
서 3371
9.7%
울 3300
9.5%
구 3281
9.5%
로 3150
9.1%
길 1882
 
5.4%
산 935
 
2.7%
경 793
 
2.3%
Other values (124) 7167
20.7%

지번주소
Text

Distinct1200
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2023-12-12T16:17:30.910003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length17.130735
Min length10

Characters and Unicode

Total characters57131
Distinct characters35
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

Unique557 ?
Unique (%)16.7%

Sample

1st row서울 동대문구 회기동 57-15
2nd row서울 동대문구 회기동 54-35
3rd row서울 동대문구 회기동 348-3
4th row서울 동대문구 회기동 348-5
5th row서울 동대문구 회기동 346-13
ValueCountFrequency (%)
서울 3334
25.0%
동대문구 3334
25.0%
제기동 1689
12.7%
회기동 517
 
3.9%
이문동 378
 
2.8%
1019 252
 
1.9%
전농동 223
 
1.7%
답십리동 181
 
1.4%
용두동 127
 
1.0%
휘경동 101
 
0.8%
Other values (1196) 3202
24.0%
2023-12-12T16:17:31.394326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10003
17.5%
동 6669
11.7%
문 3712
 
6.5%
서 3334
 
5.8%
대 3334
 
5.8%
구 3334
 
5.8%
울 3334
 
5.8%
1 3165
 
5.5%
- 2532
 
4.4%
기 2206
 
3.9%
Other values (25) 15508
27.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30224
52.9%
Decimal Number 14372
25.2%
Space Separator 10003
 
17.5%
Dash Punctuation 2532
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6669
22.1%
문 3712
12.3%
서 3334
11.0%
대 3334
11.0%
구 3334
11.0%
울 3334
11.0%
기 2206
 
7.3%
제 1689
 
5.6%
회 517
 
1.7%
이 378
 
1.3%
Other values (13) 1717
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 3165
22.0%
2 1553
10.8%
0 1550
10.8%
9 1412
9.8%
5 1362
9.5%
3 1325
9.2%
6 1190
 
8.3%
8 1142
 
7.9%
4 1060
 
7.4%
7 613
 
4.3%
Space Separator
ValueCountFrequency (%)
10003
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2532
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30224
52.9%
Common 26907
47.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6669
22.1%
문 3712
12.3%
서 3334
11.0%
대 3334
11.0%
구 3334
11.0%
울 3334
11.0%
기 2206
 
7.3%
제 1689
 
5.6%
회 517
 
1.7%
이 378
 
1.3%
Other values (13) 1717
 
5.7%
Common
ValueCountFrequency (%)
10003
37.2%
1 3165
 
11.8%
- 2532
 
9.4%
2 1553
 
5.8%
0 1550
 
5.8%
9 1412
 
5.2%
5 1362
 
5.1%
3 1325
 
4.9%
6 1190
 
4.4%
8 1142
 
4.2%
Other values (2) 1673
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30224
52.9%
ASCII 26907
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10003
37.2%
1 3165
 
11.8%
- 2532
 
9.4%
2 1553
 
5.8%
0 1550
 
5.8%
9 1412
 
5.2%
5 1362
 
5.1%
3 1325
 
4.9%
6 1190
 
4.4%
8 1142
 
4.2%
Other values (2) 1673
 
6.2%
Hangul
ValueCountFrequency (%)
동 6669
22.1%
문 3712
12.3%
서 3334
11.0%
대 3334
11.0%
구 3334
11.0%
울 3334
11.0%
기 2206
 
7.3%
제 1689
 
5.6%
회 517
 
1.7%
이 378
 
1.3%
Other values (13) 1717
 
5.7%

전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
***-****-****
3335 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row***-****-****
2nd row***-****-****
3rd row***-****-****
4th row***-****-****
5th row***-****-****

Common Values

ValueCountFrequency (%)
***-****-**** 3335
100.0%

Length

2023-12-12T16:17:31.514429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:17:31.622682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3335
100.0%

종업원수
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)0.5%
Missing104
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1.4289694
Minimum-1
Maximum16
Zeros1
Zeros (%)< 0.1%
Negative1
Negative (%)< 0.1%
Memory size29.4 KiB
2023-12-12T16:17:31.713314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum16
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0116119
Coefficient of variation (CV)0.70793114
Kurtosis44.244577
Mean1.4289694
Median Absolute Deviation (MAD)0
Skewness5.1000494
Sum4617
Variance1.0233587
MonotonicityNot monotonic
2023-12-12T16:17:31.821717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 2392
71.7%
2 528
 
15.8%
3 212
 
6.4%
4 46
 
1.4%
5 23
 
0.7%
6 9
 
0.3%
7 6
 
0.2%
10 5
 
0.1%
9 2
 
0.1%
8 2
 
0.1%
Other values (6) 6
 
0.2%
(Missing) 104
 
3.1%
ValueCountFrequency (%)
-1 1
 
< 0.1%
0 1
 
< 0.1%
1 2392
71.7%
2 528
 
15.8%
3 212
 
6.4%
4 46
 
1.4%
5 23
 
0.7%
6 9
 
0.3%
7 6
 
0.2%
8 2
 
0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
15 1
 
< 0.1%
13 1
 
< 0.1%
11 1
 
< 0.1%
10 5
 
0.1%
9 2
 
0.1%
8 2
 
0.1%
7 6
 
0.2%
6 9
 
0.3%
5 23
0.7%

제로페이가능여부
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
Y
1815 
N
1238 
<NA>
281 
2
 
1

Length

Max length4
Median length1
Mean length1.2527736
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
Y 1815
54.4%
N 1238
37.1%
<NA> 281
 
8.4%
2 1
 
< 0.1%

Length

2023-12-12T16:17:32.003087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:17:32.104279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 1815
54.4%
n 1238
37.1%
na 281
 
8.4%
2 1
 
< 0.1%

지역상품권가능여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.1%
Missing417
Missing (%)12.5%
Memory size6.6 KiB
False
1672 
True
1246 
(Missing)
417 
ValueCountFrequency (%)
False 1672
50.1%
True 1246
37.4%
(Missing) 417
 
12.5%
2023-12-12T16:17:32.182990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

스프링클러설치여부
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
N
1493 
Y
993 
<NA>
848 
-
 
1

Length

Max length4
Median length1
Mean length1.7628186
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
N 1493
44.8%
Y 993
29.8%
<NA> 848
25.4%
- 1
 
< 0.1%

Length

2023-12-12T16:17:32.293410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:17:32.383413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 1493
44.8%
y 993
29.8%
na 848
25.4%
1
 
< 0.1%

화재감지시설여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.1%
Missing850
Missing (%)25.5%
Memory size6.6 KiB
True
1501 
False
984 
(Missing)
850 
ValueCountFrequency (%)
True 1501
45.0%
False 984
29.5%
(Missing) 850
25.5%
2023-12-12T16:17:32.463110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

소화전설치여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing772
Missing (%)23.1%
Memory size6.6 KiB
True
2354 
False
 
209
(Missing)
772 
ValueCountFrequency (%)
True 2354
70.6%
False 209
 
6.3%
(Missing) 772
 
23.1%
2023-12-12T16:17:32.538723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1253
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.583625
Minimum37.566479
Maximum37.604956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.4 KiB
2023-12-12T16:17:32.923606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.566479
5-th percentile37.573262
Q137.579038
median37.580801
Q337.591068
95-th percentile37.595605
Maximum37.604956
Range0.038477
Interquartile range (IQR)0.01203055

Descriptive statistics

Standard deviation0.0072951536
Coefficient of variation (CV)0.00019410458
Kurtosis-0.060047151
Mean37.583625
Median Absolute Deviation (MAD)0.00242421
Skewness0.36239531
Sum125341.39
Variance5.3219267 × 10-5
MonotonicityNot monotonic
2023-12-12T16:17:33.102354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.57903777 189
 
5.7%
37.57916385 43
 
1.3%
37.57878423 32
 
1.0%
37.5797955 32
 
1.0%
37.56692137 29
 
0.9%
37.56757575 24
 
0.7%
37.5804913 24
 
0.7%
37.58003487 23
 
0.7%
37.5795534 23
 
0.7%
37.57804036 20
 
0.6%
Other values (1243) 2896
86.8%
ValueCountFrequency (%)
37.56647917 1
 
< 0.1%
37.56662372 2
 
0.1%
37.56668275 1
 
< 0.1%
37.56669189 2
 
0.1%
37.56683176 1
 
< 0.1%
37.56692137 29
0.9%
37.56694383 1
 
< 0.1%
37.56695297 1
 
< 0.1%
37.5669901 3
 
0.1%
37.56699891 1
 
< 0.1%
ValueCountFrequency (%)
37.60495617 1
 
< 0.1%
37.60493327 1
 
< 0.1%
37.60488534 4
 
0.1%
37.60483672 1
 
< 0.1%
37.6048095 1
 
< 0.1%
37.60477074 3
 
0.1%
37.60458841 1
 
< 0.1%
37.60455567 6
 
0.2%
37.60440373 17
0.5%
37.60409164 1
 
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1248
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04724
Minimum127.02935
Maximum127.06934
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.4 KiB
2023-12-12T16:17:33.301995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02935
5-th percentile127.03678
Q1127.03914
median127.04203
Q3127.05509
95-th percentile127.06249
Maximum127.06934
Range0.0399892
Interquartile range (IQR)0.0159466

Descriptive statistics

Standard deviation0.0094744024
Coefficient of variation (CV)7.4573857 × 10-5
Kurtosis-1.0750619
Mean127.04724
Median Absolute Deviation (MAD)0.0052017
Skewness0.51452735
Sum423702.53
Variance8.9764301 × 10-5
MonotonicityNot monotonic
2023-12-12T16:17:33.513136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0391429 189
 
5.7%
127.039313 43
 
1.3%
127.041519 32
 
1.0%
127.0396587 32
 
1.0%
127.0590711 29
 
0.9%
127.0522092 24
 
0.7%
127.0387004 24
 
0.7%
127.0414691 23
 
0.7%
127.0386776 23
 
0.7%
127.0563148 20
 
0.6%
Other values (1238) 2896
86.8%
ValueCountFrequency (%)
127.0293469 1
 
< 0.1%
127.0294892 4
0.1%
127.0295199 1
 
< 0.1%
127.0295518 8
0.2%
127.0351452 3
 
0.1%
127.0356168 3
 
0.1%
127.0358168 4
0.1%
127.0358756 1
 
< 0.1%
127.0358881 1
 
< 0.1%
127.0359704 1
 
< 0.1%
ValueCountFrequency (%)
127.0693361 3
0.1%
127.0693127 1
 
< 0.1%
127.0692741 1
 
< 0.1%
127.0692577 1
 
< 0.1%
127.0692134 1
 
< 0.1%
127.069185 3
0.1%
127.0691371 3
0.1%
127.0691261 1
 
< 0.1%
127.0691117 5
0.1%
127.0690979 1
 
< 0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2022-12-12
3335 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-12
2nd row2022-12-12
3rd row2022-12-12
4th row2022-12-12
5th row2022-12-12

Common Values

ValueCountFrequency (%)
2022-12-12 3335
100.0%

Length

2023-12-12T16:17:33.712180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:17:33.830342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-12 3335
100.0%

이미지명
Text

UNIQUE 

Distinct3335
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2023-12-12T16:17:34.044062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length14.466867
Min length10

Characters and Unicode

Total characters48247
Distinct characters775
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

Unique3335 ?
Unique (%)100.0%

Sample

1st rowM01F0001_choen
2nd rowM01F0002_GS25회기한양점
3rd rowM01F0003_JB파스타
4th rowM01F0004_LCOC
5th rowM01F0005_LG가전마트
ValueCountFrequency (%)
경희대점 74
 
2.0%
외대점 39
 
1.1%
한국외대점 8
 
0.2%
회기점 6
 
0.2%
외대본점 6
 
0.2%
전농점 6
 
0.2%
외대역점 5
 
0.1%
본점 5
 
0.1%
외대앞역점 4
 
0.1%
청량리점 3
 
0.1%
Other values (3486) 3508
95.7%
2023-12-12T16:17:34.427798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7926
 
16.4%
1 3922
 
8.1%
F 3342
 
6.9%
_ 3335
 
6.9%
M 2423
 
5.0%
2 1860
 
3.9%
4 1222
 
2.5%
3 1128
 
2.3%
8 1054
 
2.2%
U 925
 
1.9%
Other values (765) 21110
43.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20154
41.8%
Other Letter 17415
36.1%
Uppercase Letter 6876
 
14.3%
Connector Punctuation 3335
 
6.9%
Space Separator 329
 
0.7%
Lowercase Letter 77
 
0.2%
Other Punctuation 23
 
< 0.1%
Open Punctuation 19
 
< 0.1%
Close Punctuation 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 528
 
3.0%
회 495
 
2.8%
대 425
 
2.4%
산 368
 
2.1%
점 350
 
2.0%
원 300
 
1.7%
이 291
 
1.7%
경 271
 
1.6%
한 271
 
1.6%
동 265
 
1.5%
Other values (703) 13851
79.5%
Uppercase Letter
ValueCountFrequency (%)
F 3342
48.6%
M 2423
35.2%
U 925
 
13.5%
C 22
 
0.3%
S 18
 
0.3%
G 18
 
0.3%
L 16
 
0.2%
E 13
 
0.2%
O 13
 
0.2%
P 10
 
0.1%
Other values (13) 76
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
a 8
 
10.4%
c 7
 
9.1%
e 6
 
7.8%
o 6
 
7.8%
d 5
 
6.5%
i 5
 
6.5%
n 5
 
6.5%
b 4
 
5.2%
f 4
 
5.2%
z 4
 
5.2%
Other values (10) 23
29.9%
Decimal Number
ValueCountFrequency (%)
0 7926
39.3%
1 3922
19.5%
2 1860
 
9.2%
4 1222
 
6.1%
3 1128
 
5.6%
8 1054
 
5.2%
5 872
 
4.3%
9 835
 
4.1%
6 676
 
3.4%
7 659
 
3.3%
Other Punctuation
ValueCountFrequency (%)
& 18
78.3%
, 4
 
17.4%
. 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 17
89.5%
[ 2
 
10.5%
Close Punctuation
ValueCountFrequency (%)
) 17
89.5%
] 2
 
10.5%
Connector Punctuation
ValueCountFrequency (%)
_ 3335
100.0%
Space Separator
ValueCountFrequency (%)
329
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23879
49.5%
Hangul 17415
36.1%
Latin 6953
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 528
 
3.0%
회 495
 
2.8%
대 425
 
2.4%
산 368
 
2.1%
점 350
 
2.0%
원 300
 
1.7%
이 291
 
1.7%
경 271
 
1.6%
한 271
 
1.6%
동 265
 
1.5%
Other values (703) 13851
79.5%
Latin
ValueCountFrequency (%)
F 3342
48.1%
M 2423
34.8%
U 925
 
13.3%
C 22
 
0.3%
S 18
 
0.3%
G 18
 
0.3%
L 16
 
0.2%
E 13
 
0.2%
O 13
 
0.2%
P 10
 
0.1%
Other values (33) 153
 
2.2%
Common
ValueCountFrequency (%)
0 7926
33.2%
1 3922
16.4%
_ 3335
14.0%
2 1860
 
7.8%
4 1222
 
5.1%
3 1128
 
4.7%
8 1054
 
4.4%
5 872
 
3.7%
9 835
 
3.5%
6 676
 
2.8%
Other values (9) 1049
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30832
63.9%
Hangul 17415
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7926
25.7%
1 3922
12.7%
F 3342
10.8%
_ 3335
10.8%
M 2423
 
7.9%
2 1860
 
6.0%
4 1222
 
4.0%
3 1128
 
3.7%
8 1054
 
3.4%
U 925
 
3.0%
Other values (52) 3695
12.0%
Hangul
ValueCountFrequency (%)
상 528
 
3.0%
회 495
 
2.8%
대 425
 
2.4%
산 368
 
2.1%
점 350
 
2.0%
원 300
 
1.7%
이 291
 
1.7%
경 271
 
1.6%
한 271
 
1.6%
동 265
 
1.5%
Other values (703) 13851
79.5%

Interactions

2023-12-12T16:17:25.781029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:24.208489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:24.732849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:25.204355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:25.893868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:24.330269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:24.836310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:25.349379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:25.990895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:24.443720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:24.938697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:25.489147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:26.145661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:24.601346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:25.076210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:25.646152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:17:34.563570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번아이디종업원수제로페이가능여부지역상품권가능여부스프링클러설치여부화재감지시설여부소화전설치여부위도경도
연번1.0000.6590.0000.1270.2560.2230.2330.1150.3580.517
아이디0.6591.0000.3090.5330.6490.7690.7810.6540.9800.964
종업원수0.0000.3091.0000.0180.1300.0000.0950.1050.1430.214
제로페이가능여부0.1270.5330.0181.0000.3200.2600.0870.1260.3610.236
지역상품권가능여부0.2560.6490.1300.3201.0000.0430.3350.3200.2810.363
스프링클러설치여부0.2230.7690.0000.2600.0431.0000.3960.1360.5450.502
화재감지시설여부0.2330.7810.0950.0870.3350.3961.0000.3950.3750.465
소화전설치여부0.1150.6540.1050.1260.3200.1360.3951.0000.3310.202
위도0.3580.9800.1430.3610.2810.5450.3750.3311.0000.793
경도0.5170.9640.2140.2360.3630.5020.4650.2020.7931.000
2023-12-12T16:17:34.714274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
화재감지시설여부소화전설치여부제로페이가능여부스프링클러설치여부지역상품권가능여부아이디
화재감지시설여부1.0000.2580.1440.6250.2180.638
소화전설치여부0.2581.0000.2090.2250.2070.524
제로페이가능여부0.1440.2091.0000.0850.5150.291
스프링클러설치여부0.6250.2250.0851.0000.0710.505
지역상품권가능여부0.2180.2070.5150.0711.0000.520
아이디0.6380.5240.2910.5050.5201.000
2023-12-12T16:17:34.834671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종업원수위도경도아이디제로페이가능여부지역상품권가능여부스프링클러설치여부화재감지시설여부소화전설치여부
연번1.000-0.0420.188-0.3380.3080.0760.1960.1360.1780.088
종업원수-0.0421.0000.0710.0780.1180.0100.0990.0000.0720.081
위도0.1880.0711.0000.3180.8790.1700.2800.2850.3750.330
경도-0.3380.0780.3181.0000.8080.1450.2780.3480.3570.155
아이디0.3080.1180.8790.8081.0000.2910.5200.5050.6380.524
제로페이가능여부0.0760.0100.1700.1450.2911.0000.5150.0850.1440.209
지역상품권가능여부0.1960.0990.2800.2780.5200.5151.0000.0710.2180.207
스프링클러설치여부0.1360.0000.2850.3480.5050.0850.0711.0000.6250.225
화재감지시설여부0.1780.0720.3750.3570.6380.1440.2180.6251.0000.258
소화전설치여부0.0880.0810.3300.1550.5240.2090.2070.2250.2581.000

Missing values

2023-12-12T16:17:26.312059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:17:26.546356image/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.
2023-12-12T16:17:26.743468image/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

연번아이디점포명운영시간업종구분도로명주소지번주소전화번호종업원수제로페이가능여부지역상품권가능여부스프링클러설치여부화재감지시설여부소화전설치여부위도경도데이터기준일자이미지명
01M01choen(평일)11:00~02:00 | (주말)11:00~02:00식료품서울 동대문구 회기로25길 3서울 동대문구 회기동 57-15***-****-****1NNNNY37.590758127.054642022-12-12M01F0001_choen
12M01GS25회기한양점(평일)00:00~24:00 | (주말)00:00~24:00편의점서울 동대문구 회기로25길 23서울 동대문구 회기동 54-35***-****-****6YNNYY37.591209127.0556722022-12-12M01F0002_GS25회기한양점
23M01JB파스타(평일)11:30~21:30 | (주말)11:30~21:30양식음식점서울 동대문구 회기로25길 18서울 동대문구 회기동 348-3***-****-****1YYNNY37.590971127.0554532022-12-12M01F0003_JB파스타
34M01LCOC(평일)10:00~23:00 | (주말)10:00~23:00커피-음료서울 동대문구 회기로25길 26서울 동대문구 회기동 348-5***-****-****1YNNNY37.591111127.0558142022-12-12M01F0004_LCOC
45M01LG가전마트<NA>가전제품서울 동대문구 이문로 41서울 동대문구 회기동 346-13***-****-****1Y<NA><NA><NA><NA>37.591263127.0565732022-12-12M01F0005_LG가전마트
56M01LG유플러스 회기동 회기역사거리점<NA>핸드폰서울 동대문구 이문로 29서울 동대문구 회기동 346-7***-****-****1Y<NA><NA><NA><NA>37.590316127.055932022-12-12M01F0006_LG유플러스 회기동 회기역사거리점
67M01경희옷박사(평일)10:30~21:00 | (주말)10:30~21:00일반의류서울 동대문구 경희대로4길 73서울 동대문구 이문동 339-4***-****-****1<NA><NA><NA><NA><NA>37.591391127.0562872022-12-12M01F0007_경희옷박사
78M01경희의지보조기<NA>의료기기서울 동대문구 경희대로4길 76서울 동대문구 회기동 346-14***-****-****1Y<NA><NA><NA><NA>37.591252127.0564612022-12-12M01F0008_경희의지보조기
89M01고기하다(평일)12:00~24:00 | (주말)12:00~24:00한식음식점서울 동대문구 경희대로4길 64서울 동대문구 회기동 54-16***-****-****16YNNNY37.591309127.0556492022-12-12M01F0009_고기하다
910M01국민약국<NA>의약품서울 동대문구 이문로 37서울 동대문구 회기동 346-18***-****-****1Y<NA><NA><NA><NA>37.590801127.0561172022-12-12M01F0010_국민약국
연번아이디점포명운영시간업종구분도로명주소지번주소전화번호종업원수제로페이가능여부지역상품권가능여부스프링클러설치여부화재감지시설여부소화전설치여부위도경도데이터기준일자이미지명
3325312U04헤어닥터(평일)10:00~20:30 | (주말)10:00~20:30미용실서울 동대문구 휘경로 20-1서울 동대문구 이문동 305-140***-****-****2YYNYY37.595431127.062162022-12-12U04F0312_헤어닥터
3326313U04헤어살롱아미쿠스(평일)10:00~20:00 | (주말)10:00~20:00미용실서울 동대문구 이문로 78서울 동대문구 이문동 336-2***-****-****1NNYYY37.593852127.0587542022-12-12U04F0313_헤어살롱아미쿠스
3327314U04헤어코스<NA>미용실서울 동대문구 이문로16길 21서울 동대문구 이문동 325-49***-****-****1YYNNY37.594354127.0598372022-12-12U04F0314_헤어코스
3328315U04헤픈커피 이문점(평일)10:00~21:00 | (주말)10:00~21:00커피-음료서울 동대문구 휘경로 26-7서울 동대문구 이문동 306-11***-****-****1NNNYY37.5949127.0623682022-12-12U04F0315_헤픈커피 이문점
3329316U04현수막실사출력종합철물(평일)09:00~19:00 | (주말)09:00~19:00철물점서울 동대문구 이문로 88-24서울 동대문구 이문동 325-43***-****-****1NNNNY37.594768127.0597372022-12-12U04F0316_현수막실사출력종합철물
3330317U04호랑이초밥 외대직영점(평일)10:00~22:00 | (주말)10:00~22:00일식음식점서울 동대문구 휘경로 8서울 동대문구 이문동 288-48***-****-****1NN<NA><NA>Y37.596023127.0609022022-12-12U04F0317_호랑이초밥 외대직영점
3331318U04홍익광고(평일)09:00~18:00 | (주말)09:00~18:00광고물 제조서울 동대문구 이문로 92서울 동대문구 이문동 326-5***-****-****1YYNNY37.595074127.0596182022-12-12U04F0318_홍익광고
3332319U04홍콩반점0410 외대점(평일)10:30~21:00 | (주말)10:30~21:00중식음식점서울 동대문구 휘경로 17서울 동대문구 이문동 305-152***-****-****3YYNNY37.595785127.0621742022-12-12U04F0319_홍콩반점0410 외대점
3333320U04화덕고(평일)16:30~23:00 | (주말)16:30~23:00한식음식점서울 동대문구 이문로 88-13서울 동대문구 이문동 326-10***-****-****2YYNYY37.594952127.059822022-12-12U04F0320_화덕고
3334321U04휘경사진관(평일)09:30~20:30 | (주말)09:30~20:30사진관서울 동대문구 휘경로 17서울 동대문구 이문동 305-152***-****-****1NNNNY37.595785127.0621742022-12-12U04F0321_휘경사진관