Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells4870
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory810.5 KiB
Average record size in memory83.0 B

Variable types

Numeric3
Text2
Categorical4

Dataset

Description부산광역시 동래구에 소재한 옥외광고물 전수조사 정보에 대한 데이터로 상호명, 광고물종류, 수량, 시도, 구군, 읍면동, 도로명, 건물번호 등의 항목을 제공하고 있습니다.
Author부산광역시 동래구
URLhttps://www.data.go.kr/data/15086604/fileData.do

Alerts

시도 has constant value ""Constant
구군 has constant value ""Constant
도로명 has 333 (3.3%) missing valuesMissing
건물1 has 333 (3.3%) missing valuesMissing
건물2 has 4204 (42.0%) missing valuesMissing
순번 has unique valuesUnique
건물2 has 4429 (44.3%) zerosZeros

Reproduction

Analysis started2024-03-14 12:44:55.475177
Analysis finished2024-03-14 12:45:00.175812
Duration4.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7591.7838
Minimum1
Maximum15109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:45:00.385663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile763.95
Q13825.5
median7586
Q311385.5
95-th percentile14371.05
Maximum15109
Range15108
Interquartile range (IQR)7560

Descriptive statistics

Standard deviation4363.3836
Coefficient of variation (CV)0.57475077
Kurtosis-1.1942407
Mean7591.7838
Median Absolute Deviation (MAD)3780.5
Skewness-0.0058470866
Sum75917838
Variance19039116
MonotonicityNot monotonic
2024-03-14T21:45:00.822271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11617 1
 
< 0.1%
3965 1
 
< 0.1%
8719 1
 
< 0.1%
8901 1
 
< 0.1%
4786 1
 
< 0.1%
5504 1
 
< 0.1%
3325 1
 
< 0.1%
4011 1
 
< 0.1%
8 1
 
< 0.1%
4538 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
15109 1
< 0.1%
15107 1
< 0.1%
15106 1
< 0.1%
15105 1
< 0.1%
15103 1
< 0.1%
15102 1
< 0.1%
15101 1
< 0.1%
15099 1
< 0.1%
15098 1
< 0.1%
15093 1
< 0.1%

업소명
Text

Distinct6045
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T21:45:02.016046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length6.4729
Min length1

Characters and Unicode

Total characters64729
Distinct characters964
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3333 ?
Unique (%)33.3%

Sample

1st row해동 노래방
2nd row바다부동산
3rd row희망통닭
4th row손찬반찬백화점
5th row시장손칼국수
ValueCountFrequency (%)
동래점 120
 
1.0%
노래방 59
 
0.5%
명장점 55
 
0.5%
온천점 49
 
0.4%
수안점 27
 
0.2%
cu 26
 
0.2%
온천장점 25
 
0.2%
부산온천점 24
 
0.2%
부산동래점 23
 
0.2%
gs25 21
 
0.2%
Other values (6419) 11319
96.3%
2024-03-14T21:45:03.590436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1754
 
2.7%
동 1535
 
2.4%
래 1283
 
2.0%
점 1262
 
1.9%
원 1057
 
1.6%
스 1014
 
1.6%
산 975
 
1.5%
이 942
 
1.5%
장 892
 
1.4%
부 892
 
1.4%
Other values (954) 53123
82.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57928
89.5%
Uppercase Letter 2687
 
4.2%
Space Separator 1754
 
2.7%
Lowercase Letter 853
 
1.3%
Decimal Number 698
 
1.1%
Open Punctuation 320
 
0.5%
Close Punctuation 318
 
0.5%
Other Punctuation 127
 
0.2%
Dash Punctuation 25
 
< 0.1%
Math Symbol 9
 
< 0.1%
Other values (3) 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1535
 
2.6%
래 1283
 
2.2%
점 1262
 
2.2%
원 1057
 
1.8%
스 1014
 
1.8%
산 975
 
1.7%
이 942
 
1.6%
장 892
 
1.5%
부 892
 
1.5%
리 858
 
1.5%
Other values (872) 47218
81.5%
Uppercase Letter
ValueCountFrequency (%)
S 253
 
9.4%
E 206
 
7.7%
O 198
 
7.4%
C 191
 
7.1%
A 181
 
6.7%
G 151
 
5.6%
T 143
 
5.3%
N 127
 
4.7%
B 122
 
4.5%
M 116
 
4.3%
Other values (16) 999
37.2%
Lowercase Letter
ValueCountFrequency (%)
e 134
15.7%
a 95
11.1%
o 76
 
8.9%
t 59
 
6.9%
r 59
 
6.9%
l 44
 
5.2%
i 43
 
5.0%
s 43
 
5.0%
h 41
 
4.8%
c 40
 
4.7%
Other values (16) 219
25.7%
Decimal Number
ValueCountFrequency (%)
2 152
21.8%
5 105
15.0%
1 97
13.9%
0 80
11.5%
3 66
9.5%
4 56
 
8.0%
9 41
 
5.9%
8 38
 
5.4%
6 34
 
4.9%
7 29
 
4.2%
Other Punctuation
ValueCountFrequency (%)
& 64
50.4%
. 33
26.0%
# 10
 
7.9%
, 7
 
5.5%
/ 5
 
3.9%
· 3
 
2.4%
! 3
 
2.4%
: 2
 
1.6%
Open Punctuation
ValueCountFrequency (%)
( 305
95.3%
[ 15
 
4.7%
Close Punctuation
ValueCountFrequency (%)
) 303
95.3%
] 15
 
4.7%
Math Symbol
ValueCountFrequency (%)
+ 5
55.6%
| 4
44.4%
Other Symbol
ValueCountFrequency (%)
● 2
66.7%
◆ 1
33.3%
Space Separator
ValueCountFrequency (%)
1754
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57904
89.5%
Latin 3542
 
5.5%
Common 3259
 
5.0%
Han 24
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1535
 
2.7%
래 1283
 
2.2%
점 1262
 
2.2%
원 1057
 
1.8%
스 1014
 
1.8%
산 975
 
1.7%
이 942
 
1.6%
장 892
 
1.5%
부 892
 
1.5%
리 858
 
1.5%
Other values (858) 47194
81.5%
Latin
ValueCountFrequency (%)
S 253
 
7.1%
E 206
 
5.8%
O 198
 
5.6%
C 191
 
5.4%
A 181
 
5.1%
G 151
 
4.3%
T 143
 
4.0%
e 134
 
3.8%
N 127
 
3.6%
B 122
 
3.4%
Other values (43) 1836
51.8%
Common
ValueCountFrequency (%)
1754
53.8%
( 305
 
9.4%
) 303
 
9.3%
2 152
 
4.7%
5 105
 
3.2%
1 97
 
3.0%
0 80
 
2.5%
3 66
 
2.0%
& 64
 
2.0%
4 56
 
1.7%
Other values (19) 277
 
8.5%
Han
ValueCountFrequency (%)
秀 5
20.8%
愛 3
12.5%
眞 3
12.5%
味 2
 
8.3%
美 2
 
8.3%
音 1
 
4.2%
知 1
 
4.2%
本 1
 
4.2%
代 1
 
4.2%
三 1
 
4.2%
Other values (4) 4
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57894
89.4%
ASCII 6793
 
10.5%
CJK 24
 
< 0.1%
Compat Jamo 10
 
< 0.1%
None 3
 
< 0.1%
Geometric Shapes 3
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1754
25.8%
( 305
 
4.5%
) 303
 
4.5%
S 253
 
3.7%
E 206
 
3.0%
O 198
 
2.9%
C 191
 
2.8%
A 181
 
2.7%
2 152
 
2.2%
G 151
 
2.2%
Other values (68) 3099
45.6%
Hangul
ValueCountFrequency (%)
동 1535
 
2.7%
래 1283
 
2.2%
점 1262
 
2.2%
원 1057
 
1.8%
스 1014
 
1.8%
산 975
 
1.7%
이 942
 
1.6%
장 892
 
1.5%
부 892
 
1.5%
리 858
 
1.5%
Other values (853) 47184
81.5%
CJK
ValueCountFrequency (%)
秀 5
20.8%
愛 3
12.5%
眞 3
12.5%
味 2
 
8.3%
美 2
 
8.3%
音 1
 
4.2%
知 1
 
4.2%
本 1
 
4.2%
代 1
 
4.2%
三 1
 
4.2%
Other values (4) 4
16.7%
Compat Jamo
ValueCountFrequency (%)
ㆍ 5
50.0%
ㅇ 2
 
20.0%
ㄹ 1
 
10.0%
ㅋ 1
 
10.0%
ㅅ 1
 
10.0%
None
ValueCountFrequency (%)
· 3
100.0%
Geometric Shapes
ValueCountFrequency (%)
● 2
66.7%
◆ 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

광고물종류
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가로형간판
3653 
돌출간판
2983 
가로형간판_입체형
2427 
세로형간판
465 
지주이용 간판
427 

Length

Max length9
Median length7
Mean length5.7534
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가로형간판_입체형
2nd row세로형간판
3rd row가로형간판_입체형
4th row가로형간판_입체형
5th row가로형간판

Common Values

ValueCountFrequency (%)
가로형간판 3653
36.5%
돌출간판 2983
29.8%
가로형간판_입체형 2427
24.3%
세로형간판 465
 
4.7%
지주이용 간판 427
 
4.3%
옥상간판 45
 
0.4%

Length

2024-03-14T21:45:04.019081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:45:04.358888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가로형간판 3653
35.0%
돌출간판 2983
28.6%
가로형간판_입체형 2427
23.3%
세로형간판 465
 
4.5%
지주이용 427
 
4.1%
간판 427
 
4.1%
옥상간판 45
 
0.4%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부산광역시
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 10000
100.0%

Length

2024-03-14T21:45:04.731018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:45:05.028162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 10000
100.0%

구군
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
동래구
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동래구 10000
100.0%

Length

2024-03-14T21:45:05.334243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:45:05.622723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동래구 10000
100.0%

읍면동
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
온천동
5523 
명장동
1704 
수안동
1592 
낙민동
591 
복천동
 
435

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row온천동
2nd row수안동
3rd row낙민동
4th row온천동
5th row복천동

Common Values

ValueCountFrequency (%)
온천동 5523
55.2%
명장동 1704
 
17.0%
수안동 1592
 
15.9%
낙민동 591
 
5.9%
복천동 435
 
4.3%
칠산동 155
 
1.6%

Length

2024-03-14T21:45:05.930506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:45:06.242120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온천동 5523
55.2%
명장동 1704
 
17.0%
수안동 1592
 
15.9%
낙민동 591
 
5.9%
복천동 435
 
4.3%
칠산동 155
 
1.6%

도로명
Text

MISSING 

Distinct234
Distinct (%)2.4%
Missing333
Missing (%)3.3%
Memory size156.2 KiB
2024-03-14T21:45:07.031990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.4242268
Min length3

Characters and Unicode

Total characters62103
Distinct characters67
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

Unique11 ?
Unique (%)0.1%

Sample

1st row금강로
2nd row명륜로98번길
3rd row명륜로98번길
4th row금강공원로
5th row충렬대로237번길
ValueCountFrequency (%)
충렬대로 673
 
7.0%
금강로 474
 
4.9%
온천장로 328
 
3.4%
금강공원로 323
 
3.3%
아시아드대로 309
 
3.2%
충렬대로237번길 244
 
2.5%
반송로 211
 
2.2%
중앙대로1367번길 204
 
2.1%
충렬대로107번길 204
 
2.1%
명륜로98번길 195
 
2.0%
Other values (224) 6502
67.3%
2024-03-14T21:45:08.266469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 9632
 
15.5%
길 5435
 
8.8%
번 5400
 
8.7%
1 3369
 
5.4%
대 3297
 
5.3%
2 2555
 
4.1%
충 2053
 
3.3%
렬 2053
 
3.3%
명 1844
 
3.0%
3 1823
 
2.9%
Other values (57) 24642
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47374
76.3%
Decimal Number 14729
 
23.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 9632
20.3%
길 5435
 
11.5%
번 5400
 
11.4%
대 3297
 
7.0%
충 2053
 
4.3%
렬 2053
 
4.3%
명 1844
 
3.9%
장 1367
 
2.9%
아 1262
 
2.7%
천 1238
 
2.6%
Other values (47) 13793
29.1%
Decimal Number
ValueCountFrequency (%)
1 3369
22.9%
2 2555
17.3%
3 1823
12.4%
7 1450
9.8%
8 1228
 
8.3%
0 1203
 
8.2%
9 810
 
5.5%
6 798
 
5.4%
5 788
 
5.3%
4 705
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47374
76.3%
Common 14729
 
23.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 9632
20.3%
길 5435
 
11.5%
번 5400
 
11.4%
대 3297
 
7.0%
충 2053
 
4.3%
렬 2053
 
4.3%
명 1844
 
3.9%
장 1367
 
2.9%
아 1262
 
2.7%
천 1238
 
2.6%
Other values (47) 13793
29.1%
Common
ValueCountFrequency (%)
1 3369
22.9%
2 2555
17.3%
3 1823
12.4%
7 1450
9.8%
8 1228
 
8.3%
0 1203
 
8.2%
9 810
 
5.5%
6 798
 
5.4%
5 788
 
5.3%
4 705
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47374
76.3%
ASCII 14729
 
23.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 9632
20.3%
길 5435
 
11.5%
번 5400
 
11.4%
대 3297
 
7.0%
충 2053
 
4.3%
렬 2053
 
4.3%
명 1844
 
3.9%
장 1367
 
2.9%
아 1262
 
2.7%
천 1238
 
2.6%
Other values (47) 13793
29.1%
ASCII
ValueCountFrequency (%)
1 3369
22.9%
2 2555
17.3%
3 1823
12.4%
7 1450
9.8%
8 1228
 
8.3%
0 1203
 
8.2%
9 810
 
5.5%
6 798
 
5.4%
5 788
 
5.3%
4 705
 
4.8%

건물1
Real number (ℝ)

MISSING 

Distinct325
Distinct (%)3.4%
Missing333
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean104.29658
Minimum1
Maximum1523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:45:08.610967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q121
median50
Q3109
95-th percentile277.7
Maximum1523
Range1522
Interquartile range (IQR)88

Descriptive statistics

Standard deviation205.36815
Coefficient of variation (CV)1.9690785
Kurtosis32.826593
Mean104.29658
Median Absolute Deviation (MAD)36
Skewness5.4838587
Sum1008235
Variance42176.076
MonotonicityNot monotonic
2024-03-14T21:45:08.921222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 177
 
1.8%
14 171
 
1.7%
8 164
 
1.6%
11 159
 
1.6%
28 145
 
1.5%
7 144
 
1.4%
5 139
 
1.4%
6 132
 
1.3%
25 127
 
1.3%
22 127
 
1.3%
Other values (315) 8182
81.8%
(Missing) 333
 
3.3%
ValueCountFrequency (%)
1 79
0.8%
2 117
1.2%
3 177
1.8%
4 95
0.9%
5 139
1.4%
6 132
1.3%
7 144
1.4%
8 164
1.6%
9 102
1.0%
10 126
1.3%
ValueCountFrequency (%)
1523 72
0.7%
1495 6
 
0.1%
1491 2
 
< 0.1%
1487 6
 
0.1%
1483 1
 
< 0.1%
1481 4
 
< 0.1%
1465 2
 
< 0.1%
1459 4
 
< 0.1%
1455 2
 
< 0.1%
1453 3
 
< 0.1%

건물2
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)0.5%
Missing4204
Missing (%)42.0%
Infinite0
Infinite (%)0.0%
Mean1.097481
Minimum0
Maximum32
Zeros4429
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:45:09.285868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum32
Range32
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.3531802
Coefficient of variation (CV)3.0553423
Kurtosis23.636202
Mean1.097481
Median Absolute Deviation (MAD)0
Skewness4.5365721
Sum6361
Variance11.243818
MonotonicityNot monotonic
2024-03-14T21:45:09.693191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 4429
44.3%
1 586
 
5.9%
4 133
 
1.3%
2 128
 
1.3%
3 125
 
1.2%
6 64
 
0.6%
12 39
 
0.4%
5 38
 
0.4%
9 34
 
0.3%
13 26
 
0.3%
Other values (21) 194
 
1.9%
(Missing) 4204
42.0%
ValueCountFrequency (%)
0 4429
44.3%
1 586
 
5.9%
2 128
 
1.3%
3 125
 
1.2%
4 133
 
1.3%
5 38
 
0.4%
6 64
 
0.6%
7 20
 
0.2%
8 25
 
0.2%
9 34
 
0.3%
ValueCountFrequency (%)
32 3
 
< 0.1%
31 1
 
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
26 2
 
< 0.1%
25 2
 
< 0.1%
24 8
0.1%
23 11
0.1%
22 4
 
< 0.1%
21 13
0.1%

Interactions

2024-03-14T21:44:58.298644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:44:56.598688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:44:57.473272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:44:58.571824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:44:56.917022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:44:57.753741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:44:58.845330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:44:57.198401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:44:58.029342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:45:09.933995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번광고물종류읍면동건물1건물2
순번1.0000.1810.4950.2490.478
광고물종류0.1811.0000.2210.0700.101
읍면동0.4950.2211.0000.2740.099
건물10.2490.0700.2741.0000.204
건물20.4780.1010.0990.2041.000
2024-03-14T21:45:10.100515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동광고물종류
읍면동1.0000.082
광고물종류0.0821.000
2024-03-14T21:45:10.327186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번건물1건물2광고물종류읍면동
순번1.0000.001-0.3770.0960.287
건물10.0011.0000.0470.0470.189
건물2-0.3770.0471.0000.0520.052
광고물종류0.0960.0470.0521.0000.082
읍면동0.2870.1890.0520.0821.000

Missing values

2024-03-14T21:44:59.215177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:44:59.668877image/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.
2024-03-14T21:45:00.008432image/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

순번업소명광고물종류시도구군읍면동도로명건물1건물2
1161611617해동 노래방가로형간판_입체형부산광역시동래구온천동금강로1286
56525653바다부동산세로형간판부산광역시동래구수안동명륜로98번길34<NA>
88528853희망통닭가로형간판_입체형부산광역시동래구낙민동명륜로98번길940
23722373손찬반찬백화점가로형간판_입체형부산광역시동래구온천동금강공원로10<NA>
46434644시장손칼국수가로형간판부산광역시동래구복천동충렬대로237번길96<NA>
9495휴대폰잘하는집세로형간판부산광역시동래구낙민동충렬대로306<NA>
66506651강원도초제건겅원돌출간판부산광역시동래구온천동금강공원로20번길86<NA>
1339413395미스터뚱세로형간판부산광역시동래구수안동명륜로94번길140
82938294디얀요가원가로형간판_입체형부산광역시동래구낙민동온천천로339번길280
74827483하나꽃돌출간판부산광역시동래구온천동아시아드대로231번길270
순번업소명광고물종류시도구군읍면동도로명건물1건물2
35383539부산은행 미남지점가로형간판_입체형부산광역시동래구온천동<NA><NA><NA>
87048705수안건어물돌출간판부산광역시동래구수안동명륜로75번길310
41954196코리아포장나이트가로형간판부산광역시동래구온천동미남로132번길13<NA>
14261427RUNTOYOU세로형간판부산광역시동래구수안동명륜로112번길36<NA>
1445314454로즈노래연습장돌출간판부산광역시동래구명장동반송로2680
58815882e삼성공인중개사돌출간판부산광역시동래구온천동중앙대로1335번길89<NA>
84288429크린토피아 온천벽산아스타돌출간판부산광역시동래구온천동금강공원로110
66656666빛찬나래태권도돌출간판부산광역시동래구온천동온천장로125번길57<NA>
1088110882명품옷수선돌출간판부산광역시동래구명장동명안로86번길456
1033910340어린이음악대 예뜨레원돌출간판부산광역시동래구온천동충렬대로107번길1060