Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells12558
Missing cells (%)15.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory732.4 KiB
Average record size in memory75.0 B

Variable types

Numeric3
Categorical2
Text3

Dataset

Description부산광역시_교통시설물관리시스템_교통안전시설물정보(노면문자표시정보)_20220630
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15084051

Alerts

번호 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 리명High correlation
경도 is highly overall correlated with 리명High correlation
시군구명 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
리명 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
리명 is highly imbalanced (86.3%)Imbalance
도로명 has 5906 (59.1%) missing valuesMissing
교차로명 has 6652 (66.5%) missing valuesMissing
위도 is highly skewed (γ1 = -42.26043642)Skewed
경도 is highly skewed (γ1 = -30.55640637)Skewed
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:11:44.329689
Analysis finished2023-12-10 17:11:48.132191
Duration3.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8369.9543
Minimum1
Maximum16673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:11:48.253806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile812.8
Q14232
median8369.5
Q312575.5
95-th percentile15836.05
Maximum16673
Range16672
Interquartile range (IQR)8343.5

Descriptive statistics

Standard deviation4822.1945
Coefficient of variation (CV)0.57613153
Kurtosis-1.2039127
Mean8369.9543
Median Absolute Deviation (MAD)4169.5
Skewness-0.010941103
Sum83699543
Variance23253560
MonotonicityNot monotonic
2023-12-11T02:11:48.498445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5747 1
 
< 0.1%
4269 1
 
< 0.1%
2942 1
 
< 0.1%
4187 1
 
< 0.1%
13118 1
 
< 0.1%
1627 1
 
< 0.1%
7986 1
 
< 0.1%
15337 1
 
< 0.1%
2207 1
 
< 0.1%
11329 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
4 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
21 1
< 0.1%
ValueCountFrequency (%)
16673 1
< 0.1%
16671 1
< 0.1%
16670 1
< 0.1%
16669 1
< 0.1%
16665 1
< 0.1%
16664 1
< 0.1%
16659 1
< 0.1%
16658 1
< 0.1%
16657 1
< 0.1%
16656 1
< 0.1%

시군구명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강서구
1669 
해운대구
1075 
북구
865 
부산진구
829 
사하구
828 
Other values (11)
4734 

Length

Max length4
Median length3
Mean length2.9448
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사상구
2nd row기장군
3rd row부산진구
4th row해운대구
5th row서구

Common Values

ValueCountFrequency (%)
강서구 1669
16.7%
해운대구 1075
10.8%
북구 865
8.6%
부산진구 829
8.3%
사하구 828
8.3%
기장군 774
7.7%
사상구 569
 
5.7%
남구 556
 
5.6%
금정구 508
 
5.1%
연제구 499
 
5.0%
Other values (6) 1828
18.3%

Length

2023-12-11T02:11:48.748997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구 1669
16.7%
해운대구 1075
10.8%
북구 865
8.6%
부산진구 829
8.3%
사하구 828
8.3%
기장군 774
7.7%
사상구 569
 
5.7%
남구 556
 
5.6%
금정구 508
 
5.1%
연제구 499
 
5.0%
Other values (6) 1828
18.3%

동명
Text

Distinct141
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T02:11:49.136967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.1072
Min length2

Characters and Unicode

Total characters31072
Distinct characters117
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

Unique6 ?
Unique (%)0.1%

Sample

1st row학장동
2nd row정관읍
3rd row양정동
4th row우동
5th row서대신동3가
ValueCountFrequency (%)
명지동 406
 
4.1%
우동 385
 
3.9%
대저2동 338
 
3.4%
하단동 325
 
3.2%
정관읍 272
 
2.7%
대연동 257
 
2.6%
연산동 250
 
2.5%
거제동 249
 
2.5%
화명동 215
 
2.1%
구포동 204
 
2.0%
Other values (131) 7099
71.0%
2023-12-11T02:11:49.757313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9577
30.8%
대 1017
 
3.3%
천 744
 
2.4%
명 683
 
2.2%
읍 645
 
2.1%
정 639
 
2.1%
가 620
 
2.0%
연 522
 
1.7%
저 519
 
1.7%
포 497
 
1.6%
Other values (107) 15609
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30035
96.7%
Decimal Number 1037
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9577
31.9%
대 1017
 
3.4%
천 744
 
2.5%
명 683
 
2.3%
읍 645
 
2.1%
정 639
 
2.1%
가 620
 
2.1%
연 522
 
1.7%
저 519
 
1.7%
포 497
 
1.7%
Other values (101) 14572
48.5%
Decimal Number
ValueCountFrequency (%)
2 439
42.3%
1 293
28.3%
3 178
17.2%
4 57
 
5.5%
6 52
 
5.0%
5 18
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30035
96.7%
Common 1037
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9577
31.9%
대 1017
 
3.4%
천 744
 
2.5%
명 683
 
2.3%
읍 645
 
2.1%
정 639
 
2.1%
가 620
 
2.1%
연 522
 
1.7%
저 519
 
1.7%
포 497
 
1.7%
Other values (101) 14572
48.5%
Common
ValueCountFrequency (%)
2 439
42.3%
1 293
28.3%
3 178
17.2%
4 57
 
5.5%
6 52
 
5.0%
5 18
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30035
96.7%
ASCII 1037
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9577
31.9%
대 1017
 
3.4%
천 744
 
2.5%
명 683
 
2.3%
읍 645
 
2.1%
정 639
 
2.1%
가 620
 
2.1%
연 522
 
1.7%
저 519
 
1.7%
포 497
 
1.7%
Other values (101) 14572
48.5%
ASCII
ValueCountFrequency (%)
2 439
42.3%
1 293
28.3%
3 178
17.2%
4 57
 
5.5%
6 52
 
5.0%
5 18
 
1.7%

리명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9259 
용수리
 
71
좌천리
 
48
동부리
 
47
달산리
 
44
Other values (37)
 
531

Length

Max length4
Median length4
Mean length3.9234
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9259
92.6%
용수리 71
 
0.7%
좌천리 48
 
0.5%
동부리 47
 
0.5%
달산리 44
 
0.4%
화전리 43
 
0.4%
청강리 40
 
0.4%
매학리 40
 
0.4%
예림리 39
 
0.4%
모전리 34
 
0.3%
Other values (32) 335
 
3.4%

Length

2023-12-11T02:11:50.083735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9259
92.6%
용수리 71
 
0.7%
좌천리 48
 
0.5%
동부리 47
 
0.5%
달산리 44
 
0.4%
화전리 43
 
0.4%
청강리 40
 
0.4%
매학리 40
 
0.4%
예림리 39
 
0.4%
모전리 34
 
0.3%
Other values (32) 335
 
3.4%

도로명
Text

MISSING 

Distinct1165
Distinct (%)28.5%
Missing5906
Missing (%)59.1%
Memory size156.2 KiB
2023-12-11T02:11:50.657768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length9.4108451
Min length5

Characters and Unicode

Total characters38528
Distinct characters214
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

Unique423 ?
Unique (%)10.3%

Sample

1st row학감대로 156-14
2nd row해운대로 284
3rd row꽃마을로 41
4th row종합운동장로28번길 7
5th row우동3로 94
ValueCountFrequency (%)
중앙대로 201
 
2.5%
낙동대로 178
 
2.2%
14 113
 
1.4%
11 104
 
1.3%
9 95
 
1.2%
16 86
 
1.1%
7 85
 
1.0%
해운대로 75
 
0.9%
금곡대로 74
 
0.9%
가야대로 65
 
0.8%
Other values (1212) 7112
86.9%
2023-12-11T02:11:51.382279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4094
 
10.6%
로 3959
 
10.3%
1 3329
 
8.6%
2 1702
 
4.4%
길 1675
 
4.3%
3 1628
 
4.2%
4 1615
 
4.2%
대 1610
 
4.2%
번 1568
 
4.1%
5 1229
 
3.2%
Other values (204) 16119
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19251
50.0%
Decimal Number 14527
37.7%
Space Separator 4094
 
10.6%
Dash Punctuation 656
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3959
20.6%
길 1675
 
8.7%
대 1610
 
8.4%
번 1568
 
8.1%
동 610
 
3.2%
중 400
 
2.1%
앙 388
 
2.0%
낙 382
 
2.0%
수 284
 
1.5%
해 215
 
1.1%
Other values (192) 8160
42.4%
Decimal Number
ValueCountFrequency (%)
1 3329
22.9%
2 1702
11.7%
3 1628
11.2%
4 1615
11.1%
5 1229
 
8.5%
7 1179
 
8.1%
6 1081
 
7.4%
9 983
 
6.8%
8 972
 
6.7%
0 809
 
5.6%
Space Separator
ValueCountFrequency (%)
4094
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19277
50.0%
Hangul 19251
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3959
20.6%
길 1675
 
8.7%
대 1610
 
8.4%
번 1568
 
8.1%
동 610
 
3.2%
중 400
 
2.1%
앙 388
 
2.0%
낙 382
 
2.0%
수 284
 
1.5%
해 215
 
1.1%
Other values (192) 8160
42.4%
Common
ValueCountFrequency (%)
4094
21.2%
1 3329
17.3%
2 1702
8.8%
3 1628
 
8.4%
4 1615
 
8.4%
5 1229
 
6.4%
7 1179
 
6.1%
6 1081
 
5.6%
9 983
 
5.1%
8 972
 
5.0%
Other values (2) 1465
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19277
50.0%
Hangul 19251
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4094
21.2%
1 3329
17.3%
2 1702
8.8%
3 1628
 
8.4%
4 1615
 
8.4%
5 1229
 
6.4%
7 1179
 
6.1%
6 1081
 
5.6%
9 983
 
5.1%
8 972
 
5.0%
Other values (2) 1465
 
7.6%
Hangul
ValueCountFrequency (%)
로 3959
20.6%
길 1675
 
8.7%
대 1610
 
8.4%
번 1568
 
8.1%
동 610
 
3.2%
중 400
 
2.1%
앙 388
 
2.0%
낙 382
 
2.0%
수 284
 
1.5%
해 215
 
1.1%
Other values (192) 8160
42.4%

교차로명
Text

MISSING 

Distinct669
Distinct (%)20.0%
Missing6652
Missing (%)66.5%
Memory size156.2 KiB
2023-12-11T02:11:51.673542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length6.6382915
Min length3

Characters and Unicode

Total characters22225
Distinct characters352
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)4.6%

Sample

1st row명성유치원
2nd row괴정초교
3rd row아시아드코오롱하늘채
4th row제일탕
5th row하단복개로
ValueCountFrequency (%)
만덕로타리 50
 
1.3%
49호광장(도시가스 38
 
1.0%
하단복개로 38
 
1.0%
앞 36
 
1.0%
거성로타리 30
 
0.8%
구포시장 27
 
0.7%
교대로타리 27
 
0.7%
주변 27
 
0.7%
광덕물산 26
 
0.7%
제일탕 26
 
0.7%
Other values (723) 3413
91.3%
2023-12-11T02:11:52.147093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 867
 
3.9%
로 684
 
3.1%
교 615
 
2.8%
구 555
 
2.5%
타 529
 
2.4%
( 495
 
2.2%
) 494
 
2.2%
동 434
 
2.0%
390
 
1.8%
초 384
 
1.7%
Other values (342) 16778
75.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19561
88.0%
Decimal Number 855
 
3.8%
Open Punctuation 495
 
2.2%
Close Punctuation 494
 
2.2%
Space Separator 390
 
1.8%
Uppercase Letter 337
 
1.5%
Other Punctuation 65
 
0.3%
Dash Punctuation 23
 
0.1%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 867
 
4.4%
로 684
 
3.5%
교 615
 
3.1%
구 555
 
2.8%
타 529
 
2.7%
동 434
 
2.2%
초 384
 
2.0%
대 378
 
1.9%
시 366
 
1.9%
지 360
 
1.8%
Other values (305) 14389
73.6%
Uppercase Letter
ValueCountFrequency (%)
B 54
16.0%
P 49
14.5%
G 47
13.9%
L 46
13.6%
C 27
8.0%
S 24
7.1%
I 21
 
6.2%
E 18
 
5.3%
K 8
 
2.4%
A 8
 
2.4%
Other values (9) 35
10.4%
Decimal Number
ValueCountFrequency (%)
2 215
25.1%
1 196
22.9%
4 141
16.5%
3 114
13.3%
9 61
 
7.1%
6 45
 
5.3%
0 44
 
5.1%
7 14
 
1.6%
5 13
 
1.5%
8 12
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 44
67.7%
. 19
29.2%
: 2
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 495
100.0%
Close Punctuation
ValueCountFrequency (%)
) 494
100.0%
Space Separator
ValueCountFrequency (%)
390
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19566
88.0%
Common 2322
 
10.4%
Latin 337
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 867
 
4.4%
로 684
 
3.5%
교 615
 
3.1%
구 555
 
2.8%
타 529
 
2.7%
동 434
 
2.2%
초 384
 
2.0%
대 378
 
1.9%
시 366
 
1.9%
지 360
 
1.8%
Other values (306) 14394
73.6%
Latin
ValueCountFrequency (%)
B 54
16.0%
P 49
14.5%
G 47
13.9%
L 46
13.6%
C 27
8.0%
S 24
7.1%
I 21
 
6.2%
E 18
 
5.3%
K 8
 
2.4%
A 8
 
2.4%
Other values (9) 35
10.4%
Common
ValueCountFrequency (%)
( 495
21.3%
) 494
21.3%
390
16.8%
2 215
9.3%
1 196
 
8.4%
4 141
 
6.1%
3 114
 
4.9%
9 61
 
2.6%
6 45
 
1.9%
, 44
 
1.9%
Other values (7) 127
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19561
88.0%
ASCII 2659
 
12.0%
None 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 867
 
4.4%
로 684
 
3.5%
교 615
 
3.1%
구 555
 
2.8%
타 529
 
2.7%
동 434
 
2.2%
초 384
 
2.0%
대 378
 
1.9%
시 366
 
1.9%
지 360
 
1.8%
Other values (305) 14389
73.6%
ASCII
ValueCountFrequency (%)
( 495
18.6%
) 494
18.6%
390
14.7%
2 215
8.1%
1 196
 
7.4%
4 141
 
5.3%
3 114
 
4.3%
9 61
 
2.3%
B 54
 
2.0%
P 49
 
1.8%
Other values (26) 450
16.9%
None
ValueCountFrequency (%)
㈜ 5
100.0%

위도
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9985
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.164058
Minimum21.580792
Maximum35.358154
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:11:52.978293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.580792
5-th percentile35.08901
Q135.128321
median35.165709
Q335.204341
95-th percentile35.297603
Maximum35.358154
Range13.777362
Interquartile range (IQR)0.076020545

Descriptive statistics

Standard deviation0.30952221
Coefficient of variation (CV)0.0088022322
Kurtosis1852.6036
Mean35.164058
Median Absolute Deviation (MAD)0.03797797
Skewness-42.260436
Sum351640.58
Variance0.095803997
MonotonicityNot monotonic
2023-12-11T02:11:53.295048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.13981818 6
 
0.1%
35.21037736 2
 
< 0.1%
35.2390979 2
 
< 0.1%
35.23930101 2
 
< 0.1%
35.09966274 2
 
< 0.1%
35.13381265 2
 
< 0.1%
35.13395832 2
 
< 0.1%
35.13391847 2
 
< 0.1%
35.20831964 2
 
< 0.1%
35.13978393 2
 
< 0.1%
Other values (9975) 9976
99.8%
ValueCountFrequency (%)
21.58079235 1
< 0.1%
21.58080818 1
< 0.1%
21.58082205 1
< 0.1%
21.58145543 1
< 0.1%
21.58162242 1
< 0.1%
35.02296993 1
< 0.1%
35.02300016 1
< 0.1%
35.02303017 1
< 0.1%
35.0230685 1
< 0.1%
35.02309817 1
< 0.1%
ValueCountFrequency (%)
35.35815434 1
< 0.1%
35.35784597 1
< 0.1%
35.35781872 1
< 0.1%
35.35779807 1
< 0.1%
35.35778987 1
< 0.1%
35.35778616 1
< 0.1%
35.35775292 1
< 0.1%
35.35746932 1
< 0.1%
35.35744727 1
< 0.1%
35.35717958 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9959
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.04094
Minimum121.64645
Maximum129.28498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:11:53.631492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum121.64645
5-th percentile128.89194
Q1128.9834
median129.04996
Q3129.10849
95-th percentile129.19123
Maximum129.28498
Range7.6385283
Interquartile range (IQR)0.12509207

Descriptive statistics

Standard deviation0.18770488
Coefficient of variation (CV)0.0014546149
Kurtosis1201.5556
Mean129.04094
Median Absolute Deviation (MAD)0.0613815
Skewness-30.556406
Sum1290409.4
Variance0.03523312
MonotonicityNot monotonic
2023-12-11T02:11:54.041208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0423987 3
 
< 0.1%
129.014004 2
 
< 0.1%
128.9824894 2
 
< 0.1%
129.1166354 2
 
< 0.1%
128.9744249 2
 
< 0.1%
129.1007846 2
 
< 0.1%
128.862656 2
 
< 0.1%
129.0592842 2
 
< 0.1%
129.0100371 2
 
< 0.1%
129.1160889 2
 
< 0.1%
Other values (9949) 9979
99.8%
ValueCountFrequency (%)
121.6464513 1
< 0.1%
121.6467033 1
< 0.1%
121.6479643 1
< 0.1%
121.6479873 1
< 0.1%
121.6480117 1
< 0.1%
128.8094241 1
< 0.1%
128.8094863 1
< 0.1%
128.8095482 1
< 0.1%
128.809614 1
< 0.1%
128.8096754 1
< 0.1%
ValueCountFrequency (%)
129.2849796 1
< 0.1%
129.2849306 1
< 0.1%
129.2849041 1
< 0.1%
129.2848871 1
< 0.1%
129.284795 1
< 0.1%
129.2847738 1
< 0.1%
129.2847398 1
< 0.1%
129.2842636 1
< 0.1%
129.2842533 1
< 0.1%
129.2842282 1
< 0.1%

Interactions

2023-12-11T02:11:47.042011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:11:45.854561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:11:46.509933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:11:47.223787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:11:46.059544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:11:46.706520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:11:47.414864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:11:46.296813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:11:46.881955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:11:54.350066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호시군구명리명위도경도
번호1.0000.8520.8860.0780.078
시군구명0.8521.0000.9500.0660.066
리명0.8860.9501.000NaNNaN
위도0.0780.066NaN1.0000.988
경도0.0780.066NaN0.9881.000
2023-12-11T02:11:54.581501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
리명시군구명
리명1.0000.863
시군구명0.8631.000
2023-12-11T02:11:54.757159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호위도경도시군구명리명
번호1.0000.2010.4720.5520.657
위도0.2011.0000.4880.0521.000
경도0.4720.4881.0000.0521.000
시군구명0.5520.0520.0521.0000.863
리명0.6571.0001.0000.8631.000

Missing values

2023-12-11T02:11:47.674717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:11:47.859148image/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.
2023-12-11T02:11:48.030709image/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

번호시군구명동명리명도로명교차로명위도경도
57465747사상구학장동<NA>학감대로 156-14명성유치원35.14436128.990016
1575415755기장군정관읍용수리<NA><NA>35.334933129.176621
47104711부산진구양정동<NA><NA><NA>35.173927129.071963
94429443해운대구우동<NA>해운대로 284<NA>35.175181129.131076
1288512886서구서대신동3가<NA>꽃마을로 41<NA>35.118292129.01179
20202021사하구괴정동<NA><NA>괴정초교35.103333129.000844
1646516466동래구사직동<NA>종합운동장로28번길 7아시아드코오롱하늘채35.194157129.064324
26652666북구구포동<NA><NA>제일탕35.207474129.005053
1148911490해운대구우동<NA>우동3로 94<NA>35.176485129.16526
80228023강서구명지동<NA><NA><NA>35.107849128.929991
번호시군구명동명리명도로명교차로명위도경도
35153516남구용호동<NA><NA><NA>35.133592129.10934
39853986수영구남천동<NA><NA>KBS앞35.144354129.109534
1438014381동래구사직동<NA>종합운동장로 29<NA>35.192767129.064452
7374사상구모라동<NA><NA><NA>35.185119128.994358
42984299연제구연산동<NA>고분로123번길 9연일초교35.185711129.096017
65636564강서구대저1동<NA><NA><NA>35.206563128.974383
1550015501금정구노포동<NA><NA><NA>35.28551129.091052
20242025사하구괴정동<NA><NA>괴정초교35.103274129.000903
26082609북구구포동<NA>시랑로 3-1구포 교보생명35.205247129.003927
1224912250금정구구서동<NA><NA><NA>35.24885129.102357