Overview

Dataset statistics

Number of variables8
Number of observations3537
Missing cells4221
Missing cells (%)14.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory231.6 KiB
Average record size in memory67.0 B

Variable types

Numeric3
Categorical2
Text3

Dataset

Description부산광역시_교통시설물관리시스템_교통안전시설물정보(안전지대 정보)에 대한 데이터로 번호, 시군구명, 동명, 리명, 도로명, 교차로명, 경도, 위도 항목정보를 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15084055/fileData.do

Alerts

번호 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
시군구명 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
리명 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
리명 is highly imbalanced (79.5%)Imbalance
도로명 has 2189 (61.9%) missing valuesMissing
교차로명 has 2032 (57.4%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:18:29.126437
Analysis finished2023-12-12 08:18:31.720727
Duration2.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3537
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1769
Minimum1
Maximum3537
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2023-12-12T17:18:31.818436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile177.8
Q1885
median1769
Q32653
95-th percentile3360.2
Maximum3537
Range3536
Interquartile range (IQR)1768

Descriptive statistics

Standard deviation1021.1883
Coefficient of variation (CV)0.57726867
Kurtosis-1.2
Mean1769
Median Absolute Deviation (MAD)884
Skewness0
Sum6256953
Variance1042825.5
MonotonicityStrictly increasing
2023-12-12T17:18:32.038521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2364 1
 
< 0.1%
2353 1
 
< 0.1%
2354 1
 
< 0.1%
2355 1
 
< 0.1%
2356 1
 
< 0.1%
2357 1
 
< 0.1%
2358 1
 
< 0.1%
2359 1
 
< 0.1%
2360 1
 
< 0.1%
Other values (3527) 3527
99.7%
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 (%)
3537 1
< 0.1%
3536 1
< 0.1%
3535 1
< 0.1%
3534 1
< 0.1%
3533 1
< 0.1%
3532 1
< 0.1%
3531 1
< 0.1%
3530 1
< 0.1%
3529 1
< 0.1%
3528 1
< 0.1%

시군구명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size27.8 KiB
강서구
731 
기장군
444 
해운대구
388 
부산진구
308 
사상구
306 
Other values (11)
1360 

Length

Max length4
Median length3
Mean length3.0002827
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해운대구
2nd row남구
3rd row동래구
4th row금정구
5th row기장군

Common Values

ValueCountFrequency (%)
강서구 731
20.7%
기장군 444
12.6%
해운대구 388
11.0%
부산진구 308
8.7%
사상구 306
8.7%
사하구 199
 
5.6%
남구 198
 
5.6%
북구 174
 
4.9%
동구 169
 
4.8%
동래구 150
 
4.2%
Other values (6) 470
13.3%

Length

2023-12-12T17:18:32.238821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구 731
20.7%
기장군 444
12.6%
해운대구 388
11.0%
부산진구 308
8.7%
사상구 306
8.7%
사하구 199
 
5.6%
남구 198
 
5.6%
북구 174
 
4.9%
동구 169
 
4.8%
동래구 150
 
4.2%
Other values (6) 470
13.3%

동명
Text

Distinct125
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size27.8 KiB
2023-12-12T17:18:32.625493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0695505
Min length1

Characters and Unicode

Total characters10857
Distinct characters117
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.3%

Sample

1st row우동
2nd row문현동
3rd row온천동
4th row부곡동
5th row일광면
ValueCountFrequency (%)
송정동 150
 
4.2%
명지동 145
 
4.1%
우동 127
 
3.6%
장안읍 122
 
3.4%
기장읍 107
 
3.0%
정관읍 105
 
3.0%
거제동 94
 
2.7%
재송동 90
 
2.5%
대저1동 86
 
2.4%
대저2동 85
 
2.4%
Other values (115) 2426
68.6%
2023-12-12T17:18:33.140045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 3193
29.4%
읍 344
 
3.2%
장 337
 
3.1%
대 322
 
3.0%
정 293
 
2.7%
송 258
 
2.4%
명 220
 
2.0%
천 193
 
1.8%
안 191
 
1.8%
지 183
 
1.7%
Other values (107) 5323
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10565
97.3%
Decimal Number 291
 
2.7%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3193
30.2%
읍 344
 
3.3%
장 337
 
3.2%
대 322
 
3.0%
정 293
 
2.8%
송 258
 
2.4%
명 220
 
2.1%
천 193
 
1.8%
안 191
 
1.8%
지 183
 
1.7%
Other values (100) 5031
47.6%
Decimal Number
ValueCountFrequency (%)
2 129
44.3%
1 87
29.9%
3 41
 
14.1%
4 22
 
7.6%
6 8
 
2.7%
5 4
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10565
97.3%
Common 292
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3193
30.2%
읍 344
 
3.3%
장 337
 
3.2%
대 322
 
3.0%
정 293
 
2.8%
송 258
 
2.4%
명 220
 
2.1%
천 193
 
1.8%
안 191
 
1.8%
지 183
 
1.7%
Other values (100) 5031
47.6%
Common
ValueCountFrequency (%)
2 129
44.2%
1 87
29.8%
3 41
 
14.0%
4 22
 
7.5%
6 8
 
2.7%
5 4
 
1.4%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10565
97.3%
ASCII 292
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 3193
30.2%
읍 344
 
3.3%
장 337
 
3.2%
대 322
 
3.0%
정 293
 
2.8%
송 258
 
2.4%
명 220
 
2.1%
천 193
 
1.8%
안 191
 
1.8%
지 183
 
1.7%
Other values (100) 5031
47.6%
ASCII
ValueCountFrequency (%)
2 129
44.2%
1 87
29.8%
3 41
 
14.0%
4 22
 
7.5%
6 8
 
2.7%
5 4
 
1.4%
- 1
 
0.3%

리명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct50
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size27.8 KiB
<NA>
3109 
기룡리
 
30
청강리
 
27
용수리
 
25
동부리
 
22
Other values (45)
324 

Length

Max length4
Median length4
Mean length3.8758835
Min length2

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3109
87.9%
기룡리 30
 
0.8%
청강리 27
 
0.8%
용수리 25
 
0.7%
동부리 22
 
0.6%
화전리 21
 
0.6%
좌천리 18
 
0.5%
두명리 18
 
0.5%
안평리 16
 
0.5%
시랑리 14
 
0.4%
Other values (40) 237
 
6.7%

Length

2023-12-12T17:18:33.333475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3109
87.9%
기룡리 30
 
0.8%
청강리 27
 
0.8%
용수리 25
 
0.7%
동부리 22
 
0.6%
화전리 21
 
0.6%
좌천리 18
 
0.5%
두명리 18
 
0.5%
안평리 16
 
0.5%
달산리 14
 
0.4%
Other values (40) 237
 
6.7%

도로명
Text

MISSING 

Distinct737
Distinct (%)54.7%
Missing2189
Missing (%)61.9%
Memory size27.8 KiB
2023-12-12T17:18:33.751744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.4710682
Min length3

Characters and Unicode

Total characters12767
Distinct characters204
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

Unique490 ?
Unique (%)36.4%

Sample

1st row우암로360번길 4-11
2nd row아시아드대로 232
3rd row장전온천천로 19-1
4th row기장대로 672
5th row중앙대로 1817
ValueCountFrequency (%)
16 38
 
1.4%
중앙대로 36
 
1.3%
낙동대로 35
 
1.3%
9 34
 
1.3%
14 32
 
1.2%
7 27
 
1.0%
수영강변대로 26
 
1.0%
사상로147번길 25
 
0.9%
가야대로 23
 
0.9%
50 23
 
0.9%
Other values (871) 2391
88.9%
2023-12-12T17:18:34.321655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1342
 
10.5%
로 1294
 
10.1%
1 1053
 
8.2%
2 626
 
4.9%
길 587
 
4.6%
3 572
 
4.5%
대 542
 
4.2%
번 541
 
4.2%
4 474
 
3.7%
7 416
 
3.3%
Other values (194) 5320
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6370
49.9%
Decimal Number 4820
37.8%
Space Separator 1342
 
10.5%
Dash Punctuation 235
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1294
20.3%
길 587
 
9.2%
대 542
 
8.5%
번 541
 
8.5%
동 156
 
2.4%
낙 103
 
1.6%
장 95
 
1.5%
중 92
 
1.4%
산 91
 
1.4%
앙 88
 
1.4%
Other values (182) 2781
43.7%
Decimal Number
ValueCountFrequency (%)
1 1053
21.8%
2 626
13.0%
3 572
11.9%
4 474
9.8%
7 416
 
8.6%
5 395
 
8.2%
6 372
 
7.7%
9 349
 
7.2%
8 283
 
5.9%
0 280
 
5.8%
Space Separator
ValueCountFrequency (%)
1342
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 235
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6397
50.1%
Hangul 6370
49.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1294
20.3%
길 587
 
9.2%
대 542
 
8.5%
번 541
 
8.5%
동 156
 
2.4%
낙 103
 
1.6%
장 95
 
1.5%
중 92
 
1.4%
산 91
 
1.4%
앙 88
 
1.4%
Other values (182) 2781
43.7%
Common
ValueCountFrequency (%)
1342
21.0%
1 1053
16.5%
2 626
9.8%
3 572
8.9%
4 474
 
7.4%
7 416
 
6.5%
5 395
 
6.2%
6 372
 
5.8%
9 349
 
5.5%
8 283
 
4.4%
Other values (2) 515
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6397
50.1%
Hangul 6370
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1342
21.0%
1 1053
16.5%
2 626
9.8%
3 572
8.9%
4 474
 
7.4%
7 416
 
6.5%
5 395
 
6.2%
6 372
 
5.8%
9 349
 
5.5%
8 283
 
4.4%
Other values (2) 515
 
8.1%
Hangul
ValueCountFrequency (%)
로 1294
20.3%
길 587
 
9.2%
대 542
 
8.5%
번 541
 
8.5%
동 156
 
2.4%
낙 103
 
1.6%
장 95
 
1.5%
중 92
 
1.4%
산 91
 
1.4%
앙 88
 
1.4%
Other values (182) 2781
43.7%

교차로명
Text

MISSING 

Distinct537
Distinct (%)35.7%
Missing2032
Missing (%)57.4%
Memory size27.8 KiB
2023-12-12T17:18:34.649339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length6.4438538
Min length3

Characters and Unicode

Total characters9698
Distinct characters351
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)14.2%

Sample

1st row배정고교
2nd row내성로타리
3rd row금정경찰서
4th row정관월평사거리
5th row정관월평사거리
ValueCountFrequency (%)
장안산업단지 17
 
1.0%
문현로타리 16
 
1.0%
주례로타리 13
 
0.8%
좌동지하차도 13
 
0.8%
문전로타리(동성로타리 12
 
0.7%
학장로타리 12
 
0.7%
교대로타리 12
 
0.7%
진양로타리 12
 
0.7%
새벽시장입구 12
 
0.7%
만덕로타리 11
 
0.7%
Other values (578) 1501
92.0%
2023-12-12T17:18:35.195961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 548
 
5.7%
로 405
 
4.2%
타 331
 
3.4%
구 230
 
2.4%
교 218
 
2.2%
동 212
 
2.2%
거 199
 
2.1%
대 184
 
1.9%
( 179
 
1.8%
) 178
 
1.8%
Other values (341) 7014
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8710
89.8%
Decimal Number 263
 
2.7%
Uppercase Letter 203
 
2.1%
Open Punctuation 179
 
1.8%
Close Punctuation 178
 
1.8%
Space Separator 128
 
1.3%
Other Punctuation 17
 
0.2%
Dash Punctuation 13
 
0.1%
Other Symbol 6
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 548
 
6.3%
로 405
 
4.6%
타 331
 
3.8%
구 230
 
2.6%
교 218
 
2.5%
동 212
 
2.4%
거 199
 
2.3%
대 184
 
2.1%
지 168
 
1.9%
장 164
 
1.9%
Other values (305) 6051
69.5%
Uppercase Letter
ValueCountFrequency (%)
C 27
13.3%
P 26
12.8%
B 22
10.8%
E 21
10.3%
G 19
9.4%
L 16
7.9%
S 15
7.4%
I 14
6.9%
A 9
 
4.4%
T 7
 
3.4%
Other values (6) 27
13.3%
Decimal Number
ValueCountFrequency (%)
2 85
32.3%
1 52
19.8%
3 41
15.6%
4 34
 
12.9%
8 12
 
4.6%
5 11
 
4.2%
0 9
 
3.4%
6 8
 
3.0%
9 6
 
2.3%
7 5
 
1.9%
Other Punctuation
ValueCountFrequency (%)
: 7
41.2%
. 6
35.3%
, 3
17.6%
/ 1
 
5.9%
Open Punctuation
ValueCountFrequency (%)
( 179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 178
100.0%
Space Separator
ValueCountFrequency (%)
128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8716
89.9%
Common 778
 
8.0%
Latin 204
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 548
 
6.3%
로 405
 
4.6%
타 331
 
3.8%
구 230
 
2.6%
교 218
 
2.5%
동 212
 
2.4%
거 199
 
2.3%
대 184
 
2.1%
지 168
 
1.9%
장 164
 
1.9%
Other values (306) 6057
69.5%
Common
ValueCountFrequency (%)
( 179
23.0%
) 178
22.9%
128
16.5%
2 85
10.9%
1 52
 
6.7%
3 41
 
5.3%
4 34
 
4.4%
- 13
 
1.7%
8 12
 
1.5%
5 11
 
1.4%
Other values (8) 45
 
5.8%
Latin
ValueCountFrequency (%)
C 27
13.2%
P 26
12.7%
B 22
10.8%
E 21
10.3%
G 19
9.3%
L 16
7.8%
S 15
7.4%
I 14
6.9%
A 9
 
4.4%
T 7
 
3.4%
Other values (7) 28
13.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8710
89.8%
ASCII 982
 
10.1%
None 6
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 548
 
6.3%
로 405
 
4.6%
타 331
 
3.8%
구 230
 
2.6%
교 218
 
2.5%
동 212
 
2.4%
거 199
 
2.3%
대 184
 
2.1%
지 168
 
1.9%
장 164
 
1.9%
Other values (305) 6051
69.5%
ASCII
ValueCountFrequency (%)
( 179
18.2%
) 178
18.1%
128
13.0%
2 85
8.7%
1 52
 
5.3%
3 41
 
4.2%
4 34
 
3.5%
C 27
 
2.7%
P 26
 
2.6%
B 22
 
2.2%
Other values (25) 210
21.4%
None
ValueCountFrequency (%)
㈜ 6
100.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct3525
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.04471
Minimum128.81023
Maximum129.30301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2023-12-12T17:18:35.392458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.81023
5-th percentile128.8672
Q1128.97419
median129.05075
Q3129.11474
95-th percentile129.22708
Maximum129.30301
Range0.4927775
Interquartile range (IQR)0.1405471

Descriptive statistics

Standard deviation0.10346838
Coefficient of variation (CV)0.00080180255
Kurtosis-0.40586364
Mean129.04471
Median Absolute Deviation (MAD)0.0687883
Skewness0.053069218
Sum456431.14
Variance0.010705705
MonotonicityNot monotonic
2023-12-12T17:18:35.602226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0799597 2
 
0.1%
129.2137701 2
 
0.1%
129.0799041 2
 
0.1%
128.9835687 2
 
0.1%
129.1185149 2
 
0.1%
128.953588 2
 
0.1%
129.0000798 2
 
0.1%
129.0933534 2
 
0.1%
129.2137146 2
 
0.1%
129.1186317 2
 
0.1%
Other values (3515) 3517
99.4%
ValueCountFrequency (%)
128.8102302 1
< 0.1%
128.8134414 1
< 0.1%
128.8160799 1
< 0.1%
128.8173736 1
< 0.1%
128.8180734 1
< 0.1%
128.8184666 1
< 0.1%
128.8205288 1
< 0.1%
128.8205524 1
< 0.1%
128.8214051 1
< 0.1%
128.8214682 1
< 0.1%
ValueCountFrequency (%)
129.3030077 1
< 0.1%
129.3029862 1
< 0.1%
129.3029049 1
< 0.1%
129.3028981 1
< 0.1%
129.3028775 1
< 0.1%
129.3028246 1
< 0.1%
129.3028078 1
< 0.1%
129.3027398 1
< 0.1%
129.3027222 1
< 0.1%
129.302719 1
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3528
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.174434
Minimum35.028571
Maximum35.385567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2023-12-12T17:18:35.789165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.028571
5-th percentile35.088941
Q135.129821
median35.165374
Q335.206905
95-th percentile35.323554
Maximum35.385567
Range0.35699569
Interquartile range (IQR)0.07708421

Descriptive statistics

Standard deviation0.065481144
Coefficient of variation (CV)0.0018616119
Kurtosis0.59116722
Mean35.174434
Median Absolute Deviation (MAD)0.03843454
Skewness0.85349935
Sum124411.97
Variance0.0042877802
MonotonicityNot monotonic
2023-12-12T17:18:36.014138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.2146689 2
 
0.1%
35.21389869 2
 
0.1%
35.24877383 2
 
0.1%
35.21496151 2
 
0.1%
35.24871519 2
 
0.1%
35.21079937 2
 
0.1%
35.19616851 2
 
0.1%
35.19601658 2
 
0.1%
35.19855091 2
 
0.1%
35.15230287 1
 
< 0.1%
Other values (3518) 3518
99.5%
ValueCountFrequency (%)
35.02857137 1
< 0.1%
35.02883862 1
< 0.1%
35.03027945 1
< 0.1%
35.03037113 1
< 0.1%
35.03197197 1
< 0.1%
35.03212125 1
< 0.1%
35.03271238 1
< 0.1%
35.04785339 1
< 0.1%
35.04786533 1
< 0.1%
35.04899313 1
< 0.1%
ValueCountFrequency (%)
35.38556706 1
< 0.1%
35.38441928 1
< 0.1%
35.37683131 1
< 0.1%
35.3755344 1
< 0.1%
35.37533762 1
< 0.1%
35.37453613 1
< 0.1%
35.36897793 1
< 0.1%
35.36708003 1
< 0.1%
35.36458724 1
< 0.1%
35.36434296 1
< 0.1%

Interactions

2023-12-12T17:18:30.810488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:30.050553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:30.428766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:30.982025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:30.195037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:30.573764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:31.145383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:30.314222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:18:30.683307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:18:36.149280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호시군구명리명경도위도
번호1.0000.8490.9190.9020.726
시군구명0.8491.0000.9630.8860.823
리명0.9190.9631.0000.9940.985
경도0.9020.8860.9941.0000.786
위도0.7260.8230.9850.7861.000
2023-12-12T17:18:36.274770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명리명
시군구명1.0000.853
리명0.8531.000
2023-12-12T17:18:36.363793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호경도위도시군구명리명
번호1.0000.3500.3290.5460.690
경도0.3501.0000.5890.6150.910
위도0.3290.5891.0000.5050.848
시군구명0.5460.6150.5051.0000.853
리명0.6900.9100.8480.8531.000

Missing values

2023-12-12T17:18:31.350059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:18:31.521353image/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.
2023-12-12T17:18:31.634447image/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

번호시군구명동명리명도로명교차로명경도위도
01해운대구우동<NA><NA><NA>129.13612335.164899
12남구문현동<NA>우암로360번길 4-11배정고교129.06693835.134044
23동래구온천동<NA>아시아드대로 232내성로타리129.07798835.205161
34금정구부곡동<NA>장전온천천로 19-1<NA>129.08907535.226383
45기장군일광면삼성리기장대로 672<NA>129.22311435.254922
56기장군기장읍시랑리<NA><NA>129.22139335.194976
67금정구구서동<NA>중앙대로 1817금정경찰서129.09338835.246911
78기장군정관읍월평리<NA>정관월평사거리129.14116635.357937
89기장군정관읍월평리<NA>정관월평사거리129.14088435.357544
910기장군정관읍월평리<NA>정관월평사거리129.14032535.357654
번호시군구명동명리명도로명교차로명경도위도
35273528북구만덕동<NA>상학로 35만덕중학교129.03222235.214537
35283529북구만덕동<NA>상학로 35<NA>129.03637135.214138
35293530북구만덕동<NA><NA><NA>129.03624935.214171
35303531동래구사직동<NA>아시아대로134번길 14<NA>129.06615535.196354
35313532연제구연산동<NA>중앙천로 81<NA>129.08038135.181973
35323533연제구연산동<NA>중앙천로81<NA>129.07994335.181445
35333534연제구연산동<NA>중앙천로81<NA>129.08022535.181564
35343535동래구수안동<NA>명륜로70동래경찰서129.084335.2004
35353536동래구안락동<NA>충렬대로487안락SK아파트앞129.111335.1946
35363537금정구부곡동<NA>수림로부곡SK아파트앞129.091235.2395