Overview

Dataset statistics

Number of variables9
Number of observations283
Missing cells8
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.1 KiB
Average record size in memory76.5 B

Variable types

Numeric4
Text2
Categorical2
DateTime1

Dataset

Description창원시 시민공영자전거 누비자에 대하여 현재 설치된 터미널 현황을 터미널명, 위치(~구, ~동, 위도 및 경도), 주소, 등록인자, 보관대수 등을 제공합니다.
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15000545

Alerts

동 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
구 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
번호 is highly overall correlated with 구 and 1 other fieldsHigh correlation
등록일자 has 5 (1.8%) missing valuesMissing
보관대수 has 3 (1.1%) missing valuesMissing
번호 has unique valuesUnique
터미널명 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:38:28.053200
Analysis finished2023-12-10 23:38:30.524458
Duration2.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct283
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean142
Minimum1
Maximum283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T08:38:30.592662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.1
Q171.5
median142
Q3212.5
95-th percentile268.9
Maximum283
Range282
Interquartile range (IQR)141

Descriptive statistics

Standard deviation81.839273
Coefficient of variation (CV)0.57633291
Kurtosis-1.2
Mean142
Median Absolute Deviation (MAD)71
Skewness0
Sum40186
Variance6697.6667
MonotonicityStrictly increasing
2023-12-11T08:38:30.794826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
188 1
 
0.4%
194 1
 
0.4%
193 1
 
0.4%
192 1
 
0.4%
191 1
 
0.4%
190 1
 
0.4%
189 1
 
0.4%
187 1
 
0.4%
196 1
 
0.4%
Other values (273) 273
96.5%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
283 1
0.4%
282 1
0.4%
281 1
0.4%
280 1
0.4%
279 1
0.4%
278 1
0.4%
277 1
0.4%
276 1
0.4%
275 1
0.4%
274 1
0.4%

터미널명
Text

UNIQUE 

Distinct283
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T08:38:31.081137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length8.5194346
Min length3

Characters and Unicode

Total characters2411
Distinct characters314
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)100.0%

Sample

1st row경남은행 본점 앞
2nd row경남지방경찰청
3rd row대동다숲아파트 앞
4th row대동백화점
5th row도계동 안골
ValueCountFrequency (%)
앞 34
 
7.9%
버스정류소 18
 
4.2%
옆 6
 
1.4%
내서 4
 
0.9%
주차장 4
 
0.9%
정문 4
 
0.9%
공원 4
 
0.9%
건너편 3
 
0.7%
웅남동 3
 
0.7%
성주동 3
 
0.7%
Other values (334) 348
80.7%
2023-12-11T08:38:31.572550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
 
6.1%
동 92
 
3.8%
원 76
 
3.2%
앞 65
 
2.7%
트 47
 
1.9%
정 47
 
1.9%
파 44
 
1.8%
리 42
 
1.7%
스 40
 
1.7%
소 39
 
1.6%
Other values (304) 1771
73.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2155
89.4%
Space Separator 148
 
6.1%
Decimal Number 36
 
1.5%
Uppercase Letter 34
 
1.4%
Close Punctuation 17
 
0.7%
Open Punctuation 17
 
0.7%
Other Punctuation 3
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 92
 
4.3%
원 76
 
3.5%
앞 65
 
3.0%
트 47
 
2.2%
정 47
 
2.2%
파 44
 
2.0%
리 42
 
1.9%
스 40
 
1.9%
소 39
 
1.8%
터 38
 
1.8%
Other values (279) 1625
75.4%
Uppercase Letter
ValueCountFrequency (%)
K 7
20.6%
T 5
14.7%
L 4
11.8%
G 4
11.8%
P 2
 
5.9%
S 2
 
5.9%
B 2
 
5.9%
H 2
 
5.9%
A 2
 
5.9%
N 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
1 13
36.1%
2 10
27.8%
3 4
 
11.1%
5 3
 
8.3%
0 3
 
8.3%
4 2
 
5.6%
9 1
 
2.8%
Space Separator
ValueCountFrequency (%)
148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2156
89.4%
Common 221
 
9.2%
Latin 34
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 92
 
4.3%
원 76
 
3.5%
앞 65
 
3.0%
트 47
 
2.2%
정 47
 
2.2%
파 44
 
2.0%
리 42
 
1.9%
스 40
 
1.9%
소 39
 
1.8%
터 38
 
1.8%
Other values (280) 1626
75.4%
Latin
ValueCountFrequency (%)
K 7
20.6%
T 5
14.7%
L 4
11.8%
G 4
11.8%
P 2
 
5.9%
S 2
 
5.9%
B 2
 
5.9%
H 2
 
5.9%
A 2
 
5.9%
N 1
 
2.9%
Other values (3) 3
8.8%
Common
ValueCountFrequency (%)
148
67.0%
) 17
 
7.7%
( 17
 
7.7%
1 13
 
5.9%
2 10
 
4.5%
3 4
 
1.8%
. 3
 
1.4%
5 3
 
1.4%
0 3
 
1.4%
4 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2155
89.4%
ASCII 255
 
10.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
58.0%
) 17
 
6.7%
( 17
 
6.7%
1 13
 
5.1%
2 10
 
3.9%
K 7
 
2.7%
T 5
 
2.0%
3 4
 
1.6%
L 4
 
1.6%
G 4
 
1.6%
Other values (14) 26
 
10.2%
Hangul
ValueCountFrequency (%)
동 92
 
4.3%
원 76
 
3.5%
앞 65
 
3.0%
트 47
 
2.2%
정 47
 
2.2%
파 44
 
2.0%
리 42
 
1.9%
스 40
 
1.9%
소 39
 
1.8%
터 38
 
1.8%
Other values (279) 1625
75.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

구
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
성산구
114 
의창구
72 
진해구
47 
마산회원구
30 
마산합포구
20 

Length

Max length5
Median length3
Mean length3.3533569
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성산구 114
40.3%
의창구 72
25.4%
진해구 47
16.6%
마산회원구 30
 
10.6%
마산합포구 20
 
7.1%

Length

2023-12-11T08:38:31.720611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:38:31.866197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성산구 114
40.3%
의창구 72
25.4%
진해구 47
16.6%
마산회원구 30
 
10.6%
마산합포구 20
 
7.1%

동
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
중앙동
24 
명곡동
20 
용지동
 
18
봉림동
 
18
가음정동
 
16
Other values (40)
187 

Length

Max length5
Median length3
Mean length3.0918728
Min length2

Unique

Unique7 ?
Unique (%)2.5%

Sample

1st row교방동
2nd row교방동
3rd row문화동
4th row문화동
5th row반월중앙동

Common Values

ValueCountFrequency (%)
중앙동 24
 
8.5%
명곡동 20
 
7.1%
용지동 18
 
6.4%
봉림동 18
 
6.4%
가음정동 16
 
5.7%
사파동 16
 
5.7%
팔용동 14
 
4.9%
상남동 12
 
4.2%
의창동 11
 
3.9%
성주동 10
 
3.5%
Other values (35) 124
43.8%

Length

2023-12-11T08:38:32.002864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중앙동 24
 
8.5%
명곡동 20
 
7.1%
용지동 18
 
6.4%
봉림동 18
 
6.4%
가음정동 16
 
5.7%
사파동 16
 
5.7%
팔용동 14
 
4.9%
상남동 12
 
4.2%
의창동 11
 
3.9%
성주동 10
 
3.5%
Other values (35) 124
43.8%

주소
Text

Distinct273
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T08:38:32.292131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length36
Mean length23.339223
Min length17

Characters and Unicode

Total characters6605
Distinct characters178
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique264 ?
Unique (%)93.3%

Sample

1st row경남 창원시 마산회원구 석전동 267 도로
2nd row경남 창원시 의창구 사림동 1-2 대
3rd row경남 창원시 진해구 장천동 119-14 도로
4th row경남 창원시 성산구 상남동 503 도
5th row경남 창원시 의창구 도계동 88-6(도)
ValueCountFrequency (%)
경남 283
17.4%
창원시 283
17.4%
성산구 117
 
7.2%
의창구 69
 
4.2%
도 53
 
3.3%
진해구 47
 
2.9%
마산회원구 30
 
1.8%
도로 21
 
1.3%
마산합포구 20
 
1.2%
상남동 14
 
0.9%
Other values (399) 689
42.4%
2023-12-11T08:38:32.715157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1607
24.3%
창 354
 
5.4%
원 344
 
5.2%
남 312
 
4.7%
구 292
 
4.4%
경 292
 
4.4%
시 285
 
4.3%
동 282
 
4.3%
1 191
 
2.9%
산 182
 
2.8%
Other values (168) 2464
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3814
57.7%
Space Separator 1607
24.3%
Decimal Number 983
 
14.9%
Dash Punctuation 165
 
2.5%
Close Punctuation 19
 
0.3%
Open Punctuation 17
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
창 354
 
9.3%
원 344
 
9.0%
남 312
 
8.2%
구 292
 
7.7%
경 292
 
7.7%
시 285
 
7.5%
동 282
 
7.4%
산 182
 
4.8%
성 132
 
3.5%
도 110
 
2.9%
Other values (154) 1229
32.2%
Decimal Number
ValueCountFrequency (%)
1 191
19.4%
5 152
15.5%
2 116
11.8%
0 113
11.5%
3 112
11.4%
4 82
8.3%
6 68
 
6.9%
7 56
 
5.7%
9 47
 
4.8%
8 46
 
4.7%
Space Separator
ValueCountFrequency (%)
1607
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 165
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3814
57.7%
Common 2791
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
창 354
 
9.3%
원 344
 
9.0%
남 312
 
8.2%
구 292
 
7.7%
경 292
 
7.7%
시 285
 
7.5%
동 282
 
7.4%
산 182
 
4.8%
성 132
 
3.5%
도 110
 
2.9%
Other values (154) 1229
32.2%
Common
ValueCountFrequency (%)
1607
57.6%
1 191
 
6.8%
- 165
 
5.9%
5 152
 
5.4%
2 116
 
4.2%
0 113
 
4.0%
3 112
 
4.0%
4 82
 
2.9%
6 68
 
2.4%
7 56
 
2.0%
Other values (4) 129
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3814
57.7%
ASCII 2791
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1607
57.6%
1 191
 
6.8%
- 165
 
5.9%
5 152
 
5.4%
2 116
 
4.2%
0 113
 
4.0%
3 112
 
4.0%
4 82
 
2.9%
6 68
 
2.4%
7 56
 
2.0%
Other values (4) 129
 
4.6%
Hangul
ValueCountFrequency (%)
창 354
 
9.3%
원 344
 
9.0%
남 312
 
8.2%
구 292
 
7.7%
경 292
 
7.7%
시 285
 
7.5%
동 282
 
7.4%
산 182
 
4.8%
성 132
 
3.5%
도 110
 
2.9%
Other values (154) 1229
32.2%

등록일자
Date

MISSING 

Distinct45
Distinct (%)16.2%
Missing5
Missing (%)1.8%
Memory size2.3 KiB
Minimum2008-01-08 00:00:00
Maximum2021-11-11 00:00:00
2023-12-11T08:38:32.843158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:32.973608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)

보관대수
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)11.8%
Missing3
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean22.639286
Minimum0
Maximum53
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T08:38:33.083773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.95
Q120
median20
Q325
95-th percentile33
Maximum53
Range53
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.5106937
Coefficient of variation (CV)0.28758388
Kurtosis2.2575446
Mean22.639286
Median Absolute Deviation (MAD)5
Skewness0.69374435
Sum6339
Variance42.389132
MonotonicityNot monotonic
2023-12-11T08:38:33.196924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
20 90
31.8%
25 46
16.3%
30 26
 
9.2%
15 20
 
7.1%
18 8
 
2.8%
24 8
 
2.8%
23 8
 
2.8%
17 7
 
2.5%
16 6
 
2.1%
26 6
 
2.1%
Other values (23) 55
19.4%
ValueCountFrequency (%)
0 1
 
0.4%
8 1
 
0.4%
9 2
 
0.7%
10 5
 
1.8%
11 1
 
0.4%
12 1
 
0.4%
14 3
 
1.1%
15 20
7.1%
16 6
 
2.1%
17 7
 
2.5%
ValueCountFrequency (%)
53 1
 
0.4%
45 1
 
0.4%
40 5
1.8%
39 1
 
0.4%
38 1
 
0.4%
36 1
 
0.4%
35 3
1.1%
33 3
1.1%
32 3
1.1%
31 4
1.4%

위도
Real number (ℝ)

UNIQUE 

Distinct283
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.214971
Minimum35.088585
Maximum35.35329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T08:38:33.354116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.088585
5-th percentile35.140216
Q135.201689
median35.223321
Q335.241019
95-th percentile35.262048
Maximum35.35329
Range0.26470598
Interquartile range (IQR)0.03932943

Descriptive statistics

Standard deviation0.042364944
Coefficient of variation (CV)0.0012030379
Kurtosis1.1319754
Mean35.214971
Median Absolute Deviation (MAD)0.01983209
Skewness-0.70170299
Sum9965.8368
Variance0.0017947885
MonotonicityNot monotonic
2023-12-11T08:38:33.506556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.23023141 1
 
0.4%
35.15245095 1
 
0.4%
35.2839562 1
 
0.4%
35.27961762 1
 
0.4%
35.29124577 1
 
0.4%
35.2161123 1
 
0.4%
35.23765397 1
 
0.4%
35.23018759 1
 
0.4%
35.2185 1
 
0.4%
35.179214 1
 
0.4%
Other values (273) 273
96.5%
ValueCountFrequency (%)
35.0885845 1
0.4%
35.0885854 1
0.4%
35.0886905 1
0.4%
35.1000008 1
0.4%
35.10063496 1
0.4%
35.100843 1
0.4%
35.10383877 1
0.4%
35.1053123 1
0.4%
35.1054659 1
0.4%
35.1111448 1
0.4%
ValueCountFrequency (%)
35.35329048 1
0.4%
35.34809693 1
0.4%
35.3060586 1
0.4%
35.3023499 1
0.4%
35.3012806 1
0.4%
35.29124577 1
0.4%
35.2839562 1
0.4%
35.27961762 1
0.4%
35.27715209 1
0.4%
35.26636506 1
0.4%

경도
Real number (ℝ)

UNIQUE 

Distinct283
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.65728
Minimum128.49697
Maximum128.81787
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T08:38:33.644208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.49697
5-th percentile128.56055
Q1128.62669
median128.67022
Q3128.69205
95-th percentile128.71022
Maximum128.81787
Range0.3208995
Interquartile range (IQR)0.06536275

Descriptive statistics

Standard deviation0.055597088
Coefficient of variation (CV)0.00043213325
Kurtosis0.90487637
Mean128.65728
Median Absolute Deviation (MAD)0.0281122
Skewness-0.3435557
Sum36410.01
Variance0.0030910362
MonotonicityNot monotonic
2023-12-11T08:38:33.821917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5766995 1
 
0.4%
128.6730659 1
 
0.4%
128.6818273 1
 
0.4%
128.6887193 1
 
0.4%
128.6758769 1
 
0.4%
128.6727745 1
 
0.4%
128.6884081 1
 
0.4%
128.6539337 1
 
0.4%
128.6809 1
 
0.4%
128.563145 1
 
0.4%
Other values (273) 273
96.5%
ValueCountFrequency (%)
128.4969735 1
0.4%
128.5037005 1
0.4%
128.5046155 1
0.4%
128.5048056 1
0.4%
128.5105025 1
0.4%
128.52121 1
0.4%
128.5230124 1
0.4%
128.5260165 1
0.4%
128.5539188 1
0.4%
128.5576472 1
0.4%
ValueCountFrequency (%)
128.817873 1
0.4%
128.8144103 1
0.4%
128.8141018 1
0.4%
128.8100118 1
0.4%
128.809458 1
0.4%
128.8066506 1
0.4%
128.8027681 1
0.4%
128.7551345 1
0.4%
128.7510163 1
0.4%
128.7498012 1
0.4%

Interactions

2023-12-11T08:38:29.643361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:28.601032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:28.941668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:29.260102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:29.964471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:28.676939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:29.018053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:29.343261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:30.049393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:28.761575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:29.097610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:29.454220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:30.130642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:28.858533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:29.174275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:29.555997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:38:33.921474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호구동등록일자보관대수위도경도
번호1.0000.9890.9910.3410.2490.5630.612
구0.9891.0001.0000.4350.2950.3470.361
동0.9911.0001.0000.0000.0000.6810.755
등록일자0.3410.4350.0001.0000.8250.7450.715
보관대수0.2490.2950.0000.8251.0000.6020.143
위도0.5630.3470.6810.7450.6021.0000.858
경도0.6120.3610.7550.7150.1430.8581.000
2023-12-11T08:38:34.043095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동구
동1.0000.925
구0.9251.000
2023-12-11T08:38:34.166019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호보관대수위도경도구동
번호1.000-0.0110.076-0.0370.8430.841
보관대수-0.0111.0000.0220.1430.1250.000
위도0.0760.0221.000-0.4310.1500.282
경도-0.0370.143-0.4311.0000.1640.348
구0.8430.1250.1500.1641.0000.925
동0.8410.0000.2820.3480.9251.000

Missing values

2023-12-11T08:38:30.233908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:38:30.363881image/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.
2023-12-11T08:38:30.472206image/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

번호터미널명구동주소등록일자보관대수위도경도
01경남은행 본점 앞마산합포구교방동경남 창원시 마산회원구 석전동 267 도로2011-08-102035.230231128.576699
12경남지방경찰청마산합포구교방동경남 창원시 의창구 사림동 1-2 대2010-01-113035.236493128.693569
23대동다숲아파트 앞마산합포구문화동경남 창원시 진해구 장천동 119-14 도로2011-08-052035.129921128.706508
34대동백화점마산합포구문화동경남 창원시 성산구 상남동 503 도2010-06-223035.221165128.690339
45도계동 안골마산합포구반월중앙동경남 창원시 의창구 도계동 88-6(도)2021-07-272035.263783128.642599
56도계동 정류소앞마산합포구반월중앙동경남 창원시 의창구 도계동 444번지 버스정류소 옆2008-10-022035.258647128.63338
67소계동 SK주유소앞마산합포구오동동경남 창원시 의창구 소계동 366-3 도2010-01-112535.255846128.600338
78소라아파트앞마산합포구오동동경남 창원시 성산구 가음정동 558-2 도2009-05-134035.208117128.68667
89소죽도 찜질방마산합포구오동동경남 창원시 진해구 덕산동 585번지 소죽도찜질방2013-10-051435.140954128.688843
910속천종점마산합포구오동동경남 창원시 진해구 태평동 86-58도2011-08-052035.143924128.66989
번호터미널명구동주소등록일자보관대수위도경도
273274창원문성대학진해구충무동경남 창원시 성산구 중앙동 304-7 창원전문대2009-04-222535.237154128.661575
274275창원병원진해구충무동경남 창원시 성산구 중앙동 104-2 잡2009-04-232535.217527128.67121
275276창원상공회의소진해구충무동경남 창원시 성산구 신월동 501-41 도2010-06-222035.228312128.684272
276277창원시립곰두리체육센터진해구태백동경남 창원시 의창구 도계동 456-42014-12-092035.252883128.637518
277278창원시외버스터미널 옆진해구태백동경남 창원시 의창구 팔용동 35번지 창원시외버스터미널 앞2008-10-022535.235744128.639844
278279팔용동서식품진해구풍호동경남 창원시 의창구 팔용동 514-7 도2010-06-222035.250732128.613064
279280팔용종합상가진해구풍호동경남 창원시 의창구 팔용동 505 도2009-05-112635.255485128.613457
280281풍호초등학교사거리진해구풍호동경남 창원시 진해구 덕산동 516-6 도로2011-08-051735.140134128.707645
281282한국전력공사진해구풍호동경남 창원시 성산구 신월동 99-5 한국전력공사 앞 보도2008-10-022535.230858128.688789
282283한국폴리텍대학정문진해구풍호동경남 창원시 성산구 중앙동 110-12014-12-092535.225426128.668497