Overview

Dataset statistics

Number of variables10
Number of observations686
Missing cells7
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.1 KiB
Average record size in memory85.2 B

Variable types

Numeric5
Categorical3
Text2

Dataset

Description경상남도 김해시 버스정보 안내 단말기(BIT)의 정류장번호, 정류장명, 행정동, 위치, 통신망, 세부사양(LED 단면, LCD가로(23"),,,,), 장비유형(쉘터형, 독립형), 설치년도, 위도, 경도로 구성되어 있습니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15104697

Alerts

연번 is highly overall correlated with 정류소번호High correlation
정류소번호 is highly overall correlated with 연번High correlation
년도 is highly overall correlated with 형태High correlation
위도 is highly overall correlated with 읍면동명High correlation
경도 is highly overall correlated with 읍면동명High correlation
읍면동명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
형태 is highly overall correlated with 년도High correlation

Reproduction

Analysis started2023-12-10 22:52:15.659528
Analysis finished2023-12-10 22:52:19.977413
Duration4.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct685
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean343
Minimum1
Maximum685
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.2 KiB
2023-12-11T07:52:20.048747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile35.2
Q1172
median343
Q3514
95-th percentile650.8
Maximum685
Range684
Interquartile range (IQR)342

Descriptive statistics

Standard deviation197.88675
Coefficient of variation (CV)0.57692931
Kurtosis-1.2
Mean343
Median Absolute Deviation (MAD)171
Skewness0
Sum234955
Variance39159.167
MonotonicityStrictly increasing
2023-12-11T07:52:20.198957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
461 1
 
0.1%
453 1
 
0.1%
454 1
 
0.1%
455 1
 
0.1%
456 1
 
0.1%
457 1
 
0.1%
458 1
 
0.1%
459 1
 
0.1%
460 1
 
0.1%
Other values (675) 675
98.4%
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 (%)
685 1
0.1%
684 1
0.1%
683 1
0.1%
682 1
0.1%
681 1
0.1%
680 1
0.1%
679 1
0.1%
678 1
0.1%
677 1
0.1%
676 1
0.1%

읍면동명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
장유3동
73 
내외동
68 
진영읍
67 
장유1동
61 
북부동
55 
Other values (15)
362 

Length

Max length5
Median length3
Mean length3.3425656
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row칠산서부동
2nd row부원동
3rd row부원동
4th row회현동
5th row회현동

Common Values

ValueCountFrequency (%)
장유3동 73
10.6%
내외동 68
9.9%
진영읍 67
9.8%
장유1동 61
 
8.9%
북부동 55
 
8.0%
주촌면 49
 
7.1%
장유2동 42
 
6.1%
진례면 38
 
5.5%
한림면 37
 
5.4%
활천동 32
 
4.7%
Other values (10) 164
23.9%

Length

2023-12-11T07:52:20.365075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장유3동 73
10.6%
내외동 68
9.9%
진영읍 67
9.8%
장유1동 61
 
8.9%
북부동 55
 
8.0%
주촌면 49
 
7.1%
장유2동 42
 
6.1%
진례면 38
 
5.5%
한림면 37
 
5.4%
활천동 32
 
4.7%
Other values (10) 164
23.9%

정류소명
Text

Distinct429
Distinct (%)62.6%
Missing1
Missing (%)0.1%
Memory size5.5 KiB
2023-12-11T07:52:20.610289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length4.950365
Min length2

Characters and Unicode

Total characters3391
Distinct characters292
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

Unique185 ?
Unique (%)27.0%

Sample

1st row봉황역
2nd row금강병원
3rd row중앙지구대
4th row신한은행
5th row분성사거리
ValueCountFrequency (%)
동상동 4
 
0.6%
일동한신아파트 4
 
0.6%
외동축협 3
 
0.4%
경남은행 3
 
0.4%
부영6차아파트 3
 
0.4%
부원역 3
 
0.4%
삼성아파트 3
 
0.4%
진영중학교 3
 
0.4%
한림정역 3
 
0.4%
내동사거리 3
 
0.4%
Other values (420) 655
95.3%
2023-12-11T07:52:20.997289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 96
 
2.8%
아 92
 
2.7%
지 87
 
2.6%
파 81
 
2.4%
트 76
 
2.2%
교 76
 
2.2%
을 72
 
2.1%
마 72
 
2.1%
학 67
 
2.0%
대 55
 
1.6%
Other values (282) 2617
77.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3274
96.5%
Decimal Number 86
 
2.5%
Close Punctuation 7
 
0.2%
Open Punctuation 7
 
0.2%
Uppercase Letter 7
 
0.2%
Dash Punctuation 4
 
0.1%
Lowercase Letter 4
 
0.1%
Space Separator 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 96
 
2.9%
아 92
 
2.8%
지 87
 
2.7%
파 81
 
2.5%
트 76
 
2.3%
교 76
 
2.3%
을 72
 
2.2%
마 72
 
2.2%
학 67
 
2.0%
대 55
 
1.7%
Other values (265) 2500
76.4%
Decimal Number
ValueCountFrequency (%)
1 27
31.4%
2 25
29.1%
3 10
 
11.6%
4 9
 
10.5%
6 7
 
8.1%
8 4
 
4.7%
7 3
 
3.5%
9 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
S 3
42.9%
K 2
28.6%
H 1
 
14.3%
L 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3274
96.5%
Common 106
 
3.1%
Latin 11
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 96
 
2.9%
아 92
 
2.8%
지 87
 
2.7%
파 81
 
2.5%
트 76
 
2.3%
교 76
 
2.3%
을 72
 
2.2%
마 72
 
2.2%
학 67
 
2.0%
대 55
 
1.7%
Other values (265) 2500
76.4%
Common
ValueCountFrequency (%)
1 27
25.5%
2 25
23.6%
3 10
 
9.4%
4 9
 
8.5%
) 7
 
6.6%
( 7
 
6.6%
6 7
 
6.6%
8 4
 
3.8%
- 4
 
3.8%
7 3
 
2.8%
Other values (2) 3
 
2.8%
Latin
ValueCountFrequency (%)
e 4
36.4%
S 3
27.3%
K 2
18.2%
H 1
 
9.1%
L 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3274
96.5%
ASCII 117
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 96
 
2.9%
아 92
 
2.8%
지 87
 
2.7%
파 81
 
2.5%
트 76
 
2.3%
교 76
 
2.3%
을 72
 
2.2%
마 72
 
2.2%
학 67
 
2.0%
대 55
 
1.7%
Other values (265) 2500
76.4%
ASCII
ValueCountFrequency (%)
1 27
23.1%
2 25
21.4%
3 10
 
8.5%
4 9
 
7.7%
) 7
 
6.0%
( 7
 
6.0%
6 7
 
6.0%
8 4
 
3.4%
- 4
 
3.4%
e 4
 
3.4%
Other values (7) 13
11.1%

정류소번호
Real number (ℝ)

HIGH CORRELATION 

Distinct685
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1963.9956
Minimum1002
Maximum3525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.2 KiB
2023-12-11T07:52:21.163396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1002
5-th percentile1051.2
Q11215
median1757
Q32804
95-th percentile3305.8
Maximum3525
Range2523
Interquartile range (IQR)1589

Descriptive statistics

Standard deviation793.52991
Coefficient of variation (CV)0.40403853
Kurtosis-1.2638353
Mean1963.9956
Median Absolute Deviation (MAD)606
Skewness0.46126806
Sum1345337
Variance629689.71
MonotonicityStrictly increasing
2023-12-11T07:52:21.312008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1002 1
 
0.1%
2352 1
 
0.1%
2336 1
 
0.1%
2337 1
 
0.1%
2338 1
 
0.1%
2339 1
 
0.1%
2342 1
 
0.1%
2347 1
 
0.1%
2349 1
 
0.1%
2351 1
 
0.1%
Other values (675) 675
98.4%
ValueCountFrequency (%)
1002 1
0.1%
1004 1
0.1%
1005 1
0.1%
1006 1
0.1%
1007 1
0.1%
1008 1
0.1%
1009 1
0.1%
1010 1
0.1%
1011 1
0.1%
1012 1
0.1%
ValueCountFrequency (%)
3525 1
0.1%
3521 1
0.1%
3520 1
0.1%
3512 1
0.1%
3372 1
0.1%
3371 1
0.1%
3370 1
0.1%
3357 1
0.1%
3356 1
0.1%
3355 1
0.1%

형태
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
LED(3*12)(거)
225 
LED(3*6)(거)
161 
LED(3*12)
84 
LED(3*6)
61 
LED(2*12)(거)
34 
Other values (14)
121 

Length

Max length21
Median length12
Mean length10.327988
Min length4

Unique

Unique5 ?
Unique (%)0.7%

Sample

1st rowLED(3*12)(거)
2nd rowLCD40"(쉘)
3rd rowLCD46"
4th rowLCD46"
5th rowLCD46"

Common Values

ValueCountFrequency (%)
LED(3*12)(거) 225
32.8%
LED(3*6)(거) 161
23.5%
LED(3*12) 84
 
12.2%
LED(3*6) 61
 
8.9%
LED(2*12)(거) 34
 
5.0%
LCD40" 23
 
3.4%
LCD32" 22
 
3.2%
LCD32"(거) 22
 
3.2%
LED(6*6)(거) 15
 
2.2%
LCD40"(쉘) 14
 
2.0%
Other values (9) 25
 
3.6%

Length

2023-12-11T07:52:21.457920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
led(3*12)(거 225
32.8%
led(3*6)(거 161
23.5%
led(3*12 84
 
12.2%
led(3*6 61
 
8.9%
led(2*12)(거 34
 
5.0%
lcd40 23
 
3.4%
lcd32 22
 
3.2%
lcd32"(거 22
 
3.2%
led(6*6)(거 15
 
2.2%
lcd46 14
 
2.0%
Other values (9) 25
 
3.6%

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)2.3%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2016.6569
Minimum2007
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.2 KiB
2023-12-11T07:52:21.561388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2008
Q12015
median2017
Q32020
95-th percentile2021.8
Maximum2022
Range15
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.9315004
Coefficient of variation (CV)0.0019495137
Kurtosis0.10196141
Mean2016.6569
Median Absolute Deviation (MAD)3
Skewness-0.91584597
Sum1381410
Variance15.456695
MonotonicityNot monotonic
2023-12-11T07:52:21.695716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2020 123
17.9%
2017 94
13.7%
2018 72
10.5%
2015 58
8.5%
2016 56
8.2%
2021 51
7.4%
2019 47
 
6.9%
2022 35
 
5.1%
2012 29
 
4.2%
2014 26
 
3.8%
Other values (6) 94
13.7%
ValueCountFrequency (%)
2007 25
3.6%
2008 23
 
3.4%
2009 13
 
1.9%
2010 5
 
0.7%
2011 23
 
3.4%
2012 29
4.2%
2013 5
 
0.7%
2014 26
3.8%
2015 58
8.5%
2016 56
8.2%
ValueCountFrequency (%)
2022 35
 
5.1%
2021 51
7.4%
2020 123
17.9%
2019 47
 
6.9%
2018 72
10.5%
2017 94
13.7%
2016 56
8.2%
2015 58
8.5%
2014 26
 
3.8%
2013 5
 
0.7%

망 형태
Categorical

Distinct9
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
KT
481 
자가망
71 
KT LTE
 
41
자가망(M)
 
35
자가망(S)
 
30
Other values (4)
 
28

Length

Max length7
Median length2
Mean length2.7886297
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st rowKT
2nd rowKT LTE
3rd rowKT
4th rowKT
5th rowKT

Common Values

ValueCountFrequency (%)
KT 481
70.1%
자가망 71
 
10.3%
KT LTE 41
 
6.0%
자가망(M) 35
 
5.1%
자가망(S) 30
 
4.4%
KT(M) 13
 
1.9%
무선 13
 
1.9%
자가망(무선) 1
 
0.1%
<NA> 1
 
0.1%

Length

2023-12-11T07:52:21.849043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:52:21.980102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kt 522
71.8%
자가망 71
 
9.8%
lte 41
 
5.6%
자가망(m 35
 
4.8%
자가망(s 30
 
4.1%
kt(m 13
 
1.8%
무선 13
 
1.8%
자가망(무선 1
 
0.1%
na 1
 
0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct685
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean35.238561
Minimum35.164142
Maximum35.373068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.2 KiB
2023-12-11T07:52:22.109858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.164142
5-th percentile35.173912
Q135.205644
median35.234857
Q335.262072
95-th percentile35.313778
Maximum35.373068
Range0.208926
Interquartile range (IQR)0.05642842

Descriptive statistics

Standard deviation0.041998534
Coefficient of variation (CV)0.0011918345
Kurtosis-0.17961428
Mean35.238561
Median Absolute Deviation (MAD)0.02826713
Skewness0.42813593
Sum24138.414
Variance0.0017638769
MonotonicityNot monotonic
2023-12-11T07:52:22.257440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.22648541 1
 
0.1%
35.2623531 1
 
0.1%
35.25670882 1
 
0.1%
35.25349167 1
 
0.1%
35.25354927 1
 
0.1%
35.25172804 1
 
0.1%
35.24149722 1
 
0.1%
35.24469647 1
 
0.1%
35.2310129 1
 
0.1%
35.26693729 1
 
0.1%
Other values (675) 675
98.4%
ValueCountFrequency (%)
35.1641416 1
0.1%
35.1645089 1
0.1%
35.1648072 1
0.1%
35.1648867 1
0.1%
35.1661496 1
0.1%
35.1663232 1
0.1%
35.1672472 1
0.1%
35.1673512 1
0.1%
35.1677212 1
0.1%
35.168015 1
0.1%
ValueCountFrequency (%)
35.3730676 1
0.1%
35.36850556 1
0.1%
35.3609348 1
0.1%
35.35290278 1
0.1%
35.34739722 1
0.1%
35.3418341 1
0.1%
35.33911944 1
0.1%
35.33891111 1
0.1%
35.33809167 1
0.1%
35.33583889 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct682
Distinct (%)99.6%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean128.83725
Minimum128.70763
Maximum129.0013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.2 KiB
2023-12-11T07:52:22.400830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70763
5-th percentile128.73969
Q1128.80201
median128.83955
Q3128.87279
95-th percentile128.92075
Maximum129.0013
Range0.2936737
Interquartile range (IQR)0.0707813

Descriptive statistics

Standard deviation0.056405493
Coefficient of variation (CV)0.00043780422
Kurtosis-0.045781782
Mean128.83725
Median Absolute Deviation (MAD)0.0364368
Skewness0.085503092
Sum88253.518
Variance0.0031815796
MonotonicityNot monotonic
2023-12-11T07:52:22.548416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8026611 2
 
0.3%
128.8822749 2
 
0.3%
128.7360333 2
 
0.3%
128.8690482 1
 
0.1%
128.8713556 1
 
0.1%
128.8715953 1
 
0.1%
128.8723152 1
 
0.1%
128.8632667 1
 
0.1%
128.8679593 1
 
0.1%
128.9210402 1
 
0.1%
Other values (672) 672
98.0%
ValueCountFrequency (%)
128.7076263 1
0.1%
128.7078813 1
0.1%
128.7107227 1
0.1%
128.7110818 1
0.1%
128.7141437 1
0.1%
128.714275 1
0.1%
128.7145539 1
0.1%
128.7188262 1
0.1%
128.7188833 1
0.1%
128.7194945 1
0.1%
ValueCountFrequency (%)
129.0013 1
0.1%
129.0000476 1
0.1%
128.9983583 1
0.1%
128.9966444 1
0.1%
128.9946833 1
0.1%
128.994555 1
0.1%
128.9908972 1
0.1%
128.9824982 1
0.1%
128.9819556 1
0.1%
128.9816833 1
0.1%

주소
Text

Distinct669
Distinct (%)97.7%
Missing1
Missing (%)0.1%
Memory size5.5 KiB
2023-12-11T07:52:22.839510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length17.337226
Min length13

Characters and Unicode

Total characters11876
Distinct characters118
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

Unique654 ?
Unique (%)95.5%

Sample

1st row경남 김해시 전하동 31-41
2nd row경남 김해시 부원동 608-1
3rd row경남 김해시 부원동 852-5
4th row경남 김해시 서상동 129-13
5th row경남 김해시 서상동 152-3
ValueCountFrequency (%)
경남 685
23.0%
김해시 685
23.0%
진영읍 65
 
2.2%
주촌면 49
 
1.6%
진례면 39
 
1.3%
외동 37
 
1.2%
한림면 36
 
1.2%
내동 31
 
1.0%
삼계동 30
 
1.0%
부곡동 28
 
0.9%
Other values (749) 1296
43.5%
2023-12-11T07:52:23.282478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2305
19.4%
시 688
 
5.8%
경 685
 
5.8%
김 685
 
5.8%
해 685
 
5.8%
남 685
 
5.8%
1 668
 
5.6%
- 563
 
4.7%
동 535
 
4.5%
2 369
 
3.1%
Other values (108) 4008
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6105
51.4%
Decimal Number 2899
24.4%
Space Separator 2305
 
19.4%
Dash Punctuation 563
 
4.7%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 688
11.3%
경 685
11.2%
김 685
11.2%
해 685
11.2%
남 685
11.2%
동 535
 
8.8%
리 237
 
3.9%
면 168
 
2.8%
진 126
 
2.1%
영 87
 
1.4%
Other values (94) 1524
25.0%
Decimal Number
ValueCountFrequency (%)
1 668
23.0%
2 369
12.7%
3 331
11.4%
5 257
 
8.9%
4 253
 
8.7%
6 249
 
8.6%
0 219
 
7.6%
9 193
 
6.7%
7 181
 
6.2%
8 179
 
6.2%
Space Separator
ValueCountFrequency (%)
2305
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 563
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6105
51.4%
Common 5771
48.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 688
11.3%
경 685
11.2%
김 685
11.2%
해 685
11.2%
남 685
11.2%
동 535
 
8.8%
리 237
 
3.9%
면 168
 
2.8%
진 126
 
2.1%
영 87
 
1.4%
Other values (94) 1524
25.0%
Common
ValueCountFrequency (%)
2305
39.9%
1 668
 
11.6%
- 563
 
9.8%
2 369
 
6.4%
3 331
 
5.7%
5 257
 
4.5%
4 253
 
4.4%
6 249
 
4.3%
0 219
 
3.8%
9 193
 
3.3%
Other values (4) 364
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6105
51.4%
ASCII 5771
48.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2305
39.9%
1 668
 
11.6%
- 563
 
9.8%
2 369
 
6.4%
3 331
 
5.7%
5 257
 
4.5%
4 253
 
4.4%
6 249
 
4.3%
0 219
 
3.8%
9 193
 
3.3%
Other values (4) 364
 
6.3%
Hangul
ValueCountFrequency (%)
시 688
11.3%
경 685
11.2%
김 685
11.2%
해 685
11.2%
남 685
11.2%
동 535
 
8.8%
리 237
 
3.9%
면 168
 
2.8%
진 126
 
2.1%
영 87
 
1.4%
Other values (94) 1524
25.0%

Interactions

2023-12-11T07:52:18.859739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:16.316998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:16.854645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.410933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.055581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.963410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:16.414119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:16.993744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.586425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.168746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:19.083089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:16.521755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.093090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.696944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.277117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:19.201569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:16.630943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.201087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.825093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.386491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:19.318386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:16.738455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.296966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:17.924132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.473806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:52:23.405824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동명정류소번호형태년도망 형태위도경도
연번1.0000.7700.9770.5220.6280.5590.7350.716
읍면동명0.7701.0000.7800.6650.6040.5900.9050.933
정류소번호0.9770.7801.0000.4650.5950.5430.7180.707
형태0.5220.6650.4651.0000.8280.5720.4280.492
년도0.6280.6040.5950.8281.0000.5540.3370.502
망 형태0.5590.5900.5430.5720.5541.0000.2490.460
위도0.7350.9050.7180.4280.3370.2491.0000.787
경도0.7160.9330.7070.4920.5020.4600.7871.000
2023-12-11T07:52:23.520768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
형태읍면동명망 형태
형태1.0000.2620.280
읍면동명0.2621.0000.293
망 형태0.2800.2931.000
2023-12-11T07:52:23.605831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번정류소번호년도위도경도읍면동명형태망 형태
연번1.0001.0000.295-0.225-0.1410.4170.2280.308
정류소번호1.0001.0000.295-0.225-0.1410.4280.1960.295
년도0.2950.2951.0000.075-0.2370.2710.5320.317
위도-0.225-0.2250.0751.000-0.0260.6310.1770.121
경도-0.141-0.141-0.237-0.0261.0000.7060.2110.239
읍면동명0.4170.4280.2710.6310.7061.0000.2620.293
형태0.2280.1960.5320.1770.2110.2621.0000.280
망 형태0.3080.2950.3170.1210.2390.2930.2801.000

Missing values

2023-12-11T07:52:19.478167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:52:19.690051image/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.
2023-12-11T07:52:19.864232image/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

연번읍면동명정류소명정류소번호형태년도망 형태위도경도주소
01칠산서부동봉황역1002LED(3*12)(거)2015KT35.226485128.874076경남 김해시 전하동 31-41
12부원동금강병원1004LCD40"(쉘)2008KT LTE35.228377128.882527경남 김해시 부원동 608-1
23부원동중앙지구대1005LCD46"2008KT35.230109128.882275경남 김해시 부원동 852-5
34회현동신한은행1006LCD46"2008KT35.232609128.881823경남 김해시 서상동 129-13
45회현동분성사거리1007LCD46"2008KT35.233462128.880618경남 김해시 서상동 152-3
56회현동수로왕릉1008LED(3*12)(거)2020KT(M)35.233217128.878669경남 김해시 서상동 330-26
67회현동김해도서관1009LED(3*12)(거)2012KT(M)35.232669128.874194경남 김해시 봉황동 461-3
78내외동김해보건소1010LED(3*12)(거)2012KT35.230673128.869513경남 김해시 외동 1261-7
89내외동한국2차아파트1011LED(3*12)2012KT(M)35.229997128.8647경남 김해시 외동 1249-5
910내외동중앙병원1012LED(3*12)2012KT35.230985128.859326경남 김해시 외동 1269
연번읍면동명정류소명정류소번호형태년도망 형태위도경도주소
676677장유3동원메이저힐스테이트3356LCD32"(거)2020자가망35.167721128.830563경남 김해시 장유동 988
677678칠산서부동양지교3357LED(3*6)(거)2020KT35.190256128.859533경남 김해시 화목동 223-1
678679장유3동모산초등학교3370LCD32"(거)2020자가망35.168015128.827776경남 김해시 장유동 987
679680진영읍진영휴먼시아3371LED(3*12)(거)2020자가망35.305822128.739391경남 김해시 여래리 508-3
680681진영읍진영휴먼시아3372LED(3*12)(거)2020자가망35.306006128.73944경남 김해시 여래리 980
681682진영읍진영중학교3512LED(3*6)(거)2018KT35.307891128.735221경남 김해시 진영읍 진영리 1629-6
682683동상동롯데캐슬3520LCD32"2008자가망(S)35.240288128.885575경남 김해시 동상동 1102-12
683684동상동롯데캐슬3521LCD32"2008자가망(M)35.240262128.885218경남 김해시 동상동 1120-4
684685내외동무접마을3525LED(3*12)(거)2015KT35.229799128.86743경남 김해시 외동 396
685<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>