Overview

Dataset statistics

Number of variables9
Number of observations637
Missing cells92
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.8 KiB
Average record size in memory75.2 B

Variable types

Numeric3
Categorical2
Text3
DateTime1

Dataset

Description충청남도 보령시에 설치된 버스 승강장 현황 데이터로 관리번호, 읍면동, 승강장 명칭, 승강장 위치, 소재지 주소, 위도, 경도, 승장강구조 등의 항목으로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15116199/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
관리번호 is highly overall correlated with 읍면동High correlation
위도 is highly overall correlated with 읍면동High correlation
경도 is highly overall correlated with 읍면동High correlation
읍면동 is highly overall correlated with 관리번호 and 2 other fieldsHigh correlation
승강장 위치 has 12 (1.9%) missing valuesMissing
위도 has 40 (6.3%) missing valuesMissing
경도 has 40 (6.3%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:32:30.288249
Analysis finished2023-12-12 20:32:32.122542
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct637
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean319.72214
Minimum1
Maximum638
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-13T05:32:32.205745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.8
Q1160
median320
Q3479
95-th percentile606.2
Maximum638
Range637
Interquartile range (IQR)319

Descriptive statistics

Standard deviation184.37838
Coefficient of variation (CV)0.57668318
Kurtosis-1.2000272
Mean319.72214
Median Absolute Deviation (MAD)160
Skewness-0.0029127877
Sum203663
Variance33995.387
MonotonicityStrictly increasing
2023-12-13T05:32:32.381535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
430 1
 
0.2%
423 1
 
0.2%
424 1
 
0.2%
425 1
 
0.2%
426 1
 
0.2%
427 1
 
0.2%
428 1
 
0.2%
429 1
 
0.2%
431 1
 
0.2%
Other values (627) 627
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
638 1
0.2%
637 1
0.2%
636 1
0.2%
635 1
0.2%
634 1
0.2%
633 1
0.2%
632 1
0.2%
631 1
0.2%
630 1
0.2%
629 1
0.2%

읍면동
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
청라면
68 
주교면
62 
웅천읍
56 
대천5동
50 
남포면
49 
Other values (11)
352 

Length

Max length4
Median length3
Mean length3.2291994
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청라면 68
10.7%
주교면 62
9.7%
웅천읍 56
 
8.8%
대천5동 50
 
7.8%
남포면 49
 
7.7%
천북면 45
 
7.1%
오천면 42
 
6.6%
주산면 41
 
6.4%
대천4동 41
 
6.4%
청소면 39
 
6.1%
Other values (6) 144
22.6%

Length

2023-12-13T05:32:32.562531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청라면 68
10.7%
주교면 62
9.7%
웅천읍 56
 
8.8%
대천5동 50
 
7.8%
남포면 49
 
7.7%
천북면 45
 
7.1%
오천면 42
 
6.6%
주산면 41
 
6.4%
대천4동 41
 
6.4%
청소면 39
 
6.1%
Other values (6) 144
22.6%

승강장명칭
Text

Distinct516
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2023-12-13T05:32:32.942583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length4.4081633
Min length2

Characters and Unicode

Total characters2808
Distinct characters306
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

Unique420 ?
Unique (%)65.9%

Sample

1st row평2리
2nd row새터(수부1리)
3rd row신기
4th row수부1리
5th row수부3리
ValueCountFrequency (%)
명칭없음 6
 
0.9%
앞 5
 
0.8%
마강2리 4
 
0.6%
고정 4
 
0.6%
신대3리 4
 
0.6%
방목 4
 
0.6%
여술 4
 
0.6%
시티프라디움 4
 
0.6%
은포 4
 
0.6%
옥계 3
 
0.5%
Other values (511) 605
93.5%
2023-12-13T05:32:33.546002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 184
 
6.6%
) 96
 
3.4%
( 95
 
3.4%
장 58
 
2.1%
2 53
 
1.9%
동 51
 
1.8%
대 51
 
1.8%
1 44
 
1.6%
산 42
 
1.5%
천 42
 
1.5%
Other values (296) 2092
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2413
85.9%
Decimal Number 153
 
5.4%
Close Punctuation 96
 
3.4%
Open Punctuation 95
 
3.4%
Space Separator 34
 
1.2%
Uppercase Letter 8
 
0.3%
Dash Punctuation 5
 
0.2%
Other Punctuation 2
 
0.1%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 184
 
7.6%
장 58
 
2.4%
동 51
 
2.1%
대 51
 
2.1%
산 42
 
1.7%
천 42
 
1.7%
마 41
 
1.7%
주 40
 
1.7%
신 37
 
1.5%
골 34
 
1.4%
Other values (275) 1833
76.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
12.5%
K 1
12.5%
V 1
12.5%
G 1
12.5%
C 1
12.5%
T 1
12.5%
P 1
12.5%
A 1
12.5%
Decimal Number
ValueCountFrequency (%)
2 53
34.6%
1 44
28.8%
3 35
22.9%
4 17
 
11.1%
8 2
 
1.3%
9 1
 
0.7%
5 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
→ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2413
85.9%
Common 387
 
13.8%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 184
 
7.6%
장 58
 
2.4%
동 51
 
2.1%
대 51
 
2.1%
산 42
 
1.7%
천 42
 
1.7%
마 41
 
1.7%
주 40
 
1.7%
신 37
 
1.5%
골 34
 
1.4%
Other values (275) 1833
76.0%
Common
ValueCountFrequency (%)
) 96
24.8%
( 95
24.5%
2 53
13.7%
1 44
11.4%
3 35
 
9.0%
34
 
8.8%
4 17
 
4.4%
- 5
 
1.3%
, 2
 
0.5%
8 2
 
0.5%
Other values (3) 4
 
1.0%
Latin
ValueCountFrequency (%)
S 1
12.5%
K 1
12.5%
V 1
12.5%
G 1
12.5%
C 1
12.5%
T 1
12.5%
P 1
12.5%
A 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2413
85.9%
ASCII 393
 
14.0%
Arrows 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 184
 
7.6%
장 58
 
2.4%
동 51
 
2.1%
대 51
 
2.1%
산 42
 
1.7%
천 42
 
1.7%
마 41
 
1.7%
주 40
 
1.7%
신 37
 
1.5%
골 34
 
1.4%
Other values (275) 1833
76.0%
ASCII
ValueCountFrequency (%)
) 96
24.4%
( 95
24.2%
2 53
13.5%
1 44
11.2%
3 35
 
8.9%
34
 
8.7%
4 17
 
4.3%
- 5
 
1.3%
, 2
 
0.5%
8 2
 
0.5%
Other values (10) 10
 
2.5%
Arrows
ValueCountFrequency (%)
→ 2
100.0%

승강장 위치
Text

MISSING 

Distinct607
Distinct (%)97.1%
Missing12
Missing (%)1.9%
Memory size5.1 KiB
2023-12-13T05:32:33.884861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length13.184
Min length3

Characters and Unicode

Total characters8240
Distinct characters258
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

Unique591 ?
Unique (%)94.6%

Sample

1st row평2리 노인회관 옆
2nd row수부1 만수로 485 (김광제묘소 입구)
3rd row수부1 신기2길 입구
4th row수부1 만수로 420 대각 맞은편
5th row수부3 만수로 345 앞
ValueCountFrequency (%)
앞 119
 
5.7%
맞은편 76
 
3.6%
옆 55
 
2.6%
충서로 41
 
2.0%
토정로 28
 
1.3%
대해로 27
 
1.3%
동대동 20
 
1.0%
대청로 18
 
0.9%
죽성로 17
 
0.8%
성주산로 17
 
0.8%
Other values (817) 1673
80.0%
2023-12-13T05:32:34.419600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1488
 
18.1%
리 417
 
5.1%
1 417
 
5.1%
로 416
 
5.0%
2 296
 
3.6%
3 251
 
3.0%
길 201
 
2.4%
4 173
 
2.1%
5 158
 
1.9%
대 152
 
1.8%
Other values (248) 4271
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4726
57.4%
Decimal Number 1934
23.5%
Space Separator 1488
 
18.1%
Dash Punctuation 52
 
0.6%
Close Punctuation 20
 
0.2%
Open Punctuation 20
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 417
 
8.8%
로 416
 
8.8%
길 201
 
4.3%
대 152
 
3.2%
천 123
 
2.6%
은 122
 
2.6%
앞 120
 
2.5%
통 114
 
2.4%
산 104
 
2.2%
성 92
 
1.9%
Other values (234) 2865
60.6%
Decimal Number
ValueCountFrequency (%)
1 417
21.6%
2 296
15.3%
3 251
13.0%
4 173
8.9%
5 158
 
8.2%
6 146
 
7.5%
7 136
 
7.0%
0 123
 
6.4%
8 123
 
6.4%
9 111
 
5.7%
Space Separator
ValueCountFrequency (%)
1488
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4726
57.4%
Common 3514
42.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 417
 
8.8%
로 416
 
8.8%
길 201
 
4.3%
대 152
 
3.2%
천 123
 
2.6%
은 122
 
2.6%
앞 120
 
2.5%
통 114
 
2.4%
산 104
 
2.2%
성 92
 
1.9%
Other values (234) 2865
60.6%
Common
ValueCountFrequency (%)
1488
42.3%
1 417
 
11.9%
2 296
 
8.4%
3 251
 
7.1%
4 173
 
4.9%
5 158
 
4.5%
6 146
 
4.2%
7 136
 
3.9%
0 123
 
3.5%
8 123
 
3.5%
Other values (4) 203
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4726
57.4%
ASCII 3514
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1488
42.3%
1 417
 
11.9%
2 296
 
8.4%
3 251
 
7.1%
4 173
 
4.9%
5 158
 
4.5%
6 146
 
4.2%
7 136
 
3.9%
0 123
 
3.5%
8 123
 
3.5%
Other values (4) 203
 
5.8%
Hangul
ValueCountFrequency (%)
리 417
 
8.8%
로 416
 
8.8%
길 201
 
4.3%
대 152
 
3.2%
천 123
 
2.6%
은 122
 
2.6%
앞 120
 
2.5%
통 114
 
2.4%
산 104
 
2.2%
성 92
 
1.9%
Other values (234) 2865
60.6%

소재지 주소
Text

Distinct604
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2023-12-13T05:32:34.786252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length20.830455
Min length16

Characters and Unicode

Total characters13269
Distinct characters113
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique575 ?
Unique (%)90.3%

Sample

1st row충청남도 보령시 웅천읍 평리 630-1
2nd row충청남도 보령시 웅천읍 수부리 145-1
3rd row충청남도 보령시 웅천읍 수부리 산 19-10
4th row충청남도 보령시 웅천읍 수부리 331-4
5th row충청남도 보령시 웅천읍 수부리 525
ValueCountFrequency (%)
충청남도 637
20.9%
보령시 637
20.9%
청라면 68
 
2.2%
주교면 62
 
2.0%
웅천읍 56
 
1.8%
남포면 49
 
1.6%
천북면 45
 
1.5%
주산면 41
 
1.3%
청소면 39
 
1.3%
명천동 38
 
1.2%
Other values (696) 1382
45.3%
2023-12-13T05:32:35.608041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2419
18.2%
청 749
 
5.6%
남 693
 
5.2%
도 656
 
4.9%
보 648
 
4.9%
령 642
 
4.8%
충 637
 
4.8%
시 637
 
4.8%
리 491
 
3.7%
- 480
 
3.6%
Other values (103) 5217
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7863
59.3%
Decimal Number 2506
 
18.9%
Space Separator 2419
 
18.2%
Dash Punctuation 480
 
3.6%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 749
 
9.5%
남 693
 
8.8%
도 656
 
8.3%
보 648
 
8.2%
령 642
 
8.2%
충 637
 
8.1%
시 637
 
8.1%
리 491
 
6.2%
면 425
 
5.4%
천 200
 
2.5%
Other values (90) 2085
26.5%
Decimal Number
ValueCountFrequency (%)
1 437
17.4%
3 316
12.6%
2 312
12.5%
4 281
11.2%
5 224
8.9%
9 208
8.3%
7 201
8.0%
6 189
7.5%
8 170
 
6.8%
0 168
 
6.7%
Space Separator
ValueCountFrequency (%)
2419
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 480
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7863
59.3%
Common 5406
40.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 749
 
9.5%
남 693
 
8.8%
도 656
 
8.3%
보 648
 
8.2%
령 642
 
8.2%
충 637
 
8.1%
시 637
 
8.1%
리 491
 
6.2%
면 425
 
5.4%
천 200
 
2.5%
Other values (90) 2085
26.5%
Common
ValueCountFrequency (%)
2419
44.7%
- 480
 
8.9%
1 437
 
8.1%
3 316
 
5.8%
2 312
 
5.8%
4 281
 
5.2%
5 224
 
4.1%
9 208
 
3.8%
7 201
 
3.7%
6 189
 
3.5%
Other values (3) 339
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7863
59.3%
ASCII 5406
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2419
44.7%
- 480
 
8.9%
1 437
 
8.1%
3 316
 
5.8%
2 312
 
5.8%
4 281
 
5.2%
5 224
 
4.1%
9 208
 
3.8%
7 201
 
3.7%
6 189
 
3.5%
Other values (3) 339
 
6.3%
Hangul
ValueCountFrequency (%)
청 749
 
9.5%
남 693
 
8.8%
도 656
 
8.3%
보 648
 
8.2%
령 642
 
8.2%
충 637
 
8.1%
시 637
 
8.1%
리 491
 
6.2%
면 425
 
5.4%
천 200
 
2.5%
Other values (90) 2085
26.5%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct568
Distinct (%)95.1%
Missing40
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean36.348964
Minimum36.173369
Maximum36.509213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-13T05:32:35.775017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.173369
5-th percentile36.204431
Q136.297141
median36.354237
Q336.407176
95-th percentile36.476033
Maximum36.509213
Range0.33584447
Interquartile range (IQR)0.11003494

Descriptive statistics

Standard deviation0.080989932
Coefficient of variation (CV)0.0022281222
Kurtosis-0.62476477
Mean36.348964
Median Absolute Deviation (MAD)0.05415798
Skewness-0.26924929
Sum21700.332
Variance0.0065593691
MonotonicityNot monotonic
2023-12-13T05:32:35.915776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.33294323 3
 
0.5%
36.37073922 3
 
0.5%
36.34271451 2
 
0.3%
36.39081339 2
 
0.3%
36.322724 2
 
0.3%
36.31637667 2
 
0.3%
36.33494296 2
 
0.3%
36.33385815 2
 
0.3%
36.34163716 2
 
0.3%
36.44246343 2
 
0.3%
Other values (558) 575
90.3%
(Missing) 40
 
6.3%
ValueCountFrequency (%)
36.17336891 1
0.2%
36.1737343 1
0.2%
36.17468681 1
0.2%
36.17578392 1
0.2%
36.17828643 1
0.2%
36.179194 1
0.2%
36.17995395 1
0.2%
36.18009829 1
0.2%
36.18017759 1
0.2%
36.18052909 1
0.2%
ValueCountFrequency (%)
36.50921338 1
0.2%
36.50838739 1
0.2%
36.50836941 1
0.2%
36.50802899 1
0.2%
36.50511089 1
0.2%
36.50333292 1
0.2%
36.49617736 1
0.2%
36.49609418 1
0.2%
36.49503982 1
0.2%
36.49489493 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct568
Distinct (%)95.1%
Missing40
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean126.58898
Minimum126.39635
Maximum126.72685
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-13T05:32:36.076580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39635
5-th percentile126.50594
Q1126.55452
median126.58855
Q3126.62178
95-th percentile126.6831
Maximum126.72685
Range0.3304967
Interquartile range (IQR)0.0672625

Descriptive statistics

Standard deviation0.055215412
Coefficient of variation (CV)0.00043617867
Kurtosis0.34719662
Mean126.58898
Median Absolute Deviation (MAD)0.0335264
Skewness-0.1822159
Sum75573.619
Variance0.0030487417
MonotonicityNot monotonic
2023-12-13T05:32:36.221379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6640205 3
 
0.5%
126.5614454 3
 
0.5%
126.6061583 2
 
0.3%
126.6831029 2
 
0.3%
126.5089733 2
 
0.3%
126.5269761 2
 
0.3%
126.6049698 2
 
0.3%
126.6145824 2
 
0.3%
126.6054877 2
 
0.3%
126.6078528 2
 
0.3%
Other values (558) 575
90.3%
(Missing) 40
 
6.3%
ValueCountFrequency (%)
126.396351 1
0.2%
126.408701 1
0.2%
126.412897 1
0.2%
126.413336 1
0.2%
126.417923 1
0.2%
126.424129 1
0.2%
126.427178 1
0.2%
126.43244 1
0.2%
126.432521 1
0.2%
126.435383 1
0.2%
ValueCountFrequency (%)
126.7268477 1
0.2%
126.7112195 2
0.3%
126.7059332 1
0.2%
126.7057418 2
0.3%
126.7035801 1
0.2%
126.7027627 1
0.2%
126.6965269 1
0.2%
126.6953531 1
0.2%
126.6950046 1
0.2%
126.6949244 1
0.2%

승강장구조
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
철골조
562 
벽돌조
75 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row철골조
2nd row철골조
3rd row철골조
4th row벽돌조
5th row벽돌조

Common Values

ValueCountFrequency (%)
철골조 562
88.2%
벽돌조 75
 
11.8%

Length

2023-12-13T05:32:36.362144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:32:36.464426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철골조 562
88.2%
벽돌조 75
 
11.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum2023-07-04 00:00:00
Maximum2023-07-04 00:00:00
2023-12-13T05:32:36.553273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:36.641586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:32:31.402597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:30.837500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:31.113090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:31.490128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:30.919698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:31.216279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:31.598892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:31.021198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:32:31.311774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:32:36.725008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호읍면동위도경도승강장구조
관리번호1.0000.9720.9240.8080.197
읍면동0.9721.0000.9090.8350.159
위도0.9240.9091.0000.6400.195
경도0.8080.8350.6401.0000.000
승강장구조0.1970.1590.1950.0001.000
2023-12-13T05:32:36.822797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동승강장구조
읍면동1.0000.124
승강장구조0.1241.000
2023-12-13T05:32:36.918835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호위도경도읍면동승강장구조
관리번호1.000-0.2910.2600.8660.150
위도-0.2911.000-0.2230.6640.148
경도0.260-0.2231.0000.5210.000
읍면동0.8660.6640.5211.0000.124
승강장구조0.1500.1480.0000.1241.000

Missing values

2023-12-13T05:32:31.732865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:32:31.927059image/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.
2023-12-13T05:32:32.066709image/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

관리번호읍면동승강장명칭승강장 위치소재지 주소위도경도승강장구조데이터기준일자
01웅천읍평2리평2리 노인회관 옆충청남도 보령시 웅천읍 평리 630-136.265949126.633688철골조2023-07-04
12웅천읍새터(수부1리)수부1 만수로 485 (김광제묘소 입구)충청남도 보령시 웅천읍 수부리 145-136.272422126.626627철골조2023-07-04
23웅천읍신기수부1 신기2길 입구충청남도 보령시 웅천읍 수부리 산 19-1036.275352126.627556철골조2023-07-04
34웅천읍수부1리수부1 만수로 420 대각 맞은편충청남도 보령시 웅천읍 수부리 331-436.267532126.623312벽돌조2023-07-04
45웅천읍수부3리수부3 만수로 345 앞충청남도 보령시 웅천읍 수부리 525<NA><NA>벽돌조2023-07-04
56웅천읍수부2리수부2 만수로 275-3 앞충청남도 보령시 웅천읍 수부리 751-136.258876126.611818벽돌조2023-07-04
67웅천읍용와두룡2 충서로 1225 옆충청남도 보령시 웅천읍 두룡리 52736.256056126.585156철골조2023-07-04
78웅천읍두룡(1리)두룡1 충서로 1273 맞은편충청남도 보령시 웅천읍 두룡리 132-136.259375126.585355벽돌조2023-07-04
89웅천읍구)웅천역대창7 장터6길 7충청남도 보령시 웅천읍 대창리 465-5436.234035126.601227철골조2023-07-04
910웅천읍사천노천2 독산로 116 대각 맞은편충청남도 보령시 웅천읍 노천리 237-136.228006126.588377철골조2023-07-04
관리번호읍면동승강장명칭승강장 위치소재지 주소위도경도승강장구조데이터기준일자
627629오천면선촌원산도3길 391충청남도 보령시 원산도리 619-2836.381551126.432521철골조2023-07-04
628630오천면구치원산도3길 283충청남도 보령시 원산도리 1047-636.371652126.417923철골조2023-07-04
629631오천면진고지원산도3길 283충청남도 보령시 원산도리 393-136.375011126.435383철골조2023-07-04
630632오천면점촌원산도3길 153충청남도 보령시 원산도리 77636.370211126.43244철골조2023-07-04
631633오천면사창원산도5길 1충청남도 보령시 원산도리 1243-436.371615126.412897철골조2023-07-04
632634오천면진말원산도5길 250충청남도 보령시 원산도리 137136.372459126.408701철골조2023-07-04
633635오천면초전원산도5길 89-3충청남도 보령시 원산도리 1866-236.379438126.396351철골조2023-07-04
634636오천면사창사거리<NA>충청남도 보령시 원산도리 1228-1336.369645126.413336철골조2023-07-04
635637오천면농협<NA>충청남도 보령시 원산도리 969-336.368436126.424129철골조2023-07-04
636638오천면원의교차로<NA>충청남도 보령시 원산도리 965-336.368955126.427178철골조2023-07-04