Overview

Dataset statistics

Number of variables19
Number of observations847
Missing cells108
Missing cells (%)0.7%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory130.8 KiB
Average record size in memory158.2 B

Variable types

Numeric4
Categorical7
Text2
Boolean5
DateTime1

Dataset

Description보령시의 횡단보도 현황 데이터 입니다. (도로명, 횡단보도종류, 자전건횡단도 겸용 여부, 고원식 적용 여부, 위경도, 차로수, 횡단보도폭, 횡단보도연장, 보행자신호등유무 등)
URLhttps://www.data.go.kr/data/15088185/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
자전거횡단도겸용여부 is highly overall correlated with 시도명 and 4 other fieldsHigh correlation
횡단보도폭 is highly overall correlated with 횡단보도연장 and 6 other fieldsHigh correlation
고원식적용여부 is highly overall correlated with 시도명 and 4 other fieldsHigh correlation
차로수 is highly overall correlated with 횡단보도연장 and 7 other fieldsHigh correlation
관리기관명 is highly overall correlated with 연번 and 14 other fieldsHigh correlation
보행자신호등유무 is highly overall correlated with 횡단보도연장 and 6 other fieldsHigh correlation
시도명 is highly overall correlated with 연번 and 14 other fieldsHigh correlation
시군구명 is highly overall correlated with 연번 and 14 other fieldsHigh correlation
보도턱낮춤여부 is highly overall correlated with 연번 and 6 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 연번 and 14 other fieldsHigh correlation
횡단보도종류 is highly overall correlated with 연번 and 14 other fieldsHigh correlation
점자블록유무 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
연번 is highly overall correlated with 위도 and 7 other fieldsHigh correlation
위도 is highly overall correlated with 연번 and 6 other fieldsHigh correlation
경도 is highly overall correlated with 시도명 and 4 other fieldsHigh correlation
횡단보도연장 is highly overall correlated with 시도명 and 7 other fieldsHigh correlation
시도명 is highly imbalanced (91.5%)Imbalance
시군구명 is highly imbalanced (91.5%)Imbalance
자전거횡단도겸용여부 is highly imbalanced (53.4%)Imbalance
고원식적용여부 is highly imbalanced (52.3%)Imbalance
관리기관명 is highly imbalanced (91.5%)Imbalance
관리기관전화번호 is highly imbalanced (91.5%)Imbalance
연번 has 9 (1.1%) missing valuesMissing
도로명 has 9 (1.1%) missing valuesMissing
소재지지번주소 has 9 (1.1%) missing valuesMissing
자전거횡단도겸용여부 has 9 (1.1%) missing valuesMissing
고원식적용여부 has 9 (1.1%) missing valuesMissing
위도 has 9 (1.1%) missing valuesMissing
경도 has 9 (1.1%) missing valuesMissing
횡단보도연장 has 9 (1.1%) missing valuesMissing
보행자신호등유무 has 9 (1.1%) missing valuesMissing
보도턱낮춤여부 has 9 (1.1%) missing valuesMissing
점자블록유무 has 9 (1.1%) missing valuesMissing
데이터기준일자 has 9 (1.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 15:27:30.660976
Analysis finished2023-12-12 15:27:35.321299
Duration4.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct838
Distinct (%)100.0%
Missing9
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean419.5
Minimum1
Maximum838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-12-13T00:27:35.767172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile42.85
Q1210.25
median419.5
Q3628.75
95-th percentile796.15
Maximum838
Range837
Interquartile range (IQR)418.5

Descriptive statistics

Standard deviation242.05406
Coefficient of variation (CV)0.5770061
Kurtosis-1.2
Mean419.5
Median Absolute Deviation (MAD)209.5
Skewness0
Sum351541
Variance58590.167
MonotonicityStrictly increasing
2023-12-13T00:27:35.930440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
526 1
 
0.1%
554 1
 
0.1%
555 1
 
0.1%
556 1
 
0.1%
557 1
 
0.1%
558 1
 
0.1%
559 1
 
0.1%
560 1
 
0.1%
561 1
 
0.1%
562 1
 
0.1%
Other values (828) 828
97.8%
(Missing) 9
 
1.1%
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 (%)
838 1
0.1%
837 1
0.1%
836 1
0.1%
835 1
0.1%
834 1
0.1%
833 1
0.1%
832 1
0.1%
831 1
0.1%
830 1
0.1%
829 1
0.1%

시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
충청남도
838 
<NA>
 
9

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 838
98.9%
<NA> 9
 
1.1%

Length

2023-12-13T00:27:36.056634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:27:36.176486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 838
98.9%
na 9
 
1.1%

시군구명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
보령시
838 
<NA>
 
9

Length

Max length4
Median length3
Mean length3.0106257
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보령시 838
98.9%
<NA> 9
 
1.1%

Length

2023-12-13T00:27:36.299180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:27:36.438850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시 838
98.9%
na 9
 
1.1%

도로명
Text

MISSING 

Distinct111
Distinct (%)13.2%
Missing9
Missing (%)1.1%
Memory size6.7 KiB
2023-12-13T00:27:36.721938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.8210024
Min length3

Characters and Unicode

Total characters3202
Distinct characters136
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

Unique29 ?
Unique (%)3.5%

Sample

1st row해안로
2nd row해안로
3rd row대해로
4th row대해로
5th row대해로
ValueCountFrequency (%)
충서로 55
 
6.6%
중앙로 29
 
3.5%
토정로 29
 
3.5%
대해로 28
 
3.3%
대청로 26
 
3.1%
대천항로 23
 
2.7%
머드로 23
 
2.7%
보령북로 22
 
2.6%
한내로타리길 21
 
2.5%
성주산로 19
 
2.3%
Other values (100) 563
67.2%
2023-12-13T00:27:37.216492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 650
 
20.3%
길 209
 
6.5%
대 162
 
5.1%
천 130
 
4.1%
중 69
 
2.2%
충 68
 
2.1%
보 67
 
2.1%
앙 66
 
2.1%
서 60
 
1.9%
청 58
 
1.8%
Other values (126) 1663
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3134
97.9%
Decimal Number 65
 
2.0%
Space Separator 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 650
20.7%
길 209
 
6.7%
대 162
 
5.2%
천 130
 
4.1%
중 69
 
2.2%
충 68
 
2.2%
보 67
 
2.1%
앙 66
 
2.1%
서 60
 
1.9%
청 58
 
1.9%
Other values (119) 1595
50.9%
Decimal Number
ValueCountFrequency (%)
1 22
33.8%
2 21
32.3%
3 12
18.5%
6 5
 
7.7%
4 3
 
4.6%
7 2
 
3.1%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3134
97.9%
Common 68
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 650
20.7%
길 209
 
6.7%
대 162
 
5.2%
천 130
 
4.1%
중 69
 
2.2%
충 68
 
2.2%
보 67
 
2.1%
앙 66
 
2.1%
서 60
 
1.9%
청 58
 
1.9%
Other values (119) 1595
50.9%
Common
ValueCountFrequency (%)
1 22
32.4%
2 21
30.9%
3 12
17.6%
6 5
 
7.4%
3
 
4.4%
4 3
 
4.4%
7 2
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3134
97.9%
ASCII 68
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 650
20.7%
길 209
 
6.7%
대 162
 
5.2%
천 130
 
4.1%
중 69
 
2.2%
충 68
 
2.2%
보 67
 
2.1%
앙 66
 
2.1%
서 60
 
1.9%
청 58
 
1.9%
Other values (119) 1595
50.9%
ASCII
ValueCountFrequency (%)
1 22
32.4%
2 21
30.9%
3 12
17.6%
6 5
 
7.4%
3
 
4.4%
4 3
 
4.4%
7 2
 
2.9%

소재지지번주소
Text

MISSING 

Distinct826
Distinct (%)98.6%
Missing9
Missing (%)1.1%
Memory size6.7 KiB
2023-12-13T00:27:37.533481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.708831
Min length14

Characters and Unicode

Total characters15678
Distinct characters105
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

Unique814 ?
Unique (%)97.1%

Sample

1st row충남 보령시 궁촌동 167-10
2nd row충남 보령시 궁촌동 149-2
3rd row충남 보령시 내항동 330-1
4th row충남 보령시 내항동 297-38
5th row충남 보령시 궁촌동 119-3
ValueCountFrequency (%)
보령시 838
22.4%
충남 491
 
13.1%
충청남도 347
 
9.3%
대천동 129
 
3.4%
동대동 97
 
2.6%
신흑동 96
 
2.6%
웅천읍 78
 
2.1%
명천동 65
 
1.7%
주교면 56
 
1.5%
오천면 36
 
1.0%
Other values (890) 1509
40.3%
2023-12-13T00:27:38.052919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2904
18.5%
남 873
 
5.6%
보 853
 
5.4%
령 844
 
5.4%
충 838
 
5.3%
시 838
 
5.3%
- 694
 
4.4%
1 653
 
4.2%
동 570
 
3.6%
2 478
 
3.0%
Other values (95) 6133
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8557
54.6%
Decimal Number 3523
22.5%
Space Separator 2904
 
18.5%
Dash Punctuation 694
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 873
 
10.2%
보 853
 
10.0%
령 844
 
9.9%
충 838
 
9.8%
시 838
 
9.8%
동 570
 
6.7%
청 408
 
4.8%
리 374
 
4.4%
도 357
 
4.2%
천 340
 
4.0%
Other values (83) 2262
26.4%
Decimal Number
ValueCountFrequency (%)
1 653
18.5%
2 478
13.6%
3 442
12.5%
4 348
9.9%
9 297
8.4%
6 296
8.4%
7 278
7.9%
5 270
7.7%
8 239
 
6.8%
0 222
 
6.3%
Space Separator
ValueCountFrequency (%)
2904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 694
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8557
54.6%
Common 7121
45.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 873
 
10.2%
보 853
 
10.0%
령 844
 
9.9%
충 838
 
9.8%
시 838
 
9.8%
동 570
 
6.7%
청 408
 
4.8%
리 374
 
4.4%
도 357
 
4.2%
천 340
 
4.0%
Other values (83) 2262
26.4%
Common
ValueCountFrequency (%)
2904
40.8%
- 694
 
9.7%
1 653
 
9.2%
2 478
 
6.7%
3 442
 
6.2%
4 348
 
4.9%
9 297
 
4.2%
6 296
 
4.2%
7 278
 
3.9%
5 270
 
3.8%
Other values (2) 461
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8557
54.6%
ASCII 7121
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2904
40.8%
- 694
 
9.7%
1 653
 
9.2%
2 478
 
6.7%
3 442
 
6.2%
4 348
 
4.9%
9 297
 
4.2%
6 296
 
4.2%
7 278
 
3.9%
5 270
 
3.8%
Other values (2) 461
 
6.5%
Hangul
ValueCountFrequency (%)
남 873
 
10.2%
보 853
 
10.0%
령 844
 
9.9%
충 838
 
9.8%
시 838
 
9.8%
동 570
 
6.7%
청 408
 
4.8%
리 374
 
4.4%
도 357
 
4.2%
천 340
 
4.0%
Other values (83) 2262
26.4%

횡단보도종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
<NA>
491 
일반형
356 

Length

Max length4
Median length4
Mean length3.579693
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 491
58.0%
일반형 356
42.0%

Length

2023-12-13T00:27:38.217240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:27:38.349729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 491
58.0%
일반형 356
42.0%

자전거횡단도겸용여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)0.2%
Missing9
Missing (%)1.1%
Memory size1.8 KiB
False
755 
True
83 
(Missing)
 
9
ValueCountFrequency (%)
False 755
89.1%
True 83
 
9.8%
(Missing) 9
 
1.1%
2023-12-13T00:27:38.464249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

고원식적용여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)0.2%
Missing9
Missing (%)1.1%
Memory size1.8 KiB
False
752 
True
86 
(Missing)
 
9
ValueCountFrequency (%)
False 752
88.8%
True 86
 
10.2%
(Missing) 9
 
1.1%
2023-12-13T00:27:38.592949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct838
Distinct (%)100.0%
Missing9
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean36.340998
Minimum36.172608
Maximum36.508332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-12-13T00:27:38.735906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.172608
5-th percentile36.230805
Q136.316054
median36.346333
Q336.359851
95-th percentile36.44543
Maximum36.508332
Range0.33572471
Interquartile range (IQR)0.043797555

Descriptive statistics

Standard deviation0.060551467
Coefficient of variation (CV)0.0016662026
Kurtosis0.61128914
Mean36.340998
Median Absolute Deviation (MAD)0.02434949
Skewness-0.13424714
Sum30453.757
Variance0.0036664801
MonotonicityNot monotonic
2023-12-13T00:27:38.917145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.34760939 1
 
0.1%
36.35224206 1
 
0.1%
36.35242231 1
 
0.1%
36.3530287 1
 
0.1%
36.35306535 1
 
0.1%
36.35314697 1
 
0.1%
36.35310866 1
 
0.1%
36.35365963 1
 
0.1%
36.35357214 1
 
0.1%
36.35360995 1
 
0.1%
Other values (828) 828
97.8%
(Missing) 9
 
1.1%
ValueCountFrequency (%)
36.17260752 1
0.1%
36.17340316 1
0.1%
36.17799508 1
0.1%
36.17984667 1
0.1%
36.1801358 1
0.1%
36.18018951 1
0.1%
36.18803182 1
0.1%
36.19045449 1
0.1%
36.19525799 1
0.1%
36.19772978 1
0.1%
ValueCountFrequency (%)
36.50833223 1
0.1%
36.50825151 1
0.1%
36.50813749 1
0.1%
36.50758102 1
0.1%
36.50533198 1
0.1%
36.50255384 1
0.1%
36.49607839 1
0.1%
36.49243642 1
0.1%
36.48706883 1
0.1%
36.48235987 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct837
Distinct (%)99.9%
Missing9
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean126.58476
Minimum126.48953
Maximum126.68328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-12-13T00:27:39.086174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.48953
5-th percentile126.51019
Q1126.55309
median126.59433
Q3126.60807
95-th percentile126.65802
Maximum126.68328
Range0.1937523
Interquartile range (IQR)0.054982875

Descriptive statistics

Standard deviation0.043192022
Coefficient of variation (CV)0.00034121029
Kurtosis-0.43195337
Mean126.58476
Median Absolute Deviation (MAD)0.01773895
Skewness-0.2399136
Sum106078.03
Variance0.0018655507
MonotonicityNot monotonic
2023-12-13T00:27:39.305231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5981158 2
 
0.2%
126.5986181 1
 
0.1%
126.5977704 1
 
0.1%
126.5959751 1
 
0.1%
126.5960909 1
 
0.1%
126.5960185 1
 
0.1%
126.5959378 1
 
0.1%
126.5940213 1
 
0.1%
126.594095 1
 
0.1%
126.5942077 1
 
0.1%
Other values (827) 827
97.6%
(Missing) 9
 
1.1%
ValueCountFrequency (%)
126.4895251 1
0.1%
126.4913145 1
0.1%
126.4939372 1
0.1%
126.4989447 1
0.1%
126.5006945 1
0.1%
126.5008071 1
0.1%
126.5009245 1
0.1%
126.5017004 1
0.1%
126.5017861 1
0.1%
126.5024202 1
0.1%
ValueCountFrequency (%)
126.6832774 1
0.1%
126.6804568 1
0.1%
126.6803578 1
0.1%
126.6770977 1
0.1%
126.6768411 1
0.1%
126.676493 1
0.1%
126.6760828 1
0.1%
126.6760742 1
0.1%
126.6759492 1
0.1%
126.675784 1
0.1%

차로수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
1
461 
2
323 
3
53 
<NA>
 
9
4
 
1

Length

Max length4
Median length1
Mean length1.0318772
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1
2nd row2
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 461
54.4%
2 323
38.1%
3 53
 
6.3%
<NA> 9
 
1.1%
4 1
 
0.1%

Length

2023-12-13T00:27:39.524441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:27:39.670802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 461
54.4%
2 323
38.1%
3 53
 
6.3%
na 9
 
1.1%
4 1
 
0.1%

횡단보도폭
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
4
469 
6
369 
<NA>
 
9

Length

Max length4
Median length1
Mean length1.0318772
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row6
4th row4
5th row6

Common Values

ValueCountFrequency (%)
4 469
55.4%
6 369
43.6%
<NA> 9
 
1.1%

Length

2023-12-13T00:27:39.853805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:27:39.994038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 469
55.4%
6 369
43.6%
na 9
 
1.1%

횡단보도연장
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct32
Distinct (%)3.8%
Missing9
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean11.977327
Minimum3
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-12-13T00:27:40.132587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6
Q17
median11
Q315
95-th percentile24
Maximum50
Range47
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.7801797
Coefficient of variation (CV)0.48259346
Kurtosis3.3395833
Mean11.977327
Median Absolute Deviation (MAD)4
Skewness1.3802355
Sum10037
Variance33.410477
MonotonicityNot monotonic
2023-12-13T00:27:40.274627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
6 133
15.7%
8 83
9.8%
7 77
9.1%
12 73
 
8.6%
9 64
 
7.6%
15 56
 
6.6%
14 47
 
5.5%
10 40
 
4.7%
13 39
 
4.6%
11 35
 
4.1%
Other values (22) 191
22.6%
ValueCountFrequency (%)
3 6
 
0.7%
4 1
 
0.1%
5 2
 
0.2%
6 133
15.7%
7 77
9.1%
8 83
9.8%
9 64
7.6%
10 40
 
4.7%
11 35
 
4.1%
12 73
8.6%
ValueCountFrequency (%)
50 1
 
0.1%
41 1
 
0.1%
40 1
 
0.1%
31 1
 
0.1%
30 4
0.5%
29 1
 
0.1%
28 1
 
0.1%
27 4
0.5%
26 6
0.7%
25 8
0.9%

보행자신호등유무
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.2%
Missing9
Missing (%)1.1%
Memory size1.8 KiB
False
598 
True
240 
(Missing)
 
9
ValueCountFrequency (%)
False 598
70.6%
True 240
28.3%
(Missing) 9
 
1.1%
2023-12-13T00:27:40.401816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

보도턱낮춤여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.2%
Missing9
Missing (%)1.1%
Memory size1.8 KiB
True
700 
False
138 
(Missing)
 
9
ValueCountFrequency (%)
True 700
82.6%
False 138
 
16.3%
(Missing) 9
 
1.1%
2023-12-13T00:27:40.515186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점자블록유무
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.2%
Missing9
Missing (%)1.1%
Memory size1.8 KiB
False
579 
True
259 
(Missing)
 
9
ValueCountFrequency (%)
False 579
68.4%
True 259
30.6%
(Missing) 9
 
1.1%
2023-12-13T00:27:40.633857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
보령시청
838 
<NA>
 
9

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보령시청 838
98.9%
<NA> 9
 
1.1%

Length

2023-12-13T00:27:40.744658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:27:40.858447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시청 838
98.9%
na 9
 
1.1%

관리기관전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
041-930-3982
838 
<NA>
 
9

Length

Max length12
Median length12
Mean length11.914994
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row041-930-3982
2nd row041-930-3982
3rd row041-930-3982
4th row041-930-3982
5th row041-930-3982

Common Values

ValueCountFrequency (%)
041-930-3982 838
98.9%
<NA> 9
 
1.1%

Length

2023-12-13T00:27:40.982621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:27:41.126271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
041-930-3982 838
98.9%
na 9
 
1.1%

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing9
Missing (%)1.1%
Memory size6.7 KiB
Minimum2023-08-28 00:00:00
Maximum2023-08-28 00:00:00
2023-12-13T00:27:41.252844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:41.377399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T00:27:33.885429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:32.317258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:32.829448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:33.389539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:33.993017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:32.430524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:32.961155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:33.523530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:34.172409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:32.568573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:33.110504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:33.654103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:34.295652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:32.713674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:33.266883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:27:33.772734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:27:41.470575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번자전거횡단도겸용여부고원식적용여부위도경도차로수횡단보도폭횡단보도연장보행자신호등유무보도턱낮춤여부점자블록유무
연번1.0000.4540.3660.8800.8050.5540.5900.4170.4790.7580.740
자전거횡단도겸용여부0.4541.0000.1330.3220.1660.5610.2810.3900.5100.1970.559
고원식적용여부0.3660.1331.0000.1370.2620.1320.0000.1320.0000.1150.245
위도0.8800.3220.1371.0000.7560.5010.5480.3680.3080.7870.575
경도0.8050.1660.2620.7561.0000.3940.4070.2970.2400.4550.415
차로수0.5540.5610.1320.5010.3941.0000.8990.7230.7150.4550.630
횡단보도폭0.5900.2810.0000.5480.4070.8991.0000.5990.6370.3280.529
횡단보도연장0.4170.3900.1320.3680.2970.7230.5991.0000.5100.3580.310
보행자신호등유무0.4790.5100.0000.3080.2400.7150.6370.5101.0000.3150.466
보도턱낮춤여부0.7580.1970.1150.7870.4550.4550.3280.3580.3151.0000.442
점자블록유무0.7400.5590.2450.5750.4150.6300.5290.3100.4660.4421.000
2023-12-13T00:27:41.660040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자전거횡단도겸용여부횡단보도폭고원식적용여부차로수관리기관명보행자신호등유무시도명시군구명보도턱낮춤여부관리기관전화번호횡단보도종류점자블록유무
자전거횡단도겸용여부1.0000.1820.0850.3841.0000.3411.0001.0000.1261.0001.0000.378
횡단보도폭0.1821.0000.0000.7121.0000.4391.0001.0000.2131.0001.0000.355
고원식적용여부0.0850.0001.0000.0871.0000.0001.0001.0000.0741.0001.0000.157
차로수0.3840.7120.0871.0001.0000.5101.0001.0000.3071.0001.0000.438
관리기관명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
보행자신호등유무0.3410.4390.0000.5101.0001.0001.0001.0000.2041.0001.0000.309
시도명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시군구명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
보도턱낮춤여부0.1260.2130.0740.3071.0000.2041.0001.0001.0001.0001.0000.292
관리기관전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
횡단보도종류1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
점자블록유무0.3780.3550.1570.4381.0000.3091.0001.0000.2921.0001.0001.000
2023-12-13T00:27:41.851780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도횡단보도연장시도명시군구명횡단보도종류자전거횡단도겸용여부고원식적용여부차로수횡단보도폭보행자신호등유무보도턱낮춤여부점자블록유무관리기관명관리기관전화번호
연번1.0000.553-0.182-0.1801.0001.0001.0000.3470.2800.3640.4540.3670.5940.5771.0001.000
위도0.5531.000-0.0690.1731.0001.0001.0000.2460.1040.3220.4210.2350.6200.4421.0001.000
경도-0.182-0.0691.000-0.1401.0001.0001.0000.1260.2000.2450.3110.1830.3480.3171.0001.000
횡단보도연장-0.1800.173-0.1401.0001.0001.0001.0000.3890.1310.5590.6010.5100.3570.3091.0001.000
시도명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시군구명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
횡단보도종류1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
자전거횡단도겸용여부0.3470.2460.1260.3891.0001.0001.0001.0000.0850.3840.1820.3410.1260.3781.0001.000
고원식적용여부0.2800.1040.2000.1311.0001.0001.0000.0851.0000.0870.0000.0000.0740.1571.0001.000
차로수0.3640.3220.2450.5591.0001.0001.0000.3840.0871.0000.7120.5100.3070.4381.0001.000
횡단보도폭0.4540.4210.3110.6011.0001.0001.0000.1820.0000.7121.0000.4390.2130.3551.0001.000
보행자신호등유무0.3670.2350.1830.5101.0001.0001.0000.3410.0000.5100.4391.0000.2040.3091.0001.000
보도턱낮춤여부0.5940.6200.3480.3571.0001.0001.0000.1260.0740.3070.2130.2041.0000.2921.0001.000
점자블록유무0.5770.4420.3170.3091.0001.0001.0000.3780.1570.4380.3550.3090.2921.0001.0001.000
관리기관명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
관리기관전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T00:27:34.486423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:27:34.806845image/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.
2023-12-13T00:27:35.039684image/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

연번시도명시군구명도로명소재지지번주소횡단보도종류자전거횡단도겸용여부고원식적용여부위도경도차로수횡단보도폭횡단보도연장보행자신호등유무보도턱낮춤여부점자블록유무관리기관명관리기관전화번호데이터기준일자
01충청남도보령시해안로충남 보령시 궁촌동 167-10일반형YN36.34466126.5879921415NYY보령시청041-930-39822023-08-28
12충청남도보령시해안로충남 보령시 궁촌동 149-2일반형YN36.344001126.590572417YYY보령시청041-930-39822023-08-28
23충청남도보령시대해로충남 보령시 내항동 330-1일반형YN36.340206126.5868153624YYY보령시청041-930-39822023-08-28
34충청남도보령시대해로충남 보령시 내항동 297-38일반형NN36.340273126.5869883430YYY보령시청041-930-39822023-08-28
45충청남도보령시대해로충남 보령시 궁촌동 119-3일반형YN36.342074126.5908123626YYY보령시청041-930-39822023-08-28
56충청남도보령시대해로충남 보령시 궁촌동 349-1일반형YN36.342188126.5910183626YYY보령시청041-930-39822023-08-28
67충청남도보령시대해로충남 보령시 궁촌동 27-4일반형YN36.343935126.5958713626YYY보령시청041-930-39822023-08-28
78충청남도보령시대해로충남 보령시 궁촌동 45-6일반형YN36.343972126.5960923626YYY보령시청041-930-39822023-08-28
89충청남도보령시대해로충남 보령시 명천동 479-3일반형YN36.344893126.5992373630YYY보령시청041-930-39822023-08-28
910충청남도보령시터미널길충남 보령시 내항동 330-7일반형YN36.34032126.5868942420NYY보령시청041-930-39822023-08-28
연번시도명시군구명도로명소재지지번주소횡단보도종류자전거횡단도겸용여부고원식적용여부위도경도차로수횡단보도폭횡단보도연장보행자신호등유무보도턱낮춤여부점자블록유무관리기관명관리기관전화번호데이터기준일자
837838충청남도보령시대관초등길충청남도 보령시 대천동 503-16<NA>NN36.357835126.585506148NYN보령시청041-930-39822023-08-28
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Duplicate rows

Most frequently occurring

연번시도명시군구명도로명소재지지번주소횡단보도종류자전거횡단도겸용여부고원식적용여부위도경도차로수횡단보도폭횡단보도연장보행자신호등유무보도턱낮춤여부점자블록유무관리기관명관리기관전화번호데이터기준일자# duplicates
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