Overview

Dataset statistics

Number of variables11
Number of observations93
Missing cells50
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.5 KiB
Average record size in memory93.4 B

Variable types

Numeric4
Categorical2
Text3
Boolean2

Dataset

Description세종특별자치시 횡단보도 정보를 제공합니다. 데이터는 횡단보도 종류, 위치, 교통섬 유무, 도로차로 수, 도로명칭, 도로명 주소, 지번주소, 보행자 신호등 유무, 위도, 경도로 구성되어 있습니다. 횡단보도는 표준데이터셋으로 제공되는 데이터입니다. 횡단보도 정보 기타는 데이터 제공 신청에 맞춘 항목으로 구성하였습니다.
URLhttps://www.data.go.kr/data/15117334/fileData.do

Alerts

연번 is highly overall correlated with 도로차로 수 and 3 other fieldsHigh correlation
도로차로 수 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 도로명칭 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 도로명칭 and 1 other fieldsHigh correlation
횡단보도 종류 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
교통섬 유무 is highly overall correlated with 도로명칭High correlation
도로명칭 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
보행자 신호등 유무 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
교통섬 유무 is highly imbalanced (79.4%)Imbalance
도로명 주소 has 50 (53.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:22:47.615129
Analysis finished2023-12-12 09:22:50.453284
Duration2.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T18:22:50.553555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.6
Q124
median47
Q370
95-th percentile88.4
Maximum93
Range92
Interquartile range (IQR)46

Descriptive statistics

Standard deviation26.990739
Coefficient of variation (CV)0.57427105
Kurtosis-1.2
Mean47
Median Absolute Deviation (MAD)23
Skewness0
Sum4371
Variance728.5
MonotonicityStrictly increasing
2023-12-12T18:22:50.731704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
60 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%

횡단보도 종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
일반식
37 
일반
32 
고원식
24 

Length

Max length3
Median length3
Mean length2.655914
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row일반
3rd row고원식
4th row고원식
5th row일반

Common Values

ValueCountFrequency (%)
일반식 37
39.8%
일반 32
34.4%
고원식 24
25.8%

Length

2023-12-12T18:22:50.887057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:51.012090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반식 37
39.8%
일반 32
34.4%
고원식 24
25.8%

위치
Text

Distinct55
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-12T18:22:51.298062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length6.4731183
Min length3

Characters and Unicode

Total characters602
Distinct characters152
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)44.1%

Sample

1st row봉산1리 마을회관
2nd row세종장례식장입구 버스정류장
3rd row새롬초등학교 후문 앞
4th row호려울마을5단지 뒷편
5th row세종중앙농협 한솔지점
ValueCountFrequency (%)
앞 18
 
12.0%
마음로 9
 
6.0%
세종로 7
 
4.7%
갈매로 4
 
2.7%
가름로 4
 
2.7%
어울로 4
 
2.7%
보듬8로 4
 
2.7%
보듬6로 4
 
2.7%
버스정류장 4
 
2.7%
누리로 3
 
2.0%
Other values (74) 89
59.3%
2023-12-12T18:22:51.799549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58
 
9.6%
로 48
 
8.0%
앞 18
 
3.0%
마 17
 
2.8%
종 15
 
2.5%
세 15
 
2.5%
원 11
 
1.8%
리 11
 
1.8%
장 10
 
1.7%
지 10
 
1.7%
Other values (142) 389
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 501
83.2%
Space Separator 58
 
9.6%
Decimal Number 33
 
5.5%
Dash Punctuation 4
 
0.7%
Uppercase Letter 4
 
0.7%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 48
 
9.6%
앞 18
 
3.6%
마 17
 
3.4%
종 15
 
3.0%
세 15
 
3.0%
원 11
 
2.2%
리 11
 
2.2%
장 10
 
2.0%
지 10
 
2.0%
보 10
 
2.0%
Other values (128) 336
67.1%
Decimal Number
ValueCountFrequency (%)
1 8
24.2%
3 5
15.2%
6 5
15.2%
8 5
15.2%
5 4
12.1%
2 3
 
9.1%
0 2
 
6.1%
4 1
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
G 2
50.0%
Space Separator
ValueCountFrequency (%)
58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 501
83.2%
Common 97
 
16.1%
Latin 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 48
 
9.6%
앞 18
 
3.6%
마 17
 
3.4%
종 15
 
3.0%
세 15
 
3.0%
원 11
 
2.2%
리 11
 
2.2%
장 10
 
2.0%
지 10
 
2.0%
보 10
 
2.0%
Other values (128) 336
67.1%
Common
ValueCountFrequency (%)
58
59.8%
1 8
 
8.2%
3 5
 
5.2%
6 5
 
5.2%
8 5
 
5.2%
5 4
 
4.1%
- 4
 
4.1%
2 3
 
3.1%
0 2
 
2.1%
4 1
 
1.0%
Other values (2) 2
 
2.1%
Latin
ValueCountFrequency (%)
S 2
50.0%
G 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 501
83.2%
ASCII 101
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58
57.4%
1 8
 
7.9%
3 5
 
5.0%
6 5
 
5.0%
8 5
 
5.0%
5 4
 
4.0%
- 4
 
4.0%
2 3
 
3.0%
0 2
 
2.0%
S 2
 
2.0%
Other values (4) 5
 
5.0%
Hangul
ValueCountFrequency (%)
로 48
 
9.6%
앞 18
 
3.6%
마 17
 
3.4%
종 15
 
3.0%
세 15
 
3.0%
원 11
 
2.2%
리 11
 
2.2%
장 10
 
2.0%
지 10
 
2.0%
보 10
 
2.0%
Other values (128) 336
67.1%

교통섬 유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size225.0 B
False
90 
True
 
3
ValueCountFrequency (%)
False 90
96.8%
True 3
 
3.2%
2023-12-12T18:22:51.959497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

도로차로 수
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5806452
Minimum2
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T18:22:52.052615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median3
Q35
95-th percentile7
Maximum9
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8017056
Coefficient of variation (CV)0.50317904
Kurtosis0.051492244
Mean3.5806452
Median Absolute Deviation (MAD)1
Skewness0.88048248
Sum333
Variance3.2461431
MonotonicityNot monotonic
2023-12-12T18:22:52.180996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 43
46.2%
5 20
21.5%
3 9
 
9.7%
4 8
 
8.6%
6 7
 
7.5%
7 4
 
4.3%
9 2
 
2.2%
ValueCountFrequency (%)
2 43
46.2%
3 9
 
9.7%
4 8
 
8.6%
5 20
21.5%
6 7
 
7.5%
7 4
 
4.3%
9 2
 
2.2%
ValueCountFrequency (%)
9 2
 
2.2%
7 4
 
4.3%
6 7
 
7.5%
5 20
21.5%
4 8
 
8.6%
3 9
 
9.7%
2 43
46.2%

도로명칭
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Memory size876.0 B
마음로
9 
세종로
9 
도신고복로
 
5
보듬8로
 
4
보듬6로
 
4
Other values (39)
62 

Length

Max length6
Median length3
Mean length3.4946237
Min length3

Unique

Unique26 ?
Unique (%)28.0%

Sample

1st row건너말고샅길
2nd row당산로
3rd row새롬서로
4th row남세종로
5th row누리로

Common Values

ValueCountFrequency (%)
마음로 9
 
9.7%
세종로 9
 
9.7%
도신고복로 5
 
5.4%
보듬8로 4
 
4.3%
보듬6로 4
 
4.3%
가름로 4
 
4.3%
갈매로 4
 
4.3%
누리로 4
 
4.3%
어울로 4
 
4.3%
달빛1로 3
 
3.2%
Other values (34) 43
46.2%

Length

2023-12-12T18:22:52.373870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
마음로 9
 
9.7%
세종로 9
 
9.7%
도신고복로 5
 
5.4%
보듬8로 4
 
4.3%
보듬6로 4
 
4.3%
가름로 4
 
4.3%
갈매로 4
 
4.3%
누리로 4
 
4.3%
어울로 4
 
4.3%
달빛1로 3
 
3.2%
Other values (34) 43
46.2%

도로명 주소
Text

MISSING 

Distinct41
Distinct (%)95.3%
Missing50
Missing (%)53.8%
Memory size876.0 B
2023-12-12T18:22:52.707075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length15.72093
Min length13

Characters and Unicode

Total characters676
Distinct characters92
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

Unique39 ?
Unique (%)90.7%

Sample

1st row세종특별자치시 건너말고샅길 35
2nd row세종특별자치시 새롬중앙1로 27
3rd row세종특별자치시 남세종로 441
4th row세종특별자치시 누리로 54
5th row세종특별자치시 용포로 88
ValueCountFrequency (%)
세종특별자치시 43
32.1%
도신고복로 3
 
2.2%
9 3
 
2.2%
문화로 3
 
2.2%
2 2
 
1.5%
35 2
 
1.5%
반곡2길 2
 
1.5%
54 2
 
1.5%
세종로 2
 
1.5%
수원지길 2
 
1.5%
Other values (66) 70
52.2%
2023-12-12T18:22:53.198720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
13.5%
세 46
 
6.8%
종 46
 
6.8%
치 46
 
6.8%
시 44
 
6.5%
특 43
 
6.4%
별 43
 
6.4%
자 43
 
6.4%
로 27
 
4.0%
1 23
 
3.4%
Other values (82) 224
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 476
70.4%
Decimal Number 107
 
15.8%
Space Separator 91
 
13.5%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 46
 
9.7%
종 46
 
9.7%
치 46
 
9.7%
시 44
 
9.2%
특 43
 
9.0%
별 43
 
9.0%
자 43
 
9.0%
로 27
 
5.7%
길 16
 
3.4%
원 6
 
1.3%
Other values (70) 116
24.4%
Decimal Number
ValueCountFrequency (%)
1 23
21.5%
2 18
16.8%
3 15
14.0%
5 11
10.3%
7 10
9.3%
9 9
 
8.4%
4 7
 
6.5%
6 6
 
5.6%
8 5
 
4.7%
0 3
 
2.8%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 476
70.4%
Common 200
29.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 46
 
9.7%
종 46
 
9.7%
치 46
 
9.7%
시 44
 
9.2%
특 43
 
9.0%
별 43
 
9.0%
자 43
 
9.0%
로 27
 
5.7%
길 16
 
3.4%
원 6
 
1.3%
Other values (70) 116
24.4%
Common
ValueCountFrequency (%)
91
45.5%
1 23
 
11.5%
2 18
 
9.0%
3 15
 
7.5%
5 11
 
5.5%
7 10
 
5.0%
9 9
 
4.5%
4 7
 
3.5%
6 6
 
3.0%
8 5
 
2.5%
Other values (2) 5
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 476
70.4%
ASCII 200
29.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
45.5%
1 23
 
11.5%
2 18
 
9.0%
3 15
 
7.5%
5 11
 
5.5%
7 10
 
5.0%
9 9
 
4.5%
4 7
 
3.5%
6 6
 
3.0%
8 5
 
2.5%
Other values (2) 5
 
2.5%
Hangul
ValueCountFrequency (%)
세 46
 
9.7%
종 46
 
9.7%
치 46
 
9.7%
시 44
 
9.2%
특 43
 
9.0%
별 43
 
9.0%
자 43
 
9.0%
로 27
 
5.7%
길 16
 
3.4%
원 6
 
1.3%
Other values (70) 116
24.4%

지번주소
Text

Distinct58
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-12T18:22:53.514751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length16.204301
Min length14

Characters and Unicode

Total characters1507
Distinct characters74
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

Unique42 ?
Unique (%)45.2%

Sample

1st row세종특별자치시 조치원읍 봉산리 332-2
2nd row세종특별자치시 조치원읍 봉암리 84-1
3rd row세종특별자치시 새롬동 313
4th row세종특별자치시 보람동 783
5th row세종특별자치시 한솔동 971
ValueCountFrequency (%)
세종특별자치시 93
32.0%
고운동 13
 
4.5%
한솔동 11
 
3.8%
종촌동 8
 
2.7%
도담동 8
 
2.7%
아름동 7
 
2.4%
어진동 5
 
1.7%
95 4
 
1.4%
908 4
 
1.4%
710 4
 
1.4%
Other values (92) 134
46.0%
2023-12-12T18:22:54.038510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
198
 
13.1%
종 101
 
6.7%
치 96
 
6.4%
세 93
 
6.2%
특 93
 
6.2%
별 93
 
6.2%
자 93
 
6.2%
시 93
 
6.2%
1 63
 
4.2%
동 60
 
4.0%
Other values (64) 524
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 957
63.5%
Decimal Number 322
 
21.4%
Space Separator 198
 
13.1%
Dash Punctuation 30
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
종 101
10.6%
치 96
10.0%
세 93
9.7%
특 93
9.7%
별 93
9.7%
자 93
9.7%
시 93
9.7%
동 60
 
6.3%
리 35
 
3.7%
고 14
 
1.5%
Other values (52) 186
19.4%
Decimal Number
ValueCountFrequency (%)
1 63
19.6%
2 55
17.1%
6 33
10.2%
7 31
9.6%
9 28
8.7%
4 26
8.1%
3 24
 
7.5%
0 22
 
6.8%
5 20
 
6.2%
8 20
 
6.2%
Space Separator
ValueCountFrequency (%)
198
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 957
63.5%
Common 550
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
종 101
10.6%
치 96
10.0%
세 93
9.7%
특 93
9.7%
별 93
9.7%
자 93
9.7%
시 93
9.7%
동 60
 
6.3%
리 35
 
3.7%
고 14
 
1.5%
Other values (52) 186
19.4%
Common
ValueCountFrequency (%)
198
36.0%
1 63
 
11.5%
2 55
 
10.0%
6 33
 
6.0%
7 31
 
5.6%
- 30
 
5.5%
9 28
 
5.1%
4 26
 
4.7%
3 24
 
4.4%
0 22
 
4.0%
Other values (2) 40
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 957
63.5%
ASCII 550
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
198
36.0%
1 63
 
11.5%
2 55
 
10.0%
6 33
 
6.0%
7 31
 
5.6%
- 30
 
5.5%
9 28
 
5.1%
4 26
 
4.7%
3 24
 
4.4%
0 22
 
4.0%
Other values (2) 40
 
7.3%
Hangul
ValueCountFrequency (%)
종 101
10.6%
치 96
10.0%
세 93
9.7%
특 93
9.7%
별 93
9.7%
자 93
9.7%
시 93
9.7%
동 60
 
6.3%
리 35
 
3.7%
고 14
 
1.5%
Other values (52) 186
19.4%

보행자 신호등 유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size225.0 B
True
57 
False
36 
ValueCountFrequency (%)
True 57
61.3%
False 36
38.7%
2023-12-12T18:22:54.526834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.529031
Minimum36.422552
Maximum36.683447
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T18:22:54.683810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.422552
5-th percentile36.476475
Q136.496814
median36.515192
Q336.567991
95-th percentile36.608453
Maximum36.683447
Range0.260895
Interquartile range (IQR)0.071177

Descriptive statistics

Standard deviation0.050304537
Coefficient of variation (CV)0.0013771112
Kurtosis0.45245059
Mean36.529031
Median Absolute Deviation (MAD)0.01838454
Skewness0.99342407
Sum3397.1999
Variance0.0025305465
MonotonicityNot monotonic
2023-12-12T18:22:54.903609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.52155423 4
 
4.3%
36.50817453 4
 
4.3%
36.51568465 4
 
4.3%
36.4968074 3
 
3.2%
36.51519194 3
 
3.2%
36.50677504 3
 
3.2%
36.51366991 2
 
2.2%
36.475454 2
 
2.2%
36.51819862 2
 
2.2%
36.499139 2
 
2.2%
Other values (61) 64
68.8%
ValueCountFrequency (%)
36.422552 1
1.1%
36.466383 1
1.1%
36.475454 2
2.2%
36.475835 1
1.1%
36.476902 1
1.1%
36.478439 1
1.1%
36.478617 1
1.1%
36.479003 1
1.1%
36.480001 1
1.1%
36.480068 1
1.1%
ValueCountFrequency (%)
36.683447 1
1.1%
36.680813 1
1.1%
36.623886 1
1.1%
36.611654 1
1.1%
36.610742 1
1.1%
36.606927 1
1.1%
36.605927 1
1.1%
36.605864 1
1.1%
36.605142 1
1.1%
36.604534 1
1.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.26391
Minimum127.19905
Maximum127.38348
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T18:22:55.135157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.19905
5-th percentile127.22687
Q1127.24295
median127.26149
Q3127.28625
95-th percentile127.31178
Maximum127.38348
Range0.184426
Interquartile range (IQR)0.0432997

Descriptive statistics

Standard deviation0.033512291
Coefficient of variation (CV)0.0002633291
Kurtosis2.1647973
Mean127.26391
Median Absolute Deviation (MAD)0.022847
Skewness1.1325213
Sum11835.543
Variance0.0011230736
MonotonicityNot monotonic
2023-12-12T18:22:55.364726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.2627741 4
 
4.3%
127.2643386 4
 
4.3%
127.2429503 4
 
4.3%
127.2308396 4
 
4.3%
127.2622416 4
 
4.3%
127.2456091 3
 
3.2%
127.2311792 3
 
3.2%
127.2504673 2
 
2.2%
127.224557 2
 
2.2%
127.261494 2
 
2.2%
Other values (60) 61
65.6%
ValueCountFrequency (%)
127.199053 1
 
1.1%
127.203301 1
 
1.1%
127.205274 1
 
1.1%
127.224557 2
2.2%
127.228404 1
 
1.1%
127.2296487 1
 
1.1%
127.230404 1
 
1.1%
127.2308396 4
4.3%
127.2311792 3
3.2%
127.23366 1
 
1.1%
ValueCountFrequency (%)
127.383479 1
1.1%
127.370868 1
1.1%
127.364418 1
1.1%
127.341663 1
1.1%
127.311924 1
1.1%
127.311678 1
1.1%
127.301028 1
1.1%
127.300953 1
1.1%
127.300922 1
1.1%
127.300901 1
1.1%

Interactions

2023-12-12T18:22:49.644634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:48.342780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:48.759061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:49.183851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:49.746879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:48.417896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:48.851352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:49.274983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:49.862183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:48.523777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:48.948750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:49.373677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:49.971297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:48.626986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:49.048780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:49.515872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:22:55.524968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번횡단보도 종류위치교통섬 유무도로차로 수도로명칭도로명 주소지번주소보행자 신호등 유무위도경도
연번1.0000.7350.9640.3290.5680.9341.0000.9880.9270.5560.705
횡단보도 종류0.7351.0000.9630.0700.5080.9220.0000.9750.4590.7660.629
위치0.9640.9631.0001.0000.0001.0001.0001.0001.0001.0000.999
교통섬 유무0.3290.0701.0001.0000.0481.0001.0001.0000.0000.0000.000
도로차로 수0.5680.5080.0000.0481.0000.0001.0000.0000.6960.1150.000
도로명칭0.9340.9221.0001.0000.0001.0001.0001.0001.0000.9890.995
도로명 주소1.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소0.9880.9751.0001.0000.0001.0001.0001.0001.0001.0001.000
보행자 신호등 유무0.9270.4591.0000.0000.6961.0001.0001.0001.0000.6920.780
위도0.5560.7661.0000.0000.1150.9891.0001.0000.6921.0000.720
경도0.7050.6290.9990.0000.0000.9951.0001.0000.7800.7201.000
2023-12-12T18:22:55.718678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보행자 신호등 유무교통섬 유무도로명칭횡단보도 종류
보행자 신호등 유무1.0000.0000.7340.706
교통섬 유무0.0001.0000.7340.115
도로명칭0.7340.7341.0000.567
횡단보도 종류0.7060.1150.5671.000
2023-12-12T18:22:55.898815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번도로차로 수위도경도횡단보도 종류교통섬 유무도로명칭보행자 신호등 유무
연번1.0000.601-0.286-0.4810.5760.2390.5150.739
도로차로 수0.6011.000-0.250-0.2990.3850.0420.0000.732
위도-0.286-0.2501.0000.2030.4540.0000.6900.675
경도-0.481-0.2990.2031.0000.4550.0000.7270.588
횡단보도 종류0.5760.3850.4540.4551.0000.1150.5670.706
교통섬 유무0.2390.0420.0000.0000.1151.0000.7340.000
도로명칭0.5150.0000.6900.7270.5670.7341.0000.734
보행자 신호등 유무0.7390.7320.6750.5880.7060.0000.7341.000

Missing values

2023-12-12T18:22:50.144887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:22:50.374203image/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.

Sample

연번횡단보도 종류위치교통섬 유무도로차로 수도로명칭도로명 주소지번주소보행자 신호등 유무위도경도
01일반봉산1리 마을회관N2건너말고샅길세종특별자치시 건너말고샅길 35세종특별자치시 조치원읍 봉산리 332-2N36.606927127.277855
12일반세종장례식장입구 버스정류장N2당산로<NA>세종특별자치시 조치원읍 봉암리 84-1N36.570055127.287767
23고원식새롬초등학교 후문 앞N2새롬서로세종특별자치시 새롬중앙1로 27세종특별자치시 새롬동 313N36.485527127.248253
34고원식호려울마을5단지 뒷편N2남세종로세종특별자치시 남세종로 441세종특별자치시 보람동 783N36.476902127.289758
45일반세종중앙농협 한솔지점N5누리로세종특별자치시 누리로 54세종특별자치시 한솔동 971Y36.475835127.251923
56일반세종신용협동조합N2용포로세종특별자치시 용포로 88세종특별자치시 용포리 194-1N36.466383127.281495
67고원식황금이용원 앞N2당산로세종특별자치시 당산로 132세종특별자치시 연기리 429-3N36.545196127.277691
78일반범지기마을 1단지 앞N5절재로세종특별자치시 절재로 13세종특별자치시 아름동 1339Y36.508825127.242861
89일반장기중학교 부출입구N2장척로세종특별자치시 장군면 장척로 373세종특별자치시 장군면 하봉리 359-26N36.49551127.203301
910일반아름동 범지기마을 6단지N2보듬로세종특별자치시 보듬3로 95세종특별자치시 아름동 1360N36.511188127.248802
연번횡단보도 종류위치교통섬 유무도로차로 수도로명칭도로명 주소지번주소보행자 신호등 유무위도경도
8384일반식세종로N5세종로<NA>세종특별자치시 종촌동 640Y36.508175127.24295
8485일반식세종로N6세종로<NA>세종특별자치시 종촌동 640Y36.508175127.24295
8586일반식갈매로N7갈매로<NA>세종특별자치시 어진동 654Y36.496807127.264339
8687일반식갈매로N7갈매로<NA>세종특별자치시 어진동 654Y36.496807127.264339
8788일반식갈매로N7갈매로<NA>세종특별자치시 어진동 654Y36.496814127.264339
8889일반식갈매로N5갈매로<NA>세종특별자치시 어진동 654Y36.496807127.264339
8990일반식마음로N5마음로<NA>세종특별자치시 고운동 산 95Y36.521554127.234216
9091일반식마음로N3마음로<NA>세종특별자치시 고운동 산 95Y36.521554127.234214
9192일반식마음로N5마음로<NA>세종특별자치시 고운동 산 95Y36.521554127.234281
9293일반식마음로N3마음로<NA>세종특별자치시 고운동 산 95Y36.521554127.234289