Overview

Dataset statistics

Number of variables13
Number of observations73
Missing cells86
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory110.8 B

Variable types

Categorical6
Text3
Numeric4

Dataset

Description경기도 광주시 관내 교차시설(차량이 교차하는 장소의 위치) 현황에 대한 데이터로 행정구역, 법정구역, 위치, 연장, 교차방식, 경도, 위도 등을 제공합니다.
URLhttps://www.data.go.kr/data/15036908/fileData.do

Alerts

지형지물부호 has constant value ""Constant
관리기관 has constant value ""Constant
행정구역 is highly overall correlated with 교차연장 and 2 other fieldsHigh correlation
법정구역 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
교차연장 is highly overall correlated with 행정구역High correlation
위도 is highly overall correlated with 행정구역 and 2 other fieldsHigh correlation
교차로수 is highly overall correlated with 위도High correlation
교차방식 is highly overall correlated with 법정구역High correlation
위치 has 21 (28.8%) missing valuesMissing
교차시설명 has 21 (28.8%) missing valuesMissing
교차연장 has 22 (30.1%) missing valuesMissing
교차시설폭원 has 22 (30.1%) missing valuesMissing
경도 has unique valuesUnique
위도 has unique valuesUnique
교차연장 has 8 (11.0%) zerosZeros
교차시설폭원 has 8 (11.0%) zerosZeros

Reproduction

Analysis started2023-12-12 16:39:13.937289
Analysis finished2023-12-12 16:39:17.555782
Duration3.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
도로교차시설
73 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도로교차시설 73
100.0%

Length

2023-12-13T01:39:17.636410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:17.733689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도로교차시설 73
100.0%

행정구역
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
경안동
23 
송정동
10 
곤지암읍
9 
오포읍
7 
초월읍
7 
Other values (3)
17 

Length

Max length5
Median length3
Mean length3.260274
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경안동 23
31.5%
송정동 10
13.7%
곤지암읍 9
 
12.3%
오포읍 7
 
9.6%
초월읍 7
 
9.6%
광남동 6
 
8.2%
퇴촌면 6
 
8.2%
남한산성면 5
 
6.8%

Length

2023-12-13T01:39:17.865197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:18.042154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경안동 23
31.5%
송정동 10
13.7%
곤지암읍 9
 
12.3%
오포읍 7
 
9.6%
초월읍 7
 
9.6%
광남동 6
 
8.2%
퇴촌면 6
 
8.2%
남한산성면 5
 
6.8%

법정구역
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
역동
15 
곤지암읍
9 
오포읍
7 
초월읍
7 
경안동
7 
Other values (7)
28 

Length

Max length5
Median length3
Mean length3.0547945
Min length2

Unique

Unique2 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
역동 15
20.5%
곤지암읍 9
12.3%
오포읍 7
9.6%
초월읍 7
9.6%
경안동 7
9.6%
송정동 7
9.6%
퇴촌면 6
 
8.2%
장지동 5
 
6.8%
남한산성면 5
 
6.8%
탄벌동 3
 
4.1%
Other values (2) 2
 
2.7%

Length

2023-12-13T01:39:18.574040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
역동 15
20.5%
곤지암읍 9
12.3%
오포읍 7
9.6%
초월읍 7
9.6%
경안동 7
9.6%
송정동 7
9.6%
퇴촌면 6
 
8.2%
장지동 5
 
6.8%
남한산성면 5
 
6.8%
탄벌동 3
 
4.1%
Other values (2) 2
 
2.7%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
광주시
73 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주시 73
100.0%

Length

2023-12-13T01:39:18.708658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:18.812978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주시 73
100.0%

위치
Text

MISSING 

Distinct40
Distinct (%)76.9%
Missing21
Missing (%)28.8%
Memory size716.0 B
2023-12-13T01:39:19.048835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length9.0576923
Min length1

Characters and Unicode

Total characters471
Distinct characters63
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

Unique38 ?
Unique (%)73.1%

Sample

1st row오포읍 추자리 275-2도
2nd row오포읍 매산리 617-18구
3rd row오포읍 양벌리 1055-2구
4th row오포읍 고산리 187-5답
5th row오포읍 신현리 709-2도
ValueCountFrequency (%)
역동 8
 
8.2%
송정동 7
 
7.2%
오포읍 6
 
6.2%
초월읍 6
 
6.2%
경안동 4
 
4.1%
남한산성면 3
 
3.1%
탄벌동 3
 
3.1%
대쌍령리 2
 
2.1%
27-19도 2
 
2.1%
곤지암읍 2
 
2.1%
Other values (53) 54
55.7%
2023-12-13T01:39:19.480262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69
 
14.6%
2 35
 
7.4%
- 34
 
7.2%
도 31
 
6.6%
동 25
 
5.3%
1 22
 
4.7%
리 17
 
3.6%
9 16
 
3.4%
4 16
 
3.4%
7 15
 
3.2%
Other values (53) 191
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 214
45.4%
Decimal Number 154
32.7%
Space Separator 69
 
14.6%
Dash Punctuation 34
 
7.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 31
 
14.5%
동 25
 
11.7%
리 17
 
7.9%
읍 14
 
6.5%
역 8
 
3.7%
송 7
 
3.3%
산 7
 
3.3%
정 7
 
3.3%
월 6
 
2.8%
오 6
 
2.8%
Other values (41) 86
40.2%
Decimal Number
ValueCountFrequency (%)
2 35
22.7%
1 22
14.3%
9 16
10.4%
4 16
10.4%
7 15
9.7%
5 14
 
9.1%
6 12
 
7.8%
3 9
 
5.8%
0 8
 
5.2%
8 7
 
4.5%
Space Separator
ValueCountFrequency (%)
69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 257
54.6%
Hangul 214
45.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 31
 
14.5%
동 25
 
11.7%
리 17
 
7.9%
읍 14
 
6.5%
역 8
 
3.7%
송 7
 
3.3%
산 7
 
3.3%
정 7
 
3.3%
월 6
 
2.8%
오 6
 
2.8%
Other values (41) 86
40.2%
Common
ValueCountFrequency (%)
69
26.8%
2 35
13.6%
- 34
13.2%
1 22
 
8.6%
9 16
 
6.2%
4 16
 
6.2%
7 15
 
5.8%
5 14
 
5.4%
6 12
 
4.7%
3 9
 
3.5%
Other values (2) 15
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 257
54.6%
Hangul 214
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69
26.8%
2 35
13.6%
- 34
13.2%
1 22
 
8.6%
9 16
 
6.2%
4 16
 
6.2%
7 15
 
5.8%
5 14
 
5.4%
6 12
 
4.7%
3 9
 
3.5%
Other values (2) 15
 
5.8%
Hangul
ValueCountFrequency (%)
도 31
 
14.5%
동 25
 
11.7%
리 17
 
7.9%
읍 14
 
6.5%
역 8
 
3.7%
송 7
 
3.3%
산 7
 
3.3%
정 7
 
3.3%
월 6
 
2.8%
오 6
 
2.8%
Other values (41) 86
40.2%

교차시설명
Text

MISSING 

Distinct27
Distinct (%)51.9%
Missing21
Missing (%)28.8%
Memory size716.0 B
2023-12-13T01:39:19.731523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length6.9615385
Min length1

Characters and Unicode

Total characters362
Distinct characters40
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

Unique20 ?
Unique (%)38.5%

Sample

1st row추자리 교차로
2nd row45번국도
3rd row43번국도,45번국도
4th row고산리 교차로
5th row국가지원지방도57호
ValueCountFrequency (%)
교차로 7
 
14.3%
43번국도 5
 
10.2%
3번국도,43번국도 4
 
8.2%
3번국도,43번국도,45번국도 4
 
8.2%
43번국도,45번국도 3
 
6.1%
국도3호선 3
 
6.1%
송정 2
 
4.1%
지방도389,3번국도 1
 
2.0%
추자리 1
 
2.0%
국도3 1
 
2.0%
Other values (18) 18
36.7%
2023-12-13T01:39:20.123585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 55
15.2%
국 45
12.4%
3 40
11.0%
번 39
10.8%
4 32
8.8%
, 25
 
6.9%
19
 
5.2%
5 15
 
4.1%
로 10
 
2.8%
교 9
 
2.5%
Other values (30) 73
20.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 218
60.2%
Decimal Number 99
27.3%
Other Punctuation 25
 
6.9%
Space Separator 19
 
5.2%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 55
25.2%
국 45
20.6%
번 39
17.9%
로 10
 
4.6%
교 9
 
4.1%
차 8
 
3.7%
지 6
 
2.8%
시 6
 
2.8%
선 5
 
2.3%
호 5
 
2.3%
Other values (19) 30
13.8%
Decimal Number
ValueCountFrequency (%)
3 40
40.4%
4 32
32.3%
5 15
 
15.2%
2 4
 
4.0%
1 4
 
4.0%
8 2
 
2.0%
9 1
 
1.0%
7 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 218
60.2%
Common 144
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 55
25.2%
국 45
20.6%
번 39
17.9%
로 10
 
4.6%
교 9
 
4.1%
차 8
 
3.7%
지 6
 
2.8%
시 6
 
2.8%
선 5
 
2.3%
호 5
 
2.3%
Other values (19) 30
13.8%
Common
ValueCountFrequency (%)
3 40
27.8%
4 32
22.2%
, 25
17.4%
19
13.2%
5 15
 
10.4%
2 4
 
2.8%
1 4
 
2.8%
8 2
 
1.4%
9 1
 
0.7%
7 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 218
60.2%
ASCII 144
39.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 55
25.2%
국 45
20.6%
번 39
17.9%
로 10
 
4.6%
교 9
 
4.1%
차 8
 
3.7%
지 6
 
2.8%
시 6
 
2.8%
선 5
 
2.3%
호 5
 
2.3%
Other values (19) 30
13.8%
ASCII
ValueCountFrequency (%)
3 40
27.8%
4 32
22.2%
, 25
17.4%
19
13.2%
5 15
 
10.4%
2 4
 
2.8%
1 4
 
2.8%
8 2
 
1.4%
9 1
 
0.7%
7 1
 
0.7%

교차연장
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct44
Distinct (%)86.3%
Missing22
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean252.53941
Minimum0
Maximum3191.22
Zeros8
Zeros (%)11.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-13T01:39:20.311456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114.55
median19.26
Q349.77
95-th percentile1796.88
Maximum3191.22
Range3191.22
Interquartile range (IQR)35.22

Descriptive statistics

Standard deviation670.26565
Coefficient of variation (CV)2.6541031
Kurtosis9.5446383
Mean252.53941
Median Absolute Deviation (MAD)13.99
Skewness3.1348497
Sum12879.51
Variance449256.04
MonotonicityNot monotonic
2023-12-13T01:39:20.564592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.0 8
 
11.0%
13.81 1
 
1.4%
37.51 1
 
1.4%
95.92 1
 
1.4%
21.29 1
 
1.4%
18.13 1
 
1.4%
38.41 1
 
1.4%
15.47 1
 
1.4%
29.35 1
 
1.4%
20.35 1
 
1.4%
Other values (34) 34
46.6%
(Missing) 22
30.1%
ValueCountFrequency (%)
0.0 8
11.0%
8.06 1
 
1.4%
11.24 1
 
1.4%
12.36 1
 
1.4%
13.81 1
 
1.4%
14.25 1
 
1.4%
14.85 1
 
1.4%
15.47 1
 
1.4%
16.54 1
 
1.4%
16.8 1
 
1.4%
ValueCountFrequency (%)
3191.22 1
1.4%
2511.65 1
1.4%
1936.07 1
1.4%
1657.69 1
1.4%
1167.55 1
1.4%
1125.63 1
1.4%
218.6 1
1.4%
96.38 1
1.4%
95.92 1
1.4%
65.31 1
1.4%

교차시설폭원
Real number (ℝ)

MISSING  ZEROS 

Distinct44
Distinct (%)86.3%
Missing22
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean25.990196
Minimum0
Maximum90.68
Zeros8
Zeros (%)11.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-13T01:39:20.790893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.665
median18.96
Q333.43
95-th percentile73.29
Maximum90.68
Range90.68
Interquartile range (IQR)21.765

Descriptive statistics

Standard deviation22.780692
Coefficient of variation (CV)0.87651097
Kurtosis0.69851544
Mean25.990196
Median Absolute Deviation (MAD)10.92
Skewness1.1366911
Sum1325.5
Variance518.95993
MonotonicityNot monotonic
2023-12-13T01:39:21.007892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.0 8
 
11.0%
52.03 1
 
1.4%
19.85 1
 
1.4%
32.26 1
 
1.4%
90.68 1
 
1.4%
45.69 1
 
1.4%
25.15 1
 
1.4%
67.26 1
 
1.4%
66.22 1
 
1.4%
70.66 1
 
1.4%
Other values (34) 34
46.6%
(Missing) 22
30.1%
ValueCountFrequency (%)
0.0 8
11.0%
8.01 1
 
1.4%
8.04 1
 
1.4%
8.05 1
 
1.4%
8.81 1
 
1.4%
11.5 1
 
1.4%
11.83 1
 
1.4%
13.6 1
 
1.4%
14.86 1
 
1.4%
15.11 1
 
1.4%
ValueCountFrequency (%)
90.68 1
1.4%
77.87 1
1.4%
75.92 1
1.4%
70.66 1
1.4%
67.26 1
1.4%
66.22 1
1.4%
56.62 1
1.4%
52.03 1
1.4%
45.69 1
1.4%
44.49 1
1.4%

교차로명
Text

Distinct62
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-13T01:39:21.335223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length5.1917808
Min length1

Characters and Unicode

Total characters379
Distinct characters113
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

Unique60 ?
Unique (%)82.2%

Sample

1st row추자교차로
2nd row양벌삼거리교차로
3rd row양촌사거리
4th row오포교차로
5th row하태교차로
ValueCountFrequency (%)
교차로 3
 
4.5%
송정 2
 
3.0%
역동사거리 1
 
1.5%
시장입구 1
 
1.5%
광주ic 1
 
1.5%
벌원교차로 1
 
1.5%
현대주유소앞 1
 
1.5%
장지사거리 1
 
1.5%
신장지사거리 1
 
1.5%
엄미리계곡삼거리 1
 
1.5%
Other values (53) 53
80.3%
2023-12-13T01:39:21.871858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 25
 
6.6%
로 19
 
5.0%
차 18
 
4.7%
리 18
 
4.7%
앞 17
 
4.5%
거 16
 
4.2%
15
 
4.0%
도 11
 
2.9%
번 9
 
2.4%
사 9
 
2.4%
Other values (103) 222
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 341
90.0%
Space Separator 15
 
4.0%
Decimal Number 14
 
3.7%
Other Punctuation 5
 
1.3%
Uppercase Letter 2
 
0.5%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 25
 
7.3%
로 19
 
5.6%
차 18
 
5.3%
리 18
 
5.3%
앞 17
 
5.0%
거 16
 
4.7%
도 11
 
3.2%
번 9
 
2.6%
사 9
 
2.6%
동 8
 
2.3%
Other values (92) 191
56.0%
Decimal Number
ValueCountFrequency (%)
3 6
42.9%
4 4
28.6%
5 2
 
14.3%
9 1
 
7.1%
8 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 341
90.0%
Common 36
 
9.5%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 25
 
7.3%
로 19
 
5.6%
차 18
 
5.3%
리 18
 
5.3%
앞 17
 
5.0%
거 16
 
4.7%
도 11
 
3.2%
번 9
 
2.6%
사 9
 
2.6%
동 8
 
2.3%
Other values (92) 191
56.0%
Common
ValueCountFrequency (%)
15
41.7%
3 6
 
16.7%
, 5
 
13.9%
4 4
 
11.1%
5 2
 
5.6%
9 1
 
2.8%
8 1
 
2.8%
( 1
 
2.8%
) 1
 
2.8%
Latin
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 341
90.0%
ASCII 38
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 25
 
7.3%
로 19
 
5.6%
차 18
 
5.3%
리 18
 
5.3%
앞 17
 
5.0%
거 16
 
4.7%
도 11
 
3.2%
번 9
 
2.6%
사 9
 
2.6%
동 8
 
2.3%
Other values (92) 191
56.0%
ASCII
ValueCountFrequency (%)
15
39.5%
3 6
 
15.8%
, 5
 
13.2%
4 4
 
10.5%
5 2
 
5.3%
9 1
 
2.6%
8 1
 
2.6%
C 1
 
2.6%
I 1
 
2.6%
( 1
 
2.6%

교차로수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size716.0 B
3
28 
<NA>
22 
4
20 
5
 
2
2
 
1

Length

Max length4
Median length1
Mean length1.9041096
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row4
2nd row3
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
3 28
38.4%
<NA> 22
30.1%
4 20
27.4%
5 2
 
2.7%
2 1
 
1.4%

Length

2023-12-13T01:39:22.043900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:22.188818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 28
38.4%
na 22
30.1%
4 20
27.4%
5 2
 
2.7%
2 1
 
1.4%

교차방식
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
평면교차
47 
미분류
22 
입체교차
 
4

Length

Max length4
Median length4
Mean length3.6986301
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row입체교차
2nd row평면교차
3rd row평면교차
4th row입체교차
5th row평면교차

Common Values

ValueCountFrequency (%)
평면교차 47
64.4%
미분류 22
30.1%
입체교차 4
 
5.5%

Length

2023-12-13T01:39:22.362020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:22.503809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평면교차 47
64.4%
미분류 22
30.1%
입체교차 4
 
5.5%

경도
Real number (ℝ)

UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.27218
Minimum127.15051
Maximum127.3945
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-13T01:39:22.662027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.15051
5-th percentile127.23233
Q1127.24814
median127.25702
Q3127.30286
95-th percentile127.3578
Maximum127.3945
Range0.2439916
Interquartile range (IQR)0.0547226

Descriptive statistics

Standard deviation0.042549407
Coefficient of variation (CV)0.0003343182
Kurtosis1.0290257
Mean127.27218
Median Absolute Deviation (MAD)0.0101342
Skewness0.80789762
Sum9290.8691
Variance0.001810452
MonotonicityNot monotonic
2023-12-13T01:39:22.839036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.229749 1
 
1.4%
127.2602968 1
 
1.4%
127.2570165 1
 
1.4%
127.3165633 1
 
1.4%
127.2837293 1
 
1.4%
127.2415635 1
 
1.4%
127.2525507 1
 
1.4%
127.2459396 1
 
1.4%
127.2410567 1
 
1.4%
127.2357791 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
127.1505069 1
1.4%
127.2125904 1
1.4%
127.2238922 1
1.4%
127.229749 1
1.4%
127.2340574 1
1.4%
127.2357791 1
1.4%
127.2359003 1
1.4%
127.2410567 1
1.4%
127.2415635 1
1.4%
127.2442893 1
1.4%
ValueCountFrequency (%)
127.3944985 1
1.4%
127.370027 1
1.4%
127.3683737 1
1.4%
127.36138 1
1.4%
127.3554185 1
1.4%
127.3512162 1
1.4%
127.3469284 1
1.4%
127.3378896 1
1.4%
127.3297796 1
1.4%
127.3257231 1
1.4%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.401047
Minimum37.328558
Maximum37.475977
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-13T01:39:22.983474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.328558
5-th percentile37.343593
Q137.376124
median37.403451
Q337.414943
95-th percentile37.470618
Maximum37.475977
Range0.1474192
Interquartile range (IQR)0.03881899

Descriptive statistics

Standard deviation0.036061005
Coefficient of variation (CV)0.000964171
Kurtosis-0.22190338
Mean37.401047
Median Absolute Deviation (MAD)0.01441602
Skewness0.23345646
Sum2730.2764
Variance0.0013003961
MonotonicityNot monotonic
2023-12-13T01:39:23.140688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.36240068 1
 
1.4%
37.43161404 1
 
1.4%
37.41374282 1
 
1.4%
37.3602468 1
 
1.4%
37.39182769 1
 
1.4%
37.41375976 1
 
1.4%
37.45521024 1
 
1.4%
37.46347744 1
 
1.4%
37.47597737 1
 
1.4%
37.39651315 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
37.32855817 1
1.4%
37.33704529 1
1.4%
37.33954983 1
1.4%
37.34254411 1
1.4%
37.34429153 1
1.4%
37.34845048 1
1.4%
37.34862852 1
1.4%
37.35103067 1
1.4%
37.35577486 1
1.4%
37.35642111 1
1.4%
ValueCountFrequency (%)
37.47597737 1
1.4%
37.47209095 1
1.4%
37.47143132 1
1.4%
37.47074269 1
1.4%
37.47053492 1
1.4%
37.46817328 1
1.4%
37.46571477 1
1.4%
37.46347744 1
1.4%
37.45521024 1
1.4%
37.44854783 1
1.4%

Interactions

2023-12-13T01:39:16.460831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:14.726492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:15.238496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:15.675200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:16.591153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:14.832146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:15.342169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:15.903790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:16.710210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:14.942236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:15.438615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:16.075524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:16.839565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:15.074585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:15.551992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:16.274812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:39:23.238947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역법정구역위치교차시설명교차연장교차시설폭원교차로명교차로수교차방식경도위도
행정구역1.0001.0000.9110.8690.7030.0000.9610.4990.6400.7520.895
법정구역1.0001.0000.9300.9000.7420.4340.9710.5790.8150.7220.874
위치0.9110.9301.0000.9971.0000.9670.9990.0001.0000.9961.000
교차시설명0.8690.9000.9971.0000.7560.8271.0000.0000.9810.9510.831
교차연장0.7030.7421.0000.7561.0000.0001.0000.4460.0000.7070.709
교차시설폭원0.0000.4340.9670.8270.0001.0000.9830.3070.0000.0000.377
교차로명0.9610.9710.9991.0001.0000.9831.0000.0001.0000.9900.997
교차로수0.4990.5790.0000.0000.4460.3070.0001.0000.4150.5740.889
교차방식0.6400.8151.0000.9810.0000.0001.0000.4151.0000.6010.586
경도0.7520.7220.9960.9510.7070.0000.9900.5740.6011.0000.712
위도0.8950.8741.0000.8310.7090.3770.9970.8890.5860.7121.000
2023-12-13T01:39:23.358553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교차로수행정구역법정구역교차방식
교차로수1.0000.3520.3850.271
행정구역0.3521.0000.9690.494
법정구역0.3850.9691.0000.503
교차방식0.2710.4940.5031.000
2023-12-13T01:39:23.455052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교차연장교차시설폭원경도위도행정구역법정구역교차로수교차방식
교차연장1.0000.3310.242-0.3330.5080.4620.2930.000
교차시설폭원0.3311.0000.1800.1460.0000.2010.1650.000
경도0.2420.1801.000-0.1310.4910.3980.4170.309
위도-0.3330.146-0.1311.0000.7020.6080.5540.406
행정구역0.5080.0000.4910.7021.0000.9690.3520.494
법정구역0.4620.2010.3980.6080.9691.0000.3850.503
교차로수0.2930.1650.4170.5540.3520.3851.0000.271
교차방식0.0000.0000.3090.4060.4940.5030.2711.000

Missing values

2023-12-13T01:39:17.033823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:39:17.291690image/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.
2023-12-13T01:39:17.467917image/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

지형지물부호행정구역법정구역관리기관위치교차시설명교차연장교차시설폭원교차로명교차로수교차방식경도위도
0도로교차시설오포읍오포읍광주시오포읍 추자리 275-2도추자리 교차로53.4632.74추자교차로4입체교차127.22974937.362401
1도로교차시설오포읍오포읍광주시오포읍 매산리 617-18구45번국도1657.6920.21양벌삼거리교차로3평면교차127.24428937.365828
2도로교차시설오포읍오포읍광주시오포읍 양벌리 1055-2구43번국도,45번국도17.5519.36양촌사거리4평면교차127.24637237.370662
3도로교차시설오포읍오포읍광주시오포읍 고산리 187-5답고산리 교차로96.3816.37오포교차로4입체교차127.23405737.371028
4도로교차시설오포읍오포읍광주시오포읍 신현리 709-2도국가지원지방도57호59.5327.76하태교차로4평면교차127.15050737.360379
5도로교차시설광남동장지동광주시18.1615.33평면교차127.2481437.394781
6도로교차시설광남동장지동광주시14.2514.863평면교차127.24856537.395096
7도로교차시설경안동역동광주시22.9217.073평면교차127.24688237.396597
8도로교차시설경안동역동광주시17.0716.583평면교차127.24804237.398584
9도로교차시설경안동역동광주시18.878.043평면교차127.24839837.398596
지형지물부호행정구역법정구역관리기관위치교차시설명교차연장교차시설폭원교차로명교차로수교차방식경도위도
63도로교차시설송정동송정동광주시송정동 64-16도3번국도,43번국도11.2477.87송정교북단교차로4평면교차127.26020637.414095
64도로교차시설송정동송정동광주시송정동 17-1전지방도389,3번국도218.613.6지방도389,3번국도3평면교차127.27094937.415949
65도로교차시설경안동역동광주시역동 1-209답역동 교차로12.3644.49역동 교차로4평면교차127.25430437.407882
66도로교차시설경안동경안동광주시경안동 262도중앙로8.0629.2중앙로4평면교차127.25827937.40982
67도로교차시설경안동역동광주시역동 227도43번국도,45번국도,3번국도16.842.0143번국도,45번국도,3번국도4평면교차127.25606537.403976
68도로교차시설경안동역동광주시역동 229-1도3번국도,43번국도,45번국도14.8518.713번국도,43번국도,45번국도4입체교차127.2561837.403451
69도로교차시설경안동역동광주시역동 27-19도3번국도,43번국도,45번국도60.8715.75시장입구3평면교차127.26026537.406964
70도로교차시설경안동역동광주시역동 27-19도3번국도,43번국도,45번국도21.6475.92역동사거리4평면교차127.26105337.406723
71도로교차시설경안동역동광주시역동 28-57도3번국도,43번국도,45번국도20.922.1광주IC4입체교차127.26119237.405547
72도로교차시설경안동역동광주시역동 28-91임3번국도,43번국도65.3118.96역동삼거리3평면교차127.26084937.403987