Overview

Dataset statistics

Number of variables104
Number of observations44
Missing cells93
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.9 KiB
Average record size in memory928.0 B

Variable types

Numeric59
Categorical37
Text5
DateTime3

Dataset

Description경상남도 도로대장전산화 시스템 데이터의 중장기개방계획에 따른 데이터입니다. 시스템 상에서의 각 도로의 유로도로, 터널 등의 정보를 가지고 있으며, 도로대장의 도로대장 총괄 데이터를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15091939

Alerts

관리기관 has constant value ""Constant
이력코드 has constant value ""Constant
포장도로_터널개소(3차로) has constant value ""Constant
포장도로_터널연장(3차로) has constant value ""Constant
포장도로_터널개소(5차로이상) has constant value ""Constant
포장도로_터널연장(5차로이상) has constant value ""Constant
유료도로 교량_개소 has constant value ""Constant
유료도로 교량_연장 has constant value ""Constant
도로종류 is highly imbalanced (84.4%)Imbalance
구간번호 is highly imbalanced (71.2%)Imbalance
포장도로_터널개소(2차로) is highly imbalanced (67.6%)Imbalance
포장도로_터널연장(2차로) is highly imbalanced (76.6%)Imbalance
포장도로_터널개소(4차로) is highly imbalanced (84.4%)Imbalance
포장도로_터널연장(4차로) is highly imbalanced (80.3%)Imbalance
포장도로_터널개소(전체) is highly imbalanced (62.6%)Imbalance
포장도로_교량개소(강교) is highly imbalanced (50.6%)Imbalance
포장도로_교량개소(합성교) is highly imbalanced (84.4%)Imbalance
포장도로_교량연장(합성교) is highly imbalanced (84.4%)Imbalance
비포장도로연장 is highly imbalanced (84.4%)Imbalance
폭원_중앙분리대 is highly imbalanced (67.6%)Imbalance
자전거도로 연장_좌 is highly imbalanced (84.4%)Imbalance
자전거도로 연장_우 is highly imbalanced (84.4%)Imbalance
교차_지하도 is highly imbalanced (84.4%)Imbalance
교차_철도(과선) is highly imbalanced (73.3%)Imbalance
교차_철도(가도) is highly imbalanced (64.1%)Imbalance
교차_도로(입체) is highly imbalanced (54.9%)Imbalance
유료도로_관리자 is highly imbalanced (56.1%)Imbalance
유료도로_요금징수_시작일자 is highly imbalanced (62.6%)Imbalance
유료도로_요금징수_종료일자 is highly imbalanced (62.6%)Imbalance
유료도로_요금징수 시설수 is highly imbalanced (84.4%)Imbalance
유료도로 전체 연장 is highly imbalanced (84.4%)Imbalance
유료도로 도로_연장 is highly imbalanced (84.4%)Imbalance
유료도로 터널_개소 is highly imbalanced (84.4%)Imbalance
유료도로 터널_연장 is highly imbalanced (84.4%)Imbalance
비고 is highly imbalanced (84.4%)Imbalance
지적고시 연월일 has 42 (95.5%) missing valuesMissing
노선시점 위치(주소) has 1 (2.3%) missing valuesMissing
노선종점 위치(주소) has 2 (4.5%) missing valuesMissing
주요한 경과지 has 3 (6.8%) missing valuesMissing
중용연장 has 6 (13.6%) missing valuesMissing
유료도로_요금징수근거 has 39 (88.6%) missing valuesMissing
식별번호 has unique valuesUnique
노선명 has unique valuesUnique
종단경사(3퍼센트미만)_연장 has unique valuesUnique
종단경사(3_5퍼센트미만)_연장 has unique valuesUnique
관리번호 has 31 (70.5%) zerosZeros
노선연장 has 2 (4.5%) zerosZeros
전용연장 has 3 (6.8%) zerosZeros
중용연장 has 5 (11.4%) zerosZeros
통행불능연장 has 20 (45.5%) zerosZeros
포장도로_전체연장 has 3 (6.8%) zerosZeros
포장도로_도로연장 has 3 (6.8%) zerosZeros
포장도로_터널연장(전체) has 39 (88.6%) zerosZeros
포장도로_교량연장(강교) has 36 (81.8%) zerosZeros
포장도로_교량개소(철근콘크리트교) has 3 (6.8%) zerosZeros
포장도로_교량연장(철근콘크리트교) has 3 (6.8%) zerosZeros
포장도로_교량개소(기타) has 37 (84.1%) zerosZeros
포장도로_교량연장(기타) has 37 (84.1%) zerosZeros
포장도로_교량개소(전체) has 2 (4.5%) zerosZeros
포장도로_교량연장(전체) has 2 (4.5%) zerosZeros
미개통도로연장 has 18 (40.9%) zerosZeros
폭원_전체 has 5 (11.4%) zerosZeros
폭원_차도 has 6 (13.6%) zerosZeros
폭원_길어깨(보도) has 6 (13.6%) zerosZeros
포장두께_전체 has 6 (13.6%) zerosZeros
포장두께_포장기층_포장슬래브 has 7 (15.9%) zerosZeros
포장두께_보조기층 has 7 (15.9%) zerosZeros
도로연장(2차로미만) has 27 (61.4%) zerosZeros
도로연장(2차로_4차로미만) has 4 (9.1%) zerosZeros
도로연장(4차로_6차로미만) has 26 (59.1%) zerosZeros
도로연장(6차로이상) has 36 (81.8%) zerosZeros
차도 연장_전체(상행) has 3 (6.8%) zerosZeros
차도 연장_전체(하행) has 3 (6.8%) zerosZeros
아스팔트 차도 연장(상행) has 3 (6.8%) zerosZeros
아스팔트 차도 연장(하행) has 4 (9.1%) zerosZeros
콘크리트 차도 연장(상행) has 39 (88.6%) zerosZeros
콘크리트 차도 연장(하행) has 39 (88.6%) zerosZeros
비포장 차도 연장(상행) has 38 (86.4%) zerosZeros
비포장 차도 연장(하행) has 38 (86.4%) zerosZeros
포장 보도(길어깨) 연장_좌 has 6 (13.6%) zerosZeros
포장 보도(길어깨) 연장_우 has 8 (18.2%) zerosZeros
비포장 보도(길어깨) 연장_좌 has 25 (56.8%) zerosZeros
비포장 보도(길어깨) 연장_우 has 25 (56.8%) zerosZeros
도로 면적_전체 has 6 (13.6%) zerosZeros
도로 면적_국유지 has 5 (11.4%) zerosZeros
도로 면적_공유지 has 21 (47.7%) zerosZeros
도로 면적_사유지 has 6 (13.6%) zerosZeros
곡선반경(100m 미만) has 4 (9.1%) zerosZeros
곡선반경(100 이상_200m 미만) has 2 (4.5%) zerosZeros
곡선반경(200 이상 _300m 미만) has 5 (11.4%) zerosZeros
곡선반경(300 이상 _460m 미만) has 3 (6.8%) zerosZeros
곡선반경(460 이상 _700m 미만) has 5 (11.4%) zerosZeros
곡선반경(700m 이상) has 4 (9.1%) zerosZeros
교차_도로(평면) has 30 (68.2%) zerosZeros
종단경사(3퍼센트미만)_연장 has 1 (2.3%) zerosZeros
종단경사(3_5퍼센트미만)_연장 has 1 (2.3%) zerosZeros
종단경사(5_10퍼센트미만)_개소 has 4 (9.1%) zerosZeros
종단경사(5_10퍼센트미만)_연장 has 5 (11.4%) zerosZeros
종단경사(10퍼센트이상)_개소 has 13 (29.5%) zerosZeros
종단경사(10퍼센트이상)_연장 has 13 (29.5%) zerosZeros

Reproduction

Analysis started2023-12-10 22:57:28.861372
Analysis finished2023-12-10 22:57:29.775279
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

식별번호
Real number (ℝ)

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:29.838379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q111.75
median22.5
Q333.25
95-th percentile41.85
Maximum44
Range43
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation12.845233
Coefficient of variation (CV)0.57089923
Kurtosis-1.2
Mean22.5
Median Absolute Deviation (MAD)11
Skewness0
Sum990
Variance165
MonotonicityNot monotonic
2023-12-11T07:57:29.954756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
9 1
 
2.3%
32 1
 
2.3%
34 1
 
2.3%
35 1
 
2.3%
36 1
 
2.3%
37 1
 
2.3%
38 1
 
2.3%
39 1
 
2.3%
40 1
 
2.3%
41 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
44 1
2.3%
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%

관리번호
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2419318.5
Minimum0
Maximum10990001
Zeros31
Zeros (%)70.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:30.057060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3710001.75
95-th percentile10777001
Maximum10990001
Range10990001
Interquartile range (IQR)710001.75

Descriptive statistics

Standard deviation4397169.9
Coefficient of variation (CV)1.8175242
Kurtosis-0.17855787
Mean2419318.5
Median Absolute Deviation (MAD)0
Skewness1.3462356
Sum1.0645001 × 108
Variance1.9335103 × 1013
MonotonicityNot monotonic
2023-12-11T07:57:30.153912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 31
70.5%
10990001 1
 
2.3%
10890001 1
 
2.3%
10210001 1
 
2.3%
10060001 1
 
2.3%
10010001 1
 
2.3%
10410001 1
 
2.3%
10160001 1
 
2.3%
600001 1
 
2.3%
10220001 1
 
2.3%
Other values (4) 4
 
9.1%
ValueCountFrequency (%)
0 31
70.5%
600001 1
 
2.3%
600002 1
 
2.3%
1040001 1
 
2.3%
10010001 1
 
2.3%
10060001 1
 
2.3%
10160001 1
 
2.3%
10210001 1
 
2.3%
10220001 1
 
2.3%
10410001 1
 
2.3%
ValueCountFrequency (%)
10990001 1
2.3%
10890001 1
2.3%
10840001 1
2.3%
10420001 1
2.3%
10410001 1
2.3%
10220001 1
2.3%
10210001 1
2.3%
10160001 1
2.3%
10060001 1
2.3%
10010001 1
2.3%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
1683
44 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1683
2nd row1683
3rd row1683
4th row1683
5th row1683

Common Values

ValueCountFrequency (%)
1683 44
100.0%

Length

2023-12-11T07:57:30.258027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:30.343823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1683 44
100.0%

도로종류
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
1504
43 
1507
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row1504
2nd row1504
3rd row1504
4th row1504
5th row1504

Common Values

ValueCountFrequency (%)
1504 43
97.7%
1507 1
 
2.3%

Length

2023-12-11T07:57:30.449279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:30.534433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1504 43
97.7%
1507 1
 
2.3%

노선번호
Real number (ℝ)

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean872.22727
Minimum30
Maximum1099
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:30.636465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile58.3
Q11003.75
median1017
Q31037.75
95-th percentile1083.4
Maximum1099
Range1069
Interquartile range (IQR)34

Descriptive statistics

Standard deviation361.15009
Coefficient of variation (CV)0.41405503
Kurtosis1.7508493
Mean872.22727
Median Absolute Deviation (MAD)15.5
Skewness-1.901846
Sum38378
Variance130429.39
MonotonicityNot monotonic
2023-12-11T07:57:30.753046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
60 2
 
4.5%
1003 1
 
2.3%
69 1
 
2.3%
58 1
 
2.3%
1080 1
 
2.3%
1020 1
 
2.3%
1022 1
 
2.3%
1029 1
 
2.3%
1077 1
 
2.3%
1002 1
 
2.3%
Other values (33) 33
75.0%
ValueCountFrequency (%)
30 1
2.3%
37 1
2.3%
58 1
2.3%
60 2
4.5%
67 1
2.3%
69 1
2.3%
907 1
2.3%
1001 1
2.3%
1002 1
2.3%
1003 1
2.3%
ValueCountFrequency (%)
1099 1
2.3%
1089 1
2.3%
1084 1
2.3%
1080 1
2.3%
1077 1
2.3%
1051 1
2.3%
1049 1
2.3%
1047 1
2.3%
1042 1
2.3%
1041 1
2.3%

노선명
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-11T07:57:31.199458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0227273
Min length5

Characters and Unicode

Total characters221
Distinct characters87
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

Unique44 ?
Unique (%)100.0%

Sample

1st row사봉~내서
2nd row대방~악양
3rd row악양-시천
4th row어곡-단장
5th row개천-궁유
ValueCountFrequency (%)
사봉~내서 1
 
2.3%
대방~악양 1
 
2.3%
황사농공단지 1
 
2.3%
부산-울진 1
 
2.3%
나주-부산 1
 
2.3%
이반-내이 1
 
2.3%
용호~봉황 1
 
2.3%
용산~창아 1
 
2.3%
진전~정곡 1
 
2.3%
동면~상동 1
 
2.3%
Other values (34) 34
77.3%
2023-12-11T07:57:31.515372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 22
 
10.0%
~ 21
 
9.5%
7
 
3.2%
7
 
3.2%
7
 
3.2%
6
 
2.7%
5
 
2.3%
5
 
2.3%
4
 
1.8%
4
 
1.8%
Other values (77) 133
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 178
80.5%
Dash Punctuation 22
 
10.0%
Math Symbol 21
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7
 
3.9%
7
 
3.9%
7
 
3.9%
6
 
3.4%
5
 
2.8%
5
 
2.8%
4
 
2.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (75) 125
70.2%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 178
80.5%
Common 43
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7
 
3.9%
7
 
3.9%
7
 
3.9%
6
 
3.4%
5
 
2.8%
5
 
2.8%
4
 
2.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (75) 125
70.2%
Common
ValueCountFrequency (%)
- 22
51.2%
~ 21
48.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 178
80.5%
ASCII 43
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 22
51.2%
~ 21
48.8%
Hangul
ValueCountFrequency (%)
7
 
3.9%
7
 
3.9%
7
 
3.9%
6
 
3.4%
5
 
2.8%
5
 
2.8%
4
 
2.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (75) 125
70.2%

구간번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
40 
19
 
2
8
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.7727273
Min length1

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 40
90.9%
19 2
 
4.5%
8 1
 
2.3%
4 1
 
2.3%

Length

2023-12-11T07:57:31.647493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:31.742612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
90.9%
19 2
 
4.5%
8 1
 
2.3%
4 1
 
2.3%

이력코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2023-12-11T07:57:31.831577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:31.911750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%
Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum2003-02-10 00:00:00
Maximum2013-10-31 00:00:00
2023-12-11T07:57:31.990631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:57:32.074669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum2003-02-10 00:00:00
Maximum2013-10-31 00:00:00
2023-12-11T07:57:32.163594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:57:32.249489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
Distinct7
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
2003-02-20
29 
2003-02-10
10 
2010-01-04
 
1
2010-01-30
 
1
2003-02-30
 
1
Other values (2)
 
2

Length

Max length10
Median length10
Mean length9.9545455
Min length8

Unique

Unique5 ?
Unique (%)11.4%

Sample

1st row2003-02-20
2nd row2003-02-20
3rd row2003-02-20
4th row2003-02-20
5th row2003-02-20

Common Values

ValueCountFrequency (%)
2003-02-20 29
65.9%
2003-02-10 10
 
22.7%
2010-01-04 1
 
2.3%
2010-01-30 1
 
2.3%
2003-02-30 1
 
2.3%
2009-05-30 1
 
2.3%
20131031 1
 
2.3%

Length

2023-12-11T07:57:32.365257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:32.471385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2003-02-20 29
65.9%
2003-02-10 10
 
22.7%
2010-01-04 1
 
2.3%
2010-01-30 1
 
2.3%
2003-02-30 1
 
2.3%
2009-05-30 1
 
2.3%
20131031 1
 
2.3%
Distinct2
Distinct (%)100.0%
Missing42
Missing (%)95.5%
Memory size484.0 B
Minimum2003-02-10 00:00:00
Maximum2013-10-31 00:00:00
2023-12-11T07:57:32.557669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:57:32.652169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
Distinct43
Distinct (%)100.0%
Missing1
Missing (%)2.3%
Memory size484.0 B
2023-12-11T07:57:32.871496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length11.186047
Min length6

Characters and Unicode

Total characters481
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

Unique43 ?
Unique (%)100.0%

Sample

1st row진주시 사봉면 무촌리
2nd row경상남도 사천시 대방동
3rd row하동군 악양면 정동
4th row지1077분기-양산시 어곡동
5th row고성군개천면가천리
ValueCountFrequency (%)
경상남도 9
 
7.3%
하동군 5
 
4.0%
양산시 4
 
3.2%
사천시 4
 
3.2%
고성군 4
 
3.2%
진주시 3
 
2.4%
함양군 3
 
2.4%
덕호리 3
 
2.4%
함안군 3
 
2.4%
통영시 2
 
1.6%
Other values (75) 84
67.7%
2023-12-11T07:57:33.209638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
 
16.8%
31
 
6.4%
29
 
6.0%
24
 
5.0%
21
 
4.4%
19
 
4.0%
15
 
3.1%
12
 
2.5%
12
 
2.5%
11
 
2.3%
Other values (95) 226
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 392
81.5%
Space Separator 81
 
16.8%
Decimal Number 6
 
1.2%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
31
 
7.9%
29
 
7.4%
24
 
6.1%
21
 
5.4%
19
 
4.8%
15
 
3.8%
12
 
3.1%
12
 
3.1%
11
 
2.8%
10
 
2.6%
Other values (88) 208
53.1%
Decimal Number
ValueCountFrequency (%)
7 2
33.3%
2 1
16.7%
5 1
16.7%
0 1
16.7%
1 1
16.7%
Space Separator
ValueCountFrequency (%)
81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 392
81.5%
Common 89
 
18.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
31
 
7.9%
29
 
7.4%
24
 
6.1%
21
 
5.4%
19
 
4.8%
15
 
3.8%
12
 
3.1%
12
 
3.1%
11
 
2.8%
10
 
2.6%
Other values (88) 208
53.1%
Common
ValueCountFrequency (%)
81
91.0%
- 2
 
2.2%
7 2
 
2.2%
2 1
 
1.1%
5 1
 
1.1%
0 1
 
1.1%
1 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 392
81.5%
ASCII 89
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
91.0%
- 2
 
2.2%
7 2
 
2.2%
2 1
 
1.1%
5 1
 
1.1%
0 1
 
1.1%
1 1
 
1.1%
Hangul
ValueCountFrequency (%)
31
 
7.9%
29
 
7.4%
24
 
6.1%
21
 
5.4%
19
 
4.8%
15
 
3.8%
12
 
3.1%
12
 
3.1%
11
 
2.8%
10
 
2.6%
Other values (88) 208
53.1%
Distinct41
Distinct (%)97.6%
Missing2
Missing (%)4.5%
Memory size484.0 B
2023-12-11T07:57:33.434967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length11.809524
Min length7

Characters and Unicode

Total characters496
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

Unique40 ?
Unique (%)95.2%

Sample

1st row마산시 내서읍 중리
2nd row경상남도 하동군 악양면 평사리
3rd row산청군 시천면 동당
4th row지1077분기-밀양시 단장면 범도리
5th row의령군궁유면압곡리
ValueCountFrequency (%)
경상남도 8
 
6.4%
합천군 5
 
4.0%
진주시 4
 
3.2%
거창군 4
 
3.2%
창녕군 4
 
3.2%
산청군 3
 
2.4%
대양면 2
 
1.6%
밀양시 2
 
1.6%
고성군 2
 
1.6%
양산시 2
 
1.6%
Other values (84) 89
71.2%
2023-12-11T07:57:33.765135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
83
 
16.7%
36
 
7.3%
31
 
6.2%
25
 
5.0%
19
 
3.8%
16
 
3.2%
13
 
2.6%
12
 
2.4%
12
 
2.4%
12
 
2.4%
Other values (103) 237
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 402
81.0%
Space Separator 83
 
16.7%
Decimal Number 8
 
1.6%
Dash Punctuation 2
 
0.4%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
36
 
9.0%
31
 
7.7%
25
 
6.2%
19
 
4.7%
16
 
4.0%
13
 
3.2%
12
 
3.0%
12
 
3.0%
12
 
3.0%
11
 
2.7%
Other values (94) 215
53.5%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
7 2
25.0%
5 1
12.5%
2 1
12.5%
4 1
12.5%
0 1
12.5%
Space Separator
ValueCountFrequency (%)
83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 402
81.0%
Common 94
 
19.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
36
 
9.0%
31
 
7.7%
25
 
6.2%
19
 
4.7%
16
 
4.0%
13
 
3.2%
12
 
3.0%
12
 
3.0%
12
 
3.0%
11
 
2.7%
Other values (94) 215
53.5%
Common
ValueCountFrequency (%)
83
88.3%
1 2
 
2.1%
7 2
 
2.1%
- 2
 
2.1%
~ 1
 
1.1%
5 1
 
1.1%
2 1
 
1.1%
4 1
 
1.1%
0 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 402
81.0%
ASCII 94
 
19.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
83
88.3%
1 2
 
2.1%
7 2
 
2.1%
- 2
 
2.1%
~ 1
 
1.1%
5 1
 
1.1%
2 1
 
1.1%
4 1
 
1.1%
0 1
 
1.1%
Hangul
ValueCountFrequency (%)
36
 
9.0%
31
 
7.7%
25
 
6.2%
19
 
4.7%
16
 
4.0%
13
 
3.2%
12
 
3.0%
12
 
3.0%
12
 
3.0%
11
 
2.7%
Other values (94) 215
53.5%

주요한 경과지
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing3
Missing (%)6.8%
Memory size484.0 B
2023-12-11T07:57:33.920158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length17.97561
Min length3

Characters and Unicode

Total characters737
Distinct characters139
Distinct categories4 ?
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 (%)100.0%

Sample

1st row진주시사봉면 함안군군북면 가야읍산인면마산시내서읍
2nd row사천시 대방 송포 하동군 진교 양보 횡천 청암 악양
3rd row삼신봉터널, 예치터
4th row에덴벨리리조트,밀양댐
5th row남산삼거리,대사교,사봉삼거리,봉대삼거리,새골소류지
ValueCountFrequency (%)
산청군 3
 
2.3%
사천시 3
 
2.3%
함양군 3
 
2.3%
하동군 3
 
2.3%
합천군 3
 
2.3%
무안면 2
 
1.6%
창녕군 2
 
1.6%
하이면 2
 
1.6%
대양면 2
 
1.6%
함안군 2
 
1.6%
Other values (101) 104
80.6%
2023-12-11T07:57:34.176305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
 
11.9%
, 60
 
8.1%
53
 
7.2%
26
 
3.5%
23
 
3.1%
21
 
2.8%
18
 
2.4%
15
 
2.0%
14
 
1.9%
14
 
1.9%
Other values (129) 405
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 587
79.6%
Space Separator 88
 
11.9%
Other Punctuation 60
 
8.1%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
53
 
9.0%
26
 
4.4%
23
 
3.9%
21
 
3.6%
18
 
3.1%
15
 
2.6%
14
 
2.4%
14
 
2.4%
14
 
2.4%
13
 
2.2%
Other values (125) 376
64.1%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
88
100.0%
Other Punctuation
ValueCountFrequency (%)
, 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 587
79.6%
Common 148
 
20.1%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
53
 
9.0%
26
 
4.4%
23
 
3.9%
21
 
3.6%
18
 
3.1%
15
 
2.6%
14
 
2.4%
14
 
2.4%
14
 
2.4%
13
 
2.2%
Other values (125) 376
64.1%
Common
ValueCountFrequency (%)
88
59.5%
, 60
40.5%
Latin
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 587
79.6%
ASCII 150
 
20.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
58.7%
, 60
40.0%
I 1
 
0.7%
C 1
 
0.7%
Hangul
ValueCountFrequency (%)
53
 
9.0%
26
 
4.4%
23
 
3.9%
21
 
3.6%
18
 
3.1%
15
 
2.6%
14
 
2.4%
14
 
2.4%
14
 
2.4%
13
 
2.2%
Other values (125) 376
64.1%

노선연장
Real number (ℝ)

ZEROS 

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56013.822
Minimum0
Maximum186270
Zeros2
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:34.280259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile804.053
Q128034.75
median44733.5
Q371201
95-th percentile150416.3
Maximum186270
Range186270
Interquartile range (IQR)43166.25

Descriptive statistics

Standard deviation44729.888
Coefficient of variation (CV)0.79855091
Kurtosis1.1308272
Mean56013.822
Median Absolute Deviation (MAD)20109.5
Skewness1.1913971
Sum2464608.2
Variance2.0007629 × 109
MonotonicityNot monotonic
2023-12-11T07:57:34.385749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 2
 
4.5%
37251.0 1
 
2.3%
70828.0 1
 
2.3%
49131.0 1
 
2.3%
154070.0 1
 
2.3%
62660.0 1
 
2.3%
25405.0 1
 
2.3%
794.18 1
 
2.3%
79002.0 1
 
2.3%
860.0 1
 
2.3%
Other values (33) 33
75.0%
ValueCountFrequency (%)
0.0 2
4.5%
794.18 1
2.3%
860.0 1
2.3%
2400.0 1
2.3%
5000.0 1
2.3%
20620.0 1
2.3%
23854.0 1
2.3%
25394.0 1
2.3%
25405.0 1
2.3%
25856.0 1
2.3%
ValueCountFrequency (%)
186270.0 1
2.3%
161810.0 1
2.3%
154070.0 1
2.3%
129712.0 1
2.3%
126380.0 1
2.3%
124333.0 1
2.3%
109041.0 1
2.3%
82972.0 1
2.3%
82440.0 1
2.3%
79002.0 1
2.3%

전용연장
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40105.459
Minimum0
Maximum99800
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:34.495649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile119.127
Q123765.5
median38224
Q355681
95-th percentile95172.3
Maximum99800
Range99800
Interquartile range (IQR)31915.5

Descriptive statistics

Standard deviation27273.39
Coefficient of variation (CV)0.68004185
Kurtosis-0.20893521
Mean40105.459
Median Absolute Deviation (MAD)15883.5
Skewness0.48735316
Sum1764640.2
Variance7.4383781 × 108
MonotonicityNot monotonic
2023-12-11T07:57:34.609975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 3
 
6.8%
29031.0 1
 
2.3%
19920.0 1
 
2.3%
47404.0 1
 
2.3%
37870.0 1
 
2.3%
57460.0 1
 
2.3%
24205.0 1
 
2.3%
794.18 1
 
2.3%
69502.0 1
 
2.3%
860.0 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
0.0 3
6.8%
794.18 1
 
2.3%
860.0 1
 
2.3%
2400.0 1
 
2.3%
5000.0 1
 
2.3%
18707.0 1
 
2.3%
19920.0 1
 
2.3%
20620.0 1
 
2.3%
23500.0 1
 
2.3%
23854.0 1
 
2.3%
ValueCountFrequency (%)
99800.0 1
2.3%
97520.0 1
2.3%
95283.0 1
2.3%
94545.0 1
2.3%
72220.0 1
2.3%
69502.0 1
2.3%
69372.0 1
2.3%
66870.0 1
2.3%
63452.0 1
2.3%
60310.0 1
2.3%

중용연장
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)86.8%
Missing6
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean10597.711
Minimum0
Maximum69420
Zeros5
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:34.712530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11300
median4580
Q310040
95-th percentile53501.5
Maximum69420
Range69420
Interquartile range (IQR)8740

Descriptive statistics

Standard deviation16710.114
Coefficient of variation (CV)1.5767664
Kurtosis5.8242869
Mean10597.711
Median Absolute Deviation (MAD)4250
Skewness2.4879866
Sum402713
Variance2.792279 × 108
MonotonicityNot monotonic
2023-12-11T07:57:34.818336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 5
 
11.4%
9500 2
 
4.5%
6400 1
 
2.3%
6600 1
 
2.3%
1727 1
 
2.3%
52000 1
 
2.3%
1200 1
 
2.3%
5450 1
 
2.3%
498 1
 
2.3%
1000 1
 
2.3%
Other values (23) 23
52.3%
(Missing) 6
 
13.6%
ValueCountFrequency (%)
0 5
11.4%
110 1
 
2.3%
300 1
 
2.3%
498 1
 
2.3%
1000 1
 
2.3%
1200 1
 
2.3%
1600 1
 
2.3%
1727 1
 
2.3%
1960 1
 
2.3%
2500 1
 
2.3%
ValueCountFrequency (%)
69420 1
2.3%
62010 1
2.3%
52000 1
2.3%
29050 1
2.3%
28860 1
2.3%
15740 1
2.3%
15600 1
2.3%
14496 1
2.3%
13600 1
2.3%
10220 1
2.3%

통행불능연장
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4391.8182
Minimum0
Maximum21400
Zeros20
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:34.983489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1780
Q38075
95-th percentile14276.1
Maximum21400
Range21400
Interquartile range (IQR)8075

Descriptive statistics

Standard deviation5572.3482
Coefficient of variation (CV)1.2688021
Kurtosis0.97525605
Mean4391.8182
Median Absolute Deviation (MAD)1780
Skewness1.2407859
Sum193240
Variance31051064
MonotonicityNot monotonic
2023-12-11T07:57:35.187097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 20
45.5%
2400 2
 
4.5%
8000 1
 
2.3%
2656 1
 
2.3%
14286 1
 
2.3%
21400 1
 
2.3%
6463 1
 
2.3%
8300 1
 
2.3%
10038 1
 
2.3%
8420 1
 
2.3%
Other values (14) 14
31.8%
ValueCountFrequency (%)
0 20
45.5%
700 1
 
2.3%
1160 1
 
2.3%
2400 2
 
4.5%
2656 1
 
2.3%
2708 1
 
2.3%
4399 1
 
2.3%
5580 1
 
2.3%
6463 1
 
2.3%
6600 1
 
2.3%
ValueCountFrequency (%)
21400 1
2.3%
17850 1
2.3%
14286 1
2.3%
14220 1
2.3%
12500 1
2.3%
10038 1
2.3%
10000 1
2.3%
9270 1
2.3%
8500 1
2.3%
8420 1
2.3%

포장도로_전체연장
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35895.459
Minimum0
Maximum98640
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:35.335007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile119.127
Q119016.75
median32108
Q351562
95-th percentile93039.1
Maximum98640
Range98640
Interquartile range (IQR)32545.25

Descriptive statistics

Standard deviation26571.676
Coefficient of variation (CV)0.74025175
Kurtosis0.17828497
Mean35895.459
Median Absolute Deviation (MAD)16647
Skewness0.7770455
Sum1579400.2
Variance7.0605397 × 108
MonotonicityNot monotonic
2023-12-11T07:57:35.468470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 3
 
6.8%
29031.0 1
 
2.3%
19920.0 1
 
2.3%
33184.0 1
 
2.3%
20020.0 1
 
2.3%
49040.0 1
 
2.3%
24205.0 1
 
2.3%
794.18 1
 
2.3%
59464.0 1
 
2.3%
860.0 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
0.0 3
6.8%
794.18 1
 
2.3%
860.0 1
 
2.3%
2400.0 1
 
2.3%
5000.0 1
 
2.3%
11361.0 1
 
2.3%
15746.0 1
 
2.3%
15824.0 1
 
2.3%
16307.0 1
 
2.3%
19920.0 1
 
2.3%
ValueCountFrequency (%)
98640.0 1
2.3%
94545.0 1
2.3%
93121.0 1
2.3%
92575.0 1
2.3%
72220.0 1
2.3%
66870.0 1
2.3%
61572.0 1
2.3%
59464.0 1
2.3%
52688.0 1
2.3%
51810.0 1
2.3%

포장도로_도로연장
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34939.996
Minimum0
Maximum98239.18
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:35.609470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile119.127
Q115410.875
median31483.7
Q350892.675
95-th percentile92617.2
Maximum98239.18
Range98239.18
Interquartile range (IQR)35481.8

Descriptive statistics

Standard deviation26705.898
Coefficient of variation (CV)0.76433603
Kurtosis0.14172547
Mean34939.996
Median Absolute Deviation (MAD)17842.15
Skewness0.79101831
Sum1537359.8
Variance7.1320498 × 108
MonotonicityNot monotonic
2023-12-11T07:57:35.736608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 3
 
6.8%
27850.4 1
 
2.3%
19886.0 1
 
2.3%
32827.0 1
 
2.3%
17446.0 1
 
2.3%
48353.62 1
 
2.3%
12122.0 1
 
2.3%
794.18 1
 
2.3%
58482.0 1
 
2.3%
860.0 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
0.0 3
6.8%
794.18 1
 
2.3%
860.0 1
 
2.3%
2120.0 1
 
2.3%
2653.0 1
 
2.3%
11047.0 1
 
2.3%
12122.0 1
 
2.3%
13225.0 1
 
2.3%
15356.5 1
 
2.3%
15429.0 1
 
2.3%
ValueCountFrequency (%)
98239.18 1
2.3%
94260.0 1
2.3%
92970.0 1
2.3%
90618.0 1
2.3%
71396.0 1
2.3%
66007.55 1
2.3%
60666.0 1
2.3%
58482.0 1
2.3%
52208.0 1
2.3%
51335.0 1
2.3%

포장도로_터널개소(2차로)
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
40 
1
 
3
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row2
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 40
90.9%
1 3
 
6.8%
2 1
 
2.3%

Length

2023-12-11T07:57:35.854237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:35.955975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40
90.9%
1 3
 
6.8%
2 1
 
2.3%

포장도로_터널연장(2차로)
Categorical

IMBALANCE 

Distinct4
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
41 
2463
 
1
330
 
1
339
 
1

Length

Max length4
Median length1
Mean length1.1590909
Min length1

Unique

Unique3 ?
Unique (%)6.8%

Sample

1st row0
2nd row0
3rd row2463
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 41
93.2%
2463 1
 
2.3%
330 1
 
2.3%
339 1
 
2.3%

Length

2023-12-11T07:57:36.057348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:36.189165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 41
93.2%
2463 1
 
2.3%
330 1
 
2.3%
339 1
 
2.3%
Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2023-12-11T07:57:36.298774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:36.387882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%
Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2023-12-11T07:57:36.482644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:36.610134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%

포장도로_터널개소(4차로)
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
1 1
 
2.3%

Length

2023-12-11T07:57:36.716512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:36.815957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
1 1
 
2.3%

포장도로_터널연장(4차로)
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
42 
2122
 
1
2346
 
1

Length

Max length4
Median length1
Mean length1.1363636
Min length1

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 42
95.5%
2122 1
 
2.3%
2346 1
 
2.3%

Length

2023-12-11T07:57:36.969141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:37.088981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42
95.5%
2122 1
 
2.3%
2346 1
 
2.3%
Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2023-12-11T07:57:37.202903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:37.292789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%
Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2023-12-11T07:57:37.378204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:37.474267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%

포장도로_터널개소(전체)
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
39 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row2
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 39
88.6%
1 4
 
9.1%
2 1
 
2.3%

Length

2023-12-11T07:57:37.571154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:37.677468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 39
88.6%
1 4
 
9.1%
2 1
 
2.3%

포장도로_터널연장(전체)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172.72727
Minimum0
Maximum2463
Zeros39
Zeros (%)88.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:37.793931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1854.55
Maximum2463
Range2463
Interquartile range (IQR)0

Descriptive statistics

Standard deviation590.31058
Coefficient of variation (CV)3.4175875
Kurtosis10.937295
Mean172.72727
Median Absolute Deviation (MAD)0
Skewness3.4929894
Sum7600
Variance348466.58
MonotonicityNot monotonic
2023-12-11T07:57:37.894991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 39
88.6%
2463 1
 
2.3%
2122 1
 
2.3%
330 1
 
2.3%
2346 1
 
2.3%
339 1
 
2.3%
ValueCountFrequency (%)
0 39
88.6%
330 1
 
2.3%
339 1
 
2.3%
2122 1
 
2.3%
2346 1
 
2.3%
2463 1
 
2.3%
ValueCountFrequency (%)
2463 1
 
2.3%
2346 1
 
2.3%
2122 1
 
2.3%
339 1
 
2.3%
330 1
 
2.3%
0 39
88.6%

포장도로_교량개소(강교)
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
36 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 36
81.8%
1 7
 
15.9%
2 1
 
2.3%

Length

2023-12-11T07:57:38.015845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:38.109596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
81.8%
1 7
 
15.9%
2 1
 
2.3%

포장도로_교량연장(강교)
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.545455
Minimum0
Maximum2145
Zeros36
Zeros (%)81.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:38.198994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile262.6
Maximum2145
Range2145
Interquartile range (IQR)0

Descriptive statistics

Standard deviation328.76955
Coefficient of variation (CV)4.5319111
Kurtosis39.033636
Mean72.545455
Median Absolute Deviation (MAD)0
Skewness6.1237097
Sum3192
Variance108089.42
MonotonicityNot monotonic
2023-12-11T07:57:38.586277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 36
81.8%
60 1
 
2.3%
55 1
 
2.3%
8 1
 
2.3%
400 1
 
2.3%
80 1
 
2.3%
164 1
 
2.3%
2145 1
 
2.3%
280 1
 
2.3%
ValueCountFrequency (%)
0 36
81.8%
8 1
 
2.3%
55 1
 
2.3%
60 1
 
2.3%
80 1
 
2.3%
164 1
 
2.3%
280 1
 
2.3%
400 1
 
2.3%
2145 1
 
2.3%
ValueCountFrequency (%)
2145 1
 
2.3%
400 1
 
2.3%
280 1
 
2.3%
164 1
 
2.3%
80 1
 
2.3%
60 1
 
2.3%
55 1
 
2.3%
8 1
 
2.3%
0 36
81.8%
Distinct19
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.6818182
Minimum0
Maximum33
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:38.683062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q14.75
median8
Q312.25
95-th percentile21.7
Maximum33
Range33
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation7.053855
Coefficient of variation (CV)0.72856719
Kurtosis1.4773645
Mean9.6818182
Median Absolute Deviation (MAD)4
Skewness1.0613402
Sum426
Variance49.756871
MonotonicityNot monotonic
2023-12-11T07:57:38.784138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
8 5
11.4%
2 4
 
9.1%
12 4
 
9.1%
7 4
 
9.1%
0 3
 
6.8%
4 3
 
6.8%
10 3
 
6.8%
11 2
 
4.5%
17 2
 
4.5%
5 2
 
4.5%
Other values (9) 12
27.3%
ValueCountFrequency (%)
0 3
6.8%
2 4
9.1%
3 1
 
2.3%
4 3
6.8%
5 2
 
4.5%
6 2
 
4.5%
7 4
9.1%
8 5
11.4%
10 3
6.8%
11 2
 
4.5%
ValueCountFrequency (%)
33 1
 
2.3%
23 1
 
2.3%
22 1
 
2.3%
20 2
4.5%
19 1
 
2.3%
17 2
4.5%
16 1
 
2.3%
13 2
4.5%
12 4
9.1%
11 2
4.5%
Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean573.47727
Minimum0
Maximum2428
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:38.894293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.1
Q1227.25
median405.5
Q3829.25
95-th percentile1280.2
Maximum2428
Range2428
Interquartile range (IQR)602

Descriptive statistics

Standard deviation512.5163
Coefficient of variation (CV)0.8936994
Kurtosis3.3825505
Mean573.47727
Median Absolute Deviation (MAD)282.5
Skewness1.5980457
Sum25233
Variance262672.95
MonotonicityNot monotonic
2023-12-11T07:57:39.015357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 3
 
6.8%
1181 1
 
2.3%
862 1
 
2.3%
357 1
 
2.3%
99 1
 
2.3%
686 1
 
2.3%
1138 1
 
2.3%
212 1
 
2.3%
982 1
 
2.3%
928 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
0 3
6.8%
34 1
 
2.3%
63 1
 
2.3%
76 1
 
2.3%
99 1
 
2.3%
151 1
 
2.3%
183 1
 
2.3%
212 1
 
2.3%
225 1
 
2.3%
228 1
 
2.3%
ValueCountFrequency (%)
2428 1
2.3%
1957 1
2.3%
1294 1
2.3%
1202 1
2.3%
1181 1
2.3%
1138 1
2.3%
1099 1
2.3%
982 1
2.3%
928 1
2.3%
862 1
2.3%
Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
1 1
 
2.3%

Length

2023-12-11T07:57:39.123553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:39.215073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
1 1
 
2.3%
Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
72
 
1

Length

Max length2
Median length1
Mean length1.0227273
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
72 1
 
2.3%

Length

2023-12-11T07:57:39.295935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:39.375808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
72 1
 
2.3%

포장도로_교량개소(기타)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90909091
Minimum0
Maximum18
Zeros37
Zeros (%)84.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:39.443306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.55
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1829355
Coefficient of variation (CV)3.501229
Kurtosis20.973381
Mean0.90909091
Median Absolute Deviation (MAD)0
Skewness4.4250177
Sum40
Variance10.131078
MonotonicityNot monotonic
2023-12-11T07:57:39.528496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 37
84.1%
1 3
 
6.8%
10 1
 
2.3%
6 1
 
2.3%
3 1
 
2.3%
18 1
 
2.3%
ValueCountFrequency (%)
0 37
84.1%
1 3
 
6.8%
3 1
 
2.3%
6 1
 
2.3%
10 1
 
2.3%
18 1
 
2.3%
ValueCountFrequency (%)
18 1
 
2.3%
10 1
 
2.3%
6 1
 
2.3%
3 1
 
2.3%
1 3
 
6.8%
0 37
84.1%

포장도로_교량연장(기타)
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.034091
Minimum0
Maximum608.5
Zeros37
Zeros (%)84.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:39.614695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile218.35
Maximum608.5
Range608.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation104.33624
Coefficient of variation (CV)3.593577
Kurtosis23.307463
Mean29.034091
Median Absolute Deviation (MAD)0
Skewness4.6206404
Sum1277.5
Variance10886.051
MonotonicityNot monotonic
2023-12-11T07:57:39.693794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 37
84.1%
63.0 1
 
2.3%
244.0 1
 
2.3%
256.0 1
 
2.3%
73.0 1
 
2.3%
608.5 1
 
2.3%
15.0 1
 
2.3%
18.0 1
 
2.3%
ValueCountFrequency (%)
0.0 37
84.1%
15.0 1
 
2.3%
18.0 1
 
2.3%
63.0 1
 
2.3%
73.0 1
 
2.3%
244.0 1
 
2.3%
256.0 1
 
2.3%
608.5 1
 
2.3%
ValueCountFrequency (%)
608.5 1
 
2.3%
256.0 1
 
2.3%
244.0 1
 
2.3%
73.0 1
 
2.3%
63.0 1
 
2.3%
18.0 1
 
2.3%
15.0 1
 
2.3%
0.0 37
84.1%

포장도로_교량개소(전체)
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9318182
Minimum0
Maximum33
Zeros2
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:39.802582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.15
Q15
median8.5
Q312.25
95-th percentile21.7
Maximum33
Range33
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation6.9328934
Coefficient of variation (CV)0.69804876
Kurtosis1.5507986
Mean9.9318182
Median Absolute Deviation (MAD)3.5
Skewness1.0738587
Sum437
Variance48.065011
MonotonicityNot monotonic
2023-12-11T07:57:39.907563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
8 4
 
9.1%
12 4
 
9.1%
6 3
 
6.8%
4 3
 
6.8%
10 3
 
6.8%
7 3
 
6.8%
0 2
 
4.5%
2 2
 
4.5%
20 2
 
4.5%
11 2
 
4.5%
Other values (12) 16
36.4%
ValueCountFrequency (%)
0 2
4.5%
1 1
 
2.3%
2 2
4.5%
3 2
4.5%
4 3
6.8%
5 2
4.5%
6 3
6.8%
7 3
6.8%
8 4
9.1%
9 2
4.5%
ValueCountFrequency (%)
33 1
 
2.3%
23 1
 
2.3%
22 1
 
2.3%
20 2
4.5%
19 1
 
2.3%
17 2
4.5%
16 1
 
2.3%
15 1
 
2.3%
13 1
 
2.3%
12 4
9.1%

포장도로_교량연장(전체)
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean641.9
Minimum0
Maximum2428
Zeros2
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:40.030555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile38.35
Q1255.275
median444.8
Q3876.75
95-th percentile1857.5725
Maximum2428
Range2428
Interquartile range (IQR)621.475

Descriptive statistics

Standard deviation561.09631
Coefficient of variation (CV)0.87411795
Kurtosis2.5238189
Mean641.9
Median Absolute Deviation (MAD)255.05
Skewness1.5342642
Sum28243.6
Variance314829.07
MonotonicityNot monotonic
2023-12-11T07:57:40.135793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 2
 
4.5%
280.0 2
 
4.5%
1180.6 1
 
2.3%
682.45 1
 
2.3%
357.0 1
 
2.3%
2244.0 1
 
2.3%
686.38 1
 
2.3%
1138.0 1
 
2.3%
212.0 1
 
2.3%
982.0 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
0.0 2
4.5%
34.0 1
2.3%
63.0 1
2.3%
136.0 1
2.3%
151.0 1
2.3%
182.9 1
2.3%
212.0 1
2.3%
225.0 1
2.3%
228.0 1
2.3%
251.0 1
2.3%
ValueCountFrequency (%)
2428.0 1
2.3%
2244.0 1
2.3%
1957.0 1
2.3%
1294.15 1
2.3%
1202.2 1
2.3%
1180.6 1
2.3%
1179.0 1
2.3%
1138.0 1
2.3%
982.0 1
2.3%
928.0 1
2.3%

비포장도로연장
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
1600
 
1

Length

Max length4
Median length1
Mean length1.0681818
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
1600 1
 
2.3%

Length

2023-12-11T07:57:40.239162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:40.324633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
1600 1
 
2.3%

미개통도로연장
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4651.7273
Minimum0
Maximum21400
Zeros18
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:40.406516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2528
Q38075
95-th percentile14276.1
Maximum21400
Range21400
Interquartile range (IQR)8075

Descriptive statistics

Standard deviation5492.6795
Coefficient of variation (CV)1.1807828
Kurtosis0.94341552
Mean4651.7273
Median Absolute Deviation (MAD)2528
Skewness1.1724365
Sum204676
Variance30169528
MonotonicityNot monotonic
2023-12-11T07:57:40.502915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 18
40.9%
2400 2
 
4.5%
8500 1
 
2.3%
2656 1
 
2.3%
14286 1
 
2.3%
21400 1
 
2.3%
6463 1
 
2.3%
8300 1
 
2.3%
5432 1
 
2.3%
10038 1
 
2.3%
Other values (16) 16
36.4%
ValueCountFrequency (%)
0 18
40.9%
700 1
 
2.3%
1164 1
 
2.3%
2400 2
 
4.5%
2656 1
 
2.3%
2708 1
 
2.3%
4399 1
 
2.3%
5432 1
 
2.3%
5580 1
 
2.3%
6000 1
 
2.3%
ValueCountFrequency (%)
21400 1
2.3%
17850 1
2.3%
14286 1
2.3%
14220 1
2.3%
12500 1
2.3%
10038 1
2.3%
10000 1
2.3%
9270 1
2.3%
8500 1
2.3%
8420 1
2.3%

폭원_전체
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.281818
Minimum0
Maximum35
Zeros5
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:40.611430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median8.75
Q310.025
95-th percentile20
Maximum35
Range35
Interquartile range (IQR)2.025

Descriptive statistics

Standard deviation6.8913249
Coefficient of variation (CV)0.6702438
Kurtosis2.9068646
Mean10.281818
Median Absolute Deviation (MAD)0.75
Skewness1.2838475
Sum452.4
Variance47.490359
MonotonicityNot monotonic
2023-12-11T07:57:40.725868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
8.0 12
27.3%
9.0 9
20.5%
0.0 5
11.4%
19.0 3
 
6.8%
8.5 2
 
4.5%
20.0 2
 
4.5%
35.0 1
 
2.3%
7.0 1
 
2.3%
9.6 1
 
2.3%
14.0 1
 
2.3%
Other values (7) 7
15.9%
ValueCountFrequency (%)
0.0 5
11.4%
5.0 1
 
2.3%
7.0 1
 
2.3%
8.0 12
27.3%
8.2 1
 
2.3%
8.5 2
 
4.5%
9.0 9
20.5%
9.5 1
 
2.3%
9.6 1
 
2.3%
11.3 1
 
2.3%
ValueCountFrequency (%)
35.0 1
 
2.3%
24.5 1
 
2.3%
20.0 2
4.5%
19.3 1
 
2.3%
19.0 3
6.8%
18.0 1
 
2.3%
14.0 1
 
2.3%
11.3 1
 
2.3%
9.6 1
 
2.3%
9.5 1
 
2.3%

폭원_차도
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.35
Minimum0
Maximum19.5
Zeros6
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:40.856307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median6.55
Q37.625
95-th percentile15.35
Maximum19.5
Range19.5
Interquartile range (IQR)1.625

Descriptive statistics

Standard deviation4.6557541
Coefficient of variation (CV)0.63343594
Kurtosis0.42638163
Mean7.35
Median Absolute Deviation (MAD)0.55
Skewness0.6059114
Sum323.4
Variance21.676047
MonotonicityNot monotonic
2023-12-11T07:57:40.984064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
6.0 11
25.0%
7.0 8
18.2%
0.0 6
13.6%
14.0 4
 
9.1%
6.5 3
 
6.8%
8.0 2
 
4.5%
15.5 1
 
2.3%
5.5 1
 
2.3%
14.5 1
 
2.3%
17.0 1
 
2.3%
Other values (6) 6
13.6%
ValueCountFrequency (%)
0.0 6
13.6%
4.0 1
 
2.3%
5.5 1
 
2.3%
6.0 11
25.0%
6.5 3
 
6.8%
6.6 1
 
2.3%
6.7 1
 
2.3%
7.0 8
18.2%
7.5 1
 
2.3%
8.0 2
 
4.5%
ValueCountFrequency (%)
19.5 1
 
2.3%
17.0 1
 
2.3%
15.5 1
 
2.3%
14.5 1
 
2.3%
14.0 4
9.1%
13.1 1
 
2.3%
8.0 2
 
4.5%
7.5 1
 
2.3%
7.0 8
18.2%
6.7 1
 
2.3%

폭원_중앙분리대
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
0.0
40 
1.0
 
3
3.5
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 40
90.9%
1.0 3
 
6.8%
3.5 1
 
2.3%

Length

2023-12-11T07:57:41.103252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:41.196840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 40
90.9%
1.0 3
 
6.8%
3.5 1
 
2.3%

폭원_길어깨(보도)
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5
Minimum0
Maximum12
Zeros6
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:41.282735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.9
median2
Q32.625
95-th percentile5.455
Maximum12
Range12
Interquartile range (IQR)0.725

Descriptive statistics

Standard deviation2.2168488
Coefficient of variation (CV)0.88673952
Kurtosis8.2360433
Mean2.5
Median Absolute Deviation (MAD)0.4
Skewness2.4565253
Sum110
Variance4.9144186
MonotonicityNot monotonic
2023-12-11T07:57:41.406840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2.0 21
47.7%
0.0 6
 
13.6%
4.0 4
 
9.1%
1.6 2
 
4.5%
1.5 2
 
4.5%
3.0 2
 
4.5%
1.0 1
 
2.3%
4.6 1
 
2.3%
5.2 1
 
2.3%
2.5 1
 
2.3%
Other values (3) 3
 
6.8%
ValueCountFrequency (%)
0.0 6
 
13.6%
1.0 1
 
2.3%
1.5 2
 
4.5%
1.6 2
 
4.5%
2.0 21
47.7%
2.5 1
 
2.3%
3.0 2
 
4.5%
4.0 4
 
9.1%
4.6 1
 
2.3%
5.2 1
 
2.3%
ValueCountFrequency (%)
12.0 1
 
2.3%
9.0 1
 
2.3%
5.5 1
 
2.3%
5.2 1
 
2.3%
4.6 1
 
2.3%
4.0 4
 
9.1%
3.0 2
 
4.5%
2.5 1
 
2.3%
2.0 21
47.7%
1.6 2
 
4.5%

포장두께_전체
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.056818
Minimum0
Maximum90
Zeros6
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:41.504862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q144.375
median45
Q350
95-th percentile62.55
Maximum90
Range90
Interquartile range (IQR)5.625

Descriptive statistics

Standard deviation19.639251
Coefficient of variation (CV)0.45612407
Kurtosis1.5533943
Mean43.056818
Median Absolute Deviation (MAD)5
Skewness-1.0374524
Sum1894.5
Variance385.70018
MonotonicityNot monotonic
2023-12-11T07:57:41.593929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
45.0 15
34.1%
50.0 8
18.2%
0.0 6
 
13.6%
55.0 3
 
6.8%
60.0 3
 
6.8%
40.0 2
 
4.5%
35.0 2
 
4.5%
42.5 1
 
2.3%
90.0 1
 
2.3%
70.0 1
 
2.3%
Other values (2) 2
 
4.5%
ValueCountFrequency (%)
0.0 6
 
13.6%
35.0 2
 
4.5%
40.0 2
 
4.5%
42.5 1
 
2.3%
45.0 15
34.1%
50.0 8
18.2%
55.0 3
 
6.8%
59.0 1
 
2.3%
60.0 3
 
6.8%
63.0 1
 
2.3%
ValueCountFrequency (%)
90.0 1
 
2.3%
70.0 1
 
2.3%
63.0 1
 
2.3%
60.0 3
 
6.8%
59.0 1
 
2.3%
55.0 3
 
6.8%
50.0 8
18.2%
45.0 15
34.1%
42.5 1
 
2.3%
40.0 2
 
4.5%
Distinct10
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.920455
Minimum0
Maximum40
Zeros7
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:41.684903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median17.5
Q320
95-th percentile24.85
Maximum40
Range40
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.6930493
Coefficient of variation (CV)0.58262631
Kurtosis0.5509681
Mean14.920455
Median Absolute Deviation (MAD)2.5
Skewness-0.18352963
Sum656.5
Variance75.569107
MonotonicityNot monotonic
2023-12-11T07:57:41.787637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
20.0 18
40.9%
15.0 8
18.2%
0.0 7
 
15.9%
5.0 2
 
4.5%
25.0 2
 
4.5%
12.5 2
 
4.5%
10.0 2
 
4.5%
40.0 1
 
2.3%
24.0 1
 
2.3%
7.5 1
 
2.3%
ValueCountFrequency (%)
0.0 7
 
15.9%
5.0 2
 
4.5%
7.5 1
 
2.3%
10.0 2
 
4.5%
12.5 2
 
4.5%
15.0 8
18.2%
20.0 18
40.9%
24.0 1
 
2.3%
25.0 2
 
4.5%
40.0 1
 
2.3%
ValueCountFrequency (%)
40.0 1
 
2.3%
25.0 2
 
4.5%
24.0 1
 
2.3%
20.0 18
40.9%
15.0 8
18.2%
12.5 2
 
4.5%
10.0 2
 
4.5%
7.5 1
 
2.3%
5.0 2
 
4.5%
0.0 7
 
15.9%

포장두께_보조기층
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.795455
Minimum0
Maximum50
Zeros7
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:41.900492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q125
median25
Q335
95-th percentile42.125
Maximum50
Range50
Interquartile range (IQR)10

Descriptive statistics

Standard deviation13.302963
Coefficient of variation (CV)0.51570957
Kurtosis0.23976753
Mean25.795455
Median Absolute Deviation (MAD)5
Skewness-0.74763901
Sum1135
Variance176.96882
MonotonicityNot monotonic
2023-12-11T07:57:42.002264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
25.0 13
29.5%
30.0 8
18.2%
0.0 7
15.9%
35.0 6
13.6%
40.0 3
 
6.8%
20.0 3
 
6.8%
50.0 2
 
4.5%
42.5 1
 
2.3%
37.5 1
 
2.3%
ValueCountFrequency (%)
0.0 7
15.9%
20.0 3
 
6.8%
25.0 13
29.5%
30.0 8
18.2%
35.0 6
13.6%
37.5 1
 
2.3%
40.0 3
 
6.8%
42.5 1
 
2.3%
50.0 2
 
4.5%
ValueCountFrequency (%)
50.0 2
 
4.5%
42.5 1
 
2.3%
40.0 3
 
6.8%
37.5 1
 
2.3%
35.0 6
13.6%
30.0 8
18.2%
25.0 13
29.5%
20.0 3
 
6.8%
0.0 7
15.9%

도로연장(2차로미만)
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3080.6114
Minimum0
Maximum29743.9
Zeros27
Zeros (%)61.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:42.145220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32275.25
95-th percentile20177.2
Maximum29743.9
Range29743.9
Interquartile range (IQR)2275.25

Descriptive statistics

Standard deviation6836.1611
Coefficient of variation (CV)2.2190923
Kurtosis6.6075259
Mean3080.6114
Median Absolute Deviation (MAD)0
Skewness2.6676475
Sum135546.9
Variance46733098
MonotonicityNot monotonic
2023-12-11T07:57:42.250723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 27
61.4%
6920.0 1
 
2.3%
2252.0 1
 
2.3%
1700.0 1
 
2.3%
2992.0 1
 
2.3%
2723.0 1
 
2.3%
316.0 1
 
2.3%
1300.0 1
 
2.3%
16019.0 1
 
2.3%
29743.9 1
 
2.3%
Other values (8) 8
 
18.2%
ValueCountFrequency (%)
0.0 27
61.4%
270.0 1
 
2.3%
316.0 1
 
2.3%
1300.0 1
 
2.3%
1580.0 1
 
2.3%
1700.0 1
 
2.3%
2252.0 1
 
2.3%
2345.0 1
 
2.3%
2723.0 1
 
2.3%
2992.0 1
 
2.3%
ValueCountFrequency (%)
29743.9 1
2.3%
22830.0 1
2.3%
20911.0 1
2.3%
16019.0 1
2.3%
13787.0 1
2.3%
6920.0 1
2.3%
6740.0 1
2.3%
3118.0 1
2.3%
2992.0 1
2.3%
2723.0 1
2.3%

도로연장(2차로_4차로미만)
Real number (ℝ)

ZEROS 

Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32606.744
Minimum0
Maximum93121
Zeros4
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:42.404236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115782.75
median30323.5
Q345261.007
95-th percentile85544.4
Maximum93121
Range93121
Interquartile range (IQR)29478.257

Descriptive statistics

Standard deviation25801.698
Coefficient of variation (CV)0.79129943
Kurtosis0.076306881
Mean32606.744
Median Absolute Deviation (MAD)14553
Skewness0.83135866
Sum1434696.7
Variance6.6572761 × 108
MonotonicityNot monotonic
2023-12-11T07:57:42.527483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.0 4
 
9.1%
15795.0 1
 
2.3%
19931.0 1
 
2.3%
33184.0 1
 
2.3%
44710.01 1
 
2.3%
23.0 1
 
2.3%
794.18 1
 
2.3%
19082.0 1
 
2.3%
25814.0 1
 
2.3%
63705.0 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
0.0 4
9.1%
23.0 1
 
2.3%
794.18 1
 
2.3%
2400.0 1
 
2.3%
9892.36 1
 
2.3%
10400.0 1
 
2.3%
11361.0 1
 
2.3%
15746.0 1
 
2.3%
15795.0 1
 
2.3%
15824.0 1
 
2.3%
ValueCountFrequency (%)
93121.0 1
2.3%
92575.0 1
2.3%
86847.0 1
2.3%
78163.0 1
2.3%
77104.0 1
2.3%
64959.19 1
2.3%
63705.0 1
2.3%
58684.0 1
2.3%
52688.0 1
2.3%
48759.0 1
2.3%

도로연장(4차로_6차로미만)
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2539.7909
Minimum0
Maximum20872
Zeros26
Zeros (%)59.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:42.672136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31518.25
95-th percentile13215.6
Maximum20872
Range20872
Interquartile range (IQR)1518.25

Descriptive statistics

Standard deviation5038.5321
Coefficient of variation (CV)1.9838374
Kurtosis3.9038555
Mean2539.7909
Median Absolute Deviation (MAD)0
Skewness2.1492024
Sum111750.8
Variance25386806
MonotonicityNot monotonic
2023-12-11T07:57:42.807841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 26
59.1%
13236.0 1
 
2.3%
1025.0 1
 
2.3%
609.0 1
 
2.3%
2149.0 1
 
2.3%
500.0 1
 
2.3%
12474.0 1
 
2.3%
20872.0 1
 
2.3%
74.0 1
 
2.3%
10900.0 1
 
2.3%
Other values (9) 9
 
20.5%
ValueCountFrequency (%)
0.0 26
59.1%
74.0 1
 
2.3%
495.0 1
 
2.3%
500.0 1
 
2.3%
590.0 1
 
2.3%
609.0 1
 
2.3%
1025.0 1
 
2.3%
1308.0 1
 
2.3%
2149.0 1
 
2.3%
3115.0 1
 
2.3%
ValueCountFrequency (%)
20872.0 1
2.3%
13892.0 1
2.3%
13236.0 1
2.3%
13100.0 1
2.3%
12474.0 1
2.3%
10900.0 1
2.3%
7831.8 1
2.3%
5000.0 1
2.3%
4580.0 1
2.3%
3115.0 1
2.3%

도로연장(6차로이상)
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1080.8795
Minimum0
Maximum31551
Zeros36
Zeros (%)81.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:42.937311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4959.395
Maximum31551
Range31551
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4865.2234
Coefficient of variation (CV)4.5011708
Kurtosis37.951311
Mean1080.8795
Median Absolute Deviation (MAD)0
Skewness6.0104207
Sum47558.7
Variance23670399
MonotonicityNot monotonic
2023-12-11T07:57:43.069755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 36
81.8%
32.0 1
 
2.3%
40.0 1
 
2.3%
31551.0 1
 
2.3%
30.0 1
 
2.3%
5038.7 1
 
2.3%
1200.0 1
 
2.3%
4510.0 1
 
2.3%
5157.0 1
 
2.3%
ValueCountFrequency (%)
0.0 36
81.8%
30.0 1
 
2.3%
32.0 1
 
2.3%
40.0 1
 
2.3%
1200.0 1
 
2.3%
4510.0 1
 
2.3%
5038.7 1
 
2.3%
5157.0 1
 
2.3%
31551.0 1
 
2.3%
ValueCountFrequency (%)
31551.0 1
 
2.3%
5157.0 1
 
2.3%
5038.7 1
 
2.3%
4510.0 1
 
2.3%
1200.0 1
 
2.3%
40.0 1
 
2.3%
32.0 1
 
2.3%
30.0 1
 
2.3%
0.0 36
81.8%

차도 연장_전체(상행)
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36081.413
Minimum0
Maximum98640
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:43.223809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile119.127
Q119016.75
median32608
Q351562
95-th percentile93039.1
Maximum98640
Range98640
Interquartile range (IQR)32545.25

Descriptive statistics

Standard deviation26488.743
Coefficient of variation (CV)0.73413819
Kurtosis0.19378761
Mean36081.413
Median Absolute Deviation (MAD)16671
Skewness0.76690717
Sum1587582.2
Variance7.0165353 × 108
MonotonicityNot monotonic
2023-12-11T07:57:43.367956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 3
 
6.8%
29031.0 1
 
2.3%
19920.0 1
 
2.3%
33184.0 1
 
2.3%
49040.0 1
 
2.3%
25405.0 1
 
2.3%
794.18 1
 
2.3%
26002.0 1
 
2.3%
59464.0 1
 
2.3%
860.0 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
0.0 3
6.8%
794.18 1
 
2.3%
860.0 1
 
2.3%
2400.0 1
 
2.3%
5000.0 1
 
2.3%
11361.0 1
 
2.3%
15746.0 1
 
2.3%
15824.0 1
 
2.3%
16307.0 1
 
2.3%
19920.0 1
 
2.3%
ValueCountFrequency (%)
98640.0 1
2.3%
94545.0 1
2.3%
93121.0 1
2.3%
92575.0 1
2.3%
72220.0 1
2.3%
66870.0 1
2.3%
61572.0 1
2.3%
59464.0 1
2.3%
52688.0 1
2.3%
51810.0 1
2.3%

차도 연장_전체(하행)
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36058.686
Minimum0
Maximum98640
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:43.514418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile119.127
Q119016.75
median32108
Q351562
95-th percentile93039.1
Maximum98640
Range98640
Interquartile range (IQR)32545.25

Descriptive statistics

Standard deviation26491.939
Coefficient of variation (CV)0.73468953
Kurtosis0.19504321
Mean36058.686
Median Absolute Deviation (MAD)16647
Skewness0.76927318
Sum1586582.2
Variance7.0182283 × 108
MonotonicityNot monotonic
2023-12-11T07:57:43.638113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 3
 
6.8%
29031.0 1
 
2.3%
19920.0 1
 
2.3%
33184.0 1
 
2.3%
49040.0 1
 
2.3%
25405.0 1
 
2.3%
794.18 1
 
2.3%
26002.0 1
 
2.3%
59464.0 1
 
2.3%
860.0 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
0.0 3
6.8%
794.18 1
 
2.3%
860.0 1
 
2.3%
2400.0 1
 
2.3%
5000.0 1
 
2.3%
11361.0 1
 
2.3%
15746.0 1
 
2.3%
15824.0 1
 
2.3%
16307.0 1
 
2.3%
19920.0 1
 
2.3%
ValueCountFrequency (%)
98640.0 1
2.3%
94545.0 1
2.3%
93121.0 1
2.3%
92575.0 1
2.3%
72220.0 1
2.3%
66870.0 1
2.3%
61572.0 1
2.3%
59464.0 1
2.3%
52688.0 1
2.3%
51810.0 1
2.3%

아스팔트 차도 연장(상행)
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35570.368
Minimum0
Maximum98640
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:43.757309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile119.127
Q119016.75
median32108
Q349745
95-th percentile92402.8
Maximum98640
Range98640
Interquartile range (IQR)30728.25

Descriptive statistics

Standard deviation26072.683
Coefficient of variation (CV)0.73298884
Kurtosis0.3277151
Mean35570.368
Median Absolute Deviation (MAD)16323
Skewness0.80296341
Sum1565096.2
Variance6.7978478 × 108
MonotonicityNot monotonic
2023-12-11T07:57:43.890298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 3
 
6.8%
29031.0 1
 
2.3%
19920.0 1
 
2.3%
33184.0 1
 
2.3%
49040.0 1
 
2.3%
25405.0 1
 
2.3%
794.18 1
 
2.3%
26002.0 1
 
2.3%
42676.0 1
 
2.3%
860.0 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
0.0 3
6.8%
794.18 1
 
2.3%
860.0 1
 
2.3%
2400.0 1
 
2.3%
5000.0 1
 
2.3%
11361.0 1
 
2.3%
15746.0 1
 
2.3%
15824.0 1
 
2.3%
16307.0 1
 
2.3%
19920.0 1
 
2.3%
ValueCountFrequency (%)
98640.0 1
2.3%
93121.0 1
2.3%
92575.0 1
2.3%
91427.0 1
2.3%
72220.0 1
2.3%
66870.0 1
2.3%
59992.0 1
2.3%
52688.0 1
2.3%
51810.0 1
2.3%
51802.0 1
2.3%

아스팔트 차도 연장(하행)
Real number (ℝ)

ZEROS 

Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34992.981
Minimum0
Maximum98640
Zeros4
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:44.278990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116186.25
median32108
Q349745
95-th percentile92402.8
Maximum98640
Range98640
Interquartile range (IQR)33558.75

Descriptive statistics

Standard deviation26579.409
Coefficient of variation (CV)0.75956399
Kurtosis0.22001458
Mean34992.981
Median Absolute Deviation (MAD)16647
Skewness0.7691618
Sum1539691.2
Variance7.0646496 × 108
MonotonicityNot monotonic
2023-12-11T07:57:44.398956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.0 4
 
9.1%
20620.0 1
 
2.3%
5000.0 1
 
2.3%
33184.0 1
 
2.3%
49040.0 1
 
2.3%
794.18 1
 
2.3%
26002.0 1
 
2.3%
42676.0 1
 
2.3%
860.0 1
 
2.3%
66870.0 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
0.0 4
9.1%
794.18 1
 
2.3%
860.0 1
 
2.3%
2400.0 1
 
2.3%
5000.0 1
 
2.3%
11361.0 1
 
2.3%
15746.0 1
 
2.3%
15824.0 1
 
2.3%
16307.0 1
 
2.3%
19920.0 1
 
2.3%
ValueCountFrequency (%)
98640.0 1
2.3%
93121.0 1
2.3%
92575.0 1
2.3%
91427.0 1
2.3%
72220.0 1
2.3%
66870.0 1
2.3%
59992.0 1
2.3%
52688.0 1
2.3%
51810.0 1
2.3%
51802.0 1
2.3%

콘크리트 차도 연장(상행)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean538.29545
Minimum0
Maximum16788
Zeros39
Zeros (%)88.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:44.492268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1553
Maximum16788
Range16788
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2570.1986
Coefficient of variation (CV)4.7746988
Kurtosis39.534992
Mean538.29545
Median Absolute Deviation (MAD)0
Skewness6.1764211
Sum23685
Variance6605921.1
MonotonicityNot monotonic
2023-12-11T07:57:44.586599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 39
88.6%
3150 1
 
2.3%
1580 1
 
2.3%
1400 1
 
2.3%
16788 1
 
2.3%
767 1
 
2.3%
ValueCountFrequency (%)
0 39
88.6%
767 1
 
2.3%
1400 1
 
2.3%
1580 1
 
2.3%
3150 1
 
2.3%
16788 1
 
2.3%
ValueCountFrequency (%)
16788 1
 
2.3%
3150 1
 
2.3%
1580 1
 
2.3%
1400 1
 
2.3%
767 1
 
2.3%
0 39
88.6%

콘크리트 차도 연장(하행)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean538.29545
Minimum0
Maximum16788
Zeros39
Zeros (%)88.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:44.689900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1553
Maximum16788
Range16788
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2570.1986
Coefficient of variation (CV)4.7746988
Kurtosis39.534992
Mean538.29545
Median Absolute Deviation (MAD)0
Skewness6.1764211
Sum23685
Variance6605921.1
MonotonicityNot monotonic
2023-12-11T07:57:44.779921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 39
88.6%
3150 1
 
2.3%
1580 1
 
2.3%
1400 1
 
2.3%
16788 1
 
2.3%
767 1
 
2.3%
ValueCountFrequency (%)
0 39
88.6%
767 1
 
2.3%
1400 1
 
2.3%
1580 1
 
2.3%
3150 1
 
2.3%
16788 1
 
2.3%
ValueCountFrequency (%)
16788 1
 
2.3%
3150 1
 
2.3%
1580 1
 
2.3%
1400 1
 
2.3%
767 1
 
2.3%
0 39
88.6%

비포장 차도 연장(상행)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean292.95455
Minimum0
Maximum6000
Zeros38
Zeros (%)86.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:44.876993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2112
Maximum6000
Range6000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1060.2356
Coefficient of variation (CV)3.6191131
Kurtosis20.998847
Mean292.95455
Median Absolute Deviation (MAD)0
Skewness4.4327045
Sum12890
Variance1124099.6
MonotonicityNot monotonic
2023-12-11T07:57:44.969724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 38
86.4%
480 2
 
4.5%
2400 1
 
2.3%
3118 1
 
2.3%
6000 1
 
2.3%
412 1
 
2.3%
ValueCountFrequency (%)
0 38
86.4%
412 1
 
2.3%
480 2
 
4.5%
2400 1
 
2.3%
3118 1
 
2.3%
6000 1
 
2.3%
ValueCountFrequency (%)
6000 1
 
2.3%
3118 1
 
2.3%
2400 1
 
2.3%
480 2
 
4.5%
412 1
 
2.3%
0 38
86.4%

비포장 차도 연장(하행)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean292.95455
Minimum0
Maximum6000
Zeros38
Zeros (%)86.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:45.055508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2112
Maximum6000
Range6000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1060.2356
Coefficient of variation (CV)3.6191131
Kurtosis20.998847
Mean292.95455
Median Absolute Deviation (MAD)0
Skewness4.4327045
Sum12890
Variance1124099.6
MonotonicityNot monotonic
2023-12-11T07:57:45.141116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 38
86.4%
480 2
 
4.5%
2400 1
 
2.3%
3118 1
 
2.3%
6000 1
 
2.3%
412 1
 
2.3%
ValueCountFrequency (%)
0 38
86.4%
412 1
 
2.3%
480 2
 
4.5%
2400 1
 
2.3%
3118 1
 
2.3%
6000 1
 
2.3%
ValueCountFrequency (%)
6000 1
 
2.3%
3118 1
 
2.3%
2400 1
 
2.3%
480 2
 
4.5%
412 1
 
2.3%
0 38
86.4%

포장 보도(길어깨) 연장_좌
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23388.445
Minimum0
Maximum98096
Zeros6
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:45.250311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1935
median15368.25
Q336060.75
95-th percentile78917.95
Maximum98096
Range98096
Interquartile range (IQR)35125.75

Descriptive statistics

Standard deviation25876.628
Coefficient of variation (CV)1.1063851
Kurtosis0.66950762
Mean23388.445
Median Absolute Deviation (MAD)15368.25
Skewness1.1228453
Sum1029091.6
Variance6.6959987 × 108
MonotonicityNot monotonic
2023-12-11T07:57:45.370670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0.0 6
 
13.6%
27850.4 1
 
2.3%
2400.0 1
 
2.3%
47763.0 1
 
2.3%
11005.0 1
 
2.3%
25790.0 1
 
2.3%
10110.0 1
 
2.3%
1210.0 1
 
2.3%
70854.0 1
 
2.3%
20322.0 1
 
2.3%
Other values (29) 29
65.9%
ValueCountFrequency (%)
0.0 6
13.6%
310.0 1
 
2.3%
340.0 1
 
2.3%
700.0 1
 
2.3%
720.0 1
 
2.3%
860.0 1
 
2.3%
960.0 1
 
2.3%
1000.0 1
 
2.3%
1210.0 1
 
2.3%
2400.0 1
 
2.3%
ValueCountFrequency (%)
98096.0 1
2.3%
81040.0 1
2.3%
80341.0 1
2.3%
70854.0 1
2.3%
52208.0 1
2.3%
50824.5 1
2.3%
50656.0 1
2.3%
48909.0 1
2.3%
47763.0 1
2.3%
40041.3 1
2.3%

포장 보도(길어깨) 연장_우
Real number (ℝ)

ZEROS 

Distinct37
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25498.945
Minimum0
Maximum98470
Zeros8
Zeros (%)18.2%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:45.490966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1820
median20087
Q338920.575
95-th percentile80935.15
Maximum98470
Range98470
Interquartile range (IQR)38100.575

Descriptive statistics

Standard deviation28214.744
Coefficient of variation (CV)1.1065063
Kurtosis0.48242461
Mean25498.945
Median Absolute Deviation (MAD)19307
Skewness1.0860113
Sum1121953.6
Variance7.9607179 × 108
MonotonicityNot monotonic
2023-12-11T07:57:45.613395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 8
 
18.2%
27850.4 1
 
2.3%
15356.5 1
 
2.3%
98470.0 1
 
2.3%
25790.0 1
 
2.3%
8220.0 1
 
2.3%
1147.0 1
 
2.3%
70854.0 1
 
2.3%
20322.0 1
 
2.3%
2400.0 1
 
2.3%
Other values (27) 27
61.4%
ValueCountFrequency (%)
0.0 8
18.2%
360.0 1
 
2.3%
630.0 1
 
2.3%
700.0 1
 
2.3%
860.0 1
 
2.3%
1020.0 1
 
2.3%
1147.0 1
 
2.3%
2088.0 1
 
2.3%
2400.0 1
 
2.3%
3506.0 1
 
2.3%
ValueCountFrequency (%)
98470.0 1
2.3%
98096.0 1
2.3%
81040.0 1
2.3%
80341.0 1
2.3%
70854.0 1
2.3%
52208.0 1
2.3%
50824.5 1
2.3%
50656.0 1
2.3%
48909.0 1
2.3%
47763.0 1
2.3%
Distinct20
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14172.466
Minimum0
Maximum99933
Zeros25
Zeros (%)56.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:45.740456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q323383
95-th percentile56819.1
Maximum99933
Range99933
Interquartile range (IQR)23383

Descriptive statistics

Standard deviation24256.09
Coefficient of variation (CV)1.711494
Kurtosis3.8064806
Mean14172.466
Median Absolute Deviation (MAD)0
Skewness2.0026373
Sum623588.5
Variance5.8835793 × 108
MonotonicityNot monotonic
2023-12-11T07:57:45.863962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 25
56.8%
23500.0 1
 
2.3%
99933.0 1
 
2.3%
49442.0 1
 
2.3%
1.5 1
 
2.3%
19320.0 1
 
2.3%
32874.0 1
 
2.3%
32508.0 1
 
2.3%
12450.0 1
 
2.3%
57066.0 1
 
2.3%
Other values (10) 10
 
22.7%
ValueCountFrequency (%)
0.0 25
56.8%
1.5 1
 
2.3%
380.0 1
 
2.3%
5455.0 1
 
2.3%
6853.0 1
 
2.3%
12450.0 1
 
2.3%
12780.0 1
 
2.3%
19320.0 1
 
2.3%
23344.0 1
 
2.3%
23500.0 1
 
2.3%
ValueCountFrequency (%)
99933.0 1
2.3%
85825.0 1
2.3%
57066.0 1
2.3%
55420.0 1
2.3%
49442.0 1
2.3%
47341.0 1
2.3%
32874.0 1
2.3%
32847.0 1
2.3%
32508.0 1
2.3%
26249.0 1
2.3%
Distinct20
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14131.989
Minimum0
Maximum99996
Zeros25
Zeros (%)56.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:45.980436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q322600
95-th percentile57517.6
Maximum99996
Range99996
Interquartile range (IQR)22600

Descriptive statistics

Standard deviation23986.04
Coefficient of variation (CV)1.6972869
Kurtosis3.68384
Mean14131.989
Median Absolute Deviation (MAD)0
Skewness1.9732496
Sum621807.5
Variance5.753301 × 108
MonotonicityNot monotonic
2023-12-11T07:57:46.094986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 25
56.8%
23500.0 1
 
2.3%
99996.0 1
 
2.3%
50320.0 1
 
2.3%
1.5 1
 
2.3%
19320.0 1
 
2.3%
33184.0 1
 
2.3%
32508.0 1
 
2.3%
10310.0 1
 
2.3%
58066.0 1
 
2.3%
Other values (10) 10
 
22.7%
ValueCountFrequency (%)
0.0 25
56.8%
1.5 1
 
2.3%
340.0 1
 
2.3%
7692.0 1
 
2.3%
8399.0 1
 
2.3%
10310.0 1
 
2.3%
12780.0 1
 
2.3%
19320.0 1
 
2.3%
22300.0 1
 
2.3%
23500.0 1
 
2.3%
ValueCountFrequency (%)
99996.0 1
2.3%
81234.0 1
2.3%
58066.0 1
2.3%
54410.0 1
2.3%
50320.0 1
2.3%
47821.0 1
2.3%
33184.0 1
2.3%
32937.0 1
2.3%
32508.0 1
2.3%
26689.0 1
2.3%

자전거도로 연장_좌
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
4510
 
1

Length

Max length4
Median length1
Mean length1.0681818
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
4510 1
 
2.3%

Length

2023-12-11T07:57:46.219916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:46.339148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
4510 1
 
2.3%

자전거도로 연장_우
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
4510
 
1

Length

Max length4
Median length1
Mean length1.0681818
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
4510 1
 
2.3%

Length

2023-12-11T07:57:46.438271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:46.534626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
4510 1
 
2.3%

도로 면적_전체
Real number (ℝ)

ZEROS 

Distinct38
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1500058.1
Minimum0
Maximum5814325
Zeros6
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:46.658574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1537616.6
median1015937
Q31930215
95-th percentile5078293
Maximum5814325
Range5814325
Interquartile range (IQR)1392598.4

Descriptive statistics

Standard deviation1487049
Coefficient of variation (CV)0.99132761
Kurtosis1.7760158
Mean1500058.1
Median Absolute Deviation (MAD)699207
Skewness1.4750126
Sum66002556
Variance2.2113147 × 1012
MonotonicityNot monotonic
2023-12-11T07:57:46.791062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.0 6
 
13.6%
693509.0 2
 
4.5%
43507.0 1
 
2.3%
839729.0 1
 
2.3%
5169427.0 1
 
2.3%
466533.4 1
 
2.3%
31756.0 1
 
2.3%
895557.0 1
 
2.3%
1456686.0 1
 
2.3%
4561867.0 1
 
2.3%
Other values (28) 28
63.6%
ValueCountFrequency (%)
0.0 6
13.6%
31756.0 1
 
2.3%
43507.0 1
 
2.3%
271363.0 1
 
2.3%
376911.0 1
 
2.3%
466533.4 1
 
2.3%
561311.0 1
 
2.3%
693509.0 2
 
4.5%
699830.7 1
 
2.3%
756745.1 1
 
2.3%
ValueCountFrequency (%)
5814325.0 1
2.3%
5300288.3 1
2.3%
5169427.0 1
2.3%
4561867.0 1
2.3%
3855794.1 1
2.3%
3251839.2 1
2.3%
2415716.0 1
2.3%
2318951.0 1
2.3%
2252419.0 1
2.3%
2162181.9 1
2.3%

도로 면적_국유지
Real number (ℝ)

ZEROS 

Distinct40
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1023663.2
Minimum0
Maximum3819705.3
Zeros5
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:46.953566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1228641.77
median675586.1
Q31379968.2
95-th percentile3508382.3
Maximum3819705.3
Range3819705.3
Interquartile range (IQR)1151326.4

Descriptive statistics

Standard deviation1107494
Coefficient of variation (CV)1.0818929
Kurtosis0.77863379
Mean1023663.2
Median Absolute Deviation (MAD)553802
Skewness1.3481611
Sum45041182
Variance1.226543 × 1012
MonotonicityNot monotonic
2023-12-11T07:57:47.099156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0.0 5
 
11.4%
19207.0 1
 
2.3%
1046937.0 1
 
2.3%
497372.0 1
 
2.3%
3540159.0 1
 
2.3%
129988.2 1
 
2.3%
12117.0 1
 
2.3%
565377.0 1
 
2.3%
409071.0 1
 
2.3%
3277148.0 1
 
2.3%
Other values (30) 30
68.2%
ValueCountFrequency (%)
0.0 5
11.4%
12117.0 1
 
2.3%
19207.0 1
 
2.3%
77194.0 1
 
2.3%
113580.0 1
 
2.3%
129988.2 1
 
2.3%
159116.1 1
 
2.3%
251817.0 1
 
2.3%
346520.0 1
 
2.3%
409071.0 1
 
2.3%
ValueCountFrequency (%)
3819705.3 1
2.3%
3607663.0 1
2.3%
3540159.0 1
2.3%
3328314.0 1
2.3%
3277148.0 1
2.3%
2838796.2 1
2.3%
2054389.3 1
2.3%
2018562.0 1
2.3%
1791310.0 1
2.3%
1703512.0 1
2.3%

도로 면적_공유지
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184676.1
Minimum0
Maximum1265517
Zeros21
Zeros (%)47.7%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:47.237286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7391
Q3258681.53
95-th percentile793473.03
Maximum1265517
Range1265517
Interquartile range (IQR)258681.53

Descriptive statistics

Standard deviation302012.35
Coefficient of variation (CV)1.6353624
Kurtosis5.1181588
Mean184676.1
Median Absolute Deviation (MAD)7391
Skewness2.2365856
Sum8125748.5
Variance9.1211461 × 1010
MonotonicityNot monotonic
2023-12-11T07:57:47.371166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 21
47.7%
33181.1 1
 
2.3%
729067.0 1
 
2.3%
438596.59 1
 
2.3%
804838.8 1
 
2.3%
342417.0 1
 
2.3%
346067.1 1
 
2.3%
228008.0 1
 
2.3%
473320.0 1
 
2.3%
255341.7 1
 
2.3%
Other values (14) 14
31.8%
ValueCountFrequency (%)
0.0 21
47.7%
1618.0 1
 
2.3%
13164.0 1
 
2.3%
23116.0 1
 
2.3%
33181.1 1
 
2.3%
67893.0 1
 
2.3%
157783.0 1
 
2.3%
183511.0 1
 
2.3%
197444.0 1
 
2.3%
228008.0 1
 
2.3%
ValueCountFrequency (%)
1265517.0 1
2.3%
1172777.0 1
2.3%
804838.8 1
2.3%
729067.0 1
2.3%
473320.0 1
2.3%
438596.59 1
2.3%
346067.1 1
2.3%
342417.0 1
2.3%
324529.2 1
2.3%
299363.0 1
2.3%

도로 면적_사유지
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean324637.48
Minimum0
Maximum1627394
Zeros6
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:47.496399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q167288.25
median243421
Q3400160.44
95-th percentile1012410.8
Maximum1627394
Range1627394
Interquartile range (IQR)332872.19

Descriptive statistics

Standard deviation366260.99
Coefficient of variation (CV)1.1282153
Kurtosis3.544358
Mean324637.48
Median Absolute Deviation (MAD)164863
Skewness1.8284154
Sum14284049
Variance1.3414711 × 1011
MonotonicityNot monotonic
2023-12-11T07:57:47.635628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0.0 6
 
13.6%
890718.0 1
 
2.3%
174266.0 1
 
2.3%
89330.0 1
 
2.3%
1627394.0 1
 
2.3%
12016.0 1
 
2.3%
6475.0 1
 
2.3%
146669.0 1
 
2.3%
318548.0 1
 
2.3%
19202.0 1
 
2.3%
Other values (29) 29
65.9%
ValueCountFrequency (%)
0.0 6
13.6%
1186.0 1
 
2.3%
6475.0 1
 
2.3%
10131.0 1
 
2.3%
12016.0 1
 
2.3%
19202.0 1
 
2.3%
83317.0 1
 
2.3%
89330.0 1
 
2.3%
97969.0 1
 
2.3%
146669.0 1
 
2.3%
ValueCountFrequency (%)
1627394.0 1
2.3%
1331621.3 1
2.3%
1033886.0 1
2.3%
890718.0 1
2.3%
857846.0 1
2.3%
798727.0 1
2.3%
726575.0 1
2.3%
525158.1 1
2.3%
507137.0 1
2.3%
443504.0 1
2.3%

곡선반경(100m 미만)
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143.93182
Minimum0
Maximum508
Zeros4
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:47.783482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q145
median101.5
Q3208.25
95-th percentile346.2
Maximum508
Range508
Interquartile range (IQR)163.25

Descriptive statistics

Standard deviation131.01312
Coefficient of variation (CV)0.91024431
Kurtosis0.39774563
Mean143.93182
Median Absolute Deviation (MAD)79
Skewness1.0340391
Sum6333
Variance17164.437
MonotonicityNot monotonic
2023-12-11T07:57:47.931999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 4
 
9.1%
93 2
 
4.5%
18 2
 
4.5%
52 1
 
2.3%
8 1
 
2.3%
103 1
 
2.3%
100 1
 
2.3%
16 1
 
2.3%
188 1
 
2.3%
467 1
 
2.3%
Other values (29) 29
65.9%
ValueCountFrequency (%)
0 4
9.1%
8 1
 
2.3%
16 1
 
2.3%
18 2
4.5%
21 1
 
2.3%
22 1
 
2.3%
42 1
 
2.3%
46 1
 
2.3%
52 1
 
2.3%
55 1
 
2.3%
ValueCountFrequency (%)
508 1
2.3%
467 1
2.3%
348 1
2.3%
336 1
2.3%
334 1
2.3%
328 1
2.3%
313 1
2.3%
292 1
2.3%
274 1
2.3%
272 1
2.3%

곡선반경(100 이상_200m 미만)
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.840909
Minimum0
Maximum262
Zeros2
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:48.084896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q129.25
median62.5
Q3115.5
95-th percentile231.35
Maximum262
Range262
Interquartile range (IQR)86.25

Descriptive statistics

Standard deviation69.347438
Coefficient of variation (CV)0.86857024
Kurtosis0.61087818
Mean79.840909
Median Absolute Deviation (MAD)38
Skewness1.0837364
Sum3513
Variance4809.0671
MonotonicityNot monotonic
2023-12-11T07:57:48.241198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 3
 
6.8%
48 2
 
4.5%
0 2
 
4.5%
70 2
 
4.5%
43 1
 
2.3%
34 1
 
2.3%
40 1
 
2.3%
85 1
 
2.3%
90 1
 
2.3%
191 1
 
2.3%
Other values (29) 29
65.9%
ValueCountFrequency (%)
0 2
4.5%
1 3
6.8%
6 1
 
2.3%
7 1
 
2.3%
14 1
 
2.3%
23 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
30 1
 
2.3%
34 1
 
2.3%
ValueCountFrequency (%)
262 1
2.3%
249 1
2.3%
236 1
2.3%
205 1
2.3%
191 1
2.3%
152 1
2.3%
145 1
2.3%
138 1
2.3%
136 1
2.3%
134 1
2.3%

곡선반경(200 이상 _300m 미만)
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.159091
Minimum0
Maximum106
Zeros5
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:48.388624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115.5
median25.5
Q340.75
95-th percentile89.65
Maximum106
Range106
Interquartile range (IQR)25.25

Descriptive statistics

Standard deviation25.90227
Coefficient of variation (CV)0.83129094
Kurtosis1.4780266
Mean31.159091
Median Absolute Deviation (MAD)13
Skewness1.2544239
Sum1371
Variance670.92759
MonotonicityNot monotonic
2023-12-11T07:57:48.526849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 5
 
11.4%
17 3
 
6.8%
34 2
 
4.5%
23 2
 
4.5%
16 2
 
4.5%
38 2
 
4.5%
26 2
 
4.5%
11 1
 
2.3%
20 1
 
2.3%
98 1
 
2.3%
Other values (23) 23
52.3%
ValueCountFrequency (%)
0 5
11.4%
3 1
 
2.3%
8 1
 
2.3%
9 1
 
2.3%
11 1
 
2.3%
12 1
 
2.3%
14 1
 
2.3%
16 2
 
4.5%
17 3
6.8%
18 1
 
2.3%
ValueCountFrequency (%)
106 1
2.3%
98 1
2.3%
91 1
2.3%
82 1
2.3%
61 1
2.3%
56 1
2.3%
55 1
2.3%
50 1
2.3%
45 1
2.3%
44 1
2.3%

곡선반경(300 이상 _460m 미만)
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.090909
Minimum0
Maximum67
Zeros3
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:48.651562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.15
Q18
median15.5
Q329.5
95-th percentile60.5
Maximum67
Range67
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation17.68828
Coefficient of variation (CV)0.83866847
Kurtosis0.55454309
Mean21.090909
Median Absolute Deviation (MAD)8.5
Skewness1.0945082
Sum928
Variance312.87526
MonotonicityNot monotonic
2023-12-11T07:57:48.791418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 3
 
6.8%
31 3
 
6.8%
24 3
 
6.8%
20 2
 
4.5%
8 2
 
4.5%
5 2
 
4.5%
13 2
 
4.5%
7 2
 
4.5%
14 2
 
4.5%
10 2
 
4.5%
Other values (21) 21
47.7%
ValueCountFrequency (%)
0 3
6.8%
1 1
 
2.3%
2 1
 
2.3%
5 2
4.5%
6 1
 
2.3%
7 2
4.5%
8 2
4.5%
9 1
 
2.3%
10 2
4.5%
11 1
 
2.3%
ValueCountFrequency (%)
67 1
 
2.3%
63 1
 
2.3%
62 1
 
2.3%
52 1
 
2.3%
49 1
 
2.3%
47 1
 
2.3%
40 1
 
2.3%
37 1
 
2.3%
31 3
6.8%
29 1
 
2.3%

곡선반경(460 이상 _700m 미만)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.022727
Minimum0
Maximum38
Zeros5
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:48.968673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.75
median8.5
Q316
95-th percentile25
Maximum38
Range38
Interquartile range (IQR)13.25

Descriptive statistics

Standard deviation8.8383115
Coefficient of variation (CV)0.881827
Kurtosis0.89381786
Mean10.022727
Median Absolute Deviation (MAD)6.5
Skewness0.99893187
Sum441
Variance78.115751
MonotonicityNot monotonic
2023-12-11T07:57:49.123551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 5
 
11.4%
1 4
 
9.1%
9 3
 
6.8%
19 3
 
6.8%
8 3
 
6.8%
4 3
 
6.8%
17 2
 
4.5%
16 2
 
4.5%
3 2
 
4.5%
12 2
 
4.5%
Other values (11) 15
34.1%
ValueCountFrequency (%)
0 5
11.4%
1 4
9.1%
2 2
 
4.5%
3 2
 
4.5%
4 3
6.8%
5 1
 
2.3%
7 2
 
4.5%
8 3
6.8%
9 3
6.8%
10 1
 
2.3%
ValueCountFrequency (%)
38 1
 
2.3%
26 1
 
2.3%
25 2
4.5%
24 1
 
2.3%
19 3
6.8%
17 2
4.5%
16 2
4.5%
15 1
 
2.3%
13 1
 
2.3%
12 2
4.5%

곡선반경(700m 이상)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.090909
Minimum0
Maximum56
Zeros4
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:49.225846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median9
Q317
95-th percentile33.25
Maximum56
Range56
Interquartile range (IQR)14

Descriptive statistics

Standard deviation11.766761
Coefficient of variation (CV)0.97319074
Kurtosis3.243658
Mean12.090909
Median Absolute Deviation (MAD)7
Skewness1.5712749
Sum532
Variance138.45666
MonotonicityNot monotonic
2023-12-11T07:57:49.342439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 4
 
9.1%
9 4
 
9.1%
17 4
 
9.1%
4 3
 
6.8%
3 3
 
6.8%
1 3
 
6.8%
10 2
 
4.5%
5 2
 
4.5%
2 2
 
4.5%
29 2
 
4.5%
Other values (11) 15
34.1%
ValueCountFrequency (%)
0 4
9.1%
1 3
6.8%
2 2
4.5%
3 3
6.8%
4 3
6.8%
5 2
4.5%
7 2
4.5%
9 4
9.1%
10 2
4.5%
11 2
4.5%
ValueCountFrequency (%)
56 1
 
2.3%
34 2
4.5%
29 2
4.5%
27 1
 
2.3%
26 1
 
2.3%
22 1
 
2.3%
19 1
 
2.3%
17 4
9.1%
16 1
 
2.3%
15 2
4.5%

교차_육교
Categorical

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
38 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 38
86.4%
1 6
 
13.6%

Length

2023-12-11T07:57:49.453919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:49.586842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
86.4%
1 6
 
13.6%

교차_지하도
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
2 1
 
2.3%

Length

2023-12-11T07:57:49.703592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:49.824630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
2 1
 
2.3%

교차_철도(과선)
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
42 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 42
95.5%
1 2
 
4.5%

Length

2023-12-11T07:57:49.951016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:50.064282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42
95.5%
1 2
 
4.5%

교차_철도(가도)
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
41 
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 41
93.2%
1 3
 
6.8%

Length

2023-12-11T07:57:50.482412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:50.573772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 41
93.2%
1 3
 
6.8%

교차_도로(평면)
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5454545
Minimum0
Maximum13
Zeros30
Zeros (%)68.2%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:50.667003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6.85
Maximum13
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.9996476
Coefficient of variation (CV)1.9409485
Kurtosis5.7141486
Mean1.5454545
Median Absolute Deviation (MAD)0
Skewness2.3629252
Sum68
Variance8.9978858
MonotonicityNot monotonic
2023-12-11T07:57:50.818854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 30
68.2%
4 3
 
6.8%
1 2
 
4.5%
2 2
 
4.5%
5 2
 
4.5%
7 1
 
2.3%
11 1
 
2.3%
6 1
 
2.3%
13 1
 
2.3%
3 1
 
2.3%
ValueCountFrequency (%)
0 30
68.2%
1 2
 
4.5%
2 2
 
4.5%
3 1
 
2.3%
4 3
 
6.8%
5 2
 
4.5%
6 1
 
2.3%
7 1
 
2.3%
11 1
 
2.3%
13 1
 
2.3%
ValueCountFrequency (%)
13 1
 
2.3%
11 1
 
2.3%
7 1
 
2.3%
6 1
 
2.3%
5 2
 
4.5%
4 3
 
6.8%
3 1
 
2.3%
2 2
 
4.5%
1 2
 
4.5%
0 30
68.2%

교차_도로(입체)
Categorical

IMBALANCE 

Distinct5
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
36 
5
 
2
1
 
2
3
 
2
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 36
81.8%
5 2
 
4.5%
1 2
 
4.5%
3 2
 
4.5%
2 2
 
4.5%

Length

2023-12-11T07:57:50.989911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:51.125370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
81.8%
5 2
 
4.5%
1 2
 
4.5%
3 2
 
4.5%
2 2
 
4.5%
Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean170.77273
Minimum2
Maximum566
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:51.260025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q162.75
median145
Q3230.5
95-th percentile486.25
Maximum566
Range564
Interquartile range (IQR)167.75

Descriptive statistics

Standard deviation149.50956
Coefficient of variation (CV)0.87548853
Kurtosis0.66973154
Mean170.77273
Median Absolute Deviation (MAD)85.5
Skewness1.1059125
Sum7514
Variance22353.11
MonotonicityNot monotonic
2023-12-11T07:57:51.464014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2 2
 
4.5%
3 2
 
4.5%
89 2
 
4.5%
46 1
 
2.3%
4 1
 
2.3%
64 1
 
2.3%
185 1
 
2.3%
92 1
 
2.3%
313 1
 
2.3%
342 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
2 2
4.5%
3 2
4.5%
4 1
2.3%
8 1
2.3%
18 1
2.3%
36 1
2.3%
46 1
2.3%
48 1
2.3%
59 1
2.3%
64 1
2.3%
ValueCountFrequency (%)
566 1
2.3%
537 1
2.3%
487 1
2.3%
482 1
2.3%
383 1
2.3%
342 1
2.3%
319 1
2.3%
313 1
2.3%
309 1
2.3%
249 1
2.3%

종단경사(3퍼센트미만)_연장
Real number (ℝ)

UNIQUE  ZEROS 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22893.938
Minimum0
Maximum86814.73
Zeros1
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:51.643996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile618.377
Q18120
median18938
Q331050.93
95-th percentile63058.379
Maximum86814.73
Range86814.73
Interquartile range (IQR)22930.93

Descriptive statistics

Standard deviation20385.17
Coefficient of variation (CV)0.8904178
Kurtosis1.8451639
Mean22893.938
Median Absolute Deviation (MAD)11601.83
Skewness1.3464312
Sum1007333.3
Variance4.1555516 × 108
MonotonicityNot monotonic
2023-12-11T07:57:51.769732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
8929.0 1
 
2.3%
3655.64 1
 
2.3%
15790.0 1
 
2.3%
41073.17 1
 
2.3%
14952.0 1
 
2.3%
694.18 1
 
2.3%
20201.0 1
 
2.3%
34673.0 1
 
2.3%
32011.0 1
 
2.3%
605.0 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
0.0 1
2.3%
180.0 1
2.3%
605.0 1
2.3%
694.18 1
2.3%
1357.24 1
2.3%
1980.0 1
2.3%
2306.03 1
2.3%
3655.64 1
2.3%
4353.0 1
2.3%
6780.0 1
2.3%
ValueCountFrequency (%)
86814.73 1
2.3%
77295.73 1
2.3%
64719.0 1
2.3%
53648.19 1
2.3%
49216.0 1
2.3%
48720.0 1
2.3%
41073.17 1
2.3%
40378.0 1
2.3%
34673.0 1
2.3%
32011.0 1
2.3%
Distinct34
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.795455
Minimum1
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:51.901748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q114
median24
Q352
95-th percentile98
Maximum165
Range164
Interquartile range (IQR)38

Descriptive statistics

Standard deviation34.032529
Coefficient of variation (CV)0.95075001
Kurtosis4.200548
Mean35.795455
Median Absolute Deviation (MAD)15
Skewness1.8360785
Sum1575
Variance1158.213
MonotonicityNot monotonic
2023-12-11T07:57:52.046904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
28 3
 
6.8%
22 3
 
6.8%
11 2
 
4.5%
1 2
 
4.5%
52 2
 
4.5%
18 2
 
4.5%
2 2
 
4.5%
20 2
 
4.5%
16 1
 
2.3%
25 1
 
2.3%
Other values (24) 24
54.5%
ValueCountFrequency (%)
1 2
4.5%
2 2
4.5%
3 1
2.3%
5 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
11 2
4.5%
15 1
2.3%
16 1
2.3%
ValueCountFrequency (%)
165 1
2.3%
122 1
2.3%
101 1
2.3%
81 1
2.3%
72 1
2.3%
71 1
2.3%
68 1
2.3%
61 1
2.3%
60 1
2.3%
53 1
2.3%

종단경사(3_5퍼센트미만)_연장
Real number (ℝ)

UNIQUE  ZEROS 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4366.0189
Minimum0
Maximum14947
Zeros1
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:52.191908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile279.75
Q11912.5
median2892
Q35795
95-th percentile10833.55
Maximum14947
Range14947
Interquartile range (IQR)3882.5

Descriptive statistics

Standard deviation3644.8373
Coefficient of variation (CV)0.8348194
Kurtosis0.88506924
Mean4366.0189
Median Absolute Deviation (MAD)1766
Skewness1.1843015
Sum192104.83
Variance13284839
MonotonicityNot monotonic
2023-12-11T07:57:52.365750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
4701.0 1
 
2.3%
2304.36 1
 
2.3%
2670.0 1
 
2.3%
4700.0 1
 
2.3%
1633.0 1
 
2.3%
100.0 1
 
2.3%
4342.0 1
 
2.3%
8852.0 1
 
2.3%
8062.0 1
 
2.3%
255.0 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
0.0 1
2.3%
100.0 1
2.3%
255.0 1
2.3%
420.0 1
2.3%
580.0 1
2.3%
1092.0 1
2.3%
1160.0 1
2.3%
1251.0 1
2.3%
1633.0 1
2.3%
1817.0 1
2.3%
ValueCountFrequency (%)
14947.0 1
2.3%
13545.3 1
2.3%
10981.0 1
2.3%
9998.0 1
2.3%
9984.0 1
2.3%
9171.46 1
2.3%
8852.0 1
2.3%
8550.0 1
2.3%
8062.0 1
2.3%
6464.3 1
2.3%
Distinct32
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.363636
Minimum0
Maximum214
Zeros4
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:52.505611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110.5
median27
Q360.5
95-th percentile102.5
Maximum214
Range214
Interquartile range (IQR)50

Descriptive statistics

Standard deviation41.478541
Coefficient of variation (CV)1.0537274
Kurtosis6.2319005
Mean39.363636
Median Absolute Deviation (MAD)22
Skewness2.0573222
Sum1732
Variance1720.4693
MonotonicityNot monotonic
2023-12-11T07:57:52.628298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 4
 
9.1%
2 3
 
6.8%
9 2
 
4.5%
49 2
 
4.5%
13 2
 
4.5%
14 2
 
4.5%
51 2
 
4.5%
22 2
 
4.5%
21 2
 
4.5%
24 1
 
2.3%
Other values (22) 22
50.0%
ValueCountFrequency (%)
0 4
9.1%
2 3
6.8%
5 1
 
2.3%
6 1
 
2.3%
9 2
4.5%
11 1
 
2.3%
13 2
4.5%
14 2
4.5%
15 1
 
2.3%
21 2
4.5%
ValueCountFrequency (%)
214 1
2.3%
126 1
2.3%
104 1
2.3%
94 1
2.3%
84 1
2.3%
82 1
2.3%
73 1
2.3%
68 1
2.3%
66 1
2.3%
63 1
2.3%
Distinct40
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7048.5505
Minimum0
Maximum96972
Zeros5
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:52.776786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11500
median3581.2
Q37921.25
95-th percentile15314.8
Maximum96972
Range96972
Interquartile range (IQR)6421.25

Descriptive statistics

Standard deviation14786.598
Coefficient of variation (CV)2.0978212
Kurtosis33.458325
Mean7048.5505
Median Absolute Deviation (MAD)3097.5
Skewness5.5093111
Sum310136.22
Variance2.1864349 × 108
MonotonicityNot monotonic
2023-12-11T07:57:52.960439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0.0 5
 
11.4%
1730.0 1
 
2.3%
6157.0 1
 
2.3%
1560.0 1
 
2.3%
1890.0 1
 
2.3%
720.0 1
 
2.3%
6240.0 1
 
2.3%
9025.0 1
 
2.3%
12537.0 1
 
2.3%
6089.1 1
 
2.3%
Other values (30) 30
68.2%
ValueCountFrequency (%)
0.0 5
11.4%
180.0 1
 
2.3%
300.0 1
 
2.3%
400.0 1
 
2.3%
720.0 1
 
2.3%
1290.0 1
 
2.3%
1320.0 1
 
2.3%
1560.0 1
 
2.3%
1580.0 1
 
2.3%
1654.0 1
 
2.3%
ValueCountFrequency (%)
96972.0 1
2.3%
26750.0 1
2.3%
15805.0 1
2.3%
12537.0 1
2.3%
12001.95 1
2.3%
9025.0 1
2.3%
8917.0 1
2.3%
8815.0 1
2.3%
8283.0 1
2.3%
8260.0 1
2.3%
Distinct22
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.931818
Minimum0
Maximum188
Zeros13
Zeros (%)29.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:53.142539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q320.25
95-th percentile64.2
Maximum188
Range188
Interquartile range (IQR)20.25

Descriptive statistics

Standard deviation32.169173
Coefficient of variation (CV)1.8999243
Kurtosis18.591376
Mean16.931818
Median Absolute Deviation (MAD)3
Skewness3.8503259
Sum745
Variance1034.8557
MonotonicityNot monotonic
2023-12-11T07:57:53.268655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 13
29.5%
3 4
 
9.1%
6 3
 
6.8%
2 3
 
6.8%
1 3
 
6.8%
16 2
 
4.5%
18 1
 
2.3%
39 1
 
2.3%
35 1
 
2.3%
67 1
 
2.3%
Other values (12) 12
27.3%
ValueCountFrequency (%)
0 13
29.5%
1 3
 
6.8%
2 3
 
6.8%
3 4
 
9.1%
6 3
 
6.8%
8 1
 
2.3%
9 1
 
2.3%
13 1
 
2.3%
16 2
 
4.5%
18 1
 
2.3%
ValueCountFrequency (%)
188 1
2.3%
67 1
2.3%
66 1
2.3%
54 1
2.3%
46 1
2.3%
44 1
2.3%
39 1
2.3%
35 1
2.3%
24 1
2.3%
22 1
2.3%
Distinct31
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2534.1855
Minimum0
Maximum29535
Zeros13
Zeros (%)29.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-11T07:57:53.427269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median476.62
Q33295
95-th percentile7159.95
Maximum29535
Range29535
Interquartile range (IQR)3295

Descriptive statistics

Standard deviation4989.3603
Coefficient of variation (CV)1.9688221
Kurtosis20.230426
Mean2534.1855
Median Absolute Deviation (MAD)476.62
Skewness4.0580372
Sum111504.16
Variance24893716
MonotonicityNot monotonic
2023-12-11T07:57:53.605567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 13
29.5%
60.0 2
 
4.5%
2610.0 1
 
2.3%
420.0 1
 
2.3%
340.0 1
 
2.3%
6663.0 1
 
2.3%
437.0 1
 
2.3%
6933.0 1
 
2.3%
29535.0 1
 
2.3%
3580.0 1
 
2.3%
Other values (21) 21
47.7%
ValueCountFrequency (%)
0.0 13
29.5%
20.0 1
 
2.3%
60.0 2
 
4.5%
120.0 1
 
2.3%
340.0 1
 
2.3%
390.0 1
 
2.3%
420.0 1
 
2.3%
437.0 1
 
2.3%
453.24 1
 
2.3%
500.0 1
 
2.3%
ValueCountFrequency (%)
29535.0 1
2.3%
12409.92 1
2.3%
7200.0 1
2.3%
6933.0 1
2.3%
6808.0 1
2.3%
6663.0 1
2.3%
6000.0 1
2.3%
4260.0 1
2.3%
3940.0 1
2.3%
3797.0 1
2.3%

유료도로_관리자
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
40 
0
 
4

Length

Max length4
Median length4
Mean length3.7272727
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 40
90.9%
0 4
 
9.1%

Length

2023-12-11T07:57:53.776546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:53.912839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
90.9%
0 4
 
9.1%
Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
39 
0
1994-08-01
 
1

Length

Max length10
Median length4
Mean length3.8636364
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 39
88.6%
0 4
 
9.1%
1994-08-01 1
 
2.3%

Length

2023-12-11T07:57:54.048588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:54.191512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 39
88.6%
0 4
 
9.1%
1994-08-01 1
 
2.3%
Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
39 
0
2014-07-01
 
1

Length

Max length10
Median length4
Mean length3.8636364
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 39
88.6%
0 4
 
9.1%
2014-07-01 1
 
2.3%

Length

2023-12-11T07:57:54.335737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:54.458780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 39
88.6%
0 4
 
9.1%
2014-07-01 1
 
2.3%
Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
12
 
1

Length

Max length2
Median length1
Mean length1.0227273
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
12 1
 
2.3%

Length

2023-12-11T07:57:54.625057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:54.758894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
12 1
 
2.3%
Distinct3
Distinct (%)60.0%
Missing39
Missing (%)88.6%
Memory size484.0 B
2023-12-11T07:57:54.895352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length1
Mean length6.2
Min length1

Characters and Unicode

Total characters31
Distinct characters24
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

Unique2 ?
Unique (%)40.0%

Sample

1st row1.372026428
2nd row0
3rd row0
4th row0
5th row민자유치투자협정 터널건설비 회수
ValueCountFrequency (%)
0 3
42.9%
1.372026428 1
 
14.3%
민자유치투자협정 1
 
14.3%
터널건설비 1
 
14.3%
회수 1
 
14.3%
2023-12-11T07:57:55.253015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
 
12.9%
2 3
 
9.7%
2
 
6.5%
2
 
6.5%
1
 
3.2%
1
 
3.2%
1
 
3.2%
1
 
3.2%
1
 
3.2%
1
 
3.2%
Other values (14) 14
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15
48.4%
Decimal Number 13
41.9%
Space Separator 2
 
6.5%
Other Punctuation 1
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (4) 4
26.7%
Decimal Number
ValueCountFrequency (%)
0 4
30.8%
2 3
23.1%
1 1
 
7.7%
8 1
 
7.7%
4 1
 
7.7%
6 1
 
7.7%
7 1
 
7.7%
3 1
 
7.7%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16
51.6%
Hangul 15
48.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (4) 4
26.7%
Common
ValueCountFrequency (%)
0 4
25.0%
2 3
18.8%
2
12.5%
1 1
 
6.2%
8 1
 
6.2%
4 1
 
6.2%
6 1
 
6.2%
7 1
 
6.2%
3 1
 
6.2%
. 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
51.6%
Hangul 15
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
25.0%
2 3
18.8%
2
12.5%
1 1
 
6.2%
8 1
 
6.2%
4 1
 
6.2%
6 1
 
6.2%
7 1
 
6.2%
3 1
 
6.2%
. 1
 
6.2%
Hangul
ValueCountFrequency (%)
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (4) 4
26.7%

유료도로 전체 연장
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
2346
 
1

Length

Max length4
Median length1
Mean length1.0681818
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
2346 1
 
2.3%

Length

2023-12-11T07:57:55.392052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:55.498752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
2346 1
 
2.3%

유료도로 도로_연장
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
2346
 
1

Length

Max length4
Median length1
Mean length1.0681818
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
2346 1
 
2.3%

Length

2023-12-11T07:57:55.668330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:55.791616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
2346 1
 
2.3%

유료도로 터널_개소
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
1 1
 
2.3%

Length

2023-12-11T07:57:55.896983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:56.011395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
1 1
 
2.3%

유료도로 터널_연장
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
43 
2346
 
1

Length

Max length4
Median length1
Mean length1.0681818
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43
97.7%
2346 1
 
2.3%

Length

2023-12-11T07:57:56.153235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:56.304161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
97.7%
2346 1
 
2.3%

유료도로 교량_개소
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2023-12-11T07:57:56.421715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:56.539368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%

유료도로 교량_연장
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2023-12-11T07:57:56.658763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:56.785288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%

비고
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
<NA>
43 
0
 
1

Length

Max length4
Median length4
Mean length3.9318182
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
97.7%
0 1
 
2.3%

Length

2023-12-11T07:57:56.907390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:57:57.050238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
97.7%
0 1
 
2.3%

Sample

식별번호관리번호관리기관도로종류노선번호노선명구간번호이력코드노선 지정(인정) 연월일도로구역 결정(변경) 연월일접도구역 지정 연월일지적고시 연월일노선시점 위치(주소)노선종점 위치(주소)주요한 경과지노선연장전용연장중용연장통행불능연장포장도로_전체연장포장도로_도로연장포장도로_터널개소(2차로)포장도로_터널연장(2차로)포장도로_터널개소(3차로)포장도로_터널연장(3차로)포장도로_터널개소(4차로)포장도로_터널연장(4차로)포장도로_터널개소(5차로이상)포장도로_터널연장(5차로이상)포장도로_터널개소(전체)포장도로_터널연장(전체)포장도로_교량개소(강교)포장도로_교량연장(강교)포장도로_교량개소(철근콘크리트교)포장도로_교량연장(철근콘크리트교)포장도로_교량개소(합성교)포장도로_교량연장(합성교)포장도로_교량개소(기타)포장도로_교량연장(기타)포장도로_교량개소(전체)포장도로_교량연장(전체)비포장도로연장미개통도로연장폭원_전체폭원_차도폭원_중앙분리대폭원_길어깨(보도)포장두께_전체포장두께_포장기층_포장슬래브포장두께_보조기층도로연장(2차로미만)도로연장(2차로_4차로미만)도로연장(4차로_6차로미만)도로연장(6차로이상)차도 연장_전체(상행)차도 연장_전체(하행)아스팔트 차도 연장(상행)아스팔트 차도 연장(하행)콘크리트 차도 연장(상행)콘크리트 차도 연장(하행)비포장 차도 연장(상행)비포장 차도 연장(하행)포장 보도(길어깨) 연장_좌포장 보도(길어깨) 연장_우비포장 보도(길어깨) 연장_좌비포장 보도(길어깨) 연장_우자전거도로 연장_좌자전거도로 연장_우도로 면적_전체도로 면적_국유지도로 면적_공유지도로 면적_사유지곡선반경(100m 미만)곡선반경(100 이상_200m 미만)곡선반경(200 이상 _300m 미만)곡선반경(300 이상 _460m 미만)곡선반경(460 이상 _700m 미만)곡선반경(700m 이상)교차_육교교차_지하도교차_철도(과선)교차_철도(가도)교차_도로(평면)교차_도로(입체)종단경사(3퍼센트미만)_개소종단경사(3퍼센트미만)_연장종단경사(3_5퍼센트미만)_개소종단경사(3_5퍼센트미만)_연장종단경사(5_10퍼센트미만)_개소종단경사(5_10퍼센트미만)_연장종단경사(10퍼센트이상)_개소종단경사(10퍼센트이상)_연장유료도로_관리자유료도로_요금징수_시작일자유료도로_요금징수_종료일자유료도로_요금징수 시설수유료도로_요금징수근거유료도로 전체 연장유료도로 도로_연장유료도로 터널_개소유료도로 터널_연장유료도로 교량_개소유료도로 교량_연장비고
090168315041004사봉~내서<NA>02003-02-202003-02-202003-02-20<NA>진주시 사봉면 무촌리마산시 내서읍 중리진주시사봉면 함안군군북면 가야읍산인면마산시내서읍37251.029031.08220029031.027850.40000000000001111810000.0111180.6008.06.00.02.042.55.030.00.015795.013236.00.029031.029031.029031.029031.0000027850.427850.40.00.0001659682.1735783.033181.1890718.0521411161110001010468929.0164701.091730.0162610.0<NA><NA><NA>0<NA>000000<NA>
1100168315041003대방~악양<NA>02003-02-202003-02-202003-02-20<NA>경상남도 사천시 대방동경상남도 하동군 악양면 평사리사천시 대방 송포 하동군 진교 양보 횡천 청암 악양70828.055088.015740240052688.052208.0000000000000224800000.022480.0024000.00.00.00.00.00.00.00.052688.00.00.052688.052688.052688.052688.0315031502400240052208.052208.00.00.0000.00.00.00.02921455031121500000024931299.72819171.46737871.0663940.0<NA><NA><NA>0<NA>000000<NA>
2110168315041047악양-시천<NA>02003-02-202003-02-202003-02-20<NA>하동군 악양면 정동산청군 시천면 동당삼신봉터널, 예치터25394.025094.0300927015824.013225.022463000000224631602760000.03136.0092709.07.00.02.045.020.025.00.015824.00.00.015824.015824.015824.015824.000000.00.05455.07692.000376911.077194.00.0299717.021632120000002180.091092.0243240.08740.0<NA><NA><NA>0<NA>000000<NA>
3120168315041051어곡-단장<NA>02003-02-202003-02-202003-02-20<NA>지1077분기-양산시 어곡동지1077분기-밀양시 단장면 범도리에덴벨리리조트,밀양댐23854.023854.00023854.023352.000000000000042510000.04251.0008.06.00.02.045.020.025.00.023854.00.00.023854.023854.023854.023854.000001000.00.023344.022300.0001669777.0745758.0197444.0726575.01185428824000020368200.0281817.0626487.0447200.000001.372026428000000<NA>
4130168315041037개천-궁유<NA>02003-02-202003-02-202003-02-20<NA>고성군개천면가천리의령군궁유면압곡리남산삼거리,대사교,사봉삼거리,봉대삼거리,새골소류지44427.040167.04260660033567.032874.0000000000015586380000.09693.0066008.07.00.02.050.020.030.0270.033297.00.00.033567.033567.033567.033567.00000720.0630.032847.032937.0002415716.01703512.0268701.0443504.09357231281610010018225700.0224140.0213900.000.0<NA><NA><NA>0<NA>000000<NA>
5140168315041034유림-성산<NA>02003-02-202003-02-202003-02-20<NA>함양군 유림면 화촌창녕군 성산면 방유림면사무소,생초초등학교,구평초등학교,권빈교124333.095283.029050270892575.090618.00000000000001719570000.0171957.0027089.07.00.02.045.020.025.00.092575.00.00.092575.092575.092575.092575.0000015380.026357.055420.054410.0002252419.02018562.00.0233856.02692058240382900007056664719.01229998.012615805.06980.0<NA><NA><NA>0<NA>000000<NA>
6150168315041028원동-웅상<NA>02003-02-202003-02-202003-02-20<NA>양산시 원동면 대리양산시 상북면 내석리좌삼초교, 내원사, 영산대28761.023861.049001250011361.011047.000000000000053140000.05314.00125008.08.00.02.045.020.025.00.011361.00.00.011361.011361.011361.011361.00000860.0860.0380.0340.000693509.0449999.00.0243510.099239500000040676780.0281940.0221654.06500.0<NA><NA><NA>0<NA>000000<NA>
7160168315041024설천-창선<NA>02003-02-202003-02-202003-02-20<NA>남해군 설천면 노량리남해군 창선면 부윤리설천면사무소,진목초교,고현면사무소,서면중학교,남상126380.097520.028860439993121.092970.0000000000000131510000.013151.0043999.07.00.02.045.020.025.00.093121.00.00.093121.093121.093121.093121.0000080341.080341.012780.012780.0001873153.01606238.00.0266915.027413644135900000023030968.07210981.0498072.0162694.0<NA><NA><NA>0<NA>000000<NA>
8170168315041018사등-장목<NA>02003-02-202003-02-202003-02-20<NA>거제시 사등면 덕호리거제시 장목면 유호리죽림해수욕장, 연사교109041.094545.014496094545.094260.0000000000000122850000.012285.0009.07.50.02.045.020.025.03118.086847.04580.00.094545.094545.091427.091427.000311831185964.05137.085825.081234.0005814325.03607663.01172777.01033886.0336249106632522000011048249216.016514947.021426750.0463797.000000000000<NA>
9180168315041014화계-수곡<NA>02003-02-202003-02-202003-02-20<NA>하동군 화개면 용강리진주시 수곡면 대천리해광사,위태초교,괴정교,단암교,옥종초교북평분교,창37599.034479.03120759026889.026583.000000000001852980000.06306.0075909.07.00.02.045.020.025.00.026889.00.00.026889.026889.026889.026889.00000960.01020.06853.08399.000693509.0450177.00.0243332.03136221622000000484353.0282760.0303180.0211800.0<NA><NA><NA>0<NA>000000<NA>
식별번호관리번호관리기관도로종류노선번호노선명구간번호이력코드노선 지정(인정) 연월일도로구역 결정(변경) 연월일접도구역 지정 연월일지적고시 연월일노선시점 위치(주소)노선종점 위치(주소)주요한 경과지노선연장전용연장중용연장통행불능연장포장도로_전체연장포장도로_도로연장포장도로_터널개소(2차로)포장도로_터널연장(2차로)포장도로_터널개소(3차로)포장도로_터널연장(3차로)포장도로_터널개소(4차로)포장도로_터널연장(4차로)포장도로_터널개소(5차로이상)포장도로_터널연장(5차로이상)포장도로_터널개소(전체)포장도로_터널연장(전체)포장도로_교량개소(강교)포장도로_교량연장(강교)포장도로_교량개소(철근콘크리트교)포장도로_교량연장(철근콘크리트교)포장도로_교량개소(합성교)포장도로_교량연장(합성교)포장도로_교량개소(기타)포장도로_교량연장(기타)포장도로_교량개소(전체)포장도로_교량연장(전체)비포장도로연장미개통도로연장폭원_전체폭원_차도폭원_중앙분리대폭원_길어깨(보도)포장두께_전체포장두께_포장기층_포장슬래브포장두께_보조기층도로연장(2차로미만)도로연장(2차로_4차로미만)도로연장(4차로_6차로미만)도로연장(6차로이상)차도 연장_전체(상행)차도 연장_전체(하행)아스팔트 차도 연장(상행)아스팔트 차도 연장(하행)콘크리트 차도 연장(상행)콘크리트 차도 연장(하행)비포장 차도 연장(상행)비포장 차도 연장(하행)포장 보도(길어깨) 연장_좌포장 보도(길어깨) 연장_우비포장 보도(길어깨) 연장_좌비포장 보도(길어깨) 연장_우자전거도로 연장_좌자전거도로 연장_우도로 면적_전체도로 면적_국유지도로 면적_공유지도로 면적_사유지곡선반경(100m 미만)곡선반경(100 이상_200m 미만)곡선반경(200 이상 _300m 미만)곡선반경(300 이상 _460m 미만)곡선반경(460 이상 _700m 미만)곡선반경(700m 이상)교차_육교교차_지하도교차_철도(과선)교차_철도(가도)교차_도로(평면)교차_도로(입체)종단경사(3퍼센트미만)_개소종단경사(3퍼센트미만)_연장종단경사(3_5퍼센트미만)_개소종단경사(3_5퍼센트미만)_연장종단경사(5_10퍼센트미만)_개소종단경사(5_10퍼센트미만)_연장종단경사(10퍼센트이상)_개소종단경사(10퍼센트이상)_연장유료도로_관리자유료도로_요금징수_시작일자유료도로_요금징수_종료일자유료도로_요금징수 시설수유료도로_요금징수근거유료도로 전체 연장유료도로 도로_연장유료도로 터널_개소유료도로 터널_연장유료도로 교량_개소유료도로 교량_연장비고
344310420001168315041042진영~봉황<NA>02003-02-102003-02-102003-02-10<NA>김해시 진영읍 설창리김해시 봉황동장유면20620.020620.00020620.020557.000000000000026300118.0463.00020.014.50.05.559.024.035.00.019931.0609.00.020620.020620.020620.020620.0000020322.020322.00.00.0000.00.00.00.0827171510110000408418200.082160.02180.000.0<NA><NA><NA>0<NA>000000<NA>
35446000021683150760무안-부산19020131031201310312013103120131031경상남도 양산시 동면 개곡리부산광역시 기장군 정관면 월평리동면,정관면2400.02400.0<NA>02400.02120.000000000001280000000.01280.00019.014.01.04.060.025.035.00.02400.00.00.02400.02400.02400.02400.000002400.02400.00.00.000271363.0113580.0157783.00.000001100000031980.01420.000.000.0<NA><NA><NA>0<NA>000000<NA>
36101683150467통영~칠곡<NA>02003-02-202003-02-202003-02-20<NA>통영시 도남동창녕군 이방면 송곡리통영시 도남동 광도면 죽림리 창녕군 이방면 현창리129712.018707.0<NA>240016307.015356.5133900000013390026120000.02611.5024009.07.00.02.045.010.030.0316.015991.00.00.016307.016307.016307.016307.0000015356.515356.50.00.000699830.7346520.0255341.797969.02226161483000000897880.0182040.0141887.000.0<NA><NA><NA>0<NA>000000<NA>
37201683150437남원~거창<NA>02003-02-202003-02-202003-02-20<NA>함양군 백전면 오천리거창군 마리면 율리함양군 백전면 서하면 서상면 거창군 북상면 마리면57882.051482.06400051482.050824.5000000000000196580000.019657.5008.06.00.02.063.07.550.02723.048759.00.00.051482.051482.051482.051482.00048048050824.550824.50.00.0001563846.3749580.3473320.0340946.01751383831161500000312214808.0526290.0496595.0203580.0<NA><NA><NA>0<NA>000000<NA>
38301683150430대구~창원<NA>02003-02-202003-02-202003-02-20<NA>밀양시 청도면 요고리창원시 동읍 용잠리창원시 동읍 창녕군 부곡면 밀양시 무안면43231.042733.0498830034433.033230.8000000000000612020000.061202.2083008.06.00.02.050.010.035.02992.031441.00.00.034433.034433.034433.034433.0000033230.833230.80.00.000946540.0538665.0228008.0179867.05548172471700010018728163.0181830.05400.000.0<NA><NA><NA>0<NA>000000<NA>
3940168315041026오부~대양<NA>02003-02-202003-02-202003-02-20<NA>산청군 오부면 양촌리합천군 대양면 정양리산청군 오부면 차황면 합천군 대병면 대양면45040.039900.05140646333437.033254.100000000000081830000.08182.9064637.05.50.01.550.012.537.51700.031737.00.00.033437.033437.033437.033437.0000033254.133254.10.00.0000.0459418.5346067.11331621.3110971891100000081357.243580.061320.03453.24<NA><NA><NA>0<NA>000000<NA>
4050168315041023간전~함양<NA>02003-02-202003-02-202003-02-20<NA>하동군 화개면 탑리함양군 함양읍 구룡리하동군 화개면 함양군 마천면 함양읍55627.053127.025002140031727.031447.000000000000072800000.07280.00214008.06.00.02.035.015.020.00.031727.00.00.031727.031727.031727.031727.0000031447.031447.00.00.000756745.1159116.1342417.0255212.018086161044000000182306.03111251.0212260.06712409.92<NA><NA><NA>0<NA>000000<NA>
4160168315041011가야~대양<NA>02003-02-202003-02-202003-02-20<NA>경상남도 함안군 가야읍 말산리경상남도 합천군 대양면 대목리함안군 가야읍 의령군 정곡면 합천군 대양면42849.040889.01960040889.040041.3000000000000128480000.012847.7000.00.00.00.00.00.00.00.039864.01025.00.040889.040889.040889.040889.0000040041.340041.30.00.0001661221.0645299.2804838.8211083.014163342017900000014920413.0373886.656696972.0120.0<NA><NA><NA>0<NA>000000<NA>
4270168315041010하이~동해<NA>02003-02-202003-02-202003-02-20<NA>경상남도 고성군 하이면 덕호리경상남도 고성군 동해면 양촌리고성군 하이면 하일면 삼산면 고성읍 거류면 동해면66184.063452.027321428649166.048909.3000000000000112570000.011256.70142860.00.00.00.00.00.00.02252.046914.00.00.049166.049166.049166.049166.076776741241248909.048909.00.00.0001341540.22506631.79438596.59395866.253341343724191200000223219340.47716464.3948917.0353200.0<NA><NA><NA>0<NA>000000<NA>
4380168315041005서포~단성<NA>02003-02-202003-02-202003-02-20<NA>경상남도 사천시 서포면 비토리경상남도 산청군 단성면 창촌리사천시 서포 곤양 하동군 북천 산청군 단성47378.038578.08800265635922.035232.0000000000000126900000.012690.0026560.00.00.00.00.00.00.00.035922.00.00.035922.035922.035922.035922.00048048035232.035232.00.00.0000.00.00.00.096703420490000008910520.0334063.5333552.4396000.0<NA><NA><NA>0<NA>000000<NA>