Overview

Dataset statistics

Number of variables13
Number of observations9366
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory987.9 KiB
Average record size in memory108.0 B

Variable types

Text4
Categorical5
Numeric3
DateTime1

Dataset

Description대전광역시 도로관리시스템에 등재된 도로 노선 구간 현황입니다. ※ 2022년 공공데이터 기업 매칭 지원사업으로 청년 인턴을 통해 구축·정비된 데이터입니다. 법적 효력이 없으므로 참고 목적으로만 활용하시기 바랍니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15110425/fileData.do

Alerts

지형지물부호 has constant value ""Constant
대장초기화여부 has constant value ""Constant
최대도로폭원 is highly overall correlated with 도로규모High correlation
도로종류 is highly overall correlated with 도로기능High correlation
도로기능 is highly overall correlated with 도로종류 and 1 other fieldsHigh correlation
도로규모 is highly overall correlated with 최대도로폭원 and 1 other fieldsHigh correlation
도로종류 is highly imbalanced (59.7%)Imbalance
도로기능 is highly imbalanced (54.1%)Imbalance
지리정보(WKT) has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:38:58.917296
Analysis finished2023-12-12 16:39:02.418339
Duration3.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지리정보(WKT)
Text

UNIQUE 

Distinct9366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
2023-12-13T01:39:02.731524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length996
Mean length415.12599
Min length83

Characters and Unicode

Total characters3888070
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9366 ?
Unique (%)100.0%

Sample

1st rowMULTILINESTRING ((246445.972420961 416790.7344319,246433.175720974 416801.194531866,246394.130620994 416830.650831767,246255.159921046 416923.860731421,246186.820921058 416961.880631259,246158.76092106 416974.260931197,246038.180121029 417010.951030947,245997.030321018 417021.831130869,245923.324520986 417038.640030723,245865.590720962 417049.010930617,245782.920120922 417061.89053046,245590.46092083 417094.171330104,245589.110720829 417094.377630098,245532.755620803 417103.141629996,245491.99032078 417109.201629916,245346.810920707 417131.361229649,245248.270320665 417149.420629467,245216.450520643 417154.221029405,245121.010920593 417164.381629234,245120.985920589 417164.382229234,245064.960320552 417167.070329142,245064.935320551 417167.07082914,245028.190520525 417166.841329079,244952.710120456 417161.980728961,244914.280520422 417157.881428903,244891.670720395 417154.081028867,244788.501720279 417131.772528726,244744.563120224 417117.71102867,244695.837720158 417100.343328611,244655.808320097 417086.0738
2nd rowMULTILINESTRING ((243312.378631983 403721.626881122,243064.495904101 404330.583379691,243022.95409512 404407.87341858,242999.80950289 404448.765569366,242970.363091813 404497.750981848,242884.540338102 404646.552617256,242874.775140374 404665.3131763,242868.324945086 404683.258000482,242837.101129251 404744.817204455,242805.74633198 404812.763188198,242784.8326968 404861.962589946,242759.926935166 404923.54279003,242736.675897656 404986.037968134,242721.375299583 405032.693424581,242701.799494007 405093.896793618,242682.704706521 405164.031009799,242666.145746665 405234.280216221,242654.627924486 405290.025577463,242647.190302476 405328.752384036,242633.435114623 405412.40942736,242632.244929095 405424.937381442,242632.405695714 405435.200381918,242624.903925787 405492.834781243,242615.842524562 405580.190188827,242612.106928945 405629.827578896,242608.72790073 405693.361209172,242607.478938429 405751.612796016,242609.259517208 405849.545168936,242607.465510963 405909.247805575,242610.772701009 405967.6884182
3rd rowMULTILINESTRING ((238857.521503806 409032.528229445,238859.005203806 409032.513129446,239051.119903947 409029.227129767,239160.297204026 409025.588829952,239228.712804077 409024.831930064,239357.628904183 409028.781930277,239385.383604208 409030.592330317,239459.001104266 409032.33543044,239504.0438043 409031.948130518,239625.766004394 409030.901030711,239717.52930447 409035.76543086,239738.090104492 409039.823730888,239774.625404533 409047.392630939,239781.38530454 409048.932730947,239796.345304562 409052.632530969,239803.775204569 409054.752630981,239806.195204572 409055.442730984,239808.605204577 409056.132730984,239813.315304584 409057.482630989,239819.485304588 409059.272631003,239833.215304605 409063.302631018,239846.525304627 409068.152631034,239862.525304649 409074.22263105,239865.385304652 409075.452631054,239881.775304676 409082.652731073,239895.725304701 409089.052631086,239897.125304699 409089.692631086,239898.515304702 409090.332731091,239899.935204706 409090.982731095,239916.445204728 409099.122
4th rowMULTILINESTRING ((237865.886575904 415988.08016705,237825.977220908 416028.302268518))
5th rowMULTILINESTRING ((237928.581180077 416050.249717245,237886.603833336 416090.844783877,237876.206747451 416100.899552688,237875.124655611 416107.265492073,237874.099168996 416138.938258424))
ValueCountFrequency (%)
multilinestring 9366
 
7.3%
418920.933452209 3
 
< 0.1%
415223.102864334 3
 
< 0.1%
412300.75206028 3
 
< 0.1%
423963.845885082 3
 
< 0.1%
240313.656436563 3
 
< 0.1%
418088.771584627 3
 
< 0.1%
413598.799704899 3
 
< 0.1%
416012.613158571 3
 
< 0.1%
413742.234723699 3
 
< 0.1%
Other values (118814) 119557
92.7%
2023-12-13T01:39:03.265202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 448641
11.5%
4 408108
10.5%
3 361432
9.3%
1 354024
9.1%
6 300976
7.7%
5 296237
7.6%
8 281470
7.2%
7 279102
7.2%
9 274423
7.1%
0 268064
6.9%
Other values (15) 615593
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3272477
84.2%
Other Punctuation 321109
 
8.3%
Uppercase Letter 140490
 
3.6%
Space Separator 119584
 
3.1%
Open Punctuation 18732
 
0.5%
Close Punctuation 15678
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 448641
13.7%
4 408108
12.5%
3 361432
11.0%
1 354024
10.8%
6 300976
9.2%
5 296237
9.1%
8 281470
8.6%
7 279102
8.5%
9 274423
8.4%
0 268064
8.2%
Uppercase Letter
ValueCountFrequency (%)
I 28098
20.0%
N 18732
13.3%
T 18732
13.3%
L 18732
13.3%
U 9366
 
6.7%
G 9366
 
6.7%
R 9366
 
6.7%
S 9366
 
6.7%
E 9366
 
6.7%
M 9366
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 220242
68.6%
, 100867
31.4%
Space Separator
ValueCountFrequency (%)
119584
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18732
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15678
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3747580
96.4%
Latin 140490
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 448641
12.0%
4 408108
10.9%
3 361432
9.6%
1 354024
9.4%
6 300976
8.0%
5 296237
7.9%
8 281470
7.5%
7 279102
7.4%
9 274423
7.3%
0 268064
7.2%
Other values (5) 475103
12.7%
Latin
ValueCountFrequency (%)
I 28098
20.0%
N 18732
13.3%
T 18732
13.3%
L 18732
13.3%
U 9366
 
6.7%
G 9366
 
6.7%
R 9366
 
6.7%
S 9366
 
6.7%
E 9366
 
6.7%
M 9366
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3888070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 448641
11.5%
4 408108
10.5%
3 361432
9.3%
1 354024
9.1%
6 300976
7.7%
5 296237
7.6%
8 281470
7.2%
7 279102
7.2%
9 274423
7.1%
0 268064
6.9%
Other values (15) 615593
15.8%

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
노선구간
9366 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노선구간 9366
100.0%

Length

2023-12-13T01:39:03.405429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:03.501552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노선구간 9366
100.0%

노선번호
Real number (ℝ)

Distinct9327
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4661.9943
Minimum1
Maximum9358
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size82.4 KiB
2023-12-13T01:39:03.660207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile438.25
Q12315.25
median4660.5
Q37009.75
95-th percentile8889.75
Maximum9358
Range9357
Interquartile range (IQR)4694.5

Descriptive statistics

Standard deviation2710.9193
Coefficient of variation (CV)0.58149349
Kurtosis-1.2009074
Mean4661.9943
Median Absolute Deviation (MAD)2347.5
Skewness0.0016091792
Sum43664239
Variance7349083.7
MonotonicityNot monotonic
2023-12-13T01:39:03.825837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32 11
 
0.1%
4 8
 
0.1%
251 6
 
0.1%
17 5
 
0.1%
300 5
 
0.1%
1 3
 
< 0.1%
57 3
 
< 0.1%
635 3
 
< 0.1%
35 2
 
< 0.1%
30 2
 
< 0.1%
Other values (9317) 9318
99.5%
ValueCountFrequency (%)
1 3
 
< 0.1%
4 8
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
9358 1
< 0.1%
9357 1
< 0.1%
9356 1
< 0.1%
9355 1
< 0.1%
9354 1
< 0.1%
9353 1
< 0.1%
9352 1
< 0.1%
9351 1
< 0.1%
9350 1
< 0.1%
9349 1
< 0.1%

노선명
Text

Distinct3307
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
2023-12-13T01:39:04.137982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.4113816
Min length3

Characters and Unicode

Total characters60049
Distinct characters268
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1583 ?
Unique (%)16.9%

Sample

1st row경부고속도로
2nd row통영대전고속도로
3rd row대전남부순환고속도로
4th row동서대로
5th row동서대로
ValueCountFrequency (%)
대전로 90
 
1.0%
동서대로 54
 
0.6%
도솔로 47
 
0.5%
계백로 47
 
0.5%
산내로 43
 
0.5%
대종로 38
 
0.4%
대청호수로 33
 
0.4%
우암로 32
 
0.3%
세동로 31
 
0.3%
계룡로 30
 
0.3%
Other values (3297) 8921
95.2%
2023-12-13T01:39:04.654397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 7940
 
13.2%
길 7025
 
11.7%
번 5586
 
9.3%
1 3291
 
5.5%
대 1988
 
3.3%
2 1984
 
3.3%
3 1831
 
3.0%
5 1603
 
2.7%
4 1542
 
2.6%
6 1422
 
2.4%
Other values (258) 25837
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44060
73.4%
Decimal Number 15989
 
26.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 7940
18.0%
길 7025
15.9%
번 5586
 
12.7%
대 1988
 
4.5%
동 987
 
2.2%
산 786
 
1.8%
계 716
 
1.6%
도 662
 
1.5%
서 611
 
1.4%
전 471
 
1.1%
Other values (248) 17288
39.2%
Decimal Number
ValueCountFrequency (%)
1 3291
20.6%
2 1984
12.4%
3 1831
11.5%
5 1603
10.0%
4 1542
9.6%
6 1422
8.9%
7 1197
 
7.5%
0 1072
 
6.7%
8 1039
 
6.5%
9 1008
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44060
73.4%
Common 15989
 
26.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 7940
18.0%
길 7025
15.9%
번 5586
 
12.7%
대 1988
 
4.5%
동 987
 
2.2%
산 786
 
1.8%
계 716
 
1.6%
도 662
 
1.5%
서 611
 
1.4%
전 471
 
1.1%
Other values (248) 17288
39.2%
Common
ValueCountFrequency (%)
1 3291
20.6%
2 1984
12.4%
3 1831
11.5%
5 1603
10.0%
4 1542
9.6%
6 1422
8.9%
7 1197
 
7.5%
0 1072
 
6.7%
8 1039
 
6.5%
9 1008
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44060
73.4%
ASCII 15989
 
26.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 7940
18.0%
길 7025
15.9%
번 5586
 
12.7%
대 1988
 
4.5%
동 987
 
2.2%
산 786
 
1.8%
계 716
 
1.6%
도 662
 
1.5%
서 611
 
1.4%
전 471
 
1.1%
Other values (248) 17288
39.2%
ASCII
ValueCountFrequency (%)
1 3291
20.6%
2 1984
12.4%
3 1831
11.5%
5 1603
10.0%
4 1542
9.6%
6 1422
8.9%
7 1197
 
7.5%
0 1072
 
6.7%
8 1039
 
6.5%
9 1008
 
6.3%

도로종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
면/리간 도로
6137 
지방도
2776 
일반국도
 
241
미분류
 
154
기타
 
33
Other values (3)
 
25

Length

Max length8
Median length7
Mean length5.6502242
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row고속국도
2nd row고속국도
3rd row고속국도
4th row지방도
5th row지방도

Common Values

ValueCountFrequency (%)
면/리간 도로 6137
65.5%
지방도 2776
29.6%
일반국도 241
 
2.6%
미분류 154
 
1.6%
기타 33
 
0.4%
고속국도 14
 
0.1%
시도중 일반도로 10
 
0.1%
군(구)도 1
 
< 0.1%

Length

2023-12-13T01:39:04.923425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:05.174070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
면/리간 6137
39.6%
도로 6137
39.6%
지방도 2776
17.9%
일반국도 241
 
1.6%
미분류 154
 
1.0%
기타 33
 
0.2%
고속국도 14
 
0.1%
시도중 10
 
0.1%
일반도로 10
 
0.1%
군(구)도 1
 
< 0.1%

도로기능
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
미분류
6977 
집산도로
2228 
보조간선도로
 
147
기타
 
14

Length

Max length6
Median length3
Mean length3.2834721
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row기타
3rd row기타
4th row보조간선도로
5th row보조간선도로

Common Values

ValueCountFrequency (%)
미분류 6977
74.5%
집산도로 2228
 
23.8%
보조간선도로 147
 
1.6%
기타 14
 
0.1%

Length

2023-12-13T01:39:05.558603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:05.852694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미분류 6977
74.5%
집산도로 2228
 
23.8%
보조간선도로 147
 
1.6%
기타 14
 
0.1%

도로규모
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
소로3류( ~ 8)
5006 
소로2류(8 ~ 10)
1884 
중로2류(15 ~ 20)
541 
소로1류(10 ~ 12)
540 
중로3류(12 ~ 15)
 
408
Other values (7)
987 

Length

Max length13
Median length10
Mean length11.19496
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광로2류(50 ~ 70)
2nd row대로2류(30 ~ 35)
3rd row대로2류(30 ~ 35)
4th row소로3류( ~ 8)
5th row소로3류( ~ 8)

Common Values

ValueCountFrequency (%)
소로3류( ~ 8) 5006
53.4%
소로2류(8 ~ 10) 1884
 
20.1%
중로2류(15 ~ 20) 541
 
5.8%
소로1류(10 ~ 12) 540
 
5.8%
중로3류(12 ~ 15) 408
 
4.4%
중로1류(20 ~ 25) 357
 
3.8%
대로3류(25 ~ 30) 321
 
3.4%
대로1류(35 ~ 40) 119
 
1.3%
대로2류(30 ~ 35) 76
 
0.8%
광로3류(40 ~ 50) 66
 
0.7%
Other values (2) 48
 
0.5%

Length

2023-12-13T01:39:06.101182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9364
33.3%
소로3류 5006
17.8%
8 5006
17.8%
소로2류(8 1884
 
6.7%
10 1884
 
6.7%
중로2류(15 541
 
1.9%
20 541
 
1.9%
소로1류(10 540
 
1.9%
12 540
 
1.9%
중로3류(12 408
 
1.5%
Other values (15) 2382
 
8.5%

지적고시일자
Date

Distinct80
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
Minimum1999-12-28 00:00:00
Maximum2022-06-16 00:00:00
2023-12-13T01:39:06.410601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:06.690824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시점
Text

Distinct2095
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
2023-12-13T01:39:07.037651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length8.0730301
Min length5

Characters and Unicode

Total characters75612
Distinct characters162
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique850 ?
Unique (%)9.1%

Sample

1st row부산 금정구(구서IC)/ 구서동 481-1도
2nd row경남 통영시 용남면(통영IC)/ 동달리 1410-23구
3rd row대전 유성구(서대전JC) / 원내동 474-8도
4th row삼성동458도
5th row삼성동458도
ValueCountFrequency (%)
도마동 441
 
3.6%
변동 126
 
1.0%
가양동 110
 
0.9%
유성구 110
 
0.9%
대전 102
 
0.8%
용전동 94
 
0.8%
부사동255-1도 85
 
0.7%
구도동164-51도 81
 
0.7%
성남동 78
 
0.6%
괴정동385-1도 78
 
0.6%
Other values (2209) 10805
89.2%
2023-12-13T01:39:07.574282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9355
 
12.4%
도 5653
 
7.5%
1 5232
 
6.9%
- 4853
 
6.4%
2 4111
 
5.4%
5 3874
 
5.1%
4 3843
 
5.1%
3 3538
 
4.7%
6 3117
 
4.1%
0 2911
 
3.8%
Other values (152) 29125
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34118
45.1%
Decimal Number 33809
44.7%
Dash Punctuation 4853
 
6.4%
Space Separator 2744
 
3.6%
Open Punctuation 26
 
< 0.1%
Close Punctuation 26
 
< 0.1%
Uppercase Letter 19
 
< 0.1%
Lowercase Letter 14
 
< 0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9355
27.4%
도 5653
16.6%
대 891
 
2.6%
산 778
 
2.3%
정 765
 
2.2%
마 683
 
2.0%
성 643
 
1.9%
구 639
 
1.9%
천 600
 
1.8%
용 499
 
1.5%
Other values (131) 13612
39.9%
Decimal Number
ValueCountFrequency (%)
1 5232
15.5%
2 4111
12.2%
5 3874
11.5%
4 3843
11.4%
3 3538
10.5%
6 3117
9.2%
0 2911
8.6%
7 2779
8.2%
8 2241
6.6%
9 2163
6.4%
Uppercase Letter
ValueCountFrequency (%)
N 7
36.8%
C 6
31.6%
I 3
15.8%
J 3
15.8%
Lowercase Letter
ValueCountFrequency (%)
v 7
50.0%
o 7
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 4853
100.0%
Space Separator
ValueCountFrequency (%)
2744
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41461
54.8%
Hangul 34118
45.1%
Latin 33
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9355
27.4%
도 5653
16.6%
대 891
 
2.6%
산 778
 
2.3%
정 765
 
2.2%
마 683
 
2.0%
성 643
 
1.9%
구 639
 
1.9%
천 600
 
1.8%
용 499
 
1.5%
Other values (131) 13612
39.9%
Common
ValueCountFrequency (%)
1 5232
12.6%
- 4853
11.7%
2 4111
9.9%
5 3874
9.3%
4 3843
9.3%
3 3538
8.5%
6 3117
7.5%
0 2911
7.0%
7 2779
6.7%
2744
6.6%
Other values (5) 4459
10.8%
Latin
ValueCountFrequency (%)
v 7
21.2%
o 7
21.2%
N 7
21.2%
C 6
18.2%
I 3
9.1%
J 3
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41494
54.9%
Hangul 34118
45.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9355
27.4%
도 5653
16.6%
대 891
 
2.6%
산 778
 
2.3%
정 765
 
2.2%
마 683
 
2.0%
성 643
 
1.9%
구 639
 
1.9%
천 600
 
1.8%
용 499
 
1.5%
Other values (131) 13612
39.9%
ASCII
ValueCountFrequency (%)
1 5232
12.6%
- 4853
11.7%
2 4111
9.9%
5 3874
9.3%
4 3843
9.3%
3 3538
8.5%
6 3117
7.5%
0 2911
7.0%
7 2779
6.7%
2744
6.6%
Other values (11) 4492
10.8%

종점
Text

Distinct2721
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
2023-12-13T01:39:07.905570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length8.1148836
Min length4

Characters and Unicode

Total characters76004
Distinct characters168
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1312 ?
Unique (%)14.0%

Sample

1st row서울 서초구(한남IC)/ 잠원동 77도
2nd row대전 동구 신상동(비룡JC)/ 비룡동 209-10도
3rd row대전 동구(산내JC)/ 대별동 374천
4th row가양동665도
5th row가양동665도
ValueCountFrequency (%)
도마동 441
 
3.6%
변동 127
 
1.0%
가양동 119
 
1.0%
유성구 106
 
0.9%
용전동 105
 
0.9%
삼성동458도 104
 
0.9%
대전 103
 
0.9%
학하동 98
 
0.8%
관저동 84
 
0.7%
대흥동630도 81
 
0.7%
Other values (2833) 10744
88.7%
2023-12-13T01:39:08.542539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9358
 
12.3%
1 5744
 
7.6%
도 5025
 
6.6%
- 4845
 
6.4%
2 4591
 
6.0%
3 3875
 
5.1%
4 3759
 
4.9%
5 3237
 
4.3%
6 3207
 
4.2%
2746
 
3.6%
Other values (158) 29617
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34620
45.6%
Decimal Number 33728
44.4%
Dash Punctuation 4845
 
6.4%
Space Separator 2746
 
3.6%
Close Punctuation 26
 
< 0.1%
Open Punctuation 26
 
< 0.1%
Uppercase Letter 10
 
< 0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9358
27.0%
도 5025
 
14.5%
대 1154
 
3.3%
산 1152
 
3.3%
성 659
 
1.9%
마 658
 
1.9%
용 649
 
1.9%
정 621
 
1.8%
구 513
 
1.5%
천 502
 
1.5%
Other values (140) 14329
41.4%
Decimal Number
ValueCountFrequency (%)
1 5744
17.0%
2 4591
13.6%
3 3875
11.5%
4 3759
11.1%
5 3237
9.6%
6 3207
9.5%
7 2642
7.8%
8 2410
7.1%
0 2258
 
6.7%
9 2005
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
C 5
50.0%
J 3
30.0%
I 2
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 4845
100.0%
Space Separator
ValueCountFrequency (%)
2746
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41374
54.4%
Hangul 34620
45.6%
Latin 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9358
27.0%
도 5025
 
14.5%
대 1154
 
3.3%
산 1152
 
3.3%
성 659
 
1.9%
마 658
 
1.9%
용 649
 
1.9%
정 621
 
1.8%
구 513
 
1.5%
천 502
 
1.5%
Other values (140) 14329
41.4%
Common
ValueCountFrequency (%)
1 5744
13.9%
- 4845
11.7%
2 4591
11.1%
3 3875
9.4%
4 3759
9.1%
5 3237
7.8%
6 3207
7.8%
2746
6.6%
7 2642
6.4%
8 2410
5.8%
Other values (5) 4318
10.4%
Latin
ValueCountFrequency (%)
C 5
50.0%
J 3
30.0%
I 2
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41384
54.4%
Hangul 34620
45.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9358
27.0%
도 5025
 
14.5%
대 1154
 
3.3%
산 1152
 
3.3%
성 659
 
1.9%
마 658
 
1.9%
용 649
 
1.9%
정 621
 
1.8%
구 513
 
1.5%
천 502
 
1.5%
Other values (140) 14329
41.4%
ASCII
ValueCountFrequency (%)
1 5744
13.9%
- 4845
11.7%
2 4591
11.1%
3 3875
9.4%
4 3759
9.1%
5 3237
7.8%
6 3207
7.7%
2746
6.6%
7 2642
6.4%
8 2410
5.8%
Other values (8) 4328
10.5%

노선연장
Real number (ℝ)

Distinct2053
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2068.3848
Minimum0
Maximum423200
Zeros21
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size82.4 KiB
2023-12-13T01:39:08.672107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile26
Q184
median176
Q3425.4425
95-th percentile8980
Maximum423200
Range423200
Interquartile range (IQR)341.4425

Descriptive statistics

Standard deviation10932.213
Coefficient of variation (CV)5.2853864
Kurtosis623.763
Mean2068.3848
Median Absolute Deviation (MAD)119
Skewness19.940413
Sum19372492
Variance1.1951329 × 108
MonotonicityNot monotonic
2023-12-13T01:39:08.791625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49852.0 103
 
1.1%
16500.0 53
 
0.6%
49566.0 47
 
0.5%
57.0 45
 
0.5%
78.0 44
 
0.5%
66.0 43
 
0.5%
14158.0 42
 
0.4%
86.0 40
 
0.4%
99.0 40
 
0.4%
63.0 39
 
0.4%
Other values (2043) 8870
94.7%
ValueCountFrequency (%)
0.0 21
0.2%
1.42 1
 
< 0.1%
3.52 1
 
< 0.1%
3.87 1
 
< 0.1%
3.95 1
 
< 0.1%
4.0 1
 
< 0.1%
4.17 1
 
< 0.1%
4.29 1
 
< 0.1%
4.3 1
 
< 0.1%
4.36 1
 
< 0.1%
ValueCountFrequency (%)
423200.0 2
 
< 0.1%
278650.0 3
 
< 0.1%
215250.0 1
 
< 0.1%
144561.0 1
 
< 0.1%
53970.0 4
 
< 0.1%
49852.0 103
1.1%
49566.0 47
0.5%
35226.0 5
 
0.1%
31054.0 24
 
0.3%
25784.0 16
 
0.2%

최대도로폭원
Real number (ℝ)

HIGH CORRELATION 

Distinct317
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.7821781
Minimum1
Maximum74.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size82.4 KiB
2023-12-13T01:39:08.908511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median6
Q310
95-th percentile25
Maximum74.41
Range73.41
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.7802395
Coefficient of variation (CV)0.88591229
Kurtosis7.5403429
Mean8.7821781
Median Absolute Deviation (MAD)3
Skewness2.4515855
Sum82253.88
Variance60.532127
MonotonicityNot monotonic
2023-12-13T01:39:09.031238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0 1996
21.3%
8.0 1779
19.0%
4.0 1143
12.2%
6.0 1132
12.1%
10.0 470
 
5.0%
15.0 436
 
4.7%
12.0 310
 
3.3%
20.0 247
 
2.6%
25.0 243
 
2.6%
5.0 221
 
2.4%
Other values (307) 1389
14.8%
ValueCountFrequency (%)
1.0 18
0.2%
1.13 1
 
< 0.1%
1.16 1
 
< 0.1%
1.4 1
 
< 0.1%
1.42 1
 
< 0.1%
1.44 1
 
< 0.1%
1.5 1
 
< 0.1%
1.59 1
 
< 0.1%
1.65 1
 
< 0.1%
1.7 1
 
< 0.1%
ValueCountFrequency (%)
74.41 1
 
< 0.1%
70.0 1
 
< 0.1%
55.0 12
 
0.1%
50.0 34
0.4%
40.2 1
 
< 0.1%
40.04 1
 
< 0.1%
40.0 64
0.7%
39.83 1
 
< 0.1%
38.0 3
 
< 0.1%
36.0 6
 
0.1%

대장초기화여부
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size73.3 KiB
1
9366 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 9366
100.0%

Length

2023-12-13T01:39:09.177467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:39:09.273523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9366
100.0%

Interactions

2023-12-13T01:39:01.666072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:01.071663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:01.366927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:01.766640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:01.157491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:01.455352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:01.902436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:01.246115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:39:01.555765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:39:09.324579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호도로종류도로기능도로규모지적고시일자노선연장최대도로폭원
노선번호1.0000.3340.5090.4410.9420.1880.302
도로종류0.3341.0000.9400.5900.9120.6700.505
도로기능0.5090.9401.0000.8240.9220.5680.651
도로규모0.4410.5900.8241.0000.6850.3870.976
지적고시일자0.9420.9120.9220.6851.0000.8300.606
노선연장0.1880.6700.5680.3870.8301.0000.324
최대도로폭원0.3020.5050.6510.9760.6060.3241.000
2023-12-13T01:39:09.427195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로규모도로기능도로종류
도로규모1.0000.5170.296
도로기능0.5171.0000.679
도로종류0.2960.6791.000
2023-12-13T01:39:09.518942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선연장최대도로폭원도로종류도로기능도로규모
노선번호1.000-0.0410.2880.1660.3290.202
노선연장-0.0411.0000.2180.4540.4020.161
최대도로폭원0.2880.2181.0000.2760.4810.889
도로종류0.1660.4540.2761.0000.6790.296
도로기능0.3290.4020.4810.6791.0000.517
도로규모0.2020.1610.8890.2960.5171.000

Missing values

2023-12-13T01:39:02.105756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:39:02.321944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

지리정보(WKT)지형지물부호노선번호노선명도로종류도로기능도로규모지적고시일자시점종점노선연장최대도로폭원대장초기화여부
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3MULTILINESTRING ((237865.886575904 415988.08016705,237825.977220908 416028.302268518))노선구간4동서대로지방도보조간선도로소로3류( ~ 8)2009-07-14삼성동458도가양동665도16500.03.01
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지리정보(WKT)지형지물부호노선번호노선명도로종류도로기능도로규모지적고시일자시점종점노선연장최대도로폭원대장초기화여부
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9358MULTILINESTRING ((233671.065145129 423319.183132491,233675.862935667 423322.12118181,233682.403768195 423326.125759453,233741.181539296 423359.951565168,233801.248128762 423396.649380167,233863.39192771 423435.683987154,233905.264120165 423461.291348028,233945.26936926 423484.065945234,233999.450338595 423516.349575655,234020.538717538 423525.606350579,234032.969747824 423528.902187996,234039.040365503 423529.876370134,234048.014120399 423531.316555695,234067.392965633 423533.659939515,234085.395529124 423533.227139253,234099.157369953 423531.842373651,234123.564718593 423526.043362466,234140.701925629 423520.244351272,234166.062765474 423506.4979524,234201.356344548 423477.974148784,234203.430929511 423476.230374379,234239.571920697 423445.570157191,234249.124349892 423437.345364737,234264.280355742 423424.296536652,234279.436544695 423411.247952711,234294.593527109 423398.198331166,234309.749716063 423385.149564119,234324.90572191 423372.099942579,234340.062948463 423359.051358633,234355.218954312 423346.00노선구간6002유성대로지방도보조간선도로광로3류(40 ~ 50)2010-03-31원내동394전민동462-817617.040.01
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9362MULTILINESTRING ((229738.605354561 417658.343167332,229739.902107497 417662.369168306,229746.034920035 417681.405179039,229752.167549469 417700.442166327,229755.260322924 417710.042141907,229758.300117862 417719.478177058,229761.736946497 417730.146145795,229764.211922098 417738.583157513,229765.346748768 417742.452969521,229769.643562764 417757.105984645,229769.870552505 417757.764981224,229776.37513018 417776.676968516,229782.728951018 417795.151944088))노선구간32유성대로지방도보조간선도로광로3류(40 ~ 50)2010-03-31원내동394전민동462-817617.040.01
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