Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows40
Duplicate rows (%)0.4%
Total size in memory1.6 MiB
Average record size in memory173.0 B

Variable types

Categorical9
Numeric5
Text6

Dataset

Description경기도 화성시_교통표지판에 대한 데이터로, 지형지물부호, 관리번호, 행정읍면동, 도엽번호, 관리기관, 설치일자, 위치구분, 표지판구분, 지주형식, 높이, 규격, 대장초기화여부, 비고, 도로구간번호, 공사번호, 납품업체, 로딩일자, X좌표, Y좌표 등의 항목을 제공합니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15093492/fileData.do

Alerts

Dataset has 40 (0.4%) duplicate rowsDuplicates
대장초기화여부 is highly overall correlated with 관리기관High correlation
관리기관 is highly overall correlated with X좌표 and 4 other fieldsHigh correlation
공사번호 is highly overall correlated with 관리기관High correlation
관리번호 is highly overall correlated with 도로구간번호 and 1 other fieldsHigh correlation
도로구간번호 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
X좌표 is highly overall correlated with 행정읍면동 and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with 행정읍면동 and 1 other fieldsHigh correlation
행정읍면동 is highly overall correlated with X좌표 and 2 other fieldsHigh correlation
납품업체 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
지형지물부호 is highly imbalanced (99.9%)Imbalance
관리기관 is highly imbalanced (81.8%)Imbalance
대장초기화여부 is highly imbalanced (96.2%)Imbalance
공사번호 is highly imbalanced (99.4%)Imbalance
납품업체 is highly imbalanced (53.4%)Imbalance
높이 has 4003 (40.0%) zerosZeros
도로구간번호 has 152 (1.5%) zerosZeros

Reproduction

Analysis started2023-12-12 18:12:54.090167
Analysis finished2023-12-12 18:13:00.986178
Duration6.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
교통표지판
9999 
신호등
 
1

Length

Max length5
Median length5
Mean length4.9998
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
교통표지판 9999
> 99.9%
신호등 1
 
< 0.1%

Length

2023-12-13T03:13:01.066745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:13:01.175381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통표지판 9999
> 99.9%
신호등 1
 
< 0.1%

관리번호
Real number (ℝ)

HIGH CORRELATION 

Distinct4135
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1567576 × 1013
Minimum100001
Maximum8.99919 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:13:01.272335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100001
5-th percentile200057.95
Q19.992015 × 1010
median2.15304 × 1011
Q32.2162 × 1013
95-th percentile8.99919 × 1013
Maximum8.99919 × 1013
Range8.99919 × 1013
Interquartile range (IQR)2.206208 × 1013

Descriptive statistics

Standard deviation3.5720234 × 1013
Coefficient of variation (CV)1.6562007
Kurtosis-0.39748157
Mean2.1567576 × 1013
Median Absolute Deviation (MAD)2.153039 × 1011
Skewness1.2270745
Sum2.1567576 × 1017
Variance1.2759351 × 1027
MonotonicityNot monotonic
2023-12-13T03:13:01.409723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89991900000000 799
 
8.0%
888615000000 514
 
5.1%
89991600000000 415
 
4.2%
999161000000 229
 
2.3%
82111800000000 215
 
2.1%
82162000000000 213
 
2.1%
511308000000 196
 
2.0%
215304000000 193
 
1.9%
82161800000000 186
 
1.9%
82161900000000 160
 
1.6%
Other values (4125) 6880
68.8%
ValueCountFrequency (%)
100001 1
< 0.1%
100002 1
< 0.1%
100003 1
< 0.1%
100006 1
< 0.1%
100007 1
< 0.1%
100008 1
< 0.1%
100009 1
< 0.1%
100015 1
< 0.1%
100017 1
< 0.1%
100019 1
< 0.1%
ValueCountFrequency (%)
89991900000000 799
8.0%
89991600000000 415
4.2%
82992100000000 5
 
0.1%
82992000000000 132
 
1.3%
82991700000000 4
 
< 0.1%
82162000000000 213
 
2.1%
82161900000000 160
 
1.6%
82161800000000 186
 
1.9%
82112000000000 135
 
1.4%
82111900000000 5
 
0.1%

행정읍면동
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
2116 
향남읍
1230 
남양읍
733 
봉담읍
536 
동탄6동
515 
Other values (20)
4870 

Length

Max length4
Median length3
Mean length3.3743
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2116
21.2%
향남읍 1230
12.3%
남양읍 733
 
7.3%
봉담읍 536
 
5.4%
동탄6동 515
 
5.1%
서신면 457
 
4.6%
마도면 416
 
4.2%
정남면 404
 
4.0%
송산면 358
 
3.6%
동탄1동 333
 
3.3%
Other values (15) 2902
29.0%

Length

2023-12-13T03:13:01.574687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2116
21.2%
향남읍 1230
12.3%
남양읍 733
 
7.3%
봉담읍 536
 
5.4%
동탄6동 515
 
5.1%
서신면 457
 
4.6%
마도면 416
 
4.2%
정남면 404
 
4.0%
송산면 358
 
3.6%
동탄1동 333
 
3.3%
Other values (15) 2902
29.0%
Distinct2469
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:13:01.824466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters100000
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique783 ?
Unique (%)7.8%

Sample

1st row377130855D
2nd row377130873A
3rd row376162015C
4th row376161810B
5th row377130832B
ValueCountFrequency (%)
376161471c 31
 
0.3%
376160284b 31
 
0.3%
377130261a 29
 
0.3%
376160287b 29
 
0.3%
376160286a 29
 
0.3%
376122234b 27
 
0.3%
377130739d 27
 
0.3%
376161475a 24
 
0.2%
376160653b 24
 
0.2%
376160285c 24
 
0.2%
Other values (2459) 9725
97.2%
2023-12-13T03:13:02.251790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 17091
17.1%
3 16171
16.2%
1 15363
15.4%
6 14058
14.1%
0 8497
8.5%
2 5946
 
5.9%
5 3829
 
3.8%
8 3333
 
3.3%
4 3259
 
3.3%
C 2679
 
2.7%
Other values (4) 9774
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90000
90.0%
Uppercase Letter 10000
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 17091
19.0%
3 16171
18.0%
1 15363
17.1%
6 14058
15.6%
0 8497
9.4%
2 5946
 
6.6%
5 3829
 
4.3%
8 3333
 
3.7%
4 3259
 
3.6%
9 2453
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
C 2679
26.8%
D 2548
25.5%
B 2429
24.3%
A 2344
23.4%

Most occurring scripts

ValueCountFrequency (%)
Common 90000
90.0%
Latin 10000
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 17091
19.0%
3 16171
18.0%
1 15363
17.1%
6 14058
15.6%
0 8497
9.4%
2 5946
 
6.6%
5 3829
 
4.3%
8 3333
 
3.7%
4 3259
 
3.6%
9 2453
 
2.7%
Latin
ValueCountFrequency (%)
C 2679
26.8%
D 2548
25.5%
B 2429
24.3%
A 2344
23.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 17091
17.1%
3 16171
16.2%
1 15363
15.4%
6 14058
14.1%
0 8497
8.5%
2 5946
 
5.9%
5 3829
 
3.8%
8 3333
 
3.3%
4 3259
 
3.3%
C 2679
 
2.7%
Other values (4) 9774
9.8%

관리기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9235 
도로과
 
715
화성시
 
26
교통건설과
 
20
해양수산과
 
4

Length

Max length5
Median length4
Mean length3.9283
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9235
92.3%
도로과 715
 
7.1%
화성시 26
 
0.3%
교통건설과 20
 
0.2%
해양수산과 4
 
< 0.1%

Length

2023-12-13T03:13:02.426953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:13:02.570902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9235
92.3%
도로과 715
 
7.1%
화성시 26
 
0.3%
교통건설과 20
 
0.2%
해양수산과 4
 
< 0.1%
Distinct78
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:13:02.827548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.5923
Min length1

Characters and Unicode

Total characters95923
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row1900-01-01
4th row2016-01-01
5th row2016-01-01
ValueCountFrequency (%)
1990-01-01 1602
16.8%
2016-01-01 1282
13.4%
1900-01-01 1189
12.5%
2014-01-01 743
 
7.8%
2006-10-01 514
 
5.4%
2017-01-01 458
 
4.8%
2017-12-01 375
 
3.9%
2018-01-01 312
 
3.3%
2020-01-01 282
 
3.0%
2015-01-01 242
 
2.5%
Other values (67) 2548
26.7%
2023-12-13T03:13:03.190596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 29592
30.8%
1 26018
27.1%
- 19094
19.9%
2 8857
 
9.2%
9 5000
 
5.2%
6 2647
 
2.8%
7 1468
 
1.5%
4 1153
 
1.2%
3 634
 
0.7%
8 586
 
0.6%
Other values (2) 874
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76376
79.6%
Dash Punctuation 19094
 
19.9%
Space Separator 453
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 29592
38.7%
1 26018
34.1%
2 8857
 
11.6%
9 5000
 
6.5%
6 2647
 
3.5%
7 1468
 
1.9%
4 1153
 
1.5%
3 634
 
0.8%
8 586
 
0.8%
5 421
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 19094
100.0%
Space Separator
ValueCountFrequency (%)
453
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 95923
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 29592
30.8%
1 26018
27.1%
- 19094
19.9%
2 8857
 
9.2%
9 5000
 
5.2%
6 2647
 
2.8%
7 1468
 
1.5%
4 1153
 
1.2%
3 634
 
0.7%
8 586
 
0.6%
Other values (2) 874
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 95923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 29592
30.8%
1 26018
27.1%
- 19094
19.9%
2 8857
 
9.2%
9 5000
 
5.2%
6 2647
 
2.8%
7 1468
 
1.5%
4 1153
 
1.2%
3 634
 
0.7%
8 586
 
0.6%
Other values (2) 874
 
0.9%

위치구분
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4012 
3976 
미분류
1604 
중앙
 
333
기타
 
65

Length

Max length8
Median length1
Mean length1.3676
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
4012
40.1%
3976
39.8%
미분류 1604
 
16.0%
중앙 333
 
3.3%
기타 65
 
0.7%
교통안전(기타) 10
 
0.1%

Length

2023-12-13T03:13:03.358246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:13:03.465320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4012
40.1%
3976
39.8%
미분류 1604
 
16.0%
중앙 333
 
3.3%
기타 65
 
0.7%
교통안전(기타 10
 
0.1%

표지판구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
교통안전(규제)
2982 
교통안전(지시)
2929 
교통안전(주의)
2372 
교통안전(보조)
905 
교통안전(기타)
410 
Other values (2)
402 

Length

Max length8
Median length8
Mean length7.836
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교통안전(지시)
2nd row교통안전(지시)
3rd row교통안전(주의)
4th row교통안전(보조)
5th row교통안전(지시)

Common Values

ValueCountFrequency (%)
교통안전(규제) 2982
29.8%
교통안전(지시) 2929
29.3%
교통안전(주의) 2372
23.7%
교통안전(보조) 905
 
9.0%
교통안전(기타) 410
 
4.1%
<NA> 386
 
3.9%
기타 16
 
0.2%

Length

2023-12-13T03:13:03.593485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:13:03.704296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통안전(규제 2982
29.8%
교통안전(지시 2929
29.3%
교통안전(주의 2372
23.7%
교통안전(보조 905
 
9.0%
교통안전(기타 410
 
4.1%
na 386
 
3.9%
기타 16
 
0.2%

지주형식
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단주식
3794 
견착식
3471 
미분류
1602 
<NA>
411 
기타
 
303
Other values (5)
419 

Length

Max length4
Median length3
Mean length3.0108
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단주식 3794
37.9%
견착식 3471
34.7%
미분류 1602
16.0%
<NA> 411
 
4.1%
기타 303
 
3.0%
편지식 278
 
2.8%
측주식 113
 
1.1%
복주식 20
 
0.2%
현수식 6
 
0.1%
문형식 2
 
< 0.1%

Length

2023-12-13T03:13:03.835644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:13:03.970208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단주식 3794
37.9%
견착식 3471
34.7%
미분류 1602
16.0%
na 411
 
4.1%
기타 303
 
3.0%
편지식 278
 
2.8%
측주식 113
 
1.1%
복주식 20
 
0.2%
현수식 6
 
0.1%
문형식 2
 
< 0.1%

높이
Real number (ℝ)

ZEROS 

Distinct120
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.940393
Minimum0
Maximum36
Zeros4003
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:13:04.105294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.2
Q32.8
95-th percentile5.5
Maximum36
Range36
Interquartile range (IQR)2.8

Descriptive statistics

Standard deviation1.9325668
Coefficient of variation (CV)0.9959667
Kurtosis9.4664366
Mean1.940393
Median Absolute Deviation (MAD)2.2
Skewness1.2087726
Sum19403.93
Variance3.7348145
MonotonicityNot monotonic
2023-12-13T03:13:04.245094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4003
40.0%
2.5 1041
 
10.4%
5.0 493
 
4.9%
2.7 405
 
4.0%
2.8 365
 
3.6%
3.0 315
 
3.1%
2.3 298
 
3.0%
2.1 280
 
2.8%
6.0 252
 
2.5%
2.0 238
 
2.4%
Other values (110) 2310
23.1%
ValueCountFrequency (%)
0.0 4003
40.0%
0.4 1
 
< 0.1%
0.5 1
 
< 0.1%
0.6 1
 
< 0.1%
0.7 1
 
< 0.1%
0.8 6
 
0.1%
1.0 5
 
0.1%
1.1 7
 
0.1%
1.2 11
 
0.1%
1.3 11
 
0.1%
ValueCountFrequency (%)
36.0 1
 
< 0.1%
10.0 18
 
0.2%
9.0 1
 
< 0.1%
8.5 1
 
< 0.1%
8.0 6
 
0.1%
7.7 3
 
< 0.1%
7.6 4
 
< 0.1%
7.5 11
 
0.1%
7.1 1
 
< 0.1%
7.0 55
0.5%

규격
Text

Distinct440
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:13:04.572785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length6.3722
Min length1

Characters and Unicode

Total characters63722
Distinct characters71
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)1.6%

Sample

1st row오각0.8X0.3X0.8
2nd row오각0.8X0.3X0.8
3rd row0.6
4th row□600X600
5th row¨ª600
ValueCountFrequency (%)
¨ª600 1023
 
11.1%
¨ª900 542
 
5.9%
900 391
 
4.2%
600 389
 
4.2%
오각0.6x0.2x0.6 345
 
3.7%
원형ø600 345
 
3.7%
원형 345
 
3.7%
0.6 224
 
2.4%
오각 200
 
2.2%
φ600 199
 
2.2%
Other values (376) 5204
56.5%
2023-12-13T03:13:04.981229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18550
29.1%
. 7710
12.1%
6 5918
 
9.3%
X 3959
 
6.2%
9 3762
 
5.9%
2927
 
4.6%
2720
 
4.3%
2 2060
 
3.2%
1954
 
3.1%
ª 1654
 
2.6%
Other values (61) 12508
19.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33126
52.0%
Other Letter 10401
 
16.3%
Other Punctuation 8436
 
13.2%
Uppercase Letter 4895
 
7.7%
Space Separator 2927
 
4.6%
Modifier Symbol 1654
 
2.6%
Lowercase Letter 1259
 
2.0%
Other Symbol 745
 
1.2%
Math Symbol 251
 
0.4%
Open Punctuation 12
 
< 0.1%
Other values (3) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2720
26.2%
1954
18.8%
ª 1654
15.9%
1050
 
10.1%
933
 
9.0%
874
 
8.4%
779
 
7.5%
161
 
1.5%
141
 
1.4%
21
 
0.2%
Other values (22) 114
 
1.1%
Decimal Number
ValueCountFrequency (%)
0 18550
56.0%
6 5918
 
17.9%
9 3762
 
11.4%
2 2060
 
6.2%
1 1211
 
3.7%
8 616
 
1.9%
3 339
 
1.0%
7 258
 
0.8%
5 226
 
0.7%
4 186
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
X 3959
80.9%
Ø 454
 
9.3%
Φ 248
 
5.1%
Χ 82
 
1.7%
A 76
 
1.6%
E 76
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 7710
91.4%
: 334
 
4.0%
, 183
 
2.2%
* 173
 
2.1%
/ 36
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
x 993
78.9%
a 75
 
6.0%
e 75
 
6.0%
m 74
 
5.9%
ø 42
 
3.3%
Other Symbol
ValueCountFrequency (%)
403
54.1%
157
 
21.1%
115
 
15.4%
35
 
4.7%
35
 
4.7%
Math Symbol
ValueCountFrequency (%)
× 242
96.4%
+ 9
 
3.6%
Space Separator
ValueCountFrequency (%)
2927
100.0%
Modifier Symbol
ValueCountFrequency (%)
¨ 1654
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47167
74.0%
Hangul 8747
 
13.7%
Latin 7478
 
11.7%
Greek 330
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2720
31.1%
1954
22.3%
1050
 
12.0%
933
 
10.7%
874
 
10.0%
779
 
8.9%
161
 
1.8%
141
 
1.6%
21
 
0.2%
21
 
0.2%
Other values (21) 93
 
1.1%
Common
ValueCountFrequency (%)
0 18550
39.3%
. 7710
16.3%
6 5918
 
12.5%
9 3762
 
8.0%
2927
 
6.2%
2 2060
 
4.4%
¨ 1654
 
3.5%
1 1211
 
2.6%
8 616
 
1.3%
403
 
0.9%
Other values (18) 2356
 
5.0%
Latin
ValueCountFrequency (%)
X 3959
52.9%
ª 1654
22.1%
x 993
 
13.3%
Ø 454
 
6.1%
A 76
 
1.0%
E 76
 
1.0%
a 75
 
1.0%
e 75
 
1.0%
m 74
 
1.0%
ø 42
 
0.6%
Greek
ValueCountFrequency (%)
Φ 248
75.2%
Χ 82
 
24.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49854
78.2%
Hangul 8747
 
13.7%
None 4376
 
6.9%
Geometric Shapes 745
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18550
37.2%
. 7710
15.5%
6 5918
 
11.9%
X 3959
 
7.9%
9 3762
 
7.5%
2927
 
5.9%
2 2060
 
4.1%
1 1211
 
2.4%
x 993
 
2.0%
8 616
 
1.2%
Other values (18) 2148
 
4.3%
Hangul
ValueCountFrequency (%)
2720
31.1%
1954
22.3%
1050
 
12.0%
933
 
10.7%
874
 
10.0%
779
 
8.9%
161
 
1.8%
141
 
1.6%
21
 
0.2%
21
 
0.2%
Other values (21) 93
 
1.1%
None
ValueCountFrequency (%)
ª 1654
37.8%
¨ 1654
37.8%
Ø 454
 
10.4%
Φ 248
 
5.7%
× 242
 
5.5%
Χ 82
 
1.9%
ø 42
 
1.0%
Geometric Shapes
ValueCountFrequency (%)
403
54.1%
157
 
21.1%
115
 
15.4%
35
 
4.7%
35
 
4.7%
Distinct666
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:13:05.239004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length30
Mean length5.0642
Min length1

Characters and Unicode

Total characters50642
Distinct characters300
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique363 ?
Unique (%)3.6%

Sample

1st row횡단보도
2nd row횡단보도
3rd row과속방지턱
4th row견인지역
5th row자전거전용도로
ValueCountFrequency (%)
횡단보도 1510
 
17.7%
주정차금지 513
 
6.0%
과속방지턱 473
 
5.6%
견인지역 468
 
5.5%
최고속도제한 373
 
4.4%
양보 244
 
2.9%
정차주차금지 184
 
2.2%
주정차금지,견인지역표시 157
 
1.8%
자전거및보행자겸용도로 153
 
1.8%
어린이보호구역 143
 
1.7%
Other values (637) 4304
50.5%
2023-12-13T03:13:05.659348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3517
 
6.9%
2772
 
5.5%
2420
 
4.8%
2076
 
4.1%
1860
 
3.7%
1767
 
3.5%
1659
 
3.3%
1616
 
3.2%
1521
 
3.0%
1454
 
2.9%
Other values (290) 29980
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44912
88.7%
Space Separator 2076
 
4.1%
Decimal Number 1668
 
3.3%
Other Punctuation 717
 
1.4%
Uppercase Letter 466
 
0.9%
Lowercase Letter 279
 
0.6%
Open Punctuation 216
 
0.4%
Close Punctuation 216
 
0.4%
Math Symbol 54
 
0.1%
Connector Punctuation 23
 
< 0.1%
Other values (2) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3517
 
7.8%
2772
 
6.2%
2420
 
5.4%
1860
 
4.1%
1767
 
3.9%
1659
 
3.7%
1616
 
3.6%
1521
 
3.4%
1454
 
3.2%
1300
 
2.9%
Other values (240) 25026
55.7%
Uppercase Letter
ValueCountFrequency (%)
C 122
26.2%
M 91
19.5%
T 75
16.1%
V 49
10.5%
L 24
 
5.2%
P 24
 
5.2%
K 19
 
4.1%
A 16
 
3.4%
E 16
 
3.4%
N 15
 
3.2%
Other values (3) 15
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
m 138
49.5%
x 65
23.3%
k 63
22.6%
t 4
 
1.4%
c 2
 
0.7%
s 2
 
0.7%
v 1
 
0.4%
b 1
 
0.4%
u 1
 
0.4%
o 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 651
39.0%
3 238
 
14.3%
2 164
 
9.8%
6 155
 
9.3%
5 124
 
7.4%
4 96
 
5.8%
1 85
 
5.1%
7 83
 
5.0%
8 51
 
3.1%
9 21
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 286
39.9%
/ 264
36.8%
. 117
16.3%
% 20
 
2.8%
? 15
 
2.1%
# 15
 
2.1%
Other Symbol
ValueCountFrequency (%)
4
40.0%
3
30.0%
2
20.0%
1
 
10.0%
Space Separator
ValueCountFrequency (%)
2076
100.0%
Open Punctuation
ValueCountFrequency (%)
( 216
100.0%
Close Punctuation
ValueCountFrequency (%)
) 216
100.0%
Math Symbol
ValueCountFrequency (%)
+ 54
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44912
88.7%
Common 4985
 
9.8%
Latin 745
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3517
 
7.8%
2772
 
6.2%
2420
 
5.4%
1860
 
4.1%
1767
 
3.9%
1659
 
3.7%
1616
 
3.6%
1521
 
3.4%
1454
 
3.2%
1300
 
2.9%
Other values (240) 25026
55.7%
Common
ValueCountFrequency (%)
2076
41.6%
0 651
 
13.1%
, 286
 
5.7%
/ 264
 
5.3%
3 238
 
4.8%
( 216
 
4.3%
) 216
 
4.3%
2 164
 
3.3%
6 155
 
3.1%
5 124
 
2.5%
Other values (16) 595
 
11.9%
Latin
ValueCountFrequency (%)
m 138
18.5%
C 122
16.4%
M 91
12.2%
T 75
10.1%
x 65
8.7%
k 63
8.5%
V 49
 
6.6%
L 24
 
3.2%
P 24
 
3.2%
K 19
 
2.6%
Other values (14) 75
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44859
88.6%
ASCII 5720
 
11.3%
Compat Jamo 53
 
0.1%
Box Drawing 10
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3517
 
7.8%
2772
 
6.2%
2420
 
5.4%
1860
 
4.1%
1767
 
3.9%
1659
 
3.7%
1616
 
3.6%
1521
 
3.4%
1454
 
3.2%
1300
 
2.9%
Other values (237) 24973
55.7%
ASCII
ValueCountFrequency (%)
2076
36.3%
0 651
 
11.4%
, 286
 
5.0%
/ 264
 
4.6%
3 238
 
4.2%
( 216
 
3.8%
) 216
 
3.8%
2 164
 
2.9%
6 155
 
2.7%
m 138
 
2.4%
Other values (36) 1316
23.0%
Compat Jamo
ValueCountFrequency (%)
28
52.8%
21
39.6%
4
 
7.5%
Box Drawing
ValueCountFrequency (%)
4
40.0%
3
30.0%
2
20.0%
1
 
10.0%

대장초기화여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9959 
 
41

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 9959
99.6%
41
 
0.4%

Length

2023-12-13T03:13:05.789234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:13:05.871495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9959
100.0%

비고
Text

Distinct189
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:13:06.039129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length56
Mean length15.7023
Min length1

Characters and Unicode

Total characters157023
Distinct characters220
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)0.4%

Sample

1st row동탄(2)택지개발사업 부지공사(1단계)GIS DB구축용역
2nd row동탄(2)택지개발사업 부지공사(1단계)GIS DB구축용역
3rd row
4th row화성 향남 2지구 도로 및 지하시설물 DB 구축(20170831)
5th row
ValueCountFrequency (%)
gis 2648
 
8.9%
db 2290
 
7.7%
2123
 
7.1%
도로 1973
 
6.6%
지하시설물 1621
 
5.4%
구축용역 1388
 
4.6%
화성 946
 
3.2%
구축 643
 
2.2%
향남 587
 
2.0%
구축(20170831 587
 
2.0%
Other values (322) 15093
50.5%
2023-12-13T03:13:06.400251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29619
 
18.9%
5274
 
3.4%
4769
 
3.0%
4574
 
2.9%
4508
 
2.9%
4123
 
2.6%
2 3905
 
2.5%
3834
 
2.4%
3769
 
2.4%
I 3546
 
2.3%
Other values (210) 89102
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90209
57.4%
Space Separator 29619
 
18.9%
Uppercase Letter 17456
 
11.1%
Decimal Number 12507
 
8.0%
Close Punctuation 2725
 
1.7%
Open Punctuation 2725
 
1.7%
Dash Punctuation 746
 
0.5%
Other Punctuation 598
 
0.4%
Math Symbol 319
 
0.2%
Connector Punctuation 119
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5274
 
5.8%
4769
 
5.3%
4574
 
5.1%
4508
 
5.0%
4123
 
4.6%
3834
 
4.3%
3769
 
4.2%
3005
 
3.3%
2747
 
3.0%
2678
 
3.0%
Other values (179) 50928
56.5%
Decimal Number
ValueCountFrequency (%)
2 3905
31.2%
1 2967
23.7%
0 2024
16.2%
7 1327
 
10.6%
3 947
 
7.6%
8 829
 
6.6%
9 236
 
1.9%
6 105
 
0.8%
5 92
 
0.7%
4 75
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
I 3546
20.3%
S 3505
20.1%
G 3505
20.1%
D 3421
19.6%
B 3421
19.6%
C 41
 
0.2%
H 10
 
0.1%
E 3
 
< 0.1%
A 3
 
< 0.1%
M 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 344
57.5%
, 245
41.0%
. 8
 
1.3%
* 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 265
83.1%
~ 54
 
16.9%
Space Separator
ValueCountFrequency (%)
29619
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2725
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2725
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 746
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 119
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90209
57.4%
Common 49358
31.4%
Latin 17456
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5274
 
5.8%
4769
 
5.3%
4574
 
5.1%
4508
 
5.0%
4123
 
4.6%
3834
 
4.3%
3769
 
4.2%
3005
 
3.3%
2747
 
3.0%
2678
 
3.0%
Other values (179) 50928
56.5%
Common
ValueCountFrequency (%)
29619
60.0%
2 3905
 
7.9%
1 2967
 
6.0%
) 2725
 
5.5%
( 2725
 
5.5%
0 2024
 
4.1%
7 1327
 
2.7%
3 947
 
1.9%
8 829
 
1.7%
- 746
 
1.5%
Other values (11) 1544
 
3.1%
Latin
ValueCountFrequency (%)
I 3546
20.3%
S 3505
20.1%
G 3505
20.1%
D 3421
19.6%
B 3421
19.6%
C 41
 
0.2%
H 10
 
0.1%
E 3
 
< 0.1%
A 3
 
< 0.1%
M 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90209
57.4%
ASCII 66814
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29619
44.3%
2 3905
 
5.8%
I 3546
 
5.3%
S 3505
 
5.2%
G 3505
 
5.2%
D 3421
 
5.1%
B 3421
 
5.1%
1 2967
 
4.4%
) 2725
 
4.1%
( 2725
 
4.1%
Other values (21) 7475
 
11.2%
Hangul
ValueCountFrequency (%)
5274
 
5.8%
4769
 
5.3%
4574
 
5.1%
4508
 
5.0%
4123
 
4.6%
3834
 
4.3%
3769
 
4.2%
3005
 
3.3%
2747
 
3.0%
2678
 
3.0%
Other values (179) 50928
56.5%

도로구간번호
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2405
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1127753 × 1013
Minimum0
Maximum8.99919 × 1013
Zeros152
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:13:06.532162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.1474069 × 108
Q12.503394 × 109
median9.9916122 × 1010
Q32.21619 × 1013
95-th percentile8.99919 × 1013
Maximum8.99919 × 1013
Range8.99919 × 1013
Interquartile range (IQR)2.2159397 × 1013

Descriptive statistics

Standard deviation3.5630329 × 1013
Coefficient of variation (CV)1.686423
Kurtosis-0.3468741
Mean2.1127753 × 1013
Median Absolute Deviation (MAD)9.7815803 × 1010
Skewness1.246863
Sum2.1127753 × 1017
Variance1.2695204 × 1027
MonotonicityNot monotonic
2023-12-13T03:13:06.674640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89991900000000 776
 
7.8%
89991600000000 415
 
4.2%
82162000000000 213
 
2.1%
82111700000000 211
 
2.1%
82161900000000 172
 
1.7%
82161800000000 164
 
1.6%
0 152
 
1.5%
82112000000000 135
 
1.4%
82992000000000 131
 
1.3%
12111800000000 106
 
1.1%
Other values (2395) 7525
75.2%
ValueCountFrequency (%)
0 152
1.5%
307590001 1
 
< 0.1%
307600009 2
 
< 0.1%
307790017 2
 
< 0.1%
307790018 1
 
< 0.1%
613000579 1
 
< 0.1%
613000582 1
 
< 0.1%
613000587 2
 
< 0.1%
613000589 3
 
< 0.1%
613000595 1
 
< 0.1%
ValueCountFrequency (%)
89991900000000 776
7.8%
89991600000000 415
4.2%
82992100000000 5
 
0.1%
82992000000000 131
 
1.3%
82991700000000 4
 
< 0.1%
82162000000000 213
 
2.1%
82161900000000 172
 
1.7%
82161800000000 164
 
1.6%
82112000000000 135
 
1.4%
82111900000000 5
 
0.1%

공사번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
9993 
2010000189
 
5
1
 
2

Length

Max length10
Median length1
Mean length1.0045
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
9993
99.9%
2010000189 5
 
0.1%
1 2
 
< 0.1%

Length

2023-12-13T03:13:06.801609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:13:06.890733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2010000189 5
71.4%
1 2
 
28.6%

납품업체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
7000 
새한항업
 
636
(주)한라지리정보
 
453
㈜진성이엔씨
 
394
(주)지아이에스21
 
355
Other values (11)
1162 

Length

Max length10
Median length1
Mean length2.8027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row새한항업

Common Values

ValueCountFrequency (%)
7000
70.0%
새한항업 636
 
6.4%
(주)한라지리정보 453
 
4.5%
㈜진성이엔씨 394
 
3.9%
(주)지아이에스21 355
 
3.5%
㈜한양지에스티 323
 
3.2%
(주)성원공간정보 229
 
2.3%
(주)진성이엔씨 155
 
1.6%
제일항업(주) 132
 
1.3%
지오스 97
 
1.0%
Other values (6) 226
 
2.3%

Length

2023-12-13T03:13:06.982795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
새한항업 636
21.2%
주)한라지리정보 453
15.1%
㈜진성이엔씨 394
13.1%
주)지아이에스21 355
11.8%
㈜한양지에스티 323
10.8%
주)성원공간정보 229
 
7.6%
주)진성이엔씨 155
 
5.2%
제일항업(주 132
 
4.4%
지오스 97
 
3.2%
주)우주공간정보 94
 
3.1%
Other values (5) 132
 
4.4%
Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:13:07.183393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length5.0779
Min length1

Characters and Unicode

Total characters50779
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2019-12-04
2nd row2019-12-04
3rd row
4th row2017-08-31
5th row2019-01-05
ValueCountFrequency (%)
2017-08-31 587
13.0%
2021-04-16 490
10.8%
2019-12-04 453
 
10.0%
2020-05-20 443
 
9.8%
2019-01-05 415
 
9.2%
2021-03-23 355
 
7.8%
2019-04-05 221
 
4.9%
2017-12-07 161
 
3.6%
2020-10-21 133
 
2.9%
2017-12-29 112
 
2.5%
Other values (66) 1161
25.6%
2023-12-13T03:13:07.479823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11151
22.0%
- 9062
17.8%
2 8637
17.0%
1 7119
14.0%
5469
10.8%
8 1630
 
3.2%
3 1621
 
3.2%
9 1471
 
2.9%
7 1359
 
2.7%
5 1351
 
2.7%
Other values (2) 1909
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36248
71.4%
Dash Punctuation 9062
 
17.8%
Space Separator 5469
 
10.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11151
30.8%
2 8637
23.8%
1 7119
19.6%
8 1630
 
4.5%
3 1621
 
4.5%
9 1471
 
4.1%
7 1359
 
3.7%
5 1351
 
3.7%
4 1348
 
3.7%
6 561
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 9062
100.0%
Space Separator
ValueCountFrequency (%)
5469
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50779
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11151
22.0%
- 9062
17.8%
2 8637
17.0%
1 7119
14.0%
5469
10.8%
8 1630
 
3.2%
3 1621
 
3.2%
9 1471
 
2.9%
7 1359
 
2.7%
5 1351
 
2.7%
Other values (2) 1909
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50779
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11151
22.0%
- 9062
17.8%
2 8637
17.0%
1 7119
14.0%
5469
10.8%
8 1630
 
3.2%
3 1621
 
3.2%
9 1471
 
2.9%
7 1359
 
2.7%
5 1351
 
2.7%
Other values (2) 1909
 
3.8%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct9289
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194172.3
Minimum166217.66
Maximum212266.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:13:07.601019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum166217.66
5-th percentile174244.31
Q1184371.42
median193423.45
Q3205491.03
95-th percentile209798.64
Maximum212266.1
Range46048.438
Interquartile range (IQR)21119.605

Descriptive statistics

Standard deviation11380.135
Coefficient of variation (CV)0.058608438
Kurtosis-1.0519903
Mean194172.3
Median Absolute Deviation (MAD)9889.7023
Skewness-0.18723528
Sum1.941723 × 109
Variance1.2950748 × 108
MonotonicityNot monotonic
2023-12-13T03:13:07.712656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209790.84 4
 
< 0.1%
197017.942 4
 
< 0.1%
182692.941 4
 
< 0.1%
191982.331 3
 
< 0.1%
181377.896 3
 
< 0.1%
185123.159 3
 
< 0.1%
210271.494 3
 
< 0.1%
180826.316 3
 
< 0.1%
193044.397 3
 
< 0.1%
181729.574 3
 
< 0.1%
Other values (9279) 9967
99.7%
ValueCountFrequency (%)
166217.662 1
< 0.1%
166219.491 1
< 0.1%
166272.172 1
< 0.1%
166273.981 1
< 0.1%
166290.071 1
< 0.1%
166294.023 1
< 0.1%
166294.054 1
< 0.1%
166295.843 1
< 0.1%
166298.72 1
< 0.1%
166353.275 1
< 0.1%
ValueCountFrequency (%)
212266.1 1
< 0.1%
212212.83 1
< 0.1%
212034.77 1
< 0.1%
212034.559 1
< 0.1%
212034.391 2
< 0.1%
212022.18 1
< 0.1%
211975.343 1
< 0.1%
211975.254 1
< 0.1%
211974.235 1
< 0.1%
211969.584 1
< 0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct9284
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean508903.09
Minimum490912.41
Maximum521801.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:13:07.820156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum490912.41
5-th percentile498441.1
Q1505591.45
median509739.5
Q3512666.38
95-th percentile518351.84
Maximum521801.03
Range30888.62
Interquartile range (IQR)7074.928

Descriptive statistics

Standard deviation5953.2473
Coefficient of variation (CV)0.011698195
Kurtosis-0.0042088891
Mean508903.09
Median Absolute Deviation (MAD)3185.1227
Skewness-0.45777048
Sum5.0890309 × 109
Variance35441154
MonotonicityNot monotonic
2023-12-13T03:13:07.931432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
521384.669 4
 
< 0.1%
506300.786 4
 
< 0.1%
506326.394 4
 
< 0.1%
493477.056 3
 
< 0.1%
492551.379 3
 
< 0.1%
507759.9714 3
 
< 0.1%
504036.955 3
 
< 0.1%
492810.889 3
 
< 0.1%
506940.3799 3
 
< 0.1%
507340.7474 3
 
< 0.1%
Other values (9274) 9967
99.7%
ValueCountFrequency (%)
490912.41 1
< 0.1%
490979.8 1
< 0.1%
491022.41 1
< 0.1%
491198.07 1
< 0.1%
491226.97 1
< 0.1%
491778.48 1
< 0.1%
491857.99 1
< 0.1%
491861.1 1
< 0.1%
491861.91 1
< 0.1%
491863.4 1
< 0.1%
ValueCountFrequency (%)
521801.0304 2
< 0.1%
521777.9511 1
 
< 0.1%
521426.5631 1
 
< 0.1%
521384.669 4
< 0.1%
521364.2 1
 
< 0.1%
521335.02 1
 
< 0.1%
521277.17 1
 
< 0.1%
521269.968 1
 
< 0.1%
521248.301 1
 
< 0.1%
521247.992 1
 
< 0.1%

Interactions

2023-12-13T03:12:59.750554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:57.460694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.035941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.681124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.256191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.837317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:57.579113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.144391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.805585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.352419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.950903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:57.706458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.274416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.933942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.458413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:13:00.053836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:57.827365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.401295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.053110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.550868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:13:00.159688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:57.922121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.544585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.161994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:59.655246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:13:08.023631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지형지물부호관리번호행정읍면동관리기관설치일자위치구분표지판구분지주형식높이대장초기화여부도로구간번호공사번호납품업체로딩일자X좌표Y좌표
지형지물부호1.0000.0850.0000.2750.3820.0000.0590.0000.0000.0000.0000.0000.0670.3090.0000.000
관리번호0.0851.0000.6560.5190.9440.3880.3090.3980.2520.0530.9710.0000.9830.9790.4530.425
행정읍면동0.0000.6561.0000.8930.9570.4850.3900.5270.3110.2770.6780.0890.7340.9020.9540.881
관리기관0.2750.5190.8931.0000.9970.0000.0970.1860.000NaN0.489NaN0.5280.9970.9610.734
설치일자0.3820.9440.9570.9971.0000.8040.5840.7980.5141.0000.9041.0000.9770.9940.9250.899
위치구분0.0000.3880.4850.0000.8041.0000.4740.7100.1700.1080.2200.0000.3510.4820.3050.280
표지판구분0.0590.3090.3900.0970.5840.4741.0000.4460.2430.3830.1820.0000.2770.4550.2500.219
지주형식0.0000.3980.5270.1860.7980.7100.4461.0000.4800.1400.3260.0000.3620.5750.3610.326
높이0.0000.2520.3110.0000.5140.1700.2430.4801.0000.0330.2220.0000.4300.4230.2010.243
대장초기화여부0.0000.0530.277NaN1.0000.1080.3830.1400.0331.0000.0340.0000.0210.0000.2540.138
도로구간번호0.0000.9710.6780.4890.9040.2200.1820.3260.2220.0341.0000.0000.9570.9660.4360.427
공사번호0.0000.0000.089NaN1.0000.0000.0000.0000.0000.0000.0001.0000.0000.8950.0580.095
납품업체0.0670.9830.7340.5280.9770.3510.2770.3620.4300.0210.9570.0001.0000.9910.6880.722
로딩일자0.3090.9790.9020.9970.9940.4820.4550.5750.4230.0000.9660.8950.9911.0000.8930.891
X좌표0.0000.4530.9540.9610.9250.3050.2500.3610.2010.2540.4360.0580.6880.8931.0000.776
Y좌표0.0000.4250.8810.7340.8990.2800.2190.3260.2430.1380.4270.0950.7220.8910.7761.000
2023-12-13T03:13:08.426639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대장초기화여부표지판구분행정읍면동지형지물부호관리기관위치구분납품업체공사번호지주형식
대장초기화여부1.0000.2760.2190.0001.0000.0770.0160.0000.140
표지판구분0.2761.0000.1670.0430.0790.1870.1360.0000.240
행정읍면동0.2190.1671.0000.0000.8070.2580.3400.0410.230
지형지물부호0.0000.0430.0001.0000.1830.0000.0530.0000.000
관리기관1.0000.0790.8070.1831.0000.0000.3671.0000.152
위치구분0.0770.1870.2580.0000.0001.0000.1770.0000.448
납품업체0.0160.1360.3400.0530.3670.1771.0000.0000.158
공사번호0.0000.0000.0410.0001.0000.0000.0001.0000.000
지주형식0.1400.2400.2300.0000.1520.4480.1580.0001.000
2023-12-13T03:13:08.536993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호높이도로구간번호X좌표Y좌표지형지물부호행정읍면동관리기관위치구분표지판구분지주형식대장초기화여부공사번호납품업체
관리번호1.0000.1610.7040.014-0.1080.0610.3870.4470.1490.1160.2100.0380.0000.941
높이0.1611.0000.0440.2070.1780.0000.1520.0000.1080.1570.3310.0210.0000.213
도로구간번호0.7040.0441.000-0.0600.0190.0000.3430.4180.1320.1090.1780.0360.0000.853
X좌표0.0140.207-0.0601.000-0.0040.0000.7700.7360.1650.1340.1730.1950.0340.353
Y좌표-0.1080.1780.019-0.0041.0000.0000.5750.5680.1510.1170.1540.1060.0560.384
지형지물부호0.0610.0000.0000.0000.0001.0000.0000.1830.0000.0430.0000.0000.0000.053
행정읍면동0.3870.1520.3430.7700.5750.0001.0000.8070.2580.1670.2300.2190.0410.340
관리기관0.4470.0000.4180.7360.5680.1830.8071.0000.0000.0790.1521.0001.0000.367
위치구분0.1490.1080.1320.1650.1510.0000.2580.0001.0000.1870.4480.0770.0000.177
표지판구분0.1160.1570.1090.1340.1170.0430.1670.0790.1871.0000.2400.2760.0000.136
지주형식0.2100.3310.1780.1730.1540.0000.2300.1520.4480.2401.0000.1400.0000.158
대장초기화여부0.0380.0210.0360.1950.1060.0000.2191.0000.0770.2760.1401.0000.0000.016
공사번호0.0000.0000.0000.0340.0560.0000.0411.0000.0000.0000.0000.0001.0000.000
납품업체0.9410.2130.8530.3530.3840.0530.3400.3670.1770.1360.1580.0160.0001.000

Missing values

2023-12-13T03:13:00.604549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:13:00.849906image/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

지형지물부호관리번호행정읍면동도엽번호관리기관설치일자위치구분표지판구분지주형식높이규격기재사항대장초기화여부비고도로구간번호공사번호납품업체로딩일자X좌표Y좌표
16596교통표지판89991900000000<NA>377130855D<NA>교통안전(지시)견착식0.0오각0.8X0.3X0.8횡단보도1동탄(2)택지개발사업 부지공사(1단계)GIS DB구축용역899919000000002019-12-04210917.8189508103.6565
16220교통표지판89991900000000<NA>377130873A<NA>교통안전(지시)단주식3.0오각0.8X0.3X0.8횡단보도1동탄(2)택지개발사업 부지공사(1단계)GIS DB구축용역899919000000002019-12-04209801.513507212.595
6247교통표지판200449양감면376162015C<NA>1900-01-01교통안전(주의)단주식2.50.6과속방지턱13110212026197534.089499018.689
11554교통표지판888618000000향남읍376161810B<NA>2016-01-01교통안전(보조)<NA>0.0□600X600견인지역1화성 향남 2지구 도로 및 지하시설물 DB 구축(20170831)6181000292017-08-31190977.942499869.463
13892교통표지판89991600000000<NA>377130832B<NA>2016-01-01교통안전(지시)견착식2.9¨ª600자전거전용도로189991600000000새한항업2019-01-05209711.752509361.864
5164교통표지판300313서신면376150960D<NA>1900-01-01교통안전(지시)견착식0.00.8X0.8비보호12300213004173309.529508152.97
287교통표지판200462양감면376162035A<NA>1900-01-01교통안전(주의)단주식2.50.6좌우로이중굽운도로13110212019197359.525498179.335
2249교통표지판100120봉담읍376160938C<NA>1900-01-01교통안전(주의)단주식2.5삼각형0.90횡단보도11104311032194434.925509123.277
4813교통표지판402137병점2동377130189D<NA>2006-06-20<NA>단주식2.8삼각형0.9과속방지턱1주의표지2502444151203964.415511952.13
9671교통표지판411996동탄1동377130266D<NA>2006-10-01교통안전(지시)편지식5.5사각 2.0*1.5버스전용차로12201019001207039.988512922.735
지형지물부호관리번호행정읍면동도엽번호관리기관설치일자위치구분표지판구분지주형식높이규격기재사항대장초기화여부비고도로구간번호공사번호납품업체로딩일자X좌표Y좌표
11104교통표지판999161000000마도면376160656C<NA>2016-12-01교통안전(규제)견착식0.0삼각형0.7양보1경기화성바이오밸리99916121970180019.068508157.836
12058교통표지판215304000000동탄5동377130385D<NA>2014-01-01교통안전(주의)단주식2.3삼변 : 0.9과속방지턱121530385139210960.677511907.391
12196교통표지판211617000000장안면376161720B<NA>2013-06-01교통안전(주의)단주식2.60.9x0.9x0.9좌로굽은도로1도시계획도로 소로1-2호선 개설공사 GIS DB구축21161720008186555.058499533.496
2991교통표지판99920151354<NA>376161295C<NA>1990-01-01미분류교통안전(규제)미분류0.0199920150751184120.22500319.14
6007교통표지판300155비봉면376160325C<NA>1900-01-01교통안전(규제)편지식7.5사각형어린이보호구역 속도제한3012800113020188554.982515212.002
18246교통표지판82161900000000양감면376161588D<NA>2017-12-01교통안전(보조)견착식2.7600X600저속전기차진입금지,고속도로구간1화성향남2 주변도로 건설사업 도로 및 지하시설물 GIS DB 구축용역82161900000000(주)한라지리정보2021-04-16198916.949500854.125
2924교통표지판99920151360장안면376161289C<NA>1990-01-01미분류교통안전(지시)미분류0.0199920150478185937.97500910.29
11416교통표지판402254병점2동377130189B<NA>2006-06-20<NA>단주식2.8오각형0.6X0.2X0.6횡단보도1지시표지2502444151203907.094512066.575
16815교통표지판22161800000000비봉면376160311A<NA>2017-10-20중앙교통안전(규제)견착식0.0¨ª600최고속도제한601시도69호선 도로확포장공사 GIS DB 구축용역22161800000000(주)성원공간정보2018-08-31186766.4044516077.2861
2892교통표지판99920153156마도면376151010C<NA>1990-01-01미분류교통안전(주의)미분류0.0199920150634177381.38510878.54

Duplicate rows

Most frequently occurring

지형지물부호관리번호행정읍면동도엽번호관리기관설치일자위치구분표지판구분지주형식높이규격기재사항대장초기화여부비고도로구간번호공사번호납품업체로딩일자X좌표Y좌표# duplicates
0교통표지판206307000000<NA>377130719A<NA>2016-01-01교통안전(보조)측주식4.0사각:0.6X0.6해제1내민식이 없으므로 측주식으로 표기26307180293새한항업2019-04-05208018.753510570.0712
1교통표지판206307000000<NA>377130719C<NA>2016-01-01교통안전(보조)측주식4.0사각:0.6X0.6해제1내민식이 없으므로 측주식으로 표기26307190442새한항업2019-04-05208185.921510322.4252
2교통표지판211619000000장안면376161854A<NA>2011-06-01교통안전(규제)견착식0.0900X31장안면 독정리 247-2번지 원인자 공사21161854008188190.437497152.5652
3교통표지판211621000000<NA>376162117D<NA>2013-01-01교통안전(규제)단주식3.81.2x1.2x1.2천천히1이화-석천간(2공구)도로확포장공사 GIS DB 구축 사업21162129001180826.316493477.0562
4교통표지판211621000000<NA>376162117D<NA>2013-01-01교통안전(주의)단주식2.81.2x1.2x1.2과속방지턱1이화-석천간(2공구)도로확포장공사 GIS DB 구축 사업21162129001180847.152493480.5312
5교통표지판211621000000<NA>376162117D<NA>2013-01-01교통안전(주의)단주식2.81.2x1.2x1.2과속방지턱1이화-석천간(2공구)도로확포장공사 GIS DB 구축 사업21162129001180862.108493496.2732
6교통표지판211621000000<NA>376162118C<NA>2013-01-01교통안전(주의)단주식3.81.2x1.2x1.2과속방지턱1이화-석천간(2공구)도로확포장공사 GIS DB 구축 사업21162129001181065.261493475.3572
7교통표지판211621000000<NA>376162118C<NA>2013-01-01교통안전(주의)단주식2.81.2x1.2x1.2과속방지턱1이화-석천간(2공구)도로확포장공사 GIS DB 구축 사업21162129001181020.06493480.5022
8교통표지판211621000000<NA>376162118C<NA>2013-01-01교통안전(주의)단주식2.81.2x1.2x1.2과속방지턱1이화-석천간(2공구)도로확포장공사 GIS DB 구축 사업21162129001181077.654493491.0582
9교통표지판211621000000<NA>376162118D<NA>2013-01-01교통안전(규제)단주식3.81.2x1.2x1.2양보1이화-석천간(2공구)도로확포장공사 GIS DB 구축 사업21162129001181278.156493523.6242