Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells13305
Missing cells (%)10.2%
Duplicate rows18
Duplicate rows (%)0.2%
Total size in memory1.1 MiB
Average record size in memory117.0 B

Variable types

Categorical5
Numeric4
Text4

Dataset

Description경기도_도로대장 전산화 시스템_표지
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=A1RRL99FJ3GCPZAEQ8F134087733&infSeq=1

Alerts

관리기관 has constant value ""Constant
Dataset has 18 (0.2%) duplicate rowsDuplicates
설치형식 is highly imbalanced (50.3%)Imbalance
설치일자 has 4606 (46.1%) missing valuesMissing
비고 has 2038 (20.4%) missing valuesMissing
입력일 has 614 (6.1%) missing valuesMissing
사진 파일 has 6047 (60.5%) missing valuesMissing
위치?시점 is highly skewed (γ1 = 38.68066221)Skewed

Reproduction

Analysis started2023-12-10 21:06:17.598270
Analysis finished2023-12-10 21:06:20.520519
Duration2.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 10000
100.0%

Length

2023-12-11T06:06:20.576920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:06:20.656607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
100.0%

노선번호
Real number (ℝ)

Distinct51
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean257.0302
Minimum23
Maximum391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:06:20.746142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile56
Q198
median317
Q3345
95-th percentile383
Maximum391
Range368
Interquartile range (IQR)247

Descriptive statistics

Standard deviation125.46014
Coefficient of variation (CV)0.48811439
Kurtosis-1.1880494
Mean257.0302
Median Absolute Deviation (MAD)43
Skewness-0.7772363
Sum2570302
Variance15740.246
MonotonicityNot monotonic
2023-12-11T06:06:20.874159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98 553
 
5.5%
78 479
 
4.8%
56 393
 
3.9%
318 355
 
3.5%
309 346
 
3.5%
333 344
 
3.4%
23 327
 
3.3%
387 324
 
3.2%
322 322
 
3.2%
86 287
 
2.9%
Other values (41) 6270
62.7%
ValueCountFrequency (%)
23 327
3.3%
39 65
 
0.7%
56 393
3.9%
57 259
2.6%
70 244
2.4%
78 479
4.8%
82 228
2.3%
84 50
 
0.5%
86 287
2.9%
88 155
 
1.6%
ValueCountFrequency (%)
391 169
1.7%
387 324
3.2%
383 72
 
0.7%
379 57
 
0.6%
376 40
 
0.4%
375 153
1.5%
372 233
2.3%
371 194
1.9%
368 247
2.5%
367 99
 
1.0%

구간번호
Real number (ℝ)

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.2044
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:06:21.004250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q38
95-th percentile15
Maximum99
Range98
Interquartile range (IQR)6

Descriptive statistics

Standard deviation13.442287
Coefficient of variation (CV)1.8658441
Kurtosis38.152669
Mean7.2044
Median Absolute Deviation (MAD)3
Skewness6.0398141
Sum72044
Variance180.69509
MonotonicityNot monotonic
2023-12-11T06:06:21.171486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1768
17.7%
3 1054
10.5%
4 1030
10.3%
5 1012
10.1%
2 1003
10.0%
6 813
8.1%
7 808
8.1%
8 517
 
5.2%
9 401
 
4.0%
10 328
 
3.3%
Other values (16) 1266
12.7%
ValueCountFrequency (%)
1 1768
17.7%
2 1003
10.0%
3 1054
10.5%
4 1030
10.3%
5 1012
10.1%
6 813
8.1%
7 808
8.1%
8 517
 
5.2%
9 401
 
4.0%
10 328
 
3.3%
ValueCountFrequency (%)
99 166
1.7%
97 25
 
0.2%
26 22
 
0.2%
24 26
 
0.3%
23 54
 
0.5%
22 8
 
0.1%
21 13
 
0.1%
20 25
 
0.2%
18 34
 
0.3%
17 2
 
< 0.1%

이력코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5707 
1
3384 
2
752 
3
 
152
4
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 5707
57.1%
1 3384
33.8%
2 752
 
7.5%
3 152
 
1.5%
4 5
 
0.1%

Length

2023-12-11T06:06:21.321131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:06:21.415628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5707
57.1%
1 3384
33.8%
2 752
 
7.5%
3 152
 
1.5%
4 5
 
< 0.1%

위치?시점
Real number (ℝ)

SKEWED 

Distinct5863
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0217965
Minimum0
Maximum7252
Zeros21
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:06:21.532131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.234
Q11.775
median4.0025
Q37.093
95-th percentile12.03015
Maximum7252
Range7252
Interquartile range (IQR)5.318

Descriptive statistics

Standard deviation140.55633
Coefficient of variation (CV)15.579639
Kurtosis1626.8534
Mean9.0217965
Median Absolute Deviation (MAD)2.5275
Skewness38.680662
Sum90217.965
Variance19756.083
MonotonicityNot monotonic
2023-12-11T06:06:21.691092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
 
0.2%
0.02 20
 
0.2%
4.26 12
 
0.1%
0.08 12
 
0.1%
0.04 12
 
0.1%
0.8 11
 
0.1%
1.5 11
 
0.1%
2.56 9
 
0.1%
2.96 9
 
0.1%
1.12 9
 
0.1%
Other values (5853) 9874
98.7%
ValueCountFrequency (%)
0.0 21
0.2%
0.001 2
 
< 0.1%
0.002 1
 
< 0.1%
0.003 1
 
< 0.1%
0.004 1
 
< 0.1%
0.005 5
 
0.1%
0.006 2
 
< 0.1%
0.007 1
 
< 0.1%
0.008 8
 
0.1%
0.009 2
 
< 0.1%
ValueCountFrequency (%)
7252.0 1
< 0.1%
6150.0 1
< 0.1%
5877.0 1
< 0.1%
4306.0 1
< 0.1%
4150.0 1
< 0.1%
3940.0 1
< 0.1%
3052.0 1
< 0.1%
2193.0 1
< 0.1%
1518.0 1
< 0.1%
1488.0 1
< 0.1%

위치?방향
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상행
4941 
하행
4894 
중앙
 
118
횡단
 
47

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중앙
2nd row상행
3rd row상행
4th row하행
5th row하행

Common Values

ValueCountFrequency (%)
상행 4941
49.4%
하행 4894
48.9%
중앙 118
 
1.2%
횡단 47
 
0.5%

Length

2023-12-11T06:06:21.861709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:06:21.979470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상행 4941
49.4%
하행 4894
48.9%
중앙 118
 
1.2%
횡단 47
 
0.5%

표지 종류
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주의표지
2416 
규제표지
1793 
교통기타
1269 
기타표지
1108 
지시표지
907 
Other values (10)
2507 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row기타표지
2nd row지시표지
3rd row기타표지
4th row규제표지
5th row방향표지

Common Values

ValueCountFrequency (%)
주의표지 2416
24.2%
규제표지 1793
17.9%
교통기타 1269
12.7%
기타표지 1108
11.1%
지시표지 907
 
9.1%
안내기타 813
 
8.1%
방향표지 797
 
8.0%
보조표지 649
 
6.5%
이정표지 91
 
0.9%
경계표지 83
 
0.8%
Other values (5) 74
 
0.7%

Length

2023-12-11T06:06:22.113667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주의표지 2416
24.2%
규제표지 1793
17.9%
교통기타 1269
12.7%
기타표지 1108
11.1%
지시표지 907
 
9.1%
안내기타 813
 
8.1%
방향표지 797
 
8.0%
보조표지 649
 
6.5%
이정표지 91
 
0.9%
경계표지 83
 
0.8%
Other values (5) 74
 
0.7%

표지 명칭
Text

Distinct187
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:06:22.469321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.0248
Min length2

Characters and Unicode

Total characters50248
Distinct characters198
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)0.4%

Sample

1st row곡선유도
2nd row자전거및보행자겸용도로
3rd row기타
4th row양보표지
5th row1지명방향표지
ValueCountFrequency (%)
곡선유도 1200
 
12.0%
횡단보도 1006
 
10.1%
경찰청제정표지 829
 
8.3%
최고속도제한 588
 
5.9%
기타 419
 
4.2%
교통안내표지기타 371
 
3.7%
서행 336
 
3.4%
안내표지기타 325
 
3.2%
반사경 299
 
3.0%
새주소안내 295
 
2.9%
Other values (177) 4332
43.3%
2023-12-11T06:06:22.988881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 3670
 
7.3%
지 3557
 
7.1%
표 2880
 
5.7%
로 1616
 
3.2%
제 1583
 
3.2%
보 1374
 
2.7%
유 1279
 
2.5%
기 1270
 
2.5%
선 1250
 
2.5%
곡 1200
 
2.4%
Other values (188) 30569
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48985
97.5%
Decimal Number 814
 
1.6%
Other Punctuation 271
 
0.5%
Uppercase Letter 66
 
0.1%
Math Symbol 38
 
0.1%
Open Punctuation 34
 
0.1%
Close Punctuation 34
 
0.1%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 3670
 
7.5%
지 3557
 
7.3%
표 2880
 
5.9%
로 1616
 
3.3%
제 1583
 
3.2%
보 1374
 
2.8%
유 1279
 
2.6%
기 1270
 
2.6%
선 1250
 
2.6%
곡 1200
 
2.4%
Other values (169) 29306
59.8%
Decimal Number
ValueCountFrequency (%)
2 467
57.4%
3 227
27.9%
1 118
 
14.5%
0 1
 
0.1%
4 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
T 19
28.8%
N 13
19.7%
L 13
19.7%
A 13
19.7%
Y 8
12.1%
Other Punctuation
ValueCountFrequency (%)
, 152
56.1%
. 119
43.9%
Other Symbol
ValueCountFrequency (%)
┤ 1
50.0%
├ 1
50.0%
Math Symbol
ValueCountFrequency (%)
+ 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48985
97.5%
Common 1197
 
2.4%
Latin 66
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 3670
 
7.5%
지 3557
 
7.3%
표 2880
 
5.9%
로 1616
 
3.3%
제 1583
 
3.2%
보 1374
 
2.8%
유 1279
 
2.6%
기 1270
 
2.6%
선 1250
 
2.6%
곡 1200
 
2.4%
Other values (169) 29306
59.8%
Common
ValueCountFrequency (%)
2 467
39.0%
3 227
19.0%
, 152
 
12.7%
. 119
 
9.9%
1 118
 
9.9%
+ 38
 
3.2%
( 34
 
2.8%
) 34
 
2.8%
- 3
 
0.3%
1
 
0.1%
Other values (4) 4
 
0.3%
Latin
ValueCountFrequency (%)
T 19
28.8%
N 13
19.7%
L 13
19.7%
A 13
19.7%
Y 8
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48868
97.3%
ASCII 1261
 
2.5%
Compat Jamo 117
 
0.2%
Box Drawing 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 3670
 
7.5%
지 3557
 
7.3%
표 2880
 
5.9%
로 1616
 
3.3%
제 1583
 
3.2%
보 1374
 
2.8%
유 1279
 
2.6%
기 1270
 
2.6%
선 1250
 
2.6%
곡 1200
 
2.5%
Other values (166) 29189
59.7%
ASCII
ValueCountFrequency (%)
2 467
37.0%
3 227
18.0%
, 152
 
12.1%
. 119
 
9.4%
1 118
 
9.4%
+ 38
 
3.0%
( 34
 
2.7%
) 34
 
2.7%
T 19
 
1.5%
N 13
 
1.0%
Other values (7) 40
 
3.2%
Compat Jamo
ValueCountFrequency (%)
ㅏ 68
58.1%
ㅓ 46
39.3%
ㅜ 3
 
2.6%
Box Drawing
ValueCountFrequency (%)
┤ 1
50.0%
├ 1
50.0%

설치형식
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단주식
6605 
부착식
1298 
편지식
718 
측주식
 
389
복주식
 
341
Other values (7)
 
649

Length

Max length4
Median length3
Mean length2.9931
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row단주식
2nd row부착식
3rd row단주식
4th row단주식
5th row복주식

Common Values

ValueCountFrequency (%)
단주식 6605
66.0%
부착식 1298
 
13.0%
편지식 718
 
7.2%
측주식 389
 
3.9%
복주식 341
 
3.4%
현수식 310
 
3.1%
내민식 162
 
1.6%
기타 110
 
1.1%
<NA> 25
 
0.2%
문형식 19
 
0.2%
Other values (2) 23
 
0.2%

Length

2023-12-11T06:06:23.148808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단주식 6605
66.0%
부착식 1298
 
13.0%
편지식 718
 
7.2%
측주식 389
 
3.9%
복주식 341
 
3.4%
현수식 310
 
3.1%
내민식 162
 
1.6%
기타 110
 
1.1%
na 25
 
0.2%
문형식 19
 
0.2%
Other values (2) 23
 
0.2%

설치일자
Text

MISSING 

Distinct64
Distinct (%)1.2%
Missing4606
Missing (%)46.1%
Memory size156.2 KiB
2023-12-11T06:06:23.376252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length6.9043382
Min length1

Characters and Unicode

Total characters37242
Distinct characters13
Distinct categories4 ?
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 row20180925
2nd row2007
3rd row2011
4th row20050830
5th row20050830
ValueCountFrequency (%)
20050830 3159
58.7%
2010 185
 
3.4%
2017 181
 
3.4%
2007 156
 
2.9%
140
 
2.6%
2011 133
 
2.5%
2016 116
 
2.2%
2019 103
 
1.9%
2006 89
 
1.7%
20180811 84
 
1.6%
Other values (53) 1036
 
19.2%
2023-12-11T06:06:23.733650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16250
43.6%
2 5943
 
16.0%
8 3631
 
9.7%
3 3597
 
9.7%
5 3376
 
9.1%
1 2669
 
7.2%
7 535
 
1.4%
9 383
 
1.0%
6 345
 
0.9%
- 304
 
0.8%
Other values (3) 209
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36912
99.1%
Dash Punctuation 304
 
0.8%
Other Punctuation 14
 
< 0.1%
Space Separator 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16250
44.0%
2 5943
 
16.1%
8 3631
 
9.8%
3 3597
 
9.7%
5 3376
 
9.1%
1 2669
 
7.2%
7 535
 
1.4%
9 383
 
1.0%
6 345
 
0.9%
4 183
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 304
100.0%
Other Punctuation
ValueCountFrequency (%)
. 14
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37242
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16250
43.6%
2 5943
 
16.0%
8 3631
 
9.7%
3 3597
 
9.7%
5 3376
 
9.1%
1 2669
 
7.2%
7 535
 
1.4%
9 383
 
1.0%
6 345
 
0.9%
- 304
 
0.8%
Other values (3) 209
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16250
43.6%
2 5943
 
16.0%
8 3631
 
9.7%
3 3597
 
9.7%
5 3376
 
9.1%
1 2669
 
7.2%
7 535
 
1.4%
9 383
 
1.0%
6 345
 
0.9%
- 304
 
0.8%
Other values (3) 209
 
0.6%

비고
Text

MISSING 

Distinct3077
Distinct (%)38.6%
Missing2038
Missing (%)20.4%
Memory size156.2 KiB
2023-12-11T06:06:24.009742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length57
Mean length10.588546
Min length1

Characters and Unicode

Total characters84306
Distinct characters595
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2411 ?
Unique (%)30.3%

Sample

1st row자전거보행자겸용
2nd row속성없음
3rd row양보
4th row3방향표지_(과천.서울,성남.판교IC,수원.군포)
5th row횡단보도
ValueCountFrequency (%)
보조표지 976
 
7.2%
횡단보도 678
 
5.0%
도로선형 595
 
4.4%
곡선 595
 
4.4%
서행 259
 
1.9%
반사경 211
 
1.6%
좌로굽은도로 155
 
1.1%
과속방지턱 153
 
1.1%
우로굽은도로 149
 
1.1%
속성없음 116
 
0.9%
Other values (3848) 9623
71.2%
2023-12-11T06:06:24.758542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6437
 
7.6%
도 4107
 
4.9%
지 3489
 
4.1%
로 2858
 
3.4%
표 2644
 
3.1%
( 2346
 
2.8%
) 2340
 
2.8%
보 2172
 
2.6%
0 1932
 
2.3%
선 1673
 
2.0%
Other values (585) 54308
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57718
68.5%
Decimal Number 7779
 
9.2%
Space Separator 6437
 
7.6%
Other Punctuation 2591
 
3.1%
Open Punctuation 2346
 
2.8%
Close Punctuation 2340
 
2.8%
Lowercase Letter 2053
 
2.4%
Uppercase Letter 1701
 
2.0%
Connector Punctuation 583
 
0.7%
Math Symbol 426
 
0.5%
Other values (2) 332
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 4107
 
7.1%
지 3489
 
6.0%
로 2858
 
5.0%
표 2644
 
4.6%
보 2172
 
3.8%
선 1673
 
2.9%
조 1075
 
1.9%
유 1031
 
1.8%
속 1006
 
1.7%
형 947
 
1.6%
Other values (513) 36716
63.6%
Uppercase Letter
ValueCountFrequency (%)
A 330
19.4%
E 308
18.1%
C 285
16.8%
M 167
9.8%
T 126
 
7.4%
V 98
 
5.8%
K 75
 
4.4%
I 69
 
4.1%
S 42
 
2.5%
B 34
 
2.0%
Other values (14) 167
9.8%
Lowercase Letter
ValueCountFrequency (%)
m 1096
53.4%
k 477
23.2%
h 333
 
16.2%
a 43
 
2.1%
e 33
 
1.6%
t 30
 
1.5%
s 11
 
0.5%
o 5
 
0.2%
c 5
 
0.2%
n 5
 
0.2%
Other values (5) 15
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 1932
24.8%
1 1082
13.9%
3 984
12.6%
2 974
12.5%
5 592
 
7.6%
6 548
 
7.0%
4 520
 
6.7%
8 450
 
5.8%
7 443
 
5.7%
9 254
 
3.3%
Math Symbol
ValueCountFrequency (%)
> 175
41.1%
< 139
32.6%
+ 48
 
11.3%
~ 33
 
7.7%
→ 18
 
4.2%
← 7
 
1.6%
= 4
 
0.9%
↑ 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 1618
62.4%
. 474
 
18.3%
/ 424
 
16.4%
% 57
 
2.2%
: 11
 
0.4%
# 5
 
0.2%
@ 2
 
0.1%
Other Symbol
ValueCountFrequency (%)
├ 1
33.3%
┤ 1
33.3%
↕ 1
33.3%
Space Separator
ValueCountFrequency (%)
6437
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2346
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2340
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 583
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 329
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57718
68.5%
Common 22834
 
27.1%
Latin 3754
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 4107
 
7.1%
지 3489
 
6.0%
로 2858
 
5.0%
표 2644
 
4.6%
보 2172
 
3.8%
선 1673
 
2.9%
조 1075
 
1.9%
유 1031
 
1.8%
속 1006
 
1.7%
형 947
 
1.6%
Other values (513) 36716
63.6%
Latin
ValueCountFrequency (%)
m 1096
29.2%
k 477
12.7%
h 333
 
8.9%
A 330
 
8.8%
E 308
 
8.2%
C 285
 
7.6%
M 167
 
4.4%
T 126
 
3.4%
V 98
 
2.6%
K 75
 
2.0%
Other values (29) 459
12.2%
Common
ValueCountFrequency (%)
6437
28.2%
( 2346
 
10.3%
) 2340
 
10.2%
0 1932
 
8.5%
, 1618
 
7.1%
1 1082
 
4.7%
3 984
 
4.3%
2 974
 
4.3%
5 592
 
2.6%
_ 583
 
2.6%
Other values (23) 3946
17.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57620
68.3%
ASCII 26558
31.5%
Compat Jamo 98
 
0.1%
Arrows 28
 
< 0.1%
Box Drawing 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6437
24.2%
( 2346
 
8.8%
) 2340
 
8.8%
0 1932
 
7.3%
, 1618
 
6.1%
m 1096
 
4.1%
1 1082
 
4.1%
3 984
 
3.7%
2 974
 
3.7%
5 592
 
2.2%
Other values (56) 7157
26.9%
Hangul
ValueCountFrequency (%)
도 4107
 
7.1%
지 3489
 
6.1%
로 2858
 
5.0%
표 2644
 
4.6%
보 2172
 
3.8%
선 1673
 
2.9%
조 1075
 
1.9%
유 1031
 
1.8%
속 1006
 
1.7%
형 947
 
1.6%
Other values (509) 36618
63.6%
Compat Jamo
ValueCountFrequency (%)
ㅏ 54
55.1%
ㅓ 40
40.8%
ㅜ 3
 
3.1%
ㆍ 1
 
1.0%
Arrows
ValueCountFrequency (%)
→ 18
64.3%
← 7
 
25.0%
↑ 2
 
7.1%
↕ 1
 
3.6%
Box Drawing
ValueCountFrequency (%)
├ 1
50.0%
┤ 1
50.0%

입력일
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)1.2%
Missing614
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean20122772
Minimum20051024
Maximum20230129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:06:24.935704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20051024
5-th percentile20060909
Q120060909
median20101102
Q320190410
95-th percentile20230129
Maximum20230129
Range179105
Interquartile range (IQR)129501

Descriptive statistics

Standard deviation61706.586
Coefficient of variation (CV)0.0030665053
Kurtosis-1.4644485
Mean20122772
Median Absolute Deviation (MAD)40193
Skewness0.40536643
Sum1.8887234 × 1011
Variance3.8077027 × 109
MonotonicityNot monotonic
2023-12-11T06:06:25.149636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20060909 3202
32.0%
20091102 562
 
5.6%
20200225 525
 
5.2%
20211206 516
 
5.2%
20201224 507
 
5.1%
20230129 478
 
4.8%
20071204 359
 
3.6%
20120120 256
 
2.6%
20081231 253
 
2.5%
20101102 183
 
1.8%
Other values (107) 2545
25.4%
(Missing) 614
 
6.1%
ValueCountFrequency (%)
20051024 15
 
0.1%
20060909 3202
32.0%
20071130 60
 
0.6%
20071204 359
 
3.6%
20071220 83
 
0.8%
20081201 8
 
0.1%
20081231 253
 
2.5%
20091102 562
 
5.6%
20091201 31
 
0.3%
20091210 4
 
< 0.1%
ValueCountFrequency (%)
20230129 478
4.8%
20221024 59
 
0.6%
20220930 14
 
0.1%
20220613 10
 
0.1%
20220214 3
 
< 0.1%
20211206 516
5.2%
20210816 9
 
0.1%
20201228 25
 
0.2%
20201224 507
5.1%
20201221 10
 
0.1%

사진 파일
Text

MISSING 

Distinct3627
Distinct (%)91.8%
Missing6047
Missing (%)60.5%
Memory size156.2 KiB
2023-12-11T06:06:25.406039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length12.596003
Min length1

Characters and Unicode

Total characters49792
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3458 ?
Unique (%)87.5%

Sample

1st rowM030601105709
2nd row005701M06297U
3rd row
4th rowM007805104346
5th rowM030203005135
ValueCountFrequency (%)
036802m10949u 5
 
0.1%
007815m06474d 4
 
0.1%
007814m01880u 4
 
0.1%
m034106109711 4
 
0.1%
031301m02274j 4
 
0.1%
007810m00806u 3
 
0.1%
007816m00010u 3
 
0.1%
007815m08352d 3
 
0.1%
005701m07335u 3
 
0.1%
008601m00539d 3
 
0.1%
Other values (3616) 3780
99.1%
2023-12-11T06:06:25.870744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16165
32.5%
3 5111
 
10.3%
1 5061
 
10.2%
M 3815
 
7.7%
5 2799
 
5.6%
2 2766
 
5.6%
8 2637
 
5.3%
6 2582
 
5.2%
7 2398
 
4.8%
4 2156
 
4.3%
Other values (9) 4302
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43533
87.4%
Uppercase Letter 6093
 
12.2%
Space Separator 137
 
0.3%
Dash Punctuation 25
 
0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16165
37.1%
3 5111
 
11.7%
1 5061
 
11.6%
5 2799
 
6.4%
2 2766
 
6.4%
8 2637
 
6.1%
6 2582
 
5.9%
7 2398
 
5.5%
4 2156
 
5.0%
9 1858
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
M 3815
62.6%
U 1123
 
18.4%
D 1123
 
18.4%
J 24
 
0.4%
P 4
 
0.1%
G 4
 
0.1%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43699
87.8%
Latin 6093
 
12.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16165
37.0%
3 5111
 
11.7%
1 5061
 
11.6%
5 2799
 
6.4%
2 2766
 
6.3%
8 2637
 
6.0%
6 2582
 
5.9%
7 2398
 
5.5%
4 2156
 
4.9%
9 1858
 
4.3%
Other values (3) 166
 
0.4%
Latin
ValueCountFrequency (%)
M 3815
62.6%
U 1123
 
18.4%
D 1123
 
18.4%
J 24
 
0.4%
P 4
 
0.1%
G 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49792
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16165
32.5%
3 5111
 
10.3%
1 5061
 
10.2%
M 3815
 
7.7%
5 2799
 
5.6%
2 2766
 
5.6%
8 2637
 
5.3%
6 2582
 
5.2%
7 2398
 
4.8%
4 2156
 
4.3%
Other values (9) 4302
 
8.6%

Interactions

2023-12-11T06:06:19.796306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:18.781225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.154766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.461232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.878645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:18.871958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.231126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.541652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.954083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:18.970341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.303331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.617578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:20.041398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.056557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.380780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:06:19.697441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:06:25.988749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호구간번호이력코드위치?시점위치?방향표지 종류설치형식설치일자입력일
노선번호1.0000.4670.2350.0490.0930.1770.1530.8230.453
구간번호0.4671.0000.0590.1230.0590.1160.1530.8100.260
이력코드0.2350.0591.0000.0000.0790.3890.3160.9930.816
위치?시점0.0490.1230.0001.0000.0000.0000.0000.0000.000
위치?방향0.0930.0590.0790.0001.0000.1480.0560.5490.210
표지 종류0.1770.1160.3890.0000.1481.0000.6620.6250.476
설치형식0.1530.1530.3160.0000.0560.6621.0000.7490.447
설치일자0.8230.8100.9930.0000.5490.6250.7491.0000.994
입력일0.4530.2600.8160.0000.2100.4760.4470.9941.000
2023-12-11T06:06:26.103473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치형식위치?방향표지 종류이력코드
설치형식1.0000.0340.3260.179
위치?방향0.0341.0000.0840.065
표지 종류0.3260.0841.0000.176
이력코드0.1790.0650.1761.000
2023-12-11T06:06:26.200017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호구간번호위치?시점입력일이력코드위치?방향표지 종류설치형식
노선번호1.000-0.097-0.0130.0480.1610.0600.0830.079
구간번호-0.0971.000-0.015-0.0190.0480.0240.0660.093
위치?시점-0.013-0.0151.000-0.0620.0000.0000.0000.000
입력일0.048-0.019-0.0621.0000.4730.1270.1980.208
이력코드0.1610.0480.0000.4731.0000.0650.1760.179
위치?방향0.0600.0240.0000.1270.0651.0000.0840.034
표지 종류0.0830.0660.0000.1980.1760.0841.0000.326
설치형식0.0790.0930.0000.2080.1790.0340.3261.000

Missing values

2023-12-11T06:06:20.167518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:06:20.328170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T06:06:20.454007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

관리기관노선번호구간번호이력코드위치?시점위치?방향표지 종류표지 명칭설치형식설치일자비고입력일사진 파일
42692경기도309112.082중앙기타표지곡선유도단주식<NA><NA>20200225<NA>
37134경기도301218.289상행지시표지자전거및보행자겸용도로부착식20180925자전거보행자겸용20190126<NA>
31822경기도306300.655상행기타표지기타단주식2007속성없음20091102<NA>
52282경기도391629.003하행규제표지양보표지단주식<NA>양보20091102<NA>
1277경기도3601008.764하행방향표지1지명방향표지복주식2011<NA>20111104<NA>
15899경기도577011.94하행방향표지3방향표지편지식200508303방향표지_(과천.서울,성남.판교IC,수원.군포)20060909<NA>
42610경기도306115.709하행지시표지횡단보도단주식<NA>횡단보도20130111M030601105709
16802경기도57116.297상행기타표지반사경단주식<NA><NA>20211206005701M06297U
28028경기도78804.131상행교통기타반사경단주식20050830반사경20060909
55106경기도371106.56하행규제표지서행단주식20050830서행20060909<NA>
관리기관노선번호구간번호이력코드위치?시점위치?방향표지 종류표지 명칭설치형식설치일자비고입력일사진 파일
41355경기도375406.455하행기타표지안내표지기타부착식2011새주소-양연로643번길20110325<NA>
25556경기도88208.177상행보조표지기타단주식20050830보조표지 통행주의20060909<NA>
10507경기도333303.435하행주의표지횡단보도단주식20050830횡단보도20060909<NA>
51912경기도321404.076하행이정표지2지명이정표지복주식200508302지명이정표지(오산,남사)20060909<NA>
50448경기도3211002.522상행교통기타곡선유도단주식<NA>곡선도로 유도방향표지20071220<NA>
7496경기도333414.524하행안내기타기타부착식2017본두3교차로20180103<NA>
8336경기도23900.96상행규제표지직진금지단주식20050830직진금지20060909<NA>
56009경기도3711101.035하행교통기타반사경단주식20050830보조표지 반사경20060909<NA>
50449경기도321512.525하행지시표지자전거및보행자겸용도로부착식20180630자전거보행자겸용20180830<NA>
19383경기도56101.503횡단규제표지양보표지단주식20050830양보20060909<NA>

Duplicate rows

Most frequently occurring

관리기관노선번호구간번호이력코드위치?시점위치?방향표지 종류표지 명칭설치형식설치일자비고입력일사진 파일# duplicates
3경기도56703.633하행기타표지교통안내표지기타측주식<NA>CCTV20211206005607M03633D3
0경기도231112.28하행규제표지우회전금지단주식20051001우회전금지20060909<NA>2
1경기도231112.33하행규제표지차높이제한부착식200510014.5m 차높이제한20060909<NA>2
2경기도56700.005하행기타표지교통안내표지기타측주식<NA>CCTV20211206005607M00007D2
4경기도57606.404하행안내기타하천표지단주식<NA>하천명_(분당천)20071204<NA>2
5경기도57607.2상행경계표지시,군,구계단주식<NA>시/군계표지_(사고 잦은곳,속도를 줄이시오)20071204<NA>2
6경기도57607.476상행방향표지3방향표지편지식<NA>3방향표지_(야탑3동 새마을 연수원,광주 율동공원, 미금역 중앙공원)20071204<NA>2
7경기도57607.562하행방향표지3방향표지편지식<NA>3방향표지_(야탑3동 새마을 연수원,광주 율동공원, 미금역 중앙공원)20071204<NA>2
8경기도57609.714상행경계표지시,군,구계단주식<NA>시/군계표지_(사고 잦은곳,속도를 줄이시오)20071204<NA>2
9경기도70202.56상행주의표지우합류도로단주식20051001우합류도로20060909<NA>2