Overview

Dataset statistics

Number of variables17
Number of observations4906
Missing cells6075
Missing cells (%)7.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory670.9 KiB
Average record size in memory140.0 B

Variable types

Numeric4
Categorical6
Text7

Dataset

Description부산광역시_도시공간정보시스템_도로안내시설_20230717
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15084595

Alerts

지형지물명 has constant value ""Constant
관리기관 is highly overall correlated with 등록구 and 1 other fieldsHigh correlation
등록구 is highly overall correlated with 관리기관High correlation
차도폭 is highly overall correlated with 길어깨(보도)의폭High correlation
길어깨(보도)의폭 is highly overall correlated with 차도폭High correlation
허가구분 is highly overall correlated with 관리기관High correlation
허가구분 is highly imbalanced (69.1%)Imbalance
행정동 has 213 (4.3%) missing valuesMissing
허가번호 has 431 (8.8%) missing valuesMissing
설치위치 has 408 (8.3%) missing valuesMissing
방향 has 1092 (22.3%) missing valuesMissing
차도폭 has 174 (3.5%) missing valuesMissing
길어깨(보도)의폭 has 520 (10.6%) missing valuesMissing
높이 has 844 (17.2%) missing valuesMissing
도로구간명 has 1467 (29.9%) missing valuesMissing
가로표지판규격 has 463 (9.4%) missing valuesMissing
세로표지판규격 has 463 (9.4%) missing valuesMissing
공간정보일련번호 has unique valuesUnique
차도폭 has 1060 (21.6%) zerosZeros
길어깨(보도)의폭 has 1548 (31.6%) zerosZeros
높이 has 2223 (45.3%) zerosZeros

Reproduction

Analysis started2023-12-10 16:39:28.014300
Analysis finished2023-12-10 16:39:33.335412
Duration5.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보일련번호
Real number (ℝ)

UNIQUE 

Distinct4906
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9924.7191
Minimum2
Maximum19521
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2023-12-11T01:39:33.506165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile300.25
Q11601.25
median15264.5
Q316496.75
95-th percentile17480.75
Maximum19521
Range19519
Interquartile range (IQR)14895.5

Descriptive statistics

Standard deviation7358.6837
Coefficient of variation (CV)0.74145007
Kurtosis-1.8399995
Mean9924.7191
Median Absolute Deviation (MAD)2215
Skewness-0.28704011
Sum48690672
Variance54150226
MonotonicityNot monotonic
2023-12-11T01:39:34.058292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1
 
< 0.1%
17611 1
 
< 0.1%
17618 1
 
< 0.1%
17617 1
 
< 0.1%
17616 1
 
< 0.1%
17615 1
 
< 0.1%
17614 1
 
< 0.1%
17613 1
 
< 0.1%
17612 1
 
< 0.1%
17610 1
 
< 0.1%
Other values (4896) 4896
99.8%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
ValueCountFrequency (%)
19521 1
< 0.1%
19201 1
< 0.1%
18881 1
< 0.1%
18561 1
< 0.1%
18241 1
< 0.1%
17923 1
< 0.1%
17922 1
< 0.1%
17921 1
< 0.1%
17728 1
< 0.1%
17727 1
< 0.1%

지형지물명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
사설안내표지판
4906 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사설안내표지판 4906
100.0%

Length

2023-12-11T01:39:34.270805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:34.406407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사설안내표지판 4906
100.0%

등록구
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
부산진구
816 
남구
569 
해운대구
453 
수영구
390 
동구
351 
Other values (12)
2327 

Length

Max length4
Median length3
Mean length2.9584183
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강서구
2nd row강서구
3rd row강서구
4th row강서구
5th row부산진구

Common Values

ValueCountFrequency (%)
부산진구 816
16.6%
남구 569
11.6%
해운대구 453
9.2%
수영구 390
7.9%
동구 351
 
7.2%
기장군 344
 
7.0%
사상구 336
 
6.8%
서구 270
 
5.5%
금정구 254
 
5.2%
강서구 227
 
4.6%
Other values (7) 896
18.3%

Length

2023-12-11T01:39:34.550433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산진구 816
16.6%
남구 569
11.6%
해운대구 453
9.2%
수영구 390
7.9%
동구 351
 
7.2%
기장군 344
 
7.0%
사상구 336
 
6.8%
서구 270
 
5.5%
금정구 254
 
5.2%
강서구 227
 
4.6%
Other values (7) 896
18.3%

관리기관
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
1887 
남구 도시국 도시관리과
467 
수영구 도시국 도시관리과
334 
동구
298 
해운대구 도시건설국 도시디자인과
218 
Other values (27)
1702 

Length

Max length17
Median length16
Mean length6.1196494
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1887
38.5%
남구 도시국 도시관리과 467
 
9.5%
수영구 도시국 도시관리과 334
 
6.8%
동구 298
 
6.1%
해운대구 도시건설국 도시디자인과 218
 
4.4%
동래구 211
 
4.3%
기장군 205
 
4.2%
서구 168
 
3.4%
금정구 도시국 건설과 152
 
3.1%
강서구 116
 
2.4%
Other values (22) 850
17.3%

Length

2023-12-11T01:39:34.752372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1887
24.5%
도시국 1123
14.6%
도시관리과 803
10.4%
남구 562
 
7.3%
수영구 362
 
4.7%
동구 334
 
4.3%
해운대구 298
 
3.9%
기장군 283
 
3.7%
서구 270
 
3.5%
건설과 244
 
3.2%
Other values (21) 1530
19.9%

행정동
Text

MISSING 

Distinct196
Distinct (%)4.2%
Missing213
Missing (%)4.3%
Memory size38.5 KiB
2023-12-11T01:39:35.117967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.6629022
Min length3

Characters and Unicode

Total characters17190
Distinct characters106
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

Unique0 ?
Unique (%)0.0%

Sample

1st row가락동
2nd row명지동
3rd row명지동
4th row명지동
5th row전포3동
ValueCountFrequency (%)
암남동 144
 
3.1%
우1동 129
 
2.7%
초량3동 122
 
2.6%
기장읍 104
 
2.2%
용호1동 100
 
2.1%
양정1동 82
 
1.7%
대연3동 82
 
1.7%
민락동 74
 
1.6%
장안읍 74
 
1.6%
당감1동 70
 
1.5%
Other values (186) 3712
79.1%
2023-12-11T01:39:35.721302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 4488
26.1%
1 1424
 
8.3%
2 937
 
5.5%
3 527
 
3.1%
대 400
 
2.3%
연 359
 
2.1%
천 291
 
1.7%
남 291
 
1.7%
장 288
 
1.7%
정 266
 
1.5%
Other values (96) 7919
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13940
81.1%
Decimal Number 3250
 
18.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4488
32.2%
대 400
 
2.9%
연 359
 
2.6%
천 291
 
2.1%
남 291
 
2.1%
장 288
 
2.1%
정 266
 
1.9%
읍 244
 
1.8%
안 238
 
1.7%
부 236
 
1.7%
Other values (88) 6839
49.1%
Decimal Number
ValueCountFrequency (%)
1 1424
43.8%
2 937
28.8%
3 527
 
16.2%
4 241
 
7.4%
5 66
 
2.0%
6 34
 
1.0%
9 15
 
0.5%
8 6
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13940
81.1%
Common 3250
 
18.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4488
32.2%
대 400
 
2.9%
연 359
 
2.6%
천 291
 
2.1%
남 291
 
2.1%
장 288
 
2.1%
정 266
 
1.9%
읍 244
 
1.8%
안 238
 
1.7%
부 236
 
1.7%
Other values (88) 6839
49.1%
Common
ValueCountFrequency (%)
1 1424
43.8%
2 937
28.8%
3 527
 
16.2%
4 241
 
7.4%
5 66
 
2.0%
6 34
 
1.0%
9 15
 
0.5%
8 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13940
81.1%
ASCII 3250
 
18.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 4488
32.2%
대 400
 
2.9%
연 359
 
2.6%
천 291
 
2.1%
남 291
 
2.1%
장 288
 
2.1%
정 266
 
1.9%
읍 244
 
1.8%
안 238
 
1.7%
부 236
 
1.7%
Other values (88) 6839
49.1%
ASCII
ValueCountFrequency (%)
1 1424
43.8%
2 937
28.8%
3 527
 
16.2%
4 241
 
7.4%
5 66
 
2.0%
6 34
 
1.0%
9 15
 
0.5%
8 6
 
0.2%

허가번호
Text

MISSING 

Distinct1674
Distinct (%)37.4%
Missing431
Missing (%)8.8%
Memory size38.5 KiB
2023-12-11T01:39:36.092432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length7.6339665
Min length1

Characters and Unicode

Total characters34162
Distinct characters62
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique216 ?
Unique (%)4.8%

Sample

1st row부산진구10-45
2nd row2006-103
3rd row부산진구116
4th row부산진구09-25
5th row수영구-2010-03호
ValueCountFrequency (%)
중구 158
 
4.3%
강서구 76
 
2.1%
수영구-2006 42
 
1.1%
수영구-2010 39
 
1.1%
수영구-2011 36
 
1.0%
동구 36
 
1.0%
수영구-2009 16
 
0.4%
수영구-2009-5 10
 
0.3%
수영구-2009-32 8
 
0.2%
기장군-2007-18 7
 
0.2%
Other values (1642) 3231
88.3%
2023-12-11T01:39:36.663335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6073
17.8%
- 5445
15.9%
2 3728
10.9%
구 2944
 
8.6%
1 2170
 
6.4%
1364
 
4.0%
9 1064
 
3.1%
6 947
 
2.8%
8 891
 
2.6%
3 890
 
2.6%
Other values (52) 8646
25.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18208
53.3%
Other Letter 9065
26.5%
Dash Punctuation 5445
 
15.9%
Space Separator 1364
 
4.0%
Open Punctuation 40
 
0.1%
Close Punctuation 40
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2944
32.5%
부 724
 
8.0%
산 722
 
8.0%
진 721
 
8.0%
남 460
 
5.1%
영 435
 
4.8%
동 413
 
4.6%
사 350
 
3.9%
수 345
 
3.8%
상 313
 
3.5%
Other values (38) 1638
18.1%
Decimal Number
ValueCountFrequency (%)
0 6073
33.4%
2 3728
20.5%
1 2170
 
11.9%
9 1064
 
5.8%
6 947
 
5.2%
8 891
 
4.9%
3 890
 
4.9%
4 850
 
4.7%
7 820
 
4.5%
5 775
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 5445
100.0%
Space Separator
ValueCountFrequency (%)
1364
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25097
73.5%
Hangul 9065
 
26.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2944
32.5%
부 724
 
8.0%
산 722
 
8.0%
진 721
 
8.0%
남 460
 
5.1%
영 435
 
4.8%
동 413
 
4.6%
사 350
 
3.9%
수 345
 
3.8%
상 313
 
3.5%
Other values (38) 1638
18.1%
Common
ValueCountFrequency (%)
0 6073
24.2%
- 5445
21.7%
2 3728
14.9%
1 2170
 
8.6%
1364
 
5.4%
9 1064
 
4.2%
6 947
 
3.8%
8 891
 
3.6%
3 890
 
3.5%
4 850
 
3.4%
Other values (4) 1675
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25097
73.5%
Hangul 9065
 
26.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6073
24.2%
- 5445
21.7%
2 3728
14.9%
1 2170
 
8.6%
1364
 
5.4%
9 1064
 
4.2%
6 947
 
3.8%
8 891
 
3.6%
3 890
 
3.5%
4 850
 
3.4%
Other values (4) 1675
 
6.7%
Hangul
ValueCountFrequency (%)
구 2944
32.5%
부 724
 
8.0%
산 722
 
8.0%
진 721
 
8.0%
남 460
 
5.1%
영 435
 
4.8%
동 413
 
4.6%
사 350
 
3.9%
수 345
 
3.8%
상 313
 
3.5%
Other values (38) 1638
18.1%

설치위치
Text

MISSING 

Distinct1789
Distinct (%)39.8%
Missing408
Missing (%)8.3%
Memory size38.5 KiB
2023-12-11T01:39:37.124314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length41
Mean length12.880614
Min length1

Characters and Unicode

Total characters57937
Distinct characters496
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique272 ?
Unique (%)6.0%

Sample

1st row전포3동 성북초교옆 승우산업 앞
2nd row기장군 철마면 연구리 543
3rd row부산시 진구 당감동 859-1번지
4th row부산진여중 옆
5th row부산광역시 수영구 남천동 517-11(도)
ValueCountFrequency (%)
앞 729
 
6.6%
부산광역시 314
 
2.8%
수영구 308
 
2.8%
도로 223
 
2.0%
입구 223
 
2.0%
금정구 175
 
1.6%
근처 138
 
1.2%
부산시 125
 
1.1%
맞은편 121
 
1.1%
가로등 98
 
0.9%
Other values (2297) 8654
77.9%
2023-12-11T01:39:37.656676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9471
 
16.3%
동 2950
 
5.1%
1 2209
 
3.8%
- 1587
 
2.7%
로 1470
 
2.5%
구 1443
 
2.5%
2 1391
 
2.4%
앞 1349
 
2.3%
지 1138
 
2.0%
3 1026
 
1.8%
Other values (486) 33903
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35918
62.0%
Space Separator 9471
 
16.3%
Decimal Number 9420
 
16.3%
Dash Punctuation 1587
 
2.7%
Close Punctuation 594
 
1.0%
Open Punctuation 588
 
1.0%
Uppercase Letter 224
 
0.4%
Other Punctuation 96
 
0.2%
Lowercase Letter 38
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2950
 
8.2%
로 1470
 
4.1%
구 1443
 
4.0%
앞 1349
 
3.8%
지 1138
 
3.2%
부 1008
 
2.8%
번 922
 
2.6%
산 847
 
2.4%
도 757
 
2.1%
영 606
 
1.7%
Other values (439) 23428
65.2%
Uppercase Letter
ValueCountFrequency (%)
G 46
20.5%
L 35
15.6%
S 21
9.4%
K 19
8.5%
C 19
8.5%
T 15
 
6.7%
P 10
 
4.5%
R 10
 
4.5%
I 9
 
4.0%
Y 8
 
3.6%
Other values (8) 32
14.3%
Decimal Number
ValueCountFrequency (%)
1 2209
23.5%
2 1391
14.8%
3 1026
10.9%
5 881
 
9.4%
4 869
 
9.2%
6 744
 
7.9%
7 645
 
6.8%
8 590
 
6.3%
9 546
 
5.8%
0 519
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 56
58.3%
@ 22
 
22.9%
. 8
 
8.3%
/ 4
 
4.2%
& 2
 
2.1%
？ 2
 
2.1%
: 2
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
e 14
36.8%
k 8
21.1%
s 6
15.8%
c 4
 
10.5%
a 2
 
5.3%
p 2
 
5.3%
t 2
 
5.3%
Space Separator
ValueCountFrequency (%)
9471
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1587
100.0%
Close Punctuation
ValueCountFrequency (%)
) 594
100.0%
Open Punctuation
ValueCountFrequency (%)
( 588
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35918
62.0%
Common 21757
37.6%
Latin 262
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2950
 
8.2%
로 1470
 
4.1%
구 1443
 
4.0%
앞 1349
 
3.8%
지 1138
 
3.2%
부 1008
 
2.8%
번 922
 
2.6%
산 847
 
2.4%
도 757
 
2.1%
영 606
 
1.7%
Other values (439) 23428
65.2%
Latin
ValueCountFrequency (%)
G 46
17.6%
L 35
13.4%
S 21
 
8.0%
K 19
 
7.3%
C 19
 
7.3%
T 15
 
5.7%
e 14
 
5.3%
P 10
 
3.8%
R 10
 
3.8%
I 9
 
3.4%
Other values (15) 64
24.4%
Common
ValueCountFrequency (%)
9471
43.5%
1 2209
 
10.2%
- 1587
 
7.3%
2 1391
 
6.4%
3 1026
 
4.7%
5 881
 
4.0%
4 869
 
4.0%
6 744
 
3.4%
7 645
 
3.0%
) 594
 
2.7%
Other values (12) 2340
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35918
62.0%
ASCII 22017
38.0%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9471
43.0%
1 2209
 
10.0%
- 1587
 
7.2%
2 1391
 
6.3%
3 1026
 
4.7%
5 881
 
4.0%
4 869
 
3.9%
6 744
 
3.4%
7 645
 
2.9%
) 594
 
2.7%
Other values (36) 2600
 
11.8%
Hangul
ValueCountFrequency (%)
동 2950
 
8.2%
로 1470
 
4.1%
구 1443
 
4.0%
앞 1349
 
3.8%
지 1138
 
3.2%
부 1008
 
2.8%
번 922
 
2.6%
산 847
 
2.4%
도 757
 
2.1%
영 606
 
1.7%
Other values (439) 23428
65.2%
None
ValueCountFrequency (%)
？ 2
100.0%

방향
Text

MISSING 

Distinct789
Distinct (%)20.7%
Missing1092
Missing (%)22.3%
Memory size38.5 KiB
2023-12-11T01:39:37.932661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length38
Mean length7.2839539
Min length1

Characters and Unicode

Total characters27781
Distinct characters380
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

Unique54 ?
Unique (%)1.4%

Sample

1st row성북초교앞에서 이마트문현점 방면
2nd row부산진여중에서 구)대우자동차 방면
3rd row남천동로 방향
4th row무학로 방향
5th row수영로 해운대방향
ValueCountFrequency (%)
방향 722
 
15.2%
방면 292
 
6.2%
대연사거리 42
 
0.9%
대연사거리에서 42
 
0.9%
문현교차로에서 42
 
0.9%
유엔교차로 38
 
0.8%
에서 36
 
0.8%
수영로방향 36
 
0.8%
앞 34
 
0.7%
유엔교차로에서 32
 
0.7%
Other values (1008) 3428
72.3%
2023-12-11T01:39:38.435102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4722
 
17.0%
방 1485
 
5.3%
서 1262
 
4.5%
에 1178
 
4.2%
향 1116
 
4.0%
로 1003
 
3.6%
리 719
 
2.6%
동 648
 
2.3%
대 626
 
2.3%
교 595
 
2.1%
Other values (370) 14427
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22190
79.9%
Space Separator 4722
 
17.0%
Decimal Number 308
 
1.1%
Dash Punctuation 202
 
0.7%
Uppercase Letter 142
 
0.5%
Close Punctuation 54
 
0.2%
Open Punctuation 52
 
0.2%
Other Punctuation 41
 
0.1%
Lowercase Letter 40
 
0.1%
Math Symbol 30
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 1485
 
6.7%
서 1262
 
5.7%
에 1178
 
5.3%
향 1116
 
5.0%
로 1003
 
4.5%
리 719
 
3.2%
동 648
 
2.9%
대 626
 
2.8%
교 595
 
2.7%
거 525
 
2.4%
Other values (330) 13033
58.7%
Uppercase Letter
ValueCountFrequency (%)
R 42
29.6%
K 18
12.7%
S 16
 
11.3%
C 14
 
9.9%
I 10
 
7.0%
Z 8
 
5.6%
G 8
 
5.6%
L 8
 
5.6%
B 6
 
4.2%
H 4
 
2.8%
Other values (3) 8
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 102
33.1%
3 40
 
13.0%
2 40
 
13.0%
0 29
 
9.4%
8 29
 
9.4%
4 23
 
7.5%
5 15
 
4.9%
9 14
 
4.5%
7 8
 
2.6%
6 8
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 8
20.0%
b 8
20.0%
m 8
20.0%
s 6
15.0%
k 6
15.0%
c 2
 
5.0%
i 2
 
5.0%
Other Punctuation
ValueCountFrequency (%)
@ 24
58.5%
, 12
29.3%
. 3
 
7.3%
\ 2
 
4.9%
Math Symbol
ValueCountFrequency (%)
~ 28
93.3%
< 2
 
6.7%
Space Separator
ValueCountFrequency (%)
4722
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22190
79.9%
Common 5409
 
19.5%
Latin 182
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 1485
 
6.7%
서 1262
 
5.7%
에 1178
 
5.3%
향 1116
 
5.0%
로 1003
 
4.5%
리 719
 
3.2%
동 648
 
2.9%
대 626
 
2.8%
교 595
 
2.7%
거 525
 
2.4%
Other values (330) 13033
58.7%
Common
ValueCountFrequency (%)
4722
87.3%
- 202
 
3.7%
1 102
 
1.9%
) 54
 
1.0%
( 52
 
1.0%
3 40
 
0.7%
2 40
 
0.7%
0 29
 
0.5%
8 29
 
0.5%
~ 28
 
0.5%
Other values (10) 111
 
2.1%
Latin
ValueCountFrequency (%)
R 42
23.1%
K 18
9.9%
S 16
 
8.8%
C 14
 
7.7%
I 10
 
5.5%
Z 8
 
4.4%
G 8
 
4.4%
L 8
 
4.4%
e 8
 
4.4%
b 8
 
4.4%
Other values (10) 42
23.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22190
79.9%
ASCII 5591
 
20.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4722
84.5%
- 202
 
3.6%
1 102
 
1.8%
) 54
 
1.0%
( 52
 
0.9%
R 42
 
0.8%
3 40
 
0.7%
2 40
 
0.7%
0 29
 
0.5%
8 29
 
0.5%
Other values (30) 279
 
5.0%
Hangul
ValueCountFrequency (%)
방 1485
 
6.7%
서 1262
 
5.7%
에 1178
 
5.3%
향 1116
 
5.0%
로 1003
 
4.5%
리 719
 
3.2%
동 648
 
2.9%
대 626
 
2.8%
교 595
 
2.7%
거 525
 
2.4%
Other values (330) 13033
58.7%

차도폭
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct286
Distinct (%)6.0%
Missing174
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean15.174324
Minimum0
Maximum189
Zeros1060
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2023-12-11T01:39:38.588170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.8
median14.1
Q323.725
95-th percentile35.545
Maximum189
Range189
Interquartile range (IQR)17.925

Descriptive statistics

Standard deviation14.685287
Coefficient of variation (CV)0.96777207
Kurtosis48.579557
Mean15.174324
Median Absolute Deviation (MAD)8.9
Skewness4.5177221
Sum71804.9
Variance215.65765
MonotonicityNot monotonic
2023-12-11T01:39:38.744475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1060
 
21.6%
25.0 156
 
3.2%
15.0 136
 
2.8%
21.0 131
 
2.7%
14.0 101
 
2.1%
12.0 78
 
1.6%
17.0 75
 
1.5%
10.0 74
 
1.5%
26.0 71
 
1.4%
40.0 64
 
1.3%
Other values (276) 2786
56.8%
(Missing) 174
 
3.5%
ValueCountFrequency (%)
0.0 1060
21.6%
3.0 2
 
< 0.1%
3.1 6
 
0.1%
3.3 2
 
< 0.1%
3.6 8
 
0.2%
3.7 2
 
< 0.1%
3.9 12
 
0.2%
4.0 12
 
0.2%
4.1 2
 
< 0.1%
4.2 2
 
< 0.1%
ValueCountFrequency (%)
189.0 12
0.2%
98.0 2
 
< 0.1%
79.5 4
 
0.1%
62.7 1
 
< 0.1%
58.9 2
 
< 0.1%
57.8 4
 
0.1%
52.0 6
0.1%
51.5 1
 
< 0.1%
49.0 2
 
< 0.1%
47.1 2
 
< 0.1%

길어깨(보도)의폭
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct112
Distinct (%)2.6%
Missing520
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean2.6480848
Minimum0
Maximum24.2
Zeros1548
Zeros (%)31.6%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2023-12-11T01:39:38.912480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q34.2
95-th percentile7
Maximum24.2
Range24.2
Interquartile range (IQR)4.2

Descriptive statistics

Standard deviation2.9379136
Coefficient of variation (CV)1.1094484
Kurtosis8.9769678
Mean2.6480848
Median Absolute Deviation (MAD)2.5
Skewness2.1766649
Sum11614.5
Variance8.6313361
MonotonicityNot monotonic
2023-12-11T01:39:39.071232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1548
31.6%
4.5 201
 
4.1%
3.0 200
 
4.1%
2.5 181
 
3.7%
4.0 169
 
3.4%
5.0 147
 
3.0%
2.0 108
 
2.2%
3.5 84
 
1.7%
3.4 72
 
1.5%
3.8 72
 
1.5%
Other values (102) 1604
32.7%
(Missing) 520
 
10.6%
ValueCountFrequency (%)
0.0 1548
31.6%
0.1 30
 
0.6%
0.2 14
 
0.3%
0.3 6
 
0.1%
0.4 8
 
0.2%
0.5 2
 
< 0.1%
0.6 4
 
0.1%
0.8 14
 
0.3%
1.0 15
 
0.3%
1.1 8
 
0.2%
ValueCountFrequency (%)
24.2 2
 
< 0.1%
23.4 1
 
< 0.1%
22.3 3
 
0.1%
21.2 5
0.1%
20.8 2
 
< 0.1%
19.1 2
 
< 0.1%
18.9 1
 
< 0.1%
17.4 10
0.2%
16.6 4
 
0.1%
16.0 3
 
0.1%

높이
Real number (ℝ)

MISSING  ZEROS 

Distinct54
Distinct (%)1.3%
Missing844
Missing (%)17.2%
Infinite0
Infinite (%)0.0%
Mean1.9368045
Minimum0
Maximum9
Zeros2223
Zeros (%)45.3%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2023-12-11T01:39:39.233837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile6
Maximum9
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.3283246
Coefficient of variation (CV)1.2021474
Kurtosis-1.3091854
Mean1.9368045
Median Absolute Deviation (MAD)0
Skewness0.58374775
Sum7867.3
Variance5.4210952
MonotonicityNot monotonic
2023-12-11T01:39:39.412119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2223
45.3%
5.0 579
 
11.8%
4.0 344
 
7.0%
6.0 144
 
2.9%
3.0 122
 
2.5%
5.5 96
 
2.0%
3.5 90
 
1.8%
2.5 66
 
1.3%
2.0 50
 
1.0%
4.5 46
 
0.9%
Other values (44) 302
 
6.2%
(Missing) 844
 
17.2%
ValueCountFrequency (%)
0.0 2223
45.3%
0.2 3
 
0.1%
0.3 2
 
< 0.1%
0.5 10
 
0.2%
0.6 8
 
0.2%
0.7 2
 
< 0.1%
0.8 5
 
0.1%
1.0 24
 
0.5%
1.2 9
 
0.2%
1.3 14
 
0.3%
ValueCountFrequency (%)
9.0 2
 
< 0.1%
8.0 8
 
0.2%
7.8 2
 
< 0.1%
7.5 2
 
< 0.1%
7.3 2
 
< 0.1%
7.0 26
 
0.5%
6.5 14
 
0.3%
6.3 6
 
0.1%
6.1 6
 
0.1%
6.0 144
2.9%

색상
Categorical

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
1771 
흰(미)색바탕 청색글자
1038 
기타
760 
흰(미)색바탕 갈색(계열)글자
421 
흰(미)색바탕 남색글자
306 
Other values (4)
610 

Length

Max length17
Median length16
Mean length8.1930289
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row흰(미)색바탕 검정(계열)글자

Common Values

ValueCountFrequency (%)
<NA> 1771
36.1%
흰(미)색바탕 청색글자 1038
21.2%
기타 760
15.5%
흰(미)색바탕 갈색(계열)글자 421
 
8.6%
흰(미)색바탕 남색글자 306
 
6.2%
흰(미)색바탕 검정(계열)글자 214
 
4.4%
갈색바탕 흰색글자 165
 
3.4%
흰(미)색바탕 진황색(계열)글자 122
 
2.5%
흰(미)색바탕 녹색(계열)글자 109
 
2.2%

Length

2023-12-11T01:39:39.609802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:39.775153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
흰(미)색바탕 2210
30.4%
na 1771
24.3%
청색글자 1038
14.3%
기타 760
 
10.4%
갈색(계열)글자 421
 
5.8%
남색글자 306
 
4.2%
검정(계열)글자 214
 
2.9%
갈색바탕 165
 
2.3%
흰색글자 165
 
2.3%
진황색(계열)글자 122
 
1.7%

도로구간명
Text

MISSING 

Distinct389
Distinct (%)11.3%
Missing1467
Missing (%)29.9%
Memory size38.5 KiB
2023-12-11T01:39:40.118301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length6.5963943
Min length3

Characters and Unicode

Total characters22685
Distinct characters264
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.7%

Sample

1st row외부순환도로
2nd row외부순환도로
3rd row외부순환도로
4th row동성로
5th row철마로
ValueCountFrequency (%)
구덕로 298
 
6.2%
중앙로,금정로 282
 
5.9%
동평로 190
 
4.0%
수영로 169
 
3.5%
자성로 169
 
3.5%
신암로 167
 
3.5%
연산로 163
 
3.4%
낙동로,금곡로 122
 
2.5%
대영로 122
 
2.5%
백양로 90
 
1.9%
Other values (392) 3022
63.0%
2023-12-11T01:39:40.665100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 4630
20.4%
, 2008
 
8.9%
1355
 
6.0%
길 881
 
3.9%
동 528
 
2.3%
금 487
 
2.1%
영 415
 
1.8%
덕 415
 
1.8%
대 410
 
1.8%
정 388
 
1.7%
Other values (254) 11168
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18665
82.3%
Other Punctuation 2008
 
8.9%
Space Separator 1355
 
6.0%
Decimal Number 511
 
2.3%
Close Punctuation 71
 
0.3%
Open Punctuation 71
 
0.3%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 4630
24.8%
길 881
 
4.7%
동 528
 
2.8%
금 487
 
2.6%
영 415
 
2.2%
덕 415
 
2.2%
대 410
 
2.2%
정 388
 
2.1%
구 374
 
2.0%
수 333
 
1.8%
Other values (237) 9804
52.5%
Decimal Number
ValueCountFrequency (%)
1 215
42.1%
2 103
20.2%
3 86
 
16.8%
4 46
 
9.0%
5 18
 
3.5%
6 15
 
2.9%
7 14
 
2.7%
9 12
 
2.3%
8 2
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
P 1
25.0%
E 1
25.0%
C 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 2008
100.0%
Space Separator
ValueCountFrequency (%)
1355
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18665
82.3%
Common 4016
 
17.7%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 4630
24.8%
길 881
 
4.7%
동 528
 
2.8%
금 487
 
2.6%
영 415
 
2.2%
덕 415
 
2.2%
대 410
 
2.2%
정 388
 
2.1%
구 374
 
2.0%
수 333
 
1.8%
Other values (237) 9804
52.5%
Common
ValueCountFrequency (%)
, 2008
50.0%
1355
33.7%
1 215
 
5.4%
2 103
 
2.6%
3 86
 
2.1%
) 71
 
1.8%
( 71
 
1.8%
4 46
 
1.1%
5 18
 
0.4%
6 15
 
0.4%
Other values (3) 28
 
0.7%
Latin
ValueCountFrequency (%)
A 1
25.0%
P 1
25.0%
E 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18665
82.3%
ASCII 4020
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 4630
24.8%
길 881
 
4.7%
동 528
 
2.8%
금 487
 
2.6%
영 415
 
2.2%
덕 415
 
2.2%
대 410
 
2.2%
정 388
 
2.1%
구 374
 
2.0%
수 333
 
1.8%
Other values (237) 9804
52.5%
ASCII
ValueCountFrequency (%)
, 2008
50.0%
1355
33.7%
1 215
 
5.3%
2 103
 
2.6%
3 86
 
2.1%
) 71
 
1.8%
( 71
 
1.8%
4 46
 
1.1%
5 18
 
0.4%
6 15
 
0.4%
Other values (7) 32
 
0.8%

가로표지판규격
Text

MISSING 

Distinct68
Distinct (%)1.5%
Missing463
Missing (%)9.4%
Memory size38.5 KiB
2023-12-11T01:39:40.994562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.2221472
Min length1

Characters and Unicode

Total characters14316
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

Unique4 ?
Unique (%)0.1%

Sample

1st row1200
2nd row1500
3rd row1500
4th row1200
5th row1200
ValueCountFrequency (%)
1200 1915
54.8%
1500 387
 
11.1%
1100 161
 
4.6%
1800 153
 
4.4%
800 150
 
4.3%
900 135
 
3.9%
1000 80
 
2.3%
1300 45
 
1.3%
200 44
 
1.3%
1400 43
 
1.2%
Other values (53) 380
 
10.9%
2023-12-11T01:39:41.425453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6799
47.5%
1 3135
21.9%
2 2046
 
14.3%
963
 
6.7%
5 487
 
3.4%
8 318
 
2.2%
9 160
 
1.1%
4 146
 
1.0%
. 122
 
0.9%
3 64
 
0.4%
Other values (2) 76
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13231
92.4%
Space Separator 963
 
6.7%
Other Punctuation 122
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6799
51.4%
1 3135
23.7%
2 2046
 
15.5%
5 487
 
3.7%
8 318
 
2.4%
9 160
 
1.2%
4 146
 
1.1%
3 64
 
0.5%
6 54
 
0.4%
7 22
 
0.2%
Space Separator
ValueCountFrequency (%)
963
100.0%
Other Punctuation
ValueCountFrequency (%)
. 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14316
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6799
47.5%
1 3135
21.9%
2 2046
 
14.3%
963
 
6.7%
5 487
 
3.4%
8 318
 
2.2%
9 160
 
1.1%
4 146
 
1.0%
. 122
 
0.9%
3 64
 
0.4%
Other values (2) 76
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6799
47.5%
1 3135
21.9%
2 2046
 
14.3%
963
 
6.7%
5 487
 
3.4%
8 318
 
2.2%
9 160
 
1.1%
4 146
 
1.0%
. 122
 
0.9%
3 64
 
0.4%
Other values (2) 76
 
0.5%

세로표지판규격
Text

MISSING 

Distinct79
Distinct (%)1.8%
Missing463
Missing (%)9.4%
Memory size38.5 KiB
2023-12-11T01:39:41.703228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.624578
Min length1

Characters and Unicode

Total characters11661
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

Unique6 ?
Unique (%)0.1%

Sample

1st row550
2nd row850
3rd row850
4th row550
5th row550
ValueCountFrequency (%)
550 1612
46.1%
850 403
 
11.5%
900 156
 
4.5%
400 144
 
4.1%
800 131
 
3.8%
1000 113
 
3.2%
500 104
 
3.0%
650 97
 
2.8%
600 74
 
2.1%
1020 67
 
1.9%
Other values (63) 592
 
16.9%
2023-12-11T01:39:42.172638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4545
39.0%
5 4072
34.9%
967
 
8.3%
8 606
 
5.2%
1 321
 
2.8%
6 247
 
2.1%
2 208
 
1.8%
4 201
 
1.7%
9 182
 
1.6%
. 138
 
1.2%
Other values (2) 174
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10556
90.5%
Space Separator 967
 
8.3%
Other Punctuation 138
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4545
43.1%
5 4072
38.6%
8 606
 
5.7%
1 321
 
3.0%
6 247
 
2.3%
2 208
 
2.0%
4 201
 
1.9%
9 182
 
1.7%
7 87
 
0.8%
3 87
 
0.8%
Space Separator
ValueCountFrequency (%)
967
100.0%
Other Punctuation
ValueCountFrequency (%)
. 138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11661
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4545
39.0%
5 4072
34.9%
967
 
8.3%
8 606
 
5.2%
1 321
 
2.8%
6 247
 
2.1%
2 208
 
1.8%
4 201
 
1.7%
9 182
 
1.6%
. 138
 
1.2%
Other values (2) 174
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11661
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4545
39.0%
5 4072
34.9%
967
 
8.3%
8 606
 
5.2%
1 321
 
2.8%
6 247
 
2.1%
2 208
 
1.8%
4 201
 
1.7%
9 182
 
1.6%
. 138
 
1.2%
Other values (2) 174
 
1.5%

허가구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
허가
3914 
<NA>
947 
미분류
 
15
가공
 
13
기초
 
12

Length

Max length4
Median length2
Mean length2.3901345
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
허가 3914
79.8%
<NA> 947
 
19.3%
미분류 15
 
0.3%
가공 13
 
0.3%
기초 12
 
0.2%
무허가 5
 
0.1%

Length

2023-12-11T01:39:42.390612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:42.536814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
허가 3914
79.8%
na 947
 
19.3%
미분류 15
 
0.3%
가공 13
 
0.3%
기초 12
 
0.2%
무허가 5
 
0.1%

물건종류
Categorical

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
1671 
기타
663 
교육기관(학교 등)
641 
국가기관및기초자치단체(구군청)
586 
종교시설
586 
Other values (7)
759 

Length

Max length16
Median length4
Mean length6.1606196
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1671
34.1%
기타 663
 
13.5%
교육기관(학교 등) 641
 
13.1%
국가기관및기초자치단체(구군청) 586
 
11.9%
종교시설 586
 
11.9%
공동주택 244
 
5.0%
의료시설 216
 
4.4%
관광시설 191
 
3.9%
흰(미)색바탕 청색글자 56
 
1.1%
흰(미)색바탕 검정(계열)글자 28
 
0.6%
Other values (2) 24
 
0.5%

Length

2023-12-11T01:39:42.717599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1671
29.5%
기타 663
 
11.7%
교육기관(학교 641
 
11.3%
등 641
 
11.3%
국가기관및기초자치단체(구군청 586
 
10.4%
종교시설 586
 
10.4%
공동주택 244
 
4.3%
의료시설 216
 
3.8%
관광시설 191
 
3.4%
흰(미)색바탕 108
 
1.9%
Other values (4) 108
 
1.9%

Interactions

2023-12-11T01:39:31.939891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:30.459495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:30.973287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:31.473609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:32.060599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:30.577499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:31.115358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:31.581801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:32.197376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:30.699488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:31.225709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:31.707048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:32.332883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:30.834895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:31.358157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:31.812057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:39:42.860403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보일련번호등록구관리기관차도폭길어깨(보도)의폭높이색상가로표지판규격세로표지판규격허가구분물건종류
공간정보일련번호1.0000.4880.7150.1490.2610.5770.1430.7190.7130.4080.347
등록구0.4881.0000.9990.3530.4470.6580.5440.7270.7430.4010.560
관리기관0.7150.9991.0000.5250.5920.7110.5130.9110.9240.8140.634
차도폭0.1490.3530.5251.0000.3850.2860.1310.2400.2780.1910.201
길어깨(보도)의폭0.2610.4470.5920.3851.0000.3220.2000.3250.3870.0000.174
높이0.5770.6580.7110.2860.3221.0000.3430.7530.7890.0670.356
색상0.1430.5440.5130.1310.2000.3431.0000.5330.5630.2930.700
가로표지판규격0.7190.7270.9110.2400.3250.7530.5331.0000.9930.0000.510
세로표지판규격0.7130.7430.9240.2780.3870.7890.5630.9931.0000.2160.498
허가구분0.4080.4010.8140.1910.0000.0670.2930.0000.2161.0000.098
물건종류0.3470.5600.6340.2010.1740.3560.7000.5100.4980.0981.000
2023-12-11T01:39:43.041582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관허가구분색상등록구물건종류
관리기관1.0000.5570.2440.9890.290
허가구분0.5571.0000.1350.2170.059
색상0.2440.1351.0000.2200.425
등록구0.9890.2170.2201.0000.249
물건종류0.2900.0590.4250.2491.000
2023-12-11T01:39:43.165916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보일련번호차도폭길어깨(보도)의폭높이등록구관리기관색상허가구분물건종류
공간정보일련번호1.000-0.209-0.230-0.3040.2150.3420.0770.1810.171
차도폭-0.2091.0000.5400.3510.1700.2610.0730.1300.103
길어깨(보도)의폭-0.2300.5401.0000.2280.1920.2510.0960.0000.075
높이-0.3040.3510.2281.0000.3270.3550.1660.0280.165
등록구0.2150.1700.1920.3271.0000.9890.2200.2170.249
관리기관0.3420.2610.2510.3550.9891.0000.2440.5570.290
색상0.0770.0730.0960.1660.2200.2441.0000.1350.425
허가구분0.1810.1300.0000.0280.2170.5570.1351.0000.059
물건종류0.1710.1030.0750.1650.2490.2900.4250.0591.000

Missing values

2023-12-11T01:39:32.528913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:39:32.839522image/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.
2023-12-11T01:39:33.102582image/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

공간정보일련번호지형지물명등록구관리기관행정동허가번호설치위치방향차도폭길어깨(보도)의폭높이색상도로구간명가로표지판규격세로표지판규격허가구분물건종류
02사설안내표지판강서구강서구가락동<NA><NA><NA>21.23.50.0<NA>외부순환도로<NA><NA><NA><NA>
13사설안내표지판강서구강서구명지동<NA><NA><NA>79.50.00.0<NA><NA><NA><NA><NA><NA>
25사설안내표지판강서구강서구명지동<NA><NA><NA>45.93.10.0<NA>외부순환도로<NA><NA><NA><NA>
36사설안내표지판강서구강서구명지동<NA><NA><NA>42.63.00.0<NA>외부순환도로<NA><NA><NA><NA>
48사설안내표지판부산진구<NA>전포3동부산진구10-45전포3동 성북초교옆 승우산업 앞성북초교앞에서 이마트문현점 방면34.04.04.0흰(미)색바탕 검정(계열)글자동성로1200550허가의료시설
512사설안내표지판기장군기장군 건설과철마면2006-103기장군 철마면 연구리 543<NA>8.80.1<NA><NA>철마로1500850허가<NA>
613사설안내표지판부산진구<NA>당감2동부산진구116부산시 진구 당감동 859-1번지<NA>19.0<NA><NA>기타제2도시고속도로(동서고가로)1500850허가국가기관및기초자치단체(구군청)
715사설안내표지판부산진구<NA>전포1동부산진구09-25부산진여중 옆부산진여중에서 구)대우자동차 방면11.01.24.0흰(미)색바탕 남색글자동성로1200550허가기타
816사설안내표지판수영구수영구 도시국 도시관리과남천2동수영구-2010-03호부산광역시 수영구 남천동 517-11(도)남천동로 방향12.0<NA><NA>흰(미)색바탕 남색글자남천역9길1200550허가<NA>
917사설안내표지판수영구수영구 도시국 도시관리과광안1동수영구-2010-07호부산광역시 수영구 광안3동 117-3무학로 방향<NA><NA><NA>흰(미)색바탕 갈색(계열)글자수영로, 자성로1200550허가<NA>
공간정보일련번호지형지물명등록구관리기관행정동허가번호설치위치방향차도폭길어깨(보도)의폭높이색상도로구간명가로표지판규격세로표지판규격허가구분물건종류
489615410사설안내표지판해운대구해운대구 도시건설국 도시디자인과좌3동2004-56좌동 재활용센터 앞 도로0.013.60.0흰(미)색바탕 청색글자순환로1200550허가교육기관(학교 등)
489715411사설안내표지판해운대구해운대구 도시건설국 도시디자인과반여3동2006-52반여동 지리산 약국 앞12.02.53.0흰(미)색바탕 청색글자반여로, 재송로1200550허가종교시설
489815412사설안내표지판부산진구<NA>개금1동부산진구11-09사상농협 개금지점앞사상농협 개금지점에서 선봉사 방향15.02.50.0흰(미)색바탕 갈색(계열)글자금야1로1200550허가종교시설
489915413사설안내표지판해운대구<NA>송정동2005-10미림합판목재앞30.10.00.0흰(미)색바탕 갈색(계열)글자좌동로,해운로, 기장대로1200550허가종교시설
490015414사설안내표지판영도구<NA>청학2동영도구-05-09부산시 영도구 청학2동 99-240앞청학2동사무소에서 영도구청방향14.82.50.0흰(미)색바탕 갈색(계열)글자<NA>1200800허가공동주택
490115415사설안내표지판해운대구해운대구 도시건설국 도시디자인과좌2동2002-01벽산1차앞18.02.53.0기타해운대해변로,해운로1200500허가종교시설
490215416사설안내표지판영도구<NA>청학2동영도구-990.00.00.0<NA><NA>허가<NA>
490315417사설안내표지판해운대구해운대구 도시건설국 도시디자인과반여3동2004-51반여로 훼밀리마트 입구도로9.02.02.5흰(미)색바탕 청색글자반여로, 재송로1200550허가교육기관(학교 등)
490415418사설안내표지판해운대구해운대구 도시건설국 도시디자인과재송1동2004-54재송동 유창맨션 입구8.02.03.0기타소나무길1200550허가기타
490515419사설안내표지판해운대구해운대구 도시건설국 도시디자인과우2동2005-09충렬로 삼호가든 진입도로24.03.03.5흰(미)색바탕 검정(계열)글자만덕로, 충렬로,해운로20001000허가기타