Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells50359
Missing cells (%)42.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory106.0 B

Variable types

Text9
Numeric2
Categorical1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15017/S/1/datasetView.do

Alerts

데이터기준일자 has constant value ""Constant
표지판 근거리 이미지1 has 325 (3.2%) missing valuesMissing
표지판 근거리 이미지2 has 9729 (97.3%) missing valuesMissing
표지판 근거리 이미지3 has 9965 (99.7%) missing valuesMissing
표지판 근거리 이미지4 has 9992 (99.9%) missing valuesMissing
표지판 근거리 이미지5 has 9998 (> 99.9%) missing valuesMissing
표지판 원거리 이미지1 has 490 (4.9%) missing valuesMissing
표지판 원거리 이미지2 has 9860 (98.6%) missing valuesMissing

Reproduction

Analysis started2023-12-11 09:16:59.411526
Analysis finished2023-12-11 09:17:02.670103
Duration3.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

표지일련번호
Text

Distinct9654
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T18:17:02.920877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length22.3138
Min length7

Characters and Unicode

Total characters223138
Distinct characters304
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9327 ?
Unique (%)93.3%

Sample

1st rowUR(서울특별시)-[동남로]-하-13
2nd rowWR(서울특별시 구로구)-[개봉로]-하-3
3rd rowUR(서울특별시)-[삼성로]-하-16
4th rowUR(서울특별시)-70[강변북로]-상-94
5th rowWR(서울특별시 종로구)-[창경궁로]-하-3
ValueCountFrequency (%)
wr(서울특별시 5116
33.7%
ur(서울특별시 24
 
0.2%
ur(경기도 23
 
0.2%
wr(광주광역시 13
 
0.1%
ur(강원도 6
 
< 0.1%
강서구)-[금낭화로]-하-1 4
 
< 0.1%
강서구)-[금낭화로]-상-2 4
 
< 0.1%
강서구)-[금낭화로]-상-1 3
 
< 0.1%
ur(서울특별시)-[왕십리로]-하-1 3
 
< 0.1%
양천구)-[목동동로]-상-1 3
 
< 0.1%
Other values (9647) 9983
65.8%
2023-12-11T18:17:03.426365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 30000
 
13.4%
로 10418
 
4.7%
R 10062
 
4.5%
서 9991
 
4.5%
[ 9955
 
4.5%
] 9955
 
4.5%
시 8776
 
3.9%
울 8736
 
3.9%
( 8686
 
3.9%
) 8686
 
3.9%
Other values (294) 107873
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107365
48.1%
Dash Punctuation 30000
 
13.4%
Decimal Number 22719
 
10.2%
Uppercase Letter 20498
 
9.2%
Open Punctuation 18641
 
8.4%
Close Punctuation 18641
 
8.4%
Space Separator 5182
 
2.3%
Connector Punctuation 83
 
< 0.1%
Other Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 10418
 
9.7%
서 9991
 
9.3%
시 8776
 
8.2%
울 8736
 
8.1%
특 8636
 
8.0%
별 8636
 
8.0%
구 5439
 
5.1%
상 5273
 
4.9%
하 4880
 
4.5%
대 1981
 
1.8%
Other values (268) 34599
32.2%
Decimal Number
ValueCountFrequency (%)
1 5630
24.8%
2 2989
13.2%
3 2618
11.5%
4 2107
 
9.3%
6 1734
 
7.6%
0 1715
 
7.5%
5 1682
 
7.4%
8 1564
 
6.9%
7 1517
 
6.7%
9 1163
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
R 10062
49.1%
W 5218
25.5%
U 3598
 
17.6%
N 1121
 
5.5%
E 250
 
1.2%
O 83
 
0.4%
M 83
 
0.4%
A 83
 
0.4%
Open Punctuation
ValueCountFrequency (%)
[ 9955
53.4%
( 8686
46.6%
Close Punctuation
ValueCountFrequency (%)
] 9955
53.4%
) 8686
46.6%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%
Space Separator
ValueCountFrequency (%)
5182
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 83
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107365
48.1%
Common 95275
42.7%
Latin 20498
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 10418
 
9.7%
서 9991
 
9.3%
시 8776
 
8.2%
울 8736
 
8.1%
특 8636
 
8.0%
별 8636
 
8.0%
구 5439
 
5.1%
상 5273
 
4.9%
하 4880
 
4.5%
대 1981
 
1.8%
Other values (268) 34599
32.2%
Common
ValueCountFrequency (%)
- 30000
31.5%
[ 9955
 
10.4%
] 9955
 
10.4%
( 8686
 
9.1%
) 8686
 
9.1%
1 5630
 
5.9%
5182
 
5.4%
2 2989
 
3.1%
3 2618
 
2.7%
4 2107
 
2.2%
Other values (8) 9467
 
9.9%
Latin
ValueCountFrequency (%)
R 10062
49.1%
W 5218
25.5%
U 3598
 
17.6%
N 1121
 
5.5%
E 250
 
1.2%
O 83
 
0.4%
M 83
 
0.4%
A 83
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115773
51.9%
Hangul 107365
48.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 30000
25.9%
R 10062
 
8.7%
[ 9955
 
8.6%
] 9955
 
8.6%
( 8686
 
7.5%
) 8686
 
7.5%
1 5630
 
4.9%
W 5218
 
4.5%
5182
 
4.5%
U 3598
 
3.1%
Other values (16) 18801
16.2%
Hangul
ValueCountFrequency (%)
로 10418
 
9.7%
서 9991
 
9.3%
시 8776
 
8.2%
울 8736
 
8.1%
특 8636
 
8.0%
별 8636
 
8.0%
구 5439
 
5.1%
상 5273
 
4.9%
하 4880
 
4.5%
대 1981
 
1.8%
Other values (268) 34599
32.2%

표지종별
Text

Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T18:17:03.704731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length5
Mean length5.7874
Min length4

Characters and Unicode

Total characters57874
Distinct characters88
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

Unique13 ?
Unique (%)0.1%

Sample

1st row2방향표지
2nd row2지명이정표지
3rd row3방향표지
4th row2방향표지
5th row3방향예고표지
ValueCountFrequency (%)
3방향표지 3855
38.3%
2방향표지 2045
20.3%
3방향예고표지 1871
18.6%
2방향예고표지 800
 
8.0%
1방향표지 468
 
4.7%
교량표지 127
 
1.3%
2지명이정표지 84
 
0.8%
1방향예고표지 78
 
0.8%
시/군계표지 70
 
0.7%
2지명방향표지 66
 
0.7%
Other values (63) 598
 
5.9%
2023-12-11T18:17:04.163195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 10306
17.8%
표 10020
17.3%
방 9382
16.2%
향 9382
16.2%
3 5865
10.1%
2 3131
 
5.4%
고 2918
 
5.0%
예 2909
 
5.0%
1 652
 
1.1%
명 337
 
0.6%
Other values (78) 2972
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47579
82.2%
Decimal Number 9752
 
16.9%
Other Punctuation 120
 
0.2%
Open Punctuation 115
 
0.2%
Close Punctuation 115
 
0.2%
Space Separator 62
 
0.1%
Lowercase Letter 57
 
0.1%
Connector Punctuation 44
 
0.1%
Uppercase Letter 23
 
< 0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 10306
21.7%
표 10020
21.1%
방 9382
19.7%
향 9382
19.7%
고 2918
 
6.1%
예 2909
 
6.1%
명 337
 
0.7%
도 166
 
0.3%
로 156
 
0.3%
정 138
 
0.3%
Other values (63) 1865
 
3.9%
Decimal Number
ValueCountFrequency (%)
3 5865
60.1%
2 3131
32.1%
1 652
 
6.7%
0 62
 
0.6%
5 21
 
0.2%
4 15
 
0.2%
9 6
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 57
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 44
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47579
82.2%
Common 10215
 
17.7%
Latin 80
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 10306
21.7%
표 10020
21.1%
방 9382
19.7%
향 9382
19.7%
고 2918
 
6.1%
예 2909
 
6.1%
명 337
 
0.7%
도 166
 
0.3%
로 156
 
0.3%
정 138
 
0.3%
Other values (63) 1865
 
3.9%
Common
ValueCountFrequency (%)
3 5865
57.4%
2 3131
30.7%
1 652
 
6.4%
/ 120
 
1.2%
( 115
 
1.1%
) 115
 
1.1%
62
 
0.6%
0 62
 
0.6%
_ 44
 
0.4%
5 21
 
0.2%
Other values (3) 28
 
0.3%
Latin
ValueCountFrequency (%)
m 57
71.2%
K 23
28.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47579
82.2%
ASCII 10295
 
17.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 10306
21.7%
표 10020
21.1%
방 9382
19.7%
향 9382
19.7%
고 2918
 
6.1%
예 2909
 
6.1%
명 337
 
0.7%
도 166
 
0.3%
로 156
 
0.3%
정 138
 
0.3%
Other values (63) 1865
 
3.9%
ASCII
ValueCountFrequency (%)
3 5865
57.0%
2 3131
30.4%
1 652
 
6.3%
/ 120
 
1.2%
( 115
 
1.1%
) 115
 
1.1%
62
 
0.6%
0 62
 
0.6%
m 57
 
0.6%
_ 44
 
0.4%
Other values (5) 72
 
0.7%

X좌표
Real number (ℝ)

Distinct7801
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199815.32
Minimum179402.92
Maximum215935.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T18:17:04.350534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum179402.92
5-th percentile186525.56
Q1192581.42
median201430.02
Q3205996.88
95-th percentile211472.93
Maximum215935.19
Range36532.27
Interquartile range (IQR)13415.452

Descriptive statistics

Standard deviation7981.3501
Coefficient of variation (CV)0.039943634
Kurtosis-0.99853395
Mean199815.32
Median Absolute Deviation (MAD)6402.78
Skewness-0.21895052
Sum1.9981532 × 109
Variance63701950
MonotonicityNot monotonic
2023-12-11T18:17:04.500375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192287.04 15
 
0.1%
192964.35 8
 
0.1%
187984.26 4
 
< 0.1%
199615.0 4
 
< 0.1%
206974.84 4
 
< 0.1%
187694.76 4
 
< 0.1%
201405.0 4
 
< 0.1%
203401.85 4
 
< 0.1%
200082.0 4
 
< 0.1%
209316.0 4
 
< 0.1%
Other values (7791) 9945
99.5%
ValueCountFrequency (%)
179402.92 1
< 0.1%
179518.63 1
< 0.1%
179547.48 1
< 0.1%
179555.52 1
< 0.1%
181705.04 1
< 0.1%
181981.27 1
< 0.1%
181989.39 1
< 0.1%
182040.6 1
< 0.1%
182064.0 1
< 0.1%
182102.84 1
< 0.1%
ValueCountFrequency (%)
215935.19 1
< 0.1%
215896.04 1
< 0.1%
215892.94 1
< 0.1%
215865.48 1
< 0.1%
215838.52 1
< 0.1%
215753.5 1
< 0.1%
215697.27 1
< 0.1%
215653.13 1
< 0.1%
215640.02 1
< 0.1%
215603.95 1
< 0.1%

Y좌표
Real number (ℝ)

Distinct7773
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449390.88
Minimum436533.57
Maximum465554
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T18:17:04.662587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436533.57
5-th percentile441358.44
Q1444715.97
median448845.67
Q3452891.47
95-th percentile460622.83
Maximum465554
Range29020.43
Interquartile range (IQR)8175.495

Descriptive statistics

Standard deviation5839.6032
Coefficient of variation (CV)0.012994485
Kurtosis-0.47781995
Mean449390.88
Median Absolute Deviation (MAD)4090.135
Skewness0.46263054
Sum4.4939088 × 109
Variance34100966
MonotonicityNot monotonic
2023-12-11T18:17:04.803503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447168.68 15
 
0.1%
443133.58 8
 
0.1%
452619.0 4
 
< 0.1%
441362.0 4
 
< 0.1%
451355.0 4
 
< 0.1%
450738.2 4
 
< 0.1%
452037.18 4
 
< 0.1%
442650.0 4
 
< 0.1%
451095.0 4
 
< 0.1%
441685.34 4
 
< 0.1%
Other values (7763) 9945
99.5%
ValueCountFrequency (%)
436533.57 1
< 0.1%
436535.16 1
< 0.1%
436665.44 1
< 0.1%
436933.62 1
< 0.1%
436983.15 1
< 0.1%
437115.99 1
< 0.1%
437300.0 2
< 0.1%
437423.0 1
< 0.1%
437482.0 2
< 0.1%
437534.2 1
< 0.1%
ValueCountFrequency (%)
465554.0 1
< 0.1%
465520.5 1
< 0.1%
465327.87 1
< 0.1%
465194.62 1
< 0.1%
465142.34 1
< 0.1%
465106.56 1
< 0.1%
465102.05 1
< 0.1%
465022.1 2
< 0.1%
464984.94 1
< 0.1%
464982.9 1
< 0.1%

표지판 근거리 이미지1
Text

MISSING 

Distinct9597
Distinct (%)99.2%
Missing325
Missing (%)3.2%
Memory size156.2 KiB
2023-12-11T18:17:05.053225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length54
Mean length37.680103
Min length22

Characters and Unicode

Total characters364555
Distinct characters458
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9540 ?
Unique (%)98.6%

Sample

1st row/2011-10-07/URC0100동남로D/동남로거여동101-24후원거리.jpg
2nd row/2006-07-05/WRC0117개봉로D/개봉로(하)-2-근거리.jpg
3rd row/2006-06-08/WRC012341삼성로D/dsc00342.jpg
4th row/2009-01-21/URC010070강변북로U/s7304568.jpg
5th row/2006-07-12/WRC0101창경궁로D/창경궁로-3-근거리.jpg
ValueCountFrequency (%)
근.jpg 313
 
2.7%
근거리.jpg 93
 
0.8%
후.jpg 61
 
0.5%
근-re.jpg 56
 
0.5%
하3 19
 
0.2%
상4 18
 
0.2%
하4 18
 
0.2%
하1 18
 
0.2%
하2 18
 
0.2%
상3 17
 
0.1%
Other values (10193) 11083
94.6%
2023-12-11T18:17:05.468805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 49696
 
13.6%
1 34583
 
9.5%
- 30874
 
8.5%
/ 29025
 
8.0%
2 21740
 
6.0%
. 10264
 
2.8%
R 9776
 
2.7%
g 9681
 
2.7%
p 9517
 
2.6%
6 9508
 
2.6%
Other values (448) 149891
41.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148718
40.8%
Other Letter 66129
18.1%
Other Punctuation 39308
 
10.8%
Uppercase Letter 38182
 
10.5%
Lowercase Letter 32979
 
9.0%
Dash Punctuation 30874
 
8.5%
Open Punctuation 2853
 
0.8%
Close Punctuation 2749
 
0.8%
Space Separator 2039
 
0.6%
Connector Punctuation 695
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 8157
 
12.3%
근 4492
 
6.8%
길 3698
 
5.6%
리 2911
 
4.4%
거 2781
 
4.2%
동 2301
 
3.5%
상 1170
 
1.8%
도 1099
 
1.7%
대 1018
 
1.5%
면 1017
 
1.5%
Other values (389) 37485
56.7%
Lowercase Letter
ValueCountFrequency (%)
g 9681
29.4%
p 9517
28.9%
j 9373
28.4%
s 1202
 
3.6%
a 553
 
1.7%
c 486
 
1.5%
d 432
 
1.3%
r 403
 
1.2%
i 351
 
1.1%
n 192
 
0.6%
Other values (14) 789
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
R 9776
25.6%
C 8432
22.1%
U 7305
19.1%
W 6135
16.1%
D 4529
11.9%
N 1054
 
2.8%
E 276
 
0.7%
P 166
 
0.4%
J 136
 
0.4%
G 136
 
0.4%
Other values (3) 237
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 49696
33.4%
1 34583
23.3%
2 21740
14.6%
6 9508
 
6.4%
7 6542
 
4.4%
3 6022
 
4.0%
8 5852
 
3.9%
4 5599
 
3.8%
5 5004
 
3.4%
9 4172
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/ 29025
73.8%
. 10264
 
26.1%
@ 19
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2729
95.7%
[ 124
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 2625
95.5%
] 124
 
4.5%
Math Symbol
ValueCountFrequency (%)
+ 25
86.2%
~ 4
 
13.8%
Dash Punctuation
ValueCountFrequency (%)
- 30874
100.0%
Space Separator
ValueCountFrequency (%)
2039
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 695
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 227265
62.3%
Latin 71161
 
19.5%
Hangul 66129
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 8157
 
12.3%
근 4492
 
6.8%
길 3698
 
5.6%
리 2911
 
4.4%
거 2781
 
4.2%
동 2301
 
3.5%
상 1170
 
1.8%
도 1099
 
1.7%
대 1018
 
1.5%
면 1017
 
1.5%
Other values (389) 37485
56.7%
Latin
ValueCountFrequency (%)
R 9776
13.7%
g 9681
13.6%
p 9517
13.4%
j 9373
13.2%
C 8432
11.8%
U 7305
10.3%
W 6135
8.6%
D 4529
6.4%
s 1202
 
1.7%
N 1054
 
1.5%
Other values (27) 4157
5.8%
Common
ValueCountFrequency (%)
0 49696
21.9%
1 34583
15.2%
- 30874
13.6%
/ 29025
12.8%
2 21740
9.6%
. 10264
 
4.5%
6 9508
 
4.2%
7 6542
 
2.9%
3 6022
 
2.6%
8 5852
 
2.6%
Other values (12) 23159
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 298426
81.9%
Hangul 66065
 
18.1%
Compat Jamo 64
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 49696
16.7%
1 34583
11.6%
- 30874
 
10.3%
/ 29025
 
9.7%
2 21740
 
7.3%
. 10264
 
3.4%
R 9776
 
3.3%
g 9681
 
3.2%
p 9517
 
3.2%
6 9508
 
3.2%
Other values (49) 83762
28.1%
Hangul
ValueCountFrequency (%)
로 8157
 
12.3%
근 4492
 
6.8%
길 3698
 
5.6%
리 2911
 
4.4%
거 2781
 
4.2%
동 2301
 
3.5%
상 1170
 
1.8%
도 1099
 
1.7%
대 1018
 
1.5%
면 1017
 
1.5%
Other values (387) 37421
56.6%
Compat Jamo
ValueCountFrequency (%)
ㄱ 61
95.3%
ㅇ 3
 
4.7%

표지판 근거리 이미지2
Text

MISSING 

Distinct169
Distinct (%)62.4%
Missing9729
Missing (%)97.3%
Memory size156.2 KiB
2023-12-11T18:17:05.673765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length49
Mean length25.324723
Min length6

Characters and Unicode

Total characters6863
Distinct characters137
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

Unique167 ?
Unique (%)61.6%

Sample

1st row/2009-01-21/URC010070강변북로U/s7304569.jpg
2nd row근거리).jpg
3rd row/2009-01-12/URC010070강변북로U/s7304258.jpg
4th row/2009-01-21/URC010070강변북로U/s7304584.jpg
5th row/2008-09-03/URC010088U/sl557173.jpg
ValueCountFrequency (%)
근거리).jpg 99
34.6%
근거리)(1).jpg 5
 
1.7%
근.jpg 3
 
1.0%
2009-01-21/urc010070강변북로u/s7304554.jpg 1
 
0.3%
2005-12-18/nr3d/nr-3-하-1009.jpg 1
 
0.3%
2004-06-28/nr43d/nr-43-하-439(2).jpg 1
 
0.3%
2009-01-21/urc010070강변북로u/s7304674.jpg 1
 
0.3%
2009-01-28/urc010070강변북로d/s7304354.jpg 1
 
0.3%
2009-01-21/urc010070강변북로u/s7304566.jpg 1
 
0.3%
2010-09-17/wrc0119대방천길u/사진 1
 
0.3%
Other values (172) 172
60.1%
2023-12-11T18:17:06.016913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1001
 
14.6%
1 518
 
7.5%
/ 486
 
7.1%
- 462
 
6.7%
2 435
 
6.3%
. 296
 
4.3%
g 278
 
4.1%
p 276
 
4.0%
j 271
 
3.9%
7 178
 
2.6%
Other values (127) 2662
38.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2782
40.5%
Other Letter 1196
17.4%
Lowercase Letter 903
 
13.2%
Other Punctuation 782
 
11.4%
Uppercase Letter 556
 
8.1%
Dash Punctuation 462
 
6.7%
Close Punctuation 130
 
1.9%
Open Punctuation 26
 
0.4%
Space Separator 15
 
0.2%
Connector Punctuation 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
근 167
14.0%
거 141
11.8%
리 140
11.7%
로 111
 
9.3%
북 68
 
5.7%
강 57
 
4.8%
변 52
 
4.3%
도 50
 
4.2%
국 37
 
3.1%
동 31
 
2.6%
Other values (88) 342
28.6%
Lowercase Letter
ValueCountFrequency (%)
g 278
30.8%
p 276
30.6%
j 271
30.0%
s 57
 
6.3%
i 8
 
0.9%
m 4
 
0.4%
c 3
 
0.3%
b 2
 
0.2%
d 1
 
0.1%
n 1
 
0.1%
Other values (2) 2
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 1001
36.0%
1 518
18.6%
2 435
15.6%
7 178
 
6.4%
4 158
 
5.7%
3 146
 
5.2%
9 106
 
3.8%
5 94
 
3.4%
6 75
 
2.7%
8 71
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
U 169
30.4%
R 146
26.3%
C 118
21.2%
D 60
 
10.8%
W 29
 
5.2%
N 26
 
4.7%
E 5
 
0.9%
O 1
 
0.2%
A 1
 
0.2%
M 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 486
62.1%
. 296
37.9%
Dash Punctuation
ValueCountFrequency (%)
- 462
100.0%
Close Punctuation
ValueCountFrequency (%)
) 130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4208
61.3%
Latin 1459
 
21.3%
Hangul 1196
 
17.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
근 167
14.0%
거 141
11.8%
리 140
11.7%
로 111
 
9.3%
북 68
 
5.7%
강 57
 
4.8%
변 52
 
4.3%
도 50
 
4.2%
국 37
 
3.1%
동 31
 
2.6%
Other values (88) 342
28.6%
Latin
ValueCountFrequency (%)
g 278
19.1%
p 276
18.9%
j 271
18.6%
U 169
11.6%
R 146
10.0%
C 118
8.1%
D 60
 
4.1%
s 57
 
3.9%
W 29
 
2.0%
N 26
 
1.8%
Other values (12) 29
 
2.0%
Common
ValueCountFrequency (%)
0 1001
23.8%
1 518
12.3%
/ 486
11.5%
- 462
11.0%
2 435
10.3%
. 296
 
7.0%
7 178
 
4.2%
4 158
 
3.8%
3 146
 
3.5%
) 130
 
3.1%
Other values (7) 398
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5667
82.6%
Hangul 1196
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1001
17.7%
1 518
 
9.1%
/ 486
 
8.6%
- 462
 
8.2%
2 435
 
7.7%
. 296
 
5.2%
g 278
 
4.9%
p 276
 
4.9%
j 271
 
4.8%
7 178
 
3.1%
Other values (29) 1466
25.9%
Hangul
ValueCountFrequency (%)
근 167
14.0%
거 141
11.8%
리 140
11.7%
로 111
 
9.3%
북 68
 
5.7%
강 57
 
4.8%
변 52
 
4.3%
도 50
 
4.2%
국 37
 
3.1%
동 31
 
2.6%
Other values (88) 342
28.6%

표지판 근거리 이미지3
Text

MISSING 

Distinct35
Distinct (%)100.0%
Missing9965
Missing (%)99.7%
Memory size156.2 KiB
2023-12-11T18:17:06.307146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length41
Mean length37.771429
Min length28

Characters and Unicode

Total characters1322
Distinct characters50
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row/2009-01-21/URC010070강변북로U/s7304585(1).jpg
2nd row/2008-09-03/URC010088U/sl557174.jpg
3rd row/2009-01-15/URC010070U/s7304513.jpg
4th row/2005-05-03/NR3D/p4260369.jpg
5th row/2009-01-09/URC010070강변북로U/s7304197.jpg
ValueCountFrequency (%)
2009-01-21/urc010070강변북로u/s7304585(1).jpg 1
 
2.9%
2005-12-18/nr3d/nr-3-하-1009(1).jpg 1
 
2.9%
2002-5-20/국도1000서동/국도-1000-서동-15근거리3.jpg 1
 
2.9%
2009-01-28/urc010070강변북로d/s7304718.jpg 1
 
2.9%
2005-05-19/nr3u/nr-3-상-1445(3).jpg 1
 
2.9%
2009-01-28/urc010070강변북로d/s7304708.jpg 1
 
2.9%
2009-01-28/urc010070강변북로d/s7304692.jpg 1
 
2.9%
2009-01-09/urc010070강변북로u/s7304180(2).jpg 1
 
2.9%
2009-01-09/urc010070강변북로u/s7304173.jpg 1
 
2.9%
2009-01-28/urc010070강변북로d/s7304712.jpg 1
 
2.9%
Other values (25) 25
71.4%
2023-12-11T18:17:06.694467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 266
20.1%
/ 105
 
7.9%
- 96
 
7.3%
1 89
 
6.7%
2 81
 
6.1%
7 55
 
4.2%
3 48
 
3.6%
U 39
 
3.0%
p 38
 
2.9%
. 35
 
2.6%
Other values (40) 470
35.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 664
50.2%
Other Letter 164
 
12.4%
Other Punctuation 140
 
10.6%
Lowercase Letter 130
 
9.8%
Uppercase Letter 113
 
8.5%
Dash Punctuation 96
 
7.3%
Open Punctuation 7
 
0.5%
Close Punctuation 7
 
0.5%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 21
12.8%
북 19
11.6%
변 19
11.6%
강 19
11.6%
동 12
7.3%
서 12
7.3%
국 12
7.3%
도 12
7.3%
근 8
 
4.9%
리 8
 
4.9%
Other values (14) 22
13.4%
Decimal Number
ValueCountFrequency (%)
0 266
40.1%
1 89
 
13.4%
2 81
 
12.2%
7 55
 
8.3%
3 48
 
7.2%
5 35
 
5.3%
9 34
 
5.1%
4 31
 
4.7%
8 17
 
2.6%
6 8
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
U 39
34.5%
R 31
27.4%
C 22
19.5%
D 12
 
10.6%
N 9
 
8.0%
Lowercase Letter
ValueCountFrequency (%)
p 38
29.2%
g 35
26.9%
j 35
26.9%
s 21
16.2%
l 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
/ 105
75.0%
. 35
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 915
69.2%
Latin 243
 
18.4%
Hangul 164
 
12.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 21
12.8%
북 19
11.6%
변 19
11.6%
강 19
11.6%
동 12
7.3%
서 12
7.3%
국 12
7.3%
도 12
7.3%
근 8
 
4.9%
리 8
 
4.9%
Other values (14) 22
13.4%
Common
ValueCountFrequency (%)
0 266
29.1%
/ 105
 
11.5%
- 96
 
10.5%
1 89
 
9.7%
2 81
 
8.9%
7 55
 
6.0%
3 48
 
5.2%
. 35
 
3.8%
5 35
 
3.8%
9 34
 
3.7%
Other values (6) 71
 
7.8%
Latin
ValueCountFrequency (%)
U 39
16.0%
p 38
15.6%
g 35
14.4%
j 35
14.4%
R 31
12.8%
C 22
9.1%
s 21
8.6%
D 12
 
4.9%
N 9
 
3.7%
l 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1158
87.6%
Hangul 164
 
12.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 266
23.0%
/ 105
 
9.1%
- 96
 
8.3%
1 89
 
7.7%
2 81
 
7.0%
7 55
 
4.7%
3 48
 
4.1%
U 39
 
3.4%
p 38
 
3.3%
. 35
 
3.0%
Other values (16) 306
26.4%
Hangul
ValueCountFrequency (%)
로 21
12.8%
북 19
11.6%
변 19
11.6%
강 19
11.6%
동 12
7.3%
서 12
7.3%
국 12
7.3%
도 12
7.3%
근 8
 
4.9%
리 8
 
4.9%
Other values (14) 22
13.4%

표지판 근거리 이미지4
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing9992
Missing (%)99.9%
Memory size156.2 KiB
2023-12-11T18:17:06.879701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length39
Mean length37.625
Min length29

Characters and Unicode

Total characters301
Distinct characters29
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row/2008-09-03/URC010088U/sl557175.jpg
2nd row/2009-01-15/URC010070강변북로U/s7304524.jpg
3rd row/2009-01-09/URC010070강변북로U/s7304192.jpg
4th row/2009-01-09/URC010070강변북로U/s7304181(2).jpg
5th row/2009-01-28/URC010070강변북로D/s7304701.jpg
ValueCountFrequency (%)
2008-09-03/urc010088u/sl557175.jpg 1
12.5%
2009-01-15/urc010070강변북로u/s7304524.jpg 1
12.5%
2009-01-09/urc010070강변북로u/s7304192.jpg 1
12.5%
2009-01-09/urc010070강변북로u/s7304181(2).jpg 1
12.5%
2009-01-28/urc010070강변북로d/s7304701.jpg 1
12.5%
2005-05-03/nr3d/p4260359.jpg 1
12.5%
2009-01-12/urc010070강변북로u/s7304471.jpg 1
12.5%
2009-01-09/urc010070강변북로u/s7304171.jpg 1
12.5%
2023-12-11T18:17:07.169120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64
21.3%
/ 24
 
8.0%
1 23
 
7.6%
7 17
 
5.6%
- 16
 
5.3%
2 14
 
4.7%
U 13
 
4.3%
9 12
 
4.0%
3 10
 
3.3%
4 9
 
3.0%
Other values (19) 99
32.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 163
54.2%
Lowercase Letter 33
 
11.0%
Other Punctuation 32
 
10.6%
Uppercase Letter 31
 
10.3%
Other Letter 24
 
8.0%
Dash Punctuation 16
 
5.3%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64
39.3%
1 23
 
14.1%
7 17
 
10.4%
2 14
 
8.6%
9 12
 
7.4%
3 10
 
6.1%
4 9
 
5.5%
5 8
 
4.9%
8 5
 
3.1%
6 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
U 13
41.9%
R 8
25.8%
C 7
22.6%
D 2
 
6.5%
N 1
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
p 9
27.3%
g 8
24.2%
j 8
24.2%
s 7
21.2%
l 1
 
3.0%
Other Letter
ValueCountFrequency (%)
강 6
25.0%
변 6
25.0%
북 6
25.0%
로 6
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 24
75.0%
. 8
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 213
70.8%
Latin 64
 
21.3%
Hangul 24
 
8.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64
30.0%
/ 24
 
11.3%
1 23
 
10.8%
7 17
 
8.0%
- 16
 
7.5%
2 14
 
6.6%
9 12
 
5.6%
3 10
 
4.7%
4 9
 
4.2%
. 8
 
3.8%
Other values (5) 16
 
7.5%
Latin
ValueCountFrequency (%)
U 13
20.3%
p 9
14.1%
g 8
12.5%
j 8
12.5%
R 8
12.5%
s 7
10.9%
C 7
10.9%
D 2
 
3.1%
l 1
 
1.6%
N 1
 
1.6%
Hangul
ValueCountFrequency (%)
강 6
25.0%
변 6
25.0%
북 6
25.0%
로 6
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 277
92.0%
Hangul 24
 
8.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64
23.1%
/ 24
 
8.7%
1 23
 
8.3%
7 17
 
6.1%
- 16
 
5.8%
2 14
 
5.1%
U 13
 
4.7%
9 12
 
4.3%
3 10
 
3.6%
4 9
 
3.2%
Other values (15) 75
27.1%
Hangul
ValueCountFrequency (%)
강 6
25.0%
변 6
25.0%
북 6
25.0%
로 6
25.0%

표지판 근거리 이미지5
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2023-12-11T18:17:07.342443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33.5
Mean length33.5
Min length27

Characters and Unicode

Total characters67
Distinct characters35
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row/2017-04-10/WRC0104광나루로U/sam_1378(1).JPG
2nd row/2011-04-12/UR거여동길D/1.j.jpg
ValueCountFrequency (%)
2017-04-10/wrc0104광나루로u/sam_1378(1).jpg 1
50.0%
2011-04-12/ur거여동길d/1.j.jpg 1
50.0%
2023-12-11T18:17:07.652678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
 
13.4%
0 7
 
10.4%
/ 6
 
9.0%
- 4
 
6.0%
4 3
 
4.5%
2 3
 
4.5%
. 3
 
4.5%
R 2
 
3.0%
j 2
 
3.0%
U 2
 
3.0%
Other values (25) 26
38.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26
38.8%
Uppercase Letter 10
 
14.9%
Other Punctuation 9
 
13.4%
Other Letter 8
 
11.9%
Lowercase Letter 7
 
10.4%
Dash Punctuation 4
 
6.0%
Close Punctuation 1
 
1.5%
Open Punctuation 1
 
1.5%
Connector Punctuation 1
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 2
20.0%
U 2
20.0%
G 1
10.0%
P 1
10.0%
J 1
10.0%
D 1
10.0%
C 1
10.0%
W 1
10.0%
Other Letter
ValueCountFrequency (%)
길 1
12.5%
동 1
12.5%
여 1
12.5%
거 1
12.5%
로 1
12.5%
루 1
12.5%
나 1
12.5%
광 1
12.5%
Decimal Number
ValueCountFrequency (%)
1 9
34.6%
0 7
26.9%
4 3
 
11.5%
2 3
 
11.5%
7 2
 
7.7%
8 1
 
3.8%
3 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
j 2
28.6%
p 1
14.3%
m 1
14.3%
a 1
14.3%
s 1
14.3%
g 1
14.3%
Other Punctuation
ValueCountFrequency (%)
/ 6
66.7%
. 3
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42
62.7%
Latin 17
25.4%
Hangul 8
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 2
11.8%
j 2
11.8%
U 2
11.8%
p 1
 
5.9%
G 1
 
5.9%
P 1
 
5.9%
J 1
 
5.9%
D 1
 
5.9%
m 1
 
5.9%
a 1
 
5.9%
Other values (4) 4
23.5%
Common
ValueCountFrequency (%)
1 9
21.4%
0 7
16.7%
/ 6
14.3%
- 4
9.5%
4 3
 
7.1%
2 3
 
7.1%
. 3
 
7.1%
7 2
 
4.8%
) 1
 
2.4%
( 1
 
2.4%
Other values (3) 3
 
7.1%
Hangul
ValueCountFrequency (%)
길 1
12.5%
동 1
12.5%
여 1
12.5%
거 1
12.5%
로 1
12.5%
루 1
12.5%
나 1
12.5%
광 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
88.1%
Hangul 8
 
11.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
15.3%
0 7
 
11.9%
/ 6
 
10.2%
- 4
 
6.8%
4 3
 
5.1%
2 3
 
5.1%
. 3
 
5.1%
R 2
 
3.4%
j 2
 
3.4%
U 2
 
3.4%
Other values (17) 18
30.5%
Hangul
ValueCountFrequency (%)
길 1
12.5%
동 1
12.5%
여 1
12.5%
거 1
12.5%
로 1
12.5%
루 1
12.5%
나 1
12.5%
광 1
12.5%

표지판 원거리 이미지1
Text

MISSING 

Distinct9428
Distinct (%)99.1%
Missing490
Missing (%)4.9%
Memory size156.2 KiB
2023-12-11T18:17:07.889635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length54
Mean length38.384227
Min length22

Characters and Unicode

Total characters365034
Distinct characters443
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9368 ?
Unique (%)98.5%

Sample

1st row/2011-06-17/URC0100거여동길D/resized_거여동길 하12.jpg
2nd row/2006-07-05/WRC0117개봉로D/개봉로(하)-2-원거리.jpg
3rd row/2006-08-24/WRC012341D/WR(C0123)-41삼성로-하-12.jpg
4th row/2009-01-21/URC010070강변북로U/s7304567.jpg
5th row/2006-07-12/WRC0101창경궁로D/창경궁로-3-원거리.jpg
ValueCountFrequency (%)
원.jpg 355
 
3.1%
원거리.jpg 133
 
1.2%
후(원거리).jpg 39
 
0.3%
후 24
 
0.2%
하3 19
 
0.2%
하1 18
 
0.2%
하4 18
 
0.2%
상4 18
 
0.2%
앞 17
 
0.1%
하2 17
 
0.1%
Other values (9961) 10860
94.3%
2023-12-11T18:17:08.303895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 50109
 
13.7%
- 32543
 
8.9%
1 32338
 
8.9%
/ 28530
 
7.8%
2 20561
 
5.6%
. 10389
 
2.8%
R 9944
 
2.7%
6 9815
 
2.7%
g 9641
 
2.6%
p 9455
 
2.6%
Other values (433) 151709
41.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147136
40.3%
Other Letter 67846
18.6%
Other Punctuation 38939
 
10.7%
Uppercase Letter 37916
 
10.4%
Dash Punctuation 32543
 
8.9%
Lowercase Letter 32235
 
8.8%
Open Punctuation 2920
 
0.8%
Close Punctuation 2915
 
0.8%
Space Separator 2009
 
0.6%
Connector Punctuation 544
 
0.1%
Other values (2) 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 7664
 
11.3%
원 5673
 
8.4%
길 3883
 
5.7%
리 3625
 
5.3%
거 3492
 
5.1%
동 2492
 
3.7%
도 1350
 
2.0%
상 1240
 
1.8%
면 1098
 
1.6%
하 1066
 
1.6%
Other values (371) 36263
53.4%
Lowercase Letter
ValueCountFrequency (%)
g 9641
29.9%
p 9455
29.3%
j 9378
29.1%
s 1174
 
3.6%
a 552
 
1.7%
d 331
 
1.0%
c 303
 
0.9%
r 277
 
0.9%
o 232
 
0.7%
n 229
 
0.7%
Other values (15) 663
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
R 9944
26.2%
C 8493
22.4%
U 7162
18.9%
W 6168
16.3%
D 4413
11.6%
N 1070
 
2.8%
E 196
 
0.5%
P 165
 
0.4%
J 130
 
0.3%
G 130
 
0.3%
Other values (3) 45
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 50109
34.1%
1 32338
22.0%
2 20561
14.0%
6 9815
 
6.7%
7 6326
 
4.3%
4 6153
 
4.2%
8 6089
 
4.1%
3 6037
 
4.1%
5 5253
 
3.6%
9 4455
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/ 28530
73.3%
. 10389
 
26.7%
@ 19
 
< 0.1%
# 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2895
99.1%
[ 25
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 2889
99.1%
] 26
 
0.9%
Math Symbol
ValueCountFrequency (%)
+ 25
83.3%
~ 5
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 32543
100.0%
Space Separator
ValueCountFrequency (%)
2009
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 544
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 227037
62.2%
Latin 70151
 
19.2%
Hangul 67846
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 7664
 
11.3%
원 5673
 
8.4%
길 3883
 
5.7%
리 3625
 
5.3%
거 3492
 
5.1%
동 2492
 
3.7%
도 1350
 
2.0%
상 1240
 
1.8%
면 1098
 
1.6%
하 1066
 
1.6%
Other values (371) 36263
53.4%
Latin
ValueCountFrequency (%)
R 9944
14.2%
g 9641
13.7%
p 9455
13.5%
j 9378
13.4%
C 8493
12.1%
U 7162
10.2%
W 6168
8.8%
D 4413
6.3%
s 1174
 
1.7%
N 1070
 
1.5%
Other values (28) 3253
 
4.6%
Common
ValueCountFrequency (%)
0 50109
22.1%
- 32543
14.3%
1 32338
14.2%
/ 28530
12.6%
2 20561
9.1%
. 10389
 
4.6%
6 9815
 
4.3%
7 6326
 
2.8%
4 6153
 
2.7%
8 6089
 
2.7%
Other values (14) 24184
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 297188
81.4%
Hangul 67783
 
18.6%
Compat Jamo 63
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50109
16.9%
- 32543
 
11.0%
1 32338
 
10.9%
/ 28530
 
9.6%
2 20561
 
6.9%
. 10389
 
3.5%
R 9944
 
3.3%
6 9815
 
3.3%
g 9641
 
3.2%
p 9455
 
3.2%
Other values (52) 83863
28.2%
Hangul
ValueCountFrequency (%)
로 7664
 
11.3%
원 5673
 
8.4%
길 3883
 
5.7%
리 3625
 
5.3%
거 3492
 
5.2%
동 2492
 
3.7%
도 1350
 
2.0%
상 1240
 
1.8%
면 1098
 
1.6%
하 1066
 
1.6%
Other values (370) 36200
53.4%
Compat Jamo
ValueCountFrequency (%)
ㅇ 63
100.0%

표지판 원거리 이미지2
Text

MISSING 

Distinct140
Distinct (%)100.0%
Missing9860
Missing (%)98.6%
Memory size156.2 KiB
2023-12-11T18:17:08.498314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length53
Mean length33.942857
Min length7

Characters and Unicode

Total characters4752
Distinct characters113
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

Unique140 ?
Unique (%)100.0%

Sample

1st row/2006-10-25/WRC0122효령로U/효령로04(하
2nd row/2006-10-20/WRC0119강남대로D/강남대로02(상
3rd row/2006-10-25/WRC0122우면로U/우면로10(하
4th row/2013-07-23/WRC0121신림로U/크기변환_2012-12-02 09.28.29(1).jpg
5th row/2011-11-29/WRC0110자운길U/마들길 상 1(원).jpg
ValueCountFrequency (%)
원.jpg 4
 
2.5%
상 2
 
1.2%
2006-10-25/wrc0122신반포로u/신반포로16(상 1
 
0.6%
2011-08-02/urc010051고산자로u/고산자로-08-후면 1
 
0.6%
2006-10-26/wrc0104헌릉로u/헌릉로14(하 1
 
0.6%
2012-01-04/urc0100신월로d/6-1원..jpg 1
 
0.6%
2006-10-25/wrc0122우면로u/우면로04(상 1
 
0.6%
2006-10-23/wrc0122남부순환로u/남부순환로-06(하 1
 
0.6%
2008-12-22/nr6d/문안수정(원거리)8-1.jpg 1
 
0.6%
2011-01-12/wrc0117도림천로d/dscn9143(1).jpg 1
 
0.6%
Other values (146) 146
91.2%
2023-12-11T18:17:08.848139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 664
 
14.0%
2 507
 
10.7%
1 430
 
9.0%
/ 414
 
8.7%
- 349
 
7.3%
로 202
 
4.3%
R 143
 
3.0%
C 125
 
2.6%
6 116
 
2.4%
U 106
 
2.2%
Other values (103) 1696
35.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2027
42.7%
Other Letter 957
20.1%
Uppercase Letter 555
 
11.7%
Other Punctuation 501
 
10.5%
Dash Punctuation 349
 
7.3%
Lowercase Letter 209
 
4.4%
Open Punctuation 100
 
2.1%
Close Punctuation 24
 
0.5%
Space Separator 22
 
0.5%
Connector Punctuation 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 202
21.1%
남 59
 
6.2%
하 47
 
4.9%
포 41
 
4.3%
반 40
 
4.2%
상 39
 
4.1%
원 36
 
3.8%
환 35
 
3.7%
순 33
 
3.4%
부 32
 
3.3%
Other values (65) 393
41.1%
Lowercase Letter
ValueCountFrequency (%)
g 66
31.6%
j 62
29.7%
p 62
29.7%
s 5
 
2.4%
i 4
 
1.9%
m 4
 
1.9%
n 2
 
1.0%
c 1
 
0.5%
d 1
 
0.5%
k 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 664
32.8%
2 507
25.0%
1 430
21.2%
6 116
 
5.7%
4 88
 
4.3%
3 63
 
3.1%
5 60
 
3.0%
7 41
 
2.0%
8 31
 
1.5%
9 27
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
R 143
25.8%
C 125
22.5%
U 106
19.1%
W 95
17.1%
D 64
11.5%
N 12
 
2.2%
E 7
 
1.3%
M 1
 
0.2%
A 1
 
0.2%
O 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 414
82.6%
. 87
 
17.4%
Dash Punctuation
ValueCountFrequency (%)
- 349
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3031
63.8%
Hangul 957
 
20.1%
Latin 764
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 202
21.1%
남 59
 
6.2%
하 47
 
4.9%
포 41
 
4.3%
반 40
 
4.2%
상 39
 
4.1%
원 36
 
3.8%
환 35
 
3.7%
순 33
 
3.4%
부 32
 
3.3%
Other values (65) 393
41.1%
Latin
ValueCountFrequency (%)
R 143
18.7%
C 125
16.4%
U 106
13.9%
W 95
12.4%
g 66
8.6%
D 64
8.4%
j 62
8.1%
p 62
8.1%
N 12
 
1.6%
E 7
 
0.9%
Other values (11) 22
 
2.9%
Common
ValueCountFrequency (%)
0 664
21.9%
2 507
16.7%
1 430
14.2%
/ 414
13.7%
- 349
11.5%
6 116
 
3.8%
( 100
 
3.3%
4 88
 
2.9%
. 87
 
2.9%
3 63
 
2.1%
Other values (7) 213
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3795
79.9%
Hangul 957
 
20.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 664
17.5%
2 507
13.4%
1 430
11.3%
/ 414
10.9%
- 349
9.2%
R 143
 
3.8%
C 125
 
3.3%
6 116
 
3.1%
U 106
 
2.8%
( 100
 
2.6%
Other values (28) 841
22.2%
Hangul
ValueCountFrequency (%)
로 202
21.1%
남 59
 
6.2%
하 47
 
4.9%
포 41
 
4.3%
반 40
 
4.2%
상 39
 
4.1%
원 36
 
3.8%
환 35
 
3.7%
순 33
 
3.4%
부 32
 
3.3%
Other values (65) 393
41.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018-04-30
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-04-30
2nd row2018-04-30
3rd row2018-04-30
4th row2018-04-30
5th row2018-04-30

Common Values

ValueCountFrequency (%)
2018-04-30 10000
100.0%

Length

2023-12-11T18:17:08.992046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:17:09.087545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-04-30 10000
100.0%

Interactions

2023-12-11T18:17:01.821302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:17:01.564848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:17:01.933674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:17:01.699634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:17:09.161555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표지종별X좌표Y좌표표지판 근거리 이미지3표지판 근거리 이미지4표지판 근거리 이미지5
표지종별1.0000.3540.3161.0001.0000.000
X좌표0.3541.0000.5591.0001.0000.000
Y좌표0.3160.5591.0001.0001.0000.000
표지판 근거리 이미지31.0001.0001.0001.0001.000NaN
표지판 근거리 이미지41.0001.0001.0001.0001.000NaN
표지판 근거리 이미지50.0000.0000.000NaNNaN1.000
2023-12-11T18:17:09.298050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
X좌표Y좌표
X좌표1.0000.024
Y좌표0.0241.000

Missing values

2023-12-11T18:17:02.109735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:17:02.327158image/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.
2023-12-11T18:17:02.553190image/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

표지일련번호표지종별X좌표Y좌표표지판 근거리 이미지1표지판 근거리 이미지2표지판 근거리 이미지3표지판 근거리 이미지4표지판 근거리 이미지5표지판 원거리 이미지1표지판 원거리 이미지2데이터기준일자
5368UR(서울특별시)-[동남로]-하-132방향표지212306.46444954.65/2011-10-07/URC0100동남로D/동남로거여동101-24후원거리.jpg<NA><NA><NA><NA>/2011-06-17/URC0100거여동길D/resized_거여동길 하12.jpg<NA>2018-04-30
3197WR(서울특별시 구로구)-[개봉로]-하-32지명이정표지187234.52442951.27/2006-07-05/WRC0117개봉로D/개봉로(하)-2-근거리.jpg<NA><NA><NA><NA>/2006-07-05/WRC0117개봉로D/개봉로(하)-2-원거리.jpg<NA>2018-04-30
3461UR(서울특별시)-[삼성로]-하-163방향표지205321.96444140.12/2006-06-08/WRC012341삼성로D/dsc00342.jpg<NA><NA><NA><NA>/2006-08-24/WRC012341D/WR(C0123)-41삼성로-하-12.jpg<NA>2018-04-30
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4179WR(서울특별시 양천구)-[목동로]-상-10사설표지(산업/관광/공공분야 등)188070.18446695.22/2006-08-09/WRC0115등촌로U/08.등촌로-10-2.jpg<NA><NA><NA><NA>/2006-08-09/WRC0115등촌로U/08.등촌로-10-1.jpg<NA>2018-04-30
표지일련번호표지종별X좌표Y좌표표지판 근거리 이미지1표지판 근거리 이미지2표지판 근거리 이미지3표지판 근거리 이미지4표지판 근거리 이미지5표지판 원거리 이미지1표지판 원거리 이미지2데이터기준일자
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7406WR(서울특별시 용산구)-[원효로]-하-162방향표지196130.18447926.38/2006-07-31/WRC0103청파로D/용산청파원효로0031(근).jpg<NA><NA><NA><NA>/2006-07-31/WRC0103청파로D/용산청파원효로0031(원).jpg<NA>2018-04-30
4572UR(서울특별시)-[중대로]-상-53방향표지211572.42444797.47/2011-10-06/URC0100중대로U/중대로오금동오금공원옆후.jpg<NA><NA><NA><NA>/2011-10-06/URC0100중대로U/중대로오금동오금공원옆원거리(1).jpg<NA>2018-04-30
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