Overview

Dataset statistics

Number of variables27
Number of observations3391
Missing cells4806
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory765.1 KiB
Average record size in memory231.0 B

Variable types

Text9
Categorical9
Numeric8
Boolean1

Dataset

Description링크 wkt,링크 id,링크 유형 코드,시작노드 id,종료노드 id,링크 길이,시군구 코드,시군구명,읍면동 코드,읍면동명,안심벨,cctv,안심귀갓길 안내표지판,안심귀갓길 노면표기,보안등,안심귀갓길 서비스 안내판,112 위치신고 안내판,기타 시설물,부가시설물,가로등 유무,안심귀갓길 id,안심귀갓길 명,조성년월,세부위치 설명,비고,데이터기준일자,이미지명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21695/S/1/datasetView.do

Alerts

링크 유형 코드 is highly imbalanced (96.4%)Imbalance
안심벨 is highly imbalanced (53.7%)Imbalance
안심귀갓길 안내표지판 is highly imbalanced (80.3%)Imbalance
안심귀갓길 노면표기 is highly imbalanced (54.4%)Imbalance
안심귀갓길 서비스 안내판 is highly imbalanced (90.8%)Imbalance
기타 시설물 is highly imbalanced (85.9%)Imbalance
부가시설물 is highly imbalanced (81.8%)Imbalance
가로등 유무 is highly imbalanced (95.2%)Imbalance
비고 is highly imbalanced (97.6%)Imbalance
cctv has 2124 (62.6%) missing valuesMissing
보안등 has 606 (17.9%) missing valuesMissing
112 위치신고 안내판 has 1982 (58.4%) missing valuesMissing
세부위치 설명 has 94 (2.8%) missing valuesMissing
링크 wkt has unique valuesUnique
링크 id has unique valuesUnique
이미지명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 07:47:03.472829
Analysis finished2023-12-11 07:47:04.427683
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

링크 wkt
Text

UNIQUE 

Distinct3391
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-11T16:47:04.635946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length301
Median length257
Mean length77.72486
Min length57

Characters and Unicode

Total characters263565
Distinct characters33
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3391 ?
Unique (%)100.0%

Sample

1st rowMULTILINESTRING((127.068284 37.543106, 127.0680085054 37.5432042950))
2nd rowMULTILINESTRING((127.0680085054 37.5432042950, 127.0677645094 37.5432918720))
3rd rowMULTILINESTRING((127.0677645094 37.5432918720, 127.0674999999 37.543385))
4th rowMULTILINESTRING((127.0674999999 37.543385, 127.0672211360 37.5434744443))
5th rowMULTILINESTRING((127.0672211360 37.5434744443, 127.0667068808 37.5436380113))
ValueCountFrequency (%)
37.5878439225 7
 
< 0.1%
126.9471237304 7
 
< 0.1%
37.475878 4
 
< 0.1%
37.471573 4
 
< 0.1%
37.533287 4
 
< 0.1%
37.508949 4
 
< 0.1%
37.49792 4
 
< 0.1%
37.563957 4
 
< 0.1%
37.5288091641 4
 
< 0.1%
37.5944599999 4
 
< 0.1%
Other values (11880) 14932
99.7%
2023-12-11T16:47:05.203767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 23306
 
8.8%
1 19471
 
7.4%
3 19030
 
7.2%
2 18806
 
7.1%
9 18073
 
6.9%
6 15635
 
5.9%
5 15480
 
5.9%
. 14978
 
5.7%
0 14529
 
5.5%
4 12074
 
4.6%
Other values (23) 92183
35.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 168473
63.9%
Uppercase Letter 44061
 
16.7%
Other Punctuation 19076
 
7.2%
Space Separator 11587
 
4.4%
Lowercase Letter 6804
 
2.6%
Close Punctuation 6782
 
2.6%
Open Punctuation 6782
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 23306
13.8%
1 19471
11.6%
3 19030
11.3%
2 18806
11.2%
9 18073
10.7%
6 15635
9.3%
5 15480
9.2%
0 14529
8.6%
4 12074
7.2%
8 12069
7.2%
Uppercase Letter
ValueCountFrequency (%)
I 8472
19.2%
L 6215
14.1%
N 5648
12.8%
T 5648
12.8%
M 3391
7.7%
S 3391
7.7%
U 2824
 
6.4%
G 2824
 
6.4%
R 2824
 
6.4%
E 2824
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
i 1701
25.0%
t 1134
16.7%
n 1134
16.7%
u 567
 
8.3%
l 567
 
8.3%
e 567
 
8.3%
r 567
 
8.3%
g 567
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 14978
78.5%
, 4098
 
21.5%
Space Separator
ValueCountFrequency (%)
11587
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6782
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6782
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 212700
80.7%
Latin 50865
 
19.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 8472
16.7%
L 6215
12.2%
N 5648
11.1%
T 5648
11.1%
M 3391
6.7%
S 3391
6.7%
U 2824
 
5.6%
G 2824
 
5.6%
R 2824
 
5.6%
E 2824
 
5.6%
Other values (8) 6804
13.4%
Common
ValueCountFrequency (%)
7 23306
11.0%
1 19471
9.2%
3 19030
8.9%
2 18806
8.8%
9 18073
8.5%
6 15635
 
7.4%
5 15480
 
7.3%
. 14978
 
7.0%
0 14529
 
6.8%
4 12074
 
5.7%
Other values (5) 41318
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 263565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 23306
 
8.8%
1 19471
 
7.4%
3 19030
 
7.2%
2 18806
 
7.1%
9 18073
 
6.9%
6 15635
 
5.9%
5 15480
 
5.9%
. 14978
 
5.7%
0 14529
 
5.5%
4 12074
 
4.6%
Other values (23) 92183
35.0%

링크 id
Text

UNIQUE 

Distinct3391
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-11T16:47:05.425577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length18.006488
Min length18

Characters and Unicode

Total characters61060
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3391 ?
Unique (%)100.0%

Sample

1st row1121510700_01_L001
2nd row1121510700_01_L002
3rd row1121510700_01_L003
4th row1121510700_01_L004
5th row1121510700_01_L005
ValueCountFrequency (%)
1121510700_01_l001 1
 
< 0.1%
1168010800_19_l002 1
 
< 0.1%
1174010500_05_l002 1
 
< 0.1%
1174010200_12_l002 1
 
< 0.1%
1174010200_12_l003 1
 
< 0.1%
1174010200_12_l004 1
 
< 0.1%
1174010200_12_l005 1
 
< 0.1%
1174010200_12_l006 1
 
< 0.1%
1174010200_12_l007 1
 
< 0.1%
1174010200_12_l008 1
 
< 0.1%
Other values (3381) 3381
99.7%
2023-12-11T16:47:05.754551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21102
34.6%
1 14863
24.3%
_ 6782
 
11.1%
L 3391
 
5.6%
2 2783
 
4.6%
3 2634
 
4.3%
5 2390
 
3.9%
6 1829
 
3.0%
4 1723
 
2.8%
7 1325
 
2.2%
Other values (3) 2238
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50876
83.3%
Connector Punctuation 6782
 
11.1%
Uppercase Letter 3391
 
5.6%
Dash Punctuation 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21102
41.5%
1 14863
29.2%
2 2783
 
5.5%
3 2634
 
5.2%
5 2390
 
4.7%
6 1829
 
3.6%
4 1723
 
3.4%
7 1325
 
2.6%
8 1188
 
2.3%
9 1039
 
2.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6782
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 3391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57669
94.4%
Latin 3391
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21102
36.6%
1 14863
25.8%
_ 6782
 
11.8%
2 2783
 
4.8%
3 2634
 
4.6%
5 2390
 
4.1%
6 1829
 
3.2%
4 1723
 
3.0%
7 1325
 
2.3%
8 1188
 
2.1%
Other values (2) 1050
 
1.8%
Latin
ValueCountFrequency (%)
L 3391
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21102
34.6%
1 14863
24.3%
_ 6782
 
11.1%
L 3391
 
5.6%
2 2783
 
4.6%
3 2634
 
4.3%
5 2390
 
3.9%
6 1829
 
3.0%
4 1723
 
2.8%
7 1325
 
2.2%
Other values (3) 2238
 
3.7%

링크 유형 코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
201
3378 
202
 
13

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201
2nd row201
3rd row201
4th row201
5th row201

Common Values

ValueCountFrequency (%)
201 3378
99.6%
202 13
 
0.4%

Length

2023-12-11T16:47:05.883532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:47:05.974409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201 3378
99.6%
202 13
 
0.4%

시작노드 id
Text

Distinct3376
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-11T16:47:06.186933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length18.006488
Min length18

Characters and Unicode

Total characters61060
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3362 ?
Unique (%)99.1%

Sample

1st row1121510700_01_N001
2nd row1121510700_01_N002
3rd row1121510700_01_N003
4th row1121510700_01_N004
5th row1121510700_01_N005
ValueCountFrequency (%)
1156011400_21_n003 3
 
0.1%
1154510200_04_n002 2
 
0.1%
1154510200_04_n005 2
 
0.1%
1130510300_13_n025 2
 
0.1%
1156013200_13_n007 2
 
0.1%
1111018100_02_n006 2
 
0.1%
1147010300_02_n011 2
 
0.1%
1130510100_04_n008 2
 
0.1%
1126010300_21_n002 2
 
0.1%
1156012600_16_n006 2
 
0.1%
Other values (3366) 3370
99.4%
2023-12-11T16:47:06.525839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21104
34.6%
1 14860
24.3%
_ 6782
 
11.1%
N 3391
 
5.6%
2 2784
 
4.6%
3 2636
 
4.3%
5 2391
 
3.9%
6 1830
 
3.0%
4 1723
 
2.8%
7 1326
 
2.2%
Other values (3) 2233
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50876
83.3%
Connector Punctuation 6782
 
11.1%
Uppercase Letter 3391
 
5.6%
Dash Punctuation 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21104
41.5%
1 14860
29.2%
2 2784
 
5.5%
3 2636
 
5.2%
5 2391
 
4.7%
6 1830
 
3.6%
4 1723
 
3.4%
7 1326
 
2.6%
8 1188
 
2.3%
9 1034
 
2.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6782
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 3391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57669
94.4%
Latin 3391
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21104
36.6%
1 14860
25.8%
_ 6782
 
11.8%
2 2784
 
4.8%
3 2636
 
4.6%
5 2391
 
4.1%
6 1830
 
3.2%
4 1723
 
3.0%
7 1326
 
2.3%
8 1188
 
2.1%
Other values (2) 1045
 
1.8%
Latin
ValueCountFrequency (%)
N 3391
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21104
34.6%
1 14860
24.3%
_ 6782
 
11.1%
N 3391
 
5.6%
2 2784
 
4.6%
3 2636
 
4.3%
5 2391
 
3.9%
6 1830
 
3.0%
4 1723
 
2.8%
7 1326
 
2.2%
Other values (3) 2233
 
3.7%

종료노드 id
Text

Distinct3384
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-11T16:47:06.720841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length18.006488
Min length18

Characters and Unicode

Total characters61060
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3377 ?
Unique (%)99.6%

Sample

1st row1121510700_01_N002
2nd row1121510700_01_N003
3rd row1121510700_01_N004
4th row1121510700_01_N005
5th row1121510700_01_N006
ValueCountFrequency (%)
1130510300_16_n003 2
 
0.1%
1154510200_04_n008 2
 
0.1%
1144011400_06_n003 2
 
0.1%
1114014400_02_n003 2
 
0.1%
1154510200_04_n019 2
 
0.1%
1130510300_13_n026 2
 
0.1%
1111018100_02_n019 2
 
0.1%
1174010200_12_n011 1
 
< 0.1%
1174010200_12_n003 1
 
< 0.1%
1174010200_12_n008 1
 
< 0.1%
Other values (3374) 3374
99.5%
2023-12-11T16:47:07.062249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20965
34.3%
1 14680
24.0%
_ 6782
 
11.1%
N 3391
 
5.6%
2 2821
 
4.6%
3 2671
 
4.4%
5 2425
 
4.0%
6 1860
 
3.0%
4 1755
 
2.9%
7 1369
 
2.2%
Other values (3) 2341
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50876
83.3%
Connector Punctuation 6782
 
11.1%
Uppercase Letter 3391
 
5.6%
Dash Punctuation 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20965
41.2%
1 14680
28.9%
2 2821
 
5.5%
3 2671
 
5.3%
5 2425
 
4.8%
6 1860
 
3.7%
4 1755
 
3.4%
7 1369
 
2.7%
8 1241
 
2.4%
9 1089
 
2.1%
Connector Punctuation
ValueCountFrequency (%)
_ 6782
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 3391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57669
94.4%
Latin 3391
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20965
36.4%
1 14680
25.5%
_ 6782
 
11.8%
2 2821
 
4.9%
3 2671
 
4.6%
5 2425
 
4.2%
6 1860
 
3.2%
4 1755
 
3.0%
7 1369
 
2.4%
8 1241
 
2.2%
Other values (2) 1100
 
1.9%
Latin
ValueCountFrequency (%)
N 3391
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20965
34.3%
1 14680
24.0%
_ 6782
 
11.1%
N 3391
 
5.6%
2 2821
 
4.6%
3 2671
 
4.4%
5 2425
 
4.0%
6 1860
 
3.0%
4 1755
 
2.9%
7 1369
 
2.2%
Other values (3) 2341
 
3.8%

링크 길이
Real number (ℝ)

Distinct2722
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.816809
Minimum2.14
Maximum274.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.9 KiB
2023-12-11T16:47:07.195166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.14
5-th percentile9.68
Q122.16
median33.35
Q350.27
95-th percentile92.48
Maximum274.74
Range272.6
Interquartile range (IQR)28.11

Descriptive statistics

Standard deviation27.377732
Coefficient of variation (CV)0.68759232
Kurtosis7.9795596
Mean39.816809
Median Absolute Deviation (MAD)13.38
Skewness2.147965
Sum135018.8
Variance749.54022
MonotonicityNot monotonic
2023-12-11T16:47:07.318856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56.68 5
 
0.1%
20.12 5
 
0.1%
26.68 4
 
0.1%
26.77 4
 
0.1%
23.56 4
 
0.1%
35.71 4
 
0.1%
60.33 4
 
0.1%
27.67 4
 
0.1%
17.09 4
 
0.1%
23.21 4
 
0.1%
Other values (2712) 3349
98.8%
ValueCountFrequency (%)
2.14 1
< 0.1%
2.48 1
< 0.1%
2.51 1
< 0.1%
2.56 1
< 0.1%
2.66 1
< 0.1%
2.76 1
< 0.1%
2.95 1
< 0.1%
3.0 1
< 0.1%
3.04 1
< 0.1%
3.12 1
< 0.1%
ValueCountFrequency (%)
274.74 1
< 0.1%
227.88 1
< 0.1%
225.65 1
< 0.1%
223.29 1
< 0.1%
212.84 1
< 0.1%
212.11 1
< 0.1%
210.2 1
< 0.1%
195.07 1
< 0.1%
190.87 1
< 0.1%
189.24 1
< 0.1%

시군구 코드
Real number (ℝ)

Distinct25
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1416379 × 109
Minimum1.111 × 109
Maximum1.174 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.9 KiB
2023-12-11T16:47:07.435153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111 × 109
5-th percentile1.114 × 109
Q11.129 × 109
median1.135 × 109
Q31.159 × 109
95-th percentile1.171 × 109
Maximum1.174 × 109
Range63000000
Interquartile range (IQR)30000000

Descriptive statistics

Standard deviation18934636
Coefficient of variation (CV)0.016585501
Kurtosis-1.2723787
Mean1.1416379 × 109
Median Absolute Deviation (MAD)15000000
Skewness0.20624549
Sum3.871294 × 1012
Variance3.5852044 × 1014
MonotonicityNot monotonic
2023-12-11T16:47:07.780538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1130500000 370
 
10.9%
1129000000 247
 
7.3%
1168000000 224
 
6.6%
1162000000 179
 
5.3%
1135000000 177
 
5.2%
1123000000 169
 
5.0%
1159000000 157
 
4.6%
1165000000 151
 
4.5%
1111000000 144
 
4.2%
1171000000 135
 
4.0%
Other values (15) 1438
42.4%
ValueCountFrequency (%)
1111000000 144
 
4.2%
1114000000 88
 
2.6%
1117000000 126
 
3.7%
1120000000 62
 
1.8%
1121500000 119
 
3.5%
1123000000 169
5.0%
1126000000 127
 
3.7%
1129000000 247
7.3%
1130500000 370
10.9%
1132000000 86
 
2.5%
ValueCountFrequency (%)
1174000000 134
4.0%
1171000000 135
4.0%
1168000000 224
6.6%
1165000000 151
4.5%
1162000000 179
5.3%
1159000000 157
4.6%
1156000000 128
3.8%
1154500000 47
 
1.4%
1153000000 54
 
1.6%
1150000000 104
3.1%

시군구명
Categorical

Distinct25
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
서울특별시 강북구
370 
서울특별시 성북구
247 
서울특별시 강남구
224 
서울특별시 관악구
 
179
서울특별시 노원구
 
177
Other values (20)
2194 

Length

Max length10
Median length9
Mean length9.0973164
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 광진구
2nd row서울특별시 광진구
3rd row서울특별시 광진구
4th row서울특별시 광진구
5th row서울특별시 광진구

Common Values

ValueCountFrequency (%)
서울특별시 강북구 370
 
10.9%
서울특별시 성북구 247
 
7.3%
서울특별시 강남구 224
 
6.6%
서울특별시 관악구 179
 
5.3%
서울특별시 노원구 177
 
5.2%
서울특별시 동대문구 169
 
5.0%
서울특별시 동작구 157
 
4.6%
서울특별시 서초구 151
 
4.5%
서울특별시 종로구 144
 
4.2%
서울특별시 송파구 135
 
4.0%
Other values (15) 1438
42.4%

Length

2023-12-11T16:47:07.920437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 3391
50.0%
강북구 370
 
5.5%
성북구 247
 
3.6%
강남구 224
 
3.3%
관악구 179
 
2.6%
노원구 177
 
2.6%
동대문구 169
 
2.5%
동작구 157
 
2.3%
서초구 151
 
2.2%
종로구 144
 
2.1%
Other values (16) 1573
23.2%

읍면동 코드
Real number (ℝ)

Distinct169
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1416491 × 109
Minimum1.111011 × 109
Maximum1.1740109 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.9 KiB
2023-12-11T16:47:08.062125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111011 × 109
5-th percentile1.1140153 × 109
Q11.1290102 × 109
median1.1350105 × 109
Q31.1590107 × 109
95-th percentile1.1710112 × 109
Maximum1.1740109 × 109
Range62999900
Interquartile range (IQR)30000500

Descriptive statistics

Standard deviation18933893
Coefficient of variation (CV)0.016584687
Kurtosis-1.2724863
Mean1.1416491 × 109
Median Absolute Deviation (MAD)14999700
Skewness0.2063457
Sum3.8713321 × 1012
Variance3.5849232 × 1014
MonotonicityNot monotonic
2023-12-11T16:47:08.200005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1130510300 177
 
5.2%
1162010200 115
 
3.4%
1130510100 106
 
3.1%
1135010500 99
 
2.9%
1126010100 71
 
2.1%
1130510200 71
 
2.1%
1159010700 69
 
2.0%
1168010800 57
 
1.7%
1129013300 55
 
1.6%
1121510100 54
 
1.6%
Other values (159) 2517
74.2%
ValueCountFrequency (%)
1111011000 12
 
0.4%
1111011200 4
 
0.1%
1111014900 7
 
0.2%
1111016800 4
 
0.1%
1111016900 8
 
0.2%
1111017300 24
0.7%
1111017400 34
1.0%
1111017500 12
 
0.4%
1111018100 21
0.6%
1111018200 9
 
0.3%
ValueCountFrequency (%)
1174010900 26
0.8%
1174010800 24
0.7%
1174010700 20
0.6%
1174010600 15
0.4%
1174010500 22
0.6%
1174010200 16
0.5%
1174010100 11
 
0.3%
1171011400 31
0.9%
1171011200 6
 
0.2%
1171011100 17
0.5%

읍면동명
Text

Distinct168
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-11T16:47:08.478303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.1356532
Min length2

Characters and Unicode

Total characters10633
Distinct characters153
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 row화양동
2nd row화양동
3rd row화양동
4th row화양동
5th row화양동
ValueCountFrequency (%)
수유동 177
 
5.2%
신림동 115
 
3.4%
미아동 106
 
3.1%
상계동 99
 
2.9%
번동 71
 
2.1%
면목동 71
 
2.1%
사당동 69
 
2.0%
논현동 57
 
1.7%
정릉동 55
 
1.6%
중곡동 54
 
1.6%
Other values (158) 2517
74.2%
2023-12-11T16:47:08.886048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 3388
31.9%
신 342
 
3.2%
가 259
 
2.4%
수 207
 
1.9%
유 177
 
1.7%
림 174
 
1.6%
상 157
 
1.5%
계 153
 
1.4%
곡 146
 
1.4%
당 138
 
1.3%
Other values (143) 5492
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10433
98.1%
Decimal Number 200
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3388
32.5%
신 342
 
3.3%
가 259
 
2.5%
수 207
 
2.0%
유 177
 
1.7%
림 174
 
1.7%
상 157
 
1.5%
계 153
 
1.5%
곡 146
 
1.4%
당 138
 
1.3%
Other values (136) 5292
50.7%
Decimal Number
ValueCountFrequency (%)
1 67
33.5%
2 56
28.0%
3 32
16.0%
4 23
 
11.5%
5 10
 
5.0%
6 7
 
3.5%
7 5
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10433
98.1%
Common 200
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3388
32.5%
신 342
 
3.3%
가 259
 
2.5%
수 207
 
2.0%
유 177
 
1.7%
림 174
 
1.7%
상 157
 
1.5%
계 153
 
1.5%
곡 146
 
1.4%
당 138
 
1.3%
Other values (136) 5292
50.7%
Common
ValueCountFrequency (%)
1 67
33.5%
2 56
28.0%
3 32
16.0%
4 23
 
11.5%
5 10
 
5.0%
6 7
 
3.5%
7 5
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10433
98.1%
ASCII 200
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 3388
32.5%
신 342
 
3.3%
가 259
 
2.5%
수 207
 
2.0%
유 177
 
1.7%
림 174
 
1.7%
상 157
 
1.5%
계 153
 
1.5%
곡 146
 
1.4%
당 138
 
1.3%
Other values (136) 5292
50.7%
ASCII
ValueCountFrequency (%)
1 67
33.5%
2 56
28.0%
3 32
16.0%
4 23
 
11.5%
5 10
 
5.0%
6 7
 
3.5%
7 5
 
2.5%

안심벨
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
<NA>
2457 
1
892 
2
 
39
3
 
3

Length

Max length4
Median length4
Mean length3.1736951
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2457
72.5%
1 892
 
26.3%
2 39
 
1.2%
3 3
 
0.1%

Length

2023-12-11T16:47:09.024372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:47:09.127573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2457
72.5%
1 892
 
26.3%
2 39
 
1.2%
3 3
 
0.1%

cctv
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)0.8%
Missing2124
Missing (%)62.6%
Infinite0
Infinite (%)0.0%
Mean1.8847672
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.9 KiB
2023-12-11T16:47:09.218546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile4
Maximum13
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2919657
Coefficient of variation (CV)0.68547761
Kurtosis6.1776043
Mean1.8847672
Median Absolute Deviation (MAD)0
Skewness1.8770207
Sum2388
Variance1.6691754
MonotonicityNot monotonic
2023-12-11T16:47:09.321036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 733
 
21.6%
2 192
 
5.7%
3 178
 
5.2%
4 115
 
3.4%
5 36
 
1.1%
6 6
 
0.2%
8 4
 
0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
13 1
 
< 0.1%
(Missing) 2124
62.6%
ValueCountFrequency (%)
1 733
21.6%
2 192
 
5.7%
3 178
 
5.2%
4 115
 
3.4%
5 36
 
1.1%
6 6
 
0.2%
7 1
 
< 0.1%
8 4
 
0.1%
9 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
13 1
 
< 0.1%
9 1
 
< 0.1%
8 4
 
0.1%
7 1
 
< 0.1%
6 6
 
0.2%
5 36
 
1.1%
4 115
 
3.4%
3 178
 
5.2%
2 192
 
5.7%
1 733
21.6%

안심귀갓길 안내표지판
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
<NA>
3101 
1
 
231
2
 
34
3
 
18
4
 
5

Length

Max length4
Median length4
Mean length3.7434385
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3101
91.4%
1 231
 
6.8%
2 34
 
1.0%
3 18
 
0.5%
4 5
 
0.1%
5 2
 
0.1%

Length

2023-12-11T16:47:09.460018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:47:09.576904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3101
91.4%
1 231
 
6.8%
2 34
 
1.0%
3 18
 
0.5%
4 5
 
0.1%
5 2
 
0.1%

안심귀갓길 노면표기
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
<NA>
2042 
1
1215 
2
 
120
3
 
12
5
 
1

Length

Max length4
Median length4
Mean length2.8065467
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2042
60.2%
1 1215
35.8%
2 120
 
3.5%
3 12
 
0.4%
5 1
 
< 0.1%
4 1
 
< 0.1%

Length

2023-12-11T16:47:09.700337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:47:09.840648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2042
60.2%
1 1215
35.8%
2 120
 
3.5%
3 12
 
0.4%
5 1
 
< 0.1%
4 1
 
< 0.1%

보안등
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)0.5%
Missing606
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean2.1633752
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.9 KiB
2023-12-11T16:47:09.949239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum29
Range28
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4844336
Coefficient of variation (CV)0.68616559
Kurtosis43.129377
Mean2.1633752
Median Absolute Deviation (MAD)1
Skewness3.8074992
Sum6025
Variance2.2035432
MonotonicityNot monotonic
2023-12-11T16:47:10.065812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 1099
32.4%
2 864
25.5%
3 458
13.5%
4 203
 
6.0%
5 73
 
2.2%
6 38
 
1.1%
7 25
 
0.7%
8 14
 
0.4%
9 6
 
0.2%
13 2
 
0.1%
Other values (3) 3
 
0.1%
(Missing) 606
17.9%
ValueCountFrequency (%)
1 1099
32.4%
2 864
25.5%
3 458
13.5%
4 203
 
6.0%
5 73
 
2.2%
6 38
 
1.1%
7 25
 
0.7%
8 14
 
0.4%
9 6
 
0.2%
11 1
 
< 0.1%
ValueCountFrequency (%)
29 1
 
< 0.1%
13 2
 
0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
9 6
 
0.2%
8 14
 
0.4%
7 25
 
0.7%
6 38
 
1.1%
5 73
 
2.2%
4 203
6.0%

안심귀갓길 서비스 안내판
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
<NA>
3325 
1
 
61
2
 
5

Length

Max length4
Median length4
Mean length3.9416101
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3325
98.1%
1 61
 
1.8%
2 5
 
0.1%

Length

2023-12-11T16:47:10.199972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:47:10.331409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3325
98.1%
1 61
 
1.8%
2 5
 
0.1%

112 위치신고 안내판
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)0.5%
Missing1982
Missing (%)58.4%
Infinite0
Infinite (%)0.0%
Mean1.2271114
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.9 KiB
2023-12-11T16:47:10.527029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.57240294
Coefficient of variation (CV)0.46646371
Kurtosis35.835929
Mean1.2271114
Median Absolute Deviation (MAD)0
Skewness4.4642752
Sum1729
Variance0.32764513
MonotonicityNot monotonic
2023-12-11T16:47:10.647541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 1150
33.9%
2 221
 
6.5%
3 26
 
0.8%
4 7
 
0.2%
5 2
 
0.1%
6 2
 
0.1%
9 1
 
< 0.1%
(Missing) 1982
58.4%
ValueCountFrequency (%)
1 1150
33.9%
2 221
 
6.5%
3 26
 
0.8%
4 7
 
0.2%
5 2
 
0.1%
6 2
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
6 2
 
0.1%
5 2
 
0.1%
4 7
 
0.2%
3 26
 
0.8%
2 221
 
6.5%
1 1150
33.9%

기타 시설물
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
<NA>
3207 
0
 
127
1
 
51
2
 
3
3
 
2

Length

Max length4
Median length4
Mean length3.8372162
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3207
94.6%
0 127
 
3.7%
1 51
 
1.5%
2 3
 
0.1%
3 2
 
0.1%
6 1
 
< 0.1%

Length

2023-12-11T16:47:10.815771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:47:10.965453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3207
94.6%
0 127
 
3.7%
1 51
 
1.5%
2 3
 
0.1%
3 2
 
0.1%
6 1
 
< 0.1%

부가시설물
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
<NA>
3137 
212
 
177
211
 
64
211212
 
9
213
 
3

Length

Max length6
Median length4
Mean length3.9339428
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row212
2nd row<NA>
3rd row212
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3137
92.5%
212 177
 
5.2%
211 64
 
1.9%
211212 9
 
0.3%
213 3
 
0.1%
211213 1
 
< 0.1%

Length

2023-12-11T16:47:11.105147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:47:11.285260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3137
92.5%
212 177
 
5.2%
211 64
 
1.9%
211212 9
 
0.3%
213 3
 
0.1%
211213 1
 
< 0.1%

가로등 유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
False
3373 
True
 
18
ValueCountFrequency (%)
False 3373
99.5%
True 18
 
0.5%
2023-12-11T16:47:11.416502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

안심귀갓길 id
Text

Distinct362
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-11T16:47:11.720118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length13.006488
Min length13

Characters and Unicode

Total characters44105
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

Unique0 ?
Unique (%)0.0%

Sample

1st row1121510700_01
2nd row1121510700_01
3rd row1121510700_01
4th row1121510700_01
5th row1121510700_01
ValueCountFrequency (%)
1130510200_20 28
 
0.8%
1130510300_13 26
 
0.8%
1123010400_10 25
 
0.7%
1168010500_11 22
 
0.6%
1129013600_08 22
 
0.6%
1130510300_03 21
 
0.6%
1111018100_02 21
 
0.6%
1130510200_18 21
 
0.6%
1130510300_09 21
 
0.6%
1162010200_06 20
 
0.6%
Other values (352) 3164
93.3%
2023-12-11T16:47:12.225056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14866
33.7%
1 13706
31.1%
_ 3391
 
7.7%
2 2274
 
5.2%
3 2198
 
5.0%
5 2021
 
4.6%
6 1492
 
3.4%
4 1320
 
3.0%
7 1032
 
2.3%
8 947
 
2.1%
Other values (2) 858
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40703
92.3%
Connector Punctuation 3391
 
7.7%
Dash Punctuation 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14866
36.5%
1 13706
33.7%
2 2274
 
5.6%
3 2198
 
5.4%
5 2021
 
5.0%
6 1492
 
3.7%
4 1320
 
3.2%
7 1032
 
2.5%
8 947
 
2.3%
9 847
 
2.1%
Connector Punctuation
ValueCountFrequency (%)
_ 3391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44105
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14866
33.7%
1 13706
31.1%
_ 3391
 
7.7%
2 2274
 
5.2%
3 2198
 
5.0%
5 2021
 
4.6%
6 1492
 
3.4%
4 1320
 
3.0%
7 1032
 
2.3%
8 947
 
2.1%
Other values (2) 858
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14866
33.7%
1 13706
31.1%
_ 3391
 
7.7%
2 2274
 
5.2%
3 2198
 
5.0%
5 2021
 
4.6%
6 1492
 
3.4%
4 1320
 
3.0%
7 1032
 
2.3%
8 947
 
2.1%
Other values (2) 858
 
1.9%

안심귀갓길 명
Text

Distinct362
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-11T16:47:12.611729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.1386022
Min length6

Characters and Unicode

Total characters20816
Distinct characters54
Distinct categories3 ?
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 row광진안심01
2nd row광진안심01
3rd row광진안심01
4th row광진안심01
5th row광진안심01
ValueCountFrequency (%)
강북안심20 28
 
0.8%
강북안심13 26
 
0.8%
동대문안심10 25
 
0.7%
강남안심11 22
 
0.6%
종암안심08 22
 
0.6%
강북안심03 21
 
0.6%
종로안심02 21
 
0.6%
강북안심18 21
 
0.6%
강북안심09 21
 
0.6%
관악안심06 20
 
0.6%
Other values (352) 3164
93.3%
2023-12-11T16:47:13.176128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 3391
16.3%
심 3391
16.3%
0 2211
 
10.6%
1 1693
 
8.1%
강 778
 
3.7%
2 613
 
2.9%
동 522
 
2.5%
서 493
 
2.4%
북 474
 
2.3%
4 428
 
2.1%
Other values (44) 6822
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14012
67.3%
Decimal Number 6793
32.6%
Dash Punctuation 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 3391
24.2%
심 3391
24.2%
강 778
 
5.6%
동 522
 
3.7%
서 493
 
3.5%
북 474
 
3.4%
대 320
 
2.3%
문 320
 
2.3%
포 207
 
1.5%
종 205
 
1.5%
Other values (33) 3911
27.9%
Decimal Number
ValueCountFrequency (%)
0 2211
32.5%
1 1693
24.9%
2 613
 
9.0%
4 428
 
6.3%
3 384
 
5.7%
6 381
 
5.6%
5 297
 
4.4%
8 280
 
4.1%
9 254
 
3.7%
7 252
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14012
67.3%
Common 6804
32.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 3391
24.2%
심 3391
24.2%
강 778
 
5.6%
동 522
 
3.7%
서 493
 
3.5%
북 474
 
3.4%
대 320
 
2.3%
문 320
 
2.3%
포 207
 
1.5%
종 205
 
1.5%
Other values (33) 3911
27.9%
Common
ValueCountFrequency (%)
0 2211
32.5%
1 1693
24.9%
2 613
 
9.0%
4 428
 
6.3%
3 384
 
5.6%
6 381
 
5.6%
5 297
 
4.4%
8 280
 
4.1%
9 254
 
3.7%
7 252
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14012
67.3%
ASCII 6804
32.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 3391
24.2%
심 3391
24.2%
강 778
 
5.6%
동 522
 
3.7%
서 493
 
3.5%
북 474
 
3.4%
대 320
 
2.3%
문 320
 
2.3%
포 207
 
1.5%
종 205
 
1.5%
Other values (33) 3911
27.9%
ASCII
ValueCountFrequency (%)
0 2211
32.5%
1 1693
24.9%
2 613
 
9.0%
4 428
 
6.3%
3 384
 
5.6%
6 381
 
5.6%
5 297
 
4.4%
8 280
 
4.1%
9 254
 
3.7%
7 252
 
3.7%

조성년월
Real number (ℝ)

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.7756
Minimum2013
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.9 KiB
2023-12-11T16:47:13.333993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12014
median2014
Q32015
95-th percentile2019
Maximum2022
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8886572
Coefficient of variation (CV)0.00093740326
Kurtosis3.4493285
Mean2014.7756
Median Absolute Deviation (MAD)0
Skewness2.0379098
Sum6832104
Variance3.567026
MonotonicityNot monotonic
2023-12-11T16:47:13.477211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2014 1973
58.2%
2015 485
 
14.3%
2013 385
 
11.4%
2018 134
 
4.0%
2019 127
 
3.7%
2021 112
 
3.3%
2016 80
 
2.4%
2017 59
 
1.7%
2020 25
 
0.7%
2022 11
 
0.3%
ValueCountFrequency (%)
2013 385
 
11.4%
2014 1973
58.2%
2015 485
 
14.3%
2016 80
 
2.4%
2017 59
 
1.7%
2018 134
 
4.0%
2019 127
 
3.7%
2020 25
 
0.7%
2021 112
 
3.3%
2022 11
 
0.3%
ValueCountFrequency (%)
2022 11
 
0.3%
2021 112
 
3.3%
2020 25
 
0.7%
2019 127
 
3.7%
2018 134
 
4.0%
2017 59
 
1.7%
2016 80
 
2.4%
2015 485
 
14.3%
2014 1973
58.2%
2013 385
 
11.4%

세부위치 설명
Text

MISSING 

Distinct524
Distinct (%)15.9%
Missing94
Missing (%)2.8%
Memory size26.6 KiB
2023-12-11T16:47:13.779013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length6.4746739
Min length3

Characters and Unicode

Total characters21347
Distinct characters261
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)1.7%

Sample

1st row동일로24길
2nd row동일로24길
3rd row동일로24길
4th row동일로24길
5th row동일로24길
ValueCountFrequency (%)
노해로 47
 
1.3%
도봉로 35
 
0.9%
11길 34
 
0.9%
33길 34
 
0.9%
중앙로 30
 
0.8%
한천로123길 28
 
0.8%
남부순환로 27
 
0.7%
26길 26
 
0.7%
전농로37길 25
 
0.7%
41길 23
 
0.6%
Other values (540) 3423
91.7%
2023-12-11T16:47:14.334003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 3241
 
15.2%
로 3084
 
14.4%
1 1312
 
6.1%
2 980
 
4.6%
3 772
 
3.6%
4 627
 
2.9%
5 563
 
2.6%
6 534
 
2.5%
435
 
2.0%
7 414
 
1.9%
Other values (251) 9385
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14799
69.3%
Decimal Number 6094
28.5%
Space Separator 435
 
2.0%
Uppercase Letter 18
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 3241
21.9%
로 3084
20.8%
봉 350
 
2.4%
대 338
 
2.3%
산 268
 
1.8%
가 259
 
1.8%
도 242
 
1.6%
천 232
 
1.6%
동 204
 
1.4%
사 154
 
1.0%
Other values (227) 6427
43.4%
Uppercase Letter
ValueCountFrequency (%)
E 3
16.7%
A 2
11.1%
N 2
11.1%
U 2
11.1%
O 2
11.1%
C 1
 
5.6%
I 1
 
5.6%
T 1
 
5.6%
D 1
 
5.6%
F 1
 
5.6%
Other values (2) 2
11.1%
Decimal Number
ValueCountFrequency (%)
1 1312
21.5%
2 980
16.1%
3 772
12.7%
4 627
10.3%
5 563
9.2%
6 534
8.8%
7 414
 
6.8%
8 325
 
5.3%
9 305
 
5.0%
0 262
 
4.3%
Space Separator
ValueCountFrequency (%)
435
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14799
69.3%
Common 6530
30.6%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 3241
21.9%
로 3084
20.8%
봉 350
 
2.4%
대 338
 
2.3%
산 268
 
1.8%
가 259
 
1.8%
도 242
 
1.6%
천 232
 
1.6%
동 204
 
1.4%
사 154
 
1.0%
Other values (227) 6427
43.4%
Common
ValueCountFrequency (%)
1 1312
20.1%
2 980
15.0%
3 772
11.8%
4 627
9.6%
5 563
8.6%
6 534
8.2%
435
 
6.7%
7 414
 
6.3%
8 325
 
5.0%
9 305
 
4.7%
Other values (2) 263
 
4.0%
Latin
ValueCountFrequency (%)
E 3
16.7%
A 2
11.1%
N 2
11.1%
U 2
11.1%
O 2
11.1%
C 1
 
5.6%
I 1
 
5.6%
T 1
 
5.6%
D 1
 
5.6%
F 1
 
5.6%
Other values (2) 2
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14799
69.3%
ASCII 6548
30.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 3241
21.9%
로 3084
20.8%
봉 350
 
2.4%
대 338
 
2.3%
산 268
 
1.8%
가 259
 
1.8%
도 242
 
1.6%
천 232
 
1.6%
동 204
 
1.4%
사 154
 
1.0%
Other values (227) 6427
43.4%
ASCII
ValueCountFrequency (%)
1 1312
20.0%
2 980
15.0%
3 772
11.8%
4 627
9.6%
5 563
8.6%
6 534
8.2%
435
 
6.6%
7 414
 
6.3%
8 325
 
5.0%
9 305
 
4.7%
Other values (14) 281
 
4.3%

비고
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
<NA>
3374 
안심길 공사중
 
15
프로젝터
 
1
특별순찰구역 표지판, 마중길(우리지역 안전 지킴이) 표지판
 
1

Length

Max length32
Median length4
Mean length4.0215276
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3374
99.5%
안심길 공사중 15
 
0.4%
프로젝터 1
 
< 0.1%
특별순찰구역 표지판, 마중길(우리지역 안전 지킴이) 표지판 1
 
< 0.1%

Length

2023-12-11T16:47:14.497593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:47:14.614602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3374
98.9%
안심길 15
 
0.4%
공사중 15
 
0.4%
표지판 2
 
0.1%
프로젝터 1
 
< 0.1%
특별순찰구역 1
 
< 0.1%
마중길(우리지역 1
 
< 0.1%
안전 1
 
< 0.1%
지킴이 1
 
< 0.1%

데이터기준일자
Real number (ℝ)

Distinct60
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20220973
Minimum20220727
Maximum20221203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.9 KiB
2023-12-11T16:47:14.755630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220727
5-th percentile20220802
Q120220907
median20221006
Q320221107
95-th percentile20221111
Maximum20221203
Range476
Interquartile range (IQR)200

Descriptive statistics

Standard deviation116.08121
Coefficient of variation (CV)5.7406343 × 10-6
Kurtosis-0.84893008
Mean20220973
Median Absolute Deviation (MAD)101
Skewness-0.33714965
Sum6.8569319 × 1010
Variance13474.848
MonotonicityNot monotonic
2023-12-11T16:47:14.956192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20221109 282
 
8.3%
20221107 187
 
5.5%
20221108 172
 
5.1%
20221006 141
 
4.2%
20221005 119
 
3.5%
20221110 107
 
3.2%
20221013 102
 
3.0%
20220929 101
 
3.0%
20220927 100
 
2.9%
20220818 92
 
2.7%
Other values (50) 1988
58.6%
ValueCountFrequency (%)
20220727 74
2.2%
20220729 87
2.6%
20220802 71
2.1%
20220805 13
 
0.4%
20220809 40
1.2%
20220812 47
1.4%
20220818 92
2.7%
20220819 52
1.5%
20220822 22
 
0.6%
20220823 69
2.0%
ValueCountFrequency (%)
20221203 34
 
1.0%
20221117 30
 
0.9%
20221116 50
 
1.5%
20221115 30
 
0.9%
20221114 8
 
0.2%
20221111 37
 
1.1%
20221110 107
 
3.2%
20221109 282
8.3%
20221108 172
5.1%
20221107 187
5.5%

이미지명
Text

UNIQUE 

Distinct3391
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-11T16:47:15.208654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length23.006488
Min length23

Characters and Unicode

Total characters78015
Distinct characters18
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3391 ?
Unique (%)100.0%

Sample

1st row1121510700_01_L001.jpeg
2nd row1121510700_01_L002.jpeg
3rd row1121510700_01_L003.jpeg
4th row1121510700_01_L004.jpeg
5th row1121510700_01_L005.jpeg
ValueCountFrequency (%)
1121510700_01_l001.jpeg 1
 
< 0.1%
1168010800_19_l002.jpeg 1
 
< 0.1%
1174010500_05_l002.jpeg 1
 
< 0.1%
1174010200_12_l002.jpeg 1
 
< 0.1%
1174010200_12_l003.jpeg 1
 
< 0.1%
1174010200_12_l004.jpeg 1
 
< 0.1%
1174010200_12_l005.jpeg 1
 
< 0.1%
1174010200_12_l006.jpeg 1
 
< 0.1%
1174010200_12_l007.jpeg 1
 
< 0.1%
1174010200_12_l008.jpeg 1
 
< 0.1%
Other values (3381) 3381
99.7%
2023-12-11T16:47:15.593853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21102
27.0%
1 14863
19.1%
_ 6782
 
8.7%
. 3391
 
4.3%
g 3391
 
4.3%
e 3391
 
4.3%
j 3391
 
4.3%
p 3391
 
4.3%
L 3391
 
4.3%
2 2783
 
3.6%
Other values (8) 12139
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50876
65.2%
Lowercase Letter 13564
 
17.4%
Connector Punctuation 6782
 
8.7%
Other Punctuation 3391
 
4.3%
Uppercase Letter 3391
 
4.3%
Dash Punctuation 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21102
41.5%
1 14863
29.2%
2 2783
 
5.5%
3 2634
 
5.2%
5 2390
 
4.7%
6 1829
 
3.6%
4 1723
 
3.4%
7 1325
 
2.6%
8 1188
 
2.3%
9 1039
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
g 3391
25.0%
e 3391
25.0%
j 3391
25.0%
p 3391
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6782
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3391
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 3391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61060
78.3%
Latin 16955
 
21.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21102
34.6%
1 14863
24.3%
_ 6782
 
11.1%
. 3391
 
5.6%
2 2783
 
4.6%
3 2634
 
4.3%
5 2390
 
3.9%
6 1829
 
3.0%
4 1723
 
2.8%
7 1325
 
2.2%
Other values (3) 2238
 
3.7%
Latin
ValueCountFrequency (%)
g 3391
20.0%
e 3391
20.0%
j 3391
20.0%
p 3391
20.0%
L 3391
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78015
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21102
27.0%
1 14863
19.1%
_ 6782
 
8.7%
. 3391
 
4.3%
g 3391
 
4.3%
e 3391
 
4.3%
j 3391
 
4.3%
p 3391
 
4.3%
L 3391
 
4.3%
2 2783
 
3.6%
Other values (8) 12139
15.6%

Sample

링크 wkt링크 id링크 유형 코드시작노드 id종료노드 id링크 길이시군구 코드시군구명읍면동 코드읍면동명안심벨cctv안심귀갓길 안내표지판안심귀갓길 노면표기보안등안심귀갓길 서비스 안내판112 위치신고 안내판기타 시설물부가시설물가로등 유무안심귀갓길 id안심귀갓길 명조성년월세부위치 설명비고데이터기준일자이미지명
0MULTILINESTRING((127.068284 37.543106, 127.0680085054 37.5432042950))1121510700_01_L0012011121510700_01_N0011121510700_01_N00226.681121500000서울특별시 광진구1121510700화양동15<NA><NA>3<NA><NA><NA>212N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L001.jpeg
1MULTILINESTRING((127.0680085054 37.5432042950, 127.0677645094 37.5432918720))1121510700_01_L0022011121510700_01_N0021121510700_01_N00323.651121500000서울특별시 광진구1121510700화양동<NA><NA><NA><NA>2<NA><NA><NA><NA>N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L002.jpeg
2MULTILINESTRING((127.0677645094 37.5432918720, 127.0674999999 37.543385))1121510700_01_L0032011121510700_01_N0031121510700_01_N00425.561121500000서울특별시 광진구1121510700화양동11<NA><NA>1<NA><NA><NA>212N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L003.jpeg
3MULTILINESTRING((127.0674999999 37.543385, 127.0672211360 37.5434744443))1121510700_01_L0042011121510700_01_N0041121510700_01_N00526.571121500000서울특별시 광진구1121510700화양동<NA><NA><NA><NA>1<NA><NA><NA><NA>N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L004.jpeg
4MULTILINESTRING((127.0672211360 37.5434744443, 127.0667068808 37.5436380113))1121510700_01_L0052011121510700_01_N0051121510700_01_N00648.941121500000서울특별시 광진구1121510700화양동<NA><NA><NA><NA>1<NA><NA><NA><NA>N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L005.jpeg
5MULTILINESTRING((127.0667068808 37.5436380113, 127.0664170081 37.5437411541))1121510700_01_L0062011121510700_01_N0061121510700_01_N00728.061121500000서울특별시 광진구1121510700화양동<NA><NA><NA><NA><NA><NA><NA><NA><NA>N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L006.jpeg
6MULTILINESTRING((127.0664170081 37.5437411541, 127.0661636311 37.5438282965))1121510700_01_L0072011121510700_01_N0071121510700_01_N00824.391121500000서울특별시 광진구1121510700화양동<NA><NA><NA><NA>2<NA>1<NA><NA>N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L007.jpeg
7MULTILINESTRING((127.0661636311 37.5438282965, 127.0658882416 37.5439215604))1121510700_01_L0082011121510700_01_N0081121510700_01_N00926.451121500000서울특별시 광진구1121510700화양동<NA><NA><NA><NA><NA><NA><NA><NA><NA>N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L008.jpeg
8MULTILINESTRING((127.0658882416 37.5439215604, 127.0655407569 37.5440502980))1121510700_01_L0092011121510700_01_N0091121510700_01_N01033.871121500000서울특별시 광진구1121510700화양동15<NA><NA>2<NA><NA><NA>212N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L009.jpeg
9MULTILINESTRING((127.0655407569 37.5440502980, 127.065279 37.544142))1121510700_01_L0102011121510700_01_N0101121510700_01_N01125.271121500000서울특별시 광진구1121510700화양동15<NA><NA>1<NA><NA><NA><NA>N1121510700_01광진안심012014동일로24길<NA>202207271121510700_01_L010.jpeg
링크 wkt링크 id링크 유형 코드시작노드 id종료노드 id링크 길이시군구 코드시군구명읍면동 코드읍면동명안심벨cctv안심귀갓길 안내표지판안심귀갓길 노면표기보안등안심귀갓길 서비스 안내판112 위치신고 안내판기타 시설물부가시설물가로등 유무안심귀갓길 id안심귀갓길 명조성년월세부위치 설명비고데이터기준일자이미지명
3381MultiLineString((127.0110499999 37.4901089999, 127.0116539999 37.490369))1165010800_07_L0082011165010800_07_N0081165010800_07_N00960.711165000000서울특별시 서초구1165010800서초동<NA><NA><NA>12<NA><NA><NA><NA>N1165010800_07서초안심072014반포대로22길<NA>202210111165010800_07_L008.jpeg
3382MultiLineString((127.0116539999 37.490369, 127.0123289999 37.4906709999))1165010800_07_L0092011165010800_07_N0091165010800_07_N01068.461165000000서울특별시 서초구1165010800서초동11<NA>13<NA>4<NA><NA>N1165010800_07서초안심072014반포대로22길<NA>202210111165010800_07_L009.jpeg
3383MultiLineString((127.0123289999 37.4906709999, 127.012669 37.490889))1165010800_07_L0102011165010800_07_N0101165010800_07_N01138.591165000000서울특별시 서초구1165010800서초동<NA><NA><NA><NA><NA><NA><NA><NA><NA>N1165010800_07서초안심072014반포대로22길<NA>202210111165010800_07_L010.jpeg
3384MultiLineString((127.012669 37.490889, 127.0129909999 37.491103))1165010800_07_L0112011165010800_07_N0111165010800_07_N01237.081165000000서울특별시 서초구1165010800서초동<NA><NA><NA><NA><NA><NA><NA><NA><NA>N1165010800_07서초안심072014반포대로22길<NA>202210111165010800_07_L011.jpeg
3385MultiLineString((127.0129909999 37.491103, 127.0133950813 37.4913853525))1165010800_07_L0122011165010800_07_N0121165010800_07_N01347.531165000000서울특별시 서초구1165010800서초동<NA><NA><NA>12<NA>1<NA><NA>N1165010800_07서초안심072014반포대로22길<NA>202210111165010800_07_L012.jpeg
3386MultiLineString((127.0498486911 37.4617126954, 127.0502529999 37.4621289999))1165011000_11_L0012011165011000_11_N0011165011000_11_N00258.431165000000서울특별시 서초구1165011000염곡동11<NA>13<NA>1<NA>212N1165011000_11서초안심112014염곡안길<NA>202210061165011000_11_L001.jpeg
3387MultiLineString((127.0502529999 37.4621289999, 127.050566 37.4621459999))1165011000_11_L0022011165011000_11_N0021165011000_11_N00327.761165000000서울특별시 서초구1165011000염곡동<NA>3<NA>12<NA>1<NA><NA>N1165011000_11서초안심112014염곡안길<NA>202210061165011000_11_L002.jpeg
3388MultiLineString((127.050566 37.4621459999, 127.0515828644 37.4622078710, 127.05173 37.462417))1165011000_11_L0032011165011000_11_N0031165011000_11_N004116.841165000000서울특별시 서초구1165011000염곡동<NA><NA><NA><NA>3<NA><NA><NA>212N1165011000_11서초안심112014염곡안길<NA>202210061165011000_11_L003.jpeg
3389MultiLineString((127.05173 37.462417, 127.0519040633 37.4625978571, 127.0521528513 37.4626936804, 127.0524309999 37.4626689999))1165011000_11_L0042011165011000_11_N0041165011000_11_N00574.51165000000서울특별시 서초구1165011000염곡동<NA><NA><NA>23<NA>1<NA><NA>N1165011000_11서초안심112014염곡안길<NA>202210061165011000_11_L004.jpeg
3390MultiLineString((127.0524309999 37.4626689999, 127.0529088345 37.4630209356))1165011000_11_L0052011165011000_11_N0051165011000_11_N00657.561165000000서울특별시 서초구1165011000염곡동11<NA>14<NA>1<NA><NA>N1165011000_11서초안심112014염곡안길<NA>202210061165011000_11_L005.jpeg