Overview

Dataset statistics

Number of variables11
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory97.3 B

Variable types

Categorical5
Numeric6

Alerts

배출년도 has constant value ""Constant
배출월 has constant value ""Constant
지자체 시도명 has constant value ""Constant
지자체 시군구명 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
지자체코드 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
배출량(g) is highly overall correlated with 배출횟수 and 2 other fieldsHigh correlation
배출량비율(%) is highly overall correlated with 배출횟수비율(%)High correlation
배출횟수 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
배출횟수비율(%) is highly overall correlated with 배출량비율(%)High correlation
배출량(g) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:44:17.494270
Analysis finished2023-12-10 10:44:23.788307
Duration6.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

배출년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 100
100.0%

Length

2023-12-10T19:44:23.921428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:24.070113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 100
100.0%

배출월
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 100
100.0%

Length

2023-12-10T19:44:24.220483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:24.364810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 100
100.0%

배출일
Real number (ℝ)

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.96
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:24.535584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median13
Q321
95-th percentile28
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.4062507
Coefficient of variation (CV)0.60216695
Kurtosis-1.1723508
Mean13.96
Median Absolute Deviation (MAD)7
Skewness0.18939811
Sum1396
Variance70.665051
MonotonicityNot monotonic
2023-12-10T19:44:24.740920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2 4
 
4.0%
9 4
 
4.0%
3 4
 
4.0%
1 4
 
4.0%
13 4
 
4.0%
11 4
 
4.0%
10 4
 
4.0%
12 4
 
4.0%
8 4
 
4.0%
7 4
 
4.0%
Other values (19) 60
60.0%
ValueCountFrequency (%)
1 4
4.0%
2 4
4.0%
3 4
4.0%
4 4
4.0%
5 4
4.0%
6 4
4.0%
7 4
4.0%
8 4
4.0%
9 4
4.0%
10 4
4.0%
ValueCountFrequency (%)
29 3
3.0%
28 3
3.0%
27 3
3.0%
26 3
3.0%
25 3
3.0%
24 3
3.0%
23 3
3.0%
22 3
3.0%
21 3
3.0%
20 3
3.0%

배출요일
Real number (ℝ)

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.07
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:24.917241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0462086
Coefficient of variation (CV)0.50275396
Kurtosis-1.2793204
Mean4.07
Median Absolute Deviation (MAD)2
Skewness-0.016940836
Sum407
Variance4.1869697
MonotonicityNot monotonic
2023-12-10T19:44:25.126249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
7 17
17.0%
1 14
14.0%
2 14
14.0%
3 14
14.0%
4 14
14.0%
5 14
14.0%
6 13
13.0%
ValueCountFrequency (%)
1 14
14.0%
2 14
14.0%
3 14
14.0%
4 14
14.0%
5 14
14.0%
6 13
13.0%
7 17
17.0%
ValueCountFrequency (%)
7 17
17.0%
6 13
13.0%
5 14
14.0%
4 14
14.0%
3 14
14.0%
2 14
14.0%
1 14
14.0%

지자체코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
W01
29 
W02
29 
W03
29 
W04
13 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowW01
2nd rowW01
3rd rowW01
4th rowW01
5th rowW01

Common Values

ValueCountFrequency (%)
W01 29
29.0%
W02 29
29.0%
W03 29
29.0%
W04 13
13.0%

Length

2023-12-10T19:44:25.363059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:25.513867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
w01 29
29.0%
w02 29
29.0%
w03 29
29.0%
w04 13
13.0%

지자체 시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 100
100.0%

Length

2023-12-10T19:44:25.690032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:25.920838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 100
100.0%

지자체 시군구명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
29 
중구
29 
용산구
29 
성동구
13 

Length

Max length3
Median length3
Mean length2.71
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종로구 29
29.0%
중구 29
29.0%
용산구 29
29.0%
성동구 13
13.0%

Length

2023-12-10T19:44:26.088883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:26.249248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 29
29.0%
중구 29
29.0%
용산구 29
29.0%
성동구 13
13.0%

배출량(g)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5070397
Minimum410300
Maximum21182849
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:26.454890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum410300
5-th percentile460230
Q1609650
median3674775
Q36196637.5
95-th percentile15461678
Maximum21182849
Range20772549
Interquartile range (IQR)5586987.5

Descriptive statistics

Standard deviation4788284
Coefficient of variation (CV)0.94436077
Kurtosis1.6824203
Mean5070397
Median Absolute Deviation (MAD)2967325
Skewness1.433089
Sum5.070397 × 108
Variance2.2927664 × 1013
MonotonicityNot monotonic
2023-12-10T19:44:27.073713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4330600 1
 
1.0%
558800 1
 
1.0%
563899 1
 
1.0%
516700 1
 
1.0%
583400 1
 
1.0%
419700 1
 
1.0%
549550 1
 
1.0%
551400 1
 
1.0%
436150 1
 
1.0%
548650 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
410300 1
1.0%
419700 1
1.0%
436150 1
1.0%
455450 1
1.0%
458900 1
1.0%
460300 1
1.0%
474300 1
1.0%
478050 1
1.0%
510300 1
1.0%
516700 1
1.0%
ValueCountFrequency (%)
21182849 1
1.0%
19533000 1
1.0%
17383250 1
1.0%
16708350 1
1.0%
15541050 1
1.0%
15457500 1
1.0%
14839950 1
1.0%
14714950 1
1.0%
14330100 1
1.0%
13917300 1
1.0%

배출량비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.455
Minimum2.63
Maximum4.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:27.310186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.63
5-th percentile2.906
Q13.1375
median3.335
Q33.6725
95-th percentile4.495
Maximum4.81
Range2.18
Interquartile range (IQR)0.535

Descriptive statistics

Standard deviation0.47130702
Coefficient of variation (CV)0.13641303
Kurtosis0.94423595
Mean3.455
Median Absolute Deviation (MAD)0.26
Skewness1.0190088
Sum345.5
Variance0.2221303
MonotonicityNot monotonic
2023-12-10T19:44:27.540229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.32 3
 
3.0%
3.59 3
 
3.0%
3.43 3
 
3.0%
3.29 3
 
3.0%
3.74 3
 
3.0%
3.15 3
 
3.0%
3.33 3
 
3.0%
2.95 2
 
2.0%
3.04 2
 
2.0%
3.52 2
 
2.0%
Other values (61) 73
73.0%
ValueCountFrequency (%)
2.63 1
1.0%
2.69 1
1.0%
2.8 2
2.0%
2.83 1
1.0%
2.91 2
2.0%
2.92 1
1.0%
2.94 1
1.0%
2.95 2
2.0%
2.96 1
1.0%
2.97 1
1.0%
ValueCountFrequency (%)
4.81 1
1.0%
4.77 1
1.0%
4.74 1
1.0%
4.7 1
1.0%
4.59 1
1.0%
4.49 1
1.0%
4.37 1
1.0%
4.2 1
1.0%
4.13 1
1.0%
4.06 1
1.0%

배출횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3480.4
Minimum352
Maximum13050
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:27.750996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum352
5-th percentile372
Q1434.75
median2395.5
Q34476.75
95-th percentile10103.45
Maximum13050
Range12698
Interquartile range (IQR)4042

Descriptive statistics

Standard deviation3159.9316
Coefficient of variation (CV)0.90792197
Kurtosis0.91580066
Mean3480.4
Median Absolute Deviation (MAD)1978.5
Skewness1.2313133
Sum348040
Variance9985168
MonotonicityNot monotonic
2023-12-10T19:44:27.982404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
372 3
 
3.0%
375 2
 
2.0%
394 2
 
2.0%
352 2
 
2.0%
2552 2
 
2.0%
2653 1
 
1.0%
434 1
 
1.0%
396 1
 
1.0%
410 1
 
1.0%
476 1
 
1.0%
Other values (84) 84
84.0%
ValueCountFrequency (%)
352 2
2.0%
358 1
 
1.0%
372 3
3.0%
374 1
 
1.0%
375 2
2.0%
379 1
 
1.0%
382 1
 
1.0%
388 1
 
1.0%
392 1
 
1.0%
394 2
2.0%
ValueCountFrequency (%)
13050 1
1.0%
12218 1
1.0%
11138 1
1.0%
10894 1
1.0%
10587 1
1.0%
10078 1
1.0%
9826 1
1.0%
9824 1
1.0%
9813 1
1.0%
9499 1
1.0%

배출횟수비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4501
Minimum2.95
Maximum4.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:28.223969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.95
5-th percentile3.039
Q13.2
median3.375
Q33.6125
95-th percentile4.1005
Maximum4.59
Range1.64
Interquartile range (IQR)0.4125

Descriptive statistics

Standard deviation0.34480999
Coefficient of variation (CV)0.099942028
Kurtosis1.4835102
Mean3.4501
Median Absolute Deviation (MAD)0.185
Skewness1.2217918
Sum345.01
Variance0.11889393
MonotonicityNot monotonic
2023-12-10T19:44:28.487727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.29 5
 
5.0%
3.18 4
 
4.0%
3.73 4
 
4.0%
3.2 4
 
4.0%
3.38 3
 
3.0%
3.46 3
 
3.0%
3.74 3
 
3.0%
3.02 2
 
2.0%
4.09 2
 
2.0%
3.19 2
 
2.0%
Other values (54) 68
68.0%
ValueCountFrequency (%)
2.95 2
2.0%
2.98 1
1.0%
3.02 2
2.0%
3.04 1
1.0%
3.05 1
1.0%
3.07 1
1.0%
3.08 2
2.0%
3.09 1
1.0%
3.1 1
1.0%
3.11 1
1.0%
ValueCountFrequency (%)
4.59 1
1.0%
4.52 1
1.0%
4.37 1
1.0%
4.33 1
1.0%
4.3 1
1.0%
4.09 2
2.0%
3.96 2
2.0%
3.91 2
2.0%
3.89 1
1.0%
3.83 2
2.0%

Interactions

2023-12-10T19:44:22.282301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:17.982107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:18.875234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:19.770518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:20.630480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:21.398243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:22.464798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:18.133861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:19.026740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:19.902952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:20.771103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:21.550479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:22.643599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:18.292451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:19.178093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:20.075981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:20.910575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:21.699495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:22.825365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:18.433780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:19.325020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:20.213271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:21.016809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:21.839080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:22.984919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:18.556926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:19.460036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:20.335185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:21.120326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:21.969267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:23.132861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:18.708746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:19.614566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:20.485125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:21.253691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:22.126591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:44:28.805019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출일배출요일지자체코드지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
배출일1.0000.6500.0000.0000.0000.4140.0000.193
배출요일0.6501.0000.0000.0000.0370.6430.3370.610
지자체코드0.0000.0001.0001.0001.0000.3721.0000.138
지자체 시군구명0.0000.0001.0001.0001.0000.3721.0000.138
배출량(g)0.0000.0371.0001.0001.0000.8040.9550.696
배출량비율(%)0.4140.6430.3720.3720.8041.0000.7240.836
배출횟수0.0000.3371.0001.0000.9550.7241.0000.858
배출횟수비율(%)0.1930.6100.1380.1380.6960.8360.8581.000
2023-12-10T19:44:29.000762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 시군구명지자체코드
지자체 시군구명1.0001.000
지자체코드1.0001.000
2023-12-10T19:44:29.172196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출일배출요일배출량(g)배출량비율(%)배출횟수배출횟수비율(%)지자체코드지자체 시군구명
배출일1.0000.131-0.203-0.063-0.1770.0290.0000.000
배출요일0.1311.000-0.131-0.395-0.136-0.4430.0000.000
배출량(g)-0.203-0.1311.0000.2050.9940.1630.9680.968
배출량비율(%)-0.063-0.3950.2051.0000.1840.9150.2210.221
배출횟수-0.177-0.1360.9940.1841.0000.1810.9740.974
배출횟수비율(%)0.029-0.4430.1630.9150.1811.0000.0810.081
지자체코드0.0000.0000.9680.2210.9740.0811.0001.000
지자체 시군구명0.0000.0000.9680.2210.9740.0811.0001.000

Missing values

2023-12-10T19:44:23.368309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:44:23.666210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

배출년도배출월배출일배출요일지자체코드지자체 시도명지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
02020221W01서울특별시종로구43306004.226533.89
12020232W01서울특별시종로구41173003.9926113.83
22020243W01서울특별시종로구35396003.4323253.41
32020254W01서울특별시종로구31034503.0121193.11
42020265W01서울특별시종로구32322003.1321463.15
52020276W01서울특별시종로구33966503.2923583.46
62020287W01서울특별시종로구34034003.322853.35
72020291W01서울특별시종로구40641503.9425433.73
820202102W01서울특별시종로구41579004.0325523.74
920202113W01서울특별시종로구34901003.3823703.47
배출년도배출월배출일배출요일지자체코드지자체 시도명지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
902020254W04서울특별시성동구132474002.9691883.08
912020265W04서울특별시성동구148399503.32100783.38
922020276W04서울특별시성동구143301003.2198243.29
932020287W04서울특별시성동구147149503.2994993.18
942020291W04서울특별시성동구195330004.37122184.09
9520202102W04서울특별시성동구167083503.74108943.65
9620202113W04서울특별시성동구139173003.1198133.29
9720202124W04서울특별시성동구125024502.888122.95
9820202135W04서울특별시성동구154575003.46105873.55
992020217W01서울특별시종로구36409003.5323623.46