Overview

Dataset statistics

Number of variables11
Number of observations30
Missing cells30
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory98.4 B

Variable types

Categorical5
Text1
Numeric4
Unsupported1

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://bigdata-region.kr/#/dataset/26a3c4e0-4f4b-4a7a-a866-deb18037e65a

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
1인당 소비액 표준편차 has constant value ""Constant
행정동 코드 is highly overall correlated with 시군구명High correlation
1인당 소비액 is highly overall correlated with 유동 인구 소비융합지수High correlation
유동 인구 소비융합지수 is highly overall correlated with 1인당 소비액High correlation
시군구명 is highly overall correlated with 행정동 코드High correlation
소비액 has 30 (100.0%) missing valuesMissing
전체 인구 has unique valuesUnique
1인당 소비액 has unique valuesUnique
유동 인구 소비융합지수 has unique valuesUnique
소비액 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 13:51:30.879011
Analysis finished2023-12-10 13:51:34.290475
Duration3.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2019-01
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-01
2nd row2019-01
3rd row2019-01
4th row2019-01
5th row2019-01

Common Values

ValueCountFrequency (%)
2019-01 30
100.0%

Length

2023-12-10T22:51:34.390139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:51:34.556270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-01 30
100.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T22:51:34.783280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:51:34.998012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
광명시
6 
고양시 일산서구
5 
김포시
5 
고양시 덕양구
3 
고양시 일산동구
3 
Other values (3)
8 

Length

Max length8
Median length3
Mean length4.7333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고양시 덕양구
2nd row고양시 덕양구
3rd row고양시 덕양구
4th row고양시 일산동구
5th row고양시 일산동구

Common Values

ValueCountFrequency (%)
광명시 6
20.0%
고양시 일산서구 5
16.7%
김포시 5
16.7%
고양시 덕양구 3
10.0%
고양시 일산동구 3
10.0%
광주시 3
10.0%
군포시 3
10.0%
구리시 2
 
6.7%

Length

2023-12-10T22:51:35.192990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:51:35.384572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고양시 11
26.8%
광명시 6
14.6%
일산서구 5
12.2%
김포시 5
12.2%
덕양구 3
 
7.3%
일산동구 3
 
7.3%
광주시 3
 
7.3%
군포시 3
 
7.3%
구리시 2
 
4.9%

행정동명
Text

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:51:35.685119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.6333333
Min length3

Characters and Unicode

Total characters109
Distinct characters45
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

Unique21 ?
Unique (%)70.0%

Sample

1st row행주동
2nd row행신3동
3rd row화정2동
4th row백석2동
5th row마두2동
ValueCountFrequency (%)
하성면 3
 
10.0%
광명5동 2
 
6.7%
백석2동 2
 
6.7%
일산2동 2
 
6.7%
퇴촌면 1
 
3.3%
광남동 1
 
3.3%
양촌읍 1
 
3.3%
풍무동 1
 
3.3%
재궁동 1
 
3.3%
군포2동 1
 
3.3%
Other values (15) 15
50.0%
2023-12-10T22:51:36.345602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 24
22.0%
2 7
 
6.4%
산 6
 
5.5%
면 5
 
4.6%
하 4
 
3.7%
광 4
 
3.7%
성 4
 
3.7%
명 3
 
2.8%
1 3
 
2.8%
3 3
 
2.8%
Other values (35) 46
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
84.4%
Decimal Number 17
 
15.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
26.1%
산 6
 
6.5%
면 5
 
5.4%
하 4
 
4.3%
광 4
 
4.3%
성 4
 
4.3%
명 3
 
3.3%
일 2
 
2.2%
백 2
 
2.2%
철 2
 
2.2%
Other values (29) 36
39.1%
Decimal Number
ValueCountFrequency (%)
2 7
41.2%
1 3
17.6%
3 3
17.6%
5 2
 
11.8%
6 1
 
5.9%
4 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
84.4%
Common 17
 
15.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
26.1%
산 6
 
6.5%
면 5
 
5.4%
하 4
 
4.3%
광 4
 
4.3%
성 4
 
4.3%
명 3
 
3.3%
일 2
 
2.2%
백 2
 
2.2%
철 2
 
2.2%
Other values (29) 36
39.1%
Common
ValueCountFrequency (%)
2 7
41.2%
1 3
17.6%
3 3
17.6%
5 2
 
11.8%
6 1
 
5.9%
4 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
84.4%
ASCII 17
 
15.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 24
26.1%
산 6
 
6.5%
면 5
 
5.4%
하 4
 
4.3%
광 4
 
4.3%
성 4
 
4.3%
명 3
 
3.3%
일 2
 
2.2%
백 2
 
2.2%
철 2
 
2.2%
Other values (29) 36
39.1%
ASCII
ValueCountFrequency (%)
2 7
41.2%
1 3
17.6%
3 3
17.6%
5 2
 
11.8%
6 1
 
5.9%
4 1
 
5.9%

행정동 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1364624 × 109
Minimum4.121056 × 109
Maximum4.161053 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:51:36.563027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.121056 × 109
5-th percentile4.1210564 × 109
Q14.1281636 × 109
median4.1287555 × 109
Q34.1530334 × 109
95-th percentile4.1610356 × 109
Maximum4.161053 × 109
Range39997000
Interquartile range (IQR)24869825

Descriptive statistics

Standard deviation14580961
Coefficient of variation (CV)0.0035249834
Kurtosis-1.1080729
Mean4.1364624 × 109
Median Absolute Deviation (MAD)7694000
Skewness0.72293981
Sum1.2409387 × 1011
Variance2.1260443 × 1014
MonotonicityNot monotonic
2023-12-10T22:51:36.766599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
4157036000 3
 
10.0%
4128555200 2
 
6.7%
4128752000 2
 
6.7%
4121056000 2
 
6.7%
4128163000 1
 
3.3%
4161037000 1
 
3.3%
4157025600 1
 
3.3%
4157055000 1
 
3.3%
4141057000 1
 
3.3%
4141052000 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
4121056000 2
6.7%
4121057000 1
3.3%
4121061000 1
3.3%
4121062000 1
3.3%
4121063300 1
3.3%
4128162200 1
3.3%
4128163000 1
3.3%
4128165500 1
3.3%
4128555200 2
6.7%
4128557000 1
3.3%
ValueCountFrequency (%)
4161053000 1
 
3.3%
4161037000 1
 
3.3%
4161034000 1
 
3.3%
4157055000 1
 
3.3%
4157036000 3
10.0%
4157025600 1
 
3.3%
4141057000 1
 
3.3%
4141052000 1
 
3.3%
4141051000 1
 
3.3%
4131057000 1
 
3.3%

연령대코드
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
50G
10 
30G
6 
60G
6 
40G
4 
20G
4 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50G
2nd row30G
3rd row60G
4th row30G
5th row50G

Common Values

ValueCountFrequency (%)
50G 10
33.3%
30G 6
20.0%
60G 6
20.0%
40G 4
 
13.3%
20G 4
 
13.3%

Length

2023-12-10T22:51:36.983215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:51:37.144584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50g 10
33.3%
30g 6
20.0%
60g 6
20.0%
40g 4
 
13.3%
20g 4
 
13.3%

소비액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

전체 인구
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12644.867
Minimum1126.79
Maximum31059.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:51:37.404140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1126.79
5-th percentile1805.8275
Q17121.985
median11230.385
Q318657.225
95-th percentile25804.24
Maximum31059.9
Range29933.11
Interquartile range (IQR)11535.24

Descriptive statistics

Standard deviation8059.0131
Coefficient of variation (CV)0.63733473
Kurtosis-0.52043692
Mean12644.867
Median Absolute Deviation (MAD)6038.935
Skewness0.52895003
Sum379346.02
Variance64947692
MonotonicityNot monotonic
2023-12-10T22:51:37.726072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
26198.44 1
 
3.3%
6897.14 1
 
3.3%
8955.06 1
 
3.3%
7796.52 1
 
3.3%
2584.09 1
 
3.3%
31059.9 1
 
3.3%
12535.62 1
 
3.3%
5231.15 1
 
3.3%
20190.09 1
 
3.3%
20881.39 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1126.79 1
3.3%
1229.67 1
3.3%
2510.02 1
3.3%
2584.09 1
3.3%
4245.36 1
3.3%
5151.75 1
3.3%
5231.15 1
3.3%
6897.14 1
3.3%
7796.52 1
3.3%
7986.03 1
3.3%
ValueCountFrequency (%)
31059.9 1
3.3%
26198.44 1
3.3%
25322.44 1
3.3%
24683.62 1
3.3%
21022.29 1
3.3%
20881.39 1
3.3%
20190.09 1
3.3%
18920.96 1
3.3%
17866.02 1
3.3%
16768.47 1
3.3%

1인당 소비액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5911.1407
Minimum1008.45
Maximum17577.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:51:37.956491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1008.45
5-th percentile1612.437
Q12967.045
median4770.925
Q38654.92
95-th percentile12240.809
Maximum17577.2
Range16568.75
Interquartile range (IQR)5687.875

Descriptive statistics

Standard deviation4012.2258
Coefficient of variation (CV)0.67875661
Kurtosis0.80182083
Mean5911.1407
Median Absolute Deviation (MAD)2916.755
Skewness1.0148443
Sum177334.22
Variance16097956
MonotonicityNot monotonic
2023-12-10T22:51:38.272563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3520.68 1
 
3.3%
2981.91 1
 
3.3%
1658.18 1
 
3.3%
2962.09 1
 
3.3%
2050.16 1
 
3.3%
1608.81 1
 
3.3%
9810.55 1
 
3.3%
3314.6 1
 
3.3%
1616.87 1
 
3.3%
4797.36 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1008.45 1
3.3%
1608.81 1
3.3%
1616.87 1
3.3%
1658.18 1
3.3%
2050.16 1
3.3%
2326.55 1
3.3%
2552.88 1
3.3%
2962.09 1
3.3%
2981.91 1
3.3%
3005.49 1
3.3%
ValueCountFrequency (%)
17577.2 1
3.3%
12685.13 1
3.3%
11697.75 1
3.3%
10346.74 1
3.3%
9861.83 1
3.3%
9810.55 1
3.3%
8977.87 1
3.3%
8660.09 1
3.3%
8639.41 1
3.3%
8172.9 1
3.3%

1인당 소비액 표준편차
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
5428.57
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5428.57
2nd row5428.57
3rd row5428.57
4th row5428.57
5th row5428.57

Common Values

ValueCountFrequency (%)
5428.57 30
100.0%

Length

2023-12-10T22:51:38.475132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:51:38.633279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5428.57 30
100.0%

유동 인구 소비융합지수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.88967
Minimum18.58
Maximum323.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:51:38.776950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.58
5-th percentile29.703
Q154.6525
median87.885
Q3159.435
95-th percentile225.4845
Maximum323.79
Range305.21
Interquartile range (IQR)104.7825

Descriptive statistics

Standard deviation73.908891
Coefficient of variation (CV)0.67875028
Kurtosis0.80180872
Mean108.88967
Median Absolute Deviation (MAD)53.725
Skewness1.0148499
Sum3266.69
Variance5462.5242
MonotonicityNot monotonic
2023-12-10T22:51:38.951162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
64.85 1
 
3.3%
54.93 1
 
3.3%
30.55 1
 
3.3%
54.56 1
 
3.3%
37.77 1
 
3.3%
29.64 1
 
3.3%
180.72 1
 
3.3%
61.06 1
 
3.3%
29.78 1
 
3.3%
88.37 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
18.58 1
3.3%
29.64 1
3.3%
29.78 1
3.3%
30.55 1
3.3%
37.77 1
3.3%
42.86 1
3.3%
47.03 1
3.3%
54.56 1
3.3%
54.93 1
3.3%
55.36 1
3.3%
ValueCountFrequency (%)
323.79 1
3.3%
233.67 1
3.3%
215.48 1
3.3%
190.6 1
3.3%
181.67 1
3.3%
180.72 1
3.3%
165.38 1
3.3%
159.53 1
3.3%
159.15 1
3.3%
150.55 1
3.3%

Interactions

2023-12-10T22:51:33.278936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:31.291749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:31.834248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:32.661574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:33.452014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:31.434156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:31.984072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:32.826034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:33.603106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:31.571508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:32.388875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:32.966325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:33.735832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:31.691277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:32.526713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:51:33.095255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:51:39.098423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명행정동명행정동 코드연령대코드전체 인구1인당 소비액유동 인구 소비융합지수
시군구명1.0001.0000.9330.0000.5080.4440.482
행정동명1.0001.0001.0000.0000.8090.9000.894
행정동 코드0.9331.0001.0000.0000.6040.0000.107
연령대코드0.0000.0000.0001.0000.0000.4380.344
전체 인구0.5080.8090.6040.0001.0000.4620.436
1인당 소비액0.4440.9000.0000.4380.4621.0001.000
유동 인구 소비융합지수0.4820.8940.1070.3440.4361.0001.000
2023-12-10T22:51:39.262192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대코드시군구명
연령대코드1.0000.000
시군구명0.0001.000
2023-12-10T22:51:39.403758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동 코드전체 인구1인당 소비액유동 인구 소비융합지수시군구명연령대코드
행정동 코드1.0000.250-0.449-0.4490.8140.000
전체 인구0.2501.000-0.060-0.0600.2750.000
1인당 소비액-0.449-0.0601.0001.0000.2310.160
유동 인구 소비융합지수-0.449-0.0601.0001.0000.2310.160
시군구명0.8140.2750.2310.2311.0000.000
연령대코드0.0000.0000.1600.1600.0001.000

Missing values

2023-12-10T22:51:33.933600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:51:34.187640image/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

기준년월시도명시군구명행정동명행정동 코드연령대코드소비액전체 인구1인당 소비액1인당 소비액 표준편차유동 인구 소비융합지수
02019-01경기도고양시 덕양구행주동412816300050G<NA>26198.443520.685428.5764.85
12019-01경기도고양시 덕양구행신3동412816550030G<NA>10165.458977.875428.57165.38
22019-01경기도고양시 덕양구화정2동412816220060G<NA>10563.458660.095428.57159.53
32019-01경기도고양시 일산동구백석2동412855520030G<NA>13423.96123.495428.57112.8
42019-01경기도고양시 일산동구마두2동412855700050G<NA>7986.0317577.25428.57323.79
52019-01경기도고양시 일산동구백석2동412855520040G<NA>17866.025540.65428.57102.06
62019-01경기도고양시 일산서구대화동412875700050G<NA>16768.479861.835428.57181.67
72019-01경기도고양시 일산서구송산동412875900030G<NA>25322.444831.215428.5789.0
82019-01경기도고양시 일산서구일산2동412875200020G<NA>4245.364025.335428.5774.15
92019-01경기도고양시 일산서구일산2동412875200050G<NA>9358.288639.415428.57159.15
기준년월시도명시군구명행정동명행정동 코드연령대코드소비액전체 인구1인당 소비액1인당 소비액 표준편차유동 인구 소비융합지수
202019-01경기도구리시교문1동413105410060G<NA>24683.622326.555428.5742.86
212019-01경기도구리시수택1동413105700040G<NA>12696.4412685.135428.57233.67
222019-01경기도군포시군포1동414105100030G<NA>20881.394797.365428.5788.37
232019-01경기도군포시군포2동414105200060G<NA>20190.091616.875428.5729.78
242019-01경기도군포시재궁동414105700050G<NA>5231.153314.65428.5761.06
252019-01경기도김포시풍무동415705500030G<NA>12535.629810.555428.57180.72
262019-01경기도김포시양촌읍415702560060G<NA>31059.91608.815428.5729.64
272019-01경기도김포시하성면415703600020G<NA>2584.092050.165428.5737.77
282019-01경기도김포시하성면415703600040G<NA>7796.522962.095428.5754.56
292019-01경기도김포시하성면415703600060G<NA>8955.061658.185428.5730.55