Overview

Dataset statistics

Number of variables12
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory107.7 B

Variable types

Categorical7
Numeric5

Dataset

Description3년간(2020~2022) 미환급 유형별 건수 및 ㄱ금액과 누적민환급금액 증감 현황 및 연간 누적률 데이터를 제공합니다.
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15126700/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
미환급유형 has constant value ""Constant
당해미환급건수 is highly overall correlated with 당해미환급금액 and 2 other fieldsHigh correlation
당해미환급금액 is highly overall correlated with 당해미환급건수 and 3 other fieldsHigh correlation
누적미환급건수 is highly overall correlated with 당해미환급건수 and 2 other fieldsHigh correlation
누적미환급금액 is highly overall correlated with 당해미환급건수 and 2 other fieldsHigh correlation
누적미환급금액증감 is highly overall correlated with 당해미환급금액High correlation
당해미환급금액 has unique valuesUnique
누적미환급금액 has unique valuesUnique
누적미환급금액증감 has unique valuesUnique
누적미환급금액증감 has 1 (3.7%) zerosZeros

Reproduction

Analysis started2024-03-14 20:53:36.381856
Analysis finished2024-03-14 20:53:43.571393
Duration7.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
전라남도
27 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 27
100.0%

Length

2024-03-15T05:53:43.760395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:53:44.061693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 27
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
나주시
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나주시 27
100.0%

Length

2024-03-15T05:53:44.376710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:53:44.682045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나주시 27
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
46170
27 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46170
2nd row46170
3rd row46170
4th row46170
5th row46170

Common Values

ValueCountFrequency (%)
46170 27
100.0%

Length

2024-03-15T05:53:45.090761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:53:45.251148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46170 27
100.0%

세목명
Categorical

Distinct6
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size344.0 B
자동차세
6 
재산세
6 
지방소득세
6 
등록면허세
5 
주민세
3 

Length

Max length5
Median length4
Mean length4.037037
Min length3

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row등록면허세
2nd row등록면허세
3rd row자동차세
4th row자동차세
5th row재산세

Common Values

ValueCountFrequency (%)
자동차세 6
22.2%
재산세 6
22.2%
지방소득세 6
22.2%
등록면허세 5
18.5%
주민세 3
11.1%
취득세 1
 
3.7%

Length

2024-03-15T05:53:45.482959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:53:45.847309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 6
22.2%
재산세 6
22.2%
지방소득세 6
22.2%
등록면허세 5
18.5%
주민세 3
11.1%
취득세 1
 
3.7%

과세년도
Categorical

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size344.0 B
2020
9 
2021
9 
2022
9 

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 9
33.3%
2021 9
33.3%
2022 9
33.3%

Length

2024-03-15T05:53:46.240284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:53:46.551955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 9
33.3%
2021 9
33.3%
2022 9
33.3%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
신규
27 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 27
100.0%

Length

2024-03-15T05:53:46.903053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:53:47.210840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 27
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size344.0 B
개인
15 
법인
12 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row법인
3rd row개인
4th row법인
5th row개인

Common Values

ValueCountFrequency (%)
개인 15
55.6%
법인 12
44.4%

Length

2024-03-15T05:53:47.525588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:53:47.830505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 15
55.6%
법인 12
44.4%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.444444
Minimum1
Maximum467
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T05:53:48.135094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median13
Q382.5
95-th percentile402.8
Maximum467
Range466
Interquartile range (IQR)80.5

Descriptive statistics

Standard deviation137.93542
Coefficient of variation (CV)1.6730711
Kurtosis2.3619271
Mean82.444444
Median Absolute Deviation (MAD)12
Skewness1.8536736
Sum2226
Variance19026.179
MonotonicityNot monotonic
2024-03-15T05:53:48.532346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 6
22.2%
4 2
 
7.4%
14 2
 
7.4%
3 2
 
7.4%
2 2
 
7.4%
10 1
 
3.7%
351 1
 
3.7%
52 1
 
3.7%
102 1
 
3.7%
467 1
 
3.7%
Other values (8) 8
29.6%
ValueCountFrequency (%)
1 6
22.2%
2 2
 
7.4%
3 2
 
7.4%
4 2
 
7.4%
10 1
 
3.7%
13 1
 
3.7%
14 2
 
7.4%
20 1
 
3.7%
52 1
 
3.7%
54 1
 
3.7%
ValueCountFrequency (%)
467 1
3.7%
425 1
3.7%
351 1
3.7%
266 1
3.7%
213 1
3.7%
138 1
3.7%
102 1
3.7%
63 1
3.7%
54 1
3.7%
52 1
3.7%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2240194.8
Minimum1530
Maximum13396160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T05:53:48.911697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1530
5-th percentile2744
Q131920
median241560
Q32141360
95-th percentile9989675
Maximum13396160
Range13394630
Interquartile range (IQR)2109440

Descriptive statistics

Standard deviation3704779.4
Coefficient of variation (CV)1.6537755
Kurtosis2.6038483
Mean2240194.8
Median Absolute Deviation (MAD)240030
Skewness1.8578344
Sum60485260
Variance1.372539 × 1013
MonotonicityNot monotonic
2024-03-15T05:53:49.349946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
42240 1
 
3.7%
15360 1
 
3.7%
628560 1
 
3.7%
8532800 1
 
3.7%
11780 1
 
3.7%
3150 1
 
3.7%
663800 1
 
3.7%
2296960 1
 
3.7%
10614050 1
 
3.7%
57530 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1530 1
3.7%
2570 1
3.7%
3150 1
3.7%
11330 1
3.7%
11780 1
3.7%
15360 1
3.7%
21600 1
3.7%
42240 1
3.7%
57530 1
3.7%
101060 1
3.7%
ValueCountFrequency (%)
13396160 1
3.7%
10614050 1
3.7%
8532800 1
3.7%
7250700 1
3.7%
6397630 1
3.7%
4404280 1
3.7%
2296960 1
3.7%
1985760 1
3.7%
1627130 1
3.7%
1167600 1
3.7%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.92593
Minimum3
Maximum1116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T05:53:49.738399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q15
median27
Q3154.5
95-th percentile834.1
Maximum1116
Range1113
Interquartile range (IQR)149.5

Descriptive statistics

Standard deviation303.33961
Coefficient of variation (CV)1.7145006
Kurtosis3.2459491
Mean176.92593
Median Absolute Deviation (MAD)22
Skewness2.0114469
Sum4777
Variance92014.917
MonotonicityNot monotonic
2024-03-15T05:53:50.112470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
5 6
22.2%
4 2
 
7.4%
33 1
 
3.7%
783 1
 
3.7%
6 1
 
3.7%
137 1
 
3.7%
172 1
 
3.7%
1116 1
 
3.7%
22 1
 
3.7%
3 1
 
3.7%
Other values (11) 11
40.7%
ValueCountFrequency (%)
3 1
 
3.7%
4 2
 
7.4%
5 6
22.2%
6 1
 
3.7%
8 1
 
3.7%
13 1
 
3.7%
22 1
 
3.7%
27 1
 
3.7%
33 1
 
3.7%
41 1
 
3.7%
ValueCountFrequency (%)
1116 1
3.7%
856 1
3.7%
783 1
3.7%
500 1
3.7%
482 1
3.7%
300 1
3.7%
172 1
3.7%
137 1
3.7%
101 1
3.7%
95 1
3.7%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4766154.4
Minimum51550
Maximum31053030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T05:53:50.562869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51550
5-th percentile77962
Q1105205
median601920
Q33812745
95-th percentile23312153
Maximum31053030
Range31001480
Interquartile range (IQR)3707540

Descriptive statistics

Standard deviation8351011.3
Coefficient of variation (CV)1.7521487
Kurtosis3.7286373
Mean4766154.4
Median Absolute Deviation (MAD)550370
Skewness2.1238276
Sum1.2868617 × 108
Variance6.9739389 × 1013
MonotonicityNot monotonic
2024-03-15T05:53:50.835709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
51550 1
 
3.7%
592650 1
 
3.7%
2707260 1
 
3.7%
31053030 1
 
3.7%
89190 1
 
3.7%
106780 1
 
3.7%
1824240 1
 
3.7%
4770530 1
 
3.7%
21948630 1
 
3.7%
601920 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
51550 1
3.7%
73150 1
3.7%
89190 1
3.7%
95740 1
3.7%
100070 1
3.7%
101060 1
3.7%
103630 1
3.7%
106780 1
3.7%
220120 1
3.7%
274050 1
3.7%
ValueCountFrequency (%)
31053030 1
3.7%
23896520 1
3.7%
21948630 1
3.7%
13962390 1
3.7%
10677850 1
3.7%
7058290 1
3.7%
4770530 1
3.7%
2854960 1
3.7%
2707260 1
3.7%
2081500 1
3.7%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean802.65037
Minimum0
Maximum6157.5
Zeros1
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T05:53:51.053001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.96
Q171.2
median107.69
Q3493.92
95-th percentile3880.13
Maximum6157.5
Range6157.5
Interquartile range (IQR)422.72

Descriptive statistics

Standard deviation1559.7161
Coefficient of variation (CV)1.9432074
Kurtosis5.1184147
Mean802.65037
Median Absolute Deviation (MAD)85.49
Skewness2.3908423
Sum21671.56
Variance2432714.4
MonotonicityNot monotonic
2024-03-15T05:53:51.278344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
22.0 1
 
3.7%
3758.4 1
 
3.7%
330.71 1
 
3.7%
263.93 1
 
3.7%
657.13 1
 
3.7%
3289.84 1
 
3.7%
174.82 1
 
3.7%
107.69 1
 
3.7%
106.79 1
 
3.7%
946.27 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
0.0 1
3.7%
4.8 1
3.7%
22.0 1
3.7%
22.2 1
3.7%
30.28 1
3.7%
60.3 1
3.7%
66.9 1
3.7%
75.5 1
3.7%
78.4 1
3.7%
88.8 1
3.7%
ValueCountFrequency (%)
6157.5 1
3.7%
3932.3 1
3.7%
3758.4 1
3.7%
3289.84 1
3.7%
946.27 1
3.7%
783.2 1
3.7%
657.13 1
3.7%
330.71 1
3.7%
263.93 1
3.7%
238.7 1
3.7%

Interactions

2024-03-15T05:53:41.660160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:36.805305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:38.113146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:39.154596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:40.397658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:41.797335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:37.037012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:38.287647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:39.291075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:40.634382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:41.955588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:37.292955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:38.492859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:39.685844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:40.895719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:42.190343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:37.532347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:38.671329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:39.846112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:41.141004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:42.448139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:37.789887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:38.894253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:40.144333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:53:41.403140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:53:51.459512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.236
과세년도0.0001.0000.0000.0000.0890.2310.0000.000
납세자유형0.0000.0001.0000.0000.3920.3270.2440.234
당해미환급건수0.0000.0000.0001.0000.9370.8570.9820.000
당해미환급금액0.0000.0890.3920.9371.0000.9460.9660.000
누적미환급건수0.0000.2310.3270.8570.9461.0000.9110.000
누적미환급금액0.0000.0000.2440.9820.9660.9111.0000.000
누적미환급금액증감0.2360.0000.2340.0000.0000.0000.0001.000
2024-03-15T05:53:51.748577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도납세자유형세목명
과세년도1.0000.0000.000
납세자유형0.0001.0000.000
세목명0.0000.0001.000
2024-03-15T05:53:51.956661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도납세자유형
당해미환급건수1.0000.8930.9330.802-0.4760.0000.0000.000
당해미환급금액0.8931.0000.8320.917-0.5520.0000.0000.241
누적미환급건수0.9330.8321.0000.821-0.2340.0000.0270.199
누적미환급금액0.8020.9170.8211.000-0.2560.0000.0000.167
누적미환급금액증감-0.476-0.552-0.234-0.2561.0000.1300.0000.257
세목명0.0000.0000.0000.0000.1301.0000.0000.000
과세년도0.0000.0000.0270.0000.0000.0001.0000.000
납세자유형0.0000.2410.1990.1670.2570.0000.0001.000

Missing values

2024-03-15T05:53:42.815509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:53:43.353645image/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

시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
0전라남도나주시46170등록면허세2020신규개인44224055155022.0
1전라남도나주시46170등록면허세2020신규법인11536045926503758.4
2전라남도나주시46170자동차세2020신규개인2664404280482705829060.3
3전라남도나주시46170자동차세2020신규법인20566570441249540120.5
4전라남도나주시46170재산세2020신규개인1310623041274050158.0
5전라남도나주시46170재산세2020신규법인410106041010600.0
6전라남도나주시46170주민세2020신규법인12207105450240104.0
7전라남도나주시46170지방소득세2020신규개인13863976303001067785066.9
8전라남도나주시46170지방소득세2020신규법인3153013957406157.5
9전라남도나주시46170등록면허세2021신규개인321600873150238.7
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
17전라남도나주시46170취득세2021신규개인1116610322012088.8
18전라남도나주시46170등록면허세2022신규개인142415602231471030.28
19전라남도나주시46170등록면허세2022신규법인2575305601920946.27
20전라남도나주시46170자동차세2022신규개인46710614050111621948630106.79
21전라남도나주시46170자동차세2022신규법인10222969601724770530107.69
22전라남도나주시46170재산세2022신규개인526638001371824240174.82
23전라남도나주시46170재산세2022신규법인1315061067803289.84
24전라남도나주시46170주민세2022신규개인211780589190657.13
25전라남도나주시46170지방소득세2022신규개인351853280078331053030263.93
26전라남도나주시46170지방소득세2022신규법인10628560332707260330.71