Overview

Dataset statistics

Number of variables12
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory107.7 B

Variable types

Categorical7
Numeric5

Dataset

Description3년간(2019~2021) 미환급 유형별 미환급 건수 및 금액과 누적미환급금액 증감 현황 및 연간 누적률 데이터를 제공합니다
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15079622/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 2 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
당해미환급금액 has unique valuesUnique
누적미환급금액 has unique valuesUnique
누적미환급금액증감 has unique valuesUnique
누적미환급금액증감 has 1 (3.6%) zerosZeros

Reproduction

Analysis started2023-12-12 18:50:42.181691
Analysis finished2023-12-12 18:50:48.403051
Duration6.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
전라남도
28 

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 28
100.0%

Length

2023-12-13T03:50:48.513894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:48.674637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 28
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
나주시
28 

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 28
100.0%

Length

2023-12-13T03:50:48.848845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:48.999244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나주시 28
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
46170
28 

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 28
100.0%

Length

2023-12-13T03:50:49.166382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:49.342277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46170 28
100.0%

세목명
Categorical

Distinct6
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
자동차세
6 
재산세
6 
지방소득세
6 
등록면허세
4 
주민세
4 

Length

Max length5
Median length4
Mean length3.9285714
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 6
21.4%
재산세 6
21.4%
지방소득세 6
21.4%
등록면허세 4
14.3%
주민세 4
14.3%
취득세 2
 
7.1%

Length

2023-12-13T03:50:49.538266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:49.795952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 6
21.4%
재산세 6
21.4%
지방소득세 6
21.4%
등록면허세 4
14.3%
주민세 4
14.3%
취득세 2
 
7.1%

과세년도
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2019
10 
2020
9 
2021
9 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2019 10
35.7%
2020 9
32.1%
2021 9
32.1%

Length

2023-12-13T03:50:50.032026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:50.200827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 10
35.7%
2020 9
32.1%
2021 9
32.1%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
신규
28 

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 28
100.0%

Length

2023-12-13T03:50:50.369236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:50.517684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 28
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
개인
15 
법인
13 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 15
53.6%
법인 13
46.4%

Length

2023-12-13T03:50:50.678362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:50.834447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 15
53.6%
법인 13
46.4%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.392857
Minimum1
Maximum425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T03:50:50.985114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.5
median7
Q356.25
95-th percentile247.45
Maximum425
Range424
Interquartile range (IQR)53.75

Descriptive statistics

Standard deviation99.298032
Coefficient of variation (CV)1.895259
Kurtosis7.1965995
Mean52.392857
Median Absolute Deviation (MAD)6
Skewness2.6222852
Sum1467
Variance9860.0992
MonotonicityNot monotonic
2023-12-13T03:50:51.183859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 7
25.0%
3 3
 
10.7%
4 3
 
10.7%
13 1
 
3.6%
14 1
 
3.6%
213 1
 
3.6%
63 1
 
3.6%
54 1
 
3.6%
425 1
 
3.6%
138 1
 
3.6%
Other values (8) 8
28.6%
ValueCountFrequency (%)
1 7
25.0%
3 3
10.7%
4 3
10.7%
5 1
 
3.6%
9 1
 
3.6%
11 1
 
3.6%
13 1
 
3.6%
14 1
 
3.6%
15 1
 
3.6%
20 1
 
3.6%
ValueCountFrequency (%)
425 1
3.6%
266 1
3.6%
213 1
3.6%
138 1
3.6%
112 1
3.6%
81 1
3.6%
63 1
3.6%
54 1
3.6%
20 1
3.6%
15 1
3.6%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1531023.2
Minimum1530
Maximum13396160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T03:50:51.376574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1530
5-th percentile5090
Q176620
median126210
Q31651822.5
95-th percentile6952125.5
Maximum13396160
Range13394630
Interquartile range (IQR)1575202.5

Descriptive statistics

Standard deviation3010070.2
Coefficient of variation (CV)1.9660513
Kurtosis8.8081327
Mean1531023.2
Median Absolute Deviation (MAD)115660
Skewness2.8417367
Sum42868650
Variance9.0605225 × 1012
MonotonicityNot monotonic
2023-12-13T03:50:51.618588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
536530 1
 
3.6%
101060 1
 
3.6%
116610 1
 
3.6%
1985760 1
 
3.6%
13396160 1
 
3.6%
11330 1
 
3.6%
2570 1
 
3.6%
1167600 1
 
3.6%
1627130 1
 
3.6%
7250700 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1530 1
3.6%
2570 1
3.6%
9770 1
3.6%
11330 1
3.6%
15360 1
3.6%
21600 1
3.6%
42240 1
3.6%
88080 1
3.6%
91980 1
3.6%
101060 1
3.6%
ValueCountFrequency (%)
13396160 1
3.6%
7250700 1
3.6%
6397630 1
3.6%
4404280 1
3.6%
2490900 1
3.6%
1985760 1
3.6%
1725900 1
3.6%
1627130 1
3.6%
1167600 1
3.6%
566570 1
3.6%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.03571
Minimum2
Maximum856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T03:50:51.830084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.35
Q15
median15
Q396.5
95-th percentile493.7
Maximum856
Range854
Interquartile range (IQR)91.5

Descriptive statistics

Standard deviation206.44477
Coefficient of variation (CV)1.7791485
Kurtosis5.4515246
Mean116.03571
Median Absolute Deviation (MAD)12
Skewness2.3128075
Sum3249
Variance42619.443
MonotonicityNot monotonic
2023-12-13T03:50:52.051495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
5 5
17.9%
4 3
 
10.7%
41 2
 
7.1%
300 1
 
3.6%
3 1
 
3.6%
27 1
 
3.6%
500 1
 
3.6%
101 1
 
3.6%
95 1
 
3.6%
856 1
 
3.6%
Other values (11) 11
39.3%
ValueCountFrequency (%)
2 1
 
3.6%
3 1
 
3.6%
4 3
10.7%
5 5
17.9%
6 1
 
3.6%
7 1
 
3.6%
8 1
 
3.6%
13 1
 
3.6%
17 1
 
3.6%
27 1
 
3.6%
ValueCountFrequency (%)
856 1
3.6%
500 1
3.6%
482 1
3.6%
333 1
3.6%
300 1
3.6%
289 1
3.6%
101 1
3.6%
95 1
3.6%
47 1
3.6%
44 1
3.6%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2985734.3
Minimum51550
Maximum23896520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T03:50:52.310329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51550
5-th percentile67826.5
Q1103600
median407880
Q32274865
95-th percentile12812801
Maximum23896520
Range23844970
Interquartile range (IQR)2171265

Descriptive statistics

Standard deviation5525684.7
Coefficient of variation (CV)1.8506954
Kurtosis7.1593005
Mean2985734.3
Median Absolute Deviation (MAD)323435
Skewness2.571604
Sum83600560
Variance3.0533192 × 1013
MonotonicityNot monotonic
2023-12-13T03:50:52.560718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
584790 1
 
3.6%
101060 1
 
3.6%
220120 1
 
3.6%
2081500 1
 
3.6%
23896520 1
 
3.6%
100070 1
 
3.6%
103630 1
 
3.6%
1426570 1
 
3.6%
2854960 1
 
3.6%
13962390 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
51550 1
3.6%
64960 1
3.6%
73150 1
3.6%
95740 1
3.6%
100070 1
3.6%
101060 1
3.6%
103510 1
3.6%
103630 1
3.6%
111100 1
3.6%
172810 1
3.6%
ValueCountFrequency (%)
23896520 1
3.6%
13962390 1
3.6%
10677850 1
3.6%
9026520 1
3.6%
7058290 1
3.6%
6667740 1
3.6%
2854960 1
3.6%
2081500 1
3.6%
1426570 1
3.6%
1249540 1
3.6%

누적미환급금액증감
Real number (ℝ)

UNIQUE  ZEROS 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean644.93214
Minimum0
Maximum6157.5
Zeros1
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T03:50:52.761773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.27
Q128.25
median98.3
Q3288.75
95-th percentile3871.435
Maximum6157.5
Range6157.5
Interquartile range (IQR)260.5

Descriptive statistics

Standard deviation1461.2445
Coefficient of variation (CV)2.2657337
Kurtosis8.1684315
Mean644.93214
Median Absolute Deviation (MAD)76.2
Skewness2.931995
Sum18058.1
Variance2135235.4
MonotonicityNot monotonic
2023-12-13T03:50:53.530003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
9.0 1
 
3.6%
0.0 1
 
3.6%
88.8 1
 
3.6%
4.8 1
 
3.6%
78.4 1
 
3.6%
783.2 1
 
3.6%
3932.3 1
 
3.6%
22.2 1
 
3.6%
75.5 1
 
3.6%
92.6 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
0.0 1
3.6%
4.8 1
3.6%
9.0 1
3.6%
13.0 1
3.6%
22.0 1
3.6%
22.2 1
3.6%
26.0 1
3.6%
29.0 1
3.6%
60.3 1
3.6%
66.9 1
3.6%
ValueCountFrequency (%)
6157.5 1
3.6%
3932.3 1
3.6%
3758.4 1
3.6%
783.2 1
3.6%
648.0 1
3.6%
565.0 1
3.6%
423.0 1
3.6%
244.0 1
3.6%
238.7 1
3.6%
169.0 1
3.6%

Interactions

2023-12-13T03:50:46.730869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:42.696013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:43.462608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:44.577251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:45.619205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:46.912401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:42.803803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:43.607640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:44.800506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:45.820114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:47.212645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:42.954456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:43.797173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:45.055927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:46.047204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:47.580230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:43.080496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:43.992532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:45.232895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:46.251088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:47.807688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:43.241523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:44.283981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:45.417065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:46.483160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:50:53.713991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.3260.0000.0000.000
과세년도0.0001.0000.0000.1970.3240.2420.0000.000
납세자유형0.0000.0001.0000.0290.0000.2740.2720.295
당해미환급건수0.0000.1970.0291.0000.9640.9330.9900.000
당해미환급금액0.3260.3240.0000.9641.0000.8630.9370.000
누적미환급건수0.0000.2420.2740.9330.8631.0000.8940.000
누적미환급금액0.0000.0000.2720.9900.9370.8941.0000.000
누적미환급금액증감0.0000.0000.2950.0000.0000.0000.0001.000
2023-12-13T03:50:53.924454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형세목명과세년도
납세자유형1.0000.0000.000
세목명0.0001.0000.000
과세년도0.0000.0001.000
2023-12-13T03:50:54.094437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도납세자유형
당해미환급건수1.0000.7650.9310.728-0.2160.0000.0820.000
당해미환급금액0.7651.0000.7020.909-0.4160.0000.0940.000
누적미환급건수0.9310.7021.0000.7270.0490.0000.1640.307
누적미환급금액0.7280.9090.7271.000-0.1370.0000.0000.202
누적미환급금액증감-0.216-0.4160.049-0.1371.0000.0000.0000.178
세목명0.0000.0000.0000.0000.0001.0000.0000.000
과세년도0.0820.0940.1640.0000.0000.0001.0000.000
납세자유형0.0000.0000.3070.2020.1780.0000.0001.000

Missing values

2023-12-13T03:50:48.010150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:50:48.293916image/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
0전라남도나주시46170등록면허세2019신규법인353653045847909.0
1전라남도나주시46170자동차세2019신규개인11224909003336667740168.0
2전라남도나주시46170자동차세2019신규법인1511804047882540648.0
3전라남도나주시46170재산세2019신규개인910201041351190244.0
4전라남도나주시46170재산세2019신규법인59770664960565.0
5전라남도나주시46170주민세2019신규개인488080711110026.0
6전라남도나주시46170주민세2019신규법인11359905365520169.0
7전라남도나주시46170지방소득세2019신규개인8117259002899026520423.0
8전라남도나주시46170지방소득세2019신규법인111343801717281029.0
9전라남도나주시46170취득세2019신규개인191980210351013.0
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
18전라남도나주시46170지방소득세2020신규법인3153013957406157.5
19전라남도나주시46170등록면허세2021신규개인321600873150238.7
20전라남도나주시46170자동차세2021신규개인42572507008561396239092.6
21전라남도나주시46170자동차세2021신규법인54162713095285496075.5
22전라남도나주시46170재산세2021신규개인631167600101142657022.2
23전라남도나주시46170재산세2021신규법인1257051036303932.3
24전라남도나주시46170주민세2021신규개인1113305100070783.2
25전라남도나주시46170지방소득세2021신규개인213133961605002389652078.4
26전라남도나주시46170지방소득세2021신규법인1419857602720815004.8
27전라남도나주시46170취득세2021신규개인1116610322012088.8