Overview

Dataset statistics

Number of variables14
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory124.6 B

Variable types

Numeric7
Categorical7

Dataset

Description미환급 현황 및 연간 누적 현황 제공
Author인천광역시 옹진군
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079405&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 과세년도High correlation
과세년도 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
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
미환급유형 is highly overall correlated with 과세년도High correlation
미환급유형 is highly imbalanced (52.0%)Imbalance
순번 has unique valuesUnique
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has 8 (27.6%) zerosZeros

Reproduction

Analysis started2024-01-28 09:11:54.162078
Analysis finished2024-01-28 09:11:58.443258
Duration4.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-28T18:11:58.495697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2024-01-28T18:11:58.598297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
인천광역시
29 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 29
100.0%

Length

2024-01-28T18:11:58.699873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:11:58.772943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 29
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
옹진군
29 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
옹진군 29
100.0%

Length

2024-01-28T18:11:58.846020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:11:58.920831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옹진군 29
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
28720
29 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28720
2nd row28720
3rd row28720
4th row28720
5th row28720

Common Values

ValueCountFrequency (%)
28720 29
100.0%

Length

2024-01-28T18:11:59.006022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:11:59.076742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28720 29
100.0%

세목명
Categorical

Distinct4
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
자동차세
12 
지방소득세
9 
등록면허세
4 
재산세
4 

Length

Max length5
Median length4
Mean length4.3103448
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자동차세
2nd row자동차세
3rd row자동차세
4th row지방소득세
5th row지방소득세

Common Values

ValueCountFrequency (%)
자동차세 12
41.4%
지방소득세 9
31.0%
등록면허세 4
 
13.8%
재산세 4
 
13.8%

Length

2024-01-28T18:11:59.168601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:11:59.256022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 12
41.4%
지방소득세 9
31.0%
등록면허세 4
 
13.8%
재산세 4
 
13.8%

과세년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.6897
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-28T18:11:59.338072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.814691
Coefficient of variation (CV)0.00089849993
Kurtosis-1.3756208
Mean2019.6897
Median Absolute Deviation (MAD)2
Skewness-0.19440216
Sum58571
Variance3.2931034
MonotonicityIncreasing
2024-01-28T18:11:59.428079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2021 6
20.7%
2022 6
20.7%
2017 5
17.2%
2018 4
13.8%
2019 4
13.8%
2020 4
13.8%
ValueCountFrequency (%)
2017 5
17.2%
2018 4
13.8%
2019 4
13.8%
2020 4
13.8%
2021 6
20.7%
2022 6
20.7%
ValueCountFrequency (%)
2022 6
20.7%
2021 6
20.7%
2020 4
13.8%
2019 4
13.8%
2018 4
13.8%
2017 5
17.2%

미환급유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
신규
26 
송달분 미수령
3 

Length

Max length7
Median length2
Mean length2.5172414
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 26
89.7%
송달분 미수령 3
 
10.3%

Length

2024-01-28T18:11:59.527638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:11:59.602053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 26
81.2%
송달분 3
 
9.4%
미수령 3
 
9.4%

납세자유형
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
개인
19 
법인
10 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 19
65.5%
법인 10
34.5%

Length

2024-01-28T18:11:59.679751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:11:59.754646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 19
65.5%
법인 10
34.5%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.586207
Minimum1
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-28T18:11:59.824164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q333
95-th percentile108.6
Maximum121
Range120
Interquartile range (IQR)31

Descriptive statistics

Standard deviation35.188794
Coefficient of variation (CV)1.4919226
Kurtosis2.3962917
Mean23.586207
Median Absolute Deviation (MAD)3
Skewness1.8148859
Sum684
Variance1238.2512
MonotonicityNot monotonic
2024-01-28T18:11:59.919338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 7
24.1%
2 4
13.8%
3 3
 
10.3%
16 1
 
3.4%
63 1
 
3.4%
33 1
 
3.4%
111 1
 
3.4%
121 1
 
3.4%
48 1
 
3.4%
105 1
 
3.4%
Other values (8) 8
27.6%
ValueCountFrequency (%)
1 7
24.1%
2 4
13.8%
3 3
10.3%
4 1
 
3.4%
7 1
 
3.4%
9 1
 
3.4%
10 1
 
3.4%
16 1
 
3.4%
22 1
 
3.4%
23 1
 
3.4%
ValueCountFrequency (%)
121 1
3.4%
111 1
3.4%
105 1
3.4%
63 1
3.4%
48 1
3.4%
47 1
3.4%
41 1
3.4%
33 1
3.4%
23 1
3.4%
22 1
3.4%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307015.17
Minimum130
Maximum2484730
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-28T18:12:00.015980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum130
5-th percentile628
Q19640
median75340
Q3380680
95-th percentile1341394
Maximum2484730
Range2484600
Interquartile range (IQR)371040

Descriptive statistics

Standard deviation551909.35
Coefficient of variation (CV)1.7976615
Kurtosis8.7158483
Mean307015.17
Median Absolute Deviation (MAD)73650
Skewness2.8160236
Sum8903440
Variance3.0460393 × 1011
MonotonicityNot monotonic
2024-01-28T18:12:00.122412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
75340 1
 
3.4%
98160 1
 
3.4%
695330 1
 
3.4%
31620 1
 
3.4%
224300 1
 
3.4%
115100 1
 
3.4%
2484730 1
 
3.4%
9000 1
 
3.4%
1690 1
 
3.4%
1031800 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
130 1
3.4%
480 1
3.4%
850 1
3.4%
1690 1
3.4%
7330 1
3.4%
9000 1
3.4%
9130 1
3.4%
9640 1
3.4%
10600 1
3.4%
15220 1
3.4%
ValueCountFrequency (%)
2484730 1
3.4%
1547790 1
3.4%
1031800 1
3.4%
695330 1
3.4%
690030 1
3.4%
405520 1
3.4%
395190 1
3.4%
380680 1
3.4%
253970 1
3.4%
224300 1
3.4%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.931034
Minimum1
Maximum182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-28T18:12:00.218100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q348
95-th percentile162.4
Maximum182
Range181
Interquartile range (IQR)45

Descriptive statistics

Standard deviation56.893968
Coefficient of variation (CV)1.3899959
Kurtosis0.8620801
Mean40.931034
Median Absolute Deviation (MAD)5
Skewness1.4586546
Sum1187
Variance3236.9236
MonotonicityNot monotonic
2024-01-28T18:12:00.312746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3 5
17.2%
5 3
 
10.3%
1 3
 
10.3%
2 2
 
6.9%
109 2
 
6.9%
39 2
 
6.9%
10 1
 
3.4%
62 1
 
3.4%
20 1
 
3.4%
4 1
 
3.4%
Other values (8) 8
27.6%
ValueCountFrequency (%)
1 3
10.3%
2 2
 
6.9%
3 5
17.2%
4 1
 
3.4%
5 3
10.3%
6 1
 
3.4%
10 1
 
3.4%
20 1
 
3.4%
26 1
 
3.4%
39 2
 
6.9%
ValueCountFrequency (%)
182 1
3.4%
176 1
3.4%
142 1
3.4%
138 1
3.4%
109 2
6.9%
62 1
3.4%
48 1
3.4%
40 1
3.4%
39 2
6.9%
26 1
3.4%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean469538.28
Minimum130
Maximum3279380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-28T18:12:00.414269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum130
5-th percentile964
Q128950
median107820
Q3405520
95-th percentile2045304
Maximum3279380
Range3279250
Interquartile range (IQR)376570

Descriptive statistics

Standard deviation790333.56
Coefficient of variation (CV)1.6832144
Kurtosis5.5335621
Mean469538.28
Median Absolute Deviation (MAD)98690
Skewness2.3394248
Sum13616610
Variance6.2462714 × 1011
MonotonicityNot monotonic
2024-01-28T18:12:00.525863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
195900 2
 
6.9%
36980 2
 
6.9%
2374540 1
 
3.4%
1306360 1
 
3.4%
31620 1
 
3.4%
238250 1
 
3.4%
130320 1
 
3.4%
3279380 1
 
3.4%
27440 1
 
3.4%
1690 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
130 1
3.4%
480 1
3.4%
1690 1
3.4%
9130 1
3.4%
10600 1
3.4%
17930 1
3.4%
27440 1
3.4%
28950 1
3.4%
31620 1
3.4%
32190 1
3.4%
ValueCountFrequency (%)
3279380 1
3.4%
2374540 1
3.4%
1551450 1
3.4%
1306360 1
3.4%
1135580 1
3.4%
1093530 1
3.4%
540230 1
3.4%
405520 1
3.4%
403500 1
3.4%
311270 1
3.4%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean209.41828
Minimum0
Maximum4250.59
Zeros8
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-01-28T18:12:00.627783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median36.7
Q399.57
95-th percentile222.308
Maximum4250.59
Range4250.59
Interquartile range (IQR)99.57

Descriptive statistics

Standard deviation780.55587
Coefficient of variation (CV)3.7272576
Kurtosis28.453474
Mean209.41828
Median Absolute Deviation (MAD)36.7
Skewness5.3123219
Sum6073.13
Variance609267.47
MonotonicityNot monotonic
2024-01-28T18:12:00.725228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 8
27.6%
160.02 1
 
3.4%
90.21 1
 
3.4%
87.88 1
 
3.4%
6.22 1
 
3.4%
13.22 1
 
3.4%
31.98 1
 
3.4%
204.89 1
 
3.4%
50.36 1
 
3.4%
233.92 1
 
3.4%
Other values (12) 12
41.4%
ValueCountFrequency (%)
0.0 8
27.6%
6.22 1
 
3.4%
13.22 1
 
3.4%
19.58 1
 
3.4%
22.56 1
 
3.4%
31.98 1
 
3.4%
34.28 1
 
3.4%
36.7 1
 
3.4%
50.36 1
 
3.4%
53.41 1
 
3.4%
ValueCountFrequency (%)
4250.59 1
3.4%
233.92 1
3.4%
204.89 1
3.4%
198.3 1
3.4%
181.99 1
3.4%
160.02 1
3.4%
144.61 1
3.4%
99.57 1
3.4%
94.36 1
3.4%
90.21 1
3.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-08-31
29 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-31
2nd row2023-08-31
3rd row2023-08-31
4th row2023-08-31
5th row2023-08-31

Common Values

ValueCountFrequency (%)
2023-08-31 29
100.0%

Length

2024-01-28T18:12:00.814209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:12:00.883643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-31 29
100.0%

Interactions

2024-01-28T18:11:57.723388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:54.483701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.005304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.450782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.959353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.442287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.930188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.786794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:54.549611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.069704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.529629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.032291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.509430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.000041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.850091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:54.614236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.129226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.597945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.101798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.577565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.078645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.919460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:54.681664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.191323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.663369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.169234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.650867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.150584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.985690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:54.749105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.251725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.740692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.235172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.727800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.233469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:58.057037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:54.860525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.317472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.821730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.306297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.796402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.310910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:58.125115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:54.939298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.387908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:55.895575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.376804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:56.869163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:11:57.661915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:12:00.931778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
순번1.0000.4480.9720.6810.0000.0000.4450.0000.0000.000
세목명0.4481.0000.0000.0000.0000.0000.0000.3960.0000.000
과세년도0.9720.0001.000NaN0.0000.0000.3610.0000.000NaN
미환급유형0.6810.000NaN1.0000.0000.0000.0000.0000.0000.255
납세자유형0.0000.0000.0000.0001.0000.3550.0000.4920.0000.000
당해미환급건수0.0000.0000.0000.0000.3551.0000.8100.9330.8580.000
당해미환급금액0.4450.0000.3610.0000.0000.8101.0000.7910.9930.000
누적미환급건수0.0000.3960.0000.0000.4920.9330.7911.0000.8170.000
누적미환급금액0.0000.0000.0000.0000.0000.8580.9930.8171.0000.000
누적미환급금액증감0.0000.000NaN0.2550.0000.0000.0000.0000.0001.000
2024-01-28T18:12:01.036601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형미환급유형
세목명1.0000.0000.000
납세자유형0.0001.0000.000
미환급유형0.0000.0001.000
2024-01-28T18:12:01.120340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과세년도당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명미환급유형납세자유형
순번1.0000.9850.2480.2520.2010.163-0.2380.1360.4350.000
과세년도0.9851.0000.2700.2860.2390.197-0.2100.0000.6240.000
당해미환급건수0.2480.2701.0000.7970.9400.7820.0970.0000.0000.334
당해미환급금액0.2520.2860.7971.0000.7940.9580.0380.0000.0000.000
누적미환급건수0.2010.2390.9400.7941.0000.8400.3620.2500.0000.470
누적미환급금액0.1630.1970.7820.9580.8401.0000.2620.0000.0000.000
누적미환급금액증감-0.238-0.2100.0970.0380.3620.2621.0000.0000.1600.000
세목명0.1360.0000.0000.0000.2500.0000.0001.0000.0000.000
미환급유형0.4350.6240.0000.0000.0000.0000.1600.0001.0000.000
납세자유형0.0000.0000.3340.0000.4700.0000.0000.0000.0001.000

Missing values

2024-01-28T18:11:58.211621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:11:58.381953image/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

순번시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감데이터기준일자
01인천광역시옹진군28720자동차세2017송달분 미수령개인227534039195900160.022023-08-31
12인천광역시옹진군28720자동차세2017신규개인9981603919590099.572023-08-31
23인천광역시옹진군28720자동차세2017송달분 미수령법인2106002106000.02023-08-31
34인천광역시옹진군28720지방소득세2017송달분 미수령개인18503369804250.592023-08-31
45인천광역시옹진군28720지방소득세2017신규개인12754033698034.282023-08-31
56인천광역시옹진군28720등록면허세2018신규개인49130491300.02023-08-31
67인천광역시옹진군28720자동차세2018신규개인232076006240350094.362023-08-31
78인천광역시옹진군28720자동차세2018신규법인17330317930144.612023-08-31
89인천광역시옹진군28720지방소득세2018신규개인7203201057300181.992023-08-31
910인천광역시옹진군28720등록면허세2019신규법인140552014055200.02023-08-31
순번시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감데이터기준일자
1920인천광역시옹진군28720재산세2021신규개인48107820481078200.02023-08-31
2021인천광역시옹진군28720재산세2021신규법인148014800.02023-08-31
2122인천광역시옹진군28720지방소득세2021신규개인1211031800142155145050.362023-08-31
2223인천광역시옹진군28720지방소득세2021신규법인21690216900.02023-08-31
2324인천광역시옹진군28720등록면허세2022신규개인19000327440204.892023-08-31
2425인천광역시옹진군28720자동차세2022신규개인1112484730182327938031.982023-08-31
2526인천광역시옹진군28720자동차세2022신규법인2115100513032013.222023-08-31
2627인천광역시옹진군28720재산세2022신규개인33224300402382506.222023-08-31
2728인천광역시옹진군28720재산세2022신규법인3316203316200.02023-08-31
2829인천광역시옹진군28720지방소득세2022신규개인63695330138130636087.882023-08-31