Overview

Dataset statistics

Number of variables14
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory123.6 B

Variable types

Numeric6
Categorical8

Dataset

Description평창군 지방세 미환급현황에 대한 데이터로, 과세년도, 미환급유형, 납세자유형, 당해미환급건수, 당해미환급금액, 누적미환급건수, 누적미환급금액, 누적미환급금액증감을 제공합니다.(2017~2021)
Author강원도 평창군
URLhttps://www.data.go.kr/data/15080522/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
미환급유형 has constant value ""Constant
데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 과세년도High 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
과세년도 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique
당해미환급금액 has unique valuesUnique
누적미환급금액 has unique valuesUnique
누적미환급금액증감 has 6 (16.2%) zerosZeros

Reproduction

Analysis started2023-12-12 23:31:18.368992
Analysis finished2023-12-12 23:31:21.872605
Duration3.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T08:31:21.931754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q110
median19
Q328
95-th percentile35.2
Maximum37
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.56970291
Kurtosis-1.2
Mean19
Median Absolute Deviation (MAD)9
Skewness0
Sum703
Variance117.16667
MonotonicityStrictly increasing
2023-12-13T08:31:22.046241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
29 1
 
2.7%
22 1
 
2.7%
23 1
 
2.7%
24 1
 
2.7%
25 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
30 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
5 1
2.7%
6 1
2.7%
7 1
2.7%
8 1
2.7%
9 1
2.7%
10 1
2.7%
ValueCountFrequency (%)
37 1
2.7%
36 1
2.7%
35 1
2.7%
34 1
2.7%
33 1
2.7%
32 1
2.7%
31 1
2.7%
30 1
2.7%
29 1
2.7%
28 1
2.7%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
강원도
37 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 37
100.0%

Length

2023-12-13T08:31:22.180636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:22.260670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 37
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
평창군
37 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평창군 37
100.0%

Length

2023-12-13T08:31:22.350456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:22.435207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평창군 37
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
42760
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42760
2nd row42760
3rd row42760
4th row42760
5th row42760

Common Values

ValueCountFrequency (%)
42760 37
100.0%

Length

2023-12-13T08:31:22.520992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:22.610462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42760 37
100.0%

세목명
Categorical

Distinct6
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size428.0 B
자동차세
10 
지방소득세
10 
재산세
6 
등록면허세
5 
주민세
4 

Length

Max length5
Median length4
Mean length4.0810811
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 10
27.0%
지방소득세 10
27.0%
재산세 6
16.2%
등록면허세 5
13.5%
주민세 4
 
10.8%
취득세 2
 
5.4%

Length

2023-12-13T08:31:22.718409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:22.834598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 10
27.0%
지방소득세 10
27.0%
재산세 6
16.2%
등록면허세 5
13.5%
주민세 4
 
10.8%
취득세 2
 
5.4%

과세년도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
2021
10 
2019
8 
2020
8 
2017
6 
2018
5 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2021 10
27.0%
2019 8
21.6%
2020 8
21.6%
2017 6
16.2%
2018 5
13.5%

Length

2023-12-13T08:31:22.941234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:23.048292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10
27.0%
2019 8
21.6%
2020 8
21.6%
2017 6
16.2%
2018 5
13.5%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
신규
37 

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 37
100.0%

Length

2023-12-13T08:31:23.161092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:23.498618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 37
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
개인
22 
법인
15 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 22
59.5%
법인 15
40.5%

Length

2023-12-13T08:31:23.579595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:23.660968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 22
59.5%
법인 15
40.5%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.540541
Minimum1
Maximum375
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T08:31:23.748766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median8
Q321
95-th percentile112.2
Maximum375
Range374
Interquartile range (IQR)18

Descriptive statistics

Standard deviation67.279514
Coefficient of variation (CV)2.2029575
Kurtosis19.825076
Mean30.540541
Median Absolute Deviation (MAD)6
Skewness4.1681294
Sum1130
Variance4526.533
MonotonicityNot monotonic
2023-12-13T08:31:23.856100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2 6
16.2%
8 6
16.2%
1 3
 
8.1%
3 2
 
5.4%
9 2
 
5.4%
7 2
 
5.4%
5 2
 
5.4%
48 1
 
2.7%
55 1
 
2.7%
375 1
 
2.7%
Other values (11) 11
29.7%
ValueCountFrequency (%)
1 3
8.1%
2 6
16.2%
3 2
 
5.4%
4 1
 
2.7%
5 2
 
5.4%
6 1
 
2.7%
7 2
 
5.4%
8 6
16.2%
9 2
 
5.4%
14 1
 
2.7%
ValueCountFrequency (%)
375 1
2.7%
161 1
2.7%
100 1
2.7%
90 1
2.7%
57 1
2.7%
55 1
2.7%
48 1
2.7%
37 1
2.7%
34 1
2.7%
21 1
2.7%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean349281.35
Minimum1150
Maximum3064490
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T08:31:23.985595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1150
5-th percentile8490
Q145560
median88870
Q3396010
95-th percentile2010814
Maximum3064490
Range3063340
Interquartile range (IQR)350450

Descriptive statistics

Standard deviation655953.8
Coefficient of variation (CV)1.8780098
Kurtosis9.2418684
Mean349281.35
Median Absolute Deviation (MAD)60980
Skewness3.0116568
Sum12923410
Variance4.3027538 × 1011
MonotonicityNot monotonic
2023-12-13T08:31:24.119897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
408980 1
 
2.7%
67640 1
 
2.7%
518430 1
 
2.7%
89130 1
 
2.7%
60810 1
 
2.7%
541890 1
 
2.7%
6010 1
 
2.7%
107650 1
 
2.7%
57290 1
 
2.7%
1998050 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1150 1
2.7%
6010 1
2.7%
9110 1
2.7%
9210 1
2.7%
9600 1
2.7%
11330 1
2.7%
27890 1
2.7%
30830 1
2.7%
31310 1
2.7%
45560 1
2.7%
ValueCountFrequency (%)
3064490 1
2.7%
2061870 1
2.7%
1998050 1
2.7%
654990 1
2.7%
649320 1
2.7%
553560 1
2.7%
541890 1
2.7%
518430 1
2.7%
408980 1
2.7%
396010 1
2.7%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.702703
Minimum1
Maximum429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T08:31:24.227267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median18
Q343
95-th percentile264.4
Maximum429
Range428
Interquartile range (IQR)37

Descriptive statistics

Standard deviation94.977736
Coefficient of variation (CV)1.7050831
Kurtosis6.9656075
Mean55.702703
Median Absolute Deviation (MAD)13
Skewness2.6137726
Sum2061
Variance9020.7703
MonotonicityNot monotonic
2023-12-13T08:31:24.335594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2 4
 
10.8%
43 2
 
5.4%
10 2
 
5.4%
29 2
 
5.4%
8 2
 
5.4%
16 2
 
5.4%
6 2
 
5.4%
21 1
 
2.7%
9 1
 
2.7%
3 1
 
2.7%
Other values (18) 18
48.6%
ValueCountFrequency (%)
1 1
 
2.7%
2 4
10.8%
3 1
 
2.7%
4 1
 
2.7%
5 1
 
2.7%
6 2
5.4%
7 1
 
2.7%
8 2
5.4%
9 1
 
2.7%
10 2
5.4%
ValueCountFrequency (%)
429 1
2.7%
306 1
2.7%
254 1
2.7%
182 1
2.7%
154 1
2.7%
114 1
2.7%
97 1
2.7%
67 1
2.7%
64 1
2.7%
43 2
5.4%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean629364.59
Minimum9210
Maximum3678280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T08:31:24.445070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9210
5-th percentile36620
Q170250
median145730
Q3809680
95-th percentile2475498
Maximum3678280
Range3669070
Interquartile range (IQR)739430

Descriptive statistics

Standard deviation922107.67
Coefficient of variation (CV)1.4651407
Kurtosis3.3439615
Mean629364.59
Median Absolute Deviation (MAD)89960
Skewness1.9406109
Sum23286490
Variance8.5028256 × 1011
MonotonicityNot monotonic
2023-12-13T08:31:24.559603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
692080 1
 
2.7%
113750 1
 
2.7%
1628420 1
 
2.7%
125860 1
 
2.7%
253690 1
 
2.7%
809680 1
 
2.7%
42360 1
 
2.7%
107650 1
 
2.7%
66500 1
 
2.7%
3197650 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
9210 1
2.7%
13660 1
2.7%
42360 1
2.7%
55770 1
2.7%
61610 1
2.7%
62580 1
2.7%
62760 1
2.7%
64880 1
2.7%
66500 1
2.7%
70250 1
2.7%
ValueCountFrequency (%)
3678280 1
2.7%
3197650 1
2.7%
2294960 1
2.7%
1996390 1
2.7%
1628420 1
2.7%
1619610 1
2.7%
1347070 1
2.7%
1339840 1
2.7%
1223040 1
2.7%
809680 1
2.7%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317.86811
Minimum0
Maximum5357.39
Zeros6
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T08:31:24.659598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116.08
median99.84
Q3211.85
95-th percentile757.544
Maximum5357.39
Range5357.39
Interquartile range (IQR)195.77

Descriptive statistics

Standard deviation886.66689
Coefficient of variation (CV)2.7894176
Kurtosis31.007796
Mean317.86811
Median Absolute Deviation (MAD)88.54
Skewness5.3910569
Sum11761.12
Variance786178.17
MonotonicityNot monotonic
2023-12-13T08:31:24.754948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 6
 
16.2%
69.22 1
 
2.7%
16.08 1
 
2.7%
214.11 1
 
2.7%
41.21 1
 
2.7%
317.18 1
 
2.7%
49.42 1
 
2.7%
604.83 1
 
2.7%
68.17 1
 
2.7%
653.75 1
 
2.7%
Other values (22) 22
59.5%
ValueCountFrequency (%)
0.0 6
16.2%
1.0 1
 
2.7%
11.3 1
 
2.7%
15.37 1
 
2.7%
16.08 1
 
2.7%
16.94 1
 
2.7%
20.03 1
 
2.7%
20.56 1
 
2.7%
41.21 1
 
2.7%
49.42 1
 
2.7%
ValueCountFrequency (%)
5357.39 1
2.7%
1047.12 1
2.7%
685.15 1
2.7%
653.75 1
2.7%
612.18 1
2.7%
604.83 1
2.7%
478.91 1
2.7%
317.18 1
2.7%
214.11 1
2.7%
211.85 1
2.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
2022-09-21
37 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-21
2nd row2022-09-21
3rd row2022-09-21
4th row2022-09-21
5th row2022-09-21

Common Values

ValueCountFrequency (%)
2022-09-21 37
100.0%

Length

2023-12-13T08:31:24.848229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:24.922051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-21 37
100.0%

Interactions

2023-12-13T08:31:21.047259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:18.749355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.342653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.768827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.169817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.620023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:21.115120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:18.869472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.439328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.836625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.252772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.696533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:21.194206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:18.954651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.510319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.903368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.340636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.768742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:21.300108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.054688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.578417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.968101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.419106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.843457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:21.435885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.167781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.636828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.028998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.477334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.909308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:21.523006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.251889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:19.705637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.099359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.561817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:20.981456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:31:24.973932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번세목명과세년도납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
순번1.0000.5110.9930.0000.0000.4170.0000.0000.411
세목명0.5111.0000.0000.0000.0000.0000.0000.0000.000
과세년도0.9930.0001.0000.0000.0000.2240.0000.0000.283
납세자유형0.0000.0000.0001.0000.1960.3580.2560.4160.195
당해미환급건수0.0000.0000.0000.1961.0000.9640.9530.9480.000
당해미환급금액0.4170.0000.2240.3580.9641.0000.9030.9350.000
누적미환급건수0.0000.0000.0000.2560.9530.9031.0000.9430.000
누적미환급금액0.0000.0000.0000.4160.9480.9350.9431.0000.000
누적미환급금액증감0.4110.0000.2830.1950.0000.0000.0000.0001.000
2023-12-13T08:31:25.066189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형
과세년도1.0000.0000.000
세목명0.0001.0000.000
납세자유형0.0000.0001.000
2023-12-13T08:31:25.137190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도납세자유형
순번1.0000.0530.2030.0280.186-0.2460.2810.8360.000
당해미환급건수0.0531.0000.7510.9300.8300.1230.0000.0000.222
당해미환급금액0.2030.7511.0000.6810.876-0.2800.0000.0520.427
누적미환급건수0.0280.9300.6811.0000.8740.3550.0000.0000.159
누적미환급금액0.1860.8300.8760.8741.0000.1450.0000.0000.329
누적미환급금액증감-0.2460.123-0.2800.3550.1451.0000.0000.2090.313
세목명0.2810.0000.0000.0000.0000.0001.0000.0000.000
과세년도0.8360.0000.0520.0000.0000.2090.0001.0000.000
납세자유형0.0000.2220.4270.1590.3290.3130.0000.0001.000

Missing values

2023-12-13T08:31:21.646808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:31:21.809309image/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
01강원도평창군42760자동차세2017신규개인484089809769208069.222022-09-21
12강원도평창군42760자동차세2017신규법인87056016145730106.532022-09-21
23강원도평창군42760재산세2017신규개인86196010625801.02022-09-21
34강원도평창군42760주민세2017신규개인11133021366020.562022-09-21
45강원도평창군42760지방소득세2017신규개인17553560291223040120.942022-09-21
56강원도평창군42760지방소득세2017신규법인33083046161099.842022-09-21
67강원도평창군42760자동차세2018신규개인576549901541347070105.662022-09-21
78강원도평창군42760자동차세2018신규법인66879022214520211.852022-09-21
89강원도평창군42760재산세2018신규개인94556019108140137.362022-09-21
910강원도평창군42760지방소득세2018신규개인141168004313398401047.122022-09-21
순번시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감데이터기준일자
2728강원도평창군42760등록면허세2021신규개인25729036650016.082022-09-21
2829강원도평창군42760등록면허세2021신규법인367640811375068.172022-09-21
2930강원도평창군42760자동차세2021신규개인1611998050306319765060.042022-09-21
3031강원도평창군42760자동차세2021신규법인79011021209910132.952022-09-21
3132강원도평창군42760재산세2021신규개인902061870114229496011.32022-09-21
3233강원도평창군42760재산세2021신규법인213885021388500.02022-09-21
3334강원도평창군42760주민세2021신규개인373960104346311016.942022-09-21
3435강원도평창군42760지방소득세2021신규개인3753064490429367828020.032022-09-21
3536강원도평창군42760지방소득세2021신규법인9278901870250151.882022-09-21
3637강원도평창군42760취득세2021신규개인735938073593800.02022-09-21