Overview

Dataset statistics

Number of variables10
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory86.9 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description신용카드, 가상계좌 등 지방세 납부매체별 납부현황으로 납부년도, 납부매체, 납부매체전자고지여부, 납부건수, 납부금액, 납부매체비율 등으로 구성되어 있음
Author경상남도 함양군
URLhttps://www.data.go.kr/data/15079319/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부년도 has constant value ""Constant
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부건수 is highly overall correlated with 납부금액 and 1 other fieldsHigh correlation
납부금액 is highly overall correlated with 납부건수 and 2 other fieldsHigh correlation
납부매체비율 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 납부금액High correlation
납부금액 has unique valuesUnique
납부매체비율 has 1 (1.5%) zerosZeros

Reproduction

Analysis started2024-04-06 08:16:10.325077
Analysis finished2024-04-06 08:16:13.123389
Duration2.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
경상남도
68 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 68
100.0%

Length

2024-04-06T17:16:13.313450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:16:13.506590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 68
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
함양군
68 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
함양군 68
100.0%

Length

2024-04-06T17:16:13.702533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:16:13.887881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
함양군 68
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
48870
68 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48870
2nd row48870
3rd row48870
4th row48870
5th row48870

Common Values

ValueCountFrequency (%)
48870 68
100.0%

Length

2024-04-06T17:16:14.208947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:16:14.395452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48870 68
100.0%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2022
68 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 68
100.0%

Length

2024-04-06T17:16:14.621166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:16:14.822783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 68
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size676.0 B
재산세
9 
주민세
9 
등록면허세
9 
자동차세
9 
지방소득세
8 
Other values (6)
24 

Length

Max length7
Median length5
Mean length4.0735294
Min length3

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 9
13.2%
주민세 9
13.2%
등록면허세 9
13.2%
자동차세 9
13.2%
지방소득세 8
11.8%
취득세 8
11.8%
지역자원시설세 6
8.8%
등록세 6
8.8%
담배소비세 2
 
2.9%
지방소비세 1
 
1.5%

Length

2024-04-06T17:16:15.277844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재산세 9
13.2%
주민세 9
13.2%
등록면허세 9
13.2%
자동차세 9
13.2%
지방소득세 8
11.8%
취득세 8
11.8%
지역자원시설세 6
8.8%
등록세 6
8.8%
담배소비세 2
 
2.9%
지방소비세 1
 
1.5%

납부매체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size676.0 B
위택스
10 
가상계좌
9 
은행창구
8 
인터넷지로
8 
자동화기기
8 
Other values (4)
25 

Length

Max length5
Median length4
Mean length4.0882353
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위택스 10
14.7%
가상계좌 9
13.2%
은행창구 8
11.8%
인터넷지로 8
11.8%
자동화기기 8
11.8%
지자체방문 8
11.8%
기타 7
10.3%
페이사납부 6
8.8%
자동이체 4
 
5.9%

Length

2024-04-06T17:16:15.712346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:16:16.516894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위택스 10
14.7%
가상계좌 9
13.2%
은행창구 8
11.8%
인터넷지로 8
11.8%
자동화기기 8
11.8%
지자체방문 8
11.8%
기타 7
10.3%
페이사납부 6
8.8%
자동이체 4
 
5.9%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size200.0 B
True
37 
False
31 
ValueCountFrequency (%)
True 37
54.4%
False 31
45.6%
2024-04-06T17:16:16.862365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2126.0588
Minimum1
Maximum26030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-04-06T17:16:17.121131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q166.5
median421.5
Q31717
95-th percentile10349.7
Maximum26030
Range26029
Interquartile range (IQR)1650.5

Descriptive statistics

Standard deviation4217.1454
Coefficient of variation (CV)1.9835507
Kurtosis16.047568
Mean2126.0588
Median Absolute Deviation (MAD)415.5
Skewness3.6128496
Sum144572
Variance17784315
MonotonicityNot monotonic
2024-04-06T17:16:17.595678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3
 
4.4%
7 2
 
2.9%
3 2
 
2.9%
176 2
 
2.9%
260 1
 
1.5%
2035 1
 
1.5%
250 1
 
1.5%
711 1
 
1.5%
5902 1
 
1.5%
1453 1
 
1.5%
Other values (53) 53
77.9%
ValueCountFrequency (%)
1 3
4.4%
3 2
2.9%
4 1
 
1.5%
5 1
 
1.5%
7 2
2.9%
8 1
 
1.5%
9 1
 
1.5%
38 1
 
1.5%
42 1
 
1.5%
45 1
 
1.5%
ValueCountFrequency (%)
26030 1
1.5%
14971 1
1.5%
11542 1
1.5%
10692 1
1.5%
9714 1
1.5%
6479 1
1.5%
5902 1
1.5%
5335 1
1.5%
5213 1
1.5%
4769 1
1.5%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3323573 × 108
Minimum2100
Maximum1.5907504 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-04-06T17:16:17.996035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2100
5-th percentile61883.5
Q18165592.5
median60219240
Q35.2815257 × 108
95-th percentile2.5428776 × 109
Maximum1.5907504 × 1010
Range1.5907502 × 1010
Interquartile range (IQR)5.1998698 × 108

Descriptive statistics

Standard deviation2.070651 × 109
Coefficient of variation (CV)2.8239909
Kurtosis44.144123
Mean7.3323573 × 108
Median Absolute Deviation (MAD)60193630
Skewness6.1700812
Sum4.986003 × 1010
Variance4.2875957 × 1018
MonotonicityNot monotonic
2024-04-06T17:16:18.484014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2316863600 1
 
1.5%
235173320 1
 
1.5%
12348840 1
 
1.5%
2602757150 1
 
1.5%
34230 1
 
1.5%
47975830 1
 
1.5%
12853420 1
 
1.5%
373874350 1
 
1.5%
37106850 1
 
1.5%
43610550 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
2100 1
1.5%
13190 1
1.5%
16990 1
1.5%
34230 1
1.5%
113240 1
1.5%
179690 1
1.5%
193050 1
1.5%
521900 1
1.5%
654450 1
1.5%
744600 1
1.5%
ValueCountFrequency (%)
15907504410 1
1.5%
3834217120 1
1.5%
3790067180 1
1.5%
2602757150 1
1.5%
2431672670 1
1.5%
2316863600 1
1.5%
2226235430 1
1.5%
2161791860 1
1.5%
2067661920 1
1.5%
1523028550 1
1.5%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.235882
Minimum0
Maximum62.97
Zeros1
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-04-06T17:16:18.822875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0535
Q11.94
median8.235
Q318.7
95-th percentile48.3295
Maximum62.97
Range62.97
Interquartile range (IQR)16.76

Descriptive statistics

Standard deviation14.795354
Coefficient of variation (CV)1.1178215
Kurtosis2.1422428
Mean13.235882
Median Absolute Deviation (MAD)7.835
Skewness1.5603293
Sum900.04
Variance218.90251
MonotonicityNot monotonic
2024-04-06T17:16:19.220463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 2
 
2.9%
42.24 1
 
1.5%
12.64 1
 
1.5%
16.12 1
 
1.5%
17.71 1
 
1.5%
0.01 1
 
1.5%
2.18 1
 
1.5%
6.19 1
 
1.5%
51.35 1
 
1.5%
2.26 1
 
1.5%
Other values (57) 57
83.8%
ValueCountFrequency (%)
0.0 1
1.5%
0.01 1
1.5%
0.05 2
2.9%
0.06 1
1.5%
0.11 1
1.5%
0.12 1
1.5%
0.13 1
1.5%
0.3 1
1.5%
0.33 1
1.5%
0.34 1
1.5%
ValueCountFrequency (%)
62.97 1
1.5%
53.06 1
1.5%
52.07 1
1.5%
51.35 1
1.5%
42.72 1
1.5%
42.24 1
1.5%
34.15 1
1.5%
31.85 1
1.5%
27.83 1
1.5%
26.44 1
1.5%

Interactions

2024-04-06T17:16:12.057617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:10.831298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.359766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:12.255765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:10.995993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.576060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:12.435062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.181992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:11.873396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:16:19.614484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
세목명1.0000.0000.0000.0000.8000.435
납부매체0.0001.0001.0000.3640.3250.000
납부매체전자고지여부0.0001.0001.0000.0000.1170.114
납부건수0.0000.3640.0001.0000.3390.599
납부금액0.8000.3250.1170.3391.0000.000
납부매체비율0.4350.0000.1140.5990.0001.000
2024-04-06T17:16:19.906515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체전자고지여부납부매체
세목명1.0000.0000.000
납부매체전자고지여부0.0001.0000.945
납부매체0.0000.9451.000
2024-04-06T17:16:20.149937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율세목명납부매체납부매체전자고지여부
납부건수1.0000.7460.7690.0000.1940.000
납부금액0.7461.0000.5430.5970.2060.064
납부매체비율0.7690.5431.0000.2040.0000.099
세목명0.0000.5970.2041.0000.0000.000
납부매체0.1940.2060.0000.0001.0000.945
납부매체전자고지여부0.0000.0640.0990.0000.9451.000

Missing values

2024-04-06T17:16:12.672129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:16:12.960470image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
0경상남도함양군488702022재산세가상계좌Y26030231686360042.24
1경상남도함양군488702022주민세가상계좌Y971430080283015.76
2경상남도함양군488702022지방소득세가상계좌Y431622262354307.0
3경상남도함양군488702022지역자원시설세가상계좌Y7051933600.11
4경상남도함양군488702022취득세가상계좌Y97124316726701.58
5경상남도함양군488702022등록면허세기타N565219002.34
6경상남도함양군488702022자동차세기타N371152302855015.47
7경상남도함양군488702022재산세기타N268915077011.18
8경상남도함양군488702022주민세기타N17625035207.34
9경상남도함양군488702022지방소득세기타N151076494768062.97
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
58경상남도함양군488702022등록면허세페이사납부Y496544504.11
59경상남도함양군488702022자동차세페이사납부Y3325472144027.83
60경상남도함양군488702022재산세페이사납부Y6333034689053.06
61경상남도함양군488702022주민세페이사납부Y168189171014.08
62경상남도함양군488702022지방소득세페이사납부Y41930500.34
63경상남도함양군488702022취득세페이사납부Y7177274800.59
64경상남도함양군488702022담배소비세가상계좌Y3131900.0
65경상남도함양군488702022등록면허세가상계좌Y53351329500708.66
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