Overview

Dataset statistics

Number of variables11
Number of observations427
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.9 KiB
Average record size in memory93.3 B

Variable types

Categorical7
Boolean1
Numeric3

Dataset

Description해당자료는 경기도 구리시의 지방세 납부현황 자료(시군구명, 자치단체코드, 세목명, 납부매체, 납부건수, 납부매체비율등)에 대한 제공 입니다.
URLhttps://www.data.go.kr/data/15080563/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부건수 is highly overall correlated with 납부금액 and 1 other fieldsHigh correlation
납부금액 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
납부매체비율 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
납부매체비율 has 21 (4.9%) zerosZeros

Reproduction

Analysis started2023-12-12 11:44:14.486234
Analysis finished2023-12-12 11:44:17.504112
Duration3.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
경기도
427 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 427
100.0%

Length

2023-12-12T20:44:17.633874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:44:17.831723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 427
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
구리시
427 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구리시 427
100.0%

Length

2023-12-12T20:44:18.047093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:44:18.799394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구리시 427
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
41310
427 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41310
2nd row41310
3rd row41310
4th row41310
5th row41310

Common Values

ValueCountFrequency (%)
41310 427
100.0%

Length

2023-12-12T20:44:19.008012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:44:19.212401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41310 427
100.0%

납부년도
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2021
91 
2019
87 
2020
85 
2017
83 
2018
81 

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 91
21.3%
2019 87
20.4%
2020 85
19.9%
2017 83
19.4%
2018 81
19.0%

Length

2023-12-12T20:44:19.436261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:44:19.676592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 91
21.3%
2019 87
20.4%
2020 85
19.9%
2017 83
19.4%
2018 81
19.0%

세목명
Categorical

Distinct14
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
등록면허세
53 
자동차세
53 
재산세
53 
주민세
53 
지방소득세
48 
Other values (9)
167 

Length

Max length7
Median length5
Mean length4.0632319
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록면허세
2nd row등록면허세
3rd row등록세
4th row면허세
5th row자동차세

Common Values

ValueCountFrequency (%)
등록면허세 53
12.4%
자동차세 53
12.4%
재산세 53
12.4%
주민세 53
12.4%
지방소득세 48
11.2%
취득세 43
10.1%
지역자원시설세 33
7.7%
면허세 26
6.1%
등록세 23
5.4%
종합토지세 15
 
3.5%
Other values (4) 27
6.3%

Length

2023-12-12T20:44:19.992979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 53
12.4%
자동차세 53
12.4%
재산세 53
12.4%
주민세 53
12.4%
지방소득세 48
11.2%
취득세 43
10.1%
지역자원시설세 33
7.7%
면허세 26
6.1%
등록세 23
5.4%
종합토지세 15
 
3.5%
Other values (4) 27
6.3%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
ARS
68 
은행창구
60 
가상계좌
51 
위택스
49 
자동화기기
45 
Other values (5)
154 

Length

Max length5
Median length4
Mean length3.8360656
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ARS 68
15.9%
은행창구 60
14.1%
가상계좌 51
11.9%
위택스 49
11.5%
자동화기기 45
10.5%
기타 44
10.3%
인터넷지로 40
9.4%
지자체방문 32
7.5%
자동이체 20
 
4.7%
페이사납부 18
 
4.2%

Length

2023-12-12T20:44:20.328077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:44:20.629142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ars 68
15.9%
은행창구 60
14.1%
가상계좌 51
11.9%
위택스 49
11.5%
자동화기기 45
10.5%
기타 44
10.3%
인터넷지로 40
9.4%
지자체방문 32
7.5%
자동이체 20
 
4.7%
페이사납부 18
 
4.2%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size559.0 B
False
224 
True
203 
ValueCountFrequency (%)
False 224
52.5%
True 203
47.5%
2023-12-12T20:44:20.935169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct299
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5610.8899
Minimum1
Maximum76947
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T20:44:21.185521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q113
median337
Q35424
95-th percentile30826.5
Maximum76947
Range76946
Interquartile range (IQR)5411

Descriptive statistics

Standard deviation12494.185
Coefficient of variation (CV)2.2267742
Kurtosis13.315714
Mean5610.8899
Median Absolute Deviation (MAD)336
Skewness3.5409292
Sum2395850
Variance1.5610465 × 108
MonotonicityNot monotonic
2023-12-12T20:44:21.543575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 29
 
6.8%
2 18
 
4.2%
3 9
 
2.1%
7 8
 
1.9%
8 8
 
1.9%
11 7
 
1.6%
6 6
 
1.4%
4 6
 
1.4%
13 6
 
1.4%
9 6
 
1.4%
Other values (289) 324
75.9%
ValueCountFrequency (%)
1 29
6.8%
2 18
4.2%
3 9
 
2.1%
4 6
 
1.4%
5 3
 
0.7%
6 6
 
1.4%
7 8
 
1.9%
8 8
 
1.9%
9 6
 
1.4%
10 3
 
0.7%
ValueCountFrequency (%)
76947 1
0.2%
74066 1
0.2%
69036 1
0.2%
67760 1
0.2%
67020 1
0.2%
65384 1
0.2%
63620 1
0.2%
60618 1
0.2%
58717 1
0.2%
54811 1
0.2%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct426
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9940201 × 109
Minimum2280
Maximum7.2983122 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T20:44:21.885756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2280
5-th percentile29512
Q11548360
median1.0988265 × 108
Q31.4682032 × 109
95-th percentile1.644005 × 1010
Maximum7.2983122 × 1010
Range7.2983119 × 1010
Interquartile range (IQR)1.4666549 × 109

Descriptive statistics

Standard deviation7.4999001 × 109
Coefficient of variation (CV)2.5049598
Kurtosis34.152785
Mean2.9940201 × 109
Median Absolute Deviation (MAD)1.0985692 × 108
Skewness4.9874325
Sum1.2784466 × 1012
Variance5.6248502 × 1019
MonotonicityNot monotonic
2023-12-12T20:44:22.218987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21000 2
 
0.5%
562160 1
 
0.2%
300665660 1
 
0.2%
7884476950 1
 
0.2%
65650077860 1
 
0.2%
236120 1
 
0.2%
7595871190 1
 
0.2%
1017883220 1
 
0.2%
6014874490 1
 
0.2%
2744658260 1
 
0.2%
Other values (416) 416
97.4%
ValueCountFrequency (%)
2280 1
0.2%
3520 1
0.2%
3540 1
0.2%
5150 1
0.2%
5250 1
0.2%
5560 1
0.2%
8220 1
0.2%
8890 1
0.2%
9700 1
0.2%
10140 1
0.2%
ValueCountFrequency (%)
72983121690 1
0.2%
65650077860 1
0.2%
48755385950 1
0.2%
42814292490 1
0.2%
34789636320 1
0.2%
26491035140 1
0.2%
25903936920 1
0.2%
24951200320 1
0.2%
23008292650 1
0.2%
22040603030 1
0.2%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct274
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.241335
Minimum0
Maximum83.67
Zeros21
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T20:44:22.563262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.05
median5.51
Q317.77
95-th percentile40.006
Maximum83.67
Range83.67
Interquartile range (IQR)17.72

Descriptive statistics

Standard deviation14.622904
Coefficient of variation (CV)1.3008157
Kurtosis3.8546341
Mean11.241335
Median Absolute Deviation (MAD)5.5
Skewness1.7749058
Sum4800.05
Variance213.82933
MonotonicityNot monotonic
2023-12-12T20:44:22.858007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 43
 
10.1%
0.0 21
 
4.9%
0.02 20
 
4.7%
0.03 11
 
2.6%
0.05 9
 
2.1%
0.06 8
 
1.9%
0.08 7
 
1.6%
0.07 6
 
1.4%
0.09 5
 
1.2%
0.04 5
 
1.2%
Other values (264) 292
68.4%
ValueCountFrequency (%)
0.0 21
4.9%
0.01 43
10.1%
0.02 20
4.7%
0.03 11
 
2.6%
0.04 5
 
1.2%
0.05 9
 
2.1%
0.06 8
 
1.9%
0.07 6
 
1.4%
0.08 7
 
1.6%
0.09 5
 
1.2%
ValueCountFrequency (%)
83.67 1
0.2%
82.63 1
0.2%
72.75 1
0.2%
62.8 1
0.2%
62.26 1
0.2%
59.72 1
0.2%
58.88 1
0.2%
58.28 1
0.2%
58.24 1
0.2%
57.99 1
0.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-06-21
427 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-21
2nd row2023-06-21
3rd row2023-06-21
4th row2023-06-21
5th row2023-06-21

Common Values

ValueCountFrequency (%)
2023-06-21 427
100.0%

Length

2023-12-12T20:44:23.139144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:44:23.360414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-21 427
100.0%

Interactions

2023-12-12T20:44:16.408735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:44:15.196539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:44:15.806127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:44:16.597394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:44:15.408912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:44:16.005010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:44:16.797557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:44:15.619505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:44:16.209879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:44:23.526468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.2230.1360.2100.3590.570
납부매체0.0000.2231.0000.9920.5710.2470.643
납부매체전자고지여부0.0000.1360.9921.0000.2190.0000.248
납부건수0.0000.2100.5710.2191.0000.5260.757
납부금액0.0000.3590.2470.0000.5261.0000.277
납부매체비율0.0000.5700.6430.2480.7570.2771.000
2023-12-12T20:44:23.810371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체세목명납부매체전자고지여부납부년도
납부매체1.0000.0910.9120.000
세목명0.0911.0000.1040.000
납부매체전자고지여부0.9120.1041.0000.000
납부년도0.0000.0000.0001.000
2023-12-12T20:44:24.025923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8190.8500.0000.0850.2070.166
납부금액0.8191.0000.6680.0000.1590.1150.000
납부매체비율0.8500.6681.0000.0000.2700.2460.188
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.0850.1590.2700.0001.0000.0910.104
납부매체0.2070.1150.2460.0000.0911.0000.912
납부매체전자고지여부0.1660.0000.1880.0000.1040.9121.000

Missing values

2023-12-12T20:44:17.067346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:44:17.398008image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일자
0경기도구리시413102017등록면허세ARSN24341343301.822023-06-21
1경기도구리시413102017등록면허세ARSY81758700.062023-06-21
2경기도구리시413102017등록세ARSN112652200.012023-06-21
3경기도구리시413102017면허세ARSN111688600.082023-06-21
4경기도구리시413102017자동차세ARSN6331118088983047.332023-06-21
5경기도구리시413102017자동차세ARSY5050052600.372023-06-21
6경기도구리시413102017재산세ARSN438194434290032.762023-06-21
7경기도구리시413102017재산세ARSY811062200.062023-06-21
8경기도구리시413102017주민세ARSN19503448457014.582023-06-21
9경기도구리시413102017주민세ARSY748975000.552023-06-21
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일자
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