Overview

Dataset statistics

Number of variables11
Number of observations257
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.5 KiB
Average record size in memory93.5 B

Variable types

Categorical6
Boolean1
Numeric3
DateTime1

Dataset

Description경기도 용인시 처인구, 기흥구, 수지구 지방세 납부매체별 납부 현황입니다. 납부매체, 납부건수, 납부금액 등의 데이터를 제공합니다. ※ 데이터기준일자 : 2021-12-31
URLhttps://www.data.go.kr/data/15078578/fileData.do

Alerts

시도명 has constant value ""Constant
납부년도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시군구명 is highly overall correlated with 자치단체코드High correlation
자치단체코드 is highly overall correlated with 시군구명High 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
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부금액 has unique valuesUnique
납부매체비율 has 42 (16.3%) zerosZeros

Reproduction

Analysis started2023-12-11 23:35:36.159287
Analysis finished2023-12-11 23:35:37.449767
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
경기도
257 

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 257
100.0%

Length

2023-12-12T08:35:37.503855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:35:37.586766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 257
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
용인시 처인구
94 
용인시 기흥구
82 
용인시 수지구
81 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용인시 처인구
2nd row용인시 처인구
3rd row용인시 처인구
4th row용인시 처인구
5th row용인시 처인구

Common Values

ValueCountFrequency (%)
용인시 처인구 94
36.6%
용인시 기흥구 82
31.9%
용인시 수지구 81
31.5%

Length

2023-12-12T08:35:37.676226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:35:37.759871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인시 257
50.0%
처인구 94
 
18.3%
기흥구 82
 
16.0%
수지구 81
 
15.8%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
41461
94 
41463
82 
41465
81 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41461
2nd row41461
3rd row41461
4th row41461
5th row41461

Common Values

ValueCountFrequency (%)
41461 94
36.6%
41463 82
31.9%
41465 81
31.5%

Length

2023-12-12T08:35:37.858541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:35:37.944628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41461 94
36.6%
41463 82
31.9%
41465 81
31.5%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2021
257 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 257
100.0%

Length

2023-12-12T08:35:38.028503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:35:38.108188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 257
100.0%

세목명
Categorical

Distinct14
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
자동차세
33 
재산세
33 
주민세
33 
등록면허세
33 
지방소득세
30 
Other values (9)
95 

Length

Max length7
Median length5
Mean length4.0972763
Min length3

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 33
12.8%
재산세 33
12.8%
주민세 33
12.8%
등록면허세 33
12.8%
지방소득세 30
11.7%
취득세 30
11.7%
지역자원시설세 23
8.9%
면허세 14
5.4%
등록세 11
 
4.3%
종합토지세 9
 
3.5%
Other values (4) 8
 
3.1%

Length

2023-12-12T08:35:38.204036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차세 33
12.8%
재산세 33
12.8%
주민세 33
12.8%
등록면허세 33
12.8%
지방소득세 30
11.7%
취득세 30
11.7%
지역자원시설세 23
8.9%
면허세 14
5.4%
등록세 11
 
4.3%
종합토지세 9
 
3.5%
Other values (4) 8
 
3.1%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
ARS
45 
가상계좌
34 
기타
31 
지자체방문
26 
자동화기기
23 
Other values (5)
98 

Length

Max length5
Median length4
Mean length3.8404669
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ARS 45
17.5%
가상계좌 34
13.2%
기타 31
12.1%
지자체방문 26
10.1%
자동화기기 23
8.9%
위택스 23
8.9%
은행창구 23
8.9%
인터넷지로 22
8.6%
페이사납부 18
 
7.0%
자동이체 12
 
4.7%

Length

2023-12-12T08:35:38.340089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:35:38.442604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ars 45
17.5%
가상계좌 34
13.2%
기타 31
12.1%
지자체방문 26
10.1%
자동화기기 23
8.9%
위택스 23
8.9%
은행창구 23
8.9%
인터넷지로 22
8.6%
페이사납부 18
 
7.0%
자동이체 12
 
4.7%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size389.0 B
False
130 
True
127 
ValueCountFrequency (%)
False 130
50.6%
True 127
49.4%
2023-12-12T08:35:38.548056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct212
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12056.342
Minimum1
Maximum173745
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T08:35:38.654971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q128
median2901
Q310218
95-th percentile61195.2
Maximum173745
Range173744
Interquartile range (IQR)10190

Descriptive statistics

Standard deviation26674.041
Coefficient of variation (CV)2.2124489
Kurtosis15.964221
Mean12056.342
Median Absolute Deviation (MAD)2892
Skewness3.8021226
Sum3098480
Variance7.1150446 × 108
MonotonicityNot monotonic
2023-12-12T08:35:39.021871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 11
 
4.3%
1 9
 
3.5%
3 6
 
2.3%
14 4
 
1.6%
7 3
 
1.2%
6 3
 
1.2%
4 3
 
1.2%
67 2
 
0.8%
5 2
 
0.8%
21 2
 
0.8%
Other values (202) 212
82.5%
ValueCountFrequency (%)
1 9
3.5%
2 11
4.3%
3 6
2.3%
4 3
 
1.2%
5 2
 
0.8%
6 3
 
1.2%
7 3
 
1.2%
9 2
 
0.8%
10 1
 
0.4%
11 2
 
0.8%
ValueCountFrequency (%)
173745 1
0.4%
163802 1
0.4%
151064 1
0.4%
143846 1
0.4%
121556 1
0.4%
118303 1
0.4%
111333 1
0.4%
92488 1
0.4%
85086 1
0.4%
78351 1
0.4%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct257
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.2511807 × 109
Minimum6300
Maximum1.9817492 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T08:35:39.134926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6300
5-th percentile68418
Q13289750
median4.8206056 × 108
Q35.1491409 × 109
95-th percentile4.8553433 × 1010
Maximum1.9817492 × 1011
Range1.9817492 × 1011
Interquartile range (IQR)5.1458511 × 109

Descriptive statistics

Standard deviation2.536772 × 1010
Coefficient of variation (CV)2.7421062
Kurtosis30.302247
Mean9.2511807 × 109
Median Absolute Deviation (MAD)4.8193316 × 108
Skewness5.0681519
Sum2.3775534 × 1012
Variance6.4352122 × 1020
MonotonicityNot monotonic
2023-12-12T08:35:39.255626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26216380 1
 
0.4%
10301623890 1
 
0.4%
49988049140 1
 
0.4%
20120592460 1
 
0.4%
146907039390 1
 
0.4%
2023650 1
 
0.4%
187825311630 1
 
0.4%
13343207490 1
 
0.4%
12165063740 1
 
0.4%
29005596090 1
 
0.4%
Other values (247) 247
96.1%
ValueCountFrequency (%)
6300 1
0.4%
9610 1
0.4%
11540 1
0.4%
11970 1
0.4%
15420 1
0.4%
20080 1
0.4%
24880 1
0.4%
25200 1
0.4%
37080 1
0.4%
37370 1
0.4%
ValueCountFrequency (%)
198174921590 1
0.4%
187825311630 1
0.4%
172547142040 1
0.4%
146907039390 1
0.4%
72248971050 1
0.4%
71714817350 1
0.4%
69049708150 1
0.4%
66078838670 1
0.4%
62488149470 1
0.4%
59179860660 1
0.4%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct170
Distinct (%)66.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.890428
Minimum0
Maximum21.95
Zeros42
Zeros (%)16.3%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T08:35:39.377436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.02
median2.17
Q36.01
95-th percentile14.426
Maximum21.95
Range21.95
Interquartile range (IQR)5.99

Descriptive statistics

Standard deviation4.7919519
Coefficient of variation (CV)1.2317287
Kurtosis1.6854208
Mean3.890428
Median Absolute Deviation (MAD)2.17
Skewness1.4508929
Sum999.84
Variance22.962803
MonotonicityNot monotonic
2023-12-12T08:35:39.487010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 42
 
16.3%
0.01 20
 
7.8%
0.02 8
 
3.1%
0.03 6
 
2.3%
0.04 4
 
1.6%
0.08 2
 
0.8%
4.39 2
 
0.8%
3.25 2
 
0.8%
0.06 2
 
0.8%
3.48 2
 
0.8%
Other values (160) 167
65.0%
ValueCountFrequency (%)
0.0 42
16.3%
0.01 20
7.8%
0.02 8
 
3.1%
0.03 6
 
2.3%
0.04 4
 
1.6%
0.05 2
 
0.8%
0.06 2
 
0.8%
0.07 2
 
0.8%
0.08 2
 
0.8%
0.09 1
 
0.4%
ValueCountFrequency (%)
21.95 1
0.4%
21.89 1
0.4%
19.34 1
0.4%
18.29 1
0.4%
16.75 1
0.4%
16.64 1
0.4%
16.59 1
0.4%
16.53 1
0.4%
15.36 2
0.8%
15.0 1
0.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2021-12-31 00:00:00
Maximum2021-12-31 00:00:00
2023-12-12T08:35:39.572190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:39.647088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T08:35:37.015423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:36.519348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:36.747313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:37.091066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:36.592924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:36.851509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:37.168665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:36.673696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:36.942204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:35:39.704385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
시군구명1.0001.0000.0000.0000.0000.0000.0000.247
자치단체코드1.0001.0000.0000.0000.0000.0000.0000.247
세목명0.0000.0001.0000.0000.0310.0000.2390.488
납부매체0.0000.0000.0001.0000.9890.4370.2900.447
납부매체전자고지여부0.0000.0000.0310.9891.0000.2470.0650.000
납부건수0.0000.0000.0000.4370.2471.0000.5800.566
납부금액0.0000.0000.2390.2900.0650.5801.0000.243
납부매체비율0.2470.2470.4880.4470.0000.5660.2431.000
2023-12-12T08:35:39.805019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명시군구명자치단체코드납부매체전자고지여부납부매체
세목명1.0000.0000.0000.0190.000
시군구명0.0001.0001.0000.0000.000
자치단체코드0.0001.0001.0000.0000.000
납부매체전자고지여부0.0190.0000.0001.0000.894
납부매체0.0000.0000.0000.8941.000
2023-12-12T08:35:39.895879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율시군구명자치단체코드세목명납부매체납부매체전자고지여부
납부건수1.0000.8600.8940.0000.0000.0000.2150.244
납부금액0.8601.0000.7710.0000.0000.0900.1500.071
납부매체비율0.8940.7711.0000.1590.1590.2210.1580.000
시군구명0.0000.0000.1591.0001.0000.0000.0000.000
자치단체코드0.0000.0000.1591.0001.0000.0000.0000.000
세목명0.0000.0900.2210.0000.0001.0000.0000.019
납부매체0.2150.1500.1580.0000.0000.0001.0000.894
납부매체전자고지여부0.2440.0710.0000.0000.0000.0190.8941.000

Missing values

2023-12-12T08:35:37.263894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:35:37.399075image/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
0경기도용인시 처인구414612021등록세자동화기기N33262163800.012021-12-31
1경기도용인시 처인구414612021자동차세자동화기기N2045230455718407.042021-12-31
2경기도용인시 처인구414612021재산세자동화기기N486531602765144016.752021-12-31
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