Overview

Dataset statistics

Number of variables11
Number of observations83
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.7 KiB
Average record size in memory95.6 B

Variable types

Categorical6
Numeric4
DateTime1

Dataset

Description지방세 체납 현황 과세년도 2017~2019에 대한 지방세 세목별 체납금액, 체납건수, 누적체납건수, 누적체납금액 등에 대한 자료
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=346&beforeMenuCd=DOM_000000201001001000&publicdatapk=15080741

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-01-09 23:15:19.982104
Analysis finished2024-01-09 23:15:21.864701
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
충청남도
83 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 83
100.0%

Length

2024-01-10T08:15:21.920803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:15:22.006793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 83
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
공주시
83 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공주시 83
100.0%

Length

2024-01-10T08:15:22.100907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:15:22.192242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공주시 83
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
44150
83 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44150
2nd row44150
3rd row44150
4th row44150
5th row44150

Common Values

ValueCountFrequency (%)
44150 83
100.0%

Length

2024-01-10T08:15:22.290491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:15:22.381381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44150 83
100.0%

과세년도
Categorical

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size796.0 B
2019
32 
2018
28 
2017
23 

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 (%)
2019 32
38.6%
2018 28
33.7%
2017 23
27.7%

Length

2024-01-10T08:15:22.468346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:15:22.559621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 32
38.6%
2018 28
33.7%
2017 23
27.7%

세목명
Categorical

Distinct7
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size796.0 B
재산세
21 
지방소득세
20 
취득세
12 
주민세
11 
자동차세
10 
Other values (2)

Length

Max length7
Median length3
Mean length3.9638554
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 21
25.3%
지방소득세 20
24.1%
취득세 12
14.5%
주민세 11
13.3%
자동차세 10
12.0%
지역자원시설세 6
 
7.2%
등록면허세 3
 
3.6%

Length

2024-01-10T08:15:22.694256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:15:22.840996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 21
25.3%
지방소득세 20
24.1%
취득세 12
14.5%
주민세 11
13.3%
자동차세 10
12.0%
지역자원시설세 6
 
7.2%
등록면허세 3
 
3.6%

체납액구간
Categorical

Distinct10
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
10만원 미만
17 
10만원~30만원미만
13 
50만원~1백만원미만
13 
1백만원~3백만원미만
12 
30만원~50만원미만
10 
Other values (5)
18 

Length

Max length11
Median length11
Mean length10.168675
Min length7

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row50만원~1백만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 17
20.5%
10만원~30만원미만 13
15.7%
50만원~1백만원미만 13
15.7%
1백만원~3백만원미만 12
14.5%
30만원~50만원미만 10
12.0%
3백만원~5백만원미만 7
8.4%
5백만원~1천만원미만 6
 
7.2%
1천만원~3천만원미만 2
 
2.4%
3천만원~5천만원미만 2
 
2.4%
5천만원~1억원미만 1
 
1.2%

Length

2024-01-10T08:15:23.009407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:15:23.140601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 17
17.0%
미만 17
17.0%
10만원~30만원미만 13
13.0%
50만원~1백만원미만 13
13.0%
1백만원~3백만원미만 12
12.0%
30만원~50만원미만 10
10.0%
3백만원~5백만원미만 7
7.0%
5백만원~1천만원미만 6
 
6.0%
1천만원~3천만원미만 2
 
2.0%
3천만원~5천만원미만 2
 
2.0%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163.61446
Minimum1
Maximum2421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2024-01-10T08:15:23.274853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median8
Q351
95-th percentile1071.6
Maximum2421
Range2420
Interquartile range (IQR)50

Descriptive statistics

Standard deviation411.78958
Coefficient of variation (CV)2.5168288
Kurtosis13.180629
Mean163.61446
Median Absolute Deviation (MAD)7
Skewness3.4553651
Sum13580
Variance169570.65
MonotonicityNot monotonic
2024-01-10T08:15:23.696218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 22
26.5%
2 5
 
6.0%
3 4
 
4.8%
6 4
 
4.8%
5 2
 
2.4%
9 2
 
2.4%
10 2
 
2.4%
12 2
 
2.4%
29 2
 
2.4%
4 2
 
2.4%
Other values (35) 36
43.4%
ValueCountFrequency (%)
1 22
26.5%
2 5
 
6.0%
3 4
 
4.8%
4 2
 
2.4%
5 2
 
2.4%
6 4
 
4.8%
7 1
 
1.2%
8 2
 
2.4%
9 2
 
2.4%
10 2
 
2.4%
ValueCountFrequency (%)
2421 1
1.2%
1651 1
1.2%
1415 1
1.2%
1134 1
1.2%
1084 1
1.2%
960 1
1.2%
800 1
1.2%
793 1
1.2%
537 1
1.2%
467 1
1.2%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17286993
Minimum37340
Maximum1.8680479 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2024-01-10T08:15:23.821975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37340
5-th percentile385861
Q12324205
median7102140
Q320406110
95-th percentile55991922
Maximum1.8680479 × 108
Range1.8676745 × 108
Interquartile range (IQR)18081905

Descriptive statistics

Standard deviation27564458
Coefficient of variation (CV)1.5945201
Kurtosis18.415442
Mean17286993
Median Absolute Deviation (MAD)5996900
Skewness3.7487126
Sum1.4348204 × 109
Variance7.5979933 × 1014
MonotonicityNot monotonic
2024-01-10T08:15:23.954494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
837040 1
 
1.2%
186804790 1
 
1.2%
22650360 1
 
1.2%
18788230 1
 
1.2%
17819080 1
 
1.2%
8576790 1
 
1.2%
51558110 1
 
1.2%
37474470 1
 
1.2%
41624520 1
 
1.2%
16257420 1
 
1.2%
Other values (73) 73
88.0%
ValueCountFrequency (%)
37340 1
1.2%
145470 1
1.2%
177390 1
1.2%
226600 1
1.2%
349810 1
1.2%
710320 1
1.2%
837040 1
1.2%
900180 1
1.2%
1017780 1
1.2%
1043080 1
1.2%
ValueCountFrequency (%)
186804790 1
1.2%
110577280 1
1.2%
92980610 1
1.2%
59456550 1
1.2%
56261030 1
1.2%
53569950 1
1.2%
51558110 1
1.2%
50704850 1
1.2%
41624520 1
1.2%
37474470 1
1.2%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean402.75904
Minimum1
Maximum5678
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2024-01-10T08:15:24.085086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15.5
median16
Q3125.5
95-th percentile2325.2
Maximum5678
Range5677
Interquartile range (IQR)120

Descriptive statistics

Standard deviation1026.0688
Coefficient of variation (CV)2.5475997
Kurtosis12.68326
Mean402.75904
Median Absolute Deviation (MAD)14
Skewness3.4506944
Sum33429
Variance1052817.2
MonotonicityNot monotonic
2024-01-10T08:15:24.207669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 7
 
8.4%
2 6
 
7.2%
6 4
 
4.8%
3 3
 
3.6%
10 3
 
3.6%
1 3
 
3.6%
14 3
 
3.6%
12 2
 
2.4%
5 2
 
2.4%
7 2
 
2.4%
Other values (44) 48
57.8%
ValueCountFrequency (%)
1 3
3.6%
2 6
7.2%
3 3
3.6%
4 7
8.4%
5 2
 
2.4%
6 4
4.8%
7 2
 
2.4%
8 1
 
1.2%
9 2
 
2.4%
10 3
3.6%
ValueCountFrequency (%)
5678 1
1.2%
4860 1
1.2%
3257 1
1.2%
3209 1
1.2%
2353 1
1.2%
2075 1
1.2%
2074 1
1.2%
1842 1
1.2%
1274 1
1.2%
1269 1
1.2%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38619908
Minimum232200
Maximum4.0178192 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2024-01-10T08:15:24.340840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum232200
5-th percentile1059766
Q16935560
median19767410
Q348499780
95-th percentile1.208546 × 108
Maximum4.0178192 × 108
Range4.0154972 × 108
Interquartile range (IQR)41564220

Descriptive statistics

Standard deviation56282383
Coefficient of variation (CV)1.4573412
Kurtosis21.367191
Mean38619908
Median Absolute Deviation (MAD)16749970
Skewness3.9164539
Sum3.2054524 × 109
Variance3.1677067 × 1015
MonotonicityNot monotonic
2024-01-10T08:15:24.483537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2417580 1
 
1.2%
401781920 1
 
1.2%
87642890 1
 
1.2%
46230620 1
 
1.2%
52229900 1
 
1.2%
17184530 1
 
1.2%
99524540 1
 
1.2%
86507600 1
 
1.2%
131981990 1
 
1.2%
36940060 1
 
1.2%
Other values (73) 73
88.0%
ValueCountFrequency (%)
232200 1
1.2%
269540 1
1.2%
648130 1
1.2%
714040 1
1.2%
1008210 1
1.2%
1523770 1
1.2%
2025990 1
1.2%
2117260 1
1.2%
2281780 1
1.2%
2392560 1
1.2%
ValueCountFrequency (%)
401781920 1
1.2%
214977130 1
1.2%
141064240 1
1.2%
131981990 1
1.2%
121996520 1
1.2%
110577280 1
1.2%
99524540 1
1.2%
91391070 1
1.2%
90357470 1
1.2%
90109050 1
1.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
Minimum2019-12-31 00:00:00
Maximum2019-12-31 00:00:00
2024-01-10T08:15:24.595291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:24.673815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T08:15:21.275111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.279949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.585941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.937328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:21.357568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.349755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.663030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:21.017546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:21.460539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.431266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.752004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:21.103004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:21.549479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.500757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:20.830347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:15:21.180598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations