Overview

Dataset statistics

Number of variables10
Number of observations92
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory87.4 B

Variable types

Categorical6
Numeric4

Dataset

Description충청남도 논산시 지방세 체납현황에 대한 데이터로 체납액구간,체납건수,체납금액,누적체납건수,누적체납금액 등의 정보를 제공한다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=351&beforeMenuCd=DOM_000000201001001000&publicdatapk=15079392

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 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 21:32:56.828402
Analysis finished2024-01-09 21:32:58.512657
Duration1.68 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size868.0 B
충청남도
92 

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 92
100.0%

Length

2024-01-10T06:32:58.557668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:58.622499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 92
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size868.0 B
논산시
92 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
논산시 92
100.0%

Length

2024-01-10T06:32:58.689677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:58.753433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
논산시 92
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size868.0 B
44230
92 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44230
2nd row44230
3rd row44230
4th row44230
5th row44230

Common Values

ValueCountFrequency (%)
44230 92
100.0%

Length

2024-01-10T06:32:58.822489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:58.885968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44230 92
100.0%

과세년도
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size868.0 B
2018
33 
2019
33 
2017
26 

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 (%)
2018 33
35.9%
2019 33
35.9%
2017 26
28.3%

Length

2024-01-10T06:32:58.953114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:59.024159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 33
35.9%
2019 33
35.9%
2017 26
28.3%

세목명
Categorical

Distinct7
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size868.0 B
재산세
24 
지방소득세
23 
취득세
13 
자동차세
12 
주민세
12 
Other values (2)
8 

Length

Max length7
Median length3
Mean length3.826087
Min length3

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 24
26.1%
지방소득세 23
25.0%
취득세 13
14.1%
자동차세 12
13.0%
주민세 12
13.0%
등록면허세 7
 
7.6%
지역자원시설세 1
 
1.1%

Length

2024-01-10T06:32:59.113486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:59.204750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 24
26.1%
지방소득세 23
25.0%
취득세 13
14.1%
자동차세 12
13.0%
주민세 12
13.0%
등록면허세 7
 
7.6%
지역자원시설세 1
 
1.1%

체납액구간
Categorical

Distinct10
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size868.0 B
10만원 미만
18 
10만원~30만원미만
16 
50만원~1백만원미만
14 
30만원~50만원미만
11 
1백만원~3백만원미만
10 
Other values (5)
23 

Length

Max length11
Median length11
Mean length10.206522
Min length7

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row10만원 미만
2nd row10만원~30만원미만
3rd row1천만원~3천만원미만
4th row10만원 미만
5th row10만원~30만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 18
19.6%
10만원~30만원미만 16
17.4%
50만원~1백만원미만 14
15.2%
30만원~50만원미만 11
12.0%
1백만원~3백만원미만 10
10.9%
1천만원~3천만원미만 8
8.7%
3백만원~5백만원미만 6
 
6.5%
5백만원~1천만원미만 6
 
6.5%
3천만원~5천만원미만 2
 
2.2%
5천만원~1억원미만 1
 
1.1%

Length

2024-01-10T06:32:59.314673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:59.416334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 18
16.4%
미만 18
16.4%
10만원~30만원미만 16
14.5%
50만원~1백만원미만 14
12.7%
30만원~50만원미만 11
10.0%
1백만원~3백만원미만 10
9.1%
1천만원~3천만원미만 8
7.3%
3백만원~5백만원미만 6
 
5.5%
5백만원~1천만원미만 6
 
5.5%
3천만원~5천만원미만 2
 
1.8%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)48.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean229.81522
Minimum1
Maximum2959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-01-10T06:32:59.525378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.75
median8
Q352.5
95-th percentile1726.4
Maximum2959
Range2958
Interquartile range (IQR)49.75

Descriptive statistics

Standard deviation603.70837
Coefficient of variation (CV)2.6269295
Kurtosis9.8371664
Mean229.81522
Median Absolute Deviation (MAD)7
Skewness3.1970171
Sum21143
Variance364463.8
MonotonicityNot monotonic
2024-01-10T06:32:59.635470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 14
 
15.2%
2 9
 
9.8%
3 8
 
8.7%
4 6
 
6.5%
7 4
 
4.3%
17 3
 
3.3%
11 3
 
3.3%
121 2
 
2.2%
6 2
 
2.2%
8 2
 
2.2%
Other values (35) 39
42.4%
ValueCountFrequency (%)
1 14
15.2%
2 9
9.8%
3 8
8.7%
4 6
6.5%
5 2
 
2.2%
6 2
 
2.2%
7 4
 
4.3%
8 2
 
2.2%
9 2
 
2.2%
10 1
 
1.1%
ValueCountFrequency (%)
2959 1
1.1%
2850 1
1.1%
2204 1
1.1%
2181 1
1.1%
1887 1
1.1%
1595 1
1.1%
1433 1
1.1%
1123 1
1.1%
838 1
1.1%
707 1
1.1%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22294465
Minimum34640
Maximum2.4631652 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-01-10T06:32:59.756786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34640
5-th percentile284001.5
Q13368970
median12612305
Q330389242
95-th percentile63120374
Maximum2.4631652 × 108
Range2.4628188 × 108
Interquartile range (IQR)27020272

Descriptive statistics

Standard deviation33187821
Coefficient of variation (CV)1.4886126
Kurtosis23.721857
Mean22294465
Median Absolute Deviation (MAD)11165170
Skewness4.137036
Sum2.0510908 × 109
Variance1.1014315 × 1015
MonotonicityNot monotonic
2024-01-10T06:32:59.872970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1662190 1
 
1.1%
4088180 1
 
1.1%
18374490 1
 
1.1%
34724960 1
 
1.1%
53158880 1
 
1.1%
45784450 1
 
1.1%
62278280 1
 
1.1%
1689190 1
 
1.1%
25975680 1
 
1.1%
246316520 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
34640 1
1.1%
44370 1
1.1%
138860 1
1.1%
208630 1
1.1%
225740 1
1.1%
331670 1
1.1%
340370 1
1.1%
513320 1
1.1%
529830 1
1.1%
590140 1
1.1%
ValueCountFrequency (%)
246316520 1
1.1%
141757460 1
1.1%
92924700 1
1.1%
75643710 1
1.1%
64149600 1
1.1%
62278280 1
1.1%
55334000 1
1.1%
53158880 1
1.1%
50848120 1
1.1%
49634590 1
1.1%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean753.16304
Minimum1
Maximum10021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-01-10T06:32:59.992518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.55
Q19
median31.5
Q3147.75
95-th percentile4871.85
Maximum10021
Range10020
Interquartile range (IQR)138.75

Descriptive statistics

Standard deviation1943.4525
Coefficient of variation (CV)2.5803874
Kurtosis9.8807316
Mean753.16304
Median Absolute Deviation (MAD)27.5
Skewness3.1354399
Sum69291
Variance3777007.4
MonotonicityNot monotonic
2024-01-10T06:33:00.108827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5
 
5.4%
4 4
 
4.3%
7 3
 
3.3%
20 3
 
3.3%
9 3
 
3.3%
2 2
 
2.2%
5 2
 
2.2%
13 2
 
2.2%
32 2
 
2.2%
14 2
 
2.2%
Other values (56) 64
69.6%
ValueCountFrequency (%)
1 5
5.4%
2 2
 
2.2%
3 2
 
2.2%
4 4
4.3%
5 2
 
2.2%
6 2
 
2.2%
7 3
3.3%
8 2
 
2.2%
9 3
3.3%
10 1
 
1.1%
ValueCountFrequency (%)
10021 1
1.1%
9084 1
1.1%
7171 1
1.1%
6125 1
1.1%
4967 1
1.1%
4794 1
1.1%
4579 1
1.1%
3944 1
1.1%
3671 1
1.1%
3146 1
1.1%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69384998
Minimum62510
Maximum7.7223625 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-01-10T06:33:00.212316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62510
5-th percentile1139954
Q110640202
median35365100
Q381596242
95-th percentile2.2308927 × 108
Maximum7.7223625 × 108
Range7.7217374 × 108
Interquartile range (IQR)70956040

Descriptive statistics

Standard deviation1.1115348 × 108
Coefficient of variation (CV)1.6019815
Kurtosis20.051737
Mean69384998
Median Absolute Deviation (MAD)28864185
Skewness3.9704545
Sum6.3834198 × 109
Variance1.2355096 × 1016
MonotonicityNot monotonic
2024-01-10T06:33:00.334358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3809200 1
 
1.1%
10509410 1
 
1.1%
42372390 1
 
1.1%
82468440 1
 
1.1%
150355540 1
 
1.1%
121908250 1
 
1.1%
222111210 1
 
1.1%
12372990 1
 
1.1%
72280790 1
 
1.1%
772236250 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
62510 1
1.1%
225740 1
1.1%
434370 1
1.1%
795240 1
1.1%
839610 1
1.1%
1385690 1
1.1%
1472510 1
1.1%
3435550 1
1.1%
3809200 1
1.1%
3999960 1
1.1%
ValueCountFrequency (%)
772236250 1
1.1%
525919730 1
1.1%
384162270 1
1.1%
261989210 1
1.1%
224284670 1
1.1%
222111210 1
1.1%
209792760 1
1.1%
168950670 1
1.1%
160158170 1
1.1%
159832930 1
1.1%

Interactions

2024-01-10T06:32:57.975906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.102819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.370455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.634944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:58.065462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.167487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.434831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.717725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:58.157286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.230897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.496994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.803061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:58.252768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.297465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.559342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:57.880518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:33:00.419828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.4530.3560.2230.000
세목명0.0001.0000.0000.2850.3350.4060.241
체납액구간0.0000.0001.0000.0000.3150.0000.328
체납건수0.4530.2850.0001.0000.8440.9570.809
체납금액0.3560.3350.3150.8441.0000.6140.893
누적체납건수0.2230.4060.0000.9570.6141.0000.859
누적체납금액0.0000.2410.3280.8090.8930.8591.000
2024-01-10T06:33:00.504736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.000
세목명0.0000.0001.000
2024-01-10T06:33:00.574535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.4290.9420.4540.2150.1490.000
체납금액0.4291.0000.3240.9400.1420.0740.163
누적체납건수0.9420.3241.0000.4260.1470.1490.000
누적체납금액0.4540.9400.4261.0000.0000.0810.163
과세년도0.2150.1420.1470.0001.0000.0000.000
세목명0.1490.0740.1490.0810.0001.0000.000
체납액구간0.0000.1630.0000.1630.0000.0001.000

Missing values

2024-01-10T06:32:58.363178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:32:58.470797image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
0충청남도논산시442302017등록면허세10만원 미만12116621902583809200
1충청남도논산시442302017등록면허세10만원~30만원미만12257401225740
2충청남도논산시442302017등록면허세1천만원~3천만원미만111387790111387790
3충청남도논산시442302017자동차세10만원 미만537237160302964130013290
4충청남도논산시442302017자동차세10만원~30만원미만549929247002308384162270
5충청남도논산시442302017자동차세30만원~50만원미만2274467009331547010
6충청남도논산시442302017자동차세50만원~1백만원미만422006001610170480
7충청남도논산시442302017재산세10만원 미만1887365969704967116522320
8충청남도논산시442302017재산세10만원~30만원미만841280205034953221240
9충청남도논산시442302017재산세1백만원~3백만원미만11157311305072466770
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
82충청남도논산시442302019지방소득세50만원~1백만원미만31228640808661864110
83충청남도논산시442302019지방소득세5백만원~1천만원미만16934100857908310
84충청남도논산시442302019지방소득세5천만원~1억원미만164149600164149600
85충청남도논산시442302019지역자원시설세10만원 미만434640962510
86충청남도논산시442302019취득세10만원 미만24437020839610
87충청남도논산시442302019취득세10만원~30만원미만5962440244397990
88충청남도논산시442302019취득세1백만원~3백만원미만341495701322946470
89충청남도논산시442302019취득세1천만원~3천만원미만575643710695761160
90충청남도논산시442302019취득세3천만원~5천만원미만139071980270194310
91충청남도논산시442302019취득세50만원~1백만원미만424821001812203970