Overview

Dataset statistics

Number of variables10
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory91.5 B

Variable types

Categorical6
Numeric4

Dataset

Description체납액 규모별 체납 건수를 납세자 유형별(과세년도, 세목명, 체납액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금)에 대하여 설명
URLhttps://www.data.go.kr/data/15078926/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 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 started2023-12-12 06:47:12.281000
Analysis finished2023-12-12 06:47:14.886280
Duration2.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
전라북도
24 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 24
100.0%

Length

2023-12-12T15:47:14.961596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:47:15.079273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 24
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
장수군
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장수군 24
100.0%

Length

2023-12-12T15:47:15.203198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:47:15.307806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장수군 24
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
45740
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45740
2nd row45740
3rd row45740
4th row45740
5th row45740

Common Values

ValueCountFrequency (%)
45740 24
100.0%

Length

2023-12-12T15:47:15.442989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:47:15.560903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45740 24
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2022
24 

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 24
100.0%

Length

2023-12-12T15:47:15.683040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:47:15.792514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 24
100.0%

세목명
Categorical

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
재산세
7 
지방소득세
5 
주민세
4 
취득세
4 
자동차세
3 

Length

Max length5
Median length3
Mean length3.625
Min length3

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 7
29.2%
지방소득세 5
20.8%
주민세 4
16.7%
취득세 4
16.7%
자동차세 3
12.5%
등록면허세 1
 
4.2%

Length

2023-12-12T15:47:15.956001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:47:16.102813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 7
29.2%
지방소득세 5
20.8%
주민세 4
16.7%
취득세 4
16.7%
자동차세 3
12.5%
등록면허세 1
 
4.2%

체납액구간
Categorical

Distinct8
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
10만원 미만
6 
10만원~30만원미만
5 
30만원~50만원미만
3 
1백만원~3백만원미만
3 
50만원~1백만원미만
3 
Other values (3)
4 

Length

Max length11
Median length11
Mean length10
Min length7

Unique

Unique2 ?
Unique (%)8.3%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 6
25.0%
10만원~30만원미만 5
20.8%
30만원~50만원미만 3
12.5%
1백만원~3백만원미만 3
12.5%
50만원~1백만원미만 3
12.5%
1천만원~3천만원미만 2
 
8.3%
5백만원~1천만원미만 1
 
4.2%
3백만원~5백만원미만 1
 
4.2%

Length

2023-12-12T15:47:16.279892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:47:16.449607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 6
20.0%
미만 6
20.0%
10만원~30만원미만 5
16.7%
30만원~50만원미만 3
10.0%
1백만원~3백만원미만 3
10.0%
50만원~1백만원미만 3
10.0%
1천만원~3천만원미만 2
 
6.7%
5백만원~1천만원미만 1
 
3.3%
3백만원~5백만원미만 1
 
3.3%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.541667
Minimum1
Maximum615
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T15:47:16.599404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.75
median4
Q329.75
95-th percentile298.3
Maximum615
Range614
Interquartile range (IQR)28

Descriptive statistics

Standard deviation138.58979
Coefficient of variation (CV)2.5409892
Kurtosis12.546101
Mean54.541667
Median Absolute Deviation (MAD)3
Skewness3.467629
Sum1309
Variance19207.129
MonotonicityNot monotonic
2023-12-12T15:47:16.742425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 6
25.0%
2 3
12.5%
4 2
 
8.3%
6 2
 
8.3%
3 2
 
8.3%
29 1
 
4.2%
130 1
 
4.2%
84 1
 
4.2%
615 1
 
4.2%
35 1
 
4.2%
Other values (4) 4
16.7%
ValueCountFrequency (%)
1 6
25.0%
2 3
12.5%
3 2
 
8.3%
4 2
 
8.3%
6 2
 
8.3%
8 1
 
4.2%
10 1
 
4.2%
29 1
 
4.2%
32 1
 
4.2%
35 1
 
4.2%
ValueCountFrequency (%)
615 1
4.2%
328 1
4.2%
130 1
4.2%
84 1
4.2%
35 1
4.2%
32 1
4.2%
29 1
4.2%
10 1
4.2%
8 1
4.2%
6 2
8.3%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5604803.8
Minimum30050
Maximum22318280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T15:47:16.902896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30050
5-th percentile303353
Q1846817.5
median4861485
Q36997192.5
95-th percentile15097862
Maximum22318280
Range22288230
Interquartile range (IQR)6150375

Descriptive statistics

Standard deviation5733667.5
Coefficient of variation (CV)1.0229917
Kurtosis1.8717803
Mean5604803.8
Median Absolute Deviation (MAD)3910535
Skewness1.3965017
Sum1.3451529 × 108
Variance3.2874943 × 1013
MonotonicityNot monotonic
2023-12-12T15:47:17.045193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
592740 1
 
4.2%
343400 1
 
4.2%
14865650 1
 
4.2%
4031910 1
 
4.2%
298250 1
 
4.2%
30050 1
 
4.2%
4430450 1
 
4.2%
12239530 1
 
4.2%
5292520 1
 
4.2%
2031450 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
30050 1
4.2%
298250 1
4.2%
332270 1
4.2%
343400 1
4.2%
592740 1
4.2%
695730 1
4.2%
897180 1
4.2%
1004720 1
4.2%
2031450 1
4.2%
2427970 1
4.2%
ValueCountFrequency (%)
22318280 1
4.2%
15138840 1
4.2%
14865650 1
4.2%
12239530 1
4.2%
9595310 1
4.2%
7324710 1
4.2%
6888020 1
4.2%
6689540 1
4.2%
6129570 1
4.2%
5511670 1
4.2%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.79167
Minimum1
Maximum1377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T15:47:17.160141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median9
Q353.5
95-th percentile490.15
Maximum1377
Range1376
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation297.59865
Coefficient of variation (CV)2.5481154
Kurtosis14.952401
Mean116.79167
Median Absolute Deviation (MAD)6.5
Skewness3.7029094
Sum2803
Variance88564.955
MonotonicityNot monotonic
2023-12-12T15:47:17.265773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4 5
20.8%
2 3
12.5%
14 2
 
8.3%
9 2
 
8.3%
3 1
 
4.2%
7 1
 
4.2%
12 1
 
4.2%
20 1
 
4.2%
64 1
 
4.2%
1 1
 
4.2%
Other values (6) 6
25.0%
ValueCountFrequency (%)
1 1
 
4.2%
2 3
12.5%
3 1
 
4.2%
4 5
20.8%
7 1
 
4.2%
9 2
 
8.3%
12 1
 
4.2%
14 2
 
8.3%
20 1
 
4.2%
50 1
 
4.2%
ValueCountFrequency (%)
1377 1
4.2%
523 1
4.2%
304 1
4.2%
299 1
4.2%
71 1
4.2%
64 1
4.2%
50 1
4.2%
20 1
4.2%
14 2
8.3%
12 1
4.2%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11264962
Minimum587210
Maximum54079570
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T15:47:17.391065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum587210
5-th percentile709355.5
Q11432600
median7408250
Q314419558
95-th percentile42893977
Maximum54079570
Range53492360
Interquartile range (IQR)12986958

Descriptive statistics

Standard deviation13751736
Coefficient of variation (CV)1.220753
Kurtosis4.3664301
Mean11264962
Median Absolute Deviation (MAD)6106510
Skewness2.0819798
Sum2.7035909 × 108
Variance1.8911025 × 1014
MonotonicityNot monotonic
2023-12-12T15:47:17.534937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1434760 1
 
4.2%
1283030 1
 
4.2%
14865650 1
 
4.2%
5406040 1
 
4.2%
1426120 1
 
4.2%
676210 1
 
4.2%
9838780 1
 
4.2%
25830100 1
 
4.2%
16287810 1
 
4.2%
3887050 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
587210 1
4.2%
676210 1
4.2%
897180 1
4.2%
1283030 1
4.2%
1320450 1
4.2%
1426120 1
4.2%
1434760 1
4.2%
1463320 1
4.2%
3579920 1
4.2%
3887050 1
4.2%
ValueCountFrequency (%)
54079570 1
4.2%
45905250 1
4.2%
25830100 1
4.2%
18116230 1
4.2%
16287810 1
4.2%
14865650 1
4.2%
14270860 1
4.2%
13769860 1
4.2%
10674640 1
4.2%
9942550 1
4.2%

Interactions

2023-12-12T15:47:13.856350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:12.555541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:12.949946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:13.433741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:13.963367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:12.633388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:13.052332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:13.531811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:14.056434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:12.710218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:13.153278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:13.633535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:14.164674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:12.817193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:13.287594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:13.745284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:47:17.629077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.2730.0000.5280.000
체납액구간0.0001.0000.0000.7420.0000.426
체납건수0.2730.0001.0000.6391.0000.792
체납금액0.0000.7420.6391.0000.8400.910
누적체납건수0.5280.0001.0000.8401.0000.772
누적체납금액0.0000.4260.7920.9100.7721.000
2023-12-12T15:47:17.738575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간
세목명1.0000.000
체납액구간0.0001.000
2023-12-12T15:47:17.821335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.2600.9140.3170.1520.000
체납금액0.2601.0000.0530.9320.0000.319
누적체납건수0.9140.0531.0000.1950.3360.000
누적체납금액0.3170.9320.1951.0000.0000.215
세목명0.1520.0000.3360.0001.0000.000
체납액구간0.0000.3190.0000.2150.0001.000

Missing values

2023-12-12T15:47:14.629191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:47:14.823709image/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
0전라북도장수군457402022등록면허세10만원 미만29592740711434760
1전라북도장수군457402022자동차세10만원 미만130612957029914270860
2전라북도장수군457402022자동차세10만원~30만원미만841513884030454079570
3전라북도장수군457402022자동차세30만원~50만원미만269573041320450
4전라북도장수군457402022재산세10만원 미만6159595310137718116230
5전라북도장수군457402022재산세10만원~30만원미만355405530507928480
6전라북도장수군457402022재산세1백만원~3백만원미만4688802046888020
7전라북도장수군457402022재산세1천만원~3천만원미만122318280245905250
8전라북도장수군457402022재산세30만원~50만원미만6242797093579920
9전라북도장수군457402022재산세50만원~1백만원미만85511670149942550
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
14전라북도장수군457402022주민세50만원~1백만원미만18971801897180
15전라북도장수군457402022지방소득세10만원 미만321004720641463320
16전라북도장수군457402022지방소득세10만원~30만원미만102031450203887050
17전라북도장수군457402022지방소득세1백만원~3백만원미만35292520916287810
18전라북도장수군457402022지방소득세1천만원~3천만원미만112239530225830100
19전라북도장수군457402022지방소득세50만원~1백만원미만64430450149838780
20전라북도장수군457402022취득세10만원 미만13005012676210
21전라북도장수군457402022취득세10만원~30만원미만229825071426120
22전라북도장수군457402022취득세1백만원~3백만원미만3403191045406040
23전라북도장수군457402022취득세3백만원~5백만원미만414865650414865650