Overview

Dataset statistics

Number of variables10
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory89.4 B

Variable types

Categorical6
Numeric4

Dataset

Description지방세 체납현황에 관한 정보로서 체납액 규모별 체납건수를 납세자 유형별로 제공합니다. (과세연도, 세목명, 체납액구간, 체납건수, 체납금액 등)
URLhttps://www.data.go.kr/data/15080510/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 체납금액 and 2 other fieldsHigh correlation
체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
누적체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:46:24.327409
Analysis finished2023-12-11 22:46:26.670846
Duration2.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
광주광역시
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주광역시 39
100.0%

Length

2023-12-12T07:46:26.725722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:46:26.860049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 39
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
광산구
39 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광산구 39
100.0%

Length

2023-12-12T07:46:26.997768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:46:27.090447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광산구 39
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
29200
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row29200
2nd row29200
3rd row29200
4th row29200
5th row29200

Common Values

ValueCountFrequency (%)
29200 39
100.0%

Length

2023-12-12T07:46:27.188128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:46:27.291146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
29200 39
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
2021
39 

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 39
100.0%

Length

2023-12-12T07:46:27.409674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:46:27.510299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 39
100.0%

세목명
Categorical

Distinct7
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size444.0 B
재산세
9 
지방소득세
9 
취득세
8 
주민세
5 
자동차세
4 
Other values (2)
4 

Length

Max length7
Median length3
Mean length3.9230769
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 9
23.1%
지방소득세 9
23.1%
취득세 8
20.5%
주민세 5
12.8%
자동차세 4
10.3%
지역자원시설세 3
 
7.7%
등록면허세 1
 
2.6%

Length

2023-12-12T07:46:27.614224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:46:27.759057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 9
23.1%
지방소득세 9
23.1%
취득세 8
20.5%
주민세 5
12.8%
자동차세 4
10.3%
지역자원시설세 3
 
7.7%
등록면허세 1
 
2.6%

체납액구간
Categorical

Distinct10
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
10만원 미만
7 
10만원~30만원미만
6 
50만원~1백만원미만
6 
30만원~50만원미만
5 
1백만원~3백만원미만
4 
Other values (5)
11 

Length

Max length11
Median length11
Mean length10.25641
Min length7

Unique

Unique2 ?
Unique (%)5.1%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 7
17.9%
10만원~30만원미만 6
15.4%
50만원~1백만원미만 6
15.4%
30만원~50만원미만 5
12.8%
1백만원~3백만원미만 4
10.3%
1천만원~3천만원미만 3
7.7%
3백만원~5백만원미만 3
7.7%
5백만원~1천만원미만 3
7.7%
5천만원~1억원미만 1
 
2.6%
3천만원~5천만원미만 1
 
2.6%

Length

2023-12-12T07:46:27.932975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:46:28.107474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 7
15.2%
미만 7
15.2%
10만원~30만원미만 6
13.0%
50만원~1백만원미만 6
13.0%
30만원~50만원미만 5
10.9%
1백만원~3백만원미만 4
8.7%
1천만원~3천만원미만 3
6.5%
3백만원~5백만원미만 3
6.5%
5백만원~1천만원미만 3
6.5%
5천만원~1억원미만 1
 
2.2%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1188.9231
Minimum1
Maximum18679
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T07:46:28.264224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q111
median29
Q3327
95-th percentile6061.8
Maximum18679
Range18678
Interquartile range (IQR)316

Descriptive statistics

Standard deviation3324.0573
Coefficient of variation (CV)2.7958557
Kurtosis20.770551
Mean1188.9231
Median Absolute Deviation (MAD)27
Skewness4.2600623
Sum46368
Variance11049357
MonotonicityNot monotonic
2023-12-12T07:46:28.410650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2 4
 
10.3%
1 3
 
7.7%
12 2
 
5.1%
17 2
 
5.1%
10 2
 
5.1%
1308 1
 
2.6%
224 1
 
2.6%
560 1
 
2.6%
193 1
 
2.6%
225 1
 
2.6%
Other values (21) 21
53.8%
ValueCountFrequency (%)
1 3
7.7%
2 4
10.3%
8 1
 
2.6%
10 2
5.1%
12 2
5.1%
14 1
 
2.6%
16 1
 
2.6%
17 2
5.1%
18 1
 
2.6%
19 1
 
2.6%
ValueCountFrequency (%)
18679 1
2.6%
6159 1
2.6%
6051 1
2.6%
5238 1
2.6%
4322 1
2.6%
1641 1
2.6%
1308 1
2.6%
563 1
2.6%
560 1
2.6%
429 1
2.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4616134 × 108
Minimum103300
Maximum1.0624745 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T07:46:28.581992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum103300
5-th percentile640056
Q111658495
median86346580
Q31.7378834 × 108
95-th percentile5.2358944 × 108
Maximum1.0624745 × 109
Range1.0623712 × 109
Interquartile range (IQR)1.6212984 × 108

Descriptive statistics

Standard deviation2.2427109 × 108
Coefficient of variation (CV)1.5344078
Kurtosis9.6177087
Mean1.4616134 × 108
Median Absolute Deviation (MAD)75065700
Skewness2.9730263
Sum5.7002922 × 109
Variance5.0297524 × 1016
MonotonicityNot monotonic
2023-12-12T07:46:28.747060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
44953290 1
 
2.6%
251461310 1
 
2.6%
152398890 1
 
2.6%
86346580 1
 
2.6%
133300810 1
 
2.6%
74931450 1
 
2.6%
157431610 1
 
2.6%
207401470 1
 
2.6%
419880 1
 
2.6%
103300 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
103300 1
2.6%
419880 1
2.6%
664520 1
2.6%
716000 1
2.6%
1918150 1
2.6%
4037040 1
2.6%
4440180 1
2.6%
6529930 1
2.6%
11248070 1
2.6%
11280880 1
2.6%
ValueCountFrequency (%)
1062474480 1
2.6%
905347420 1
2.6%
481171890 1
2.6%
309685070 1
2.6%
251461310 1
2.6%
228211530 1
2.6%
217009100 1
2.6%
207401470 1
2.6%
206495470 1
2.6%
190145060 1
2.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2083.2564
Minimum1
Maximum33933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T07:46:28.865889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q118
median36
Q3507
95-th percentile10101
Maximum33933
Range33932
Interquartile range (IQR)489

Descriptive statistics

Standard deviation6047.6041
Coefficient of variation (CV)2.9029572
Kurtosis20.911478
Mean2083.2564
Median Absolute Deviation (MAD)34
Skewness4.2902989
Sum81247
Variance36573516
MonotonicityNot monotonic
2023-12-12T07:46:28.982775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2 4
 
10.3%
1 3
 
7.7%
33 2
 
5.1%
1714 1
 
2.6%
320 1
 
2.6%
710 1
 
2.6%
282 1
 
2.6%
10 1
 
2.6%
274 1
 
2.6%
37 1
 
2.6%
Other values (23) 23
59.0%
ValueCountFrequency (%)
1 3
7.7%
2 4
10.3%
10 1
 
2.6%
12 1
 
2.6%
16 1
 
2.6%
20 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
ValueCountFrequency (%)
33933 1
2.6%
12621 1
2.6%
9821 1
2.6%
8748 1
2.6%
8110 1
2.6%
2155 1
2.6%
1714 1
2.6%
760 1
2.6%
710 1
2.6%
694 1
2.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2955751 × 108
Minimum103300
Maximum2.1991107 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T07:46:29.122504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum103300
5-th percentile702509
Q118014515
median1.0701282 × 108
Q32.3987277 × 108
95-th percentile7.7923386 × 108
Maximum2.1991107 × 109
Range2.1990074 × 109
Interquartile range (IQR)2.2185826 × 108

Descriptive statistics

Standard deviation4.1318768 × 108
Coefficient of variation (CV)1.799931
Kurtosis14.615124
Mean2.2955751 × 108
Median Absolute Deviation (MAD)93636920
Skewness3.5931033
Sum8.9527427 × 109
Variance1.7072406 × 1017
MonotonicityNot monotonic
2023-12-12T07:46:29.310831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
58110160 1
 
2.6%
414799310 1
 
2.6%
152398890 1
 
2.6%
107012820 1
 
2.6%
140287320 1
 
2.6%
74931450 1
 
2.6%
224262170 1
 
2.6%
219362810 1
 
2.6%
581090 1
 
2.6%
103300 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
103300 1
2.6%
581090 1
2.6%
716000 1
2.6%
1274400 1
2.6%
2622150 1
2.6%
4440180 1
2.6%
4746620 1
2.6%
14359090 1
2.6%
16103200 1
2.6%
17614780 1
2.6%
ValueCountFrequency (%)
2199110660 1
2.6%
1379422420 1
2.6%
712546240 1
2.6%
509223850 1
2.6%
449359880 1
2.6%
414799310 1
2.6%
345253400 1
2.6%
315604800 1
2.6%
264121720 1
2.6%
255483370 1
2.6%

Interactions

2023-12-12T07:46:26.066977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:24.662943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:25.077716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:25.725611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:26.144465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:24.786658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:25.197400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:25.806466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:26.243226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:24.879693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:25.542181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:25.904155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:26.337268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:24.963068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:25.635158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:46:25.989355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:46:29.405418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.5120.4410.3110.158
체납액구간0.0001.0000.0000.0000.0000.000
체납건수0.5120.0001.0000.9230.9910.924
체납금액0.4410.0000.9231.0000.9650.991
누적체납건수0.3110.0000.9910.9651.0000.978
누적체납금액0.1580.0000.9240.9910.9781.000
2023-12-12T07:46:29.520217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간
세목명1.0000.000
체납액구간0.0001.000
2023-12-12T07:46:29.619367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.6460.9820.6690.3560.000
체납금액0.6461.0000.6410.9850.2800.000
누적체납건수0.9820.6411.0000.6850.1990.000
누적체납금액0.6690.9850.6851.0000.1010.000
세목명0.3560.2800.1990.1011.0000.000
체납액구간0.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T07:46:26.441567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:46:26.610253image/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
0광주광역시광산구292002021등록면허세10만원 미만130844953290171458110160
1광주광역시광산구292002021자동차세10만원 미만61592514613109821414799310
2광주광역시광산구292002021자동차세10만원~30만원미만60511062474480126212199110660
3광주광역시광산구292002021자동차세30만원~50만원미만429149332510760264121720
4광주광역시광산구292002021자동차세50만원~1백만원미만1265299303016103200
5광주광역시광산구292002021재산세10만원 미만43221901450608748345253400
6광주광역시광산구292002021재산세10만원~30만원미만523890534742081101379422420
7광주광역시광산구292002021재산세1백만원~3백만원미만128217009100185315604800
8광주광역시광산구292002021재산세1천만원~3천만원미만1422821153033509223850
9광주광역시광산구292002021재산세30만원~50만원미만563206495470694255483370
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
29광주광역시광산구292002021지역자원시설세10만원~30만원미만11033001103300
30광주광역시광산구292002021지역자원시설세50만원~1백만원미만17160001716000
31광주광역시광산구292002021취득세10만원 미만19664520331274400
32광주광역시광산구292002021취득세10만원~30만원미만121918150162622150
33광주광역시광산구292002021취득세1백만원~3백만원미만17311677902440845050
34광주광역시광산구292002021취득세1천만원~3천만원미만238748440238748440
35광주광역시광산구292002021취득세30만원~50만원미만104037040124746620
36광주광역시광산구292002021취득세3백만원~5백만원미만1444018014440180
37광주광역시광산구292002021취득세50만원~1백만원미만16112480702014359090
38광주광역시광산구292002021취득세5백만원~1천만원미만218414250218414250