Overview

Dataset statistics

Number of variables10
Number of observations124
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.5 KiB
Average record size in memory87.0 B

Variable types

Categorical6
Numeric4

Dataset

Description3년간(2020~2022) 체납액 규모별 체납 건수를 납세자 유형별로 제공하는 데이터로 구간별 체납건수 및 체납금액과 누적 체납액 등을 제공합니다.
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15126704/fileData.do

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
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-04-21 09:31:18.169410
Analysis finished2024-04-21 09:31:23.275300
Duration5.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
전라남도
124 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 124
100.0%

Length

2024-04-21T18:31:23.471766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:31:23.775535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 124
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
나주시
124 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나주시 124
100.0%

Length

2024-04-21T18:31:24.088132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:31:24.388011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나주시 124
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
46170
124 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46170
2nd row46170
3rd row46170
4th row46170
5th row46170

Common Values

ValueCountFrequency (%)
46170 124
100.0%

Length

2024-04-21T18:31:24.704672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:31:25.004176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46170 124
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2022
43 
2020
41 
2021
40 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2022 43
34.7%
2020 41
33.1%
2021 40
32.3%

Length

2024-04-21T18:31:25.321917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:31:25.636183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 43
34.7%
2020 41
33.1%
2021 40
32.3%

세목명
Categorical

Distinct7
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
지방소득세
31 
취득세
30 
재산세
29 
주민세
15 
자동차세
12 
Other values (2)
7 

Length

Max length7
Median length3
Mean length3.7419355
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 31
25.0%
취득세 30
24.2%
재산세 29
23.4%
주민세 15
12.1%
자동차세 12
 
9.7%
등록면허세 5
 
4.0%
지역자원시설세 2
 
1.6%

Length

2024-04-21T18:31:26.032385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:31:26.403309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 31
25.0%
취득세 30
24.2%
재산세 29
23.4%
주민세 15
12.1%
자동차세 12
 
9.7%
등록면허세 5
 
4.0%
지역자원시설세 2
 
1.6%

체납액구간
Categorical

Distinct12
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
10만원 미만
20 
10만원~30만원미만
15 
30만원~50만원미만
15 
50만원~1백만원미만
15 
1백만원~3백만원미만
14 
Other values (7)
45 

Length

Max length11
Median length11
Mean length10.217742
Min length7

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row10만원 미만
2nd row1백만원~3백만원미만
3rd row10만원 미만
4th row10만원~30만원미만
5th row30만원~50만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 20
16.1%
10만원~30만원미만 15
12.1%
30만원~50만원미만 15
12.1%
50만원~1백만원미만 15
12.1%
1백만원~3백만원미만 14
11.3%
1천만원~3천만원미만 9
7.3%
3백만원~5백만원미만 9
7.3%
5백만원~1천만원미만 9
7.3%
5천만원~1억원미만 7
 
5.6%
3천만원~5천만원미만 6
 
4.8%
Other values (2) 5
 
4.0%

Length

2024-04-21T18:31:26.840238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 20
13.9%
미만 20
13.9%
10만원~30만원미만 15
10.4%
30만원~50만원미만 15
10.4%
50만원~1백만원미만 15
10.4%
1백만원~3백만원미만 14
9.7%
1천만원~3천만원미만 9
6.2%
3백만원~5백만원미만 9
6.2%
5백만원~1천만원미만 9
6.2%
5천만원~1억원미만 7
 
4.9%
Other values (3) 11
7.6%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean479.34677
Minimum1
Maximum7390
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-21T18:31:27.236035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median15.5
Q3130
95-th percentile2213.1
Maximum7390
Range7389
Interquartile range (IQR)127

Descriptive statistics

Standard deviation1393.9678
Coefficient of variation (CV)2.908057
Kurtosis15.194048
Mean479.34677
Median Absolute Deviation (MAD)14
Skewness3.8985712
Sum59439
Variance1943146.1
MonotonicityNot monotonic
2024-04-21T18:31:27.669688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 12
 
9.7%
2 11
 
8.9%
3 9
 
7.3%
10 5
 
4.0%
4 5
 
4.0%
6 4
 
3.2%
12 4
 
3.2%
5 3
 
2.4%
9 2
 
1.6%
26 2
 
1.6%
Other values (60) 67
54.0%
ValueCountFrequency (%)
1 12
9.7%
2 11
8.9%
3 9
7.3%
4 5
4.0%
5 3
 
2.4%
6 4
 
3.2%
8 2
 
1.6%
9 2
 
1.6%
10 5
4.0%
11 1
 
0.8%
ValueCountFrequency (%)
7390 1
0.8%
7360 1
0.8%
7267 1
0.8%
5174 1
0.8%
5142 1
0.8%
5086 1
0.8%
2274 1
0.8%
1868 1
0.8%
1827 1
0.8%
1592 1
0.8%

체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct123
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81582907
Minimum3640
Maximum4.28014 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-21T18:31:28.095554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3640
5-th percentile1042870
Q18868447.5
median54381260
Q31.2629649 × 108
95-th percentile2.4220487 × 108
Maximum4.28014 × 108
Range4.2801036 × 108
Interquartile range (IQR)1.1742804 × 108

Descriptive statistics

Standard deviation86456199
Coefficient of variation (CV)1.0597342
Kurtosis1.3794176
Mean81582907
Median Absolute Deviation (MAD)48475985
Skewness1.2558331
Sum1.011628 × 1010
Variance7.4746743 × 1015
MonotonicityNot monotonic
2024-04-21T18:31:28.529172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1042870 2
 
1.6%
8743100 1
 
0.8%
12241560 1
 
0.8%
101878690 1
 
0.8%
140551520 1
 
0.8%
204177510 1
 
0.8%
235522820 1
 
0.8%
266063020 1
 
0.8%
205849820 1
 
0.8%
133734610 1
 
0.8%
Other values (113) 113
91.1%
ValueCountFrequency (%)
3640 1
0.8%
5760 1
0.8%
340340 1
0.8%
501510 1
0.8%
525670 1
0.8%
765080 1
0.8%
1042870 2
1.6%
1197790 1
0.8%
1241900 1
0.8%
1552790 1
0.8%
ValueCountFrequency (%)
428014000 1
0.8%
317182390 1
0.8%
280111260 1
0.8%
274695020 1
0.8%
266063020 1
0.8%
261201890 1
0.8%
243384050 1
0.8%
235522820 1
0.8%
231285320 1
0.8%
230875490 1
0.8%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1069
Minimum1
Maximum16385
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-21T18:31:28.930456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median28
Q3281.25
95-th percentile5555
Maximum16385
Range16384
Interquartile range (IQR)274.25

Descriptive statistics

Standard deviation3086.3946
Coefficient of variation (CV)2.8871792
Kurtosis13.931313
Mean1069
Median Absolute Deviation (MAD)26
Skewness3.7325691
Sum132556
Variance9525831.3
MonotonicityNot monotonic
2024-04-21T18:31:29.561630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 7
 
5.6%
1 6
 
4.8%
5 5
 
4.0%
4 5
 
4.0%
3 4
 
3.2%
10 3
 
2.4%
13 3
 
2.4%
15 3
 
2.4%
7 3
 
2.4%
12 2
 
1.6%
Other values (70) 83
66.9%
ValueCountFrequency (%)
1 6
4.8%
2 7
5.6%
3 4
3.2%
4 5
4.0%
5 5
4.0%
6 2
 
1.6%
7 3
2.4%
8 1
 
0.8%
9 2
 
1.6%
10 3
2.4%
ValueCountFrequency (%)
16385 1
0.8%
15900 1
0.8%
15512 1
0.8%
12151 1
0.8%
11170 1
0.8%
10109 1
0.8%
5588 1
0.8%
5368 1
0.8%
5165 1
0.8%
4892 1
0.8%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4485244 × 108
Minimum5760
Maximum8.8901293 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-21T18:31:29.982495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5760
5-th percentile2326166
Q122008205
median1.0419122 × 108
Q32.1194582 × 108
95-th percentile3.8586569 × 108
Maximum8.8901293 × 108
Range8.8900717 × 108
Interquartile range (IQR)1.8993762 × 108

Descriptive statistics

Standard deviation1.6250653 × 108
Coefficient of variation (CV)1.1218764
Kurtosis6.0123426
Mean1.4485244 × 108
Median Absolute Deviation (MAD)91155495
Skewness2.1021997
Sum1.7961702 × 1010
Variance2.6408372 × 1016
MonotonicityNot monotonic
2024-04-21T18:31:30.411828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21889840 1
 
0.8%
34445880 1
 
0.8%
153914620 1
 
0.8%
212652250 1
 
0.8%
301471460 1
 
0.8%
235522820 1
 
0.8%
527968700 1
 
0.8%
330810320 1
 
0.8%
241575100 1
 
0.8%
9171820 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
5760 1
0.8%
24850 1
0.8%
1042870 1
0.8%
1552790 1
0.8%
2029180 1
0.8%
2085740 1
0.8%
2231750 1
0.8%
2861190 1
0.8%
3664750 1
0.8%
4031900 1
0.8%
ValueCountFrequency (%)
889012930 1
0.8%
797413620 1
0.8%
776095070 1
0.8%
571200590 1
0.8%
527968700 1
0.8%
457657190 1
0.8%
386175780 1
0.8%
384108490 1
0.8%
364807120 1
0.8%
330810320 1
0.8%

Interactions

2024-04-21T18:31:21.553781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:18.619194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:19.610651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:20.566502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:21.809340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:18.873966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:19.862095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:20.825699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:22.039748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:19.115409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:20.091532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:21.064761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:22.285339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:19.369714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:20.336547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:31:21.315328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T18:31:30.675158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.6970.5150.6910.474
체납액구간0.0000.0001.0000.2140.7640.2500.503
체납건수0.0000.6970.2141.0000.6160.9960.654
체납금액0.0000.5150.7640.6161.0000.6240.960
누적체납건수0.0000.6910.2500.9960.6241.0000.744
누적체납금액0.0000.4740.5030.6540.9600.7441.000
2024-04-21T18:31:30.957038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.000
세목명0.0000.0001.000
2024-04-21T18:31:31.213011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.3280.9800.4040.0000.3070.099
체납금액0.3281.0000.2490.9660.0000.3020.450
누적체납건수0.9800.2491.0000.3550.0000.3020.118
누적체납금액0.4040.9660.3551.0000.0000.2730.236
과세년도0.0000.0000.0000.0001.0000.0000.000
세목명0.3070.3020.3020.2730.0001.0000.000
체납액구간0.0990.4500.1180.2360.0000.0001.000

Missing values

2024-04-21T18:31:22.620864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T18:31:23.093285image/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
0전라남도나주시461702020등록면허세10만원 미만4798743100117221889840
1전라남도나주시461702020등록면허세1백만원~3백만원미만1104287011042870
2전라남도나주시461702020자동차세10만원 미만1868781350605588234585280
3전라남도나주시461702020자동차세10만원~30만원미만15922801112605165889012930
4전라남도나주시461702020자동차세30만원~50만원미만1013606221027494453590
5전라남도나주시461702020자동차세50만원~1백만원미만42530640106048350
6전라남도나주시461702020재산세10만원 미만517412374217012151262780540
7전라남도나주시461702020재산세10만원~30만원미만13252312853202139364807120
8전라남도나주시461702020재산세1백만원~3백만원미만129204647730182286963140
9전라남도나주시461702020재산세1천만원~3천만원미만46861812012194086240
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
114전라남도나주시461702022취득세10만원 미만12501510542861190
115전라남도나주시461702022취득세10만원~30만원미만61197790315681460
116전라남도나주시461702022취득세1백만원~3백만원미만8174089002040382490
117전라남도나주시461702022취득세1천만원~3천만원미만3460708307112843570
118전라남도나주시461702022취득세30만원~50만원미만3124190052029180
119전라남도나주시461702022취득세3백만원~5백만원미만417259470522047660
120전라남도나주시461702022취득세3억원~5억원미만13171823901317182390
121전라남도나주시461702022취득세50만원~1백만원미만1067474601913207320
122전라남도나주시461702022취득세5백만원~1천만원미만316622050750154960
123전라남도나주시461702022취득세5천만원~1억원미만1746757903207241440