Overview

Dataset statistics

Number of variables10
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory89.1 B

Variable types

Categorical6
Numeric4

Dataset

Description체납액 규모별 체납 건수를 납세자 유형별로 제공인천광역시 부평구 (시도명, 시군구명, 자치단체코드, 과세년도, 세목명, 체납액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금액)예) 인천광역시, 부평구, 28237, 2017, 등록면허세, 10만원 미만, 589, 20351950, 1949, 64500650
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/15079443/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 started2024-04-29 22:45:50.431332
Analysis finished2024-04-29 22:45:53.643854
Duration3.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
인천광역시
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 42
100.0%

Length

2024-04-30T07:45:53.704084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:45:53.796183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 42
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
부평구
42 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부평구 42
100.0%

Length

2024-04-30T07:45:53.891437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:45:53.988502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부평구 42
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
28237
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28237
2nd row28237
3rd row28237
4th row28237
5th row28237

Common Values

ValueCountFrequency (%)
28237 42
100.0%

Length

2024-04-30T07:45:54.118464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:45:54.215566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28237 42
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
2021
42 

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 42
100.0%

Length

2024-04-30T07:45:54.317023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:45:54.414948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 42
100.0%

세목명
Categorical

Distinct7
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size468.0 B
지방소득세
11 
재산세
9 
취득세
7 
주민세
6 
등록면허세
4 
Other values (2)
5 

Length

Max length7
Median length3
Mean length3.9047619
Min length3

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 11
26.2%
재산세 9
21.4%
취득세 7
16.7%
주민세 6
14.3%
등록면허세 4
 
9.5%
자동차세 4
 
9.5%
지역자원시설세 1
 
2.4%

Length

2024-04-30T07:45:54.546415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:45:54.681963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 11
26.2%
재산세 9
21.4%
취득세 7
16.7%
주민세 6
14.3%
등록면허세 4
 
9.5%
자동차세 4
 
9.5%
지역자원시설세 1
 
2.4%

체납액구간
Categorical

Distinct11
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size468.0 B
10만원 미만
7 
50만원~1백만원미만
6 
5백만원~1천만원미만
5 
10만원~30만원미만
5 
30만원~50만원미만
5 
Other values (6)
14 

Length

Max length11
Median length11
Mean length10.261905
Min length7

Unique

Unique2 ?
Unique (%)4.8%

Sample

1st row10만원 미만
2nd row3백만원~5백만원미만
3rd row50만원~1백만원미만
4th row5백만원~1천만원미만
5th row10만원 미만

Common Values

ValueCountFrequency (%)
10만원 미만 7
16.7%
50만원~1백만원미만 6
14.3%
5백만원~1천만원미만 5
11.9%
10만원~30만원미만 5
11.9%
30만원~50만원미만 5
11.9%
3백만원~5백만원미만 4
9.5%
1백만원~3백만원미만 4
9.5%
1천만원~3천만원미만 2
 
4.8%
3천만원~5천만원미만 2
 
4.8%
1억원~3억원미만 1
 
2.4%

Length

2024-04-30T07:45:54.843737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 7
14.3%
미만 7
14.3%
50만원~1백만원미만 6
12.2%
5백만원~1천만원미만 5
10.2%
10만원~30만원미만 5
10.2%
30만원~50만원미만 5
10.2%
3백만원~5백만원미만 4
8.2%
1백만원~3백만원미만 4
8.2%
1천만원~3천만원미만 2
 
4.1%
3천만원~5천만원미만 2
 
4.1%
Other values (2) 2
 
4.1%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1270.7619
Minimum1
Maximum19077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-30T07:45:55.009516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median24.5
Q3272.75
95-th percentile5255.55
Maximum19077
Range19076
Interquartile range (IQR)265.75

Descriptive statistics

Standard deviation3526.8197
Coefficient of variation (CV)2.7753584
Kurtosis17.078015
Mean1270.7619
Median Absolute Deviation (MAD)23.5
Skewness3.939049
Sum53372
Variance12438457
MonotonicityNot monotonic
2024-04-30T07:45:55.163486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 6
 
14.3%
2 3
 
7.1%
13 2
 
4.8%
20 2
 
4.8%
29 1
 
2.4%
57 1
 
2.4%
14 1
 
2.4%
10 1
 
2.4%
43 1
 
2.4%
2522 1
 
2.4%
Other values (23) 23
54.8%
ValueCountFrequency (%)
1 6
14.3%
2 3
7.1%
3 1
 
2.4%
6 1
 
2.4%
10 1
 
2.4%
11 1
 
2.4%
13 2
 
4.8%
14 1
 
2.4%
15 1
 
2.4%
17 1
 
2.4%
ValueCountFrequency (%)
19077 1
2.4%
11302 1
2.4%
5281 1
2.4%
4772 1
2.4%
4759 1
2.4%
2522 1
2.4%
2183 1
2.4%
832 1
2.4%
803 1
2.4%
303 1
2.4%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5615895 × 108
Minimum87030
Maximum8.3327503 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-30T07:45:55.318506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum87030
5-th percentile3610243
Q16573522.5
median1.0725362 × 108
Q32.0899135 × 108
95-th percentile5.8125201 × 108
Maximum8.3327503 × 108
Range8.33188 × 108
Interquartile range (IQR)2.0241783 × 108

Descriptive statistics

Standard deviation2.0318123 × 108
Coefficient of variation (CV)1.3011181
Kurtosis4.0425894
Mean1.5615895 × 108
Median Absolute Deviation (MAD)1.0071903 × 108
Skewness1.9761998
Sum6.5586759 × 109
Variance4.1282612 × 1016
MonotonicityNot monotonic
2024-04-30T07:45:55.471356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
75651000 1
 
2.4%
281215040 1
 
2.4%
151390780 1
 
2.4%
394945880 1
 
2.4%
127370050 1
 
2.4%
283228670 1
 
2.4%
118312300 1
 
2.4%
238457020 1
 
2.4%
118320200 1
 
2.4%
190767260 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
87030 1
2.4%
798680 1
2.4%
3562640 1
2.4%
4514700 1
2.4%
4643000 1
2.4%
4921820 1
2.4%
5177540 1
2.4%
5373650 1
2.4%
5414960 1
2.4%
6520980 1
2.4%
ValueCountFrequency (%)
833275030 1
2.4%
803519350 1
2.4%
590775040 1
2.4%
400314380 1
2.4%
394945880 1
2.4%
341202970 1
2.4%
300295060 1
2.4%
283228670 1
2.4%
281215040 1
2.4%
238457020 1
2.4%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2046.8095
Minimum1
Maximum22493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-30T07:45:55.775611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q110.75
median49.5
Q3423.5
95-th percentile12524.6
Maximum22493
Range22492
Interquartile range (IQR)412.75

Descriptive statistics

Standard deviation5146.2411
Coefficient of variation (CV)2.5142746
Kurtosis8.2213671
Mean2046.8095
Median Absolute Deviation (MAD)48
Skewness2.9377541
Sum85966
Variance26483798
MonotonicityNot monotonic
2024-04-30T07:45:55.890845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 4
 
9.5%
2 4
 
9.5%
13 2
 
4.8%
65 1
 
2.4%
14 1
 
2.4%
2598 1
 
2.4%
862 1
 
2.4%
244 1
 
2.4%
17 1
 
2.4%
309 1
 
2.4%
Other values (25) 25
59.5%
ValueCountFrequency (%)
1 4
9.5%
2 4
9.5%
3 1
 
2.4%
5 1
 
2.4%
10 1
 
2.4%
13 2
4.8%
14 1
 
2.4%
15 1
 
2.4%
17 1
 
2.4%
26 1
 
2.4%
ValueCountFrequency (%)
22493 1
2.4%
19259 1
2.4%
12585 1
2.4%
11377 1
2.4%
8324 1
2.4%
4231 1
2.4%
2598 1
2.4%
1192 1
2.4%
862 1
2.4%
647 1
2.4%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7594744 × 108
Minimum87030
Maximum2.1747421 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-30T07:45:56.015703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum87030
5-th percentile3616658
Q19895800
median1.3314174 × 108
Q33.8067125 × 108
95-th percentile1.0814687 × 109
Maximum2.1747421 × 109
Range2.174655 × 109
Interquartile range (IQR)3.7077545 × 108

Descriptive statistics

Standard deviation4.2192536 × 108
Coefficient of variation (CV)1.5290063
Kurtosis9.8256933
Mean2.7594744 × 108
Median Absolute Deviation (MAD)1.2774744 × 108
Skewness2.8398171
Sum1.1589792 × 1010
Variance1.7802101 × 1017
MonotonicityNot monotonic
2024-04-30T07:45:56.165952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
147269740 1
 
2.4%
281215040 1
 
2.4%
156835880 1
 
2.4%
412987190 1
 
2.4%
127370050 1
 
2.4%
283228670 1
 
2.4%
120781840 1
 
2.4%
246322840 1
 
2.4%
118320200 1
 
2.4%
197584560 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
87030 1
2.4%
1703510 1
2.4%
3562640 1
2.4%
4643000 1
2.4%
4921820 1
2.4%
5177540 1
2.4%
5373650 1
2.4%
5414960 1
2.4%
6548210 1
2.4%
6886870 1
2.4%
ValueCountFrequency (%)
2174742080 1
2.4%
1266140490 1
2.4%
1091227970 1
2.4%
896042550 1
2.4%
593824850 1
2.4%
514966860 1
2.4%
510924520 1
2.4%
446824780 1
2.4%
432191430 1
2.4%
412987190 1
2.4%

Interactions

2024-04-30T07:45:53.101750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:51.968081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.482261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.782425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:53.185940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.103762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.563203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.876605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:53.252042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.312898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.628774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.958298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:53.332648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.392114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:52.705394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:45:53.033437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:45:56.259670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.2660.3770.3500.662
체납액구간0.0001.0000.0000.0000.0000.000
체납건수0.2660.0001.0000.7891.0000.586
체납금액0.3770.0000.7891.0000.7660.781
누적체납건수0.3500.0001.0000.7661.0000.873
누적체납금액0.6620.0000.5860.7810.8731.000
2024-04-30T07:45:56.356460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2024-04-30T07:45:56.443405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.6500.9780.6460.1570.000
체납금액0.6501.0000.6480.9410.1390.000
누적체납건수0.9780.6481.0000.7000.2040.000
누적체납금액0.6460.9410.7001.0000.2440.000
세목명0.1570.1390.2040.2441.0000.000
체납액구간0.0000.0000.0000.0000.0001.000

Missing values

2024-04-30T07:45:53.441051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:45:53.585613image/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
0인천광역시부평구282372021등록면허세10만원 미만2183756510004231147269740
1인천광역시부평구282372021등록면허세3백만원~5백만원미만1464300014643000
2인천광역시부평구282372021등록면허세50만원~1백만원미만179868021703510
3인천광역시부평구282372021등록면허세5백만원~1천만원미만1541496015414960
4인천광역시부평구282372021자동차세10만원 미만477221506605011377510924520
5인천광역시부평구282372021자동차세10만원~30만원미만4759833275030125852174742080
6인천광역시부평구282372021자동차세30만원~50만원미만27396194950647226307740
7인천광역시부평구282372021자동차세50만원~1백만원미만1165209804023364420
8인천광역시부평구282372021재산세10만원 미만11302590775040224931091227970
9인천광역시부평구282372021재산세10만원~30만원미만528180351935083241266140490
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
32인천광역시부평구282372021지방소득세5백만원~1천만원미만4328121504043281215040
33인천광역시부평구282372021지방소득세5천만원~1억원미만21389134302138913430
34인천광역시부평구282372021지역자원시설세10만원 미만13870301387030
35인천광역시부평구282372021취득세10만원 미만573562640573562640
36인천광역시부평구282372021취득세10만원~30만원미만295373650295373650
37인천광역시부평구282372021취득세1백만원~3백만원미만14225319901525341680
38인천광역시부평구282372021취득세30만원~50만원미만134921820134921820
39인천광역시부평구282372021취득세3백만원~5백만원미만2688687026886870
40인천광역시부평구282372021취득세50만원~1백만원미만106548210106548210
41인천광역시부평구282372021취득세5백만원~1천만원미만213827470213827470