Overview

Dataset statistics

Number of variables10
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory89.5 B

Variable types

Categorical6
Numeric4

Dataset

Description체납액 규모별 체납 건수를 납세자 유형별로 제공합니다. (체납액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금액)
Author인천광역시 계양구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15078871&srcSe=7661IVAWM27C61E190

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 started2024-04-21 13:58:43.670492
Analysis finished2024-04-21 13:58:47.081750
Duration3.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size424.0 B
인천광역시
37 

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 37
100.0%

Length

2024-04-21T22:58:47.197488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:58:47.366819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 37
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size424.0 B
계양구
37 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계양구 37
100.0%

Length

2024-04-21T22:58:47.541945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:58:47.710314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계양구 37
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size424.0 B
28245
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28245
2nd row28245
3rd row28245
4th row28245
5th row28245

Common Values

ValueCountFrequency (%)
28245 37
100.0%

Length

2024-04-21T22:58:47.882015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:58:48.054105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28245 37
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size424.0 B
2021
37 

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 37
100.0%

Length

2024-04-21T22:58:48.226865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:58:48.397968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 37
100.0%

세목명
Categorical

Distinct7
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size424.0 B
지방소득세
9 
재산세
8 
취득세
7 
등록면허세
4 
자동차세
4 
Other values (2)
5 

Length

Max length7
Median length3
Mean length3.9189189
Min length3

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 9
24.3%
재산세 8
21.6%
취득세 7
18.9%
등록면허세 4
10.8%
자동차세 4
10.8%
주민세 4
10.8%
지역자원시설세 1
 
2.7%

Length

2024-04-21T22:58:48.593804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:58:48.821888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 9
24.3%
재산세 8
21.6%
취득세 7
18.9%
등록면허세 4
10.8%
자동차세 4
10.8%
주민세 4
10.8%
지역자원시설세 1
 
2.7%

체납액구간
Categorical

Distinct9
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size424.0 B
10만원 미만
7 
30만원~50만원미만
6 
50만원~1백만원미만
6 
10만원~30만원미만
5 
1백만원~3백만원미만
4 
Other values (4)
9 

Length

Max length11
Median length11
Mean length10.216216
Min length7

Unique

Unique1 ?
Unique (%)2.7%

Sample

1st row10만원 미만
2nd row1백만원~3백만원미만
3rd row30만원~50만원미만
4th row50만원~1백만원미만
5th row10만원 미만

Common Values

ValueCountFrequency (%)
10만원 미만 7
18.9%
30만원~50만원미만 6
16.2%
50만원~1백만원미만 6
16.2%
10만원~30만원미만 5
13.5%
1백만원~3백만원미만 4
10.8%
3백만원~5백만원미만 3
8.1%
5백만원~1천만원미만 3
8.1%
1천만원~3천만원미만 2
 
5.4%
5천만원~1억원미만 1
 
2.7%

Length

2024-04-21T22:58:49.068799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:58:49.305851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 7
15.9%
미만 7
15.9%
30만원~50만원미만 6
13.6%
50만원~1백만원미만 6
13.6%
10만원~30만원미만 5
11.4%
1백만원~3백만원미만 4
9.1%
3백만원~5백만원미만 3
6.8%
5백만원~1천만원미만 3
6.8%
1천만원~3천만원미만 2
 
4.5%
5천만원~1억원미만 1
 
2.3%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean852.64865
Minimum1
Maximum12391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size461.0 B
2024-04-21T22:58:49.549446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.8
Q15
median20
Q3153
95-th percentile3786.4
Maximum12391
Range12390
Interquartile range (IQR)148

Descriptive statistics

Standard deviation2457.668
Coefficient of variation (CV)2.8823924
Kurtosis15.613544
Mean852.64865
Median Absolute Deviation (MAD)18
Skewness3.8785893
Sum31548
Variance6040131.9
MonotonicityNot monotonic
2024-04-21T22:58:49.772148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
5 3
 
8.1%
3 3
 
8.1%
1 2
 
5.4%
9 2
 
5.4%
2 2
 
5.4%
4 2
 
5.4%
6 2
 
5.4%
513 1
 
2.7%
153 1
 
2.7%
167 1
 
2.7%
Other values (18) 18
48.6%
ValueCountFrequency (%)
1 2
5.4%
2 2
5.4%
3 3
8.1%
4 2
5.4%
5 3
8.1%
6 2
5.4%
9 2
5.4%
10 1
 
2.7%
14 1
 
2.7%
20 1
 
2.7%
ValueCountFrequency (%)
12391 1
2.7%
8392 1
2.7%
2635 1
2.7%
2480 1
2.7%
2064 1
2.7%
1555 1
2.7%
513 1
2.7%
484 1
2.7%
167 1
2.7%
153 1
2.7%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82375843
Minimum52330
Maximum4.3272804 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size461.0 B
2024-04-21T22:58:50.005300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum52330
5-th percentile952384
Q13420180
median43296080
Q398671790
95-th percentile3.3756755 × 108
Maximum4.3272804 × 108
Range4.3267571 × 108
Interquartile range (IQR)95251610

Descriptive statistics

Standard deviation1.1407185 × 108
Coefficient of variation (CV)1.3847731
Kurtosis2.7876999
Mean82375843
Median Absolute Deviation (MAD)40970330
Skewness1.8518293
Sum3.0479062 × 109
Variance1.3012388 × 1016
MonotonicityNot monotonic
2024-04-21T22:58:50.236734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
17904560 1
 
2.7%
179596370 1
 
2.7%
88038050 1
 
2.7%
259562720 1
 
2.7%
128696580 1
 
2.7%
66124210 1
 
2.7%
142728430 1
 
2.7%
98671790 1
 
2.7%
63928680 1
 
2.7%
52330 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
52330 1
2.7%
740200 1
2.7%
1005430 1
2.7%
1413000 1
2.7%
1498280 1
2.7%
1800430 1
2.7%
1930480 1
2.7%
2325750 1
2.7%
2638640 1
2.7%
3420180 1
2.7%
ValueCountFrequency (%)
432728040 1
2.7%
398657490 1
2.7%
322295060 1
2.7%
266598900 1
2.7%
259562720 1
2.7%
179596370 1
2.7%
142728430 1
2.7%
128696580 1
2.7%
110162900 1
2.7%
98671790 1
2.7%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1623.9459
Minimum1
Maximum18111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size461.0 B
2024-04-21T22:58:50.538287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median29
Q3319
95-th percentile10996.8
Maximum18111
Range18110
Interquartile range (IQR)313

Descriptive statistics

Standard deviation4137.8702
Coefficient of variation (CV)2.5480344
Kurtosis7.8557681
Mean1623.9459
Median Absolute Deviation (MAD)27
Skewness2.8862777
Sum60086
Variance17121970
MonotonicityNot monotonic
2024-04-21T22:58:50.941982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
5 4
 
10.8%
2 2
 
5.4%
3 2
 
5.4%
40 1
 
2.7%
1587 1
 
2.7%
492 1
 
2.7%
161 1
 
2.7%
9 1
 
2.7%
172 1
 
2.7%
1489 1
 
2.7%
Other values (22) 22
59.5%
ValueCountFrequency (%)
1 1
 
2.7%
2 2
5.4%
3 2
5.4%
5 4
10.8%
6 1
 
2.7%
7 1
 
2.7%
9 1
 
2.7%
10 1
 
2.7%
14 1
 
2.7%
17 1
 
2.7%
ValueCountFrequency (%)
18111 1
2.7%
12472 1
2.7%
10628 1
2.7%
9971 1
2.7%
3561 1
2.7%
1587 1
2.7%
1489 1
2.7%
492 1
2.7%
389 1
2.7%
319 1
2.7%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6827704 × 108
Minimum52330
Maximum1.6941288 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size461.0 B
2024-04-21T22:58:51.336311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum52330
5-th percentile1512936
Q16822810
median63928680
Q31.470943 × 108
95-th percentile5.9867767 × 108
Maximum1.6941288 × 109
Range1.6940765 × 109
Interquartile range (IQR)1.4027149 × 108

Descriptive statistics

Standard deviation3.139159 × 108
Coefficient of variation (CV)1.8654708
Kurtosis15.741965
Mean1.6827704 × 108
Median Absolute Deviation (MAD)61998200
Skewness3.6448082
Sum6.2262503 × 109
Variance9.854319 × 1016
MonotonicityNot monotonic
2024-04-21T22:58:51.962569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
51671840 1
 
2.7%
179596370 1
 
2.7%
89530170 1
 
2.7%
270704670 1
 
2.7%
128696580 1
 
2.7%
68208280 1
 
2.7%
146618950 1
 
2.7%
101939160 1
 
2.7%
63928680 1
 
2.7%
52330 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
52330 1
2.7%
1498280 1
2.7%
1516600 1
2.7%
1698180 1
2.7%
1800430 1
2.7%
1930480 1
2.7%
2344290 1
2.7%
3543810 1
2.7%
4232650 1
2.7%
6822810 1
2.7%
ValueCountFrequency (%)
1694128840 1
2.7%
794950866 1
2.7%
549609370 1
2.7%
487471890 1
2.7%
453257710 1
2.7%
270704670 1
2.7%
268270160 1
2.7%
182315920 1
2.7%
179596370 1
2.7%
147094300 1
2.7%

Interactions

2024-04-21T22:58:46.063378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:44.262171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:44.857164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:45.432625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:46.215570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:44.408255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:45.000372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:45.583193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:46.359810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:44.543612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:45.127982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:45.726299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:46.519670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:44.699802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:45.278706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:58:45.886547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T22:58:52.232680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.3750.5700.4040.050
체납액구간0.0001.0000.0000.7270.0000.401
체납건수0.3750.0001.0000.8390.9970.837
체납금액0.5700.7270.8391.0000.9010.883
누적체납건수0.4040.0000.9970.9011.0000.896
누적체납금액0.0500.4010.8370.8830.8961.000
2024-04-21T22:58:52.497438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2024-04-21T22:58:52.740431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.6950.9620.6600.2330.000
체납금액0.6951.0000.6730.9440.2000.303
누적체납건수0.9620.6731.0000.7080.2550.000
누적체납금액0.6600.9440.7081.0000.0000.175
세목명0.2330.2000.2550.0001.0000.000
체납액구간0.0000.3030.0000.1750.0001.000

Missing values

2024-04-21T22:58:46.738891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T22:58:46.986287image/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
0인천광역시계양구282452021등록면허세10만원 미만51317904560148951671840
1인천광역시계양구282452021등록면허세1백만원~3백만원미만2263864056928470
2인천광역시계양구282452021등록면허세30만원~50만원미만3100543051698180
3인천광역시계양구282452021등록면허세50만원~1백만원미만174020021516600
4인천광역시계양구282452021자동차세10만원 미만263511016290010628453257710
5인천광역시계양구282452021자동차세10만원~30만원미만248043272804099711694128840
6인천광역시계양구282452021자동차세30만원~50만원미만10838310660389133942590
7인천광역시계양구282452021자동차세50만원~1백만원미만423257502414993910
8인천광역시계양구282452021재산세10만원 미만839239865749018111794950866
9인천광역시계양구282452021재산세10만원~30만원미만20643222950603561549609370
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
27인천광역시계양구282452021지방소득세5백만원~1천만원미만10639286801063928680
28인천광역시계양구282452021지방소득세5천만원~1억원미만31795963703179596370
29인천광역시계양구282452021지역자원시설세10만원 미만552330552330
30인천광역시계양구282452021취득세10만원 미만291930480291930480
31인천광역시계양구282452021취득세10만원~30만원미만203543810203543810
32인천광역시계양구282452021취득세1백만원~3백만원미만14209804801420980480
33인천광역시계양구282452021취득세30만원~50만원미만5180043051800430
34인천광역시계양구282452021취득세3백만원~5백만원미만311639400311639400
35인천광역시계양구282452021취득세50만원~1백만원미만2149828021498280
36인천광역시계양구282452021취득세5백만원~1천만원미만1682281016822810