Overview

Dataset statistics

Number of variables9
Number of observations31
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory82.1 B

Variable types

Categorical5
Numeric4

Dataset

Description대구광역시 북구_지방세 비과감면율 현황_20201231
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15080096&dataSetDetailId=150800961dce31e8b719e&provdMethod=FILE

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
부과금액 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
비과세금액 has 2 (6.5%) missing valuesMissing
감면금액 has unique valuesUnique
비과세금액 has 5 (16.1%) zerosZeros
부과금액 has 2 (6.5%) zerosZeros
비과세감면율 has 6 (19.4%) zerosZeros

Reproduction

Analysis started2024-04-20 18:29:33.423917
Analysis finished2024-04-20 18:29:38.272932
Duration4.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size376.0 B
대구광역시
31 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 31
100.0%

Length

2024-04-21T03:29:38.477959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:29:38.778331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 31
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size376.0 B
북구
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
북구 31
100.0%

Length

2024-04-21T03:29:39.091258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:29:39.395035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북구 31
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size376.0 B
27230
31 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27230
2nd row27230
3rd row27230
4th row27230
5th row27230

Common Values

ValueCountFrequency (%)
27230 31
100.0%

Length

2024-04-21T03:29:39.707359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:29:40.010857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27230 31
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size376.0 B
교육세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (3)
11 

Length

Max length7
Median length3
Mean length3.9032258
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교육세
2nd row등록세
3rd row재산세
4th row주민세
5th row취득세

Common Values

ValueCountFrequency (%)
교육세 4
12.9%
재산세 4
12.9%
주민세 4
12.9%
취득세 4
12.9%
자동차세 4
12.9%
등록면허세 4
12.9%
지역자원시설세 4
12.9%
등록세 3
9.7%

Length

2024-04-21T03:29:40.369571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:29:40.752237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 4
12.9%
재산세 4
12.9%
주민세 4
12.9%
취득세 4
12.9%
자동차세 4
12.9%
등록면허세 4
12.9%
지역자원시설세 4
12.9%
등록세 3
9.7%

과세년도
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size376.0 B
2020
8 
2017
8 
2018
8 
2019
7 

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 (%)
2020 8
25.8%
2017 8
25.8%
2018 8
25.8%
2019 7
22.6%

Length

2024-04-21T03:29:41.160416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:29:41.483113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 8
25.8%
2017 8
25.8%
2018 8
25.8%
2019 7
22.6%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct25
Distinct (%)86.2%
Missing2
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean6.025146 × 109
Minimum0
Maximum3.2279839 × 1010
Zeros5
Zeros (%)16.1%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-04-21T03:29:41.813810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.88705 × 108
median7.62275 × 108
Q35.875711 × 109
95-th percentile3.0746854 × 1010
Maximum3.2279839 × 1010
Range3.2279839 × 1010
Interquartile range (IQR)5.687006 × 109

Descriptive statistics

Standard deviation1.0442887 × 1010
Coefficient of variation (CV)1.7332173
Kurtosis2.2954122
Mean6.025146 × 109
Median Absolute Deviation (MAD)7.62275 × 108
Skewness1.9307651
Sum1.7472923 × 1011
Variance1.090539 × 1020
MonotonicityNot monotonic
2024-04-21T03:29:42.204433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 5
 
16.1%
3263306000 1
 
3.2%
6162434000 1
 
3.2%
753344000 1
 
3.2%
188705000 1
 
3.2%
205022000 1
 
3.2%
8953536000 1
 
3.2%
3355645000 1
 
3.2%
31138878000 1
 
3.2%
737767000 1
 
3.2%
Other values (15) 15
48.4%
(Missing) 2
 
6.5%
ValueCountFrequency (%)
0 5
16.1%
117161000 1
 
3.2%
140547000 1
 
3.2%
188705000 1
 
3.2%
198812000 1
 
3.2%
205022000 1
 
3.2%
206464000 1
 
3.2%
679095000 1
 
3.2%
737767000 1
 
3.2%
753344000 1
 
3.2%
ValueCountFrequency (%)
32279839000 1
3.2%
31138878000 1
3.2%
30158818000 1
3.2%
29142811000 1
3.2%
11529153000 1
3.2%
8953536000 1
3.2%
6162434000 1
3.2%
5875711000 1
3.2%
3734648000 1
3.2%
3355645000 1
3.2%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7705216 × 109
Minimum2000
Maximum2.924403 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-04-21T03:29:42.577609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile3500
Q173153500
median6.99103 × 108
Q34.165326 × 109
95-th percentile2.7036043 × 1010
Maximum2.924403 × 1010
Range2.9244028 × 1010
Interquartile range (IQR)4.0921725 × 109

Descriptive statistics

Standard deviation8.8989539 × 109
Coefficient of variation (CV)1.8654048
Kurtosis3.1666552
Mean4.7705216 × 109
Median Absolute Deviation (MAD)6.99099 × 108
Skewness2.1249567
Sum1.4788617 × 1011
Variance7.9191381 × 1019
MonotonicityNot monotonic
2024-04-21T03:29:42.977654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
5000 1
 
3.2%
1005000 1
 
3.2%
271457000 1
 
3.2%
101757000 1
 
3.2%
2483609000 1
 
3.2%
29244030000 1
 
3.2%
735579000 1
 
3.2%
6637774000 1
 
3.2%
3000 1
 
3.2%
416948000 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
2000 1
3.2%
3000 1
3.2%
4000 1
3.2%
5000 1
3.2%
691000 1
3.2%
1005000 1
3.2%
5765000 1
3.2%
69014000 1
3.2%
77293000 1
3.2%
98313000 1
3.2%
ValueCountFrequency (%)
29244030000 1
3.2%
28504813000 1
3.2%
25567273000 1
3.2%
23699710000 1
3.2%
7471125000 1
3.2%
6637774000 1
3.2%
6155625000 1
3.2%
5830805000 1
3.2%
2499847000 1
3.2%
2483609000 1
3.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9101097 × 1010
Minimum0
Maximum1.8391113 × 1011
Zeros2
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-04-21T03:29:43.358546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25349500
Q18.48331 × 109
median2.773066 × 1010
Q34.8685784 × 1010
95-th percentile1.3460655 × 1011
Maximum1.8391113 × 1011
Range1.8391113 × 1011
Interquartile range (IQR)4.0202474 × 1010

Descriptive statistics

Standard deviation4.6249182 × 1010
Coefficient of variation (CV)1.1828104
Kurtosis2.684025
Mean3.9101097 × 1010
Median Absolute Deviation (MAD)1.9291297 × 1010
Skewness1.7542548
Sum1.212134 × 1012
Variance2.1389868 × 1021
MonotonicityNot monotonic
2024-04-21T03:29:43.769677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 2
 
6.5%
35156033000 1
 
3.2%
27730660000 1
 
3.2%
8574448000 1
 
3.2%
10772946000 1
 
3.2%
38712932000 1
 
3.2%
122589497000 1
 
3.2%
8527257000 1
 
3.2%
68237246000 1
 
3.2%
29452202000 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
0 2
6.5%
50699000 1
3.2%
6580786000 1
3.2%
7731385000 1
3.2%
7925898000 1
3.2%
8168948000 1
3.2%
8439363000 1
3.2%
8527257000 1
3.2%
8574448000 1
3.2%
8941647000 1
3.2%
ValueCountFrequency (%)
183911128000 1
3.2%
146623606000 1
3.2%
122589497000 1
3.2%
115092891000 1
3.2%
73848245000 1
3.2%
68237246000 1
3.2%
62714055000 1
3.2%
57897283000 1
3.2%
39474285000 1
3.2%
38712932000 1
3.2%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.317419
Minimum0
Maximum87.58
Zeros6
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-04-21T03:29:44.151491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.235
median11.49
Q339.275
95-th percentile59.155
Maximum87.58
Range87.58
Interquartile range (IQR)37.04

Descriptive statistics

Standard deviation24.520833
Coefficient of variation (CV)1.1502721
Kurtosis0.1345009
Mean21.317419
Median Absolute Deviation (MAD)11.49
Skewness1.0968308
Sum660.84
Variance601.27125
MonotonicityNot monotonic
2024-04-21T03:29:44.514227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 6
 
19.4%
2.49 2
 
6.5%
57.9 1
 
3.2%
11.95 1
 
3.2%
2.7 1
 
3.2%
6.95 1
 
3.2%
31.16 1
 
3.2%
47.98 1
 
3.2%
55.36 1
 
3.2%
13.68 1
 
3.2%
Other values (15) 15
48.4%
ValueCountFrequency (%)
0.0 6
19.4%
1.91 1
 
3.2%
1.98 1
 
3.2%
2.49 2
 
6.5%
2.7 1
 
3.2%
6.48 1
 
3.2%
6.95 1
 
3.2%
7.26 1
 
3.2%
7.48 1
 
3.2%
11.49 1
 
3.2%
ValueCountFrequency (%)
87.58 1
3.2%
60.41 1
3.2%
57.9 1
3.2%
57.85 1
3.2%
55.36 1
3.2%
53.83 1
3.2%
47.98 1
3.2%
47.39 1
3.2%
31.16 1
3.2%
30.61 1
3.2%

Interactions

2024-04-21T03:29:36.719227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:33.743891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:34.731252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:35.716266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:36.886893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:33.991382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:34.978119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:35.969247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:37.097029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:34.240450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:35.226177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:36.224041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:37.295108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:34.496477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:35.481867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:29:36.480250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:29:44.750618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.7680.7500.9560.866
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.7680.0001.0000.9470.8210.831
감면금액0.7500.0000.9471.0000.8510.700
부과금액0.9560.0000.8210.8511.0000.805
비과세감면율0.8660.0000.8310.7000.8051.000
2024-04-21T03:29:45.009279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2024-04-21T03:29:45.252725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.8940.4590.9160.5690.000
감면금액0.8941.0000.6280.8150.5550.000
부과금액0.4590.6281.0000.2610.6640.000
비과세감면율0.9160.8150.2611.0000.6770.000
세목명0.5690.5550.6640.6771.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2024-04-21T03:29:37.665258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:29:38.105051image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
0대구광역시북구27230교육세202005000351560330000.0
1대구광역시북구27230등록세202001005000506990001.98
2대구광역시북구27230재산세20203227983900074711250007384824500053.83
3대구광역시북구27230주민세202032633060002499847000658078600087.58
4대구광역시북구27230취득세202061624340002850481300018391112800018.85
5대구광역시북구27230자동차세20202064640002352743000394742850006.48
6대구광역시북구27230등록면허세202019881200077293000110861670002.49
7대구광역시북구27230지역자원시설세2020762275000265389000894164700011.49
8대구광역시북구27230교육세201702000294785820000.0
9대구광역시북구27230등록세2017<NA>576500000.0
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
21대구광역시북구27230자동차세201810127990001756591000381616790007.26
22대구광역시북구27230등록면허세20181405470009831300095969400002.49
23대구광역시북구27230지역자원시설세2018737767000416948000843936300013.68
24대구광역시북구27230교육세201903000294522020000.0
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