Overview

Dataset statistics

Number of variables8
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory76.3 B

Variable types

Categorical2
Numeric6

Dataset

Description-2022년 12월말 기준 청구 유형별(개인, 법인), 청구세액 규모별 과세전적부심사청구 처리 실적 - 심사제외 건수에 직권시정분 포함 단위 : 건, 백만원, %
URLhttps://www.data.go.kr/data/15114173/fileData.do

Alerts

전년이월 건수 is highly overall correlated with 당년접수 건수 and 3 other fieldsHigh correlation
당년접수 건수 is highly overall correlated with 전년이월 건수 and 4 other fieldsHigh correlation
채택 건수 is highly overall correlated with 전년이월 건수 and 3 other fieldsHigh correlation
불채택 건수 is highly overall correlated with 전년이월 건수 and 3 other fieldsHigh correlation
심사제외 건수 is highly overall correlated with 전년이월 건수 and 3 other fieldsHigh correlation
구분1 is highly overall correlated with 당년접수 건수High correlation
불채택 건수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:51:10.030197
Analysis finished2023-12-12 09:51:14.503303
Duration4.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분1
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
청구세액 규모별
7 
개인
7 
법인
7 

Length

Max length8
Median length2
Mean length4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row청구세액 규모별
2nd row청구세액 규모별
3rd row청구세액 규모별
4th row청구세액 규모별
5th row청구세액 규모별

Common Values

ValueCountFrequency (%)
청구세액 규모별 7
33.3%
개인 7
33.3%
법인 7
33.3%

Length

2023-12-12T18:51:14.602876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:51:14.735212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청구세액 7
25.0%
규모별 7
25.0%
개인 7
25.0%
법인 7
25.0%

구분2
Categorical

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
1천만 미만
3 
3천만 미만
3 
5천만 미만
3 
1억 미만
3 
5억 미만
3 
Other values (2)
6 

Length

Max length6
Median length6
Mean length5.7142857
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1천만 미만
2nd row3천만 미만
3rd row5천만 미만
4th row1억 미만
5th row5억 미만

Common Values

ValueCountFrequency (%)
1천만 미만 3
14.3%
3천만 미만 3
14.3%
5천만 미만 3
14.3%
1억 미만 3
14.3%
5억 미만 3
14.3%
10억 미만 3
14.3%
10억 이상 3
14.3%

Length

2023-12-12T18:51:14.862904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:51:15.002374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 18
42.9%
10억 6
 
14.3%
1천만 3
 
7.1%
3천만 3
 
7.1%
5천만 3
 
7.1%
1억 3
 
7.1%
5억 3
 
7.1%
이상 3
 
7.1%

전년이월 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.047619
Minimum2
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T18:51:15.121963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q113
median25
Q342
95-th percentile61
Maximum79
Range77
Interquartile range (IQR)29

Descriptive statistics

Standard deviation21.093782
Coefficient of variation (CV)0.72617936
Kurtosis-0.036635595
Mean29.047619
Median Absolute Deviation (MAD)15
Skewness0.69619101
Sum610
Variance444.94762
MonotonicityNot monotonic
2023-12-12T18:51:15.254765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
42 2
 
9.5%
18 2
 
9.5%
4 2
 
9.5%
35 2
 
9.5%
61 1
 
4.8%
2 1
 
4.8%
13 1
 
4.8%
7 1
 
4.8%
10 1
 
4.8%
23 1
 
4.8%
Other values (7) 7
33.3%
ValueCountFrequency (%)
2 1
4.8%
4 2
9.5%
7 1
4.8%
10 1
4.8%
13 1
4.8%
14 1
4.8%
18 2
9.5%
23 1
4.8%
25 1
4.8%
33 1
4.8%
ValueCountFrequency (%)
79 1
4.8%
61 1
4.8%
60 1
4.8%
46 1
4.8%
42 2
9.5%
39 1
4.8%
35 2
9.5%
33 1
4.8%
25 1
4.8%
23 1
4.8%

당년접수 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188.95238
Minimum31
Maximum518
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T18:51:15.379869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile34
Q172
median148
Q3294
95-th percentile430
Maximum518
Range487
Interquartile range (IQR)222

Descriptive statistics

Standard deviation143.36718
Coefficient of variation (CV)0.75874766
Kurtosis-0.27534173
Mean188.95238
Median Absolute Deviation (MAD)92
Skewness0.85791249
Sum3968
Variance20554.148
MonotonicityNot monotonic
2023-12-12T18:51:15.517070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
56 2
 
9.5%
392 1
 
4.8%
430 1
 
4.8%
34 1
 
4.8%
88 1
 
4.8%
72 1
 
4.8%
31 1
 
4.8%
70 1
 
4.8%
92 1
 
4.8%
87 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
31 1
4.8%
34 1
4.8%
56 2
9.5%
70 1
4.8%
72 1
4.8%
87 1
4.8%
88 1
4.8%
92 1
4.8%
121 1
4.8%
148 1
4.8%
ValueCountFrequency (%)
518 1
4.8%
430 1
4.8%
392 1
4.8%
336 1
4.8%
319 1
4.8%
294 1
4.8%
249 1
4.8%
222 1
4.8%
192 1
4.8%
161 1
4.8%

채택 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.047619
Minimum5
Maximum133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T18:51:15.617206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile14
Q117
median33
Q349
95-th percentile110
Maximum133
Range128
Interquartile range (IQR)32

Descriptive statistics

Standard deviation32.042903
Coefficient of variation (CV)0.78062756
Kurtosis2.8496379
Mean41.047619
Median Absolute Deviation (MAD)16
Skewness1.6560541
Sum862
Variance1026.7476
MonotonicityNot monotonic
2023-12-12T18:51:15.748711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
17 2
 
9.5%
16 2
 
9.5%
49 1
 
4.8%
62 1
 
4.8%
15 1
 
4.8%
23 1
 
4.8%
14 1
 
4.8%
5 1
 
4.8%
27 1
 
4.8%
110 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
5 1
4.8%
14 1
4.8%
15 1
4.8%
16 2
9.5%
17 2
9.5%
23 1
4.8%
27 1
4.8%
31 1
4.8%
33 1
4.8%
38 1
4.8%
ValueCountFrequency (%)
133 1
4.8%
110 1
4.8%
69 1
4.8%
62 1
4.8%
55 1
4.8%
49 1
4.8%
45 1
4.8%
44 1
4.8%
43 1
4.8%
38 1
4.8%

불채택 건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.38095
Minimum13
Maximum360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T18:51:15.862627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile21
Q154
median94
Q3215
95-th percentile300
Maximum360
Range347
Interquartile range (IQR)161

Descriptive statistics

Standard deviation106.43471
Coefficient of variation (CV)0.79203718
Kurtosis-0.72108478
Mean134.38095
Median Absolute Deviation (MAD)62
Skewness0.74806136
Sum2822
Variance11328.348
MonotonicityNot monotonic
2023-12-12T18:51:15.967472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
299 1
 
4.8%
237 1
 
4.8%
32 1
 
4.8%
13 1
 
4.8%
60 1
 
4.8%
48 1
 
4.8%
21 1
 
4.8%
54 1
 
4.8%
37 1
 
4.8%
62 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
13 1
4.8%
21 1
4.8%
32 1
4.8%
37 1
4.8%
48 1
4.8%
54 1
4.8%
57 1
4.8%
60 1
4.8%
62 1
4.8%
70 1
4.8%
ValueCountFrequency (%)
360 1
4.8%
300 1
4.8%
299 1
4.8%
262 1
4.8%
237 1
4.8%
215 1
4.8%
183 1
4.8%
167 1
4.8%
136 1
4.8%
115 1
4.8%

심사제외 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.380952
Minimum2
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T18:51:16.068532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q17
median10
Q331
95-th percentile57
Maximum63
Range61
Interquartile range (IQR)24

Descriptive statistics

Standard deviation18.158954
Coefficient of variation (CV)0.98792238
Kurtosis0.85410515
Mean18.380952
Median Absolute Deviation (MAD)4
Skewness1.3692022
Sum386
Variance329.74762
MonotonicityNot monotonic
2023-12-12T18:51:16.164840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
7 4
19.0%
10 3
14.3%
12 2
9.5%
2 2
9.5%
63 1
 
4.8%
38 1
 
4.8%
9 1
 
4.8%
19 1
 
4.8%
42 1
 
4.8%
57 1
 
4.8%
Other values (4) 4
19.0%
ValueCountFrequency (%)
2 2
9.5%
3 1
 
4.8%
6 1
 
4.8%
7 4
19.0%
9 1
 
4.8%
10 3
14.3%
12 2
9.5%
19 1
 
4.8%
31 1
 
4.8%
32 1
 
4.8%
ValueCountFrequency (%)
63 1
 
4.8%
57 1
 
4.8%
42 1
 
4.8%
38 1
 
4.8%
32 1
 
4.8%
31 1
 
4.8%
19 1
 
4.8%
12 2
9.5%
10 3
14.3%
9 1
 
4.8%

채택비율
Real number (ℝ)

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.757143
Minimum9.4
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T18:51:16.291852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.4
5-th percentile11.9
Q119.3
median23.5
Q327.1
95-th percentile32.7
Maximum50
Range40.6
Interquartile range (IQR)7.8

Descriptive statistics

Standard deviation8.1801327
Coefficient of variation (CV)0.34432309
Kurtosis4.7734305
Mean23.757143
Median Absolute Deviation (MAD)3.9
Skewness1.3925329
Sum498.9
Variance66.914571
MonotonicityNot monotonic
2023-12-12T18:51:16.416283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
24.9 2
 
9.5%
11.9 1
 
4.8%
19.3 1
 
4.8%
32.7 1
 
4.8%
50.0 1
 
4.8%
24.7 1
 
4.8%
20.3 1
 
4.8%
17.9 1
 
4.8%
21.8 1
 
4.8%
27.1 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
9.4 1
4.8%
11.9 1
4.8%
17.4 1
4.8%
17.9 1
4.8%
18.4 1
4.8%
19.3 1
4.8%
20.3 1
4.8%
21.8 1
4.8%
22.8 1
4.8%
22.9 1
4.8%
ValueCountFrequency (%)
50.0 1
4.8%
32.7 1
4.8%
29.7 1
4.8%
28.1 1
4.8%
27.4 1
4.8%
27.1 1
4.8%
24.9 2
9.5%
24.7 1
4.8%
23.8 1
4.8%
23.5 1
4.8%

Interactions

2023-12-12T18:51:13.627159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:10.354364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.006388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.542021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:12.092440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:12.994997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:13.754957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:10.472790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.096950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.635106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:12.192397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:13.117456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:13.846747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:10.573018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.181669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.715016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:12.296647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:13.217340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:13.944506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:10.671993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.267671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.800478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:12.402334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:13.297705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:14.070317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:10.784938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.354957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.899957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:12.519389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:13.399386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:14.162959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:10.888965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.436804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:11.995255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:12.604180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:51:13.491149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:51:16.508789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1구분2전년이월 건수당년접수 건수채택 건수불채택 건수심사제외 건수채택비율
구분11.0000.0000.5210.7790.6540.6860.5910.000
구분20.0001.0000.5170.0000.0000.0000.5750.808
전년이월 건수0.5210.5171.0000.7580.7320.7880.8210.000
당년접수 건수0.7790.0000.7581.0000.8640.9780.9110.551
채택 건수0.6540.0000.7320.8641.0000.8950.8780.000
불채택 건수0.6860.0000.7880.9780.8951.0000.9070.000
심사제외 건수0.5910.5750.8210.9110.8780.9071.0000.600
채택비율0.0000.8080.0000.5510.0000.0000.6001.000
2023-12-12T18:51:16.625148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분2구분1
구분21.0000.000
구분10.0001.000
2023-12-12T18:51:16.716194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전년이월 건수당년접수 건수채택 건수불채택 건수심사제외 건수채택비율구분1구분2
전년이월 건수1.0000.8580.9040.8580.7360.0170.3410.145
당년접수 건수0.8581.0000.9210.9970.923-0.3220.5040.000
채택 건수0.9040.9211.0000.9230.799-0.0940.4950.000
불채택 건수0.8580.9970.9231.0000.924-0.3450.4020.000
심사제외 건수0.7360.9230.7990.9241.000-0.4490.4110.185
채택비율0.017-0.322-0.094-0.345-0.4491.0000.0000.327
구분10.3410.5040.4950.4020.4110.0001.0000.000
구분20.1450.0000.0000.0000.1850.3270.0001.000

Missing values

2023-12-12T18:51:14.308211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:51:14.456773image/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

구분1구분2전년이월 건수당년접수 건수채택 건수불채택 건수심사제외 건수채택비율
0청구세액 규모별1천만 미만42392492996311.9
1청구세액 규모별3천만 미만46319622373818.4
2청구세액 규모별5천만 미만2519243136922.9
3청구세액 규모별1억 미만39294692151922.8
4청구세액 규모별5억 미만795181333604224.9
5청구세액 규모별10억 미만1412131701227.4
6청구세액 규모별10억 이상6014844941029.7
7개인1천만 미만3533633262579.4
8개인3천만 미만33249451833117.4
9개인5천만 미만2316138115723.8
구분1구분2전년이월 건수당년접수 건수채택 건수불채택 건수심사제외 건수채택비율
11개인5억 미만614301103003224.9
12개인10억 미만108716571019.3
13개인10억 이상42922762728.1
14법인1천만 미만7561637627.1
15법인3천만 미만13701754721.8
16법인5천만 미만231521217.9
17법인1억 미만4721448720.3
18법인5억 미만188823601024.7
19법인10억 미만4341513250.0
20법인10억 이상18561732332.7