Overview

Dataset statistics

Number of variables7
Number of observations275
Missing cells243
Missing cells (%)12.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.5 KiB
Average record size in memory61.5 B

Variable types

Categorical1
Text2
Numeric4

Dataset

Description지방세 비과세 감면율 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=WEPFP7XTRUIKFW0Z8UMS22852793&infSeq=1

Alerts

비과세액(원) is highly overall correlated with 감면액(원) and 1 other fieldsHigh correlation
감면액(원) is highly overall correlated with 비과세액(원) and 1 other fieldsHigh correlation
지방세징수액(원) is highly overall correlated with 비과세액(원) and 1 other fieldsHigh correlation
시군명 has 243 (88.4%) missing valuesMissing
비과세액(원) has unique valuesUnique
감면액(원) has unique valuesUnique
지방세징수액(원) has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:02:03.093026
Analysis finished2023-12-10 21:02:05.663311
Duration2.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2020
243 
2021
32 

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 (%)
2020 243
88.4%
2021 32
 
11.6%

Length

2023-12-11T06:02:05.740659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:02:05.845604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 243
88.4%
2021 32
 
11.6%

시군명
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing243
Missing (%)88.4%
Memory size2.3 KiB
2023-12-11T06:02:06.095279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.09375
Min length3

Characters and Unicode

Total characters99
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row경기도
3rd row고양시
4th row과천시
5th row광명시
ValueCountFrequency (%)
경기도 1
 
3.1%
고양시 1
 
3.1%
화성시 1
 
3.1%
하남시 1
 
3.1%
포천시 1
 
3.1%
평택시 1
 
3.1%
파주시 1
 
3.1%
이천시 1
 
3.1%
의정부시 1
 
3.1%
의왕시 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T06:02:06.533157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

자치단체명
Text

Distinct243
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T06:02:06.940742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.8872727
Min length4

Characters and Unicode

Total characters1344
Distinct characters133
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)76.7%

Sample

1st row경기가평군
2nd row경기본청
3rd row경기고양시
4th row경기과천시
5th row경기광명시
ValueCountFrequency (%)
경기가평군 2
 
0.7%
경기평택시 2
 
0.7%
경기안성시 2
 
0.7%
경기여주시 2
 
0.7%
경기용인시 2
 
0.7%
경기연천군 2
 
0.7%
경기양평군 2
 
0.7%
경기의왕시 2
 
0.7%
경기하남시 2
 
0.7%
경기이천시 2
 
0.7%
Other values (233) 255
92.7%
2023-12-11T06:02:07.491198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1344
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1344
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1344
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

비과세액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0830139 × 1010
Minimum8.6923156 × 108
Maximum5.9883952 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:02:07.676446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.6923156 × 108
5-th percentile1.9381496 × 109
Q15.5580625 × 109
median1.5811715 × 1010
Q33.5509779 × 1010
95-th percentile9.2406706 × 1010
Maximum5.9883952 × 1011
Range5.9797029 × 1011
Interquartile range (IQR)2.9951717 × 1010

Descriptive statistics

Standard deviation5.3366557 × 1010
Coefficient of variation (CV)1.7309866
Kurtosis53.911216
Mean3.0830139 × 1010
Median Absolute Deviation (MAD)1.2361332 × 1010
Skewness6.194913
Sum8.4782883 × 1012
Variance2.8479895 × 1021
MonotonicityNot monotonic
2023-12-11T06:02:07.907596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11749948490 1
 
0.4%
58259125280 1
 
0.4%
6870802220 1
 
0.4%
12244908120 1
 
0.4%
18337492200 1
 
0.4%
9234837130 1
 
0.4%
11966722130 1
 
0.4%
37716426620 1
 
0.4%
3450383060 1
 
0.4%
8540518040 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
869231560 1
0.4%
992195740 1
0.4%
1115061460 1
0.4%
1163115060 1
0.4%
1362679140 1
0.4%
1371792610 1
0.4%
1397869820 1
0.4%
1474332660 1
0.4%
1505910240 1
0.4%
1521834940 1
0.4%
ValueCountFrequency (%)
598839522688 1
0.4%
342756334030 1
0.4%
328243888530 1
0.4%
215781172860 1
0.4%
175878551610 1
0.4%
159795775320 1
0.4%
131604328470 1
0.4%
122016552560 1
0.4%
111923535140 1
0.4%
110379132918 1
0.4%

감면액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.92586 × 1010
Minimum1.9200812 × 108
Maximum1.5280962 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:02:08.078995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9200812 × 108
5-th percentile4.0787847 × 108
Q11.4627087 × 109
median4.3330612 × 109
Q31.1300949 × 1010
95-th percentile1.1812065 × 1011
Maximum1.5280962 × 1012
Range1.5279042 × 1012
Interquartile range (IQR)9.8382404 × 109

Descriptive statistics

Standard deviation1.4336897 × 1011
Coefficient of variation (CV)4.9000627
Kurtosis83.936298
Mean2.92586 × 1010
Median Absolute Deviation (MAD)3.412596 × 109
Skewness8.9162789
Sum8.0461149 × 1012
Variance2.0554662 × 1022
MonotonicityNot monotonic
2023-12-11T06:02:08.227554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1460924020 1
 
0.4%
149474317780 1
 
0.4%
2618951630 1
 
0.4%
3784597100 1
 
0.4%
8549938920 1
 
0.4%
2386455230 1
 
0.4%
2611007430 1
 
0.4%
15906629210 1
 
0.4%
364125930 1
 
0.4%
2901449100 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
192008120 1
0.4%
252847720 1
0.4%
279627980 1
0.4%
297751230 1
0.4%
330455120 1
0.4%
331599280 1
0.4%
332473580 1
0.4%
338501930 1
0.4%
341650670 1
0.4%
364125930 1
0.4%
ValueCountFrequency (%)
1528096204880 1
0.4%
1415720170350 1
0.4%
1053296821498 1
0.4%
258715576250 1
0.4%
238656822780 1
0.4%
204027353900 1
0.4%
196977416090 1
0.4%
177762130150 1
0.4%
173456153490 1
0.4%
149474317780 1
0.4%

지방세징수액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8495107 × 1011
Minimum6.2408768 × 109
Maximum2.3393017 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:02:08.440039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.2408768 × 109
5-th percentile2.1013427 × 1010
Q14.2519729 × 1010
median1.030027 × 1011
Q32.236631 × 1011
95-th percentile1.6088514 × 1012
Maximum2.3393017 × 1013
Range2.3386776 × 1013
Interquartile range (IQR)1.8114337 × 1011

Descriptive statistics

Standard deviation1.9991007 × 1012
Coefficient of variation (CV)4.122273
Kurtosis86.82636
Mean4.8495107 × 1011
Median Absolute Deviation (MAD)6.9751147 × 1010
Skewness8.8710991
Sum1.3336154 × 1014
Variance3.9964037 × 1024
MonotonicityNot monotonic
2023-12-11T06:02:08.580020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64395668560 1
 
0.4%
2338215664200 1
 
0.4%
70927347150 1
 
0.4%
174481544020 1
 
0.4%
339349937300 1
 
0.4%
64949698460 1
 
0.4%
86193422280 1
 
0.4%
516047576730 1
 
0.4%
24243384800 1
 
0.4%
83158723300 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
6240876760 1
0.4%
10825341450 1
0.4%
12659841460 1
0.4%
14006356670 1
0.4%
16299082680 1
0.4%
16589788580 1
0.4%
16872511340 1
0.4%
16947816220 1
0.4%
17868463260 1
0.4%
18201192770 1
0.4%
ValueCountFrequency (%)
23393017226737 1
0.4%
16798716080970 1
0.4%
14418116808590 1
0.4%
5070207735930 1
0.4%
4201744974363 1
0.4%
3273535588829 1
0.4%
3168709057300 1
0.4%
2549369630460 1
0.4%
2338215664200 1
0.4%
2140801019600 1
0.4%

지방세비과세감면율(%)
Real number (ℝ)

Distinct255
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.092364
Minimum4.53
Maximum42.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:02:08.790969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.53
5-th percentile7.447
Q110.28
median13.45
Q319.795
95-th percentile30.878
Maximum42.69
Range38.16
Interquartile range (IQR)9.515

Descriptive statistics

Standard deviation7.9385804
Coefficient of variation (CV)0.49331351
Kurtosis0.38014388
Mean16.092364
Median Absolute Deviation (MAD)3.89
Skewness1.0867283
Sum4425.4
Variance63.021058
MonotonicityNot monotonic
2023-12-11T06:02:09.159333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.27 2
 
0.7%
26.96 2
 
0.7%
10.36 2
 
0.7%
9.41 2
 
0.7%
11.38 2
 
0.7%
14.62 2
 
0.7%
7.34 2
 
0.7%
13.31 2
 
0.7%
29.4 2
 
0.7%
12.42 2
 
0.7%
Other values (245) 255
92.7%
ValueCountFrequency (%)
4.53 1
0.4%
5.57 1
0.4%
5.66 1
0.4%
6.0 1
0.4%
6.29 1
0.4%
6.43 1
0.4%
6.6 1
0.4%
6.91 1
0.4%
7.23 1
0.4%
7.32 1
0.4%
ValueCountFrequency (%)
42.69 1
0.4%
39.31 1
0.4%
38.8 1
0.4%
38.01 1
0.4%
37.63 1
0.4%
37.41 1
0.4%
36.14 1
0.4%
35.52 1
0.4%
35.32 1
0.4%
32.69 1
0.4%

Interactions

2023-12-11T06:02:04.906443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:03.431358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:03.931217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:04.388012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:05.027274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:03.560385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:04.051018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:04.525897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:05.171132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:03.683345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:04.166042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:04.680122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:05.297477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:03.808827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:04.274006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:04.785906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:02:09.264564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명비과세액(원)감면액(원)지방세징수액(원)지방세비과세감면율(%)
회계연도1.000NaN0.2490.0810.1580.208
시군명NaN1.0001.0001.0001.0001.000
비과세액(원)0.2491.0001.0000.9390.9410.261
감면액(원)0.0811.0000.9391.0000.9850.163
지방세징수액(원)0.1581.0000.9410.9851.0000.161
지방세비과세감면율(%)0.2081.0000.2610.1630.1611.000
2023-12-11T06:02:09.411257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세액(원)감면액(원)지방세징수액(원)지방세비과세감면율(%)회계연도
비과세액(원)1.0000.9380.8820.2840.178
감면액(원)0.9381.0000.9180.1200.053
지방세징수액(원)0.8820.9181.000-0.1410.113
지방세비과세감면율(%)0.2840.120-0.1411.0000.157
회계연도0.1780.0530.1130.1571.000

Missing values

2023-12-11T06:02:05.468874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:02:05.612763image/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

회계연도시군명자치단체명비과세액(원)감면액(원)지방세징수액(원)지방세비과세감면율(%)
02021가평군경기가평군1174994849014609240206439566856017.02
12021경기도경기본청34275633403015280962048801679871608097010.02
22021고양시경기고양시1316043284702649074472074129473848017.58
32021과천시경기과천시26325152080300766850013334497367018.03
42021광명시경기광명시32908982300792687758023558816861014.77
52021광주시경기광주시2864845703064206423303343560720409.49
62021구리시경기구리시21171905170598109509013001670057017.28
72021군포시경기군포시22076548370669743377019010354794013.15
82021김포시경기김포시397510848001182583397039575027969011.53
92021남양주시경기남양주시555671618301638763402047803821021013.08
회계연도시군명자치단체명비과세액(원)감면액(원)지방세징수액(원)지방세비과세감면율(%)
2652020<NA>경남김해시309267893001050111003037179814820010.03
2662020<NA>경남밀양시10258952190257143891010314054479011.06
2672020<NA>경남거제시1064275461032963036601561371426208.2
2682020<NA>경남양산시2398568965080396255503153007749429.22
2692020<NA>경남의령군2012179580338501930232516717509.18
2702020<NA>경남함안군53975829701820630680718095999309.13
2712020<NA>경남창녕군712484317012519235704742743503015.01
2722020<NA>경남고성군2788352330929025250414661386308.23
2732020<NA>경남남해군21399759208023838002612124969010.12
2742020<NA>경남하동군31177071706645286602856939280011.69