Overview

Dataset statistics

Number of variables4
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory35.0 B

Variable types

Text4

Dataset

Description대전광역시 2022년 (2021년 대비) 세입과목별 세입현황 입니다. 증감액(원)으로 데이터가 이루어져 있다.
Author대전광역시
URLhttps://www.data.go.kr/data/15072766/fileData.do

Reproduction

Analysis started2023-12-12 22:08:28.111943
Analysis finished2023-12-12 22:08:28.502518
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

세입과목
Text

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T07:08:28.670558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length10
Mean length6.1136364
Min length2

Characters and Unicode

Total characters269
Distinct characters86
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)95.5%

Sample

1st row취득세
2nd row등록면허세
3rd row주민세
4th row재산세
5th row자동차세
ValueCountFrequency (%)
지난년도수입 2
 
4.5%
취득세 1
 
2.3%
시ㆍ군조정교부금등 1
 
2.3%
보조금 1
 
2.3%
기금 1
 
2.3%
지방채 1
 
2.3%
잉여금 1
 
2.3%
전년도이월금 1
 
2.3%
융자금원금수입 1
 
2.3%
전입금 1
 
2.3%
Other values (33) 33
75.0%
2023-12-13T07:08:28.994133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 16
 
5.9%
수 15
 
5.6%
입 12
 
4.5%
세 12
 
4.5%
지 11
 
4.1%
계 11
 
4.1%
회 10
 
3.7%
별 10
 
3.7%
특 10
 
3.7%
교 8
 
3.0%
Other values (76) 154
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 269
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 16
 
5.9%
수 15
 
5.6%
입 12
 
4.5%
세 12
 
4.5%
지 11
 
4.1%
계 11
 
4.1%
회 10
 
3.7%
별 10
 
3.7%
특 10
 
3.7%
교 8
 
3.0%
Other values (76) 154
57.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 269
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 16
 
5.9%
수 15
 
5.6%
입 12
 
4.5%
세 12
 
4.5%
지 11
 
4.1%
계 11
 
4.1%
회 10
 
3.7%
별 10
 
3.7%
특 10
 
3.7%
교 8
 
3.0%
Other values (76) 154
57.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 268
99.6%
Compat Jamo 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 16
 
6.0%
수 15
 
5.6%
입 12
 
4.5%
세 12
 
4.5%
지 11
 
4.1%
계 11
 
4.1%
회 10
 
3.7%
별 10
 
3.7%
특 10
 
3.7%
교 8
 
3.0%
Other values (75) 153
57.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

2020년 수입액(원)
Text

Distinct37
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T07:08:29.169755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length11.522727
Min length1

Characters and Unicode

Total characters507
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)81.8%

Sample

1st row419,077,652,541
2nd row5,295,062,910
3rd row14,034,955,186
4th row59,635,522,483
5th row232,567,251,421
ValueCountFrequency (%)
0 8
 
18.2%
419,077,652,541 1
 
2.3%
1,062,909,000 1
 
2.3%
44,439,027,132 1
 
2.3%
2,591,532,746 1
 
2.3%
1,121,707,000,000 1
 
2.3%
1,232,662,309,000 1
 
2.3%
40,000,000,000 1
 
2.3%
361,753,597,579 1
 
2.3%
4,332,394,160 1
 
2.3%
Other values (27) 27
61.4%
2023-12-13T07:08:29.466280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 107
21.1%
0 71
14.0%
5 45
8.9%
4 44
8.7%
2 43
8.5%
1 42
 
8.3%
3 35
 
6.9%
9 34
 
6.7%
6 30
 
5.9%
7 30
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400
78.9%
Other Punctuation 107
 
21.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71
17.8%
5 45
11.2%
4 44
11.0%
2 43
10.8%
1 42
10.5%
3 35
8.8%
9 34
8.5%
6 30
7.5%
7 30
7.5%
8 26
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 107
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 507
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 107
21.1%
0 71
14.0%
5 45
8.9%
4 44
8.7%
2 43
8.5%
1 42
 
8.3%
3 35
 
6.9%
9 34
 
6.7%
6 30
 
5.9%
7 30
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 507
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 107
21.1%
0 71
14.0%
5 45
8.9%
4 44
8.7%
2 43
8.5%
1 42
 
8.3%
3 35
 
6.9%
9 34
 
6.7%
6 30
 
5.9%
7 30
 
5.9%

2021년 수입액(원)
Text

Distinct37
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T07:08:29.651791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length11.318182
Min length1

Characters and Unicode

Total characters498
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)81.8%

Sample

1st row525,543,010,850
2nd row5,730,862,310
3rd row14,410,685,000
4th row62,163,539,630
5th row241,683,757,630
ValueCountFrequency (%)
0 8
 
18.2%
525,543,010,850 1
 
2.3%
1203672980 1
 
2.3%
64,221,530,225 1
 
2.3%
2,016,037,122 1
 
2.3%
960,664,000,000 1
 
2.3%
1,551,716,016,900 1
 
2.3%
245,200,000,000 1
 
2.3%
578,819,833,312 1
 
2.3%
3,585,288,820 1
 
2.3%
Other values (27) 27
61.4%
2023-12-13T07:08:29.931270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 99
19.9%
0 76
15.3%
2 47
9.4%
1 47
9.4%
3 39
 
7.8%
5 37
 
7.4%
8 35
 
7.0%
6 34
 
6.8%
7 28
 
5.6%
4 28
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 399
80.1%
Other Punctuation 99
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76
19.0%
2 47
11.8%
1 47
11.8%
3 39
9.8%
5 37
9.3%
8 35
8.8%
6 34
8.5%
7 28
 
7.0%
4 28
 
7.0%
9 28
 
7.0%
Other Punctuation
ValueCountFrequency (%)
, 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 498
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 99
19.9%
0 76
15.3%
2 47
9.4%
1 47
9.4%
3 39
 
7.8%
5 37
 
7.4%
8 35
 
7.0%
6 34
 
6.8%
7 28
 
5.6%
4 28
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 99
19.9%
0 76
15.3%
2 47
9.4%
1 47
9.4%
3 39
 
7.8%
5 37
 
7.4%
8 35
 
7.0%
6 34
 
6.8%
7 28
 
5.6%
4 28
 
5.6%

전년대비 증감액(원)
Text

Distinct37
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T07:08:30.117769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.840909
Min length1

Characters and Unicode

Total characters477
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)81.8%

Sample

1st row106,465,358,309
2nd row435,799,400
3rd row375,729,814
4th row2,528,017,147
5th row9,116,506,209
ValueCountFrequency (%)
0 8
 
18.2%
106,465,358,309 1
 
2.3%
140,763,980 1
 
2.3%
19,782,503,093 1
 
2.3%
575,495,624 1
 
2.3%
161,043,000,000 1
 
2.3%
319,053,707,900 1
 
2.3%
205,200,000,000 1
 
2.3%
217,066,235,733 1
 
2.3%
747,105,340 1
 
2.3%
Other values (27) 27
61.4%
2023-12-13T07:08:30.453955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 96
20.1%
0 77
16.1%
7 42
8.8%
1 36
 
7.5%
6 35
 
7.3%
4 34
 
7.1%
3 34
 
7.1%
5 33
 
6.9%
2 30
 
6.3%
9 26
 
5.5%
Other values (2) 34
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 368
77.1%
Other Punctuation 96
 
20.1%
Dash Punctuation 13
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 77
20.9%
7 42
11.4%
1 36
9.8%
6 35
9.5%
4 34
9.2%
3 34
9.2%
5 33
9.0%
2 30
 
8.2%
9 26
 
7.1%
8 21
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 477
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 96
20.1%
0 77
16.1%
7 42
8.8%
1 36
 
7.5%
6 35
 
7.3%
4 34
 
7.1%
3 34
 
7.1%
5 33
 
6.9%
2 30
 
6.3%
9 26
 
5.5%
Other values (2) 34
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 96
20.1%
0 77
16.1%
7 42
8.8%
1 36
 
7.5%
6 35
 
7.3%
4 34
 
7.1%
3 34
 
7.1%
5 33
 
6.9%
2 30
 
6.3%
9 26
 
5.5%
Other values (2) 34
 
7.1%

Correlations

2023-12-13T07:08:30.547379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세입과목2020년 수입액(원)2021년 수입액(원)전년대비 증감액(원)
세입과목1.0000.9770.9770.977
2020년 수입액(원)0.9771.0001.0001.000
2021년 수입액(원)0.9771.0001.0001.000
전년대비 증감액(원)0.9771.0001.0001.000

Missing values

2023-12-13T07:08:28.376122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:08:28.462524image/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

세입과목2020년 수입액(원)2021년 수입액(원)전년대비 증감액(원)
0취득세419,077,652,541525,543,010,850106,465,358,309
1등록면허세5,295,062,9105,730,862,310435,799,400
2주민세14,034,955,18614,410,685,000375,729,814
3재산세59,635,522,48362,163,539,6302,528,017,147
4자동차세232,567,251,421241,683,757,6309,116,506,209
5레저세19,418,487,5903,629,138,120-15,789,349,470
6담배소비세129,913,885,740127,647,076,810-2,266,808,930
7지방소비세362,875,147,290432,954,375,60070,079,228,310
8지방소득세58,413,388,30053,348,990,880-5,064,397,420
9지역자원시설세1,972,657,000258,360,430-1,714,296,570
세입과목2020년 수입액(원)2021년 수입액(원)전년대비 증감액(원)
34소방안전특별회계184,788,587,948182,811,793,935-1,976,794,013
35교통사업특별회계46,821,257,88060,702,798,58513,881,540,705
36의료급여기금특별회계000
37도시개발특별회계66,596,259,20924,938,604,968-41,657,654,241
38산업단지특별회계53,073,470,55457,789,557,5324,716,086,978
39도시철도사업특별회계10,644,342,26718,273,174,0477,628,831,780
40광역교통시설특별회계14,072,529,50910,727,499,089-3,345,030,420
41학교용지부담금특별회계25,311,302,47442,706,109,19417,394,806,720
42장기미집행도시계획시설대지보상특별회계16,256,29216386962130,670
43기반시설특별회계000