Overview

Dataset statistics

Number of variables5
Number of observations71
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory44.9 B

Variable types

Text1
Numeric3
Categorical1

Dataset

Description인천광역시의 청년정책 예산(국비, 시비, 기타) 및 (사업명, 추진부서, 사업예산)등의 항목에 대한 현황 자료를 제공하는 데이터입니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15038446&srcSe=7661IVAWM27C61E190

Alerts

사업명 has unique valuesUnique
예산-국비_백만원 has 47 (66.2%) zerosZeros
예산-시비_백만원 has 8 (11.3%) zerosZeros
예산-기타_백만원 has 62 (87.3%) zerosZeros

Reproduction

Analysis started2024-01-28 08:44:16.576771
Analysis finished2024-01-28 08:44:17.613735
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업명
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2024-01-28T17:44:17.796997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length35
Mean length27.056338
Min length18

Characters and Unicode

Total characters1921
Distinct characters251
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st rowⅠ-1-1-01. 창업기업 청년일자리 지원 사업
2nd rowⅠ-1-1-02. 지역성장 도약기업 청년일자리 지원 사업
3rd rowⅠ-1-1-04. 인천 청년 면접지원(드림나래)
4th rowⅠ-1-1-05. 인천지역 대학일자리플러스센터 운영 지원
5th rowⅠ-1-1-06. 인천 지역대학 취업 지원 사업 추진
ValueCountFrequency (%)
청년 21
 
6.1%
지원사업 13
 
3.8%
지원 13
 
3.8%
운영 13
 
3.8%
사업 12
 
3.5%
인천 10
 
2.9%
위한 6
 
1.7%
및 5
 
1.5%
청년창업 4
 
1.2%
청년일자리 4
 
1.2%
Other values (223) 242
70.6%
2024-01-28T17:44:18.165154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
275
 
14.3%
- 213
 
11.1%
1 102
 
5.3%
2 75
 
3.9%
. 72
 
3.7%
업 63
 
3.3%
0 58
 
3.0%
년 58
 
3.0%
청 57
 
3.0%
지 46
 
2.4%
Other values (241) 902
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 968
50.4%
Decimal Number 282
 
14.7%
Space Separator 275
 
14.3%
Dash Punctuation 213
 
11.1%
Other Punctuation 81
 
4.2%
Letter Number 71
 
3.7%
Lowercase Letter 10
 
0.5%
Uppercase Letter 9
 
0.5%
Close Punctuation 6
 
0.3%
Open Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 63
 
6.5%
년 58
 
6.0%
청 57
 
5.9%
지 46
 
4.8%
사 36
 
3.7%
원 35
 
3.6%
인 31
 
3.2%
천 19
 
2.0%
영 18
 
1.9%
기 17
 
1.8%
Other values (204) 588
60.7%
Decimal Number
ValueCountFrequency (%)
1 102
36.2%
2 75
26.6%
0 58
20.6%
3 21
 
7.4%
4 8
 
2.8%
8 4
 
1.4%
5 4
 
1.4%
6 4
 
1.4%
9 3
 
1.1%
7 3
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
20.0%
r 2
20.0%
u 2
20.0%
b 1
10.0%
y 1
10.0%
e 1
10.0%
t 1
10.0%
Uppercase Letter
ValueCountFrequency (%)
M 2
22.2%
F 2
22.2%
I 1
11.1%
A 1
11.1%
O 1
11.1%
R 1
11.1%
J 1
11.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 27
38.0%
Ⅲ 16
22.5%
Ⅳ 15
21.1%
Ⅱ 8
 
11.3%
Ⅴ 5
 
7.0%
Other Punctuation
ValueCountFrequency (%)
. 72
88.9%
· 4
 
4.9%
' 4
 
4.9%
, 1
 
1.2%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 213
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 968
50.4%
Common 863
44.9%
Latin 90
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 63
 
6.5%
년 58
 
6.0%
청 57
 
5.9%
지 46
 
4.8%
사 36
 
3.7%
원 35
 
3.6%
인 31
 
3.2%
천 19
 
2.0%
영 18
 
1.9%
기 17
 
1.8%
Other values (204) 588
60.7%
Latin
ValueCountFrequency (%)
Ⅰ 27
30.0%
Ⅲ 16
17.8%
Ⅳ 15
16.7%
Ⅱ 8
 
8.9%
Ⅴ 5
 
5.6%
o 2
 
2.2%
M 2
 
2.2%
r 2
 
2.2%
u 2
 
2.2%
F 2
 
2.2%
Other values (9) 9
 
10.0%
Common
ValueCountFrequency (%)
275
31.9%
- 213
24.7%
1 102
 
11.8%
2 75
 
8.7%
. 72
 
8.3%
0 58
 
6.7%
3 21
 
2.4%
4 8
 
0.9%
) 6
 
0.7%
( 6
 
0.7%
Other values (8) 27
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 968
50.4%
ASCII 878
45.7%
Number Forms 71
 
3.7%
None 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275
31.3%
- 213
24.3%
1 102
 
11.6%
2 75
 
8.5%
. 72
 
8.2%
0 58
 
6.6%
3 21
 
2.4%
4 8
 
0.9%
) 6
 
0.7%
( 6
 
0.7%
Other values (21) 42
 
4.8%
Hangul
ValueCountFrequency (%)
업 63
 
6.5%
년 58
 
6.0%
청 57
 
5.9%
지 46
 
4.8%
사 36
 
3.7%
원 35
 
3.6%
인 31
 
3.2%
천 19
 
2.0%
영 18
 
1.9%
기 17
 
1.8%
Other values (204) 588
60.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 27
38.0%
Ⅲ 16
22.5%
Ⅳ 15
21.1%
Ⅱ 8
 
11.3%
Ⅴ 5
 
7.0%
None
ValueCountFrequency (%)
· 4
100.0%

예산-국비_백만원
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1319.3239
Minimum0
Maximum51795
Zeros47
Zeros (%)66.2%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-01-28T17:44:18.267671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3286
95-th percentile2666.5
Maximum51795
Range51795
Interquartile range (IQR)286

Descriptive statistics

Standard deviation6399.9554
Coefficient of variation (CV)4.8509355
Kurtosis57.315493
Mean1319.3239
Median Absolute Deviation (MAD)0
Skewness7.3344365
Sum93672
Variance40959429
MonotonicityNot monotonic
2024-01-28T17:44:18.368712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 47
66.2%
50 2
 
2.8%
1017 1
 
1.4%
11500 1
 
1.4%
605 1
 
1.4%
2473 1
 
1.4%
90 1
 
1.4%
520 1
 
1.4%
12098 1
 
1.4%
608 1
 
1.4%
Other values (14) 14
 
19.7%
ValueCountFrequency (%)
0 47
66.2%
50 2
 
2.8%
64 1
 
1.4%
90 1
 
1.4%
194 1
 
1.4%
280 1
 
1.4%
292 1
 
1.4%
520 1
 
1.4%
540 1
 
1.4%
605 1
 
1.4%
ValueCountFrequency (%)
51795 1
1.4%
12098 1
1.4%
11500 1
1.4%
2860 1
1.4%
2473 1
1.4%
2275 1
1.4%
1736 1
1.4%
1129 1
1.4%
1035 1
1.4%
1017 1
1.4%

예산-시비_백만원
Real number (ℝ)

ZEROS 

Distinct58
Distinct (%)81.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean822.46479
Minimum0
Maximum15000
Zeros8
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-01-28T17:44:18.479987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q170
median194
Q3811.5
95-th percentile2224
Maximum15000
Range15000
Interquartile range (IQR)741.5

Descriptive statistics

Standard deviation1991.9116
Coefficient of variation (CV)2.4218806
Kurtosis38.177669
Mean822.46479
Median Absolute Deviation (MAD)184
Skewness5.73098
Sum58395
Variance3967711.6
MonotonicityNot monotonic
2024-01-28T17:44:18.597016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8
 
11.3%
100 3
 
4.2%
70 2
 
2.8%
200 2
 
2.8%
25 2
 
2.8%
120 2
 
2.8%
834 1
 
1.4%
950 1
 
1.4%
2100 1
 
1.4%
110 1
 
1.4%
Other values (48) 48
67.6%
ValueCountFrequency (%)
0 8
11.3%
10 1
 
1.4%
14 1
 
1.4%
20 1
 
1.4%
25 2
 
2.8%
27 1
 
1.4%
39 1
 
1.4%
50 1
 
1.4%
60 1
 
1.4%
70 2
 
2.8%
ValueCountFrequency (%)
15000 1
1.4%
6827 1
1.4%
3540 1
1.4%
2262 1
1.4%
2186 1
1.4%
2100 1
1.4%
2030 1
1.4%
1800 1
1.4%
1669 1
1.4%
1650 1
1.4%

예산-기타_백만원
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.323944
Minimum0
Maximum1430
Zeros62
Zeros (%)87.3%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-01-28T17:44:18.694979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile238
Maximum1430
Range1430
Interquartile range (IQR)0

Descriptive statistics

Standard deviation188.02688
Coefficient of variation (CV)4.4425652
Kurtosis43.841969
Mean42.323944
Median Absolute Deviation (MAD)0
Skewness6.2631743
Sum3005
Variance35354.108
MonotonicityNot monotonic
2024-01-28T17:44:18.780035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 62
87.3%
116 1
 
1.4%
60 1
 
1.4%
13 1
 
1.4%
1430 1
 
1.4%
420 1
 
1.4%
470 1
 
1.4%
111 1
 
1.4%
25 1
 
1.4%
360 1
 
1.4%
ValueCountFrequency (%)
0 62
87.3%
13 1
 
1.4%
25 1
 
1.4%
60 1
 
1.4%
111 1
 
1.4%
116 1
 
1.4%
360 1
 
1.4%
420 1
 
1.4%
470 1
 
1.4%
1430 1
 
1.4%
ValueCountFrequency (%)
1430 1
 
1.4%
470 1
 
1.4%
420 1
 
1.4%
360 1
 
1.4%
116 1
 
1.4%
111 1
 
1.4%
60 1
 
1.4%
25 1
 
1.4%
13 1
 
1.4%
0 62
87.3%

소관부서
Categorical

Distinct30
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size700.0 B
청년정책담당관
21 
창업벤처과
5 
관광마이스과
4 
문화정책과
4 
교육협력담당관
 
3
Other values (25)
34 

Length

Max length8
Median length7
Mean length6.028169
Min length4

Unique

Unique18 ?
Unique (%)25.4%

Sample

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

Common Values

ValueCountFrequency (%)
청년정책담당관 21
29.6%
창업벤처과 5
 
7.0%
관광마이스과 4
 
5.6%
문화정책과 4
 
5.6%
교육협력담당관 3
 
4.2%
인천도시공사 3
 
4.2%
아동정책과 3
 
4.2%
산업정책과 2
 
2.8%
농축산과 2
 
2.8%
경제정책과 2
 
2.8%
Other values (20) 22
31.0%

Length

2024-01-28T17:44:18.882530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청년정책담당관 21
29.6%
창업벤처과 5
 
7.0%
관광마이스과 4
 
5.6%
문화정책과 4
 
5.6%
교육협력담당관 3
 
4.2%
인천도시공사 3
 
4.2%
아동정책과 3
 
4.2%
경제정책과 2
 
2.8%
복지서비스과 2
 
2.8%
주택정책과 2
 
2.8%
Other values (20) 22
31.0%

Interactions

2024-01-28T17:44:17.226343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:44:16.791033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:44:16.999681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:44:17.296405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:44:16.855385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:44:17.068743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:44:17.379884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:44:16.926232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:44:17.151814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:44:18.955190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업명예산-국비_백만원예산-시비_백만원예산-기타_백만원소관부서
사업명1.0001.0001.0001.0001.000
예산-국비_백만원1.0001.0000.0000.2930.788
예산-시비_백만원1.0000.0001.0000.0000.637
예산-기타_백만원1.0000.2930.0001.0000.764
소관부서1.0000.7880.6370.7641.000
2024-01-28T17:44:19.036224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산-국비_백만원예산-시비_백만원예산-기타_백만원소관부서
예산-국비_백만원1.0000.0850.2380.406
예산-시비_백만원0.0851.000-0.0080.251
예산-기타_백만원0.238-0.0081.0000.395
소관부서0.4060.2510.3951.000

Missing values

2024-01-28T17:44:17.486754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:44:17.574027image/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

사업명예산-국비_백만원예산-시비_백만원예산-기타_백만원소관부서
0Ⅰ-1-1-01. 창업기업 청년일자리 지원 사업10178340청년정책담당관
1Ⅰ-1-1-02. 지역성장 도약기업 청년일자리 지원 사업2922390청년정책담당관
2Ⅰ-1-1-04. 인천 청년 면접지원(드림나래)02850청년정책담당관
3Ⅰ-1-1-05. 인천지역 대학일자리플러스센터 운영 지원9003000청년정책담당관
4Ⅰ-1-1-06. 인천 지역대학 취업 지원 사업 추진01750청년정책담당관
5Ⅰ-1-1-07. 창년실업문제 완화를 위한 청년의무 고용할당제 확대000청년정책담당관
6Ⅰ-1-1-08. 중소·중견기업 인천 청년 취업 지원 사업011120청년정책담당관
7Ⅰ-1-1-09. 인천 지역전략산업 청년일자리 지원 사업173616690청년정책담당관
8Ⅰ-1-1-10. 청년도전 지원사업1035770청년정책담당관
9Ⅰ-1-1-11. 중소기업 디지털 전환을 위한 청년일자리 지원사업7618230산업정책과
사업명예산-국비_백만원예산-시비_백만원예산-기타_백만원소관부서
61Ⅳ-3-4-01. 인천 재직청년 복지포인트 지원사업018000청년정책담당관
62Ⅳ-4-2-01. 청년문화창작소 운영01560문화정책과
63Ⅳ-4-2-02. 청년참여형 인천관광 활성화 사업01200관광마이스과
64Ⅳ-4-2-03. 인천 유니크베뉴 청년체험단0700관광마이스과
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