Overview

Dataset statistics

Number of variables6
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory56.0 B

Variable types

Categorical2
Text1
Numeric3

Dataset

Description용인도시공사의 연도별 경영평가 지표 점수로 평가대상연도 기준 2022년부터 제공하고 있습니다. 연 주기로 갱신되는 자료입니다.
Author용인도시공사
URLhttps://www.data.go.kr/data/15114308/fileData.do

Alerts

배점 is highly overall correlated with 득점 and 1 other fieldsHigh correlation
득점 is highly overall correlated with 배점 and 1 other fieldsHigh correlation
평가대상연도 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 배점 and 2 other fieldsHigh correlation
배점 has 4 (12.1%) zerosZeros
득점 has 4 (12.1%) zerosZeros

Reproduction

Analysis started2023-12-13 00:32:45.893644
Analysis finished2023-12-13 00:32:47.012219
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

평가대상연도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
2022
17 
2023
16 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 17
51.5%
2023 16
48.5%

Length

2023-12-13T09:32:47.058622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:32:47.130889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 17
51.5%
2023 16
48.5%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
경영성과
12 
경영관리
10 
지속가능경영
5 
사회적가치
5 
코로나19 대응지표
 
1

Length

Max length10
Median length4
Mean length4.6363636
Min length4

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
경영성과 12
36.4%
경영관리 10
30.3%
지속가능경영 5
15.2%
사회적가치 5
15.2%
코로나19 대응지표 1
 
3.0%

Length

2023-12-13T09:32:47.210384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:32:47.291230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경영성과 12
35.3%
경영관리 10
29.4%
지속가능경영 5
14.7%
사회적가치 5
14.7%
코로나19 1
 
2.9%
대응지표 1
 
2.9%

지표명
Text

Distinct18
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T09:32:47.450508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length6.8181818
Min length4

Characters and Unicode

Total characters225
Distinct characters74
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.1%

Sample

1st row경영층의 리더십
2nd row전략경영
3rd row혁신성과
4th row조직·인사관리
5th row재무관리
ValueCountFrequency (%)
및 5
 
9.4%
경영층의 2
 
3.8%
일자리 2
 
3.8%
시설유지관리 2
 
3.8%
지역상생발전 2
 
3.8%
재난·안전관리 2
 
3.8%
윤리경영 2
 
3.8%
참여 2
 
3.8%
소통 2
 
3.8%
양립 2
 
3.8%
Other values (17) 30
56.6%
2023-12-13T09:32:47.689416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
8.9%
리 16
 
7.1%
관 10
 
4.4%
경 6
 
2.7%
영 6
 
2.7%
· 6
 
2.7%
사 6
 
2.7%
전 6
 
2.7%
및 5
 
2.2%
지 5
 
2.2%
Other values (64) 139
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 197
87.6%
Space Separator 20
 
8.9%
Other Punctuation 6
 
2.7%
Decimal Number 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 16
 
8.1%
관 10
 
5.1%
경 6
 
3.0%
영 6
 
3.0%
사 6
 
3.0%
전 6
 
3.0%
및 5
 
2.5%
지 5
 
2.5%
성 5
 
2.5%
설 4
 
2.0%
Other values (61) 128
65.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
· 6
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 197
87.6%
Common 28
 
12.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 16
 
8.1%
관 10
 
5.1%
경 6
 
3.0%
영 6
 
3.0%
사 6
 
3.0%
전 6
 
3.0%
및 5
 
2.5%
지 5
 
2.5%
성 5
 
2.5%
설 4
 
2.0%
Other values (61) 128
65.0%
Common
ValueCountFrequency (%)
20
71.4%
· 6
 
21.4%
1 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 197
87.6%
ASCII 22
 
9.8%
None 6
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
90.9%
1 2
 
9.1%
Hangul
ValueCountFrequency (%)
리 16
 
8.1%
관 10
 
5.1%
경 6
 
3.0%
영 6
 
3.0%
사 6
 
3.0%
전 6
 
3.0%
및 5
 
2.5%
지 5
 
2.5%
성 5
 
2.5%
설 4
 
2.0%
Other values (61) 128
65.0%
None
ValueCountFrequency (%)
· 6
100.0%

배점
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0606061
Minimum0
Maximum22
Zeros4
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T09:32:47.777010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median5
Q38
95-th percentile10
Maximum22
Range22
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.9681497
Coefficient of variation (CV)0.6547447
Kurtosis7.4921466
Mean6.0606061
Median Absolute Deviation (MAD)1
Skewness1.7603161
Sum200
Variance15.746212
MonotonicityNot monotonic
2023-12-13T09:32:47.852298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
5 12
36.4%
6 5
15.2%
0 4
 
12.1%
8 4
 
12.1%
9 3
 
9.1%
10 2
 
6.1%
22 1
 
3.0%
7 1
 
3.0%
2 1
 
3.0%
ValueCountFrequency (%)
0 4
 
12.1%
2 1
 
3.0%
5 12
36.4%
6 5
15.2%
7 1
 
3.0%
8 4
 
12.1%
9 3
 
9.1%
10 2
 
6.1%
22 1
 
3.0%
ValueCountFrequency (%)
22 1
 
3.0%
10 2
 
6.1%
9 3
 
9.1%
8 4
 
12.1%
7 1
 
3.0%
6 5
15.2%
5 12
36.4%
2 1
 
3.0%
0 4
 
12.1%

평점(100점 환산)
Real number (ℝ)

Distinct26
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.116667
Minimum73.2
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T09:32:47.935922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73.2
5-th percentile78.692
Q186.77
median91.2
Q398.89
95-th percentile100
Maximum100
Range26.8
Interquartile range (IQR)12.12

Descriptive statistics

Standard deviation7.4125968
Coefficient of variation (CV)0.081352809
Kurtosis-0.28624734
Mean91.116667
Median Absolute Deviation (MAD)5.6
Skewness-0.48036989
Sum3006.85
Variance54.946592
MonotonicityNot monotonic
2023-12-13T09:32:48.024795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
100.0 7
21.2%
87.3 2
 
6.1%
89.0 1
 
3.0%
90.8 1
 
3.0%
93.5 1
 
3.0%
81.52 1
 
3.0%
86.17 1
 
3.0%
98.89 1
 
3.0%
89.6 1
 
3.0%
99.6 1
 
3.0%
Other values (16) 16
48.5%
ValueCountFrequency (%)
73.2 1
3.0%
75.83 1
3.0%
80.6 1
3.0%
81.52 1
3.0%
84.0 1
3.0%
85.2 1
3.0%
85.6 1
3.0%
86.17 1
3.0%
86.77 1
3.0%
87.01 1
3.0%
ValueCountFrequency (%)
100.0 7
21.2%
99.6 1
 
3.0%
98.89 1
 
3.0%
98.75 1
 
3.0%
96.67 1
 
3.0%
93.5 1
 
3.0%
93.0 1
 
3.0%
92.38 1
 
3.0%
91.89 1
 
3.0%
91.67 1
 
3.0%

득점
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4648485
Minimum0
Maximum19.09
Zeros4
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T09:32:48.111871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.26
median4.65
Q37.39
95-th percentile8.798
Maximum19.09
Range19.09
Interquartile range (IQR)3.13

Descriptive statistics

Standard deviation3.5353891
Coefficient of variation (CV)0.64693268
Kurtosis6.0516285
Mean5.4648485
Median Absolute Deviation (MAD)1.35
Skewness1.5082865
Sum180.34
Variance12.498976
MonotonicityNot monotonic
2023-12-13T09:32:48.214952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 4
 
12.1%
8.73 2
 
6.1%
6.0 2
 
6.1%
4.45 1
 
3.0%
4.26 1
 
3.0%
7.48 1
 
3.0%
2.0 1
 
3.0%
6.52 1
 
3.0%
7.0 1
 
3.0%
5.17 1
 
3.0%
Other values (18) 18
54.5%
ValueCountFrequency (%)
0.0 4
12.1%
2.0 1
 
3.0%
3.66 1
 
3.0%
4.03 1
 
3.0%
4.2 1
 
3.0%
4.26 1
 
3.0%
4.28 1
 
3.0%
4.45 1
 
3.0%
4.47 1
 
3.0%
4.48 1
 
3.0%
ValueCountFrequency (%)
19.09 1
3.0%
8.9 1
3.0%
8.73 2
6.1%
8.27 1
3.0%
8.25 1
3.0%
7.9 1
3.0%
7.48 1
3.0%
7.39 1
3.0%
7.0 1
3.0%
6.52 1
3.0%

Interactions

2023-12-13T09:32:46.693008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:46.333652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:46.511684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:46.754138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:46.387356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:46.566624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:46.816433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:46.445523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:46.624269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:32:48.296322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가대상연도구분지표명배점평점(100점 환산)득점
평가대상연도1.0000.6370.0000.1390.1690.304
구분0.6371.0000.7240.9230.5040.718
지표명0.0000.7241.0000.9170.7660.898
배점0.1390.9230.9171.0000.3810.908
평점(100점 환산)0.1690.5040.7660.3811.0000.386
득점0.3040.7180.8980.9080.3861.000
2023-12-13T09:32:48.372322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분평가대상연도
구분1.0000.726
평가대상연도0.7261.000
2023-12-13T09:32:48.442230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배점평점(100점 환산)득점평가대상연도구분
배점1.000-0.1130.9620.1490.613
평점(100점 환산)-0.1131.0000.0670.1200.283
득점0.9620.0671.0000.1920.571
평가대상연도0.1490.1200.1921.0000.726
구분0.6130.2830.5710.7261.000

Missing values

2023-12-13T09:32:46.905987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:32:46.982115image/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

평가대상연도구분지표명배점평점(100점 환산)득점
02022지속가능경영경영층의 리더십589.04.45
12022지속가능경영전략경영593.04.65
22022지속가능경영혁신성과675.834.55
32022지속가능경영조직·인사관리573.23.66
42022지속가능경영재무관리696.675.8
52022경영성과1인당 시설관리실적0100.00.0
62022경영성과사업수입0100.00.0
72022경영성과시설유지관리589.44.47
82022경영성과노동생산성0100.00.0
92022경영성과대행사업비절감률087.010.0
평가대상연도구분지표명배점평점(100점 환산)득점
232023경영관리소통 및 참여599.64.98
242023경영관리윤리경영589.64.48
252023경영관리재난·안전관리1087.38.73
262023경영관리지역상생발전998.898.9
272023경영성과시설유지관리 및 활성화686.175.17
282023경영성과사업수입7100.07.0
292023경영성과1인당 시설관리실적6100.06.0
302023경영성과대행사업비절감률881.526.52
312023경영성과노동생산성2100.02.0
322023경영성과고객만족도893.57.48