Overview

Dataset statistics

Number of variables10
Number of observations310
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.1 KiB
Average record size in memory89.4 B

Variable types

Text1
Numeric9

Dataset

Description2021년 기관별 성별영향평가 추진 결과 기관명,추진과제수,개선계획과제수,개선과제수,법령추진과제수,사업추진과제수,법령개선계획수립과제수,사업개선계획수립과제수,법령개선과제수,사업개선과제수에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15049346/fileData.do

Alerts

추진과제수 is highly overall correlated with 법령추진과제수 and 3 other fieldsHigh correlation
개선계획과제수 is highly overall correlated with 개선과제수 and 4 other fieldsHigh correlation
개선과제수 is highly overall correlated with 개선계획과제수 and 4 other fieldsHigh correlation
법령추진과제수 is highly overall correlated with 추진과제수 and 3 other fieldsHigh correlation
사업추진과제수 is highly overall correlated with 추진과제수 and 1 other fieldsHigh correlation
법령개선계획수립과제수 is highly overall correlated with 추진과제수 and 4 other fieldsHigh correlation
사업개선계획수립과제수 is highly overall correlated with 개선계획과제수 and 2 other fieldsHigh correlation
법령개선과제수 is highly overall correlated with 추진과제수 and 4 other fieldsHigh correlation
사업개선과제수 is highly overall correlated with 개선계획과제수 and 2 other fieldsHigh correlation
기관명 has unique valuesUnique
개선계획과제수 has 35 (11.3%) zerosZeros
개선과제수 has 36 (11.6%) zerosZeros
사업추진과제수 has 10 (3.2%) zerosZeros
법령개선계획수립과제수 has 79 (25.5%) zerosZeros
사업개선계획수립과제수 has 122 (39.4%) zerosZeros
법령개선과제수 has 80 (25.8%) zerosZeros
사업개선과제수 has 125 (40.3%) zerosZeros

Reproduction

Analysis started2023-12-12 16:59:40.565835
Analysis finished2023-12-12 16:59:49.513484
Duration8.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Text

UNIQUE 

Distinct310
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-13T01:59:49.717882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18
Mean length7.4774194
Min length3

Characters and Unicode

Total characters2318
Distinct characters202
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)100.0%

Sample

1st row5.18민주화운동진상규명조사위원회
2nd row가습기살균제사건과4.16세월호참사특별조사위원회
3rd row강원도
4th row강원도 강릉시
5th row강원도 고성군
ValueCountFrequency (%)
경기도 32
 
6.0%
서울특별시 26
 
4.9%
경상북도 24
 
4.5%
전라남도 23
 
4.3%
경상남도 19
 
3.5%
강원도 19
 
3.5%
부산광역시 17
 
3.2%
충청남도 16
 
3.0%
전라북도 15
 
2.8%
충청북도 12
 
2.2%
Other values (278) 333
62.1%
2023-12-13T01:59:50.229323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
226
 
9.7%
도 176
 
7.6%
시 167
 
7.2%
군 86
 
3.7%
경 84
 
3.6%
구 84
 
3.6%
광 75
 
3.2%
남 73
 
3.1%
청 69
 
3.0%
역 61
 
2.6%
Other values (192) 1217
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2084
89.9%
Space Separator 226
 
9.7%
Decimal Number 6
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 176
 
8.4%
시 167
 
8.0%
군 86
 
4.1%
경 84
 
4.0%
구 84
 
4.0%
광 75
 
3.6%
남 73
 
3.5%
청 69
 
3.3%
역 61
 
2.9%
북 60
 
2.9%
Other values (185) 1149
55.1%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
6 1
16.7%
4 1
16.7%
5 1
16.7%
8 1
16.7%
Space Separator
ValueCountFrequency (%)
226
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2084
89.9%
Common 234
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 176
 
8.4%
시 167
 
8.0%
군 86
 
4.1%
경 84
 
4.0%
구 84
 
4.0%
광 75
 
3.6%
남 73
 
3.5%
청 69
 
3.3%
역 61
 
2.9%
북 60
 
2.9%
Other values (185) 1149
55.1%
Common
ValueCountFrequency (%)
226
96.6%
1 2
 
0.9%
. 2
 
0.9%
6 1
 
0.4%
4 1
 
0.4%
5 1
 
0.4%
8 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2084
89.9%
ASCII 234
 
10.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
226
96.6%
1 2
 
0.9%
. 2
 
0.9%
6 1
 
0.4%
4 1
 
0.4%
5 1
 
0.4%
8 1
 
0.4%
Hangul
ValueCountFrequency (%)
도 176
 
8.4%
시 167
 
8.0%
군 86
 
4.1%
경 84
 
4.0%
구 84
 
4.0%
광 75
 
3.6%
남 73
 
3.5%
청 69
 
3.3%
역 61
 
2.9%
북 60
 
2.9%
Other values (185) 1149
55.1%

추진과제수
Real number (ℝ)

HIGH CORRELATION 

Distinct148
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.425806
Minimum1
Maximum349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:50.417263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.45
Q172.25
median96
Q3121
95-th percentile193.1
Maximum349
Range348
Interquartile range (IQR)48.75

Descriptive statistics

Standard deviation51.939652
Coefficient of variation (CV)0.5277036
Kurtosis2.7146101
Mean98.425806
Median Absolute Deviation (MAD)24
Skewness0.87986192
Sum30512
Variance2697.7275
MonotonicityNot monotonic
2023-12-13T01:59:50.597106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
91 7
 
2.3%
87 6
 
1.9%
109 6
 
1.9%
86 6
 
1.9%
102 6
 
1.9%
124 5
 
1.6%
90 5
 
1.6%
98 5
 
1.6%
107 5
 
1.6%
72 5
 
1.6%
Other values (138) 254
81.9%
ValueCountFrequency (%)
1 4
1.3%
2 2
0.6%
3 1
 
0.3%
4 1
 
0.3%
5 3
1.0%
8 1
 
0.3%
9 2
0.6%
10 1
 
0.3%
11 1
 
0.3%
12 1
 
0.3%
ValueCountFrequency (%)
349 1
0.3%
300 1
0.3%
289 1
0.3%
256 1
0.3%
248 1
0.3%
234 1
0.3%
223 1
0.3%
222 1
0.3%
217 2
0.6%
214 1
0.3%

개선계획과제수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9709677
Minimum0
Maximum47
Zeros35
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:50.787920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q313.75
95-th percentile27
Maximum47
Range47
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation8.9700578
Coefficient of variation (CV)0.99989857
Kurtosis1.4212964
Mean8.9709677
Median Absolute Deviation (MAD)5
Skewness1.2891448
Sum2781
Variance80.461938
MonotonicityNot monotonic
2023-12-13T01:59:50.964051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 39
 
12.6%
0 35
 
11.3%
2 20
 
6.5%
7 20
 
6.5%
3 18
 
5.8%
4 17
 
5.5%
5 15
 
4.8%
6 13
 
4.2%
9 12
 
3.9%
10 11
 
3.5%
Other values (26) 110
35.5%
ValueCountFrequency (%)
0 35
11.3%
1 39
12.6%
2 20
6.5%
3 18
5.8%
4 17
5.5%
5 15
 
4.8%
6 13
 
4.2%
7 20
6.5%
8 7
 
2.3%
9 12
 
3.9%
ValueCountFrequency (%)
47 1
 
0.3%
42 1
 
0.3%
36 2
0.6%
34 1
 
0.3%
32 2
0.6%
31 4
1.3%
30 2
0.6%
29 1
 
0.3%
27 3
1.0%
26 3
1.0%

개선과제수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8096774
Minimum0
Maximum47
Zeros36
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:51.120785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q313
95-th percentile26.55
Maximum47
Range47
Interquartile range (IQR)11

Descriptive statistics

Standard deviation8.8225533
Coefficient of variation (CV)1.0014616
Kurtosis1.4146655
Mean8.8096774
Median Absolute Deviation (MAD)5
Skewness1.2809808
Sum2731
Variance77.837446
MonotonicityNot monotonic
2023-12-13T01:59:51.251298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 39
 
12.6%
0 36
 
11.6%
2 21
 
6.8%
7 20
 
6.5%
3 19
 
6.1%
4 18
 
5.8%
5 13
 
4.2%
9 13
 
4.2%
10 11
 
3.5%
6 11
 
3.5%
Other values (26) 109
35.2%
ValueCountFrequency (%)
0 36
11.6%
1 39
12.6%
2 21
6.8%
3 19
6.1%
4 18
5.8%
5 13
 
4.2%
6 11
 
3.5%
7 20
6.5%
8 7
 
2.3%
9 13
 
4.2%
ValueCountFrequency (%)
47 1
 
0.3%
41 1
 
0.3%
36 1
 
0.3%
34 1
 
0.3%
32 2
0.6%
31 2
0.6%
30 3
1.0%
29 2
0.6%
27 3
1.0%
26 4
1.3%

법령추진과제수
Real number (ℝ)

HIGH CORRELATION 

Distinct124
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.845161
Minimum0
Maximum269
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:51.413748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.45
Q154
median74
Q392
95-th percentile138.55
Maximum269
Range269
Interquartile range (IQR)38

Descriptive statistics

Standard deviation37.915874
Coefficient of variation (CV)0.51345103
Kurtosis2.4962543
Mean73.845161
Median Absolute Deviation (MAD)20
Skewness0.72441975
Sum22892
Variance1437.6135
MonotonicityNot monotonic
2023-12-13T01:59:51.563606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71 10
 
3.2%
59 10
 
3.2%
74 9
 
2.9%
81 7
 
2.3%
77 7
 
2.3%
79 6
 
1.9%
52 6
 
1.9%
54 6
 
1.9%
91 6
 
1.9%
92 6
 
1.9%
Other values (114) 237
76.5%
ValueCountFrequency (%)
0 1
 
0.3%
1 4
1.3%
2 2
0.6%
3 2
0.6%
4 1
 
0.3%
5 2
0.6%
6 1
 
0.3%
7 1
 
0.3%
9 2
0.6%
10 2
0.6%
ValueCountFrequency (%)
269 1
0.3%
216 1
0.3%
197 1
0.3%
172 1
0.3%
161 1
0.3%
158 2
0.6%
157 1
0.3%
153 1
0.3%
150 1
0.3%
146 2
0.6%

사업추진과제수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct65
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.580645
Minimum0
Maximum199
Zeros10
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:51.719212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q116
median21
Q328
95-th percentile59
Maximum199
Range199
Interquartile range (IQR)12

Descriptive statistics

Standard deviation21.210265
Coefficient of variation (CV)0.86288481
Kurtosis23.330565
Mean24.580645
Median Absolute Deviation (MAD)6
Skewness3.6707168
Sum7620
Variance449.87535
MonotonicityNot monotonic
2023-12-13T01:59:51.866265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 27
 
8.7%
26 17
 
5.5%
21 16
 
5.2%
24 15
 
4.8%
2 14
 
4.5%
28 13
 
4.2%
18 12
 
3.9%
17 12
 
3.9%
23 11
 
3.5%
1 10
 
3.2%
Other values (55) 163
52.6%
ValueCountFrequency (%)
0 10
3.2%
1 10
3.2%
2 14
4.5%
3 4
 
1.3%
4 3
 
1.0%
5 3
 
1.0%
6 4
 
1.3%
7 3
 
1.0%
8 1
 
0.3%
9 1
 
0.3%
ValueCountFrequency (%)
199 1
0.3%
176 1
0.3%
108 1
0.3%
98 1
0.3%
86 1
0.3%
84 1
0.3%
79 2
0.6%
71 1
0.3%
70 1
0.3%
67 1
0.3%

법령개선계획수립과제수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3741935
Minimum0
Maximum32
Zeros79
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:52.016143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q38
95-th percentile17.55
Maximum32
Range32
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.1250701
Coefficient of variation (CV)1.1397189
Kurtosis2.376489
Mean5.3741935
Median Absolute Deviation (MAD)3
Skewness1.5471047
Sum1666
Variance37.516484
MonotonicityNot monotonic
2023-12-13T01:59:52.158377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 79
25.5%
2 29
 
9.4%
1 27
 
8.7%
3 23
 
7.4%
4 22
 
7.1%
7 19
 
6.1%
5 17
 
5.5%
8 14
 
4.5%
11 12
 
3.9%
6 10
 
3.2%
Other values (18) 58
18.7%
ValueCountFrequency (%)
0 79
25.5%
1 27
 
8.7%
2 29
 
9.4%
3 23
 
7.4%
4 22
 
7.1%
5 17
 
5.5%
6 10
 
3.2%
7 19
 
6.1%
8 14
 
4.5%
9 8
 
2.6%
ValueCountFrequency (%)
32 1
 
0.3%
28 1
 
0.3%
27 2
0.6%
25 1
 
0.3%
24 1
 
0.3%
22 2
0.6%
21 2
0.6%
20 2
0.6%
19 1
 
0.3%
18 3
1.0%

사업개선계획수립과제수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5967742
Minimum0
Maximum31
Zeros122
Zeros (%)39.4%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:52.278765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile15
Maximum31
Range31
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.6047243
Coefficient of variation (CV)1.5582642
Kurtosis5.443237
Mean3.5967742
Median Absolute Deviation (MAD)1
Skewness2.2353584
Sum1115
Variance31.412935
MonotonicityNot monotonic
2023-12-13T01:59:52.432530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 122
39.4%
1 52
16.8%
2 24
 
7.7%
4 18
 
5.8%
3 17
 
5.5%
5 9
 
2.9%
7 8
 
2.6%
6 7
 
2.3%
8 7
 
2.3%
11 5
 
1.6%
Other values (17) 41
 
13.2%
ValueCountFrequency (%)
0 122
39.4%
1 52
16.8%
2 24
 
7.7%
3 17
 
5.5%
4 18
 
5.8%
5 9
 
2.9%
6 7
 
2.3%
7 8
 
2.6%
8 7
 
2.3%
9 4
 
1.3%
ValueCountFrequency (%)
31 1
 
0.3%
30 1
 
0.3%
28 1
 
0.3%
26 1
 
0.3%
23 1
 
0.3%
21 1
 
0.3%
20 2
0.6%
19 1
 
0.3%
18 3
1.0%
17 1
 
0.3%

법령개선과제수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3290323
Minimum0
Maximum32
Zeros80
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:52.565541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q38
95-th percentile17.55
Maximum32
Range32
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.1181566
Coefficient of variation (CV)1.1480802
Kurtosis2.4396146
Mean5.3290323
Median Absolute Deviation (MAD)3
Skewness1.5654636
Sum1652
Variance37.43184
MonotonicityNot monotonic
2023-12-13T01:59:52.689801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 80
25.8%
2 29
 
9.4%
1 27
 
8.7%
3 25
 
8.1%
7 20
 
6.5%
4 19
 
6.1%
5 17
 
5.5%
8 14
 
4.5%
11 11
 
3.5%
6 11
 
3.5%
Other values (18) 57
18.4%
ValueCountFrequency (%)
0 80
25.8%
1 27
 
8.7%
2 29
 
9.4%
3 25
 
8.1%
4 19
 
6.1%
5 17
 
5.5%
6 11
 
3.5%
7 20
 
6.5%
8 14
 
4.5%
9 7
 
2.3%
ValueCountFrequency (%)
32 1
 
0.3%
28 1
 
0.3%
27 2
0.6%
25 1
 
0.3%
24 1
 
0.3%
22 2
0.6%
21 2
0.6%
20 2
0.6%
19 1
 
0.3%
18 3
1.0%

사업개선과제수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4806452
Minimum0
Maximum30
Zeros125
Zeros (%)40.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-13T01:59:52.805293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile14
Maximum30
Range30
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.4212168
Coefficient of variation (CV)1.5575322
Kurtosis5.3787932
Mean3.4806452
Median Absolute Deviation (MAD)1
Skewness2.2110776
Sum1079
Variance29.389592
MonotonicityNot monotonic
2023-12-13T01:59:52.927804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 125
40.3%
1 51
16.5%
2 24
 
7.7%
3 18
 
5.8%
4 17
 
5.5%
7 8
 
2.6%
8 8
 
2.6%
5 8
 
2.6%
14 8
 
2.6%
6 6
 
1.9%
Other values (16) 37
 
11.9%
ValueCountFrequency (%)
0 125
40.3%
1 51
16.5%
2 24
 
7.7%
3 18
 
5.8%
4 17
 
5.5%
5 8
 
2.6%
6 6
 
1.9%
7 8
 
2.6%
8 8
 
2.6%
9 3
 
1.0%
ValueCountFrequency (%)
30 2
0.6%
27 1
0.3%
23 1
0.3%
22 1
0.3%
21 1
0.3%
20 1
0.3%
19 1
0.3%
18 2
0.6%
17 1
0.3%
16 2
0.6%

Interactions

2023-12-13T01:59:48.154294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:40.934279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.986222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.695228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.288959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.073288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.988384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.900085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.810708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:48.265300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.017449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.063785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.763291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.360412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.182156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.083946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.008373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:47.237908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:48.390059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.092379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.142895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.825025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.426937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.278512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.179435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.109894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:47.338804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:48.483679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.438111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.231107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.884044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.503052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.375105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.263032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.194194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:47.458215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:48.613061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.515731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.317615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.951064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.598425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.472191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.349296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.283873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:47.563919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:48.759313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.611729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.410414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.023892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.754408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.588143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.480093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.375338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:47.693798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:48.877831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.726281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.479745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.089126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.833659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.706268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.597546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.466996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:47.817448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:49.007544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.827589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.550938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.157373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.916776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.806091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.690676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.564259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:47.933613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:49.147739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:41.900922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:42.626996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.222233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:43.994581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:44.893873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:45.806872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:46.695707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:59:48.051038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:59:53.018485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
추진과제수개선계획과제수개선과제수법령추진과제수사업추진과제수법령개선계획수립과제수사업개선계획수립과제수법령개선과제수사업개선과제수
추진과제수1.0000.7570.7310.9550.8620.5820.5450.5690.397
개선계획과제수0.7571.0000.9990.6490.6790.8430.8790.8400.757
개선과제수0.7310.9991.0000.5490.6810.8450.8600.8450.770
법령추진과제수0.9550.6490.5491.0000.5920.4500.7760.4100.446
사업추진과제수0.8620.6790.6810.5921.0000.3620.4490.3650.437
법령개선계획수립과제수0.5820.8430.8450.4500.3621.0000.1001.0000.237
사업개선계획수립과제수0.5450.8790.8600.7760.4490.1001.0000.0000.931
법령개선과제수0.5690.8400.8450.4100.3651.0000.0001.0000.193
사업개선과제수0.3970.7570.7700.4460.4370.2370.9310.1931.000
2023-12-13T01:59:53.493598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
추진과제수개선계획과제수개선과제수법령추진과제수사업추진과제수법령개선계획수립과제수사업개선계획수립과제수법령개선과제수사업개선과제수
추진과제수1.0000.4460.4420.9600.7330.5390.0750.5350.063
개선계획과제수0.4461.0000.9960.4270.3820.8550.6230.8500.620
개선과제수0.4420.9961.0000.4230.3790.8560.6120.8550.622
법령추진과제수0.9600.4270.4231.0000.5650.5230.0660.5190.056
사업추진과제수0.7330.3820.3790.5651.0000.4300.0660.4310.052
법령개선계획수립과제수0.5390.8550.8560.5230.4301.0000.2060.9980.210
사업개선계획수립과제수0.0750.6230.6120.0660.0660.2061.0000.2000.987
법령개선과제수0.5350.8500.8550.5190.4310.9980.2001.0000.206
사업개선과제수0.0630.6200.6220.0560.0520.2100.9870.2061.000

Missing values

2023-12-13T01:59:49.287090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:59:49.434990image/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

기관명추진과제수개선계획과제수개선과제수법령추진과제수사업추진과제수법령개선계획수립과제수사업개선계획수립과제수법령개선과제수사업개선과제수
05.18민주화운동진상규명조사위원회200200000
1가습기살균제사건과4.16세월호참사특별조사위원회100100000
2강원도1333232745911211121
3강원도 강릉시1236693305151
4강원도 고성군129252510920214214
5강원도 동해시8621217115147147
6강원도 삼척시1116691205151
7강원도 속초시1152929922314151415
8강원도 양구군11700102150000
9강원도 양양군8422226024166166
기관명추진과제수개선계획과제수개선과제수법령추진과제수사업추진과제수법령개선계획수립과제수사업개선계획수립과제수법령개선과제수사업개선과제수
300충청북도 충주시1241191330101
301충청북도교육청510036150000
302통계청811620101
303통일부12111020101
304특허청21111920101
305해양경찰청20221820202
306해양수산부9011117812110110
307행정안전부1681616158109797
308행정중심복합도시건설청200110000
309환경부94998776363