Overview

Dataset statistics

Number of variables14
Number of observations69
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.5 KiB
Average record size in memory125.9 B

Variable types

DateTime1
Numeric10
Categorical3

Dataset

Description월별 청구건수, 전부공개, 부분공개, 비공개, 공개율(%), 청구취하, 기관이송, 내부종결, 민원이첩, 정보부존재, 진정·질의, 미결정 건수를 제공합니다.
URLhttps://www.data.go.kr/data/3081188/fileData.do

Alerts

민원이첩 has constant value ""Constant
데이터기준일자 has constant value ""Constant
청구건수 is highly overall correlated with 전부공개 and 3 other fieldsHigh correlation
전부공개 is highly overall correlated with 청구건수 and 2 other fieldsHigh correlation
부분공개 is highly overall correlated with 청구건수 and 2 other fieldsHigh correlation
비공개 is highly overall correlated with 공개율High correlation
공개율 is highly overall correlated with 비공개High correlation
정보부존재 is highly overall correlated with 청구건수 and 1 other fieldsHigh correlation
진정질의 is highly overall correlated with 전부공개High correlation
미결정 is highly overall correlated with 청구건수 and 2 other fieldsHigh correlation
미결정 is highly imbalanced (86.2%)Imbalance
공개율 has 1 (1.4%) missing valuesMissing
정보공개처리연월 has unique valuesUnique
비공개 has 6 (8.7%) zerosZeros
진정질의 has 38 (55.1%) zerosZeros

Reproduction

Analysis started2023-12-12 11:32:24.293831
Analysis finished2023-12-12 11:32:42.674933
Duration18.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정보공개처리연월
Date

UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum2018-01-18 00:00:00
Maximum2023-08-06 00:00:00
2023-12-12T20:32:42.812826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:43.057835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

청구건수
Real number (ℝ)

HIGH CORRELATION 

Distinct58
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.27536
Minimum43
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:43.308684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile152
Q1196
median230
Q3259
95-th percentile308.4
Maximum336
Range293
Interquartile range (IQR)63

Descriptive statistics

Standard deviation55.301283
Coefficient of variation (CV)0.24439816
Kurtosis1.148105
Mean226.27536
Median Absolute Deviation (MAD)34
Skewness-0.58537523
Sum15613
Variance3058.2319
MonotonicityNot monotonic
2023-12-12T20:32:43.533288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
248 3
 
4.3%
209 2
 
2.9%
213 2
 
2.9%
214 2
 
2.9%
152 2
 
2.9%
279 2
 
2.9%
296 2
 
2.9%
266 2
 
2.9%
259 2
 
2.9%
199 2
 
2.9%
Other values (48) 48
69.6%
ValueCountFrequency (%)
43 1
1.4%
94 1
1.4%
95 1
1.4%
152 2
2.9%
158 1
1.4%
159 1
1.4%
164 1
1.4%
169 1
1.4%
173 1
1.4%
174 1
1.4%
ValueCountFrequency (%)
336 1
1.4%
335 1
1.4%
325 1
1.4%
314 1
1.4%
300 1
1.4%
298 1
1.4%
296 2
2.9%
287 1
1.4%
279 2
2.9%
273 1
1.4%

전부공개
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140.21739
Minimum11
Maximum242
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:43.776168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile78.6
Q1120
median137
Q3170
95-th percentile192
Maximum242
Range231
Interquartile range (IQR)50

Descriptive statistics

Standard deviation39.631712
Coefficient of variation (CV)0.28264477
Kurtosis1.2348243
Mean140.21739
Median Absolute Deviation (MAD)23
Skewness-0.31550705
Sum9675
Variance1570.6726
MonotonicityNot monotonic
2023-12-12T20:32:44.016732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
174 3
 
4.3%
120 3
 
4.3%
128 3
 
4.3%
127 2
 
2.9%
142 2
 
2.9%
168 2
 
2.9%
116 2
 
2.9%
112 2
 
2.9%
129 2
 
2.9%
177 2
 
2.9%
Other values (43) 46
66.7%
ValueCountFrequency (%)
11 1
1.4%
51 1
1.4%
63 1
1.4%
75 1
1.4%
84 2
2.9%
92 1
1.4%
93 1
1.4%
98 1
1.4%
102 1
1.4%
112 2
2.9%
ValueCountFrequency (%)
242 1
1.4%
230 1
1.4%
206 1
1.4%
192 2
2.9%
191 1
1.4%
186 1
1.4%
180 1
1.4%
179 1
1.4%
178 1
1.4%
177 2
2.9%

부분공개
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.985507
Minimum3
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:44.240888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3.4
Q18
median9
Q315
95-th percentile33.8
Maximum43
Range40
Interquartile range (IQR)7

Descriptive statistics

Standard deviation9.5432341
Coefficient of variation (CV)0.73491423
Kurtosis2.4377889
Mean12.985507
Median Absolute Deviation (MAD)3
Skewness1.6960027
Sum896
Variance91.073316
MonotonicityNot monotonic
2023-12-12T20:32:44.465573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
9 10
14.5%
8 9
13.0%
7 5
 
7.2%
10 4
 
5.8%
4 4
 
5.8%
3 4
 
5.8%
12 4
 
5.8%
29 4
 
5.8%
19 4
 
5.8%
11 3
 
4.3%
Other values (14) 18
26.1%
ValueCountFrequency (%)
3 4
 
5.8%
4 4
 
5.8%
5 1
 
1.4%
6 3
 
4.3%
7 5
7.2%
8 9
13.0%
9 10
14.5%
10 4
 
5.8%
11 3
 
4.3%
12 4
 
5.8%
ValueCountFrequency (%)
43 1
 
1.4%
42 1
 
1.4%
41 1
 
1.4%
37 1
 
1.4%
29 4
5.8%
27 1
 
1.4%
22 1
 
1.4%
21 1
 
1.4%
19 4
5.8%
17 1
 
1.4%

비공개
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7536232
Minimum0
Maximum14
Zeros6
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:44.674613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q35
95-th percentile8.2
Maximum14
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.697525
Coefficient of variation (CV)0.71864565
Kurtosis2.2141948
Mean3.7536232
Median Absolute Deviation (MAD)2
Skewness1.084628
Sum259
Variance7.2766411
MonotonicityNot monotonic
2023-12-12T20:32:44.841011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 13
18.8%
5 13
18.8%
1 8
11.6%
3 8
11.6%
6 8
11.6%
4 6
8.7%
0 6
8.7%
7 3
 
4.3%
9 2
 
2.9%
14 1
 
1.4%
ValueCountFrequency (%)
0 6
8.7%
1 8
11.6%
2 13
18.8%
3 8
11.6%
4 6
8.7%
5 13
18.8%
6 8
11.6%
7 3
 
4.3%
9 2
 
2.9%
11 1
 
1.4%
ValueCountFrequency (%)
14 1
 
1.4%
11 1
 
1.4%
9 2
 
2.9%
7 3
 
4.3%
6 8
11.6%
5 13
18.8%
4 6
8.7%
3 8
11.6%
2 13
18.8%
1 8
11.6%

공개율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct48
Distinct (%)70.6%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean97.614118
Minimum92.7
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:45.033154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum92.7
5-th percentile94.835
Q196.6
median97.915
Q398.8175
95-th percentile100
Maximum100
Range7.3
Interquartile range (IQR)2.2175

Descriptive statistics

Standard deviation1.6575726
Coefficient of variation (CV)0.01698087
Kurtosis0.44143092
Mean97.614118
Median Absolute Deviation (MAD)1.06
Skewness-0.76768655
Sum6637.76
Variance2.747547
MonotonicityNot monotonic
2023-12-12T20:32:45.249086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
100.0 6
 
8.7%
98.0 4
 
5.8%
96.6 3
 
4.3%
99.5 2
 
2.9%
98.8 2
 
2.9%
96.8 2
 
2.9%
98.5 2
 
2.9%
97.3 2
 
2.9%
96.2 2
 
2.9%
98.3 2
 
2.9%
Other values (38) 41
59.4%
ValueCountFrequency (%)
92.7 1
1.4%
93.3 1
1.4%
93.9 1
1.4%
94.8 1
1.4%
94.9 1
1.4%
94.97 1
1.4%
95.4 1
1.4%
95.5 1
1.4%
95.7 1
1.4%
95.9 1
1.4%
ValueCountFrequency (%)
100.0 6
8.7%
99.5 2
 
2.9%
99.4 1
 
1.4%
99.3 2
 
2.9%
99.26 1
 
1.4%
99.0 1
 
1.4%
98.94 1
 
1.4%
98.9 2
 
2.9%
98.87 1
 
1.4%
98.8 2
 
2.9%

청구취하
Real number (ℝ)

Distinct24
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.507246
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:45.451559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.4
Q112
median16
Q320
95-th percentile28.8
Maximum36
Range35
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.6501287
Coefficient of variation (CV)0.40286118
Kurtosis0.86965296
Mean16.507246
Median Absolute Deviation (MAD)4
Skewness0.48961305
Sum1139
Variance44.224211
MonotonicityNot monotonic
2023-12-12T20:32:45.621562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
17 8
11.6%
12 7
 
10.1%
15 6
 
8.7%
22 6
 
8.7%
9 6
 
8.7%
18 5
 
7.2%
16 4
 
5.8%
20 4
 
5.8%
24 2
 
2.9%
10 2
 
2.9%
Other values (14) 19
27.5%
ValueCountFrequency (%)
1 1
 
1.4%
2 1
 
1.4%
6 1
 
1.4%
8 1
 
1.4%
9 6
8.7%
10 2
 
2.9%
11 2
 
2.9%
12 7
10.1%
13 2
 
2.9%
14 2
 
2.9%
ValueCountFrequency (%)
36 1
 
1.4%
34 1
 
1.4%
30 2
 
2.9%
27 1
 
1.4%
26 1
 
1.4%
24 2
 
2.9%
23 2
 
2.9%
22 6
8.7%
20 4
5.8%
19 1
 
1.4%

기관이송
Real number (ℝ)

Distinct16
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9275362
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:45.831160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q310
95-th percentile14.6
Maximum17
Range16
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.0956176
Coefficient of variation (CV)0.5912084
Kurtosis-0.56849579
Mean6.9275362
Median Absolute Deviation (MAD)3
Skewness0.62364685
Sum478
Variance16.774084
MonotonicityNot monotonic
2023-12-12T20:32:46.030772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4 10
14.5%
7 7
10.1%
3 7
10.1%
5 6
8.7%
6 6
8.7%
2 5
 
7.2%
10 5
 
7.2%
13 4
 
5.8%
15 3
 
4.3%
8 3
 
4.3%
Other values (6) 13
18.8%
ValueCountFrequency (%)
1 3
 
4.3%
2 5
7.2%
3 7
10.1%
4 10
14.5%
5 6
8.7%
6 6
8.7%
7 7
10.1%
8 3
 
4.3%
9 3
 
4.3%
10 5
7.2%
ValueCountFrequency (%)
17 1
 
1.4%
15 3
4.3%
14 2
 
2.9%
13 4
5.8%
12 2
 
2.9%
11 2
 
2.9%
10 5
7.2%
9 3
4.3%
8 3
4.3%
7 7
10.1%

내부종결
Real number (ℝ)

Distinct35
Distinct (%)50.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.623188
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:46.278688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.2
Q116
median24
Q332
95-th percentile46
Maximum57
Range56
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.505412
Coefficient of variation (CV)0.50787136
Kurtosis-0.12750592
Mean24.623188
Median Absolute Deviation (MAD)8
Skewness0.41403839
Sum1699
Variance156.38534
MonotonicityNot monotonic
2023-12-12T20:32:46.516932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
11 5
 
7.2%
20 4
 
5.8%
29 4
 
5.8%
28 4
 
5.8%
18 3
 
4.3%
21 3
 
4.3%
41 3
 
4.3%
33 3
 
4.3%
30 2
 
2.9%
5 2
 
2.9%
Other values (25) 36
52.2%
ValueCountFrequency (%)
1 2
 
2.9%
5 2
 
2.9%
8 1
 
1.4%
10 2
 
2.9%
11 5
7.2%
12 1
 
1.4%
13 2
 
2.9%
14 1
 
1.4%
15 1
 
1.4%
16 2
 
2.9%
ValueCountFrequency (%)
57 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
46 2
2.9%
42 2
2.9%
41 3
4.3%
37 1
 
1.4%
36 2
2.9%
34 1
 
1.4%
33 3
4.3%

민원이첩
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
0
69 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 69
100.0%

Length

2023-12-12T20:32:46.771490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:32:46.975220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 69
100.0%

정보부존재
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.507246
Minimum3
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:47.174612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.4
Q110
median18
Q326
95-th percentile43.2
Maximum62
Range59
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.356974
Coefficient of variation (CV)0.60256621
Kurtosis1.0324391
Mean20.507246
Median Absolute Deviation (MAD)8
Skewness1.0775598
Sum1415
Variance152.6948
MonotonicityNot monotonic
2023-12-12T20:32:47.423085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
9 5
 
7.2%
10 4
 
5.8%
7 4
 
5.8%
25 3
 
4.3%
21 3
 
4.3%
17 3
 
4.3%
30 3
 
4.3%
16 3
 
4.3%
13 3
 
4.3%
18 3
 
4.3%
Other values (26) 35
50.7%
ValueCountFrequency (%)
3 1
 
1.4%
5 1
 
1.4%
6 2
 
2.9%
7 4
5.8%
8 1
 
1.4%
9 5
7.2%
10 4
5.8%
11 1
 
1.4%
12 2
 
2.9%
13 3
4.3%
ValueCountFrequency (%)
62 1
1.4%
50 1
1.4%
49 1
1.4%
44 1
1.4%
42 2
2.9%
39 1
1.4%
37 1
1.4%
36 1
1.4%
35 1
1.4%
34 1
1.4%

진정질의
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4057971
Minimum0
Maximum23
Zeros38
Zeros (%)55.1%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T20:32:47.639178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile13
Maximum23
Range23
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.4368737
Coefficient of variation (CV)1.8442427
Kurtosis7.2371887
Mean2.4057971
Median Absolute Deviation (MAD)0
Skewness2.5606387
Sum166
Variance19.685848
MonotonicityNot monotonic
2023-12-12T20:32:47.904557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 38
55.1%
1 7
 
10.1%
2 7
 
10.1%
3 3
 
4.3%
13 3
 
4.3%
5 2
 
2.9%
8 2
 
2.9%
6 2
 
2.9%
4 1
 
1.4%
7 1
 
1.4%
Other values (3) 3
 
4.3%
ValueCountFrequency (%)
0 38
55.1%
1 7
 
10.1%
2 7
 
10.1%
3 3
 
4.3%
4 1
 
1.4%
5 2
 
2.9%
6 2
 
2.9%
7 1
 
1.4%
8 2
 
2.9%
10 1
 
1.4%
ValueCountFrequency (%)
23 1
 
1.4%
15 1
 
1.4%
13 3
4.3%
10 1
 
1.4%
8 2
2.9%
7 1
 
1.4%
6 2
2.9%
5 2
2.9%
4 1
 
1.4%
3 3
4.3%

미결정
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size684.0 B
0
67 
5
 
1
22
 
1

Length

Max length2
Median length1
Mean length1.0144928
Min length1

Unique

Unique2 ?
Unique (%)2.9%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 67
97.1%
5 1
 
1.4%
22 1
 
1.4%

Length

2023-12-12T20:32:48.163389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:32:48.371598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 67
97.1%
5 1
 
1.4%
22 1
 
1.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-08-07
69 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-07
2nd row2023-08-07
3rd row2023-08-07
4th row2023-08-07
5th row2023-08-07

Common Values

ValueCountFrequency (%)
2023-08-07 69
100.0%

Length

2023-12-12T20:32:48.713050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:32:48.895380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-07 69
100.0%

Interactions

2023-12-12T20:32:40.075377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:25.055420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:26.680140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:28.161698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:29.908875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:32.124027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:33.724520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:35.275538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:36.944287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:38.462249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:40.229894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:25.214400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:26.828628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:28.337280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:30.097156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:32.282429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:33.880808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:35.450498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:37.084484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:38.611141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:40.372615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:25.388038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:26.985278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:28.519799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:30.250625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:32.430959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:34.035630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:35.629774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:37.223450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:38.769764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:41.065671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:25.568219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:27.128017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:28.703633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:30.444095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:32.624920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:34.205552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:35.832212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:37.382361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:38.957269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:41.213818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:25.730312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:27.275718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:28.888523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:30.625806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:32.783734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:34.361642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:35.988281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:37.536861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:39.117920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:41.389714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:25.917845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:27.434425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:29.078633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:31.369297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:32.957448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:34.520284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:36.154298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:37.691134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:39.289802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:41.542430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:26.068658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:27.599825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:29.258983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:31.524128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:33.127423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:34.679761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:36.337778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:37.822358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:39.456955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:41.711846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:26.232837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:27.750874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:29.421070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:31.657076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:33.296798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:34.853868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:36.497742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:37.999061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:39.625068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:41.845752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:26.375456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:27.894125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:29.564130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:31.816922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:33.442000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:35.012817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:36.647229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:38.155711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:39.780904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:41.983481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:26.523655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:28.025018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:29.742178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:31.972593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:33.579547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:35.143016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:36.792061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:38.317906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:39.938209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:32:49.008022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정보공개처리연월청구건수전부공개부분공개비공개공개율청구취하기관이송내부종결정보부존재진정질의미결정
정보공개처리연월1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
청구건수1.0001.0000.8520.3100.0000.0000.5740.3900.5380.4040.1480.926
전부공개1.0000.8521.0000.4100.3320.0000.6400.0000.4360.2410.2770.784
부분공개1.0000.3100.4101.0000.0000.2240.1270.3040.3580.6750.0000.780
비공개1.0000.0000.3320.0001.0000.8540.3990.0000.0000.0000.0000.000
공개율1.0000.0000.0000.2240.8541.0000.4430.6930.2470.0000.3270.000
청구취하1.0000.5740.6400.1270.3990.4431.0000.5160.6420.2070.1300.578
기관이송1.0000.3900.0000.3040.0000.6930.5161.0000.0000.0000.5550.000
내부종결1.0000.5380.4360.3580.0000.2470.6420.0001.0000.0000.5100.329
정보부존재1.0000.4040.2410.6750.0000.0000.2070.0000.0001.0000.0000.483
진정질의1.0000.1480.2770.0000.0000.3270.1300.5550.5100.0001.0000.000
미결정1.0000.9260.7840.7800.0000.0000.5780.0000.3290.4830.0001.000
2023-12-12T20:32:49.764253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
청구건수전부공개부분공개비공개공개율청구취하기관이송내부종결정보부존재진정질의미결정
청구건수1.0000.8090.5650.282-0.0170.4740.3530.3980.510-0.3100.651
전부공개0.8091.0000.3430.2470.0360.4790.0960.3590.258-0.5920.630
부분공개0.5650.3431.0000.266-0.1190.1100.315-0.0950.690-0.0610.646
비공개0.2820.2470.2661.000-0.9300.414-0.0490.1440.084-0.0390.000
공개율-0.0170.036-0.119-0.9301.000-0.2820.089-0.0740.034-0.1500.000
청구취하0.4740.4790.1100.414-0.2821.000-0.0030.2490.069-0.1650.375
기관이송0.3530.0960.315-0.0490.089-0.0031.0000.0310.2880.2930.135
내부종결0.3980.359-0.0950.144-0.0740.2490.0311.000-0.111-0.1930.193
정보부존재0.5100.2580.6900.0840.0340.0690.288-0.1111.000-0.0130.229
진정질의-0.310-0.592-0.061-0.039-0.150-0.1650.293-0.193-0.0131.0000.000
미결정0.6510.6300.6460.0000.0000.3750.1350.1930.2290.0001.000

Missing values

2023-12-12T20:32:42.204887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:32:42.541909image/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

정보공개처리연월청구건수전부공개부분공개비공개공개율청구취하기관이송내부종결민원이첩정보부존재진정질의미결정데이터기준일자
02018-01-1824917413199.511520025002023-08-07
12018-02-181641128496.81511509002023-08-07
22018-03-182171744298.91731106002023-08-07
32018-04-182161427398.020529010002023-08-07
42018-05-181821277199.31821809002023-08-07
52018-06-181851383397.91122107002023-08-07
62018-07-1823516890100.015627010002023-08-07
72018-08-1824417412696.881842307002023-08-07
82018-09-181891268199.261832805002023-08-07
92018-10-182131513594.971712907002023-08-07
정보공개처리연월청구건수전부공개부분공개비공개공개율청구취하기관이송내부종결민원이첩정보부존재진정질의미결정데이터기준일자
592022-12-1526915029597.3131321036202023-08-07
602023-01-1525314429597.2151314031202023-08-07
612023-02-1529616829597.530311050002023-08-07
622023-02-28946340100.0271017002023-08-07
632023-03-3124212927298.791510049102023-08-07
642023-04-3023812829199.491419037102023-08-07
652023-05-31250131410100.0121013042102023-08-07
662023-06-3027212042696.417717062102023-08-07
672023-07-31251133370100.012108044252023-08-07
682023-08-06431130100.0121030222023-08-07