Overview

Dataset statistics

Number of variables12
Number of observations117
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory106.1 B

Variable types

Categorical3
Numeric9

Dataset

Description전북특별자치도 장기미집행 도시계획시설 현황(시군구명, 시설명, (부분)미집행결정면적, 미집행10년미만 개소 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/15048073/fileData.do

Alerts

시도명 has constant value ""Constant
결정연장(용량) is highly overall correlated with 미집행연장(용량)High correlation
미집행연장(용량) is highly overall correlated with 결정연장(용량)High correlation
(부분)미집행 결정면적 is highly overall correlated with 미집행10년이상 개소 and 2 other fieldsHigh correlation
미집행10년미만 개소 is highly overall correlated with 미집행10년미만 면적 and 1 other fieldsHigh correlation
미집행10년미만 면적 is highly overall correlated with 미집행10년미만 개소 and 1 other fieldsHigh correlation
미집행10년미만 사업비 is highly overall correlated with 미집행10년미만 개소 and 1 other fieldsHigh correlation
미집행10년이상 개소 is highly overall correlated with (부분)미집행 결정면적 and 2 other fieldsHigh correlation
미집행10년이상 면적 is highly overall correlated with (부분)미집행 결정면적 and 2 other fieldsHigh correlation
미집행10년이상 사업비 is highly overall correlated with (부분)미집행 결정면적 and 2 other fieldsHigh correlation
(부분)미집행 결정면적 has unique valuesUnique
결정연장(용량) has 94 (80.3%) zerosZeros
미집행연장(용량) has 99 (84.6%) zerosZeros
미집행10년미만 개소 has 54 (46.2%) zerosZeros
미집행10년미만 면적 has 54 (46.2%) zerosZeros
미집행10년미만 사업비 has 55 (47.0%) zerosZeros
미집행10년이상 개소 has 28 (23.9%) zerosZeros
미집행10년이상 면적 has 28 (23.9%) zerosZeros
미집행10년이상 사업비 has 30 (25.6%) zerosZeros

Reproduction

Analysis started2024-03-15 00:06:12.392027
Analysis finished2024-03-15 00:06:34.875995
Duration22.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
전라북도
117 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 117
100.0%

Length

2024-03-15T09:06:34.992461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:06:35.156171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 117
100.0%

시군구명
Categorical

Distinct14
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
군산시
20 
완주군
11 
임실군
11 
남원시
10 
전주시
9 
Other values (9)
56 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군산시 20
17.1%
완주군 11
9.4%
임실군 11
9.4%
남원시 10
8.5%
전주시 9
7.7%
김제시 9
7.7%
부안군 9
7.7%
정읍시 8
 
6.8%
익산시 6
 
5.1%
무주군 6
 
5.1%
Other values (4) 18
15.4%

Length

2024-03-15T09:06:35.324931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
군산시 20
17.1%
완주군 11
9.4%
임실군 11
9.4%
남원시 10
8.5%
전주시 9
7.7%
김제시 9
7.7%
부안군 9
7.7%
정읍시 8
 
6.8%
익산시 6
 
5.1%
무주군 6
 
5.1%
Other values (4) 18
15.4%

시설명
Categorical

Distinct25
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
도로
14 
공원
14 
녹지
11 
광장
10 
주차장
9 
Other values (20)
59 

Length

Max length13
Median length2
Mean length3.1709402
Min length2

Unique

Unique6 ?
Unique (%)5.1%

Sample

1st row도로
2nd row공원
3rd row녹지
4th row광장
5th row자동차정류장

Common Values

ValueCountFrequency (%)
도로 14
12.0%
공원 14
12.0%
녹지 11
 
9.4%
광장 10
 
8.5%
주차장 9
 
7.7%
체육시설 9
 
7.7%
학교 6
 
5.1%
유원지 6
 
5.1%
공공청사 5
 
4.3%
자동차정류장 4
 
3.4%
Other values (15) 29
24.8%

Length

2024-03-15T09:06:35.622997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도로 14
11.8%
공원 14
11.8%
녹지 11
 
9.2%
광장 10
 
8.4%
주차장 9
 
7.6%
체육시설 9
 
7.6%
학교 6
 
5.0%
유원지 6
 
5.0%
공공청사 5
 
4.2%
자동차정류장 4
 
3.4%
Other values (17) 31
26.1%

결정연장(용량)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16157.94
Minimum0
Maximum559943
Zeros94
Zeros (%)80.3%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:35.847604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile90419.6
Maximum559943
Range559943
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64199.759
Coefficient of variation (CV)3.9732638
Kurtosis46.881101
Mean16157.94
Median Absolute Deviation (MAD)0
Skewness6.2858401
Sum1890479
Variance4.121609 × 109
MonotonicityNot monotonic
2024-03-15T09:06:36.266460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 94
80.3%
168718 1
 
0.9%
126 1
 
0.9%
89872 1
 
0.9%
27286 1
 
0.9%
21832 1
 
0.9%
6 1
 
0.9%
42307 1
 
0.9%
26225 1
 
0.9%
69381 1
 
0.9%
Other values (14) 14
 
12.0%
ValueCountFrequency (%)
0 94
80.3%
6 1
 
0.9%
122 1
 
0.9%
126 1
 
0.9%
213 1
 
0.9%
4000 1
 
0.9%
6001 1
 
0.9%
12581 1
 
0.9%
21832 1
 
0.9%
23153 1
 
0.9%
ValueCountFrequency (%)
559943 1
0.9%
254106 1
0.9%
229497 1
0.9%
168718 1
0.9%
123297 1
0.9%
92610 1
0.9%
89872 1
0.9%
80824 1
0.9%
69381 1
0.9%
42307 1
0.9%

미집행연장(용량)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7448.6154
Minimum0
Maximum150165
Zeros99
Zeros (%)84.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:36.469126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile58103.8
Maximum150165
Range150165
Interquartile range (IQR)0

Descriptive statistics

Standard deviation24395.659
Coefficient of variation (CV)3.2751938
Kurtosis17.979057
Mean7448.6154
Median Absolute Deviation (MAD)0
Skewness4.0875501
Sum871488
Variance5.9514816 × 108
MonotonicityNot monotonic
2024-03-15T09:06:36.818351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 99
84.6%
57488 1
 
0.9%
89872 1
 
0.9%
14440 1
 
0.9%
2917 1
 
0.9%
31820 1
 
0.9%
8970 1
 
0.9%
40254 1
 
0.9%
10829 1
 
0.9%
90092 1
 
0.9%
Other values (9) 9
 
7.7%
ValueCountFrequency (%)
0 99
84.6%
2917 1
 
0.9%
4000 1
 
0.9%
6001 1
 
0.9%
8970 1
 
0.9%
10829 1
 
0.9%
14440 1
 
0.9%
23668 1
 
0.9%
31820 1
 
0.9%
34711 1
 
0.9%
ValueCountFrequency (%)
150165 1
0.9%
137381 1
0.9%
90092 1
0.9%
89872 1
0.9%
64359 1
0.9%
60567 1
0.9%
57488 1
0.9%
43954 1
0.9%
40254 1
0.9%
34711 1
0.9%

(부분)미집행 결정면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct117
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean823734.79
Minimum400
Maximum14280358
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:37.230753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum400
5-th percentile2764.8
Q114446
median101766
Q3558938
95-th percentile3919149.6
Maximum14280358
Range14279958
Interquartile range (IQR)544492

Descriptive statistics

Standard deviation1883201.9
Coefficient of variation (CV)2.286175
Kurtosis24.38054
Mean823734.79
Median Absolute Deviation (MAD)98646
Skewness4.335513
Sum96376971
Variance3.5464494 × 1012
MonotonicityNot monotonic
2024-03-15T09:06:37.678751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3889697 1
 
0.9%
367250 1
 
0.9%
237726 1
 
0.9%
788697 1
 
0.9%
203673 1
 
0.9%
9397 1
 
0.9%
3120 1
 
0.9%
21556 1
 
0.9%
14446 1
 
0.9%
66682 1
 
0.9%
Other values (107) 107
91.5%
ValueCountFrequency (%)
400 1
0.9%
420 1
0.9%
611 1
0.9%
997 1
0.9%
1415 1
0.9%
1976 1
0.9%
2962 1
0.9%
3120 1
0.9%
3355 1
0.9%
4048 1
0.9%
ValueCountFrequency (%)
14280358 1
0.9%
8358544 1
0.9%
6415181 1
0.9%
5327676 1
0.9%
4713921 1
0.9%
4036960 1
0.9%
3889697 1
0.9%
3519298 1
0.9%
3267401 1
0.9%
3171619 1
0.9%

미집행10년미만 개소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1709402
Minimum0
Maximum103
Zeros54
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:38.081349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile18.8
Maximum103
Range103
Interquartile range (IQR)3

Descriptive statistics

Standard deviation11.984394
Coefficient of variation (CV)2.8733076
Kurtosis41.997005
Mean4.1709402
Median Absolute Deviation (MAD)1
Skewness5.8714235
Sum488
Variance143.6257
MonotonicityNot monotonic
2024-03-15T09:06:38.282951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 54
46.2%
1 20
 
17.1%
2 9
 
7.7%
3 7
 
6.0%
5 6
 
5.1%
4 4
 
3.4%
9 3
 
2.6%
7 2
 
1.7%
45 2
 
1.7%
8 2
 
1.7%
Other values (7) 8
 
6.8%
ValueCountFrequency (%)
0 54
46.2%
1 20
 
17.1%
2 9
 
7.7%
3 7
 
6.0%
4 4
 
3.4%
5 6
 
5.1%
6 2
 
1.7%
7 2
 
1.7%
8 2
 
1.7%
9 3
 
2.6%
ValueCountFrequency (%)
103 1
 
0.9%
45 2
1.7%
35 1
 
0.9%
29 1
 
0.9%
22 1
 
0.9%
18 1
 
0.9%
17 1
 
0.9%
9 3
2.6%
8 2
1.7%
7 2
1.7%

미집행10년미만 면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct64
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68226.769
Minimum0
Maximum1593073
Zeros54
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:38.655395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median635
Q320781
95-th percentile426782.2
Maximum1593073
Range1593073
Interquartile range (IQR)20781

Descriptive statistics

Standard deviation209811.03
Coefficient of variation (CV)3.075201
Kurtosis28.464972
Mean68226.769
Median Absolute Deviation (MAD)635
Skewness4.8942765
Sum7982532
Variance4.4020667 × 1010
MonotonicityNot monotonic
2024-03-15T09:06:39.105032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 54
46.2%
16829 1
 
0.9%
16174 1
 
0.9%
22819 1
 
0.9%
7237 1
 
0.9%
9050 1
 
0.9%
99511 1
 
0.9%
359129 1
 
0.9%
420 1
 
0.9%
2070 1
 
0.9%
Other values (54) 54
46.2%
ValueCountFrequency (%)
0 54
46.2%
48 1
 
0.9%
351 1
 
0.9%
400 1
 
0.9%
420 1
 
0.9%
635 1
 
0.9%
926 1
 
0.9%
1976 1
 
0.9%
2070 1
 
0.9%
2617 1
 
0.9%
ValueCountFrequency (%)
1593073 1
0.9%
1075290 1
0.9%
658126 1
0.9%
621759 1
0.9%
465770 1
0.9%
427535 1
0.9%
426594 1
0.9%
374660 1
0.9%
359129 1
0.9%
356330 1
0.9%

미집행10년미만 사업비
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct63
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9022.5556
Minimum0
Maximum184032
Zeros55
Zeros (%)47.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:39.534412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median75
Q32807
95-th percentile54877.4
Maximum184032
Range184032
Interquartile range (IQR)2807

Descriptive statistics

Standard deviation25872.463
Coefficient of variation (CV)2.8675316
Kurtosis21.41256
Mean9022.5556
Median Absolute Deviation (MAD)75
Skewness4.2904639
Sum1055639
Variance6.6938435 × 108
MonotonicityNot monotonic
2024-03-15T09:06:39.956449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 55
47.0%
301 1
 
0.9%
2711 1
 
0.9%
558 1
 
0.9%
630 1
 
0.9%
8835 1
 
0.9%
93236 1
 
0.9%
29 1
 
0.9%
529 1
 
0.9%
7110 1
 
0.9%
Other values (53) 53
45.3%
ValueCountFrequency (%)
0 55
47.0%
3 1
 
0.9%
29 1
 
0.9%
63 1
 
0.9%
75 1
 
0.9%
179 1
 
0.9%
228 1
 
0.9%
301 1
 
0.9%
307 1
 
0.9%
426 1
 
0.9%
ValueCountFrequency (%)
184032 1
0.9%
110198 1
0.9%
97528 1
0.9%
93236 1
0.9%
87461 1
0.9%
62283 1
0.9%
53026 1
0.9%
48470 1
0.9%
38520 1
0.9%
36395 1
0.9%

미집행10년이상 개소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.273504
Minimum0
Maximum679
Zeros28
Zeros (%)23.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:40.189904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q37
95-th percentile179.2
Maximum679
Range679
Interquartile range (IQR)6

Descriptive statistics

Standard deviation91.220614
Coefficient of variation (CV)3.4719622
Kurtosis29.238467
Mean26.273504
Median Absolute Deviation (MAD)1
Skewness5.1209157
Sum3074
Variance8321.2004
MonotonicityNot monotonic
2024-03-15T09:06:40.556313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 32
27.4%
0 28
23.9%
3 7
 
6.0%
4 7
 
6.0%
2 6
 
5.1%
8 5
 
4.3%
6 4
 
3.4%
9 3
 
2.6%
5 3
 
2.6%
13 2
 
1.7%
Other values (20) 20
17.1%
ValueCountFrequency (%)
0 28
23.9%
1 32
27.4%
2 6
 
5.1%
3 7
 
6.0%
4 7
 
6.0%
5 3
 
2.6%
6 4
 
3.4%
7 1
 
0.9%
8 5
 
4.3%
9 3
 
2.6%
ValueCountFrequency (%)
679 1
0.9%
474 1
0.9%
409 1
0.9%
209 1
0.9%
190 1
0.9%
184 1
0.9%
178 1
0.9%
151 1
0.9%
118 1
0.9%
64 1
0.9%

미집행10년이상 면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct90
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean390626.67
Minimum0
Maximum9689466
Zeros28
Zeros (%)23.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:40.955839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1215
median15000
Q3228546
95-th percentile2320205.6
Maximum9689466
Range9689466
Interquartile range (IQR)228331

Descriptive statistics

Standard deviation1109573.3
Coefficient of variation (CV)2.8404956
Kurtosis43.048006
Mean390626.67
Median Absolute Deviation (MAD)15000
Skewness5.751026
Sum45703320
Variance1.231153 × 1012
MonotonicityNot monotonic
2024-03-15T09:06:41.220746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28
 
23.9%
612642 1
 
0.9%
81808 1
 
0.9%
3485 1
 
0.9%
55652 1
 
0.9%
359651 1
 
0.9%
27263 1
 
0.9%
215 1
 
0.9%
21556 1
 
0.9%
66682 1
 
0.9%
Other values (80) 80
68.4%
ValueCountFrequency (%)
0 28
23.9%
122 1
 
0.9%
215 1
 
0.9%
231 1
 
0.9%
273 1
 
0.9%
294 1
 
0.9%
338 1
 
0.9%
611 1
 
0.9%
814 1
 
0.9%
997 1
 
0.9%
ValueCountFrequency (%)
9689466 1
0.9%
3269339 1
0.9%
3112490 1
0.9%
2637346 1
0.9%
2465592 1
0.9%
2398452 1
0.9%
2300644 1
0.9%
2065387 1
0.9%
2055303 1
0.9%
1983573 1
0.9%

미집행10년이상 사업비
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct88
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46786.094
Minimum0
Maximum550951
Zeros30
Zeros (%)25.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T09:06:41.494542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2492
Q331777
95-th percentile267482
Maximum550951
Range550951
Interquartile range (IQR)31777

Descriptive statistics

Standard deviation100187.59
Coefficient of variation (CV)2.1413967
Kurtosis8.4611879
Mean46786.094
Median Absolute Deviation (MAD)2492
Skewness2.8540504
Sum5473973
Variance1.0037553 × 1010
MonotonicityNot monotonic
2024-03-15T09:06:41.927195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
25.6%
262446 1
 
0.9%
14895 1
 
0.9%
2986 1
 
0.9%
20930 1
 
0.9%
10220 1
 
0.9%
14 1
 
0.9%
2798 1
 
0.9%
12624 1
 
0.9%
30439 1
 
0.9%
Other values (78) 78
66.7%
ValueCountFrequency (%)
0 30
25.6%
14 1
 
0.9%
17 1
 
0.9%
25 1
 
0.9%
30 1
 
0.9%
35 1
 
0.9%
124 1
 
0.9%
152 1
 
0.9%
210 1
 
0.9%
224 1
 
0.9%
ValueCountFrequency (%)
550951 1
0.9%
426928 1
0.9%
413223 1
0.9%
337499 1
0.9%
318526 1
0.9%
287626 1
0.9%
262446 1
0.9%
258414 1
0.9%
245642 1
0.9%
239289 1
0.9%

Interactions

2024-03-15T09:06:32.633858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:13.112406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:15.565633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:18.519625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:20.946407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:23.365585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:26.078765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:28.400338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:30.687018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:32.887298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:13.356653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:15.868197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:18.798542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:21.192237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:23.691356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:26.346291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:28.573749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:30.941203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:33.073240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:13.617766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:16.182431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:19.106481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:21.450549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:23.975475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:26.562456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:28.845640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:31.203070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:33.293852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:13.886147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:16.616729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:19.373926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:21.712221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:24.252335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:26.793314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:29.113879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:31.362617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:33.438244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:14.133148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:16.897852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:19.627258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:21.953135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:24.624608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:27.042476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:29.370186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:31.509336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:33.608466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:14.405327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:17.222811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:19.902450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:22.216814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:24.910200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:27.318116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:29.654988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:31.683493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:33.797950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:14.669945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:17.524976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:20.169490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:22.554249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:25.085611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:27.583252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:29.929410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:31.886869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:33.984635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:14.989093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:17.838072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:20.435992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:22.844677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:25.297972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:27.856750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:30.193494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:32.144675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:34.132127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:15.285477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:18.258779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:20.689802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:23.106413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:25.804397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:28.116185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:30.447559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:06:32.389691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:06:42.205346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명시설명결정연장(용량)미집행연장(용량)(부분)미집행 결정면적미집행10년미만 개소미집행10년미만 면적미집행10년미만 사업비미집행10년이상 개소미집행10년이상 면적미집행10년이상 사업비
시군구명1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
시설명0.0001.0000.0000.1440.3980.0000.6620.0000.0000.0000.000
결정연장(용량)0.0000.0001.0000.9110.7110.9560.6700.7970.9770.6070.773
미집행연장(용량)0.0000.1440.9111.0000.6580.7930.6170.8580.8350.6250.696
(부분)미집행 결정면적0.0000.3980.7110.6581.0000.7940.9390.8620.5410.8190.827
미집행10년미만 개소0.0000.0000.9560.7930.7941.0000.8510.8170.8940.2070.712
미집행10년미만 면적0.0000.6620.6700.6170.9390.8511.0000.9440.4850.3810.665
미집행10년미만 사업비0.0000.0000.7970.8580.8620.8170.9441.0000.7260.4340.658
미집행10년이상 개소0.0000.0000.9770.8350.5410.8940.4850.7261.0000.5250.742
미집행10년이상 면적0.0000.0000.6070.6250.8190.2070.3810.4340.5251.0000.843
미집행10년이상 사업비0.0000.0000.7730.6960.8270.7120.6650.6580.7420.8431.000
2024-03-15T09:06:42.531320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명시설명
시군구명1.0000.000
시설명0.0001.000
2024-03-15T09:06:42.738458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결정연장(용량)미집행연장(용량)(부분)미집행 결정면적미집행10년미만 개소미집행10년미만 면적미집행10년미만 사업비미집행10년이상 개소미집행10년이상 면적미집행10년이상 사업비시군구명시설명
결정연장(용량)1.0000.9020.2880.4790.3870.3810.4110.2540.2870.0000.000
미집행연장(용량)0.9021.0000.3310.4990.4160.4040.4450.3050.3380.0000.037
(부분)미집행 결정면적0.2880.3311.0000.1600.2310.1990.6060.7860.7660.0000.166
미집행10년미만 개소0.4790.4990.1601.0000.9080.9000.039-0.101-0.0520.0000.000
미집행10년미만 면적0.3870.4160.2310.9081.0000.967-0.009-0.107-0.0680.0000.322
미집행10년미만 사업비0.3810.4040.1990.9000.9671.000-0.028-0.136-0.0940.0000.000
미집행10년이상 개소0.4110.4450.6060.039-0.009-0.0281.0000.8310.8260.0000.000
미집행10년이상 면적0.2540.3050.786-0.101-0.107-0.1360.8311.0000.9530.0000.000
미집행10년이상 사업비0.2870.3380.766-0.052-0.068-0.0940.8260.9531.0000.0000.000
시군구명0.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
시설명0.0000.0370.1660.0000.3220.0000.0000.0000.0000.0001.000

Missing values

2024-03-15T09:06:34.425874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:06:34.739837image/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

시도명시군구명시설명결정연장(용량)미집행연장(용량)(부분)미집행 결정면적미집행10년미만 개소미집행10년미만 면적미집행10년미만 사업비미집행10년이상 개소미집행10년이상 면적미집행10년이상 사업비
0전라북도전주시도로1687185748838896973635301184612642262446
1전라북도전주시공원0014280358000189689466550951
2전라북도전주시녹지0036136000122133232699
3전라북도전주시광장00294000003123933189
4전라북도전주시자동차정류장00219120001338224
5전라북도전주시학교009467700031439629
6전라북도전주시주차장2130640300021407251
7전라북도전주시체육시설00647112000122854687675
8전라북도전주시문화시설001171500004867512577
9전라북도군산시도로229497150165326740122465770874614741679142426928
시도명시군구명시설명결정연장(용량)미집행연장(용량)(부분)미집행 결정면적미집행10년미만 개소미집행10년미만 면적미집행10년미만 사업비미집행10년이상 개소미집행10년이상 면적미집행10년이상 사업비
107전라북도고창군주차장004432244321150000
108전라북도부안군도로898728987211882142921706738520151528887111526
109전라북도부안군공원003519298000103112490258414
110전라북도부안군녹지004210094210011956000
111전라북도부안군광장005665356652540000
112전라북도부안군사회복지시설001170570001366405072
113전라북도부안군자동차정류장0056100001231210
114전라북도부안군학교00989292912811713187342019
115전라북도부안군주차장006525465251134000
116전라북도부안군체육시설0025812000019531823