Overview

Dataset statistics

Number of variables8
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory72.4 B

Variable types

Text1
Categorical1
Numeric6

Dataset

Description전북특별자치도 토지 수용 현황 데이터입니다.(사업명, 사업시행자, 수용재결 신청 건수, 수용재결 신청 면적, 수용재결 신청 금액 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/15051313/fileData.do

Alerts

수용재결 신청 건수 is highly overall correlated with 수용재결 건수High correlation
수용재결 신청 면적(제곱미터) is highly overall correlated with 수용재결 면적(제곱미터)High correlation
수용재결 신청 금액 is highly overall correlated with 수용재결 금액High correlation
수용재결 건수 is highly overall correlated with 수용재결 신청 건수High correlation
수용재결 면적(제곱미터) is highly overall correlated with 수용재결 신청 면적(제곱미터)High correlation
수용재결 금액 is highly overall correlated with 수용재결 신청 금액High correlation
수용재결 신청 금액 has unique valuesUnique
수용재결 금액 has unique valuesUnique
수용재결 신청 면적(제곱미터) has 19 (35.2%) zerosZeros
수용재결 면적(제곱미터) has 19 (35.2%) zerosZeros

Reproduction

Analysis started2024-03-15 01:14:04.504285
Analysis finished2024-03-15 01:14:14.933341
Duration10.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업명
Text

Distinct35
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Memory size560.0 B
2024-03-15T10:14:15.439506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length23
Mean length18.074074
Min length8

Characters and Unicode

Total characters976
Distinct characters163
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)29.6%

Sample

1st row지방도712호선 김제육교 재가설공사(1차)
2nd row익산왕궁물류단지(1차)
3rd row적풍지구 배수개선사업(2차)
4th row군계획시설(소로1류2호선 및 2류8호선) 사업
5th row익산고도지정기구[금마시장(면사무소)이전사업(2차)]
ValueCountFrequency (%)
조성사업 8
 
5.6%
개설공사 4
 
2.8%
임실군 4
 
2.8%
건립사업 3
 
2.1%
생태하천 3
 
2.1%
조성사업(5차 2
 
1.4%
신송지구 2
 
1.4%
다목적농촌용수개발사업(1차 2
 
1.4%
다목적체육관 2
 
1.4%
북부권 2
 
1.4%
Other values (78) 111
77.6%
2024-03-15T10:14:16.442591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
9.1%
사 52
 
5.3%
업 38
 
3.9%
지 29
 
3.0%
) 29
 
3.0%
( 29
 
3.0%
구 23
 
2.4%
1 19
 
1.9%
차 19
 
1.9%
도 18
 
1.8%
Other values (153) 631
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 757
77.6%
Space Separator 89
 
9.1%
Decimal Number 55
 
5.6%
Close Punctuation 31
 
3.2%
Open Punctuation 31
 
3.2%
Math Symbol 7
 
0.7%
Dash Punctuation 3
 
0.3%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 52
 
6.9%
업 38
 
5.0%
지 29
 
3.8%
구 23
 
3.0%
차 19
 
2.5%
도 18
 
2.4%
공 18
 
2.4%
원 18
 
2.4%
개 17
 
2.2%
선 14
 
1.8%
Other values (135) 511
67.5%
Decimal Number
ValueCountFrequency (%)
1 19
34.5%
2 11
20.0%
3 6
 
10.9%
7 4
 
7.3%
5 3
 
5.5%
9 3
 
5.5%
0 3
 
5.5%
6 2
 
3.6%
8 2
 
3.6%
4 2
 
3.6%
Close Punctuation
ValueCountFrequency (%)
) 29
93.5%
] 2
 
6.5%
Open Punctuation
ValueCountFrequency (%)
( 29
93.5%
[ 2
 
6.5%
Space Separator
ValueCountFrequency (%)
89
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 757
77.6%
Common 219
 
22.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 52
 
6.9%
업 38
 
5.0%
지 29
 
3.8%
구 23
 
3.0%
차 19
 
2.5%
도 18
 
2.4%
공 18
 
2.4%
원 18
 
2.4%
개 17
 
2.2%
선 14
 
1.8%
Other values (135) 511
67.5%
Common
ValueCountFrequency (%)
89
40.6%
) 29
 
13.2%
( 29
 
13.2%
1 19
 
8.7%
2 11
 
5.0%
~ 7
 
3.2%
3 6
 
2.7%
7 4
 
1.8%
5 3
 
1.4%
- 3
 
1.4%
Other values (8) 19
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 757
77.6%
ASCII 219
 
22.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
40.6%
) 29
 
13.2%
( 29
 
13.2%
1 19
 
8.7%
2 11
 
5.0%
~ 7
 
3.2%
3 6
 
2.7%
7 4
 
1.8%
5 3
 
1.4%
- 3
 
1.4%
Other values (8) 19
 
8.7%
Hangul
ValueCountFrequency (%)
사 52
 
6.9%
업 38
 
5.0%
지 29
 
3.8%
구 23
 
3.0%
차 19
 
2.5%
도 18
 
2.4%
공 18
 
2.4%
원 18
 
2.4%
개 17
 
2.2%
선 14
 
1.8%
Other values (135) 511
67.5%

사업 시행자
Categorical

Distinct17
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Memory size560.0 B
남원시장
8 
김제시장
7 
한국농어촌공사
6 
임실군수
4 
익산왕궁물류단지 주식회사
4 
Other values (12)
25 

Length

Max length13
Median length4
Mean length5.3148148
Min length4

Unique

Unique4 ?
Unique (%)7.4%

Sample

1st row김제시장
2nd row익산왕궁물류단지 주식회사
3rd row한국농어촌공사
4th row순창군수
5th row익산시장

Common Values

ValueCountFrequency (%)
남원시장 8
14.8%
김제시장 7
13.0%
한국농어촌공사 6
11.1%
임실군수 4
 
7.4%
익산왕궁물류단지 주식회사 4
 
7.4%
완주군수 4
 
7.4%
익산시장 4
 
7.4%
부안군수 3
 
5.6%
고창군수 2
 
3.7%
전북개발공사사장 2
 
3.7%
Other values (7) 10
18.5%

Length

2024-03-15T10:14:16.846804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남원시장 8
13.8%
김제시장 7
12.1%
한국농어촌공사 6
10.3%
임실군수 4
 
6.9%
익산왕궁물류단지 4
 
6.9%
주식회사 4
 
6.9%
완주군수 4
 
6.9%
익산시장 4
 
6.9%
부안군수 3
 
5.2%
정읍시장 2
 
3.4%
Other values (8) 12
20.7%

수용재결 신청 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.574074
Minimum1
Maximum406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:14:17.200720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median7.5
Q320.25
95-th percentile111.85
Maximum406
Range405
Interquartile range (IQR)17.25

Descriptive statistics

Standard deviation68.507981
Coefficient of variation (CV)2.3975573
Kurtosis19.922242
Mean28.574074
Median Absolute Deviation (MAD)6
Skewness4.3171234
Sum1543
Variance4693.3435
MonotonicityNot monotonic
2024-03-15T10:14:17.615350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2 6
 
11.1%
1 6
 
11.1%
14 4
 
7.4%
5 4
 
7.4%
4 4
 
7.4%
3 3
 
5.6%
36 2
 
3.7%
6 2
 
3.7%
7 2
 
3.7%
30 2
 
3.7%
Other values (17) 19
35.2%
ValueCountFrequency (%)
1 6
11.1%
2 6
11.1%
3 3
5.6%
4 4
7.4%
5 4
7.4%
6 2
 
3.7%
7 2
 
3.7%
8 1
 
1.9%
9 1
 
1.9%
11 1
 
1.9%
ValueCountFrequency (%)
406 1
1.9%
262 1
1.9%
197 1
1.9%
66 1
1.9%
54 1
1.9%
48 1
1.9%
43 1
1.9%
36 2
3.7%
33 1
1.9%
30 2
3.7%

수용재결 신청 면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4086.7963
Minimum0
Maximum54687
Zeros19
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:14:17.954341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median699
Q33604.25
95-th percentile14174.05
Maximum54687
Range54687
Interquartile range (IQR)3604.25

Descriptive statistics

Standard deviation10374.89
Coefficient of variation (CV)2.5386364
Kurtosis18.827706
Mean4086.7963
Median Absolute Deviation (MAD)699
Skewness4.2732673
Sum220687
Variance1.0763834 × 108
MonotonicityNot monotonic
2024-03-15T10:14:18.397190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 19
35.2%
2151 1
 
1.9%
37 1
 
1.9%
65 1
 
1.9%
457 1
 
1.9%
708 1
 
1.9%
1613 1
 
1.9%
3521 1
 
1.9%
1443 1
 
1.9%
5856 1
 
1.9%
Other values (26) 26
48.1%
ValueCountFrequency (%)
0 19
35.2%
37 1
 
1.9%
65 1
 
1.9%
69 1
 
1.9%
100 1
 
1.9%
126 1
 
1.9%
141 1
 
1.9%
457 1
 
1.9%
690 1
 
1.9%
708 1
 
1.9%
ValueCountFrequency (%)
54687 1
1.9%
52455 1
1.9%
15996 1
1.9%
13193 1
1.9%
10928 1
1.9%
6882 1
1.9%
6303 1
1.9%
6126 1
1.9%
5856 1
1.9%
5027 1
1.9%

수용재결 신청 금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7573141 × 108
Minimum370000
Maximum3.1893574 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:14:18.912050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum370000
5-th percentile8496963
Q138061442
median1.5210059 × 108
Q33.7519873 × 108
95-th percentile1.7219125 × 109
Maximum3.1893574 × 109
Range3.1889874 × 109
Interquartile range (IQR)3.3713728 × 108

Descriptive statistics

Standard deviation6.4172484 × 108
Coefficient of variation (CV)1.7079351
Kurtosis9.4186216
Mean3.7573141 × 108
Median Absolute Deviation (MAD)1.1854027 × 108
Skewness3.0017338
Sum2.0289496 × 1010
Variance4.1181078 × 1017
MonotonicityNot monotonic
2024-03-15T10:14:19.404233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147727330 1
 
1.9%
202534920 1
 
1.9%
37815490 1
 
1.9%
12408990 1
 
1.9%
30831450 1
 
1.9%
553024200 1
 
1.9%
1526195630 1
 
1.9%
2200000 1
 
1.9%
379682930 1
 
1.9%
260288600 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
370000 1
1.9%
2200000 1
1.9%
3358180 1
1.9%
11264000 1
1.9%
12408990 1
1.9%
15150000 1
1.9%
19916000 1
1.9%
20082000 1
1.9%
25575400 1
1.9%
25740800 1
1.9%
ValueCountFrequency (%)
3189357400 1
1.9%
2661960180 1
1.9%
2085386800 1
1.9%
1526195630 1
1.9%
1082386670 1
1.9%
1024515350 1
1.9%
833600250 1
1.9%
617679450 1
1.9%
557590210 1
1.9%
553024200 1
1.9%

수용재결 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.574074
Minimum1
Maximum406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:14:19.818762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median7.5
Q320.25
95-th percentile111.85
Maximum406
Range405
Interquartile range (IQR)17.25

Descriptive statistics

Standard deviation68.507981
Coefficient of variation (CV)2.3975573
Kurtosis19.922242
Mean28.574074
Median Absolute Deviation (MAD)6
Skewness4.3171234
Sum1543
Variance4693.3435
MonotonicityNot monotonic
2024-03-15T10:14:20.292026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2 6
 
11.1%
1 6
 
11.1%
14 4
 
7.4%
5 4
 
7.4%
4 4
 
7.4%
3 3
 
5.6%
36 2
 
3.7%
6 2
 
3.7%
7 2
 
3.7%
30 2
 
3.7%
Other values (17) 19
35.2%
ValueCountFrequency (%)
1 6
11.1%
2 6
11.1%
3 3
5.6%
4 4
7.4%
5 4
7.4%
6 2
 
3.7%
7 2
 
3.7%
8 1
 
1.9%
9 1
 
1.9%
11 1
 
1.9%
ValueCountFrequency (%)
406 1
1.9%
262 1
1.9%
197 1
1.9%
66 1
1.9%
54 1
1.9%
48 1
1.9%
43 1
1.9%
36 2
3.7%
33 1
1.9%
30 2
3.7%

수용재결 면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4086.7963
Minimum0
Maximum54687
Zeros19
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:14:20.710555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median699
Q33604.25
95-th percentile14174.05
Maximum54687
Range54687
Interquartile range (IQR)3604.25

Descriptive statistics

Standard deviation10374.89
Coefficient of variation (CV)2.5386364
Kurtosis18.827706
Mean4086.7963
Median Absolute Deviation (MAD)699
Skewness4.2732673
Sum220687
Variance1.0763834 × 108
MonotonicityNot monotonic
2024-03-15T10:14:21.198971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 19
35.2%
2151 1
 
1.9%
37 1
 
1.9%
65 1
 
1.9%
457 1
 
1.9%
708 1
 
1.9%
1613 1
 
1.9%
3521 1
 
1.9%
1443 1
 
1.9%
5856 1
 
1.9%
Other values (26) 26
48.1%
ValueCountFrequency (%)
0 19
35.2%
37 1
 
1.9%
65 1
 
1.9%
69 1
 
1.9%
100 1
 
1.9%
126 1
 
1.9%
141 1
 
1.9%
457 1
 
1.9%
690 1
 
1.9%
708 1
 
1.9%
ValueCountFrequency (%)
54687 1
1.9%
52455 1
1.9%
15996 1
1.9%
13193 1
1.9%
10928 1
1.9%
6882 1
1.9%
6303 1
1.9%
6126 1
1.9%
5856 1
1.9%
5027 1
1.9%

수용재결 금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9396073 × 108
Minimum370000
Maximum3.2670416 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:14:21.603879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum370000
5-th percentile8529590
Q139987788
median1.5605176 × 108
Q33.8239302 × 108
95-th percentile1.7589795 × 109
Maximum3.2670416 × 109
Range3.2666716 × 109
Interquartile range (IQR)3.4240523 × 108

Descriptive statistics

Standard deviation6.6345403 × 108
Coefficient of variation (CV)1.6840613
Kurtosis8.9551594
Mean3.9396073 × 108
Median Absolute Deviation (MAD)1.1757372 × 108
Skewness2.923269
Sum2.127388 × 1010
Variance4.4017125 × 1017
MonotonicityNot monotonic
2024-03-15T10:14:22.105009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150327880 1
 
1.9%
209351970 1
 
1.9%
38896100 1
 
1.9%
12408990 1
 
1.9%
31525000 1
 
1.9%
571921200 1
 
1.9%
1544709710 1
 
1.9%
2200000 1
 
1.9%
384225770 1
 
1.9%
269604600 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
370000 1
1.9%
2200000 1
1.9%
3386400 1
1.9%
11299000 1
1.9%
12408990 1
1.9%
15955000 1
1.9%
20462870 1
1.9%
20635150 1
1.9%
26136500 1
1.9%
30639800 1
1.9%
ValueCountFrequency (%)
3267041580 1
1.9%
2746808740 1
1.9%
2156909070 1
1.9%
1544709710 1
1.9%
1135539550 1
1.9%
1088822660 1
1.9%
905911270 1
1.9%
842795600 1
1.9%
626148450 1
1.9%
571921200 1
1.9%

Interactions

2024-03-15T10:14:12.643863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:04.958778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:06.529404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:08.091148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:09.452592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:11.115698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:12.934165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:05.132314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:06.797815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:08.374295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:09.719433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:11.395299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:13.183426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:05.459803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:07.044341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:08.623627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:09.973094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:11.710399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:13.442805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:05.748743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:07.300828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:08.789523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:10.243448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:11.983856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:13.708207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:06.015862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:07.563643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:08.961588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:10.672615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:12.244849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:13.963013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:06.269816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:07.778585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:09.196405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:10.853522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:14:12.489162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:14:22.410697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업명사업 시행자수용재결 신청 건수수용재결 신청 면적(제곱미터)수용재결 신청 금액수용재결 건수수용재결 면적(제곱미터)수용재결 금액
사업명1.0001.0000.0000.6110.0000.0000.6110.000
사업 시행자1.0001.0000.5330.5820.5340.5330.5820.421
수용재결 신청 건수0.0000.5331.0000.0000.7181.0000.0000.722
수용재결 신청 면적(제곱미터)0.6110.5820.0001.0000.9620.0001.0000.967
수용재결 신청 금액0.0000.5340.7180.9621.0000.7180.9620.999
수용재결 건수0.0000.5331.0000.0000.7181.0000.0000.722
수용재결 면적(제곱미터)0.6110.5820.0001.0000.9620.0001.0000.967
수용재결 금액0.0000.4210.7220.9670.9990.7220.9671.000
2024-03-15T10:14:23.073693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수용재결 신청 건수수용재결 신청 면적(제곱미터)수용재결 신청 금액수용재결 건수수용재결 면적(제곱미터)수용재결 금액사업 시행자
수용재결 신청 건수1.000-0.1600.4191.000-0.1600.4260.258
수용재결 신청 면적(제곱미터)-0.1601.0000.438-0.1601.0000.4210.305
수용재결 신청 금액0.4190.4381.0000.4190.4380.9970.232
수용재결 건수1.000-0.1600.4191.000-0.1600.4260.258
수용재결 면적(제곱미터)-0.1601.0000.438-0.1601.0000.4210.305
수용재결 금액0.4260.4210.9970.4260.4211.0000.173
사업 시행자0.2580.3050.2320.2580.3050.1731.000

Missing values

2024-03-15T10:14:14.331498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:14:14.755585image/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

사업명사업 시행자수용재결 신청 건수수용재결 신청 면적(제곱미터)수용재결 신청 금액수용재결 건수수용재결 면적(제곱미터)수용재결 금액
0지방도712호선 김제육교 재가설공사(1차)김제시장142151147727330142151150327880
1익산왕궁물류단지(1차)익산왕궁물류단지 주식회사2152455208538680021524552156909070
2적풍지구 배수개선사업(2차)한국농어촌공사1141335818011413386400
3군계획시설(소로1류2호선 및 2류8호선) 사업순창군수57991564738505799161775650
4익산고도지정기구[금마시장(면사무소)이전사업(2차)]익산시장49725076615004972905911270
5지방도 709호선 옥구~옥서간 확포장공사군산시장486126557590210486126557864310
6전북혁신도시 원천 정비공사(3차)전북개발공사2206521822633022065233766750
7남원시 지리산 구룡계곡 흙탕물 저감사업남원시장11516484362001151651165000
8소양신원~반곡 도로확포장공사(1차)완주군수110015150000110015955000
9용진읍 행정복지센터 건립사업완주군수250271082386670250271088822660
사업명사업 시행자수용재결 신청 건수수용재결 신청 면적(제곱미터)수용재결 신청 금액수용재결 건수수용재결 면적(제곱미터)수용재결 금액
44남원 일반사업단지 조성사업(5차)남원시장120204140120120204629790
45외정천 생태하천 복원사업고창군수3609666125036097440450
46순창지구 농촌용수이용체계재편사업(4차)한국농어촌공사1508907469015095254510
47격포해수욕장 경관광장 조성사업부안군수300833600250300842795600
48대율저수지 관광자원개발사업김제시장3002574080030026136500
49완주운곡지구 도시개발구역완주군수80200820008020462870
50금산면 농촌중심지활성화사업(일반지구)김제시장70935700007099416000
51금암길 개설공사남원시장1202557540012039988650
52신흥공원 조성사업익산시장1503628919015038060000
53순창 순화지구 도시개발사업전북개발공사사장140138521060140136954800