Overview

Dataset statistics

Number of variables9
Number of observations217
Missing cells390
Missing cells (%)20.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 KiB
Average record size in memory79.6 B

Variable types

Categorical2
Numeric7

Dataset

Description농지면적 및 농업진흥 지역면적 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=8M7880469YIY4864Z4L012453467&infSeq=1

Alerts

논(답)경지면적(ha) is highly overall correlated with 밭(전)경지면적(ha) and 6 other fieldsHigh correlation
밭(전)경지면적(ha) is highly overall correlated with 논(답)경지면적(ha) and 6 other fieldsHigh correlation
농업진흥지역면적(ha) is highly overall correlated with 논(답)경지면적(ha) and 6 other fieldsHigh correlation
농업보호구역면적(ha) is highly overall correlated with 논(답)경지면적(ha) and 5 other fieldsHigh correlation
농업진흥지역논(답)면적(ha) is highly overall correlated with 논(답)경지면적(ha) and 6 other fieldsHigh correlation
농업진흥지역밭(전)면적(ha) is highly overall correlated with 논(답)경지면적(ha) and 6 other fieldsHigh correlation
농업진흥지역논밭비율(%) is highly overall correlated with 논(답)경지면적(ha) and 5 other fieldsHigh correlation
시군명 is highly overall correlated with 논(답)경지면적(ha) and 6 other fieldsHigh correlation
논(답)경지면적(ha) has 12 (5.5%) missing valuesMissing
농업진흥지역면적(ha) has 70 (32.3%) missing valuesMissing
농업보호구역면적(ha) has 94 (43.3%) missing valuesMissing
농업진흥지역논(답)면적(ha) has 70 (32.3%) missing valuesMissing
농업진흥지역밭(전)면적(ha) has 74 (34.1%) missing valuesMissing
농업진흥지역논밭비율(%) has 70 (32.3%) missing valuesMissing
농업보호구역면적(ha) has 4 (1.8%) zerosZeros

Reproduction

Analysis started2024-03-12 23:54:50.334790
Analysis finished2024-03-12 23:54:55.216122
Duration4.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계일자
Categorical

Distinct7
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2022-12-31
31 
2021-12-31
31 
2020-12-31
31 
2019-12-31
31 
2018-12-31
31 
Other values (2)
62 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 31
14.3%
2021-12-31 31
14.3%
2020-12-31 31
14.3%
2019-12-31 31
14.3%
2018-12-31 31
14.3%
2017-12-31 31
14.3%
2016-12-31 31
14.3%

Length

2024-03-13T08:54:55.266980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:54:55.361164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 31
14.3%
2021-12-31 31
14.3%
2020-12-31 31
14.3%
2019-12-31 31
14.3%
2018-12-31 31
14.3%
2017-12-31 31
14.3%
2016-12-31 31
14.3%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
가평군
 
7
고양시
 
7
과천시
 
7
광명시
 
7
광주시
 
7
Other values (26)
182 

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row고양시
3rd row과천시
4th row광명시
5th row광주시

Common Values

ValueCountFrequency (%)
가평군 7
 
3.2%
고양시 7
 
3.2%
과천시 7
 
3.2%
광명시 7
 
3.2%
광주시 7
 
3.2%
구리시 7
 
3.2%
군포시 7
 
3.2%
김포시 7
 
3.2%
남양주시 7
 
3.2%
동두천시 7
 
3.2%
Other values (21) 147
67.7%

Length

2024-03-13T08:54:55.470847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 7
 
3.2%
안양시 7
 
3.2%
하남시 7
 
3.2%
포천시 7
 
3.2%
평택시 7
 
3.2%
파주시 7
 
3.2%
이천시 7
 
3.2%
의정부시 7
 
3.2%
의왕시 7
 
3.2%
용인시 7
 
3.2%
Other values (21) 147
67.7%

논(답)경지면적(ha)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct187
Distinct (%)91.2%
Missing12
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean2907.5707
Minimum0
Maximum14326
Zeros2
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-13T08:54:55.578556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.2
Q1113
median926
Q34220
95-th percentile12337
Maximum14326
Range14326
Interquartile range (IQR)4107

Descriptive statistics

Standard deviation3801.2972
Coefficient of variation (CV)1.3073791
Kurtosis0.9302817
Mean2907.5707
Median Absolute Deviation (MAD)879
Skewness1.3908747
Sum596052
Variance14449861
MonotonicityNot monotonic
2024-03-13T08:54:55.721219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34 3
 
1.4%
23 3
 
1.4%
448 2
 
0.9%
7 2
 
0.9%
64 2
 
0.9%
246 2
 
0.9%
66 2
 
0.9%
88 2
 
0.9%
6 2
 
0.9%
286 2
 
0.9%
Other values (177) 183
84.3%
(Missing) 12
 
5.5%
ValueCountFrequency (%)
0 2
0.9%
2 2
0.9%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 2
0.9%
7 2
0.9%
8 1
0.5%
10 1
0.5%
13 1
0.5%
ValueCountFrequency (%)
14326 1
0.5%
13662 1
0.5%
13653 1
0.5%
13488 1
0.5%
13074 1
0.5%
12920 1
0.5%
12767 1
0.5%
12699 1
0.5%
12679 1
0.5%
12512 1
0.5%

밭(전)경지면적(ha)
Real number (ℝ)

HIGH CORRELATION 

Distinct201
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2401.3871
Minimum29
Maximum7931
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-13T08:54:55.851151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile108.6
Q1300
median1860
Q33866
95-th percentile7460.4
Maximum7931
Range7902
Interquartile range (IQR)3566

Descriptive statistics

Standard deviation2455.141
Coefficient of variation (CV)1.0223845
Kurtosis-0.42952664
Mean2401.3871
Median Absolute Deviation (MAD)1599
Skewness0.92387441
Sum521101
Variance6027717.3
MonotonicityNot monotonic
2024-03-13T08:54:55.969373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
291 3
 
1.4%
106 2
 
0.9%
190 2
 
0.9%
3829 2
 
0.9%
1260 2
 
0.9%
2327 2
 
0.9%
205 2
 
0.9%
310 2
 
0.9%
368 2
 
0.9%
195 2
 
0.9%
Other values (191) 196
90.3%
ValueCountFrequency (%)
29 1
0.5%
30 1
0.5%
60 1
0.5%
63 2
0.9%
64 1
0.5%
72 1
0.5%
105 1
0.5%
106 2
0.9%
107 1
0.5%
109 1
0.5%
ValueCountFrequency (%)
7931 1
0.5%
7914 1
0.5%
7859 1
0.5%
7835 1
0.5%
7769 1
0.5%
7764 1
0.5%
7763 1
0.5%
7706 1
0.5%
7638 1
0.5%
7551 1
0.5%

농업진흥지역면적(ha)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct102
Distinct (%)69.4%
Missing70
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean4637.5782
Minimum22
Maximum14429.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-13T08:54:56.136372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile40.5
Q1232
median4078
Q39258.5
95-th percentile11861.83
Maximum14429.1
Range14407.1
Interquartile range (IQR)9026.5

Descriptive statistics

Standard deviation4488.3789
Coefficient of variation (CV)0.96782818
Kurtosis-0.95012847
Mean4637.5782
Median Absolute Deviation (MAD)3875
Skewness0.60973249
Sum681724
Variance20145545
MonotonicityNot monotonic
2024-03-13T08:54:56.266515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
181.0 6
 
2.8%
39.0 5
 
2.3%
232.0 5
 
2.3%
124.0 5
 
2.3%
748.0 4
 
1.8%
22.0 3
 
1.4%
203.0 3
 
1.4%
5202.0 3
 
1.4%
4206.0 3
 
1.4%
9256.0 3
 
1.4%
Other values (92) 107
49.3%
(Missing) 70
32.3%
ValueCountFrequency (%)
22.0 3
1.4%
39.0 5
2.3%
44.0 1
 
0.5%
44.6 1
 
0.5%
46.0 3
1.4%
46.1 1
 
0.5%
64.0 1
 
0.5%
98.0 1
 
0.5%
124.0 5
2.3%
124.4 1
 
0.5%
ValueCountFrequency (%)
14429.1 1
0.5%
14412.0 1
0.5%
14203.0 1
0.5%
14189.0 1
0.5%
14184.0 1
0.5%
14183.0 1
0.5%
13712.0 1
0.5%
11875.9 1
0.5%
11829.0 1
0.5%
11709.0 1
0.5%

농업보호구역면적(ha)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct68
Distinct (%)55.3%
Missing94
Missing (%)43.3%
Infinite0
Infinite (%)0.0%
Mean499.00081
Minimum0
Maximum1928
Zeros4
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-13T08:54:56.376578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile51
Q174
median381
Q3820
95-th percentile1645.12
Maximum1928
Range1928
Interquartile range (IQR)746

Descriptive statistics

Standard deviation488.8836
Coefficient of variation (CV)0.97972507
Kurtosis1.2041809
Mean499.00081
Median Absolute Deviation (MAD)311
Skewness1.2723158
Sum61377.1
Variance239007.18
MonotonicityNot monotonic
2024-03-13T08:54:56.496955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51.0 7
 
3.2%
60.0 6
 
2.8%
56.0 5
 
2.3%
1127.0 4
 
1.8%
133.0 4
 
1.8%
471.0 4
 
1.8%
381.0 4
 
1.8%
74.0 4
 
1.8%
820.0 4
 
1.8%
0.0 4
 
1.8%
Other values (58) 77
35.5%
(Missing) 94
43.3%
ValueCountFrequency (%)
0.0 4
1.8%
47.1 1
 
0.5%
51.0 7
3.2%
51.2 1
 
0.5%
53.6 1
 
0.5%
56.0 5
2.3%
60.0 6
2.8%
60.4 1
 
0.5%
70.0 2
 
0.9%
74.0 4
1.8%
ValueCountFrequency (%)
1928.0 1
 
0.5%
1910.0 1
 
0.5%
1909.0 2
0.9%
1908.0 1
 
0.5%
1757.0 1
 
0.5%
1701.8 1
 
0.5%
1135.0 1
 
0.5%
1128.0 1
 
0.5%
1127.0 4
1.8%
1091.0 2
0.9%

농업진흥지역논(답)면적(ha)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct105
Distinct (%)71.4%
Missing70
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean3266.1796
Minimum18
Maximum11449.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-13T08:54:56.612381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile31.2
Q1199
median2925
Q36202.5
95-th percentile8812.37
Maximum11449.1
Range11431.1
Interquartile range (IQR)6003.5

Descriptive statistics

Standard deviation3323.4183
Coefficient of variation (CV)1.0175247
Kurtosis-0.37717999
Mean3266.1796
Median Absolute Deviation (MAD)2767
Skewness0.82654082
Sum480128.4
Variance11045109
MonotonicityNot monotonic
2024-03-13T08:54:56.720137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199.0 6
 
2.8%
71.0 5
 
2.3%
30.0 5
 
2.3%
158.0 3
 
1.4%
3213.0 3
 
1.4%
18.0 3
 
1.4%
39.0 3
 
1.4%
127.0 3
 
1.4%
2925.0 3
 
1.4%
473.0 3
 
1.4%
Other values (95) 110
50.7%
(Missing) 70
32.3%
ValueCountFrequency (%)
18.0 3
1.4%
30.0 5
2.3%
34.0 1
 
0.5%
34.4 1
 
0.5%
39.0 3
1.4%
39.1 1
 
0.5%
70.0 1
 
0.5%
70.9 1
 
0.5%
71.0 5
2.3%
85.0 2
 
0.9%
ValueCountFrequency (%)
11449.1 1
0.5%
11443.0 1
0.5%
11328.0 1
0.5%
11319.0 1
0.5%
11314.0 2
0.9%
11161.0 1
0.5%
8815.1 1
0.5%
8806.0 1
0.5%
8799.0 1
0.5%
8798.0 1
0.5%

농업진흥지역밭(전)면적(ha)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct93
Distinct (%)65.0%
Missing74
Missing (%)34.1%
Infinite0
Infinite (%)0.0%
Mean523.49301
Minimum0
Maximum2211.6
Zeros1
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-13T08:54:56.834403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q119
median440
Q3712.5
95-th percentile1255.53
Maximum2211.6
Range2211.6
Interquartile range (IQR)693.5

Descriptive statistics

Standard deviation546.71166
Coefficient of variation (CV)1.0443533
Kurtosis1.9804339
Mean523.49301
Median Absolute Deviation (MAD)341
Skewness1.3966917
Sum74859.5
Variance298893.64
MonotonicityNot monotonic
2024-03-13T08:54:57.188217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.0 7
 
3.2%
5.0 6
 
2.8%
9.0 6
 
2.8%
103.0 5
 
2.3%
3.0 5
 
2.3%
440.0 4
 
1.8%
988.0 4
 
1.8%
678.0 4
 
1.8%
141.0 4
 
1.8%
19.0 3
 
1.4%
Other values (83) 95
43.8%
(Missing) 74
34.1%
ValueCountFrequency (%)
0.0 1
 
0.5%
0.2 1
 
0.5%
1.0 1
 
0.5%
2.0 1
 
0.5%
3.0 5
2.3%
3.4 1
 
0.5%
5.0 6
2.8%
5.4 1
 
0.5%
9.0 6
2.8%
9.2 1
 
0.5%
ValueCountFrequency (%)
2211.6 1
0.5%
2200.0 1
0.5%
2199.0 1
0.5%
2190.0 1
0.5%
2187.0 2
0.9%
2176.0 1
0.5%
1255.7 1
0.5%
1254.0 1
0.5%
1251.0 1
0.5%
1250.0 1
0.5%

농업진흥지역논밭비율(%)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct129
Distinct (%)87.8%
Missing70
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean39.34898
Minimum4
Maximum88.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-13T08:54:57.298501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5.36
Q117.4
median44.5
Q351.05
95-th percentile77.57
Maximum88.4
Range84.4
Interquartile range (IQR)33.65

Descriptive statistics

Standard deviation23.088574
Coefficient of variation (CV)0.58676423
Kurtosis-0.97810449
Mean39.34898
Median Absolute Deviation (MAD)23
Skewness0.17757734
Sum5784.3
Variance533.08224
MonotonicityNot monotonic
2024-03-13T08:54:57.404211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44.7 3
 
1.4%
15.4 3
 
1.4%
20.6 3
 
1.4%
15.6 2
 
0.9%
47.3 2
 
0.9%
10.6 2
 
0.9%
8.4 2
 
0.9%
49.3 2
 
0.9%
10.2 2
 
0.9%
4.9 2
 
0.9%
Other values (119) 124
57.1%
(Missing) 70
32.3%
ValueCountFrequency (%)
4.0 1
0.5%
4.1 1
0.5%
4.2 1
0.5%
4.4 1
0.5%
4.5 1
0.5%
4.9 2
0.9%
5.3 1
0.5%
5.5 1
0.5%
5.7 1
0.5%
8.4 2
0.9%
ValueCountFrequency (%)
88.4 1
0.5%
87.0 1
0.5%
85.8 1
0.5%
84.4 1
0.5%
83.4 1
0.5%
79.2 1
0.5%
78.9 1
0.5%
77.6 1
0.5%
77.5 1
0.5%
75.3 1
0.5%

Interactions

2024-03-13T08:54:54.262949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:50.637659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.153203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.727308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.295704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.109312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.660053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.335080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:50.708419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.229210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.817097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.390604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.182971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.739595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.415692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:50.781239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.304520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.898079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.476101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.268816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.839226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.532038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:50.851467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.376297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.972157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.566754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.354907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.964586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.624150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:50.923044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.453372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.060302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.663060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.438227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.055811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.715413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:50.990685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.539900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.149585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.975296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.509365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.137317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.794479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.067766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:51.632149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:52.223260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.040033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:53.585689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:54.202066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:54:57.483534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계일자시군명논(답)경지면적(ha)밭(전)경지면적(ha)농업진흥지역면적(ha)농업보호구역면적(ha)농업진흥지역논(답)면적(ha)농업진흥지역밭(전)면적(ha)농업진흥지역논밭비율(%)
집계일자1.0000.0000.0000.0000.0000.0000.0000.0000.000
시군명0.0001.0000.9460.9610.9810.9470.9820.9990.963
논(답)경지면적(ha)0.0000.9461.0000.8960.9690.7850.9050.8290.928
밭(전)경지면적(ha)0.0000.9610.8961.0000.9070.7860.7690.7740.874
농업진흥지역면적(ha)0.0000.9810.9690.9071.0000.7960.9430.8760.932
농업보호구역면적(ha)0.0000.9470.7850.7860.7961.0000.7560.7730.750
농업진흥지역논(답)면적(ha)0.0000.9820.9050.7690.9430.7561.0000.8210.788
농업진흥지역밭(전)면적(ha)0.0000.9990.8290.7740.8760.7730.8211.0000.845
농업진흥지역논밭비율(%)0.0000.9630.9280.8740.9320.7500.7880.8451.000
2024-03-13T08:54:57.607440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계일자시군명
집계일자1.0000.000
시군명0.0001.000
2024-03-13T08:54:57.701340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
논(답)경지면적(ha)밭(전)경지면적(ha)농업진흥지역면적(ha)농업보호구역면적(ha)농업진흥지역논(답)면적(ha)농업진흥지역밭(전)면적(ha)농업진흥지역논밭비율(%)집계일자시군명
논(답)경지면적(ha)1.0000.8910.9780.8360.9850.7750.7750.0000.681
밭(전)경지면적(ha)0.8911.0000.8810.8320.8770.8400.6180.0000.735
농업진흥지역면적(ha)0.9780.8811.0000.7780.9950.8400.8280.0000.847
농업보호구역면적(ha)0.8360.8320.7781.0000.8060.6200.4700.0000.741
농업진흥지역논(답)면적(ha)0.9850.8770.9950.8061.0000.8210.8280.0000.854
농업진흥지역밭(전)면적(ha)0.7750.8400.8400.6200.8211.0000.8190.0000.895
농업진흥지역논밭비율(%)0.7750.6180.8280.4700.8280.8191.0000.0000.772
집계일자0.0000.0000.0000.0000.0000.0000.0001.0000.000
시군명0.6810.7350.8470.7410.8540.8950.7720.0001.000

Missing values

2024-03-13T08:54:54.884508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:54:55.015752image/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.
2024-03-13T08:54:55.148144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

집계일자시군명논(답)경지면적(ha)밭(전)경지면적(ha)농업진흥지역면적(ha)농업보호구역면적(ha)농업진흥지역논(답)면적(ha)농업진흥지역밭(전)면적(ha)농업진흥지역논밭비율(%)
02022-12-31가평군8381925607.074.0467.0101.020.6
12022-12-31고양시107023433216.051.01718.0651.069.4
22022-12-31과천시3182<NA><NA><NA><NA><NA>
32022-12-31광명시65291<NA><NA><NA><NA><NA>
42022-12-31광주시5851529669.079.0470.0139.028.8
52022-12-31구리시0217<NA><NA><NA><NA><NA>
62022-12-31군포시79154<NA><NA><NA><NA><NA>
72022-12-31김포시436218606131.0129.04466.0353.077.5
82022-12-31남양주시164214598.051.086.011.04.2
92022-12-31동두천시3436722.00.018.00.04.5
집계일자시군명논(답)경지면적(ha)밭(전)경지면적(ha)농업진흥지역면적(ha)농업보호구역면적(ha)농업진흥지역논(답)면적(ha)농업진흥지역밭(전)면적(ha)농업진흥지역논밭비율(%)
2072016-12-31오산시280211124.460.470.913.117.1
2082016-12-31용인시442129494089.8571.92995.3243.543.9
2092016-12-31의왕시106401<NA><NA><NA><NA><NA>
2102016-12-31의정부시15022144.6<NA>34.45.410.7
2112016-12-31이천시9141791410537.0917.57220.81215.949.5
2122016-12-31파주시7102382910627.3386.26906.62211.683.4
2132016-12-31평택시13653556914429.1405.411449.1581.162.6
2142016-12-31포천시393060065230.6289.43187.21255.744.7
2152016-12-31하남시13353<NA><NA><NA><NA><NA>
2162016-12-31화성시14326770611875.9878.28815.1737.443.4