Overview

Dataset statistics

Number of variables18
Number of observations227
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.6 KiB
Average record size in memory160.6 B

Variable types

Categorical1
Text1
Numeric16

Dataset

Description농업, 임업 등에 사용되는 지하수의 세부용도별 시설현황 및 이용량현황 정보 제공(세부용도는 전작용, 답작용, 원예용 등)
URLhttps://www.data.go.kr/data/15054536/fileData.do

Alerts

총계-개소수 is highly overall correlated with 총계-이용량 and 14 other fieldsHigh correlation
총계-이용량 is highly overall correlated with 총계-개소수 and 12 other fieldsHigh correlation
전작용-개소수 is highly overall correlated with 총계-개소수 and 12 other fieldsHigh correlation
전작용-이용량 is highly overall correlated with 총계-개소수 and 12 other fieldsHigh correlation
답작용-개소수 is highly overall correlated with 총계-개소수 and 14 other fieldsHigh correlation
답작용-이용량 is highly overall correlated with 총계-개소수 and 13 other fieldsHigh correlation
원예용-개소수 is highly overall correlated with 총계-개소수 and 12 other fieldsHigh correlation
원예용-이용량 is highly overall correlated with 총계-개소수 and 12 other fieldsHigh correlation
수산업용-개소수 is highly overall correlated with 총계-개소수 and 5 other fieldsHigh correlation
수산업용-이용량 is highly overall correlated with 총계-개소수 and 7 other fieldsHigh correlation
축산업용-개소수 is highly overall correlated with 총계-개소수 and 14 other fieldsHigh correlation
축산업용-이용량 is highly overall correlated with 총계-개소수 and 13 other fieldsHigh correlation
양어장용-개소수 is highly overall correlated with 총계-개소수 and 14 other fieldsHigh correlation
양어장용-이용량 is highly overall correlated with 총계-개소수 and 14 other fieldsHigh correlation
기타-개소수 is highly overall correlated with 총계-개소수 and 12 other fieldsHigh correlation
기타-이용량 is highly overall correlated with 총계-개소수 and 12 other fieldsHigh correlation
총계-이용량 has 3 (1.3%) zerosZeros
전작용-개소수 has 22 (9.7%) zerosZeros
전작용-이용량 has 23 (10.1%) zerosZeros
답작용-개소수 has 27 (11.9%) zerosZeros
답작용-이용량 has 29 (12.8%) zerosZeros
원예용-개소수 has 22 (9.7%) zerosZeros
원예용-이용량 has 23 (10.1%) zerosZeros
수산업용-개소수 has 108 (47.6%) zerosZeros
수산업용-이용량 has 114 (50.2%) zerosZeros
축산업용-개소수 has 56 (24.7%) zerosZeros
축산업용-이용량 has 56 (24.7%) zerosZeros
양어장용-개소수 has 68 (30.0%) zerosZeros
양어장용-이용량 has 69 (30.4%) zerosZeros
기타-개소수 has 17 (7.5%) zerosZeros
기타-이용량 has 19 (8.4%) zerosZeros

Reproduction

Analysis started2023-12-12 22:38:46.804581
Analysis finished2023-12-12 22:39:13.738407
Duration26.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct16
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
경기도
31 
경상북도
23 
서울특별시
23 
전라남도
22 
강원도
18 
Other values (11)
110 

Length

Max length7
Median length5
Mean length4.1409692
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 31
13.7%
경상북도 23
10.1%
서울특별시 23
10.1%
전라남도 22
9.7%
강원도 18
7.9%
경상남도 18
7.9%
부산광역시 16
7.0%
충청남도 15
6.6%
대구광역시 14
6.2%
전라북도 14
6.2%
Other values (6) 33
14.5%

Length

2023-12-13T07:39:13.830950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 31
13.7%
경상북도 23
10.1%
서울특별시 23
10.1%
전라남도 22
9.7%
강원도 18
7.9%
경상남도 18
7.9%
부산광역시 16
7.0%
충청남도 15
6.6%
대구광역시 14
6.2%
전라북도 14
6.2%
Other values (6) 33
14.5%
Distinct207
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T07:39:14.181009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.938326
Min length2

Characters and Unicode

Total characters667
Distinct characters133
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)88.1%

Sample

1st row강릉시
2nd row고성군
3rd row동해시
4th row삼척시
5th row속초시
ValueCountFrequency (%)
중구 5
 
2.2%
동구 5
 
2.2%
서구 5
 
2.2%
북구 4
 
1.8%
남구 4
 
1.8%
강서구 2
 
0.9%
고성군 2
 
0.9%
옹진군 1
 
0.4%
중랑구 1
 
0.4%
부평구 1
 
0.4%
Other values (197) 197
86.8%
2023-12-13T07:39:14.747034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
12.7%
79
 
11.8%
71
 
10.6%
22
 
3.3%
20
 
3.0%
18
 
2.7%
17
 
2.5%
16
 
2.4%
15
 
2.2%
13
 
1.9%
Other values (123) 311
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 667
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
85
 
12.7%
79
 
11.8%
71
 
10.6%
22
 
3.3%
20
 
3.0%
18
 
2.7%
17
 
2.5%
16
 
2.4%
15
 
2.2%
13
 
1.9%
Other values (123) 311
46.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 667
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
85
 
12.7%
79
 
11.8%
71
 
10.6%
22
 
3.3%
20
 
3.0%
18
 
2.7%
17
 
2.5%
16
 
2.4%
15
 
2.2%
13
 
1.9%
Other values (123) 311
46.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 667
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
85
 
12.7%
79
 
11.8%
71
 
10.6%
22
 
3.3%
20
 
3.0%
18
 
2.7%
17
 
2.5%
16
 
2.4%
15
 
2.2%
13
 
1.9%
Other values (123) 311
46.6%

총계-개소수
Real number (ℝ)

HIGH CORRELATION 

Distinct203
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3701.7313
Minimum0
Maximum34767
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:14.913278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q1344
median1904
Q34846.5
95-th percentile13116.4
Maximum34767
Range34767
Interquartile range (IQR)4502.5

Descriptive statistics

Standard deviation5026.439
Coefficient of variation (CV)1.3578617
Kurtosis8.7571679
Mean3701.7313
Median Absolute Deviation (MAD)1858
Skewness2.5170857
Sum840293
Variance25265089
MonotonicityNot monotonic
2023-12-13T07:39:15.101522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 8
 
3.5%
6 5
 
2.2%
2 5
 
2.2%
8 3
 
1.3%
17 2
 
0.9%
830 2
 
0.9%
15 2
 
0.9%
3 2
 
0.9%
19 2
 
0.9%
711 2
 
0.9%
Other values (193) 194
85.5%
ValueCountFrequency (%)
0 1
 
0.4%
1 8
3.5%
2 5
2.2%
3 2
 
0.9%
4 1
 
0.4%
6 5
2.2%
7 1
 
0.4%
8 3
 
1.3%
9 1
 
0.4%
15 2
 
0.9%
ValueCountFrequency (%)
34767 1
0.4%
25696 1
0.4%
21896 1
0.4%
21274 1
0.4%
19819 1
0.4%
19783 1
0.4%
17071 1
0.4%
14451 1
0.4%
14143 1
0.4%
14008 1
0.4%

총계-이용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct225
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6962383.7
Minimum0
Maximum65615818
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:15.290677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2649.4
Q1551634
median3872530
Q310754962
95-th percentile23720458
Maximum65615818
Range65615818
Interquartile range (IQR)10203328

Descriptive statistics

Standard deviation9096086.3
Coefficient of variation (CV)1.3064615
Kurtosis9.6627409
Mean6962383.7
Median Absolute Deviation (MAD)3726549
Skewness2.5155931
Sum1.5804611 × 109
Variance8.2738786 × 1013
MonotonicityNot monotonic
2023-12-13T07:39:15.452702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
1.3%
5816262 1
 
0.4%
730 1
 
0.4%
12472 1
 
0.4%
22290 1
 
0.4%
10284551 1
 
0.4%
117824 1
 
0.4%
25002 1
 
0.4%
645575 1
 
0.4%
3036358 1
 
0.4%
Other values (215) 215
94.7%
ValueCountFrequency (%)
0 3
1.3%
300 1
 
0.4%
580 1
 
0.4%
630 1
 
0.4%
730 1
 
0.4%
800 1
 
0.4%
807 1
 
0.4%
1008 1
 
0.4%
2194 1
 
0.4%
2467 1
 
0.4%
ValueCountFrequency (%)
65615818 1
0.4%
46698622 1
0.4%
45361353 1
0.4%
33241339 1
0.4%
33133431 1
0.4%
29066643 1
0.4%
26653320 1
0.4%
26627739 1
0.4%
26275460 1
0.4%
25671348 1
0.4%

전작용-개소수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct191
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1167.9559
Minimum0
Maximum11677
Zeros22
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:15.603054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1146
median558
Q31573
95-th percentile4279.6
Maximum11677
Range11677
Interquartile range (IQR)1427

Descriptive statistics

Standard deviation1654.8966
Coefficient of variation (CV)1.416917
Kurtosis11.784191
Mean1167.9559
Median Absolute Deviation (MAD)544
Skewness2.8992851
Sum265126
Variance2738682.8
MonotonicityNot monotonic
2023-12-13T07:39:15.758213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
9.7%
10 3
 
1.3%
1 3
 
1.3%
284 2
 
0.9%
290 2
 
0.9%
14 2
 
0.9%
995 2
 
0.9%
329 2
 
0.9%
145 2
 
0.9%
316 2
 
0.9%
Other values (181) 185
81.5%
ValueCountFrequency (%)
0 22
9.7%
1 3
 
1.3%
2 2
 
0.9%
3 1
 
0.4%
5 1
 
0.4%
6 1
 
0.4%
8 2
 
0.9%
9 2
 
0.9%
10 3
 
1.3%
14 2
 
0.9%
ValueCountFrequency (%)
11677 1
0.4%
10484 1
0.4%
6765 1
0.4%
6472 1
0.4%
6266 1
0.4%
5864 1
0.4%
5247 1
0.4%
5189 1
0.4%
5026 1
0.4%
4523 1
0.4%

전작용-이용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct205
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2702401.2
Minimum0
Maximum46476214
Zeros23
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:15.900853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1238064
median1187982
Q33262537
95-th percentile9666166.5
Maximum46476214
Range46476214
Interquartile range (IQR)3024473

Descriptive statistics

Standard deviation5199413.1
Coefficient of variation (CV)1.9239975
Kurtosis41.422948
Mean2702401.2
Median Absolute Deviation (MAD)1169037
Skewness5.6495855
Sum6.1344507 × 108
Variance2.7033897 × 1013
MonotonicityNot monotonic
2023-12-13T07:39:16.031811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23
 
10.1%
4336647 1
 
0.4%
14212 1
 
0.4%
689815 1
 
0.4%
99530 1
 
0.4%
8125214 1
 
0.4%
1349606 1
 
0.4%
1034671 1
 
0.4%
26503 1
 
0.4%
383662 1
 
0.4%
Other values (195) 195
85.9%
ValueCountFrequency (%)
0 23
10.1%
220 1
 
0.4%
300 1
 
0.4%
2115 1
 
0.4%
7436 1
 
0.4%
11342 1
 
0.4%
11854 1
 
0.4%
12403 1
 
0.4%
12407 1
 
0.4%
12740 1
 
0.4%
ValueCountFrequency (%)
46476214 1
0.4%
44920466 1
0.4%
21178715 1
0.4%
20228350 1
0.4%
17700208 1
0.4%
11410106 1
0.4%
11399156 1
0.4%
11062315 1
0.4%
10576514 1
0.4%
10048063 1
0.4%

답작용-개소수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct183
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.2026
Minimum0
Maximum30841
Zeros27
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:16.163098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q136.5
median668
Q32212.5
95-th percentile7954.5
Maximum30841
Range30841
Interquartile range (IQR)2176

Descriptive statistics

Standard deviation3668.4066
Coefficient of variation (CV)1.8185613
Kurtosis20.607084
Mean2017.2026
Median Absolute Deviation (MAD)664
Skewness3.8149849
Sum457905
Variance13457207
MonotonicityNot monotonic
2023-12-13T07:39:16.311167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27
 
11.9%
1 6
 
2.6%
4 3
 
1.3%
41 3
 
1.3%
38 2
 
0.9%
28 2
 
0.9%
7 2
 
0.9%
45 2
 
0.9%
870 2
 
0.9%
999 2
 
0.9%
Other values (173) 176
77.5%
ValueCountFrequency (%)
0 27
11.9%
1 6
 
2.6%
2 2
 
0.9%
3 1
 
0.4%
4 3
 
1.3%
5 1
 
0.4%
6 1
 
0.4%
7 2
 
0.9%
8 1
 
0.4%
10 2
 
0.9%
ValueCountFrequency (%)
30841 1
0.4%
19836 1
0.4%
17223 1
0.4%
14788 1
0.4%
14645 1
0.4%
13473 1
0.4%
10720 1
0.4%
10527 1
0.4%
8618 1
0.4%
8564 1
0.4%

답작용-이용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct198
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2674075.5
Minimum0
Maximum44443353
Zeros29
Zeros (%)12.8%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:16.473562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q135162
median743846
Q33386745
95-th percentile12394156
Maximum44443353
Range44443353
Interquartile range (IQR)3351583

Descriptive statistics

Standard deviation4837936.7
Coefficient of variation (CV)1.8091998
Kurtosis26.469114
Mean2674075.5
Median Absolute Deviation (MAD)743292
Skewness4.1431081
Sum6.0701513 × 108
Variance2.3405632 × 1013
MonotonicityNot monotonic
2023-12-13T07:39:16.621036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29
 
12.8%
34886 2
 
0.9%
875458 1
 
0.4%
4363210 1
 
0.4%
701898 1
 
0.4%
53032 1
 
0.4%
4474917 1
 
0.4%
378810 1
 
0.4%
28899 1
 
0.4%
29435 1
 
0.4%
Other values (188) 188
82.8%
ValueCountFrequency (%)
0 29
12.8%
554 1
 
0.4%
594 1
 
0.4%
630 1
 
0.4%
807 1
 
0.4%
1211 1
 
0.4%
1444 1
 
0.4%
2100 1
 
0.4%
2686 1
 
0.4%
5170 1
 
0.4%
ValueCountFrequency (%)
44443353 1
0.4%
24840367 1
0.4%
17212933 1
0.4%
16918227 1
0.4%
16429641 1
0.4%
14837525 1
0.4%
14554070 1
0.4%
14183065 1
0.4%
14050000 1
0.4%
13600466 1
0.4%

원예용-개소수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct146
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean274.25991
Minimum0
Maximum7653
Zeros22
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:17.076915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median59
Q3286.5
95-th percentile1152.1
Maximum7653
Range7653
Interquartile range (IQR)276.5

Descriptive statistics

Standard deviation668.94669
Coefficient of variation (CV)2.4390976
Kurtosis70.21416
Mean274.25991
Median Absolute Deviation (MAD)58
Skewness7.250473
Sum62257
Variance447489.67
MonotonicityNot monotonic
2023-12-13T07:39:17.229220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
9.7%
1 7
 
3.1%
2 7
 
3.1%
9 7
 
3.1%
6 4
 
1.8%
14 4
 
1.8%
3 4
 
1.8%
12 4
 
1.8%
22 4
 
1.8%
38 3
 
1.3%
Other values (136) 161
70.9%
ValueCountFrequency (%)
0 22
9.7%
1 7
 
3.1%
2 7
 
3.1%
3 4
 
1.8%
4 2
 
0.9%
5 2
 
0.9%
6 4
 
1.8%
7 1
 
0.4%
9 7
 
3.1%
10 3
 
1.3%
ValueCountFrequency (%)
7653 1
0.4%
4119 1
0.4%
2386 1
0.4%
1823 1
0.4%
1692 1
0.4%
1690 1
0.4%
1540 1
0.4%
1520 1
0.4%
1406 1
0.4%
1365 1
0.4%

원예용-이용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct205
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean585290.7
Minimum0
Maximum20351422
Zeros23
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:17.395295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115961.5
median104184
Q3447024
95-th percentile2022620
Maximum20351422
Range20351422
Interquartile range (IQR)431062.5

Descriptive statistics

Standard deviation1911940.8
Coefficient of variation (CV)3.2666516
Kurtosis70.554649
Mean585290.7
Median Absolute Deviation (MAD)102998
Skewness7.8577513
Sum1.3286099 × 108
Variance3.6555176 × 1012
MonotonicityNot monotonic
2023-12-13T07:39:17.572893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23
 
10.1%
136774 1
 
0.4%
2605 1
 
0.4%
731225 1
 
0.4%
8961 1
 
0.4%
3450 1
 
0.4%
81308 1
 
0.4%
314101 1
 
0.4%
14222 1
 
0.4%
448661 1
 
0.4%
Other values (195) 195
85.9%
ValueCountFrequency (%)
0 23
10.1%
720 1
 
0.4%
730 1
 
0.4%
1008 1
 
0.4%
1186 1
 
0.4%
1234 1
 
0.4%
1799 1
 
0.4%
2360 1
 
0.4%
2605 1
 
0.4%
3450 1
 
0.4%
ValueCountFrequency (%)
20351422 1
0.4%
16012979 1
0.4%
9413437 1
0.4%
6070868 1
0.4%
3050297 1
0.4%
2764720 1
0.4%
2655538 1
0.4%
2475054 1
0.4%
2438650 1
0.4%
2389529 1
0.4%

수산업용-개소수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.092511
Minimum0
Maximum624
Zeros108
Zeros (%)47.6%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:17.736758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile17.7
Maximum624
Range624
Interquartile range (IQR)3

Descriptive statistics

Standard deviation43.235057
Coefficient of variation (CV)6.0958745
Kurtosis185.72186
Mean7.092511
Median Absolute Deviation (MAD)1
Skewness13.140156
Sum1610
Variance1869.2702
MonotonicityNot monotonic
2023-12-13T07:39:17.878157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 108
47.6%
1 37
 
16.3%
2 18
 
7.9%
4 13
 
5.7%
3 11
 
4.8%
13 4
 
1.8%
6 3
 
1.3%
8 3
 
1.3%
17 3
 
1.3%
7 2
 
0.9%
Other values (18) 25
 
11.0%
ValueCountFrequency (%)
0 108
47.6%
1 37
 
16.3%
2 18
 
7.9%
3 11
 
4.8%
4 13
 
5.7%
5 2
 
0.9%
6 3
 
1.3%
7 2
 
0.9%
8 3
 
1.3%
9 2
 
0.9%
ValueCountFrequency (%)
624 1
0.4%
123 1
0.4%
101 1
0.4%
94 1
0.4%
48 1
0.4%
36 1
0.4%
29 1
0.4%
21 1
0.4%
19 2
0.9%
18 2
0.9%

수산업용-이용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26228.216
Minimum0
Maximum721343
Zeros114
Zeros (%)50.2%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:18.006939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q312776
95-th percentile129218.5
Maximum721343
Range721343
Interquartile range (IQR)12776

Descriptive statistics

Standard deviation82032.984
Coefficient of variation (CV)3.1276616
Kurtosis39.218476
Mean26228.216
Median Absolute Deviation (MAD)0
Skewness5.7492737
Sum5953805
Variance6.7294105 × 109
MonotonicityNot monotonic
2023-12-13T07:39:18.137510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 114
50.2%
7300 5
 
2.2%
1460 4
 
1.8%
36135 2
 
0.9%
18381 1
 
0.4%
44009 1
 
0.4%
77848 1
 
0.4%
31377 1
 
0.4%
59385 1
 
0.4%
125050 1
 
0.4%
Other values (96) 96
42.3%
ValueCountFrequency (%)
0 114
50.2%
244 1
 
0.4%
270 1
 
0.4%
365 1
 
0.4%
453 1
 
0.4%
590 1
 
0.4%
709 1
 
0.4%
1022 1
 
0.4%
1080 1
 
0.4%
1460 4
 
1.8%
ValueCountFrequency (%)
721343 1
0.4%
639239 1
0.4%
431959 1
0.4%
306272 1
0.4%
301660 1
0.4%
289544 1
0.4%
202105 1
0.4%
184955 1
0.4%
154510 1
0.4%
146048 1
0.4%

축산업용-개소수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct112
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.101322
Minimum0
Maximum568
Zeros56
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:18.284864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median19
Q396.5
95-th percentile254.6
Maximum568
Range568
Interquartile range (IQR)95.5

Descriptive statistics

Standard deviation90.028134
Coefficient of variation (CV)1.4496976
Kurtosis6.2679671
Mean62.101322
Median Absolute Deviation (MAD)19
Skewness2.2435345
Sum14097
Variance8105.0649
MonotonicityNot monotonic
2023-12-13T07:39:18.435060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 56
24.7%
1 7
 
3.1%
4 6
 
2.6%
9 5
 
2.2%
6 5
 
2.2%
5 5
 
2.2%
7 5
 
2.2%
2 4
 
1.8%
18 4
 
1.8%
3 3
 
1.3%
Other values (102) 127
55.9%
ValueCountFrequency (%)
0 56
24.7%
1 7
 
3.1%
2 4
 
1.8%
3 3
 
1.3%
4 6
 
2.6%
5 5
 
2.2%
6 5
 
2.2%
7 5
 
2.2%
8 1
 
0.4%
9 5
 
2.2%
ValueCountFrequency (%)
568 1
0.4%
398 1
0.4%
382 1
0.4%
379 1
0.4%
346 1
0.4%
330 1
0.4%
324 1
0.4%
316 1
0.4%
287 1
0.4%
285 1
0.4%

축산업용-이용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct172
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean178052.33
Minimum0
Maximum1669821
Zeros56
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:18.572268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1326.5
median48121
Q3281070
95-th percentile693542.5
Maximum1669821
Range1669821
Interquartile range (IQR)280743.5

Descriptive statistics

Standard deviation275831.31
Coefficient of variation (CV)1.5491587
Kurtosis8.6394009
Mean178052.33
Median Absolute Deviation (MAD)48121
Skewness2.5877336
Sum40417879
Variance7.6082913 × 1010
MonotonicityNot monotonic
2023-12-13T07:39:18.706298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 56
 
24.7%
167738 1
 
0.4%
399510 1
 
0.4%
295712 1
 
0.4%
31620 1
 
0.4%
10715 1
 
0.4%
111717 1
 
0.4%
550361 1
 
0.4%
154272 1
 
0.4%
16665 1
 
0.4%
Other values (162) 162
71.4%
ValueCountFrequency (%)
0 56
24.7%
300 1
 
0.4%
353 1
 
0.4%
480 1
 
0.4%
600 1
 
0.4%
1469 1
 
0.4%
1500 1
 
0.4%
1887 1
 
0.4%
1908 1
 
0.4%
2667 1
 
0.4%
ValueCountFrequency (%)
1669821 1
0.4%
1635129 1
0.4%
1298790 1
0.4%
1219810 1
0.4%
1146318 1
0.4%
1079095 1
0.4%
760755 1
0.4%
755058 1
0.4%
746349 1
0.4%
742808 1
0.4%

양어장용-개소수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.8414097
Minimum0
Maximum185
Zeros68
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:18.838013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q311.5
95-th percentile33
Maximum185
Range185
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation21.181296
Coefficient of variation (CV)2.1522624
Kurtosis37.635562
Mean9.8414097
Median Absolute Deviation (MAD)4
Skewness5.5542628
Sum2234
Variance448.6473
MonotonicityNot monotonic
2023-12-13T07:39:19.003757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 68
30.0%
1 20
 
8.8%
2 18
 
7.9%
4 14
 
6.2%
5 10
 
4.4%
7 9
 
4.0%
8 7
 
3.1%
9 7
 
3.1%
14 6
 
2.6%
3 6
 
2.6%
Other values (32) 62
27.3%
ValueCountFrequency (%)
0 68
30.0%
1 20
 
8.8%
2 18
 
7.9%
3 6
 
2.6%
4 14
 
6.2%
5 10
 
4.4%
6 6
 
2.6%
7 9
 
4.0%
8 7
 
3.1%
9 7
 
3.1%
ValueCountFrequency (%)
185 1
0.4%
156 1
0.4%
148 1
0.4%
75 1
0.4%
68 1
0.4%
54 1
0.4%
48 1
0.4%
39 1
0.4%
35 2
0.9%
34 1
0.4%

양어장용-이용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct159
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122597.27
Minimum0
Maximum5508175
Zeros69
Zeros (%)30.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:19.131021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median18000
Q380279.5
95-th percentile511913
Maximum5508175
Range5508175
Interquartile range (IQR)80279.5

Descriptive statistics

Standard deviation439383.31
Coefficient of variation (CV)3.5839566
Kurtosis104.82256
Mean122597.27
Median Absolute Deviation (MAD)18000
Skewness9.3153231
Sum27829581
Variance1.9305769 × 1011
MonotonicityNot monotonic
2023-12-13T07:39:19.276748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 69
30.4%
68691 1
 
0.4%
9900 1
 
0.4%
71123 1
 
0.4%
593100 1
 
0.4%
191773 1
 
0.4%
5456 1
 
0.4%
285265 1
 
0.4%
47450 1
 
0.4%
44051 1
 
0.4%
Other values (149) 149
65.6%
ValueCountFrequency (%)
0 69
30.4%
365 1
 
0.4%
519 1
 
0.4%
730 1
 
0.4%
927 1
 
0.4%
1037 1
 
0.4%
1095 1
 
0.4%
1100 1
 
0.4%
1416 1
 
0.4%
1440 1
 
0.4%
ValueCountFrequency (%)
5508175 1
0.4%
2569750 1
0.4%
1633068 1
0.4%
1191998 1
0.4%
999185 1
0.4%
803608 1
0.4%
593100 1
0.4%
586788 1
0.4%
586213 1
0.4%
550482 1
0.4%

기타-개소수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct137
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163.27753
Minimum0
Maximum4210
Zeros17
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:19.454337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.5
median53
Q3164
95-th percentile554.6
Maximum4210
Range4210
Interquartile range (IQR)154.5

Descriptive statistics

Standard deviation380.60133
Coefficient of variation (CV)2.3310086
Kurtosis59.930103
Mean163.27753
Median Absolute Deviation (MAD)51
Skewness6.6763858
Sum37064
Variance144857.37
MonotonicityNot monotonic
2023-12-13T07:39:19.652351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
 
7.5%
1 12
 
5.3%
4 8
 
3.5%
15 5
 
2.2%
2 5
 
2.2%
3 4
 
1.8%
8 4
 
1.8%
16 3
 
1.3%
25 3
 
1.3%
65 3
 
1.3%
Other values (127) 163
71.8%
ValueCountFrequency (%)
0 17
7.5%
1 12
5.3%
2 5
 
2.2%
3 4
 
1.8%
4 8
3.5%
5 1
 
0.4%
6 3
 
1.3%
7 2
 
0.9%
8 4
 
1.8%
9 1
 
0.4%
ValueCountFrequency (%)
4210 1
0.4%
1805 1
0.4%
1752 1
0.4%
1449 1
0.4%
1402 1
0.4%
1246 1
0.4%
1220 1
0.4%
1097 1
0.4%
908 1
0.4%
630 1
0.4%

기타-이용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct209
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean673738.52
Minimum0
Maximum13980813
Zeros19
Zeros (%)8.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T07:39:19.794008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126638
median212573
Q3664837.5
95-th percentile2877461.6
Maximum13980813
Range13980813
Interquartile range (IQR)638199.5

Descriptive statistics

Standard deviation1385486.1
Coefficient of variation (CV)2.0564151
Kurtosis40.553573
Mean673738.52
Median Absolute Deviation (MAD)209942
Skewness5.291696
Sum1.5293864 × 108
Variance1.9195717 × 1012
MonotonicityNot monotonic
2023-12-13T07:39:19.934558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19
 
8.4%
212573 1
 
0.4%
473341 1
 
0.4%
1717 1
 
0.4%
2825 1
 
0.4%
873650 1
 
0.4%
72714 1
 
0.4%
496978 1
 
0.4%
38789 1
 
0.4%
98126 1
 
0.4%
Other values (199) 199
87.7%
ValueCountFrequency (%)
0 19
8.4%
366 1
 
0.4%
448 1
 
0.4%
570 1
 
0.4%
580 1
 
0.4%
730 1
 
0.4%
800 1
 
0.4%
960 1
 
0.4%
966 1
 
0.4%
1049 1
 
0.4%
ValueCountFrequency (%)
13980813 1
0.4%
7381419 1
0.4%
5590236 1
0.4%
4842061 1
0.4%
4745445 1
0.4%
4710660 1
0.4%
4305457 1
0.4%
3794588 1
0.4%
3505456 1
0.4%
3112217 1
0.4%

Interactions

2023-12-13T07:39:11.478191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:47.815133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:49.258114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:50.636567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:51.945353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:53.666192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:55.393175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:56.650563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:57.994801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:59.916159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:01.445906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:02.968870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:04.716909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:06.513007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:08.022114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:09.540785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:11.605129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:47.899952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:49.344726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:50.722917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:52.027103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:53.780231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:55.490139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:56.744320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:58.096095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:00.001845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:01.552619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:03.057846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:04.841890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:06.619115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-13T07:38:51.794168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:53.490460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:55.165879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:56.506271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:57.827396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:59.724764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:01.263805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:02.778638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:04.220148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:06.320302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:07.834044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:09.374993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:11.299946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:13.188433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:49.152336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:50.552258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:51.859899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:53.565622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:55.273573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:56.573995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:57.905022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:38:59.819151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:01.349659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:02.872072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:04.618089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:06.401401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:07.915942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:09.452913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:39:11.383060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:39:20.072203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도총계-개소수총계-이용량전작용-개소수전작용-이용량답작용-개소수답작용-이용량원예용-개소수원예용-이용량수산업용-개소수수산업용-이용량축산업용-개소수축산업용-이용량양어장용-개소수양어장용-이용량기타-개소수기타-이용량
시도1.0000.4150.7000.5250.7520.5970.3240.2030.1250.0000.2270.5080.4970.2890.1220.0000.056
총계-개소수0.4151.0000.8730.6820.6330.9210.8110.5810.4040.7720.4940.8080.5710.6840.5860.4880.293
총계-이용량0.7000.8731.0000.5660.8210.7020.8800.8050.7960.3720.2160.6500.5340.5650.4680.5820.582
전작용-개소수0.5250.6820.5661.0000.8530.6200.2020.1020.0000.0000.0330.4750.5210.7270.5690.4570.180
전작용-이용량0.7520.6330.8210.8531.0000.3250.1680.0000.0000.0000.0000.3750.2830.3440.3050.4130.126
답작용-개소수0.5970.9210.7020.6200.3251.0000.7920.4280.1100.7830.6460.6150.7660.8080.4860.2580.000
답작용-이용량0.3240.8110.8800.2020.1680.7921.0000.8710.8480.4390.1670.4630.4680.6950.4680.2440.307
원예용-개소수0.2030.5810.8050.1020.0000.4280.8711.0000.9850.3690.0000.5180.3490.4260.3580.3310.496
원예용-이용량0.1250.4040.7960.0000.0000.1100.8480.9851.0000.0000.0000.4780.3330.2550.1390.4400.000
수산업용-개소수0.0000.7720.3720.0000.0000.7830.4390.3690.0001.0000.9090.5100.6080.0000.0000.5130.000
수산업용-이용량0.2270.4940.2160.0330.0000.6460.1670.0000.0000.9091.0000.2920.4870.4520.4870.3940.119
축산업용-개소수0.5080.8080.6500.4750.3750.6150.4630.5180.4780.5100.2921.0000.7760.5110.3740.2550.337
축산업용-이용량0.4970.5710.5340.5210.2830.7660.4680.3490.3330.6080.4870.7761.0000.6990.3460.2770.272
양어장용-개소수0.2890.6840.5650.7270.3440.8080.6950.4260.2550.0000.4520.5110.6991.0000.9260.4920.277
양어장용-이용량0.1220.5860.4680.5690.3050.4860.4680.3580.1390.0000.4870.3740.3460.9261.0000.6070.418
기타-개소수0.0000.4880.5820.4570.4130.2580.2440.3310.4400.5130.3940.2550.2770.4920.6071.0000.907
기타-이용량0.0560.2930.5820.1800.1260.0000.3070.4960.0000.0000.1190.3370.2720.2770.4180.9071.000
2023-12-13T07:39:20.285836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총계-개소수총계-이용량전작용-개소수전작용-이용량답작용-개소수답작용-이용량원예용-개소수원예용-이용량수산업용-개소수수산업용-이용량축산업용-개소수축산업용-이용량양어장용-개소수양어장용-이용량기타-개소수기타-이용량시도
총계-개소수1.0000.9320.8910.8640.9480.8910.8200.7990.5320.5310.8520.8270.7570.7270.7480.7310.181
총계-이용량0.9321.0000.8450.8930.8570.8890.7490.7770.4940.4970.8390.8480.7130.6970.7300.7530.373
전작용-개소수0.8910.8451.0000.9640.7670.6990.6600.6390.4660.4440.7890.7620.6910.6420.6640.6480.206
전작용-이용량0.8640.8930.9641.0000.7360.7210.6340.6460.4660.4490.7800.7770.6680.6280.6500.6570.475
답작용-개소수0.9480.8570.7670.7361.0000.9480.8130.7930.5250.5310.8230.7960.7320.7050.7000.7030.246
답작용-이용량0.8910.8890.6990.7210.9481.0000.7790.8060.4960.5060.8020.7910.6990.6810.6960.7190.157
원예용-개소수0.8200.7490.6600.6340.8130.7791.0000.9640.4570.4650.7380.6950.6370.6290.6900.6610.095
원예용-이용량0.7990.7770.6390.6460.7930.8060.9641.0000.4360.4520.7360.7030.6250.6170.6750.6690.056
수산업용-개소수0.5320.4940.4660.4660.5250.4960.4570.4361.0000.9500.5080.4940.6140.5620.3390.3340.000
수산업용-이용량0.5310.4970.4440.4490.5310.5060.4650.4520.9501.0000.5090.5060.5970.5670.3360.3340.102
축산업용-개소수0.8520.8390.7890.7800.8230.8020.7380.7360.5080.5091.0000.9480.7690.7190.6440.6550.232
축산업용-이용량0.8270.8480.7620.7770.7960.7910.6950.7030.4940.5060.9481.0000.7490.7130.6260.6770.192
양어장용-개소수0.7570.7130.6910.6680.7320.6990.6370.6250.6140.5970.7690.7491.0000.9280.5710.5730.101
양어장용-이용량0.7270.6970.6420.6280.7050.6810.6290.6170.5620.5670.7190.7130.9281.0000.5740.5950.058
기타-개소수0.7480.7300.6640.6500.7000.6960.6900.6750.3390.3360.6440.6260.5710.5741.0000.9150.000
기타-이용량0.7310.7530.6480.6570.7030.7190.6610.6690.3340.3340.6550.6770.5730.5950.9151.0000.020
시도0.1810.3730.2060.4750.2460.1570.0950.0560.0000.1020.2320.1920.1010.0580.0000.0201.000

Missing values

2023-12-13T07:39:13.347862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:39:13.628195image/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

시도시군구총계-개소수총계-이용량전작용-개소수전작용-이용량답작용-개소수답작용-이용량원예용-개소수원예용-이용량수산업용-개소수수산업용-이용량축산업용-개소수축산업용-이용량양어장용-개소수양어장용-이용량기타-개소수기타-이용량
0강원도강릉시254358162621773433664754187545894136774131838139167738286869155212573
1강원도고성군15634448695500772474893326838514252310053733628580895303435
2강원도동해시382547745260401600633922779606002353005096959
3강원도삼척시85946629595162514712296190074022275361194141663751245071576886
4강원도속초시333700732276609856242512216360352345510159051206948290
5강원도양구군31575051664721130113222953530011325105012190365296513266555987661
6강원도양양군11241162725325441396702410709911293001822828814037862136121
7강원도영월군1257202805192215347452091778846759051248462229665121788312343029
8강원도원주시805985023533132492772144212658332322371319613740143328851181151831787207
9강원도인제군379902077248438649381263151719471173003350013141789552881374
시도시군구총계-개소수총계-이용량전작용-개소수전작용-이용량답작용-개소수답작용-이용량원예용-개소수원예용-이용량수산업용-개소수수산업용-이용량축산업용-개소수축산업용-이용량양어장용-개소수양어장용-이용량기타-개소수기타-이용량
217충청북도단양군48212303733527958943934602101284600321552641222745359278
218충청북도보은군55951058882822815488896255233309192754460690012419222271124703561018252
219충청북도영동군5751166836644049961679985924845874043050297001174174664400013181074514
220충청북도옥천군82621310713429166348875331935349661690206126342530016831265719287155146536918
221충청북도음성군88311907677245231001653831674551624292113696426000330121981010609525072084884
222충청북도제천시58242075860544451770020810921801878521819560010126039717225850117588316
223충청북도증평군2105338474549197892213921996435549513127300136239416273002860241
224충청북도진천군4333129787805691367416309596800901705231571560028575505875261929138385530
225충청북도청주시2569626275460414882238571983614554070996168118541340037974634920118244313938355
226충청북도충주시1119025671348524710048063208421288881692247505424968257760755156550817517524745445