Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells5748
Missing cells (%)7.2%
Duplicate rows74
Duplicate rows (%)0.7%
Total size in memory742.2 KiB
Average record size in memory76.0 B

Variable types

Text2
Unsupported1
DateTime1
Numeric4

Dataset

Description공유수면 관리 및 매립에 관한 법률에 의거 점,사용 허가를 받은 공유수면현황을 관리기관, 위치, 목적, 허가일, 점사용유형으로 목록화하여 제공(2022.2) 하는 자료로 자세한 내용은 연안포털(coast.mof.go.kr)을 참조
Author해양수산부
URLhttps://www.data.go.kr/data/15105485/fileData.do

Alerts

Dataset has 74 (0.7%) duplicate rowsDuplicates
채취량 is highly overall correlated with 투기량High correlation
투기량 is highly overall correlated with 채취량High correlation
목적 has 581 (5.8%) missing valuesMissing
채취량 has 262 (2.6%) missing valuesMissing
투기량 has 260 (2.6%) missing valuesMissing
점사용유형 has 4645 (46.5%) missing valuesMissing
채취량 is highly skewed (γ1 = 70.95975365)Skewed
투기량 is highly skewed (γ1 = 78.70382437)Skewed
면적 is highly skewed (γ1 = 46.71310339)Skewed
위치 is an unsupported type, check if it needs cleaning or further analysisUnsupported
채취량 has 9675 (96.8%) zerosZeros
투기량 has 9675 (96.8%) zerosZeros
면적 has 370 (3.7%) zerosZeros

Reproduction

Analysis started2023-12-12 07:10:57.159142
Analysis finished2023-12-12 07:11:00.429873
Duration3.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관
Text

Distinct193
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T16:11:00.641645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.813
Min length4

Characters and Unicode

Total characters78130
Distinct characters129
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.1%

Sample

1st row충청남도 천안시
2nd row경기도 양평군
3rd row강원도 강릉시
4th row부산광역시 북구
5th row경기도 광주시
ValueCountFrequency (%)
경기도 3508
 
17.8%
전라남도 1124
 
5.7%
강원도 1115
 
5.7%
충청남도 1058
 
5.4%
경상남도 735
 
3.7%
남양주시 613
 
3.1%
부산광역시 592
 
3.0%
경상북도 449
 
2.3%
광주시 424
 
2.2%
여주시 391
 
2.0%
Other values (181) 9700
49.2%
2023-12-12T16:11:01.165899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9709
 
12.4%
도 8990
 
11.5%
시 7020
 
9.0%
경 4782
 
6.1%
남 3837
 
4.9%
기 3573
 
4.6%
군 3094
 
4.0%
주 2507
 
3.2%
광 1682
 
2.2%
양 1666
 
2.1%
Other values (119) 31270
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68421
87.6%
Space Separator 9709
 
12.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 8990
 
13.1%
시 7020
 
10.3%
경 4782
 
7.0%
남 3837
 
5.6%
기 3573
 
5.2%
군 3094
 
4.5%
주 2507
 
3.7%
광 1682
 
2.5%
양 1666
 
2.4%
산 1566
 
2.3%
Other values (118) 29704
43.4%
Space Separator
ValueCountFrequency (%)
9709
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68421
87.6%
Common 9709
 
12.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 8990
 
13.1%
시 7020
 
10.3%
경 4782
 
7.0%
남 3837
 
5.6%
기 3573
 
5.2%
군 3094
 
4.5%
주 2507
 
3.7%
광 1682
 
2.5%
양 1666
 
2.4%
산 1566
 
2.3%
Other values (118) 29704
43.4%
Common
ValueCountFrequency (%)
9709
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68421
87.6%
ASCII 9709
 
12.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9709
100.0%
Hangul
ValueCountFrequency (%)
도 8990
 
13.1%
시 7020
 
10.3%
경 4782
 
7.0%
남 3837
 
5.6%
기 3573
 
5.2%
군 3094
 
4.5%
주 2507
 
3.7%
광 1682
 
2.5%
양 1666
 
2.4%
산 1566
 
2.3%
Other values (118) 29704
43.4%

위치
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

목적
Text

MISSING 

Distinct4993
Distinct (%)53.0%
Missing581
Missing (%)5.8%
Memory size156.2 KiB
2023-12-12T16:11:01.501441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length124
Median length64
Mean length9.9344941
Min length1

Characters and Unicode

Total characters93573
Distinct characters688
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4316 ?
Unique (%)45.8%

Sample

1st row주택 진출입로
2nd row버섯재배사 진출입 도로
3rd row농경지
4th row대지(비주거)
5th row대지 및 경작
ValueCountFrequency (%)
진출입로 1152
 
5.4%
및 1035
 
4.8%
설치 964
 
4.5%
대지 451
 
2.1%
위한 423
 
2.0%
경작 339
 
1.6%
주택 293
 
1.4%
진입로 278
 
1.3%
매설 267
 
1.2%
운영 193
 
0.9%
Other values (6158) 16066
74.9%
2023-12-12T16:11:02.075026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12078
 
12.9%
설 3081
 
3.3%
로 2737
 
2.9%
지 2712
 
2.9%
수 2666
 
2.8%
입 2287
 
2.4%
진 2219
 
2.4%
장 2064
 
2.2%
출 1667
 
1.8%
치 1536
 
1.6%
Other values (678) 60526
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75831
81.0%
Space Separator 12078
 
12.9%
Decimal Number 1484
 
1.6%
Open Punctuation 1345
 
1.4%
Close Punctuation 1340
 
1.4%
Other Punctuation 825
 
0.9%
Uppercase Letter 313
 
0.3%
Dash Punctuation 131
 
0.1%
Lowercase Letter 101
 
0.1%
Math Symbol 70
 
0.1%
Other values (5) 55
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 3081
 
4.1%
로 2737
 
3.6%
지 2712
 
3.6%
수 2666
 
3.5%
입 2287
 
3.0%
진 2219
 
2.9%
장 2064
 
2.7%
출 1667
 
2.2%
치 1536
 
2.0%
시 1341
 
1.8%
Other values (593) 53521
70.6%
Uppercase Letter
ValueCountFrequency (%)
T 51
16.3%
P 32
 
10.2%
C 32
 
10.2%
L 23
 
7.3%
V 23
 
7.3%
B 16
 
5.1%
M 14
 
4.5%
O 14
 
4.5%
D 13
 
4.2%
X 12
 
3.8%
Other values (13) 83
26.5%
Lowercase Letter
ValueCountFrequency (%)
m 56
55.4%
k 7
 
6.9%
c 6
 
5.9%
p 4
 
4.0%
l 3
 
3.0%
o 3
 
3.0%
e 3
 
3.0%
a 3
 
3.0%
t 3
 
3.0%
v 2
 
2.0%
Other values (8) 11
 
10.9%
Other Punctuation
ValueCountFrequency (%)
, 449
54.4%
. 243
29.5%
: 48
 
5.8%
· 48
 
5.8%
/ 15
 
1.8%
* 8
 
1.0%
" 6
 
0.7%
? 4
 
0.5%
？ 2
 
0.2%
， 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 295
19.9%
2 289
19.5%
0 249
16.8%
3 145
9.8%
4 107
 
7.2%
5 102
 
6.9%
7 89
 
6.0%
6 86
 
5.8%
8 69
 
4.6%
9 53
 
3.6%
Math Symbol
ValueCountFrequency (%)
= 34
48.6%
~ 26
37.1%
> 4
 
5.7%
+ 2
 
2.9%
× 1
 
1.4%
∮ 1
 
1.4%
∼ 1
 
1.4%
→ 1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 1337
99.4%
[ 7
 
0.5%
「 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1333
99.5%
] 6
 
0.4%
」 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
㎡ 45
90.0%
○ 4
 
8.0%
㎥ 1
 
2.0%
Space Separator
ValueCountFrequency (%)
12078
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 131
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75830
81.0%
Common 17327
 
18.5%
Latin 415
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 3081
 
4.1%
로 2737
 
3.6%
지 2712
 
3.6%
수 2666
 
3.5%
입 2287
 
3.0%
진 2219
 
2.9%
장 2064
 
2.7%
출 1667
 
2.2%
치 1536
 
2.0%
시 1341
 
1.8%
Other values (592) 53520
70.6%
Common
ValueCountFrequency (%)
12078
69.7%
( 1337
 
7.7%
) 1333
 
7.7%
, 449
 
2.6%
1 295
 
1.7%
2 289
 
1.7%
0 249
 
1.4%
. 243
 
1.4%
3 145
 
0.8%
- 131
 
0.8%
Other values (33) 778
 
4.5%
Latin
ValueCountFrequency (%)
m 56
 
13.5%
T 51
 
12.3%
P 32
 
7.7%
C 32
 
7.7%
L 23
 
5.5%
V 23
 
5.5%
B 16
 
3.9%
M 14
 
3.4%
O 14
 
3.4%
D 13
 
3.1%
Other values (32) 141
34.0%
Han
ValueCountFrequency (%)
昊 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75817
81.0%
ASCII 17629
 
18.8%
None 59
 
0.1%
CJK Compat 46
 
< 0.1%
Compat Jamo 13
 
< 0.1%
Geometric Shapes 4
 
< 0.1%
Math Operators 2
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12078
68.5%
( 1337
 
7.6%
) 1333
 
7.6%
, 449
 
2.5%
1 295
 
1.7%
2 289
 
1.6%
0 249
 
1.4%
. 243
 
1.4%
3 145
 
0.8%
- 131
 
0.7%
Other values (60) 1080
 
6.1%
Hangul
ValueCountFrequency (%)
설 3081
 
4.1%
로 2737
 
3.6%
지 2712
 
3.6%
수 2666
 
3.5%
입 2287
 
3.0%
진 2219
 
2.9%
장 2064
 
2.7%
출 1667
 
2.2%
치 1536
 
2.0%
시 1341
 
1.8%
Other values (589) 53507
70.6%
None
ValueCountFrequency (%)
· 48
81.4%
Ø 3
 
5.1%
？ 2
 
3.4%
² 2
 
3.4%
， 1
 
1.7%
× 1
 
1.7%
」 1
 
1.7%
「 1
 
1.7%
CJK Compat
ValueCountFrequency (%)
㎡ 45
97.8%
㎥ 1
 
2.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
84.6%
ㅏ 1
 
7.7%
ㅣ 1
 
7.7%
Geometric Shapes
ValueCountFrequency (%)
○ 4
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%
CJK
ValueCountFrequency (%)
昊 1
100.0%
Math Operators
ValueCountFrequency (%)
∮ 1
50.0%
∼ 1
50.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

최초허가일
Date

Distinct4237
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1961-02-28 00:00:00
Maximum2022-03-14 00:00:00
2023-12-12T16:11:02.253437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:11:02.435699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

채취량
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct54
Distinct (%)0.6%
Missing262
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean1407.3296
Minimum0
Maximum6000000
Zeros9675
Zeros (%)96.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T16:11:02.613996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6000000
Range6000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation72472.871
Coefficient of variation (CV)51.496728
Kurtosis5405.2455
Mean1407.3296
Median Absolute Deviation (MAD)0
Skewness70.959754
Sum13704576
Variance5.252317 × 109
MonotonicityNot monotonic
2023-12-12T16:11:02.765783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9675
96.8%
150000.0 6
 
0.1%
200.0 2
 
< 0.1%
30000.0 2
 
< 0.1%
100000.0 2
 
< 0.1%
96.0 2
 
< 0.1%
1.0 2
 
< 0.1%
36408.0 1
 
< 0.1%
2.0 1
 
< 0.1%
2694.0 1
 
< 0.1%
Other values (44) 44
 
0.4%
(Missing) 262
 
2.6%
ValueCountFrequency (%)
0.0 9675
96.8%
0.32 1
 
< 0.1%
0.522 1
 
< 0.1%
1.0 2
 
< 0.1%
2.0 1
 
< 0.1%
8.0 1
 
< 0.1%
10.0 1
 
< 0.1%
24.0 1
 
< 0.1%
26.044 1
 
< 0.1%
68.0 1
 
< 0.1%
ValueCountFrequency (%)
6000000.0 1
 
< 0.1%
3504000.0 1
 
< 0.1%
1600000.0 1
 
< 0.1%
212000.0 1
 
< 0.1%
200000.0 1
 
< 0.1%
157943.0 1
 
< 0.1%
150000.0 6
0.1%
130000.0 1
 
< 0.1%
100000.0 2
 
< 0.1%
92495.0 1
 
< 0.1%

투기량
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct56
Distinct (%)0.6%
Missing260
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean816.33335
Minimum0
Maximum3504000
Zeros9675
Zeros (%)96.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T16:11:02.931346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3504000
Range3504000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation39472.662
Coefficient of variation (CV)48.353607
Kurtosis6648.2374
Mean816.33335
Median Absolute Deviation (MAD)0
Skewness78.703824
Sum7951086.8
Variance1.5580911 × 109
MonotonicityNot monotonic
2023-12-12T16:11:03.126754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9675
96.8%
150000.0 6
 
0.1%
30000.0 2
 
< 0.1%
96.0 2
 
< 0.1%
200.0 2
 
< 0.1%
1.0 2
 
< 0.1%
100000.0 2
 
< 0.1%
71004.0 1
 
< 0.1%
0.32 1
 
< 0.1%
30643.0 1
 
< 0.1%
Other values (46) 46
 
0.5%
(Missing) 260
 
2.6%
ValueCountFrequency (%)
0.0 9675
96.8%
0.32 1
 
< 0.1%
0.522 1
 
< 0.1%
1.0 2
 
< 0.1%
2.0 1
 
< 0.1%
8.0 1
 
< 0.1%
10.0 1
 
< 0.1%
68.0 1
 
< 0.1%
96.0 2
 
< 0.1%
101.0 1
 
< 0.1%
ValueCountFrequency (%)
3504000.0 1
 
< 0.1%
1600000.0 1
 
< 0.1%
212000.0 1
 
< 0.1%
200000.0 1
 
< 0.1%
157943.0 1
 
< 0.1%
150000.0 6
0.1%
130000.0 1
 
< 0.1%
112340.0 1
 
< 0.1%
100000.0 2
 
< 0.1%
92495.0 1
 
< 0.1%

면적
Real number (ℝ)

SKEWED  ZEROS 

Distinct2610
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3613.7223
Minimum0
Maximum4436000
Zeros370
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T16:11:03.295329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q131
median125
Q3470
95-th percentile3574.35
Maximum4436000
Range4436000
Interquartile range (IQR)439

Descriptive statistics

Standard deviation66598.691
Coefficient of variation (CV)18.429388
Kurtosis2639.8048
Mean3613.7223
Median Absolute Deviation (MAD)116
Skewness46.713103
Sum36137223
Variance4.4353856 × 109
MonotonicityNot monotonic
2023-12-12T16:11:03.435318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 370
 
3.7%
1.0 131
 
1.3%
100.0 104
 
1.0%
30.0 95
 
0.9%
50.0 90
 
0.9%
4.0 78
 
0.8%
40.0 75
 
0.8%
10.0 74
 
0.7%
200.0 74
 
0.7%
20.0 73
 
0.7%
Other values (2600) 8836
88.4%
ValueCountFrequency (%)
0.0 370
3.7%
0.02 1
 
< 0.1%
0.04 5
 
0.1%
0.05 1
 
< 0.1%
0.06 5
 
0.1%
0.09 1
 
< 0.1%
0.1 4
 
< 0.1%
0.12 7
 
0.1%
0.13 3
 
< 0.1%
0.14 4
 
< 0.1%
ValueCountFrequency (%)
4436000.0 1
 
< 0.1%
3140000.0 1
 
< 0.1%
2355000.0 1
 
< 0.1%
1200000.0 1
 
< 0.1%
1097000.0 1
 
< 0.1%
834000.0 1
 
< 0.1%
785398.0 1
 
< 0.1%
785000.0 3
< 0.1%
697161.0 1
 
< 0.1%
668982.0 1
 
< 0.1%

점사용유형
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)0.2%
Missing4645
Missing (%)46.5%
Infinite0
Infinite (%)0.0%
Mean6.0113912
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T16:11:03.560100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median6
Q311
95-th percentile11
Maximum11
Range10
Interquartile range (IQR)10

Descriptive statistics

Standard deviation4.5654724
Coefficient of variation (CV)0.75947019
Kurtosis-1.8343041
Mean6.0113912
Median Absolute Deviation (MAD)5
Skewness-0.021081234
Sum32191
Variance20.843539
MonotonicityNot monotonic
2023-12-12T16:11:03.682088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 2189
21.9%
11 2069
20.7%
5 338
 
3.4%
9 233
 
2.3%
7 221
 
2.2%
10 74
 
0.7%
8 65
 
0.7%
3 51
 
0.5%
4 47
 
0.5%
6 43
 
0.4%
(Missing) 4645
46.5%
ValueCountFrequency (%)
1 2189
21.9%
2 25
 
0.2%
3 51
 
0.5%
4 47
 
0.5%
5 338
 
3.4%
6 43
 
0.4%
7 221
 
2.2%
8 65
 
0.7%
9 233
 
2.3%
10 74
 
0.7%
ValueCountFrequency (%)
11 2069
20.7%
10 74
 
0.7%
9 233
 
2.3%
8 65
 
0.7%
7 221
 
2.2%
6 43
 
0.4%
5 338
 
3.4%
4 47
 
0.5%
3 51
 
0.5%
2 25
 
0.2%

Interactions

2023-12-12T16:10:59.680508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:58.299103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:58.761551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.263015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.762320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:58.403879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:58.881302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.364163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.866258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:58.540864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.018692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.471903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.956617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:58.647096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.140416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:10:59.574613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:11:03.783274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채취량투기량면적점사용유형
채취량1.0001.0000.9250.168
투기량1.0001.0000.7180.044
면적0.9250.7181.0000.186
점사용유형0.1680.0440.1861.000
2023-12-12T16:11:03.905484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채취량투기량면적점사용유형
채취량1.0001.0000.056-0.013
투기량1.0001.0000.062-0.014
면적0.0560.0621.000-0.008
점사용유형-0.013-0.014-0.0081.000

Missing values

2023-12-12T16:11:00.101984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:11:00.233971image/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.
2023-12-12T16:11:00.345904image/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

관리기관위치목적최초허가일채취량투기량면적점사용유형
22183충청남도 천안시충청남도 천안시 동남구 목천읍 도장리 358번지주택 진출입로2018-04-230.00.010.01
64301경기도 양평군경기도 양평군 개군면 구미리 120번지버섯재배사 진출입 도로2004-09-160.00.0342.0<NA>
57676강원도 강릉시강원도 강릉시 사천면 노동리 1107번지 4 호 (646-1번지선)농경지2006-06-280.00.0109.0<NA>
50774부산광역시 북구부산광역시 북구 구포동 1141번지 112 호대지(비주거)2000-12-290.00.078.0<NA>
24008경기도 광주시경기도 광주시 송정동 516번지 10호대지 및 경작2018-01-010.00.097.011
67284경기도 여주시경기도 여주시 금사면 금사리 631번지 3호대지2013-02-070.00.0417.011
6024제주특별자치도 제주시제주특별자치도 제주시 한림읍 금능리 2028번지수상레저 계류장2016-06-280.00.026.011
28422경상북도 포항시경상북도 포항시 북구 송라면 지경리 403-2 송라파출소야영장 운영2021-07-080.00.03000.011
49373경기도 안성시경기도 안성시 원곡면 외가천리 336번지대지(공작물) 인근번지: 외가천리 4번지2012-11-200.00.0754.0<NA>
47134부산광역시 동래구부산광역시 동래구 사직동 1002번지 22호<NA>2012-09-140.00.00.0<NA>
관리기관위치목적최초허가일채취량투기량면적점사용유형
61528경기도 남양주시경기도 남양주시 와부읍 덕소리 503번지 13 호대지2008-09-100.00.046.0<NA>
46353경기도 남양주시경기도 남양주시 화도읍 차산리 391번지 7호 외2필지(391-8,391-10)농경지 활용2015-06-240.00.01252.0<NA>
33016강원도 원주시강원도 원주시 신림면 황둔리 1933<NA>2021-12-280.00.040.011
47398경기도 평택시경기도 평택시 지산동 924번지배수시설(흄관) 매설2016-04-150.00.05.0<NA>
34286경상북도 김천시경상북도 김천시 대항면 대룡리 893-9전주 설치2021-09-130.00.01.791
16100부산광역시 동래구부산광역시 동래구 명장2동 585번지 32호주택대지2006-01-010.00.011.010
69357경기도 여주시경기도 여주시 산북면 하품리 765번지 (하품리620,625번지선)주택부지 진,출입로 및 마당부지조성2008-10-150.00.0184.0<NA>
36867경상남도 고성군경상남도 고성군 삼산면 장치리 617번지 1호 지선수산물운반 콤베어 및 선박접안 부잔교시설2000-03-060.00.049.56<NA>
34322서울특별시 강서구서울특별시 강서구 화곡본동 748번지 21호주거2011-11-300.00.022.011
51239경상북도 안동시안동시 신안동 305(34-1번지선)대지2002-11-020.00.096.0<NA>

Duplicate rows

Most frequently occurring

관리기관목적최초허가일채취량투기량면적점사용유형# duplicates
6강원도 횡성군<NA>2013-09-100.00.00.0<NA>7
53울산광역시 울주군<NA>2010-07-020.00.0130.0117
68충청남도 보령시이동차양막 등 설치2018-06-160.00.0180.0117
31광주광역시 동구<NA>2014-12-260.00.00.0<NA>6
23경상북도 안동시대지2002-11-020.00.012.0<NA>5
67충청남도 보령시대천해수욕장 계절영업2019-06-100.00.0200.0115
2강원도 강릉시해변운영2017-06-200.00.00.0113
5강원도 횡성군<NA>2013-08-070.00.00.0<NA>3
18경상남도 창원시해양쓰레기 선상집하장 설치2020-03-130.00.0684.0113
19경상남도 창원시<NA>2008-10-200.00.00.0<NA>3