Overview

Dataset statistics

Number of variables38
Number of observations10000
Missing cells24129
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 MiB
Average record size in memory321.0 B

Variable types

Numeric2
Categorical19
Text15
Unsupported2

Dataset

Description충청남도 외래생물 분포현황 현장조사 정보입니다. 서식지유형,상세주소,위도,경도,밀도등의 컬럼 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2604

Alerts

조사자명 is highly imbalanced (68.7%)Imbalance
동반외래종명 is highly imbalanced (71.3%)Imbalance
분포 is highly imbalanced (53.5%)Imbalance
시군 is highly imbalanced (53.6%)Imbalance
문화재거리 is highly imbalanced (53.3%)Imbalance
분포유형 is highly imbalanced (51.9%)Imbalance
등급 is highly imbalanced (81.9%)Imbalance
긴급 is highly imbalanced (94.2%)Imbalance
보전 is highly imbalanced (98.5%)Imbalance
경제 is highly imbalanced (99.7%)Imbalance
GPS좌표 has 240 (2.4%) missing valuesMissing
위도 has 340 (3.4%) missing valuesMissing
경도 has 471 (4.7%) missing valuesMissing
토지면적 has 392 (3.9%) missing valuesMissing
개별수 has 2443 (24.4%) missing valuesMissing
밀도 has 176 (1.8%) missing valuesMissing
목표 has 10000 (100.0%) missing valuesMissing
관리연도 has 10000 (100.0%) missing valuesMissing
번호 has unique valuesUnique
목표 is an unsupported type, check if it needs cleaning or further analysisUnsupported
관리연도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공원거리 has 663 (6.6%) zerosZeros

Reproduction

Analysis started2024-01-09 23:07:10.609074
Analysis finished2024-01-09 23:07:13.163847
Duration2.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7236.5334
Minimum1
Maximum14495
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T08:07:13.224524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile754.85
Q13609.75
median7222.5
Q310839.5
95-th percentile13777.05
Maximum14495
Range14494
Interquartile range (IQR)7229.75

Descriptive statistics

Standard deviation4177.7922
Coefficient of variation (CV)0.57731955
Kurtosis-1.1944891
Mean7236.5334
Median Absolute Deviation (MAD)3614
Skewness0.0089733754
Sum72365334
Variance17453948
MonotonicityNot monotonic
2024-01-10T08:07:13.344016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1116 1
 
< 0.1%
5991 1
 
< 0.1%
8464 1
 
< 0.1%
3646 1
 
< 0.1%
8147 1
 
< 0.1%
14036 1
 
< 0.1%
9813 1
 
< 0.1%
13017 1
 
< 0.1%
11840 1
 
< 0.1%
81 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
14495 1
< 0.1%
14493 1
< 0.1%
14492 1
< 0.1%
14491 1
< 0.1%
14488 1
< 0.1%
14486 1
< 0.1%
14484 1
< 0.1%
14483 1
< 0.1%
14479 1
< 0.1%
14478 1
< 0.1%

행정동명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
서산시
893 
공주시
885 
당진시
859 
천안시
822 
부여군
805 
Other values (10)
5736 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row천안시
2nd row서산시
3rd row서산시
4th row서산시
5th row천안시

Common Values

ValueCountFrequency (%)
서산시 893
8.9%
공주시 885
8.8%
당진시 859
8.6%
천안시 822
 
8.2%
부여군 805
 
8.1%
논산시 751
 
7.5%
태안군 728
 
7.3%
금산군 727
 
7.3%
아산시 717
 
7.2%
예산군 705
 
7.0%
Other values (5) 2108
21.1%

Length

2024-01-10T08:07:13.458540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서산시 893
8.9%
공주시 885
8.8%
당진시 859
8.6%
천안시 822
 
8.2%
부여군 805
 
8.1%
논산시 751
 
7.5%
태안군 728
 
7.3%
금산군 727
 
7.3%
아산시 717
 
7.2%
예산군 705
 
7.0%
Other values (5) 2108
21.1%

시군구명
Text

Distinct227
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:07:13.742135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9932
Min length2

Characters and Unicode

Total characters29932
Distinct characters152
Distinct categories2 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.1%

Sample

1st row동남구
2nd row부석면
3rd row지곡면
4th row잠홍동
5th row서북구
ValueCountFrequency (%)
동남구 558
 
5.6%
서북구 264
 
2.6%
안면읍 134
 
1.3%
부석면 133
 
1.3%
대산읍 131
 
1.3%
원북면 113
 
1.1%
석문면 111
 
1.1%
태안읍 111
 
1.1%
계룡면 109
 
1.1%
송악읍 107
 
1.1%
Other values (217) 8229
82.3%
2024-01-10T08:07:14.157887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 7638
25.5%
읍 1344
 
4.5%
산 1269
 
4.2%
동 1052
 
3.5%
남 1033
 
3.5%
구 1001
 
3.3%
북 684
 
2.3%
성 527
 
1.8%
서 501
 
1.7%
대 485
 
1.6%
Other values (142) 14398
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29931
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 7638
25.5%
읍 1344
 
4.5%
산 1269
 
4.2%
동 1052
 
3.5%
남 1033
 
3.5%
구 1001
 
3.3%
북 684
 
2.3%
성 527
 
1.8%
서 501
 
1.7%
대 485
 
1.6%
Other values (141) 14397
48.1%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29929
> 99.9%
Han 2
 
< 0.1%
Common 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 7638
25.5%
읍 1344
 
4.5%
산 1269
 
4.2%
동 1052
 
3.5%
남 1033
 
3.5%
구 1001
 
3.3%
북 684
 
2.3%
성 527
 
1.8%
서 501
 
1.7%
대 485
 
1.6%
Other values (139) 14395
48.1%
Han
ValueCountFrequency (%)
謨 1
50.0%
截 1
50.0%
Common
ValueCountFrequency (%)
? 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29929
> 99.9%
CJK 2
 
< 0.1%
ASCII 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 7638
25.5%
읍 1344
 
4.5%
산 1269
 
4.2%
동 1052
 
3.5%
남 1033
 
3.5%
구 1001
 
3.3%
북 684
 
2.3%
성 527
 
1.8%
서 501
 
1.7%
대 485
 
1.6%
Other values (139) 14395
48.1%
CJK
ValueCountFrequency (%)
謨 1
50.0%
截 1
50.0%
ASCII
ValueCountFrequency (%)
? 1
100.0%

법정읍면동명
Text

Distinct1403
Distinct (%)14.1%
Missing44
Missing (%)0.4%
Memory size156.2 KiB
2024-01-10T08:07:14.467903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0053234
Min length1

Characters and Unicode

Total characters29921
Distinct characters289
Distinct categories4 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)1.4%

Sample

1st row수신면
2nd row강당리
3rd row대요리
4th rowA368
5th row성거읍
ValueCountFrequency (%)
광덕면 96
 
1.0%
병천면 84
 
0.8%
성환읍 65
 
0.7%
입장면 64
 
0.6%
북면 62
 
0.6%
풍세면 58
 
0.6%
동면 51
 
0.5%
목천읍 51
 
0.5%
중장리 51
 
0.5%
신정리 51
 
0.5%
Other values (1393) 9323
93.6%
2024-01-10T08:07:14.887740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 8792
29.4%
산 966
 
3.2%
신 697
 
2.3%
동 549
 
1.8%
곡 533
 
1.8%
성 516
 
1.7%
면 494
 
1.7%
대 477
 
1.6%
천 461
 
1.5%
장 432
 
1.4%
Other values (279) 16004
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28709
95.9%
Decimal Number 906
 
3.0%
Uppercase Letter 302
 
1.0%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 8792
30.6%
산 966
 
3.4%
신 697
 
2.4%
동 549
 
1.9%
곡 533
 
1.9%
성 516
 
1.8%
면 494
 
1.7%
대 477
 
1.7%
천 461
 
1.6%
장 432
 
1.5%
Other values (262) 14792
51.5%
Decimal Number
ValueCountFrequency (%)
2 201
22.2%
1 147
16.2%
0 105
11.6%
3 99
10.9%
4 91
10.0%
7 71
 
7.8%
6 59
 
6.5%
9 53
 
5.8%
5 47
 
5.2%
8 33
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 110
36.4%
D 66
21.9%
B 58
19.2%
F 37
 
12.3%
E 22
 
7.3%
C 9
 
3.0%
Other Punctuation
ValueCountFrequency (%)
? 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28707
95.9%
Common 910
 
3.0%
Latin 302
 
1.0%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 8792
30.6%
산 966
 
3.4%
신 697
 
2.4%
동 549
 
1.9%
곡 533
 
1.9%
성 516
 
1.8%
면 494
 
1.7%
대 477
 
1.7%
천 461
 
1.6%
장 432
 
1.5%
Other values (260) 14790
51.5%
Common
ValueCountFrequency (%)
2 201
22.1%
1 147
16.2%
0 105
11.5%
3 99
10.9%
4 91
10.0%
7 71
 
7.8%
6 59
 
6.5%
9 53
 
5.8%
5 47
 
5.2%
8 33
 
3.6%
Latin
ValueCountFrequency (%)
A 110
36.4%
D 66
21.9%
B 58
19.2%
F 37
 
12.3%
E 22
 
7.3%
C 9
 
3.0%
Han
ValueCountFrequency (%)
致 1
50.0%
膨 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28707
95.9%
ASCII 1212
 
4.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 8792
30.6%
산 966
 
3.4%
신 697
 
2.4%
동 549
 
1.9%
곡 533
 
1.9%
성 516
 
1.8%
면 494
 
1.7%
대 477
 
1.7%
천 461
 
1.6%
장 432
 
1.5%
Other values (260) 14790
51.5%
ASCII
ValueCountFrequency (%)
2 201
16.6%
1 147
12.1%
A 110
9.1%
0 105
8.7%
3 99
8.2%
4 91
7.5%
7 71
 
5.9%
D 66
 
5.4%
6 59
 
4.9%
B 58
 
4.8%
Other values (7) 205
16.9%
CJK
ValueCountFrequency (%)
致 1
50.0%
膨 1
50.0%

법정리명
Text

Distinct2413
Distinct (%)24.1%
Missing8
Missing (%)0.1%
Memory size156.2 KiB
2024-01-10T08:07:15.234787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.4538631
Min length2

Characters and Unicode

Total characters44503
Distinct characters121
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique247 ?
Unique (%)2.5%

Sample

1st row발산리
2nd rowC006
3rd rowA173
4th row2020-10-17
5th row석교리
ValueCountFrequency (%)
2019년 240
 
2.4%
2020-10-17 70
 
0.7%
2021-06-02 37
 
0.4%
2020-11-01 31
 
0.3%
2020-10-15 28
 
0.3%
2020-09-25 28
 
0.3%
2021-04-17 26
 
0.3%
광덕리 26
 
0.3%
2020-08-25 24
 
0.2%
대평리 23
 
0.2%
Other values (2403) 9459
94.7%
2024-01-10T08:07:15.712335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5893
13.2%
2 5652
12.7%
1 5170
11.6%
3 3062
 
6.9%
4 2628
 
5.9%
5 2165
 
4.9%
A 2159
 
4.9%
F 2081
 
4.7%
9 1891
 
4.2%
6 1888
 
4.2%
Other values (111) 11914
26.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31881
71.6%
Uppercase Letter 8305
 
18.7%
Other Letter 2335
 
5.2%
Dash Punctuation 1502
 
3.4%
Open Punctuation 240
 
0.5%
Close Punctuation 240
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 696
29.8%
년 240
 
10.3%
덕 90
 
3.9%
정 59
 
2.5%
원 49
 
2.1%
송 45
 
1.9%
산 44
 
1.9%
성 44
 
1.9%
용 43
 
1.8%
신 41
 
1.8%
Other values (92) 984
42.1%
Decimal Number
ValueCountFrequency (%)
0 5893
18.5%
2 5652
17.7%
1 5170
16.2%
3 3062
9.6%
4 2628
8.2%
5 2165
 
6.8%
9 1891
 
5.9%
6 1888
 
5.9%
7 1770
 
5.6%
8 1762
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 2159
26.0%
F 2081
25.1%
C 1432
17.2%
D 970
11.7%
E 863
 
10.4%
B 800
 
9.6%
Dash Punctuation
ValueCountFrequency (%)
- 1502
100.0%
Open Punctuation
ValueCountFrequency (%)
( 240
100.0%
Close Punctuation
ValueCountFrequency (%)
) 240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33863
76.1%
Latin 8305
 
18.7%
Hangul 2335
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 696
29.8%
년 240
 
10.3%
덕 90
 
3.9%
정 59
 
2.5%
원 49
 
2.1%
송 45
 
1.9%
산 44
 
1.9%
성 44
 
1.9%
용 43
 
1.8%
신 41
 
1.8%
Other values (92) 984
42.1%
Common
ValueCountFrequency (%)
0 5893
17.4%
2 5652
16.7%
1 5170
15.3%
3 3062
9.0%
4 2628
7.8%
5 2165
 
6.4%
9 1891
 
5.6%
6 1888
 
5.6%
7 1770
 
5.2%
8 1762
 
5.2%
Other values (3) 1982
 
5.9%
Latin
ValueCountFrequency (%)
A 2159
26.0%
F 2081
25.1%
C 1432
17.2%
D 970
11.7%
E 863
 
10.4%
B 800
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42168
94.8%
Hangul 2335
 
5.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5893
14.0%
2 5652
13.4%
1 5170
12.3%
3 3062
 
7.3%
4 2628
 
6.2%
5 2165
 
5.1%
A 2159
 
5.1%
F 2081
 
4.9%
9 1891
 
4.5%
6 1888
 
4.5%
Other values (9) 9579
22.7%
Hangul
ValueCountFrequency (%)
리 696
29.8%
년 240
 
10.3%
덕 90
 
3.9%
정 59
 
2.5%
원 49
 
2.1%
송 45
 
1.9%
산 44
 
1.9%
성 44
 
1.9%
용 43
 
1.8%
신 41
 
1.8%
Other values (92) 984
42.1%

좌표명
Text

Distinct260
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:07:16.080544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.2658
Min length3

Characters and Unicode

Total characters92658
Distinct characters69
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)0.2%

Sample

1st rowB311
2nd row2020-10-25
3rd row2020-10-16
4th row나혜련
5th rowB100
ValueCountFrequency (%)
2020-11-15 478
 
4.4%
2020-11-14 431
 
4.0%
2020-11-07 381
 
3.5%
2020-11-08 353
 
3.3%
2021-06-27 350
 
3.2%
최승호 338
 
3.1%
김민수 338
 
3.1%
2021-07-02 335
 
3.1%
2020-10-16 321
 
3.0%
2020-10-31 302
 
2.8%
Other values (254) 7162
66.4%
2024-01-10T08:07:16.577382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22746
24.5%
2 19895
21.5%
- 16670
18.0%
1 14547
15.7%
7 3264
 
3.5%
6 2451
 
2.6%
3 1757
 
1.9%
5 1605
 
1.7%
4 1392
 
1.5%
789
 
0.9%
Other values (59) 7542
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68702
74.1%
Dash Punctuation 16670
 
18.0%
Other Letter 5343
 
5.8%
Space Separator 789
 
0.9%
Uppercase Letter 674
 
0.7%
Close Punctuation 240
 
0.3%
Open Punctuation 240
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
최 558
 
10.4%
김 437
 
8.2%
호 347
 
6.5%
정 346
 
6.5%
수 340
 
6.4%
승 338
 
6.3%
민 338
 
6.3%
장 319
 
6.0%
옥 245
 
4.6%
하 240
 
4.5%
Other values (43) 1835
34.3%
Decimal Number
ValueCountFrequency (%)
0 22746
33.1%
2 19895
29.0%
1 14547
21.2%
7 3264
 
4.8%
6 2451
 
3.6%
3 1757
 
2.6%
5 1605
 
2.3%
4 1392
 
2.0%
8 648
 
0.9%
9 397
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
B 653
96.9%
D 21
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 16670
100.0%
Space Separator
ValueCountFrequency (%)
789
100.0%
Close Punctuation
ValueCountFrequency (%)
) 240
100.0%
Open Punctuation
ValueCountFrequency (%)
( 240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86641
93.5%
Hangul 5343
 
5.8%
Latin 674
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
최 558
 
10.4%
김 437
 
8.2%
호 347
 
6.5%
정 346
 
6.5%
수 340
 
6.4%
승 338
 
6.3%
민 338
 
6.3%
장 319
 
6.0%
옥 245
 
4.6%
하 240
 
4.5%
Other values (43) 1835
34.3%
Common
ValueCountFrequency (%)
0 22746
26.3%
2 19895
23.0%
- 16670
19.2%
1 14547
16.8%
7 3264
 
3.8%
6 2451
 
2.8%
3 1757
 
2.0%
5 1605
 
1.9%
4 1392
 
1.6%
789
 
0.9%
Other values (4) 1525
 
1.8%
Latin
ValueCountFrequency (%)
B 653
96.9%
D 21
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87315
94.2%
Hangul 5343
 
5.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22746
26.1%
2 19895
22.8%
- 16670
19.1%
1 14547
16.7%
7 3264
 
3.7%
6 2451
 
2.8%
3 1757
 
2.0%
5 1605
 
1.8%
4 1392
 
1.6%
789
 
0.9%
Other values (6) 2199
 
2.5%
Hangul
ValueCountFrequency (%)
최 558
 
10.4%
김 437
 
8.2%
호 347
 
6.5%
정 346
 
6.5%
수 340
 
6.4%
승 338
 
6.3%
민 338
 
6.3%
장 319
 
6.0%
옥 245
 
4.6%
하 240
 
4.5%
Other values (43) 1835
34.3%

조사일자(YYYY-MM-DD)
Text

Distinct103
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:07:16.812413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.7442
Min length3

Characters and Unicode

Total characters57442
Distinct characters96
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row2020-10-10
2nd row장한이 안진성
3rd row장한이 김지선
4th row1_식물
5th row2020-10-08
ValueCountFrequency (%)
권희정 1334
 
8.9%
최미숙 1120
 
7.5%
신규형 825
 
5.5%
홍숙윤 812
 
5.4%
강경숙 692
 
4.6%
장한이 638
 
4.3%
김호담 598
 
4.0%
최인재 467
 
3.1%
김세령 464
 
3.1%
유진수 449
 
3.0%
Other values (65) 7581
50.6%
2024-01-10T08:07:17.163011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4981
 
8.7%
김 3148
 
5.5%
숙 3117
 
5.4%
0 2249
 
3.9%
최 2079
 
3.6%
정 1869
 
3.3%
미 1764
 
3.1%
2 1721
 
3.0%
권 1465
 
2.6%
희 1465
 
2.6%
Other values (86) 33584
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43663
76.0%
Decimal Number 6452
 
11.2%
Space Separator 4981
 
8.7%
Dash Punctuation 1348
 
2.3%
Connector Punctuation 991
 
1.7%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 3148
 
7.2%
숙 3117
 
7.1%
최 2079
 
4.8%
정 1869
 
4.3%
미 1764
 
4.0%
권 1465
 
3.4%
희 1465
 
3.4%
유 1317
 
3.0%
장 1230
 
2.8%
진 1229
 
2.8%
Other values (72) 24980
57.2%
Decimal Number
ValueCountFrequency (%)
0 2249
34.9%
2 1721
26.7%
1 831
 
12.9%
5 614
 
9.5%
9 403
 
6.2%
3 259
 
4.0%
4 220
 
3.4%
8 71
 
1.1%
6 58
 
0.9%
7 26
 
0.4%
Space Separator
ValueCountFrequency (%)
4981
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1348
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 991
100.0%
Other Punctuation
ValueCountFrequency (%)
? 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43660
76.0%
Common 13779
 
24.0%
Han 2
 
< 0.1%
Hiragana 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 3148
 
7.2%
숙 3117
 
7.1%
최 2079
 
4.8%
정 1869
 
4.3%
미 1764
 
4.0%
권 1465
 
3.4%
희 1465
 
3.4%
유 1317
 
3.0%
장 1230
 
2.8%
진 1229
 
2.8%
Other values (69) 24977
57.2%
Common
ValueCountFrequency (%)
4981
36.1%
0 2249
16.3%
2 1721
 
12.5%
- 1348
 
9.8%
_ 991
 
7.2%
1 831
 
6.0%
5 614
 
4.5%
9 403
 
2.9%
3 259
 
1.9%
4 220
 
1.6%
Other values (4) 162
 
1.2%
Han
ValueCountFrequency (%)
熏 1
50.0%
遍 1
50.0%
Hiragana
ValueCountFrequency (%)
で 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43659
76.0%
ASCII 13779
 
24.0%
CJK 2
 
< 0.1%
Hiragana 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4981
36.1%
0 2249
16.3%
2 1721
 
12.5%
- 1348
 
9.8%
_ 991
 
7.2%
1 831
 
6.0%
5 614
 
4.5%
9 403
 
2.9%
3 259
 
1.9%
4 220
 
1.6%
Other values (4) 162
 
1.2%
Hangul
ValueCountFrequency (%)
김 3148
 
7.2%
숙 3117
 
7.1%
최 2079
 
4.8%
정 1869
 
4.3%
미 1764
 
4.0%
권 1465
 
3.4%
희 1465
 
3.4%
유 1317
 
3.0%
장 1230
 
2.8%
진 1229
 
2.8%
Other values (68) 24976
57.2%
Hiragana
ValueCountFrequency (%)
で 1
100.0%
CJK
ValueCountFrequency (%)
熏 1
50.0%
遍 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅐ 1
100.0%

조사자명
Categorical

IMBALANCE 

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1_식물
7719 
2_곤충
 
583
(미확인)
 
238
배스
 
221
황소개구리
 
164
Other values (36)
1075 

Length

Max length9
Median length4
Mean length4.0921
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row장한이
2nd row1_식물
3rd row1_식물
4th row환삼덩굴
5th row나혜련

Common Values

ValueCountFrequency (%)
1_식물 7719
77.2%
2_곤충 583
 
5.8%
(미확인) 238
 
2.4%
배스 221
 
2.2%
황소개구리 164
 
1.6%
환삼덩굴 163
 
1.6%
나혜련 117
 
1.2%
한병우 114
 
1.1%
미국쑥부쟁이 70
 
0.7%
권희정 최인재 60
 
0.6%
Other values (31) 551
 
5.5%

Length

2024-01-10T08:07:17.315416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1_식물 7719
74.5%
2_곤충 583
 
5.6%
미확인 238
 
2.3%
배스 221
 
2.1%
황소개구리 164
 
1.6%
환삼덩굴 163
 
1.6%
한병우 155
 
1.5%
나혜련 117
 
1.1%
김양숙 110
 
1.1%
장한이 90
 
0.9%
Other values (33) 801
 
7.7%

대분류
Categorical

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
환삼덩굴
4105 
미국쑥부쟁이
1324 
가시박
679 
1_식물
628 
가시상추
559 
Other values (32)
2705 

Length

Max length9
Median length4
Mean length4.5727
Min length2

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row1_식물
2nd row환삼덩굴
3rd row가시박
4th row습지(정수)
5th row1_식물

Common Values

ValueCountFrequency (%)
환삼덩굴 4105
41.0%
미국쑥부쟁이 1324
 
13.2%
가시박 679
 
6.8%
1_식물 628
 
6.3%
가시상추 559
 
5.6%
하천(유수) 480
 
4.8%
돼지풀 368
 
3.7%
단풍잎돼지풀 327
 
3.3%
미국선녀벌레 300
 
3.0%
습지(정수) 175
 
1.8%
Other values (27) 1055
 
10.5%

Length

2024-01-10T08:07:17.468048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
환삼덩굴 4105
39.8%
미국쑥부쟁이 1324
 
12.8%
가시박 679
 
6.6%
1_식물 628
 
6.1%
가시상추 559
 
5.4%
하천(유수 480
 
4.7%
돼지풀 368
 
3.6%
단풍잎돼지풀 327
 
3.2%
미국선녀벌레 300
 
2.9%
습지(정수 175
 
1.7%
Other values (30) 1362
 
13.2%

생태계교란생물명
Text

Distinct781
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:07:17.865932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length6.3641
Min length2

Characters and Unicode

Total characters63641
Distinct characters262
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique585 ?
Unique (%)5.9%

Sample

1st row환삼덩굴
2nd row도로 및 경계지역
3rd row하천(유수)
4th row서산시 잠홍동 335-17
5th row환삼덩굴
ValueCountFrequency (%)
도로 2368
13.1%
경계지역 2368
13.1%
및 2368
13.1%
하천(유수 2091
11.5%
숲 1320
 
7.3%
가장자리 1319
 
7.3%
경작지 935
 
5.2%
공터 734
 
4.1%
환삼덩굴 321
 
1.8%
습지(정수 266
 
1.5%
Other values (982) 4018
22.2%
2024-01-10T08:07:18.364735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8108
 
12.7%
지 4034
 
6.3%
경 3306
 
5.2%
계 2408
 
3.8%
도 2404
 
3.8%
수 2384
 
3.7%
역 2375
 
3.7%
로 2370
 
3.7%
및 2368
 
3.7%
) 2357
 
3.7%
Other values (252) 31527
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49034
77.0%
Space Separator 8108
 
12.7%
Close Punctuation 2357
 
3.7%
Open Punctuation 2357
 
3.7%
Decimal Number 1519
 
2.4%
Dash Punctuation 264
 
0.4%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 4034
 
8.2%
경 3306
 
6.7%
계 2408
 
4.9%
도 2404
 
4.9%
수 2384
 
4.9%
역 2375
 
4.8%
로 2370
 
4.8%
및 2368
 
4.8%
천 2210
 
4.5%
유 2102
 
4.3%
Other values (237) 23073
47.1%
Decimal Number
ValueCountFrequency (%)
1 252
16.6%
2 215
14.2%
3 174
11.5%
4 165
10.9%
5 156
10.3%
7 150
9.9%
6 135
8.9%
8 119
7.8%
9 81
 
5.3%
0 72
 
4.7%
Space Separator
ValueCountFrequency (%)
8108
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2357
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2357
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 264
100.0%
Other Punctuation
ValueCountFrequency (%)
? 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49034
77.0%
Common 14607
 
23.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 4034
 
8.2%
경 3306
 
6.7%
계 2408
 
4.9%
도 2404
 
4.9%
수 2384
 
4.9%
역 2375
 
4.8%
로 2370
 
4.8%
및 2368
 
4.8%
천 2210
 
4.5%
유 2102
 
4.3%
Other values (237) 23073
47.1%
Common
ValueCountFrequency (%)
8108
55.5%
) 2357
 
16.1%
( 2357
 
16.1%
- 264
 
1.8%
1 252
 
1.7%
2 215
 
1.5%
3 174
 
1.2%
4 165
 
1.1%
5 156
 
1.1%
7 150
 
1.0%
Other values (5) 409
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49034
77.0%
ASCII 14607
 
23.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8108
55.5%
) 2357
 
16.1%
( 2357
 
16.1%
- 264
 
1.8%
1 252
 
1.7%
2 215
 
1.5%
3 174
 
1.2%
4 165
 
1.1%
5 156
 
1.1%
7 150
 
1.0%
Other values (5) 409
 
2.8%
Hangul
ValueCountFrequency (%)
지 4034
 
8.2%
경 3306
 
6.7%
계 2408
 
4.9%
도 2404
 
4.9%
수 2384
 
4.9%
역 2375
 
4.8%
로 2370
 
4.8%
및 2368
 
4.8%
천 2210
 
4.5%
유 2102
 
4.3%
Other values (237) 23073
47.1%

서식지유형
Text

Distinct7123
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:07:18.731006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length15.4822
Min length2

Characters and Unicode

Total characters154822
Distinct characters317
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5483 ?
Unique (%)54.8%

Sample

1st row숲 가장자리
2nd row서산시 부석면 강당리 465-19
3rd row서산시 지곡면 대요리 1123
4th rowN36 46 56.7 E126 28 46.2
5th row하천(유수)
ValueCountFrequency (%)
산 1171
 
3.0%
서산시 794
 
2.0%
공주시 776
 
2.0%
부여군 754
 
1.9%
당진시 724
 
1.8%
금산군 691
 
1.8%
논산시 682
 
1.7%
태안군 668
 
1.7%
예산군 644
 
1.6%
아산시 586
 
1.5%
Other values (6261) 31906
81.0%
2024-01-10T08:07:19.213141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29413
19.0%
리 8371
 
5.4%
면 7099
 
4.6%
1 6945
 
4.5%
산 6603
 
4.3%
- 5060
 
3.3%
2 4846
 
3.1%
3 4504
 
2.9%
시 4351
 
2.8%
군 4254
 
2.7%
Other values (307) 73376
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80900
52.3%
Decimal Number 37397
24.2%
Space Separator 29413
 
19.0%
Dash Punctuation 5060
 
3.3%
Uppercase Letter 1092
 
0.7%
Other Punctuation 614
 
0.4%
Close Punctuation 173
 
0.1%
Open Punctuation 173
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 8371
 
10.3%
면 7099
 
8.8%
산 6603
 
8.2%
시 4351
 
5.4%
군 4254
 
5.3%
천 1787
 
2.2%
서 1558
 
1.9%
성 1385
 
1.7%
부 1304
 
1.6%
읍 1272
 
1.6%
Other values (290) 42916
53.0%
Decimal Number
ValueCountFrequency (%)
1 6945
18.6%
2 4846
13.0%
3 4504
12.0%
6 3842
10.3%
4 3737
10.0%
5 3506
9.4%
7 2763
 
7.4%
0 2447
 
6.5%
9 2429
 
6.5%
8 2378
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
E 546
50.0%
N 546
50.0%
Space Separator
ValueCountFrequency (%)
29413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5060
100.0%
Other Punctuation
ValueCountFrequency (%)
. 614
100.0%
Close Punctuation
ValueCountFrequency (%)
) 173
100.0%
Open Punctuation
ValueCountFrequency (%)
( 173
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80900
52.3%
Common 72830
47.0%
Latin 1092
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 8371
 
10.3%
면 7099
 
8.8%
산 6603
 
8.2%
시 4351
 
5.4%
군 4254
 
5.3%
천 1787
 
2.2%
서 1558
 
1.9%
성 1385
 
1.7%
부 1304
 
1.6%
읍 1272
 
1.6%
Other values (290) 42916
53.0%
Common
ValueCountFrequency (%)
29413
40.4%
1 6945
 
9.5%
- 5060
 
6.9%
2 4846
 
6.7%
3 4504
 
6.2%
6 3842
 
5.3%
4 3737
 
5.1%
5 3506
 
4.8%
7 2763
 
3.8%
0 2447
 
3.4%
Other values (5) 5767
 
7.9%
Latin
ValueCountFrequency (%)
E 546
50.0%
N 546
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80900
52.3%
ASCII 73922
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29413
39.8%
1 6945
 
9.4%
- 5060
 
6.8%
2 4846
 
6.6%
3 4504
 
6.1%
6 3842
 
5.2%
4 3737
 
5.1%
5 3506
 
4.7%
7 2763
 
3.7%
0 2447
 
3.3%
Other values (7) 6859
 
9.3%
Hangul
ValueCountFrequency (%)
리 8371
 
10.3%
면 7099
 
8.8%
산 6603
 
8.2%
시 4351
 
5.4%
군 4254
 
5.3%
천 1787
 
2.2%
서 1558
 
1.9%
성 1385
 
1.7%
부 1304
 
1.6%
읍 1272
 
1.6%
Other values (290) 42916
53.0%

상세주소
Text

Distinct8317
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:07:19.559865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length22.9443
Min length2

Characters and Unicode

Total characters229443
Distinct characters129
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6893 ?
Unique (%)68.9%

Sample

1st row천안시 동남구 수신면 발산리 산 4-1
2nd rowN36 39 04.9 E126 24 30.2
3rd rowN36 54 33.7 E126 27 37.5
4th row36.79086111
5th row천안시 서북구 성거읍 석교리 251-3
ValueCountFrequency (%)
n36 8676
 
15.3%
e126 6123
 
10.8%
e127 2619
 
4.6%
천안시 674
 
1.2%
동남구 469
 
0.8%
51 393
 
0.7%
48 383
 
0.7%
35 379
 
0.7%
34 379
 
0.7%
10 378
 
0.7%
Other values (2686) 36058
63.8%
2024-01-10T08:07:20.020964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46547
20.3%
3 21707
9.5%
6 21156
9.2%
1 20659
9.0%
2 20331
8.9%
. 17846
 
7.8%
4 12648
 
5.5%
5 11531
 
5.0%
0 10480
 
4.6%
E 8747
 
3.8%
Other values (119) 37791
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 138869
60.5%
Space Separator 46547
 
20.3%
Other Punctuation 17846
 
7.8%
Uppercase Letter 17494
 
7.6%
Other Letter 8226
 
3.6%
Dash Punctuation 461
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 868
 
10.6%
안 684
 
8.3%
시 680
 
8.3%
구 679
 
8.3%
리 677
 
8.2%
동 542
 
6.6%
남 538
 
6.5%
면 477
 
5.8%
북 266
 
3.2%
서 222
 
2.7%
Other values (104) 2593
31.5%
Decimal Number
ValueCountFrequency (%)
3 21707
15.6%
6 21156
15.2%
1 20659
14.9%
2 20331
14.6%
4 12648
9.1%
5 11531
8.3%
0 10480
7.5%
7 8624
 
6.2%
8 5961
 
4.3%
9 5772
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
E 8747
50.0%
N 8747
50.0%
Space Separator
ValueCountFrequency (%)
46547
100.0%
Other Punctuation
ValueCountFrequency (%)
. 17846
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 461
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203723
88.8%
Latin 17494
 
7.6%
Hangul 8226
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 868
 
10.6%
안 684
 
8.3%
시 680
 
8.3%
구 679
 
8.3%
리 677
 
8.2%
동 542
 
6.6%
남 538
 
6.5%
면 477
 
5.8%
북 266
 
3.2%
서 222
 
2.7%
Other values (104) 2593
31.5%
Common
ValueCountFrequency (%)
46547
22.8%
3 21707
10.7%
6 21156
10.4%
1 20659
10.1%
2 20331
10.0%
. 17846
 
8.8%
4 12648
 
6.2%
5 11531
 
5.7%
0 10480
 
5.1%
7 8624
 
4.2%
Other values (3) 12194
 
6.0%
Latin
ValueCountFrequency (%)
E 8747
50.0%
N 8747
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 221217
96.4%
Hangul 8226
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46547
21.0%
3 21707
9.8%
6 21156
9.6%
1 20659
9.3%
2 20331
9.2%
. 17846
 
8.1%
4 12648
 
5.7%
5 11531
 
5.2%
0 10480
 
4.7%
E 8747
 
4.0%
Other values (5) 29565
13.4%
Hangul
ValueCountFrequency (%)
천 868
 
10.6%
안 684
 
8.3%
시 680
 
8.3%
구 679
 
8.3%
리 677
 
8.2%
동 542
 
6.6%
남 538
 
6.5%
면 477
 
5.8%
북 266
 
3.2%
서 222
 
2.7%
Other values (104) 2593
31.5%

조사지역명
Text

Distinct7584
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:07:20.320192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length11
Mean length11.527
Min length4

Characters and Unicode

Total characters115270
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5736 ?
Unique (%)57.4%

Sample

1st rowN36 43 08.6 E127 18 22.5
2nd row36.65866667
3rd row36.8975
4th row126.4864722
5th rowN36 51 43.9 E127 11 07.6
ValueCountFrequency (%)
n36 707
 
5.2%
e127 703
 
5.2%
44 68
 
0.5%
45 66
 
0.5%
54 55
 
0.4%
16 52
 
0.4%
53 50
 
0.4%
07 50
 
0.4%
13 47
 
0.3%
06 45
 
0.3%
Other values (7604) 11692
86.4%
2024-01-10T08:07:20.726031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 18122
15.7%
3 17760
15.4%
1 10776
9.3%
. 10693
9.3%
2 9562
8.3%
7 9314
8.1%
8 8420
7.3%
4 8188
7.1%
5 7568
6.6%
9 5347
 
4.6%
Other values (4) 9520
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99627
86.4%
Other Punctuation 10693
 
9.3%
Space Separator 3536
 
3.1%
Uppercase Letter 1414
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 18122
18.2%
3 17760
17.8%
1 10776
10.8%
2 9562
9.6%
7 9314
9.3%
8 8420
8.5%
4 8188
8.2%
5 7568
7.6%
9 5347
 
5.4%
0 4570
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
N 707
50.0%
E 707
50.0%
Other Punctuation
ValueCountFrequency (%)
. 10693
100.0%
Space Separator
ValueCountFrequency (%)
3536
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 113856
98.8%
Latin 1414
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
6 18122
15.9%
3 17760
15.6%
1 10776
9.5%
. 10693
9.4%
2 9562
8.4%
7 9314
8.2%
8 8420
7.4%
4 8188
7.2%
5 7568
6.6%
9 5347
 
4.7%
Other values (2) 8106
7.1%
Latin
ValueCountFrequency (%)
N 707
50.0%
E 707
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 18122
15.7%
3 17760
15.4%
1 10776
9.3%
. 10693
9.3%
2 9562
8.3%
7 9314
8.1%
8 8420
7.3%
4 8188
7.1%
5 7568
6.6%
9 5347
 
4.6%
Other values (4) 9520
8.3%

GPS좌표
Text

MISSING 

Distinct7287
Distinct (%)74.7%
Missing240
Missing (%)2.4%
Memory size156.2 KiB
2024-01-10T08:07:21.012259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.420082
Min length1

Characters and Unicode

Total characters101700
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5451 ?
Unique (%)55.9%

Sample

1st row36.71905556
2nd row126.3963333
3rd row126.4618333
4th row2500
5th row36.86219444
ValueCountFrequency (%)
600 14
 
0.1%
120 13
 
0.1%
100 11
 
0.1%
40 11
 
0.1%
20 11
 
0.1%
50 11
 
0.1%
1000 9
 
0.1%
500 9
 
0.1%
1500 9
 
0.1%
400 8
 
0.1%
Other values (7277) 9654
98.9%
2024-01-10T08:07:21.379097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15665
15.4%
2 15308
15.1%
6 14075
13.8%
7 10002
9.8%
. 9454
9.3%
8 7413
7.3%
3 7407
7.3%
5 6413
6.3%
4 6228
 
6.1%
9 5234
 
5.1%
Other values (3) 4501
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92241
90.7%
Other Punctuation 9454
 
9.3%
Space Separator 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15665
17.0%
2 15308
16.6%
6 14075
15.3%
7 10002
10.8%
8 7413
8.0%
3 7407
8.0%
5 6413
7.0%
4 6228
 
6.8%
9 5234
 
5.7%
0 4496
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 9454
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 101700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15665
15.4%
2 15308
15.1%
6 14075
13.8%
7 10002
9.8%
. 9454
9.3%
8 7413
7.3%
3 7407
7.3%
5 6413
6.3%
4 6228
 
6.1%
9 5234
 
5.1%
Other values (3) 4501
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 101700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15665
15.4%
2 15308
15.1%
6 14075
13.8%
7 10002
9.8%
. 9454
9.3%
8 7413
7.3%
3 7407
7.3%
5 6413
6.3%
4 6228
 
6.1%
9 5234
 
5.1%
Other values (3) 4501
 
4.4%

위도
Text

MISSING 

Distinct864
Distinct (%)8.9%
Missing340
Missing (%)3.4%
Memory size156.2 KiB
2024-01-10T08:07:21.671437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.1624224
Min length1

Characters and Unicode

Total characters30549
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique572 ?
Unique (%)5.9%

Sample

1st row127.30625
2nd row90
3rd row100
4th row9000
5th row127.1854444
ValueCountFrequency (%)
100 500
 
5.2%
50 339
 
3.5%
200 335
 
3.5%
4 315
 
3.3%
20 265
 
2.7%
10 264
 
2.7%
25 259
 
2.7%
30 257
 
2.7%
15 253
 
2.6%
150 246
 
2.5%
Other values (854) 6627
68.6%
2024-01-10T08:07:22.075302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10217
33.4%
1 4247
13.9%
2 3673
 
12.0%
5 2715
 
8.9%
4 1864
 
6.1%
3 1584
 
5.2%
7 1482
 
4.9%
6 1398
 
4.6%
8 1004
 
3.3%
9 818
 
2.7%
Other values (3) 1547
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29002
94.9%
Other Punctuation 707
 
2.3%
Space Separator 672
 
2.2%
Dash Punctuation 168
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10217
35.2%
1 4247
14.6%
2 3673
 
12.7%
5 2715
 
9.4%
4 1864
 
6.4%
3 1584
 
5.5%
7 1482
 
5.1%
6 1398
 
4.8%
8 1004
 
3.5%
9 818
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 707
100.0%
Space Separator
ValueCountFrequency (%)
672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30549
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10217
33.4%
1 4247
13.9%
2 3673
 
12.0%
5 2715
 
8.9%
4 1864
 
6.1%
3 1584
 
5.2%
7 1482
 
4.9%
6 1398
 
4.6%
8 1004
 
3.3%
9 818
 
2.7%
Other values (3) 1547
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10217
33.4%
1 4247
13.9%
2 3673
 
12.0%
5 2715
 
8.9%
4 1864
 
6.1%
3 1584
 
5.2%
7 1482
 
4.9%
6 1398
 
4.6%
8 1004
 
3.3%
9 818
 
2.7%
Other values (3) 1547
 
5.1%

경도
Text

MISSING 

Distinct453
Distinct (%)4.8%
Missing471
Missing (%)4.7%
Memory size156.2 KiB
2024-01-10T08:07:22.455162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length34
Mean length2.9604366
Min length1

Characters and Unicode

Total characters28210
Distinct characters57
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)1.8%

Sample

1st row13000
2nd row1000
3rd row2000
4th row4
5th row1200
ValueCountFrequency (%)
100 465
 
4.9%
200 422
 
4.4%
300 406
 
4.3%
500 400
 
4.2%
1000 373
 
3.9%
50 348
 
3.6%
30 266
 
2.8%
20 256
 
2.7%
150 244
 
2.6%
10 235
 
2.5%
Other values (451) 6134
64.2%
2024-01-10T08:07:22.944101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15057
53.4%
1 3122
 
11.1%
5 2559
 
9.1%
2 2454
 
8.7%
3 1582
 
5.6%
4 977
 
3.5%
8 698
 
2.5%
6 689
 
2.4%
7 605
 
2.1%
9 294
 
1.0%
Other values (47) 173
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28037
99.4%
Other Letter 103
 
0.4%
Space Separator 60
 
0.2%
Dash Punctuation 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 13
 
12.6%
망 12
 
11.7%
개 7
 
6.8%
국 4
 
3.9%
리 4
 
3.9%
서 4
 
3.9%
이 3
 
2.9%
큰 3
 
2.9%
미 3
 
2.9%
가 3
 
2.9%
Other values (35) 47
45.6%
Decimal Number
ValueCountFrequency (%)
0 15057
53.7%
1 3122
 
11.1%
5 2559
 
9.1%
2 2454
 
8.8%
3 1582
 
5.6%
4 977
 
3.5%
8 698
 
2.5%
6 689
 
2.5%
7 605
 
2.2%
9 294
 
1.0%
Space Separator
ValueCountFrequency (%)
60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28107
99.6%
Hangul 103
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 13
 
12.6%
망 12
 
11.7%
개 7
 
6.8%
국 4
 
3.9%
리 4
 
3.9%
서 4
 
3.9%
이 3
 
2.9%
큰 3
 
2.9%
미 3
 
2.9%
가 3
 
2.9%
Other values (35) 47
45.6%
Common
ValueCountFrequency (%)
0 15057
53.6%
1 3122
 
11.1%
5 2559
 
9.1%
2 2454
 
8.7%
3 1582
 
5.6%
4 977
 
3.5%
8 698
 
2.5%
6 689
 
2.5%
7 605
 
2.2%
9 294
 
1.0%
Other values (2) 70
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28107
99.6%
Hangul 103
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15057
53.6%
1 3122
 
11.1%
5 2559
 
9.1%
2 2454
 
8.7%
3 1582
 
5.6%
4 977
 
3.5%
8 698
 
2.5%
6 689
 
2.5%
7 605
 
2.2%
9 294
 
1.0%
Other values (2) 70
 
0.2%
Hangul
ValueCountFrequency (%)
초 13
 
12.6%
망 12
 
11.7%
개 7
 
6.8%
국 4
 
3.9%
리 4
 
3.9%
서 4
 
3.9%
이 3
 
2.9%
큰 3
 
2.9%
미 3
 
2.9%
가 3
 
2.9%
Other values (35) 47
45.6%

토지면적
Text

MISSING 

Distinct438
Distinct (%)4.6%
Missing392
Missing (%)3.9%
Memory size156.2 KiB
2024-01-10T08:07:23.260115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length1
Mean length1.8653206
Min length1

Characters and Unicode

Total characters17922
Distinct characters196
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique228 ?
Unique (%)2.4%

Sample

1st row65000
2nd row11
3rd row20
4th row서양민들레 울산도깨비바늘 큰김의털 큰도꼬마리 토끼풀
5th row10000
ValueCountFrequency (%)
1 1583
15.4%
0 1016
 
9.9%
2 754
 
7.3%
5 751
 
7.3%
3 703
 
6.8%
10 591
 
5.8%
4 464
 
4.5%
8 291
 
2.8%
6 254
 
2.5%
13 254
 
2.5%
Other values (382) 3611
35.2%
2024-01-10T08:07:23.716800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3514
19.6%
0 3332
18.6%
2 1640
9.2%
3 1412
 
7.9%
5 1365
 
7.6%
4 748
 
4.2%
666
 
3.7%
8 512
 
2.9%
6 452
 
2.5%
7 430
 
2.4%
Other values (186) 3851
21.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13645
76.1%
Other Letter 3611
 
20.1%
Space Separator 666
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 236
 
6.5%
국 191
 
5.3%
미 179
 
5.0%
초 159
 
4.4%
이 146
 
4.0%
망 143
 
4.0%
가 137
 
3.8%
쟁 98
 
2.7%
개 86
 
2.4%
막 84
 
2.3%
Other values (175) 2152
59.6%
Decimal Number
ValueCountFrequency (%)
1 3514
25.8%
0 3332
24.4%
2 1640
12.0%
3 1412
10.3%
5 1365
 
10.0%
4 748
 
5.5%
8 512
 
3.8%
6 452
 
3.3%
7 430
 
3.2%
9 240
 
1.8%
Space Separator
ValueCountFrequency (%)
666
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14311
79.9%
Hangul 3611
 
20.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 236
 
6.5%
국 191
 
5.3%
미 179
 
5.0%
초 159
 
4.4%
이 146
 
4.0%
망 143
 
4.0%
가 137
 
3.8%
쟁 98
 
2.7%
개 86
 
2.4%
막 84
 
2.3%
Other values (175) 2152
59.6%
Common
ValueCountFrequency (%)
1 3514
24.6%
0 3332
23.3%
2 1640
11.5%
3 1412
9.9%
5 1365
 
9.5%
4 748
 
5.2%
666
 
4.7%
8 512
 
3.6%
6 452
 
3.2%
7 430
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14311
79.9%
Hangul 3611
 
20.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3514
24.6%
0 3332
23.3%
2 1640
11.5%
3 1412
9.9%
5 1365
 
9.5%
4 748
 
5.2%
666
 
4.7%
8 512
 
3.6%
6 452
 
3.2%
7 430
 
3.0%
Hangul
ValueCountFrequency (%)
리 236
 
6.5%
국 191
 
5.3%
미 179
 
5.0%
초 159
 
4.4%
이 146
 
4.0%
망 143
 
4.0%
가 137
 
3.8%
쟁 98
 
2.7%
개 86
 
2.4%
막 84
 
2.3%
Other values (175) 2152
59.6%

개별수
Text

MISSING 

Distinct2805
Distinct (%)37.1%
Missing2443
Missing (%)24.4%
Memory size156.2 KiB
2024-01-10T08:07:24.298556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length53
Mean length12.831679
Min length1

Characters and Unicode

Total characters96969
Distinct characters252
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1940 ?
Unique (%)25.7%

Sample

1st row5
2nd row미국가막사리 아까시나무
3rd row0
4th row8
5th row가는털비름 망초
ValueCountFrequency (%)
개망초 2709
 
12.7%
망초 2190
 
10.2%
소리쟁이 2006
 
9.4%
미국가막사리 1791
 
8.4%
미국자리공 1025
 
4.8%
달맞이꽃 1017
 
4.8%
아까시나무 907
 
4.2%
서양민들레 607
 
2.8%
환삼덩굴 526
 
2.5%
토끼풀 452
 
2.1%
Other values (227) 8153
38.1%
2024-01-10T08:07:24.780390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13826
 
14.3%
리 6040
 
6.2%
초 5146
 
5.3%
망 4932
 
5.1%
국 4080
 
4.2%
이 3662
 
3.8%
미 3551
 
3.7%
개 3168
 
3.3%
가 2826
 
2.9%
쟁 2453
 
2.5%
Other values (242) 47285
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81245
83.8%
Space Separator 13826
 
14.3%
Decimal Number 1893
 
2.0%
Other Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 6040
 
7.4%
초 5146
 
6.3%
망 4932
 
6.1%
국 4080
 
5.0%
이 3662
 
4.5%
미 3551
 
4.4%
개 3168
 
3.9%
가 2826
 
3.5%
쟁 2453
 
3.0%
소 2229
 
2.7%
Other values (229) 43158
53.1%
Decimal Number
ValueCountFrequency (%)
1 512
27.0%
3 461
24.4%
0 427
22.6%
2 209
11.0%
5 118
 
6.2%
4 54
 
2.9%
7 43
 
2.3%
6 31
 
1.6%
8 31
 
1.6%
9 7
 
0.4%
Space Separator
ValueCountFrequency (%)
13826
100.0%
Other Punctuation
ValueCountFrequency (%)
? 3
100.0%
Open Punctuation
ValueCountFrequency (%)
「 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81242
83.8%
Common 15724
 
16.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 6040
 
7.4%
초 5146
 
6.3%
망 4932
 
6.1%
국 4080
 
5.0%
이 3662
 
4.5%
미 3551
 
4.4%
개 3168
 
3.9%
가 2826
 
3.5%
쟁 2453
 
3.0%
소 2229
 
2.7%
Other values (227) 43155
53.1%
Common
ValueCountFrequency (%)
13826
87.9%
1 512
 
3.3%
3 461
 
2.9%
0 427
 
2.7%
2 209
 
1.3%
5 118
 
0.8%
4 54
 
0.3%
7 43
 
0.3%
6 31
 
0.2%
8 31
 
0.2%
Other values (3) 12
 
0.1%
Han
ValueCountFrequency (%)
潁 2
66.7%
堅 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81242
83.8%
ASCII 15722
 
16.2%
CJK 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13826
87.9%
1 512
 
3.3%
3 461
 
2.9%
0 427
 
2.7%
2 209
 
1.3%
5 118
 
0.8%
4 54
 
0.3%
7 43
 
0.3%
6 31
 
0.2%
8 31
 
0.2%
Other values (2) 10
 
0.1%
Hangul
ValueCountFrequency (%)
리 6040
 
7.4%
초 5146
 
6.3%
망 4932
 
6.1%
국 4080
 
5.0%
이 3662
 
4.5%
미 3551
 
4.4%
개 3168
 
3.9%
가 2826
 
3.5%
쟁 2453
 
3.0%
소 2229
 
2.7%
Other values (227) 43155
53.1%
None
ValueCountFrequency (%)
「 2
100.0%
CJK
ValueCountFrequency (%)
潁 2
66.7%
堅 1
33.3%

밀도
Text

MISSING 

Distinct391
Distinct (%)4.0%
Missing176
Missing (%)1.8%
Memory size156.2 KiB
2024-01-10T08:07:24.962059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length1
Mean length1.8906759
Min length1

Characters and Unicode

Total characters18574
Distinct characters168
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)3.2%

Sample

1st row돼지풀 미국가막사리 미국쑥부쟁이 미국자리공 소리쟁이 아까시나무
2nd row0
3rd row0
4th row1
5th row달맞이꽃 둥근잎유홍초 망초 붉은서나물 유럽점나도나물 큰개불알풀
ValueCountFrequency (%)
0 6864
61.3%
1 1875
 
16.7%
3 339
 
3.0%
2 227
 
2.0%
망초 224
 
2.0%
개망초 204
 
1.8%
미국가막사리 148
 
1.3%
아까시나무 131
 
1.2%
소리쟁이 116
 
1.0%
미국자리공 108
 
1.0%
Other values (94) 960
 
8.6%
2024-01-10T08:07:25.262698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6864
37.0%
1 1875
 
10.1%
1372
 
7.4%
초 490
 
2.6%
리 482
 
2.6%
망 442
 
2.4%
국 415
 
2.2%
미 395
 
2.1%
3 339
 
1.8%
이 282
 
1.5%
Other values (158) 5618
30.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9322
50.2%
Other Letter 7880
42.4%
Space Separator 1372
 
7.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 490
 
6.2%
리 482
 
6.1%
망 442
 
5.6%
국 415
 
5.3%
미 395
 
5.0%
이 282
 
3.6%
나 249
 
3.2%
개 241
 
3.1%
가 231
 
2.9%
쟁 189
 
2.4%
Other values (152) 4464
56.6%
Decimal Number
ValueCountFrequency (%)
0 6864
73.6%
1 1875
 
20.1%
3 339
 
3.6%
2 227
 
2.4%
4 17
 
0.2%
Space Separator
ValueCountFrequency (%)
1372
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10694
57.6%
Hangul 7880
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 490
 
6.2%
리 482
 
6.1%
망 442
 
5.6%
국 415
 
5.3%
미 395
 
5.0%
이 282
 
3.6%
나 249
 
3.2%
개 241
 
3.1%
가 231
 
2.9%
쟁 189
 
2.4%
Other values (152) 4464
56.6%
Common
ValueCountFrequency (%)
0 6864
64.2%
1 1875
 
17.5%
1372
 
12.8%
3 339
 
3.2%
2 227
 
2.1%
4 17
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10694
57.6%
Hangul 7880
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6864
64.2%
1 1875
 
17.5%
1372
 
12.8%
3 339
 
3.2%
2 227
 
2.1%
4 17
 
0.2%
Hangul
ValueCountFrequency (%)
초 490
 
6.2%
리 482
 
6.1%
망 442
 
5.6%
국 415
 
5.3%
미 395
 
5.0%
이 282
 
3.6%
나 249
 
3.2%
개 241
 
3.1%
가 231
 
2.9%
쟁 189
 
2.4%
Other values (152) 4464
56.6%

동반외래종명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8413 
0
1177 
2
 
251
3
 
155
우선 관리종
 
2
Other values (2)
 
2

Length

Max length6
Median length1
Mean length1.0013
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row1
3rd row1
4th row3
5th row0

Common Values

ValueCountFrequency (%)
1 8413
84.1%
0 1177
 
11.8%
2 251
 
2.5%
3 155
 
1.6%
우선 관리종 2
 
< 0.1%
<NA> 1
 
< 0.1%
4 1
 
< 0.1%

Length

2024-01-10T08:07:25.383235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:07:25.479204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8413
84.1%
0 1177
 
11.8%
2 251
 
2.5%
3 155
 
1.5%
우선 2
 
< 0.1%
관리종 2
 
< 0.1%
na 1
 
< 0.1%
4 1
 
< 0.1%

비고
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
4423 
3
2833 
1
1975 
0
501 
<NA>
 
264

Length

Max length4
Median length1
Mean length1.0792
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row3
4th row0
5th row1

Common Values

ValueCountFrequency (%)
2 4423
44.2%
3 2833
28.3%
1 1975
19.8%
0 501
 
5.0%
<NA> 264
 
2.6%
4 4
 
< 0.1%

Length

2024-01-10T08:07:25.588074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:07:25.686251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 4423
44.2%
3 2833
28.3%
1 1975
19.8%
0 501
 
5.0%
na 264
 
2.6%
4 4
 
< 0.1%

분포
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
7713 
2
912 
1
 
662
3
 
523
4
 
174

Length

Max length4
Median length1
Mean length1.0048
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row0
3rd row0
4th row0
5th row3

Common Values

ValueCountFrequency (%)
0 7713
77.1%
2 912
 
9.1%
1 662
 
6.6%
3 523
 
5.2%
4 174
 
1.7%
<NA> 16
 
0.2%

Length

2024-01-10T08:07:25.808550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:07:25.939006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 7713
77.1%
2 912
 
9.1%
1 662
 
6.6%
3 523
 
5.2%
4 174
 
1.7%
na 16
 
0.2%

시군
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
7607 
1
1207 
2
 
749
<NA>
 
265
3
 
145

Length

Max length4
Median length1
Mean length1.0795
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 7607
76.1%
1 1207
 
12.1%
2 749
 
7.5%
<NA> 265
 
2.6%
3 145
 
1.5%
4 27
 
0.3%

Length

2024-01-10T08:07:26.069517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:07:26.166507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 7607
76.1%
1 1207
 
12.1%
2 749
 
7.5%
na 265
 
2.6%
3 145
 
1.5%
4 27
 
0.3%

서식지
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
4223 
1
3776 
2
1573 
<NA>
 
279
3
 
146

Length

Max length4
Median length1
Mean length1.0837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 4223
42.2%
1 3776
37.8%
2 1573
 
15.7%
<NA> 279
 
2.8%
3 146
 
1.5%
4 3
 
< 0.1%

Length

2024-01-10T08:07:26.276422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:07:26.375975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4223
42.2%
1 3776
37.8%
2 1573
 
15.7%
na 279
 
2.8%
3 146
 
1.5%
4 3
 
< 0.1%

공원거리
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.1%
Missing15
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1.4707061
Minimum0
Maximum18
Zeros663
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T08:07:26.470726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8732278
Coefficient of variation (CV)1.2736929
Kurtosis30.412352
Mean1.4707061
Median Absolute Deviation (MAD)0
Skewness5.3209785
Sum14685
Variance3.5089825
MonotonicityNot monotonic
2024-01-10T08:07:26.572981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 7024
70.2%
2 1558
 
15.6%
0 663
 
6.6%
3 497
 
5.0%
11 88
 
0.9%
13 82
 
0.8%
14 38
 
0.4%
12 17
 
0.2%
15 10
 
0.1%
16 4
 
< 0.1%
Other values (2) 4
 
< 0.1%
(Missing) 15
 
0.1%
ValueCountFrequency (%)
0 663
 
6.6%
1 7024
70.2%
2 1558
 
15.6%
3 497
 
5.0%
11 88
 
0.9%
12 17
 
0.2%
13 82
 
0.8%
14 38
 
0.4%
15 10
 
0.1%
16 4
 
< 0.1%
ValueCountFrequency (%)
18 2
 
< 0.1%
17 2
 
< 0.1%
16 4
 
< 0.1%
15 10
 
0.1%
14 38
 
0.4%
13 82
 
0.8%
12 17
 
0.2%
11 88
 
0.9%
3 497
 
5.0%
2 1558
15.6%

문화재거리
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
3751 
3
3166 
1
2243 
0
389 
II
 
120
Other values (16)
 
331

Length

Max length4
Median length1
Mean length1.0524
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row3
3rd row2
4th row0
5th row1

Common Values

ValueCountFrequency (%)
2 3751
37.5%
3 3166
31.7%
1 2243
22.4%
0 389
 
3.9%
II 120
 
1.2%
III 105
 
1.1%
13 77
 
0.8%
12 53
 
0.5%
14 34
 
0.3%
I 18
 
0.2%
Other values (11) 44
 
0.4%

Length

2024-01-10T08:07:26.694447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 3751
37.5%
3 3166
31.7%
1 2243
22.4%
0 389
 
3.9%
ii 120
 
1.2%
iii 105
 
1.1%
13 77
 
0.8%
12 53
 
0.5%
14 34
 
0.3%
i 18
 
0.2%
Other values (11) 44
 
0.4%

분포규모
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
4323 
1
3385 
2
1028 
3
 
273
<NA>
 
265
Other values (15)
726 

Length

Max length4
Median length1
Mean length1.1112
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row0
3rd row2
4th row9
5th row2

Common Values

ValueCountFrequency (%)
0 4323
43.2%
1 3385
33.9%
2 1028
 
10.3%
3 273
 
2.7%
<NA> 265
 
2.6%
4 177
 
1.8%
II 111
 
1.1%
8 70
 
0.7%
9 70
 
0.7%
10 60
 
0.6%
Other values (10) 238
 
2.4%

Length

2024-01-10T08:07:26.812487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4323
43.2%
1 3385
33.9%
2 1028
 
10.3%
3 273
 
2.7%
na 265
 
2.6%
4 177
 
1.8%
ii 111
 
1.1%
8 70
 
0.7%
9 70
 
0.7%
10 60
 
0.6%
Other values (10) 238
 
2.4%

분포밀도
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
9
1922 
8
1768 
7
1275 
10
1108 
6
778 
Other values (22)
3149 

Length

Max length4
Median length1
Mean length1.3217
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row7
3rd row11
4th row-
5th row0

Common Values

ValueCountFrequency (%)
9 1922
19.2%
8 1768
17.7%
7 1275
12.8%
10 1108
11.1%
6 778
7.8%
11 594
 
5.9%
5 375
 
3.8%
0 326
 
3.3%
<NA> 280
 
2.8%
12 267
 
2.7%
Other values (17) 1307
13.1%

Length

2024-01-10T08:07:26.956622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9 1922
19.2%
8 1768
17.7%
7 1275
12.8%
10 1108
11.1%
6 778
7.8%
11 594
 
5.9%
5 375
 
3.8%
0 326
 
3.3%
na 280
 
2.8%
12 267
 
2.7%
Other values (17) 1307
13.1%

분포유형
Categorical

IMBALANCE 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
-
6035 
IV
1100 
III
861 
3
 
306
<NA>
 
280
Other values (22)
1418 

Length

Max length4
Median length1
Mean length1.4112
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row8
2nd row-
3rd rowIII
4th row4
5th row10

Common Values

ValueCountFrequency (%)
- 6035
60.4%
IV 1100
 
11.0%
III 861
 
8.6%
3 306
 
3.1%
<NA> 280
 
2.8%
II 246
 
2.5%
4 214
 
2.1%
6 184
 
1.8%
9 151
 
1.5%
8 145
 
1.5%
Other values (17) 478
 
4.8%

Length

2024-01-10T08:07:27.095691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
6035
60.4%
iv 1100
 
11.0%
iii 861
 
8.6%
3 306
 
3.1%
na 280
 
2.8%
ii 246
 
2.5%
4 214
 
2.1%
6 184
 
1.8%
9 151
 
1.5%
8 145
 
1.5%
Other values (17) 478
 
4.8%

방제
Categorical

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
3661 
4
3039 
2
1024 
5
668 
-
479 
Other values (18)
1129 

Length

Max length4
Median length1
Mean length1.1703
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row-
2nd row3
3rd row4
4th row2
5th rowIV

Common Values

ValueCountFrequency (%)
3 3661
36.6%
4 3039
30.4%
2 1024
 
10.2%
5 668
 
6.7%
- 479
 
4.8%
<NA> 467
 
4.7%
6 119
 
1.2%
1 108
 
1.1%
IV 91
 
0.9%
0 90
 
0.9%
Other values (13) 254
 
2.5%

Length

2024-01-10T08:07:27.207183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 3661
36.6%
4 3039
30.4%
2 1024
 
10.2%
5 668
 
6.7%
479
 
4.8%
na 467
 
4.7%
6 119
 
1.2%
1 108
 
1.1%
iv 91
 
0.9%
0 90
 
0.9%
Other values (13) 254
 
2.5%

전문가
Categorical

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
3089 
0
2741 
2
1641 
3
869 
<NA>
616 
Other values (17)
1044 

Length

Max length4
Median length1
Mean length1.2018
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row3
2nd row0
3rd row1
4th row3
5th row4

Common Values

ValueCountFrequency (%)
1 3089
30.9%
0 2741
27.4%
2 1641
16.4%
3 869
 
8.7%
<NA> 616
 
6.2%
4 596
 
6.0%
5 209
 
2.1%
6 76
 
0.8%
7 39
 
0.4%
A 35
 
0.4%
Other values (12) 89
 
0.9%

Length

2024-01-10T08:07:27.317971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 3089
30.9%
0 2741
27.4%
2 1641
16.4%
3 869
 
8.7%
na 616
 
6.2%
4 596
 
6.0%
5 209
 
2.1%
6 76
 
0.8%
7 39
 
0.4%
a 35
 
0.4%
Other values (12) 89
 
0.9%

합계
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4
2508 
3
2221 
5
2015 
2
1021 
<NA>
977 
Other values (13)
1258 

Length

Max length4
Median length1
Mean length1.3054
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row3
2nd row4
3rd row6
4th row<NA>
5th row3

Common Values

ValueCountFrequency (%)
4 2508
25.1%
3 2221
22.2%
5 2015
20.2%
2 1021
10.2%
<NA> 977
 
9.8%
6 594
 
5.9%
1 267
 
2.7%
0 176
 
1.8%
7 151
 
1.5%
2026 19
 
0.2%
Other values (8) 51
 
0.5%

Length

2024-01-10T08:07:27.427881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4 2508
25.1%
3 2221
22.2%
5 2015
20.2%
2 1021
10.2%
na 977
 
9.8%
6 594
 
5.9%
1 267
 
2.7%
0 176
 
1.8%
7 151
 
1.5%
2026 19
 
0.2%
Other values (8) 51
 
0.5%

등급
Categorical

IMBALANCE 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9033 
3
 
186
4
 
177
5
 
172
A
 
125
Other values (13)
 
307

Length

Max length4
Median length4
Mean length3.7234
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row3

Common Values

ValueCountFrequency (%)
<NA> 9033
90.3%
3 186
 
1.9%
4 177
 
1.8%
5 172
 
1.7%
A 125
 
1.2%
B 98
 
1.0%
2 78
 
0.8%
6 61
 
0.6%
2022 26
 
0.3%
O 14
 
0.1%
Other values (8) 30
 
0.3%

Length

2024-01-10T08:07:27.537831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9033
90.3%
3 186
 
1.9%
4 177
 
1.8%
5 172
 
1.7%
a 125
 
1.2%
b 98
 
1.0%
2 78
 
0.8%
6 61
 
0.6%
2022 26
 
0.3%
o 14
 
0.1%
Other values (8) 30
 
0.3%

긴급
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9804 
2023
 
55
2022
 
30
B
 
25
2025
 
24
Other values (5)
 
62

Length

Max length4
Median length4
Mean length3.9856
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9804
98.0%
2023 55
 
0.5%
2022 30
 
0.3%
B 25
 
0.2%
2025 24
 
0.2%
2026 24
 
0.2%
A 20
 
0.2%
2024 15
 
0.1%
5 2
 
< 0.1%
O 1
 
< 0.1%

Length

2024-01-10T08:07:27.647459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:07:27.761630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9804
98.0%
2023 55
 
0.5%
2022 30
 
0.3%
b 25
 
0.2%
2025 24
 
0.2%
2026 24
 
0.2%
a 20
 
0.2%
2024 15
 
0.1%
5 2
 
< 0.1%
o 1
 
< 0.1%

보전
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9964 
2025
 
11
2024
 
9
2022
 
8
2026
 
4
Other values (2)
 
4

Length

Max length4
Median length4
Mean length3.9994
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9964
99.6%
2025 11
 
0.1%
2024 9
 
0.1%
2022 8
 
0.1%
2026 4
 
< 0.1%
2023 2
 
< 0.1%
A 2
 
< 0.1%

Length

2024-01-10T08:07:27.890226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:07:27.991426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9964
99.6%
2025 11
 
0.1%
2024 9
 
0.1%
2022 8
 
0.1%
2026 4
 
< 0.1%
2023 2
 
< 0.1%
a 2
 
< 0.1%

경제
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9998 
2022
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9998
> 99.9%
2022 2
 
< 0.1%

Length

2024-01-10T08:07:28.100033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:07:28.186354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9998
> 99.9%
2022 2
 
< 0.1%

목표
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

관리연도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

번호행정동명시군구명법정읍면동명법정리명좌표명조사일자(YYYY-MM-DD)조사자명대분류생태계교란생물명서식지유형상세주소조사지역명GPS좌표위도경도토지면적개별수밀도동반외래종명비고분포시군서식지공원거리문화재거리분포규모분포밀도분포유형방제전문가합계등급긴급보전경제목표관리연도
11151116천안시동남구수신면발산리B3112020-10-10장한이1_식물환삼덩굴숲 가장자리천안시 동남구 수신면 발산리 산 4-1N36 43 08.6 E127 18 22.536.71905556127.3062513000650005돼지풀 미국가막사리 미국쑥부쟁이 미국자리공 소리쟁이 아까시나무0120031108-332<NA><NA><NA><NA><NA>
30863087서산시부석면강당리C0062020-10-25장한이 안진성1_식물환삼덩굴도로 및 경계지역서산시 부석면 강당리 465-19N36 39 04.9 E126 24 30.236.65866667126.396333390100011미국가막사리 아까시나무0120001307-304<NA><NA><NA><NA><NA><NA>
19221923서산시지곡면대요리A1732020-10-16장한이 김지선1_식물가시박하천(유수)서산시 지곡면 대요리 1123N36 54 33.7 E126 27 37.536.8975126.4618333100200020<NA>01300122211III416<NA><NA><NA><NA><NA><NA>
26232624서산시잠홍동A3682020-10-17나혜련1_식물환삼덩굴습지(정수)서산시 잠홍동 335-17N36 46 56.7 E126 28 46.236.79086111126.4864722250090004서양민들레 울산도깨비바늘 큰김의털 큰도꼬마리 토끼풀0130021209-423<NA><NA><NA><NA><NA><NA><NA>
899900천안시서북구성거읍석교리B1002020-10-08나혜련1_식물환삼덩굴하천(유수)천안시 서북구 성거읍 석교리 251-3N36 51 43.9 E127 11 07.636.86219444127.18544441200100008달맞이꽃 둥근잎유홍초 망초 붉은서나물 유럽점나도나물 큰개불알풀01301212010IV433<NA><NA><NA><NA><NA>
1240312404논산시부적면신교리F2352021-07-08권희정 홍숙윤2_곤충미국선녀벌레숲 가장자리논산시 부적면 신교리 산 4-1N36 11 54.1 E127 8 41.636.19836111127.144888925301<NA>0120011117-313<NA><NA><NA><NA><NA><NA>
1145211453논산시연무읍소룡리F3982021-07-10권희정 김효진1_식물환삼덩굴도로 및 경계지역논산시 연무읍 소룡리 220-3N36 06 10.8 E127 08 10.436.103127.13622222501301가는털비름 망초0120011308-314<NA><NA><NA><NA><NA><NA>
1045110452금산군부리면방우리F5022020-10-29권희정 홍숙윤1_식물미국쑥부쟁이도로 및 경계지역금산군 부리면 방우리 99N36 01 40.5 E127 37 27.436.02791667127.624277820804<NA>0120001318-305<NA><NA><NA><NA><NA><NA>
63146315서천군마서면한성리E2432020-11-14유진수1_식물환삼덩굴도로 및 경계지역서천군 마서면 한성리 36N36 05 30.4 E126 39 59.536.07155556126.65330562403001소리쟁이 족제비싸리0120011308-314<NA><NA><NA><NA><NA><NA>
1390113902서천군시초면후암리(2019년)(정옥식 장하라)3_양서류황소개구리묘지서천군 시초면 후암리N36 8 25 E126 45 5336.14027778126.7647222<NA><NA>11100312211III335<NA><NA><NA><NA><NA><NA><NA><NA><NA>
번호행정동명시군구명법정읍면동명법정리명좌표명조사일자(YYYY-MM-DD)조사자명대분류생태계교란생물명서식지유형상세주소조사지역명GPS좌표위도경도토지면적개별수밀도동반외래종명비고분포시군서식지공원거리문화재거리분포규모분포밀도분포유형방제전문가합계등급긴급보전경제목표관리연도
67686769예산군대술면송석리B3372021-06-22신규형 유태욱2_곤충미국선녀벌레습지(정수)예산군 대술면 송석리 92-1N36 41 15.3 E126 56 48.636.68758333126.94683331502001기생초 덩굴장미 분홍낮달맞이꽃01300212110IV424<NA><NA><NA><NA><NA><NA>
74257426아산시염치읍곡교리B1632021-06-22한병우1_식물가시박하천(유수)아산시 염치읍 곡교리 34-15N36 48 21.6 E126 59 04.136.806126.9844722402005<NA>0130001229-405<NA><NA><NA><NA><NA><NA>
21782179당진시고대면장항리A1032020-10-15김미옥 최인재1_식물가시박하천(유수)당진시 고대면 장항리 1262N36 57 50.1 E126 35 24.836.94969444126.590111124703환삼덩굴0130001229-405<NA><NA><NA><NA><NA><NA>
66686669예산군고덕면상궁리A4822021-06-24강경숙1_식물가시박하천(유수)예산군 고덕면 상궁리 1155N36 44 54.8 E126 45 30.436.74855556126.7584444541503개망초 큰도꼬마리0130001229-405<NA><NA><NA><NA><NA><NA>
43004301공주시우성면안양리D2062020-10-31최미숙1_식물환삼덩굴습지(정수)공주시 우성면 안양리 25N36 26 51.4 E127 00 31.636.44766667127.00877782075038미국가막사리 울산도깨비바늘 족제비싸리01302022010IV424<NA><NA><NA><NA><NA><NA>
18041805서산시팔봉면흑석리A2632020-10-16강승일 김양숙1_식물환삼덩굴도로 및 경계지역서산시 팔봉면 흑석리 770N36 50 09.5 E126 22 50.836.84216667126.37363894001000025가시상추 망초0120012309-315<NA><NA><NA><NA><NA><NA>
64926493당진시합덕읍신흥리A3842021-06-22강경숙1_식물가시상추도로 및 경계지역당진시 합덕읍 신흥리 204-7N36 47 27.5 E126 49 41.636.79097222126.8282222133소리쟁이1120001319-405<NA><NA><NA><NA><NA><NA>
21572158당진시정미면하성리A2372020-10-17장정자 김주영1_식물환삼덩굴경작지당진시 정미면 하성리 232-3N36 51 36.7 E126 32 40.136.85305556126.5297004201<NA>0110011206-213<NA><NA><NA><NA><NA><NA>
147148천안시서북구입장면시장리B0792020-09-25강경숙 김양숙1_식물가시박공터천안시 서북구 입장면 시장리 228-2N36 53 11.3 E127 13 53.536.88647222127.231527880100망초 아까시나무 환삼덩굴0120001329-306<NA><NA><NA><NA><NA>
14611462아산시둔포면염작리B0322020-10-10김유미 김세령1_식물미국쑥부쟁이초지아산시 둔포면 염작리 88-4N36 54 21.6 E127 04 31.436.906127.075388975010001개망초 망초 미국가막사리 소리쟁이 환삼덩굴0110011217-214<NA><NA><NA><NA><NA><NA>