Overview

Dataset statistics

Number of variables6
Number of observations319
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory50.4 B

Variable types

Categorical2
Numeric2
Text2

Dataset

Description경상남도 내 습지 현황으로, 습지의 구분, 습지명, 습지유형, 위치(주소), 면적(제곱미터)에 관한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3084107/fileData.do

Alerts

습지유형 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 구분High correlation
연번 has unique valuesUnique
습지명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:00:39.684554
Analysis finished2023-12-12 14:00:40.646795
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
내륙습지
272 
연안습지
47 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
내륙습지 272
85.3%
연안습지 47
 
14.7%

Length

2023-12-12T23:00:40.712219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:00:40.819915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내륙습지 272
85.3%
연안습지 47
 
14.7%

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct319
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean160
Minimum1
Maximum319
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T23:00:40.958674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.9
Q180.5
median160
Q3239.5
95-th percentile303.1
Maximum319
Range318
Interquartile range (IQR)159

Descriptive statistics

Standard deviation92.231593
Coefficient of variation (CV)0.57644745
Kurtosis-1.2
Mean160
Median Absolute Deviation (MAD)80
Skewness0
Sum51040
Variance8506.6667
MonotonicityStrictly increasing
2023-12-12T23:00:41.107625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
2 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
215 1
 
0.3%
214 1
 
0.3%
213 1
 
0.3%
212 1
 
0.3%
Other values (309) 309
96.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
319 1
0.3%
318 1
0.3%
317 1
0.3%
316 1
0.3%
315 1
0.3%
314 1
0.3%
313 1
0.3%
312 1
0.3%
311 1
0.3%
310 1
0.3%

습지명
Text

UNIQUE 

Distinct319
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T23:00:41.449167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.5517241
Min length2

Characters and Unicode

Total characters1452
Distinct characters214
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique319 ?
Unique (%)100.0%

Sample

1st row산남저수지
2nd row정병산습지
3rd row주남저수지
4th row동판저수지
5th row사파정저수지
ValueCountFrequency (%)
하도습지 10
 
2.9%
묵논습지 4
 
1.2%
보습지 4
 
1.2%
우각호습지 2
 
0.6%
하구염습지 2
 
0.6%
월평리 2
 
0.6%
인공호습지 2
 
0.6%
신월리 2
 
0.6%
두곡습지 1
 
0.3%
하동습지 1
 
0.3%
Other values (317) 317
91.4%
2023-12-12T23:00:41.949239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 196
 
13.5%
습 161
 
11.1%
늪 88
 
6.1%
리 53
 
3.7%
30
 
2.1%
하 25
 
1.7%
산 25
 
1.7%
수 23
 
1.6%
대 22
 
1.5%
( 21
 
1.4%
Other values (204) 808
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1362
93.8%
Space Separator 30
 
2.1%
Open Punctuation 21
 
1.4%
Close Punctuation 21
 
1.4%
Decimal Number 18
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 196
 
14.4%
습 161
 
11.8%
늪 88
 
6.5%
리 53
 
3.9%
하 25
 
1.8%
산 25
 
1.8%
수 23
 
1.7%
대 22
 
1.6%
천 20
 
1.5%
도 19
 
1.4%
Other values (197) 730
53.6%
Decimal Number
ValueCountFrequency (%)
2 8
44.4%
1 6
33.3%
3 3
 
16.7%
4 1
 
5.6%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1362
93.8%
Common 90
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 196
 
14.4%
습 161
 
11.8%
늪 88
 
6.5%
리 53
 
3.9%
하 25
 
1.8%
산 25
 
1.8%
수 23
 
1.7%
대 22
 
1.6%
천 20
 
1.5%
도 19
 
1.4%
Other values (197) 730
53.6%
Common
ValueCountFrequency (%)
30
33.3%
( 21
23.3%
) 21
23.3%
2 8
 
8.9%
1 6
 
6.7%
3 3
 
3.3%
4 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1362
93.8%
ASCII 90
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 196
 
14.4%
습 161
 
11.8%
늪 88
 
6.5%
리 53
 
3.9%
하 25
 
1.8%
산 25
 
1.8%
수 23
 
1.7%
대 22
 
1.6%
천 20
 
1.5%
도 19
 
1.4%
Other values (197) 730
53.6%
ASCII
ValueCountFrequency (%)
30
33.3%
( 21
23.3%
) 21
23.3%
2 8
 
8.9%
1 6
 
6.7%
3 3
 
3.3%
4 1
 
1.1%

습지유형
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
하도습지
103 
담수호습지
61 
연안습지
47 
소택지
24 
인공호습지
23 
Other values (12)
61 

Length

Max length6
Median length4
Mean length4.2789969
Min length3

Unique

Unique3 ?
Unique (%)0.9%

Sample

1st row담수호습지
2nd row소택지
3rd row담수호습지
4th row담수호습지
5th row담수호습지

Common Values

ValueCountFrequency (%)
하도습지 103
32.3%
담수호습지 61
19.1%
연안습지 47
14.7%
소택지 24
 
7.5%
인공호습지 23
 
7.2%
간척호습지 13
 
4.1%
배후습지 12
 
3.8%
저층습원 11
 
3.4%
보습지 5
 
1.6%
인공수로습지 4
 
1.3%
Other values (7) 16
 
5.0%

Length

2023-12-12T23:00:42.108458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
하도습지 103
32.3%
담수호습지 61
19.1%
연안습지 47
14.7%
소택지 24
 
7.5%
인공호습지 23
 
7.2%
간척호습지 13
 
4.1%
배후습지 12
 
3.8%
저층습원 11
 
3.4%
보습지 5
 
1.6%
인공수로습지 4
 
1.3%
Other values (7) 16
 
5.0%

위치(주소)
Text

Distinct271
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T23:00:42.462722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length16
Mean length16.410658
Min length12

Characters and Unicode

Total characters5235
Distinct characters196
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

Unique237 ?
Unique (%)74.3%

Sample

1st row경상남도 창원시 동읍 금산리, 죽동리
2nd row경상남도 창원시 동읍 덕산리
3rd row경상남도 창원시 동읍 석산리
4th row경상남도 창원시 동읍 월잠리
5th row경상남도 창원시 성산구 사파정동 30
ValueCountFrequency (%)
경상남도 319
24.5%
함안군 41
 
3.1%
창녕군 29
 
2.2%
양산시 28
 
2.1%
합천군 24
 
1.8%
하동군 24
 
1.8%
진주시 23
 
1.8%
밀양시 20
 
1.5%
사천시 16
 
1.2%
거제시 15
 
1.2%
Other values (409) 765
58.7%
2023-12-12T23:00:43.016176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
985
18.8%
남 367
 
7.0%
상 346
 
6.6%
도 326
 
6.2%
경 321
 
6.1%
리 308
 
5.9%
면 269
 
5.1%
군 191
 
3.6%
시 136
 
2.6%
산 96
 
1.8%
Other values (186) 1890
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4170
79.7%
Space Separator 985
 
18.8%
Decimal Number 63
 
1.2%
Dash Punctuation 7
 
0.1%
Other Punctuation 6
 
0.1%
Uppercase Letter 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 367
 
8.8%
상 346
 
8.3%
도 326
 
7.8%
경 321
 
7.7%
리 308
 
7.4%
면 269
 
6.5%
군 191
 
4.6%
시 136
 
3.3%
산 96
 
2.3%
동 90
 
2.2%
Other values (170) 1720
41.2%
Decimal Number
ValueCountFrequency (%)
1 12
19.0%
2 12
19.0%
8 8
12.7%
3 7
11.1%
9 6
9.5%
7 5
7.9%
6 5
7.9%
0 4
 
6.3%
4 2
 
3.2%
5 2
 
3.2%
Space Separator
ValueCountFrequency (%)
985
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4170
79.7%
Common 1063
 
20.3%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 367
 
8.8%
상 346
 
8.3%
도 326
 
7.8%
경 321
 
7.7%
리 308
 
7.4%
면 269
 
6.5%
군 191
 
4.6%
시 136
 
3.3%
산 96
 
2.3%
동 90
 
2.2%
Other values (170) 1720
41.2%
Common
ValueCountFrequency (%)
985
92.7%
1 12
 
1.1%
2 12
 
1.1%
8 8
 
0.8%
- 7
 
0.7%
3 7
 
0.7%
9 6
 
0.6%
, 6
 
0.6%
7 5
 
0.5%
6 5
 
0.5%
Other values (5) 10
 
0.9%
Latin
ValueCountFrequency (%)
E 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4170
79.7%
ASCII 1065
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
985
92.5%
1 12
 
1.1%
2 12
 
1.1%
8 8
 
0.8%
- 7
 
0.7%
3 7
 
0.7%
9 6
 
0.6%
, 6
 
0.6%
7 5
 
0.5%
6 5
 
0.5%
Other values (6) 12
 
1.1%
Hangul
ValueCountFrequency (%)
남 367
 
8.8%
상 346
 
8.3%
도 326
 
7.8%
경 321
 
7.7%
리 308
 
7.4%
면 269
 
6.5%
군 191
 
4.6%
시 136
 
3.3%
산 96
 
2.3%
동 90
 
2.2%
Other values (170) 1720
41.2%

면적(제곱미터)
Real number (ℝ)

Distinct318
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343497.67
Minimum241
Maximum4778397
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T23:00:43.196409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum241
5-th percentile2013.5
Q118567.5
median98440
Q3333826.5
95-th percentile1575009.6
Maximum4778397
Range4778156
Interquartile range (IQR)315259

Descriptive statistics

Standard deviation663589.42
Coefficient of variation (CV)1.9318601
Kurtosis16.696791
Mean343497.67
Median Absolute Deviation (MAD)92964
Skewness3.7501127
Sum1.0957576 × 108
Variance4.4035092 × 1011
MonotonicityNot monotonic
2023-12-12T23:00:43.380161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
94005 2
 
0.6%
687553 1
 
0.3%
97813 1
 
0.3%
315158 1
 
0.3%
892511 1
 
0.3%
156676 1
 
0.3%
998609 1
 
0.3%
306824 1
 
0.3%
63025 1
 
0.3%
35165 1
 
0.3%
Other values (308) 308
96.6%
ValueCountFrequency (%)
241 1
0.3%
372 1
0.3%
415 1
0.3%
457 1
0.3%
530 1
0.3%
776 1
0.3%
830 1
0.3%
893 1
0.3%
894 1
0.3%
991 1
0.3%
ValueCountFrequency (%)
4778397 1
0.3%
4412492 1
0.3%
3923351 1
0.3%
3748821 1
0.3%
2988884 1
0.3%
2977371 1
0.3%
2741230 1
0.3%
2550806 1
0.3%
2405552 1
0.3%
2212911 1
0.3%

Interactions

2023-12-12T23:00:40.232303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:00:40.013142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:00:40.368757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:00:40.121679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:00:43.484041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분연번습지유형면적(제곱미터)
구분1.0000.9851.0000.425
연번0.9851.0000.7560.175
습지유형1.0000.7561.0000.000
면적(제곱미터)0.4250.1750.0001.000
2023-12-12T23:00:43.872031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
습지유형구분
습지유형1.0000.976
구분0.9761.000
2023-12-12T23:00:43.947232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(제곱미터)구분습지유형
연번1.0000.2180.8810.413
면적(제곱미터)0.2181.0000.3220.000
구분0.8810.3221.0000.976
습지유형0.4130.0000.9761.000

Missing values

2023-12-12T23:00:40.495823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:00:40.605887image/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

구분연번습지명습지유형위치(주소)면적(제곱미터)
0내륙습지1산남저수지담수호습지경상남도 창원시 동읍 금산리, 죽동리687553
1내륙습지2정병산습지소택지경상남도 창원시 동읍 덕산리43055
2내륙습지3주남저수지담수호습지경상남도 창원시 동읍 석산리2741230
3내륙습지4동판저수지담수호습지경상남도 창원시 동읍 월잠리1399400
4내륙습지5사파정저수지담수호습지경상남도 창원시 성산구 사파정동 302343
5내륙습지6모암소류지담수호습지경상남도 창원시 의창구 동읍 신방리 878-35476
6내륙습지7화량리3습지소택지경상남도 창원시 의창구 동읍 화양리 1964128
7내륙습지8화양리2습지인공수로습지경상남도 창원시 의창구 동읍 화양리 2183805
8내륙습지9화양리1습지대체습지경상남도 창원시 의창구 동읍 화양리 684830
9내륙습지10주봉저수지습지인공호습지경상남도 진주시 금곡면 가봉리110017
구분연번습지명습지유형위치(주소)면적(제곱미터)
309연안습지310고현연안습지경상남도 남해군 설천면 진목리1657464
310연안습지311강진만연안습지경상남도 남해군 이동면 초음리2083254
311연안습지312지족해협연안습지경상남도 남해군 삼동면 금송리566484
312연안습지313동대만연안습지경상남도 남해군 창선면 당항리2977371
313연안습지314섬진강하구연안습지경상남도 하동군 금성면 고포리2550806
314연안습지315갈사고포연안습지경상남도 하동군 금성면 갈사리3923351
315연안습지316대송리연안습지경상남도 하동군 금남면 대송리457445
316연안습지317대치리연안습지경상남도 하동군 금남면 중평리517124
317연안습지318중평리연안습지경상남도 하동군 금남면 중평리379564
318연안습지319진교연안습지경상남도 하동군 진교면 술상리1565848