Overview

Dataset statistics

Number of variables12
Number of observations90
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory102.5 B

Variable types

Numeric5
Text4
Categorical3

Dataset

Description샘플 데이터
Author한국해양과학기술원
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=b3c15920-5988-11ec-a202-0b2a0a987ad6

Alerts

위치(좌표계WGS84)위도도 is highly overall correlated with 데이터건수 and 2 other fieldsHigh correlation
위치(좌표계WGS84)위도도분초 is highly overall correlated with 데이터건수 and 2 other fieldsHigh correlation
위치(좌표계WGS84)위도도분 is highly overall correlated with 데이터건수 and 2 other fieldsHigh correlation
데이터건수 is highly overall correlated with 함량(%)모래 and 4 other fieldsHigh correlation
함량(%)모래 is highly overall correlated with 데이터건수 and 2 other fieldsHigh correlation
함량(%)실트 is highly overall correlated with 함량(%)모래 and 1 other fieldsHigh correlation
함량(%)점토 is highly overall correlated with 데이터건수 and 2 other fieldsHigh correlation
데이터건수 has unique valuesUnique
관리번호 has unique valuesUnique
함량(%)실트 has unique valuesUnique
함량(%)자갈 has 26 (28.9%) zerosZeros

Reproduction

Analysis started2023-12-10 10:55:20.806722
Analysis finished2023-12-10 10:55:29.827347
Duration9.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

데이터건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean160.5
Minimum116
Maximum205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-10T19:55:29.972067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum116
5-th percentile120.45
Q1138.25
median160.5
Q3182.75
95-th percentile200.55
Maximum205
Range89
Interquartile range (IQR)44.5

Descriptive statistics

Standard deviation26.124701
Coefficient of variation (CV)0.16277072
Kurtosis-1.2
Mean160.5
Median Absolute Deviation (MAD)22.5
Skewness0
Sum14445
Variance682.5
MonotonicityStrictly increasing
2023-12-10T19:55:30.247863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
116 1
 
1.1%
184 1
 
1.1%
182 1
 
1.1%
181 1
 
1.1%
180 1
 
1.1%
179 1
 
1.1%
178 1
 
1.1%
177 1
 
1.1%
176 1
 
1.1%
175 1
 
1.1%
Other values (80) 80
88.9%
ValueCountFrequency (%)
116 1
1.1%
117 1
1.1%
118 1
1.1%
119 1
1.1%
120 1
1.1%
121 1
1.1%
122 1
1.1%
123 1
1.1%
124 1
1.1%
125 1
1.1%
ValueCountFrequency (%)
205 1
1.1%
204 1
1.1%
203 1
1.1%
202 1
1.1%
201 1
1.1%
200 1
1.1%
199 1
1.1%
198 1
1.1%
197 1
1.1%
196 1
1.1%

관리번호
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-10T19:55:31.030528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9
Min length2

Characters and Unicode

Total characters261
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)100.0%

Sample

1st rowN1
2nd rowN2
3rd rowN3
4th rowN4
5th rowN5
ValueCountFrequency (%)
n1 1
 
1.1%
n67 1
 
1.1%
n65 1
 
1.1%
n64 1
 
1.1%
n63 1
 
1.1%
n62 1
 
1.1%
n61 1
 
1.1%
n60 1
 
1.1%
n59 1
 
1.1%
n58 1
 
1.1%
Other values (80) 80
88.9%
2023-12-10T19:55:31.947410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 90
34.5%
1 19
 
7.3%
2 19
 
7.3%
4 19
 
7.3%
5 19
 
7.3%
6 19
 
7.3%
7 19
 
7.3%
8 19
 
7.3%
3 19
 
7.3%
9 10
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 171
65.5%
Uppercase Letter 90
34.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
11.1%
2 19
11.1%
4 19
11.1%
5 19
11.1%
6 19
11.1%
7 19
11.1%
8 19
11.1%
3 19
11.1%
9 10
5.8%
0 9
5.3%
Uppercase Letter
ValueCountFrequency (%)
N 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 171
65.5%
Latin 90
34.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
11.1%
2 19
11.1%
4 19
11.1%
5 19
11.1%
6 19
11.1%
7 19
11.1%
8 19
11.1%
3 19
11.1%
9 10
5.8%
0 9
5.3%
Latin
ValueCountFrequency (%)
N 90
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 261
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 90
34.5%
1 19
 
7.3%
2 19
 
7.3%
4 19
 
7.3%
5 19
 
7.3%
6 19
 
7.3%
7 19
 
7.3%
8 19
 
7.3%
3 19
 
7.3%
9 10
 
3.8%

위치(좌표계WGS84)위도도
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
N 35.036667°
12 
N 35.075000°
11 
N 35.046667°
11 
N 35.058333°
8 
N 35.065000°
6 
Other values (30)
42 

Length

Max length12
Median length12
Mean length11.988889
Min length11

Unique

Unique23 ?
Unique (%)25.6%

Sample

1st rowN 35.135167°
2nd rowN 35.135167°
3rd rowN 35.125000°
4th rowN 35.116667°
5th rowN 35.116667°

Common Values

ValueCountFrequency (%)
N 35.036667° 12
13.3%
N 35.075000° 11
12.2%
N 35.046667° 11
12.2%
N 35.058333° 8
 
8.9%
N 35.065000° 6
 
6.7%
N 35.080000° 5
 
5.6%
N 35.080833° 3
 
3.3%
N 35.088333° 3
 
3.3%
N 35.116667° 2
 
2.2%
N 35.111667° 2
 
2.2%
Other values (25) 27
30.0%

Length

2023-12-10T19:55:32.210659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
n 90
50.0%
35.036667° 12
 
6.7%
35.075000° 11
 
6.1%
35.046667° 11
 
6.1%
35.058333° 8
 
4.4%
35.065000° 6
 
3.3%
35.080000° 5
 
2.8%
35.080833° 3
 
1.7%
35.088333° 3
 
1.7%
35.095000° 2
 
1.1%
Other values (26) 29
 
16.1%

위치(좌표계WGS84)경도도
Text

Distinct52
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-10T19:55:32.666598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.988889
Min length12

Characters and Unicode

Total characters1169
Distinct characters14
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

Unique33 ?
Unique (%)36.7%

Sample

1st rowE 128.957217°
2nd rowE 128.961033°
3rd rowE 128.953333°
4th rowE 128.941667°
5th rowE 128.954167°
ValueCountFrequency (%)
e 90
50.0%
128.891667° 7
 
3.9%
128.861667° 5
 
2.8%
128.950000° 5
 
2.8%
128.901667° 4
 
2.2%
128.873333° 4
 
2.2%
128.913333° 3
 
1.7%
128.925000° 3
 
1.7%
128.850000° 3
 
1.7%
128.883333° 3
 
1.7%
Other values (43) 53
29.4%
2023-12-10T19:55:33.359895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 149
12.7%
1 134
11.5%
2 103
8.8%
3 96
8.2%
E 90
7.7%
90
7.7%
. 90
7.7%
° 89
7.6%
0 86
7.4%
6 80
6.8%
Other values (4) 162
13.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 810
69.3%
Uppercase Letter 90
 
7.7%
Space Separator 90
 
7.7%
Other Punctuation 90
 
7.7%
Other Symbol 89
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 149
18.4%
1 134
16.5%
2 103
12.7%
3 96
11.9%
0 86
10.6%
6 80
9.9%
9 70
8.6%
7 47
 
5.8%
5 31
 
3.8%
4 14
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
E 90
100.0%
Space Separator
ValueCountFrequency (%)
90
100.0%
Other Punctuation
ValueCountFrequency (%)
. 90
100.0%
Other Symbol
ValueCountFrequency (%)
° 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1079
92.3%
Latin 90
 
7.7%

Most frequent character per script

Common
ValueCountFrequency (%)
8 149
13.8%
1 134
12.4%
2 103
9.5%
3 96
8.9%
90
8.3%
. 90
8.3%
° 89
8.2%
0 86
8.0%
6 80
7.4%
9 70
6.5%
Other values (3) 92
8.5%
Latin
ValueCountFrequency (%)
E 90
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1080
92.4%
None 89
 
7.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 149
13.8%
1 134
12.4%
2 103
9.5%
3 96
8.9%
E 90
8.3%
90
8.3%
. 90
8.3%
0 86
8.0%
6 80
7.4%
9 70
6.5%
Other values (3) 92
8.5%
None
ValueCountFrequency (%)
° 89
100.0%

위치(좌표계WGS84)위도도분
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
N 35° 2.200'
12 
N 35° 4.500'
11 
N 35° 2.800'
11 
N 35° 3.500'
8 
N 35° 3.900'
6 
Other values (30)
42 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique23 ?
Unique (%)25.6%

Sample

1st rowN 35° 8.110'
2nd rowN 35° 8.110'
3rd rowN 35° 7.500'
4th rowN 35° 7.000'
5th rowN 35° 7.000'

Common Values

ValueCountFrequency (%)
N 35° 2.200' 12
13.3%
N 35° 4.500' 11
12.2%
N 35° 2.800' 11
12.2%
N 35° 3.500' 8
 
8.9%
N 35° 3.900' 6
 
6.7%
N 35° 4.800' 5
 
5.6%
N 35° 4.850' 3
 
3.3%
N 35° 5.300' 3
 
3.3%
N 35° 7.000' 2
 
2.2%
N 35° 6.700' 2
 
2.2%
Other values (25) 27
30.0%

Length

2023-12-10T19:55:33.637753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
n 90
33.3%
35° 90
33.3%
2.200 12
 
4.4%
4.500 11
 
4.1%
2.800 11
 
4.1%
3.500 8
 
3.0%
3.900 6
 
2.2%
4.800 5
 
1.9%
4.850 3
 
1.1%
5.300 3
 
1.1%
Other values (27) 31
 
11.5%

위치(좌표계WGS84)경도도분
Text

Distinct51
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-10T19:55:34.024739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters1260
Distinct characters15
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

Unique31 ?
Unique (%)34.4%

Sample

1st rowE 128° 57.433'
2nd rowE 128° 57.662'
3rd rowE 128° 57.200'
4th rowE 128° 56.500'
5th rowE 128° 57.250'
ValueCountFrequency (%)
e 90
33.3%
128° 90
33.3%
53.500 7
 
2.6%
51.700 5
 
1.9%
57.000 5
 
1.9%
54.100 4
 
1.5%
52.400 4
 
1.5%
53.000 3
 
1.1%
55.500 3
 
1.1%
54.800 3
 
1.1%
Other values (43) 56
20.7%
2023-12-10T19:55:34.695886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
14.3%
0 159
12.6%
5 123
9.8%
1 114
9.0%
2 105
8.3%
8 98
7.8%
E 90
7.1%
° 90
7.1%
. 90
7.1%
' 90
7.1%
Other values (5) 121
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 720
57.1%
Space Separator 180
 
14.3%
Other Punctuation 180
 
14.3%
Uppercase Letter 90
 
7.1%
Other Symbol 90
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 159
22.1%
5 123
17.1%
1 114
15.8%
2 105
14.6%
8 98
13.6%
3 31
 
4.3%
7 29
 
4.0%
4 26
 
3.6%
6 23
 
3.2%
9 12
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 90
50.0%
' 90
50.0%
Space Separator
ValueCountFrequency (%)
180
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 90
100.0%
Other Symbol
ValueCountFrequency (%)
° 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1170
92.9%
Latin 90
 
7.1%

Most frequent character per script

Common
ValueCountFrequency (%)
180
15.4%
0 159
13.6%
5 123
10.5%
1 114
9.7%
2 105
9.0%
8 98
8.4%
° 90
7.7%
. 90
7.7%
' 90
7.7%
3 31
 
2.6%
Other values (4) 90
7.7%
Latin
ValueCountFrequency (%)
E 90
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1170
92.9%
None 90
 
7.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
15.4%
0 159
13.6%
5 123
10.5%
1 114
9.7%
2 105
9.0%
8 98
8.4%
E 90
7.7%
. 90
7.7%
' 90
7.7%
3 31
 
2.6%
Other values (4) 90
7.7%
None
ValueCountFrequency (%)
° 90
100.0%

위치(좌표계WGS84)위도도분초
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
N 35° 2' 48.000"
11 
N 35° 2' 12.000"
11 
N 35° 4' 30.000"
11 
N 35° 3' 30.000"
8 
N 35° 3' 54.000"
6 
Other values (31)
43 

Length

Max length17
Median length16
Mean length15.922222
Min length15

Unique

Unique24 ?
Unique (%)26.7%

Sample

1st rowN 35° 8' 6.600"
2nd rowN 35° 8' 6.600"
3rd rowN 35° 7' 30.000"
4th rowN 35° 7' 0.000"
5th rowN 35° 7' 0.000"

Common Values

ValueCountFrequency (%)
N 35° 2' 48.000" 11
 
12.2%
N 35° 2' 12.000" 11
 
12.2%
N 35° 4' 30.000" 11
 
12.2%
N 35° 3' 30.000" 8
 
8.9%
N 35° 3' 54.000" 6
 
6.7%
N 35° 4' 48.000" 5
 
5.6%
N 35° 4' 51.000" 3
 
3.3%
N 35° 5' 18.000" 3
 
3.3%
N 35° 6' 42.000" 2
 
2.2%
N 35° 7' 0.000" 2
 
2.2%
Other values (26) 28
31.1%

Length

2023-12-10T19:55:35.111376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
n 90
25.0%
35° 90
25.0%
2 25
 
6.9%
4 22
 
6.1%
30.000 21
 
5.8%
3 21
 
5.8%
48.000 18
 
5.0%
12.000 12
 
3.3%
5 11
 
3.1%
54.000 6
 
1.7%
Other values (24) 44
12.2%

위치(좌표계WGS84)경도도분초
Text

Distinct53
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-10T19:55:35.538439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length17.777778
Min length16

Characters and Unicode

Total characters1600
Distinct characters16
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

Unique34 ?
Unique (%)37.8%

Sample

1st rowE 128° 57' 25.980"
2nd rowE 128° 57' 39.720"
3rd rowE 128° 57' 12.000"
4th rowE 128° 56' 30.000"
5th rowE 128° 57' 15.000"
ValueCountFrequency (%)
128° 90
25.1%
e 89
24.8%
53 17
 
4.7%
56 15
 
4.2%
57 14
 
3.9%
54 13
 
3.6%
0.000 13
 
3.6%
55 11
 
3.1%
51 11
 
3.1%
30.000 11
 
3.1%
Other values (30) 75
20.9%
2023-12-10T19:55:36.143716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
271
16.9%
0 264
16.5%
2 126
7.9%
5 121
7.6%
1 119
7.4%
8 106
 
6.6%
° 90
 
5.6%
' 90
 
5.6%
. 90
 
5.6%
" 90
 
5.6%
Other values (6) 233
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 880
55.0%
Space Separator 271
 
16.9%
Other Punctuation 270
 
16.9%
Other Symbol 90
 
5.6%
Uppercase Letter 89
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 264
30.0%
2 126
14.3%
5 121
13.8%
1 119
13.5%
8 106
12.0%
4 54
 
6.1%
3 36
 
4.1%
6 30
 
3.4%
7 16
 
1.8%
9 8
 
0.9%
Other Punctuation
ValueCountFrequency (%)
' 90
33.3%
. 90
33.3%
" 90
33.3%
Space Separator
ValueCountFrequency (%)
271
100.0%
Other Symbol
ValueCountFrequency (%)
° 90
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1511
94.4%
Latin 89
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
271
17.9%
0 264
17.5%
2 126
8.3%
5 121
8.0%
1 119
7.9%
8 106
 
7.0%
° 90
 
6.0%
' 90
 
6.0%
. 90
 
6.0%
" 90
 
6.0%
Other values (5) 144
9.5%
Latin
ValueCountFrequency (%)
E 89
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1510
94.4%
None 90
 
5.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
271
17.9%
0 264
17.5%
2 126
8.3%
5 121
8.0%
1 119
7.9%
8 106
 
7.0%
' 90
 
6.0%
. 90
 
6.0%
" 90
 
6.0%
E 89
 
5.9%
Other values (5) 144
9.5%
None
ValueCountFrequency (%)
° 90
100.0%

함량(%)자갈
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10366667
Minimum0
Maximum0.72
Zeros26
Zeros (%)28.9%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-10T19:55:36.374388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.06
Q30.1475
95-th percentile0.35
Maximum0.72
Range0.72
Interquartile range (IQR)0.1475

Descriptive statistics

Standard deviation0.13250779
Coefficient of variation (CV)1.2782102
Kurtosis7.5052844
Mean0.10366667
Median Absolute Deviation (MAD)0.06
Skewness2.4099571
Sum9.33
Variance0.017558315
MonotonicityNot monotonic
2023-12-10T19:55:36.636918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 26
28.9%
0.04 8
 
8.9%
0.05 8
 
8.9%
0.09 5
 
5.6%
0.1 3
 
3.3%
0.35 3
 
3.3%
0.19 3
 
3.3%
0.06 3
 
3.3%
0.08 3
 
3.3%
0.17 3
 
3.3%
Other values (18) 25
27.8%
ValueCountFrequency (%)
0.0 26
28.9%
0.03 2
 
2.2%
0.04 8
 
8.9%
0.05 8
 
8.9%
0.06 3
 
3.3%
0.07 2
 
2.2%
0.08 3
 
3.3%
0.09 5
 
5.6%
0.1 3
 
3.3%
0.11 2
 
2.2%
ValueCountFrequency (%)
0.72 1
 
1.1%
0.66 1
 
1.1%
0.43 1
 
1.1%
0.35 3
3.3%
0.33 1
 
1.1%
0.3 1
 
1.1%
0.29 1
 
1.1%
0.25 1
 
1.1%
0.22 1
 
1.1%
0.2 1
 
1.1%

함량(%)모래
Real number (ℝ)

HIGH CORRELATION 

Distinct87
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.097889
Minimum1.65
Maximum98.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-10T19:55:37.328836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.65
5-th percentile7.9
Q158.585
median84.365
Q392.49
95-th percentile96.363
Maximum98.13
Range96.48
Interquartile range (IQR)33.905

Descriptive statistics

Standard deviation29.048593
Coefficient of variation (CV)0.4085718
Kurtosis0.088014956
Mean71.097889
Median Absolute Deviation (MAD)10.34
Skewness-1.1946704
Sum6398.81
Variance843.82074
MonotonicityNot monotonic
2023-12-10T19:55:37.611463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.9 2
 
2.2%
80.96 2
 
2.2%
95.6 2
 
2.2%
85.98 1
 
1.1%
94.51 1
 
1.1%
19.9 1
 
1.1%
92.61 1
 
1.1%
85.31 1
 
1.1%
95.78 1
 
1.1%
92.43 1
 
1.1%
Other values (77) 77
85.6%
ValueCountFrequency (%)
1.65 1
1.1%
3.75 1
1.1%
4.12 1
1.1%
6.28 1
1.1%
7.9 2
2.2%
11.27 1
1.1%
15.02 1
1.1%
17.92 1
1.1%
19.83 1
1.1%
19.9 1
1.1%
ValueCountFrequency (%)
98.13 1
1.1%
97.89 1
1.1%
97.87 1
1.1%
96.87 1
1.1%
96.84 1
1.1%
95.78 1
1.1%
95.64 1
1.1%
95.6 2
2.2%
95.3 1
1.1%
95.28 1
1.1%

함량(%)실트
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.509444
Minimum0.69
Maximum49.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-10T19:55:37.858671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.69
5-th percentile1.6275
Q13.155
median7.235
Q321.01
95-th percentile39.343
Maximum49.07
Range48.38
Interquartile range (IQR)17.855

Descriptive statistics

Standard deviation13.353233
Coefficient of variation (CV)0.98843689
Kurtosis-0.11483591
Mean13.509444
Median Absolute Deviation (MAD)4.725
Skewness1.0966596
Sum1215.85
Variance178.30884
MonotonicityNot monotonic
2023-12-10T19:55:38.143598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.96 1
 
1.1%
2.71 1
 
1.1%
5.0 1
 
1.1%
6.21 1
 
1.1%
49.07 1
 
1.1%
3.05 1
 
1.1%
7.26 1
 
1.1%
1.82 1
 
1.1%
3.3 1
 
1.1%
2.29 1
 
1.1%
Other values (80) 80
88.9%
ValueCountFrequency (%)
0.69 1
1.1%
1.01 1
1.1%
1.1 1
1.1%
1.17 1
1.1%
1.47 1
1.1%
1.82 1
1.1%
1.93 1
1.1%
2.1 1
1.1%
2.15 1
1.1%
2.18 1
1.1%
ValueCountFrequency (%)
49.07 1
1.1%
44.44 1
1.1%
43.57 1
1.1%
41.2 1
1.1%
39.46 1
1.1%
39.2 1
1.1%
39.13 1
1.1%
39.06 1
1.1%
38.32 1
1.1%
36.32 1
1.1%

함량(%)점토
Real number (ℝ)

HIGH CORRELATION 

Distinct88
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.290222
Minimum0.96
Maximum64.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-10T19:55:38.418526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.96
5-th percentile1.9675
Q14.255
median8.215
Q319.42
95-th percentile53.711
Maximum64.12
Range63.16
Interquartile range (IQR)15.165

Descriptive statistics

Standard deviation16.45961
Coefficient of variation (CV)1.0764795
Kurtosis1.1869695
Mean15.290222
Median Absolute Deviation (MAD)5.365
Skewness1.5037085
Sum1376.12
Variance270.91876
MonotonicityNot monotonic
2023-12-10T19:55:38.821350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.3 2
 
2.2%
4.24 2
 
2.2%
3.17 1
 
1.1%
4.02 1
 
1.1%
6.35 1
 
1.1%
30.98 1
 
1.1%
7.27 1
 
1.1%
2.41 1
 
1.1%
3.66 1
 
1.1%
4.71 1
 
1.1%
Other values (78) 78
86.7%
ValueCountFrequency (%)
0.96 1
1.1%
1.05 1
1.1%
1.18 1
1.1%
1.67 1
1.1%
1.9 1
1.1%
2.05 1
1.1%
2.11 1
1.1%
2.17 1
1.1%
2.22 1
1.1%
2.3 1
1.1%
ValueCountFrequency (%)
64.12 1
1.1%
58.67 1
1.1%
57.13 1
1.1%
55.69 1
1.1%
54.26 1
1.1%
53.04 1
1.1%
51.44 1
1.1%
49.53 1
1.1%
49.2 1
1.1%
43.71 1
1.1%

Interactions

2023-12-10T19:55:28.232618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:25.160117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:25.926739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:26.753879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:27.465824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:28.385064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:25.333843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:26.083149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:26.887938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:27.609464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:28.561527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:25.475324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:26.270360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:27.051614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:27.764460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:28.737801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:25.602203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:26.425707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:27.186585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:27.912460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:28.939994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:25.746906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:26.589950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:27.320769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:55:28.050988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:55:39.030313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터건수관리번호위치(좌표계WGS84)위도도위치(좌표계WGS84)경도도위치(좌표계WGS84)위도도분위치(좌표계WGS84)경도도분위치(좌표계WGS84)위도도분초위치(좌표계WGS84)경도도분초함량(%)자갈함량(%)모래함량(%)실트함량(%)점토
데이터건수1.0001.0000.9600.0000.9600.0000.9560.0000.2940.2540.4780.531
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치(좌표계WGS84)위도도0.9601.0001.0000.9781.0000.9781.0000.9810.5040.8490.6260.803
위치(좌표계WGS84)경도도0.0001.0000.9781.0000.9781.0000.9751.0000.7110.8230.8280.850
위치(좌표계WGS84)위도도분0.9601.0001.0000.9781.0000.9781.0000.9810.5040.8490.6260.803
위치(좌표계WGS84)경도도분0.0001.0000.9781.0000.9781.0000.9761.0000.6900.8320.8340.857
위치(좌표계WGS84)위도도분초0.9561.0001.0000.9751.0000.9761.0000.9780.4590.8620.6670.816
위치(좌표계WGS84)경도도분초0.0001.0000.9811.0000.9811.0000.9781.0000.7820.8020.8040.841
함량(%)자갈0.2941.0000.5040.7110.5040.6900.4590.7821.0000.0000.0000.000
함량(%)모래0.2541.0000.8490.8230.8490.8320.8620.8020.0001.0000.9330.936
함량(%)실트0.4781.0000.6260.8280.6260.8340.6670.8040.0000.9331.0000.911
함량(%)점토0.5311.0000.8030.8500.8030.8570.8160.8410.0000.9360.9111.000
2023-12-10T19:55:39.422126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위치(좌표계WGS84)위도도위치(좌표계WGS84)위도도분초위치(좌표계WGS84)위도도분
위치(좌표계WGS84)위도도1.0000.9911.000
위치(좌표계WGS84)위도도분초0.9911.0000.991
위치(좌표계WGS84)위도도분1.0000.9911.000
2023-12-10T19:55:39.610791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터건수함량(%)자갈함량(%)모래함량(%)실트함량(%)점토위치(좌표계WGS84)위도도위치(좌표계WGS84)위도도분위치(좌표계WGS84)위도도분초
데이터건수1.0000.2770.511-0.472-0.5400.6250.6250.618
함량(%)자갈0.2771.0000.205-0.177-0.2240.1620.1620.152
함량(%)모래0.5110.2051.000-0.988-0.9930.4020.4020.423
함량(%)실트-0.472-0.177-0.9881.0000.9690.2120.2120.239
함량(%)점토-0.540-0.224-0.9930.9691.0000.3480.3480.365
위치(좌표계WGS84)위도도0.6250.1620.4020.2120.3481.0001.0000.991
위치(좌표계WGS84)위도도분0.6250.1620.4020.2120.3481.0001.0000.991
위치(좌표계WGS84)위도도분초0.6180.1520.4230.2390.3650.9910.9911.000

Missing values

2023-12-10T19:55:29.276543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:55:29.670929image/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

데이터건수관리번호위치(좌표계WGS84)위도도위치(좌표계WGS84)경도도위치(좌표계WGS84)위도도분위치(좌표계WGS84)경도도분위치(좌표계WGS84)위도도분초위치(좌표계WGS84)경도도분초함량(%)자갈함량(%)모래함량(%)실트함량(%)점토
0116N1N 35.135167°E 128.957217°N 35° 8.110'E 128° 57.433'N 35° 8' 6.600"E 128° 57' 25.980"0.4385.985.967.63
1117N2N 35.135167°E 128.961033°N 35° 8.110'E 128° 57.662'N 35° 8' 6.600"E 128° 57' 39.720"0.1474.7712.1112.98
2118N3N 35.125000°E 128.953333°N 35° 7.500'E 128° 57.200'N 35° 7' 30.000"E 128° 57' 12.000"0.382.997.219.5
3119N4N 35.116667°E 128.941667°N 35° 7.000'E 128° 56.500'N 35° 7' 0.000"E 128° 56' 30.000"0.07.939.0653.04
4120N5N 35.116667°E 128.954167°N 35° 7.000'E 128° 57.250'N 35° 7' 0.000"E 128° 57' 15.000"0.098.130.691.18
5121N6N 35.111667°E 128.893333°N 35° 6.700'E 128° 53.600'N 35° 6' 42.000"E 128° 53' 36.000"0.7268.6810.6619.94
6122N7N 35.111667°E 128.898333°N 35° 6.700'E 128° 53.900'N 35° 6' 42.000"E 128° 53' 54.000"0.06.2839.4654.26
7123N8N 35.102300°E 128.895833°N 35° 6.138'E 128° 53.750'N 35° 6' 8.280"E 128° 53' 45.000"0.027.5435.8636.6
8124N9N 35.095000°E 128.891667°N 35° 5.700'E 128° 53.500'N 35° 5' 42.000"E 128° 53' 30.000"0.2987.65.097.02
9125N10N 35.095000°E 128.898333°N 35° 5.700'E 128° 53.900'N 35° 5' 42.000"E 128° 53' 54.000"0.037.6133.2229.17
데이터건수관리번호위치(좌표계WGS84)위도도위치(좌표계WGS84)경도도위치(좌표계WGS84)위도도분위치(좌표계WGS84)경도도분위치(좌표계WGS84)위도도분초위치(좌표계WGS84)경도도분초함량(%)자갈함량(%)모래함량(%)실트함량(%)점토
80196N81N 35.036667°E 128.881667°N 35° 2.200'E 128° 52.900'N 35° 2' 12.000"E 128° 52' 54.000"0.3588.386.774.5
81197N82N 35.036667°E 128.891667°N 35° 2.200'E 128° 53.500'N 35° 2' 12.000"E 128° 53' 30.000"0.1878.4211.969.44
82198N83N 35.036667°E 128.901667°N 35° 2.200'E 128° 54.100'N 35° 2' 12.000"E 128° 54' 6.000"0.0647.1927.2425.51
83199N84N 35.036667°E 128.911667°N 35° 2.200'E 128° 54.700'N 35° 2' 12.000"E 128° 54' 42.000"0.1992.512.944.36
84200N85N 35.036667°E 128.921667°N 35° 2.200'E 128° 55.300'N 35° 2' 12.000"E 128° 55' 18.000"0.0495.62.152.22
85201N86N 35.036667°E 128.931667°N 35° 2.200'E 128° 55.900'N 35° 2' 12.000"E 128° 55' 54.000"0.192.92.774.23
86202N87N 35.036667°E 128.940000°N 35° 2.200'E 128° 56.400'N 35° 2' 12.000"E 128° 56' 24.000"0.3590.463.735.46
87203N88N 35.036667°E 128.950000°N 35° 2.200'E 128° 57.000'N 35° 2' 12.000"E 128° 57' 0.000"0.1792.783.23.85
88204N89N 35.036667°E 128.960000°N 35° 2.200'E 128° 57.600'N 35° 2' 12.000"E 128° 57' 36.000"0.1990.384.165.27
89205N90N 35.040900°E 128.963650°N 35° 2.454'E 128° 57.819'N 35° 2' 27.240"E 128° 57' 49.140"0.1795.61.932.3