Overview

Dataset statistics

Number of variables29
Number of observations3349
Missing cells208
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory758.9 KiB
Average record size in memory232.0 B

Variable types

Text17
Categorical12

Alerts

soil12 has a high cardinality: 51 distinct valuesHigh cardinality
soil11 is highly imbalanced (59.6%)Imbalance
soil12 is highly imbalanced (60.2%)Imbalance
soil16 is highly imbalanced (59.1%)Imbalance
soil17 is highly imbalanced (55.2%)Imbalance
inspec_deep is highly imbalanced (58.5%)Imbalance
soil19 is highly imbalanced (59.3%)Imbalance
soil20 is highly imbalanced (78.5%)Imbalance
soil21 is highly imbalanced (94.3%)Imbalance
last_load_dttm is highly imbalanced (93.4%)Imbalance

Reproduction

Analysis started2024-04-17 15:47:07.767694
Analysis finished2024-04-17 15:47:08.649514
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Text

Distinct3337
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2024-04-18T00:47:08.825253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9805912
Min length2

Characters and Unicode

Total characters23378
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3336 ?
Unique (%)99.6%

Sample

1st row1515834
2nd row1515835
3rd row1515836
4th row1515837
5th row1515838
ValueCountFrequency (%)
용지 13
 
0.4%
1513708 1
 
< 0.1%
1513653 1
 
< 0.1%
1513667 1
 
< 0.1%
1513656 1
 
< 0.1%
1513658 1
 
< 0.1%
1513659 1
 
< 0.1%
1513660 1
 
< 0.1%
1513661 1
 
< 0.1%
1513662 1
 
< 0.1%
Other values (3327) 3327
99.3%
2024-04-18T00:47:09.170471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7636
32.7%
5 5235
22.4%
3 1964
 
8.4%
4 1963
 
8.4%
2 1396
 
6.0%
8 1074
 
4.6%
7 1073
 
4.6%
6 1065
 
4.6%
9 978
 
4.2%
0 968
 
4.1%
Other values (2) 26
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23352
99.9%
Other Letter 26
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7636
32.7%
5 5235
22.4%
3 1964
 
8.4%
4 1963
 
8.4%
2 1396
 
6.0%
8 1074
 
4.6%
7 1073
 
4.6%
6 1065
 
4.6%
9 978
 
4.2%
0 968
 
4.1%
Other Letter
ValueCountFrequency (%)
13
50.0%
13
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23352
99.9%
Hangul 26
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7636
32.7%
5 5235
22.4%
3 1964
 
8.4%
4 1963
 
8.4%
2 1396
 
6.0%
8 1074
 
4.6%
7 1073
 
4.6%
6 1065
 
4.6%
9 978
 
4.2%
0 968
 
4.1%
Hangul
ValueCountFrequency (%)
13
50.0%
13
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23352
99.9%
Hangul 26
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7636
32.7%
5 5235
22.4%
3 1964
 
8.4%
4 1963
 
8.4%
2 1396
 
6.0%
8 1074
 
4.6%
7 1073
 
4.6%
6 1065
 
4.6%
9 978
 
4.2%
0 968
 
4.1%
Hangul
ValueCountFrequency (%)
13
50.0%
13
50.0%

inspec_yy
Categorical

Distinct24
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2012
263 
2008
248 
2007
234 
2010
225 
2011
225 
Other values (19)
2154 

Length

Max length14
Median length4
Mean length4.0352344
Min length4

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row2002
2nd row2002
3rd row2002
4th row2002
5th row2002

Common Values

ValueCountFrequency (%)
2012 263
 
7.9%
2008 248
 
7.4%
2007 234
 
7.0%
2010 225
 
6.7%
2011 225
 
6.7%
2006 222
 
6.6%
2009 217
 
6.5%
2013 207
 
6.2%
2017 188
 
5.6%
2016 183
 
5.5%
Other values (14) 1137
34.0%

Length

2024-04-18T00:47:09.284359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2012 263
 
7.8%
2008 248
 
7.3%
2007 234
 
6.9%
2010 225
 
6.7%
2011 225
 
6.7%
2006 222
 
6.6%
2009 217
 
6.4%
2013 207
 
6.1%
2017 188
 
5.6%
2016 183
 
5.4%
Other values (20) 1163
34.5%
Distinct65
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2024-04-18T00:47:09.422615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length2.5586742
Min length1

Characters and Unicode

Total characters8569
Distinct characters53
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)0.7%

Sample

1st row
2nd row
3rd row대지
4th row대지
5th row공장용지
ValueCountFrequency (%)
잡종지 573
16.7%
공원 517
15.1%
공장용지 421
12.3%
대지 418
12.2%
233
6.8%
201
 
5.9%
철도용지 181
 
5.3%
임야 161
 
4.7%
학교용지 137
 
4.0%
공장 84
 
2.5%
Other values (58) 496
14.5%
2024-04-18T00:47:09.655190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1835
21.4%
1046
12.2%
777
9.1%
624
 
7.3%
590
 
6.9%
587
 
6.9%
526
 
6.1%
521
 
6.1%
241
 
2.8%
234
 
2.7%
Other values (43) 1588
18.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8247
96.2%
Decimal Number 145
 
1.7%
Space Separator 131
 
1.5%
Other Punctuation 44
 
0.5%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1835
22.3%
1046
12.7%
777
9.4%
624
 
7.6%
590
 
7.2%
587
 
7.1%
526
 
6.4%
521
 
6.3%
241
 
2.9%
234
 
2.8%
Other values (28) 1266
15.4%
Decimal Number
ValueCountFrequency (%)
2 32
22.1%
3 31
21.4%
1 31
21.4%
4 30
20.7%
7 6
 
4.1%
6 4
 
2.8%
0 4
 
2.8%
9 3
 
2.1%
8 2
 
1.4%
5 2
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 31
70.5%
. 13
29.5%
Space Separator
ValueCountFrequency (%)
131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8247
96.2%
Common 322
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1835
22.3%
1046
12.7%
777
9.4%
624
 
7.6%
590
 
7.2%
587
 
7.1%
526
 
6.4%
521
 
6.3%
241
 
2.9%
234
 
2.8%
Other values (28) 1266
15.4%
Common
ValueCountFrequency (%)
131
40.7%
2 32
 
9.9%
3 31
 
9.6%
, 31
 
9.6%
1 31
 
9.6%
4 30
 
9.3%
. 13
 
4.0%
7 6
 
1.9%
6 4
 
1.2%
0 4
 
1.2%
Other values (5) 9
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8247
96.2%
ASCII 322
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1835
22.3%
1046
12.7%
777
9.4%
624
 
7.6%
590
 
7.2%
587
 
7.1%
526
 
6.4%
521
 
6.3%
241
 
2.9%
234
 
2.8%
Other values (28) 1266
15.4%
ASCII
ValueCountFrequency (%)
131
40.7%
2 32
 
9.9%
3 31
 
9.6%
, 31
 
9.6%
1 31
 
9.6%
4 30
 
9.3%
. 13
 
4.0%
7 6
 
1.9%
6 4
 
1.2%
0 4
 
1.2%
Other values (5) 9
 
2.8%
Distinct1692
Distinct (%)50.7%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:09.903799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length11.645084
Min length2

Characters and Unicode

Total characters38848
Distinct characters337
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1131 ?
Unique (%)33.9%

Sample

1st row신호공단
2nd row화명매립장
3rd row검역원
4th row고려제강
5th row염색단지조합
ValueCountFrequency (%)
강서구 227
 
2.8%
사하구 194
 
2.4%
표토 192
 
2.3%
사상구 168
 
2.0%
m 159
 
1.9%
149
 
1.8%
기장군 145
 
1.8%
해운대구 134
 
1.6%
부산진구 103
 
1.3%
수영구 101
 
1.2%
Other values (1495) 6645
80.9%
2024-04-18T00:47:10.252669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4905
 
12.6%
1 1932
 
5.0%
1793
 
4.6%
1556
 
4.0%
2 1023
 
2.6%
- 942
 
2.4%
0 828
 
2.1%
3 816
 
2.1%
4 737
 
1.9%
5 707
 
1.8%
Other values (327) 23609
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22431
57.7%
Decimal Number 7924
 
20.4%
Space Separator 4905
 
12.6%
Dash Punctuation 942
 
2.4%
Other Punctuation 617
 
1.6%
Close Punctuation 554
 
1.4%
Open Punctuation 554
 
1.4%
Lowercase Letter 423
 
1.1%
Other Symbol 299
 
0.8%
Uppercase Letter 199
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1793
 
8.0%
1556
 
6.9%
688
 
3.1%
665
 
3.0%
583
 
2.6%
511
 
2.3%
492
 
2.2%
368
 
1.6%
351
 
1.6%
350
 
1.6%
Other values (294) 15074
67.2%
Decimal Number
ValueCountFrequency (%)
1 1932
24.4%
2 1023
12.9%
0 828
10.4%
3 816
10.3%
4 737
 
9.3%
5 707
 
8.9%
8 545
 
6.9%
9 484
 
6.1%
6 455
 
5.7%
7 397
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
M 91
45.7%
K 34
 
17.1%
S 31
 
15.6%
B 16
 
8.0%
C 9
 
4.5%
J 8
 
4.0%
Y 6
 
3.0%
G 2
 
1.0%
L 2
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
m 363
85.8%
a 30
 
7.1%
b 28
 
6.6%
d 1
 
0.2%
c 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 451
73.1%
· 96
 
15.6%
, 62
 
10.0%
? 8
 
1.3%
Space Separator
ValueCountFrequency (%)
4905
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 942
100.0%
Close Punctuation
ValueCountFrequency (%)
) 554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 554
100.0%
Other Symbol
ValueCountFrequency (%)
299
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22730
58.5%
Common 15496
39.9%
Latin 622
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1793
 
7.9%
1556
 
6.8%
688
 
3.0%
665
 
2.9%
583
 
2.6%
511
 
2.2%
492
 
2.2%
368
 
1.6%
351
 
1.5%
350
 
1.5%
Other values (295) 15373
67.6%
Common
ValueCountFrequency (%)
4905
31.7%
1 1932
 
12.5%
2 1023
 
6.6%
- 942
 
6.1%
0 828
 
5.3%
3 816
 
5.3%
4 737
 
4.8%
5 707
 
4.6%
) 554
 
3.6%
( 554
 
3.6%
Other values (8) 2498
16.1%
Latin
ValueCountFrequency (%)
m 363
58.4%
M 91
 
14.6%
K 34
 
5.5%
S 31
 
5.0%
a 30
 
4.8%
b 28
 
4.5%
B 16
 
2.6%
C 9
 
1.4%
J 8
 
1.3%
Y 6
 
1.0%
Other values (4) 6
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22431
57.7%
ASCII 16022
41.2%
None 395
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4905
30.6%
1 1932
 
12.1%
2 1023
 
6.4%
- 942
 
5.9%
0 828
 
5.2%
3 816
 
5.1%
4 737
 
4.6%
5 707
 
4.4%
) 554
 
3.5%
( 554
 
3.5%
Other values (21) 3024
18.9%
Hangul
ValueCountFrequency (%)
1793
 
8.0%
1556
 
6.9%
688
 
3.1%
665
 
3.0%
583
 
2.6%
511
 
2.3%
492
 
2.2%
368
 
1.6%
351
 
1.6%
350
 
1.6%
Other values (294) 15074
67.2%
None
ValueCountFrequency (%)
299
75.7%
· 96
 
24.3%

soil01
Text

Distinct539
Distinct (%)16.2%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:10.585780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.8696043
Min length1

Characters and Unicode

Total characters12909
Distinct characters14
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

Unique153 ?
Unique (%)4.6%

Sample

1st row0.175
2nd row0.07
3rd row0.2
4th row0.34
5th row0.07
ValueCountFrequency (%)
2 72
 
2.2%
0.00 68
 
2.0%
0 65
 
1.9%
1 62
 
1.9%
30
 
0.9%
1.43 26
 
0.8%
1.37 26
 
0.8%
0.25 25
 
0.7%
0.26 25
 
0.7%
0.11 23
 
0.7%
Other values (529) 2914
87.4%
2024-04-18T00:47:10.995604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3101
24.0%
0 2208
17.1%
1 1665
12.9%
2 1285
10.0%
5 1084
 
8.4%
3 892
 
6.9%
7 679
 
5.3%
4 597
 
4.6%
6 501
 
3.9%
8 435
 
3.4%
Other values (4) 462
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9776
75.7%
Other Punctuation 3101
 
24.0%
Dash Punctuation 30
 
0.2%
Other Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2208
22.6%
1 1665
17.0%
2 1285
13.1%
5 1084
11.1%
3 892
9.1%
7 679
 
6.9%
4 597
 
6.1%
6 501
 
5.1%
8 435
 
4.4%
9 430
 
4.4%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 3101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12907
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3101
24.0%
0 2208
17.1%
1 1665
12.9%
2 1285
10.0%
5 1084
 
8.4%
3 892
 
6.9%
7 679
 
5.3%
4 597
 
4.6%
6 501
 
3.9%
8 435
 
3.4%
Other values (2) 460
 
3.6%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12907
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3101
24.0%
0 2208
17.1%
1 1665
12.9%
2 1285
10.0%
5 1084
 
8.4%
3 892
 
6.9%
7 679
 
5.3%
4 597
 
4.6%
6 501
 
3.9%
8 435
 
3.4%
Other values (2) 460
 
3.6%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

soil02
Text

Distinct2357
Distinct (%)70.7%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:11.281329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.4253597
Min length1

Characters and Unicode

Total characters14763
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1789 ?
Unique (%)53.6%

Sample

1st row6.705
2nd row1.6
3rd row8.05
4th row43.1
5th row0.57
ValueCountFrequency (%)
0 48
 
1.4%
17 14
 
0.4%
14 13
 
0.4%
16 13
 
0.4%
9 11
 
0.3%
13 9
 
0.3%
20 8
 
0.2%
25 8
 
0.2%
8
 
0.2%
26 8
 
0.2%
Other values (2347) 3196
95.8%
2024-04-18T00:47:11.661785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3119
21.1%
1 1715
11.6%
5 1517
10.3%
2 1450
9.8%
3 1394
9.4%
4 1021
 
6.9%
0 993
 
6.7%
7 979
 
6.6%
6 901
 
6.1%
8 862
 
5.8%
Other values (2) 812
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11636
78.8%
Other Punctuation 3119
 
21.1%
Dash Punctuation 8
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1715
14.7%
5 1517
13.0%
2 1450
12.5%
3 1394
12.0%
4 1021
8.8%
0 993
8.5%
7 979
8.4%
6 901
7.7%
8 862
7.4%
9 804
6.9%
Other Punctuation
ValueCountFrequency (%)
. 3119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14763
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3119
21.1%
1 1715
11.6%
5 1517
10.3%
2 1450
9.8%
3 1394
9.4%
4 1021
 
6.9%
0 993
 
6.7%
7 979
 
6.6%
6 901
 
6.1%
8 862
 
5.8%
Other values (2) 812
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14763
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3119
21.1%
1 1715
11.6%
5 1517
10.3%
2 1450
9.8%
3 1394
9.4%
4 1021
 
6.9%
0 993
 
6.7%
7 979
 
6.6%
6 901
 
6.1%
8 862
 
5.8%
Other values (2) 812
 
5.5%

soil03
Text

Distinct1304
Distinct (%)39.1%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:11.960559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.9574341
Min length1

Characters and Unicode

Total characters13202
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique645 ?
Unique (%)19.3%

Sample

1st row0.33
2nd row0
3rd row0
4th row0.71
5th row0
ValueCountFrequency (%)
0 96
 
2.9%
8.2 34
 
1.0%
8.1 32
 
1.0%
8 17
 
0.5%
8.3 15
 
0.4%
0.01 13
 
0.4%
0.68 12
 
0.4%
0.22 11
 
0.3%
0.29 11
 
0.3%
5.3 11
 
0.3%
Other values (1294) 3084
92.4%
2024-04-18T00:47:12.560146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3165
24.0%
0 1426
10.8%
5 1341
10.2%
1 1184
 
9.0%
3 1116
 
8.5%
2 1028
 
7.8%
4 952
 
7.2%
7 908
 
6.9%
6 774
 
5.9%
8 740
 
5.6%
Other values (2) 568
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10029
76.0%
Other Punctuation 3165
 
24.0%
Dash Punctuation 8
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1426
14.2%
5 1341
13.4%
1 1184
11.8%
3 1116
11.1%
2 1028
10.3%
4 952
9.5%
7 908
9.1%
6 774
7.7%
8 740
7.4%
9 560
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 3165
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3165
24.0%
0 1426
10.8%
5 1341
10.2%
1 1184
 
9.0%
3 1116
 
8.5%
2 1028
 
7.8%
4 952
 
7.2%
7 908
 
6.9%
6 774
 
5.9%
8 740
 
5.6%
Other values (2) 568
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3165
24.0%
0 1426
10.8%
5 1341
10.2%
1 1184
 
9.0%
3 1116
 
8.5%
2 1028
 
7.8%
4 952
 
7.2%
7 908
 
6.9%
6 774
 
5.9%
8 740
 
5.6%
Other values (2) 568
 
4.3%

soil04
Text

Distinct585
Distinct (%)17.5%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:12.830765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.0683453
Min length1

Characters and Unicode

Total characters13572
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)10.8%

Sample

1st row0.01
2nd row0.004
3rd row0.709
4th row0.01
5th row0.008
ValueCountFrequency (%)
0 442
 
13.2%
0.01 257
 
7.7%
0.02 231
 
6.9%
0.03 181
 
5.4%
0.04 127
 
3.8%
0.00 99
 
3.0%
0.05 94
 
2.8%
0.07 50
 
1.5%
0.06 47
 
1.4%
0.006 35
 
1.0%
Other values (575) 1773
53.1%
2024-04-18T00:47:13.199656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5897
43.4%
. 2874
21.2%
1 1110
 
8.2%
2 788
 
5.8%
3 628
 
4.6%
4 483
 
3.6%
5 416
 
3.1%
6 366
 
2.7%
8 351
 
2.6%
7 342
 
2.5%
Other values (2) 317
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10690
78.8%
Other Punctuation 2874
 
21.2%
Dash Punctuation 8
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5897
55.2%
1 1110
 
10.4%
2 788
 
7.4%
3 628
 
5.9%
4 483
 
4.5%
5 416
 
3.9%
6 366
 
3.4%
8 351
 
3.3%
7 342
 
3.2%
9 309
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 2874
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5897
43.4%
. 2874
21.2%
1 1110
 
8.2%
2 788
 
5.8%
3 628
 
4.6%
4 483
 
3.6%
5 416
 
3.1%
6 366
 
2.7%
8 351
 
2.6%
7 342
 
2.5%
Other values (2) 317
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5897
43.4%
. 2874
21.2%
1 1110
 
8.2%
2 788
 
5.8%
3 628
 
4.6%
4 483
 
3.6%
5 416
 
3.1%
6 366
 
2.7%
8 351
 
2.6%
7 342
 
2.5%
Other values (2) 317
 
2.3%

soil05
Text

Distinct2073
Distinct (%)62.1%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:13.502319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.1882494
Min length1

Characters and Unicode

Total characters13972
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1537 ?
Unique (%)46.1%

Sample

1st row9.35
2nd row2.2
3rd row6.5
4th row92
5th row1.5
ValueCountFrequency (%)
0 142
 
4.3%
0.05 35
 
1.0%
0.1 35
 
1.0%
1.4 22
 
0.7%
1.8 16
 
0.5%
1.6 16
 
0.5%
1.7 16
 
0.5%
1.3 15
 
0.4%
1.5 15
 
0.4%
1.2 12
 
0.4%
Other values (2063) 3012
90.3%
2024-04-18T00:47:13.901749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3076
22.0%
1 1705
12.2%
3 1426
10.2%
2 1416
10.1%
5 1263
9.0%
7 1028
 
7.4%
4 930
 
6.7%
0 909
 
6.5%
6 793
 
5.7%
8 743
 
5.3%
Other values (2) 683
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10888
77.9%
Other Punctuation 3076
 
22.0%
Dash Punctuation 8
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1705
15.7%
3 1426
13.1%
2 1416
13.0%
5 1263
11.6%
7 1028
9.4%
4 930
8.5%
0 909
8.3%
6 793
7.3%
8 743
6.8%
9 675
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 3076
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13972
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3076
22.0%
1 1705
12.2%
3 1426
10.2%
2 1416
10.1%
5 1263
9.0%
7 1028
 
7.4%
4 930
 
6.7%
0 909
 
6.5%
6 793
 
5.7%
8 743
 
5.3%
Other values (2) 683
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3076
22.0%
1 1705
12.2%
3 1426
10.2%
2 1416
10.1%
5 1263
9.0%
7 1028
 
7.4%
4 930
 
6.7%
0 909
 
6.5%
6 793
 
5.7%
8 743
 
5.3%
Other values (2) 683
 
4.9%

soil06
Text

Distinct162
Distinct (%)4.9%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:14.139081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length1
Mean length1.508693
Min length1

Characters and Unicode

Total characters5033
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)3.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 2672
80.1%
0.0 275
 
8.2%
0.00 146
 
4.4%
0.8 13
 
0.4%
13
 
0.4%
0.7 9
 
0.3%
0.6 9
 
0.3%
1.2 7
 
0.2%
1.0 7
 
0.2%
1.6 4
 
0.1%
Other values (151) 181
 
5.4%
2024-04-18T00:47:14.470060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3838
76.3%
. 651
 
12.9%
2 112
 
2.2%
1 75
 
1.5%
3 64
 
1.3%
5 54
 
1.1%
7 49
 
1.0%
4 49
 
1.0%
6 48
 
1.0%
8 40
 
0.8%
Other values (2) 53
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4355
86.5%
Other Punctuation 651
 
12.9%
Dash Punctuation 27
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3838
88.1%
2 112
 
2.6%
1 75
 
1.7%
3 64
 
1.5%
5 54
 
1.2%
7 49
 
1.1%
4 49
 
1.1%
6 48
 
1.1%
8 40
 
0.9%
9 26
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 651
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5033
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3838
76.3%
. 651
 
12.9%
2 112
 
2.2%
1 75
 
1.5%
3 64
 
1.3%
5 54
 
1.1%
7 49
 
1.0%
4 49
 
1.0%
6 48
 
1.0%
8 40
 
0.8%
Other values (2) 53
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5033
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3838
76.3%
. 651
 
12.9%
2 112
 
2.2%
1 75
 
1.5%
3 64
 
1.3%
5 54
 
1.1%
7 49
 
1.0%
4 49
 
1.0%
6 48
 
1.0%
8 40
 
0.8%
Other values (2) 53
 
1.1%

soil07
Text

Distinct1386
Distinct (%)41.5%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:14.736264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length3.4151679
Min length1

Characters and Unicode

Total characters11393
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1205 ?
Unique (%)36.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0.028
ValueCountFrequency (%)
0 1145
34.3%
223
 
6.7%
99999 117
 
3.5%
0.03 37
 
1.1%
0.02 27
 
0.8%
0.01 14
 
0.4%
0.002 14
 
0.4%
0.025 14
 
0.4%
0.04 13
 
0.4%
0.028 10
 
0.3%
Other values (1375) 1722
51.6%
2024-04-18T00:47:15.097946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2553
22.4%
. 1770
15.5%
1 1137
10.0%
9 1041
9.1%
3 839
 
7.4%
2 813
 
7.1%
7 657
 
5.8%
5 560
 
4.9%
6 549
 
4.8%
4 533
 
4.7%
Other values (2) 941
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9210
80.8%
Other Punctuation 1770
 
15.5%
Dash Punctuation 413
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2553
27.7%
1 1137
12.3%
9 1041
11.3%
3 839
 
9.1%
2 813
 
8.8%
7 657
 
7.1%
5 560
 
6.1%
6 549
 
6.0%
4 533
 
5.8%
8 528
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 1770
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 413
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11393
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2553
22.4%
. 1770
15.5%
1 1137
10.0%
9 1041
9.1%
3 839
 
7.4%
2 813
 
7.1%
7 657
 
5.8%
5 560
 
4.9%
6 549
 
4.8%
4 533
 
4.7%
Other values (2) 941
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11393
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2553
22.4%
. 1770
15.5%
1 1137
10.0%
9 1041
9.1%
3 839
 
7.4%
2 813
 
7.1%
7 657
 
5.8%
5 560
 
4.9%
6 549
 
4.8%
4 533
 
4.7%
Other values (2) 941
 
8.3%

soil08
Text

Distinct1018
Distinct (%)30.5%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:15.393568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.6936451
Min length1

Characters and Unicode

Total characters8986
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique791 ?
Unique (%)23.7%

Sample

1st row0
2nd row0.205
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1555
46.6%
99999 251
 
7.5%
165
 
4.9%
5.8 8
 
0.2%
4.9 6
 
0.2%
9.43 6
 
0.2%
11.5 6
 
0.2%
5.6 5
 
0.1%
12.53 5
 
0.1%
9.13 5
 
0.1%
Other values (1007) 1324
39.7%
2024-04-18T00:47:15.773622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1890
21.0%
9 1612
17.9%
. 1344
15.0%
1 907
10.1%
3 530
 
5.9%
2 469
 
5.2%
7 444
 
4.9%
5 400
 
4.5%
6 371
 
4.1%
4 364
 
4.1%
Other values (2) 655
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7345
81.7%
Other Punctuation 1344
 
15.0%
Dash Punctuation 297
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1890
25.7%
9 1612
21.9%
1 907
12.3%
3 530
 
7.2%
2 469
 
6.4%
7 444
 
6.0%
5 400
 
5.4%
6 371
 
5.1%
4 364
 
5.0%
8 358
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 1344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 297
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8986
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1890
21.0%
9 1612
17.9%
. 1344
15.0%
1 907
10.1%
3 530
 
5.9%
2 469
 
5.2%
7 444
 
4.9%
5 400
 
4.5%
6 371
 
4.1%
4 364
 
4.1%
Other values (2) 655
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8986
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1890
21.0%
9 1612
17.9%
. 1344
15.0%
1 907
10.1%
3 530
 
5.9%
2 469
 
5.2%
7 444
 
4.9%
5 400
 
4.5%
6 371
 
4.1%
4 364
 
4.1%
Other values (2) 655
 
7.3%

soil09
Text

Distinct660
Distinct (%)19.8%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:16.082889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length2.0467626
Min length1

Characters and Unicode

Total characters6828
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)10.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 926
27.8%
878
26.3%
99999 106
 
3.2%
6 13
 
0.4%
1 11
 
0.3%
87 10
 
0.3%
66 10
 
0.3%
35 9
 
0.3%
5 9
 
0.3%
93 9
 
0.3%
Other values (649) 1355
40.6%
2024-04-18T00:47:16.496244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1200
17.6%
- 977
14.3%
9 857
12.6%
1 721
10.6%
2 574
8.4%
3 539
7.9%
4 426
 
6.2%
5 387
 
5.7%
6 340
 
5.0%
7 338
 
5.0%
Other values (2) 469
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5704
83.5%
Dash Punctuation 977
 
14.3%
Other Punctuation 147
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1200
21.0%
9 857
15.0%
1 721
12.6%
2 574
10.1%
3 539
9.4%
4 426
 
7.5%
5 387
 
6.8%
6 340
 
6.0%
7 338
 
5.9%
8 322
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 977
100.0%
Other Punctuation
ValueCountFrequency (%)
. 147
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6828
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1200
17.6%
- 977
14.3%
9 857
12.6%
1 721
10.6%
2 574
8.4%
3 539
7.9%
4 426
 
6.2%
5 387
 
5.7%
6 340
 
5.0%
7 338
 
5.0%
Other values (2) 469
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6828
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1200
17.6%
- 977
14.3%
9 857
12.6%
1 721
10.6%
2 574
8.4%
3 539
7.9%
4 426
 
6.2%
5 387
 
5.7%
6 340
 
5.0%
7 338
 
5.0%
Other values (2) 469
 
6.9%

soil10
Categorical

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
0
1604 
-
1040 
-0
317 
99999
 
154
0.00
 
141
Other values (2)
 
93

Length

Max length5
Median length1
Mean length1.5120932
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1604
47.9%
- 1040
31.1%
-0 317
 
9.5%
99999 154
 
4.6%
0.00 141
 
4.2%
0.000 80
 
2.4%
<NA> 13
 
0.4%

Length

2024-04-18T00:47:16.623462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:47:16.734283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1921
57.4%
1040
31.1%
99999 154
 
4.6%
0.00 141
 
4.2%
0.000 80
 
2.4%
na 13
 
0.4%

soil11
Categorical

IMBALANCE 

Distinct46
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
0
1511 
-
1026 
-0
317 
99999
154 
0.00
 
141
Other values (41)
200 

Length

Max length5
Median length1
Mean length1.5771872
Min length1

Unique

Unique17 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 1511
45.1%
- 1026
30.6%
-0 317
 
9.5%
99999 154
 
4.6%
0.00 141
 
4.2%
0.000 81
 
2.4%
<NA> 13
 
0.4%
300 10
 
0.3%
800 9
 
0.3%
500 8
 
0.2%
Other values (36) 79
 
2.4%

Length

2024-04-18T00:47:16.859283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 1828
54.6%
1026
30.6%
99999 154
 
4.6%
0.00 141
 
4.2%
0.000 81
 
2.4%
na 13
 
0.4%
300 10
 
0.3%
800 9
 
0.3%
500 8
 
0.2%
110 6
 
0.2%
Other values (35) 73
 
2.2%

soil12
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct51
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
0
1507 
-
992 
-0
339 
99999
165 
0.00
 
137
Other values (46)
209 

Length

Max length6
Median length1
Mean length1.5807704
Min length1

Unique

Unique24 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 1507
45.0%
- 992
29.6%
-0 339
 
10.1%
99999 165
 
4.9%
0.00 137
 
4.1%
0.0 88
 
2.6%
0.01 20
 
0.6%
<NA> 13
 
0.4%
0.02 11
 
0.3%
0.04 8
 
0.2%
Other values (41) 69
 
2.1%

Length

2024-04-18T00:47:16.963752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 1846
55.1%
992
29.6%
99999 165
 
4.9%
0.00 137
 
4.1%
0.0 88
 
2.6%
0.01 20
 
0.6%
na 13
 
0.4%
0.02 11
 
0.3%
0.04 8
 
0.2%
0.03 6
 
0.2%
Other values (40) 63
 
1.9%

soil13
Text

Distinct1147
Distinct (%)34.4%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:17.251627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length2.9760192
Min length1

Characters and Unicode

Total characters9928
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique767 ?
Unique (%)23.0%

Sample

1st row4.433
2nd row3.5
3rd row0
4th row11.333
5th row0
ValueCountFrequency (%)
819
24.6%
0 630
 
18.9%
0.00 163
 
4.9%
7.4 8
 
0.2%
7.9 7
 
0.2%
6.7 7
 
0.2%
10.2 7
 
0.2%
16 7
 
0.2%
6 6
 
0.2%
6.533 5
 
0.1%
Other values (1137) 1677
50.3%
2024-04-18T00:47:17.685184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1820
18.3%
0 1400
14.1%
3 1186
11.9%
1 846
8.5%
- 819
8.2%
7 806
8.1%
6 769
7.7%
2 615
 
6.2%
5 453
 
4.6%
4 452
 
4.6%
Other values (2) 762
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7289
73.4%
Other Punctuation 1820
 
18.3%
Dash Punctuation 819
 
8.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1400
19.2%
3 1186
16.3%
1 846
11.6%
7 806
11.1%
6 769
10.6%
2 615
8.4%
5 453
 
6.2%
4 452
 
6.2%
9 384
 
5.3%
8 378
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 1820
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 819
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9928
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1820
18.3%
0 1400
14.1%
3 1186
11.9%
1 846
8.5%
- 819
8.2%
7 806
8.1%
6 769
7.7%
2 615
 
6.2%
5 453
 
4.6%
4 452
 
4.6%
Other values (2) 762
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9928
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1820
18.3%
0 1400
14.1%
3 1186
11.9%
1 846
8.5%
- 819
8.2%
7 806
8.1%
6 769
7.7%
2 615
 
6.2%
5 453
 
4.6%
4 452
 
4.6%
Other values (2) 762
7.7%

soil14
Text

Distinct1554
Distinct (%)46.6%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:17.936456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.4442446
Min length1

Characters and Unicode

Total characters11490
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1396 ?
Unique (%)41.8%

Sample

1st row113.333
2nd row186.667
3rd row0
4th row490
5th row0
ValueCountFrequency (%)
0 882
26.4%
485
 
14.5%
0.0 224
 
6.7%
250 7
 
0.2%
136.667 5
 
0.1%
55.333 5
 
0.1%
196 4
 
0.1%
101.2 4
 
0.1%
88.667 4
 
0.1%
58 4
 
0.1%
Other values (1544) 1712
51.3%
2024-04-18T00:47:18.318449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1749
15.2%
. 1730
15.1%
3 1439
12.5%
6 1113
9.7%
1 998
8.7%
7 926
8.1%
2 803
7.0%
4 598
 
5.2%
5 597
 
5.2%
8 559
 
4.9%
Other values (2) 978
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9275
80.7%
Other Punctuation 1730
 
15.1%
Dash Punctuation 485
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1749
18.9%
3 1439
15.5%
6 1113
12.0%
1 998
10.8%
7 926
10.0%
2 803
8.7%
4 598
 
6.4%
5 597
 
6.4%
8 559
 
6.0%
9 493
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 1730
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 485
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1749
15.2%
. 1730
15.1%
3 1439
12.5%
6 1113
9.7%
1 998
8.7%
7 926
8.1%
2 803
7.0%
4 598
 
5.2%
5 597
 
5.2%
8 559
 
4.9%
Other values (2) 978
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1749
15.2%
. 1730
15.1%
3 1439
12.5%
6 1113
9.7%
1 998
8.7%
7 926
8.1%
2 803
7.0%
4 598
 
5.2%
5 597
 
5.2%
8 559
 
4.9%
Other values (2) 978
8.5%

soil15
Text

Distinct587
Distinct (%)17.6%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:18.548637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length2.0257794
Min length1

Characters and Unicode

Total characters6758
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique441 ?
Unique (%)13.2%

Sample

1st row271.852
2nd row327.784
3rd row0
4th row441.207
5th row0
ValueCountFrequency (%)
0 1549
46.4%
656
19.7%
0.0 222
 
6.7%
99999 119
 
3.6%
0.1 6
 
0.2%
0.2 6
 
0.2%
48 5
 
0.1%
26 5
 
0.1%
93 4
 
0.1%
41 4
 
0.1%
Other values (576) 760
22.8%
2024-04-18T00:47:18.863807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2169
32.1%
- 884
13.1%
9 791
 
11.7%
. 589
 
8.7%
5 403
 
6.0%
1 377
 
5.6%
2 360
 
5.3%
3 334
 
4.9%
4 238
 
3.5%
7 217
 
3.2%
Other values (2) 396
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5285
78.2%
Dash Punctuation 884
 
13.1%
Other Punctuation 589
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2169
41.0%
9 791
 
15.0%
5 403
 
7.6%
1 377
 
7.1%
2 360
 
6.8%
3 334
 
6.3%
4 238
 
4.5%
7 217
 
4.1%
8 202
 
3.8%
6 194
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 884
100.0%
Other Punctuation
ValueCountFrequency (%)
. 589
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6758
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2169
32.1%
- 884
13.1%
9 791
 
11.7%
. 589
 
8.7%
5 403
 
6.0%
1 377
 
5.6%
2 360
 
5.3%
3 334
 
4.9%
4 238
 
3.5%
7 217
 
3.2%
Other values (2) 396
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6758
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2169
32.1%
- 884
13.1%
9 791
 
11.7%
. 589
 
8.7%
5 403
 
6.0%
1 377
 
5.6%
2 360
 
5.3%
3 334
 
4.9%
4 238
 
3.5%
7 217
 
3.2%
Other values (2) 396
 
5.9%

soil16
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
0
1899 
-
680 
-0
301 
0.0
278 
99999
 
158
Other values (18)
 
33

Length

Max length6
Median length1
Mean length1.469991
Min length1

Unique

Unique15 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 1899
56.7%
- 680
 
20.3%
-0 301
 
9.0%
0.0 278
 
8.3%
99999 158
 
4.7%
<NA> 13
 
0.4%
0.1 3
 
0.1%
0.3 2
 
0.1%
201 1
 
< 0.1%
28.589 1
 
< 0.1%
Other values (13) 13
 
0.4%

Length

2024-04-18T00:47:18.977153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2200
65.7%
680
 
20.3%
0.0 278
 
8.3%
99999 158
 
4.7%
na 13
 
0.4%
0.1 3
 
0.1%
0.3 2
 
0.1%
3.1 1
 
< 0.1%
401 1
 
< 0.1%
189 1
 
< 0.1%
Other values (12) 12
 
0.4%

soil17
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
0
1882 
-
679 
-0
301 
0.0
270 
99999
 
158
Other values (14)
 
59

Length

Max length6
Median length1
Mean length1.4765602
Min length1

Unique

Unique8 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 1882
56.2%
- 679
 
20.3%
-0 301
 
9.0%
0.0 270
 
8.1%
99999 158
 
4.7%
<NA> 13
 
0.4%
0.1 13
 
0.4%
중구 12
 
0.4%
0.2 7
 
0.2%
0.3 4
 
0.1%
Other values (9) 10
 
0.3%

Length

2024-04-18T00:47:19.064917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2183
65.2%
679
 
20.3%
0.0 270
 
8.1%
99999 158
 
4.7%
na 13
 
0.4%
0.1 13
 
0.4%
중구 12
 
0.4%
0.2 7
 
0.2%
0.3 4
 
0.1%
0.4 2
 
0.1%
Other values (8) 8
 
0.2%

soil18
Text

Distinct531
Distinct (%)15.9%
Missing13
Missing (%)0.4%
Memory size26.3 KiB
2024-04-18T00:47:19.325597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.4718225
Min length1

Characters and Unicode

Total characters8246
Distinct characters16
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)7.5%

Sample

1st row6.1
2nd row7.3
3rd row8.1
4th row7.2
5th row8.5
ValueCountFrequency (%)
0 397
 
11.9%
353
 
10.6%
8.6 77
 
2.3%
8.4 70
 
2.1%
8.5 68
 
2.0%
8.1 65
 
1.9%
8.7 65
 
1.9%
8.2 60
 
1.8%
8.9 57
 
1.7%
7.8 55
 
1.6%
Other values (521) 2069
62.0%
2024-04-18T00:47:19.706350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1554
18.8%
8 968
11.7%
1 886
10.7%
7 764
9.3%
0 649
7.9%
6 580
 
7.0%
2 578
 
7.0%
9 566
 
6.9%
5 481
 
5.8%
3 419
 
5.1%
Other values (6) 801
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6307
76.5%
Other Punctuation 1568
 
19.0%
Dash Punctuation 353
 
4.3%
Other Letter 16
 
0.2%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 968
15.3%
1 886
14.0%
7 764
12.1%
0 649
10.3%
6 580
9.2%
2 578
9.2%
9 566
9.0%
5 481
7.6%
3 419
6.6%
4 416
6.6%
Other Punctuation
ValueCountFrequency (%)
. 1554
99.1%
, 14
 
0.9%
Other Letter
ValueCountFrequency (%)
8
50.0%
8
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 353
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8228
99.8%
Hangul 16
 
0.2%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1554
18.9%
8 968
11.8%
1 886
10.8%
7 764
9.3%
0 649
7.9%
6 580
 
7.0%
2 578
 
7.0%
9 566
 
6.9%
5 481
 
5.8%
3 419
 
5.1%
Other values (3) 783
9.5%
Hangul
ValueCountFrequency (%)
8
50.0%
8
50.0%
Latin
ValueCountFrequency (%)
m 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8230
99.8%
Hangul 16
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1554
18.9%
8 968
11.8%
1 886
10.8%
7 764
9.3%
0 649
7.9%
6 580
 
7.0%
2 578
 
7.0%
9 566
 
6.9%
5 481
 
5.8%
3 419
 
5.1%
Other values (4) 785
9.5%
Hangul
ValueCountFrequency (%)
8
50.0%
8
50.0%

inspec_gu
Categorical

Distinct28
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
-
2080 
강서구
 
133
사하구
 
104
사상구
 
97
기장군
 
89
Other values (23)
846 

Length

Max length8
Median length1
Mean length1.9172887
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 2080
62.1%
강서구 133
 
4.0%
사하구 104
 
3.1%
사상구 97
 
2.9%
기장군 89
 
2.7%
해운대구 80
 
2.4%
부산진구 75
 
2.2%
교통관련 70
 
2.1%
어린이 66
 
2.0%
폐기물처리 63
 
1.9%
Other values (18) 492
 
14.7%

Length

2024-04-18T00:47:19.818853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2080
62.1%
강서구 133
 
4.0%
사하구 104
 
3.1%
사상구 97
 
2.9%
기장군 89
 
2.7%
해운대구 80
 
2.4%
부산진구 75
 
2.2%
교통관련 70
 
2.1%
어린이 66
 
2.0%
폐기물처리 63
 
1.9%
Other values (18) 492
 
14.7%

inspec_deep
Categorical

IMBALANCE 

Distinct18
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
-
2080 
표토
778 
중간토
 
129
심토
 
114
1.5
 
100
Other values (13)
 
148

Length

Max length4
Median length1
Mean length1.4493879
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 2080
62.1%
표토 778
 
23.2%
중간토 129
 
3.9%
심토 114
 
3.4%
1.5 100
 
3.0%
3 58
 
1.7%
3.0 34
 
1.0%
<NA> 13
 
0.4%
2 10
 
0.3%
1 9
 
0.3%
Other values (8) 24
 
0.7%

Length

2024-04-18T00:47:19.912824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2080
62.1%
표토 778
 
23.2%
중간토 129
 
3.9%
심토 114
 
3.4%
1.5 100
 
3.0%
3 58
 
1.7%
3.0 34
 
1.0%
na 13
 
0.4%
2 10
 
0.3%
1 9
 
0.3%
Other values (8) 24
 
0.7%

soil19
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
-
2802 
0
358 
0.0
 
176
<NA>
 
13

Length

Max length4
Median length1
Mean length1.1167513
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 2802
83.7%
0 358
 
10.7%
0.0 176
 
5.3%
<NA> 13
 
0.4%

Length

2024-04-18T00:47:20.008266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:47:20.089346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2802
83.7%
0 358
 
10.7%
0.0 176
 
5.3%
na 13
 
0.4%

soil20
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
-
2793 
0
355 
0.0
 
175
<NA>
 
13
8.4
 
2
Other values (11)
 
11

Length

Max length4
Median length1
Mean length1.125112
Min length1

Unique

Unique11 ?
Unique (%)0.3%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 2793
83.4%
0 355
 
10.6%
0.0 175
 
5.2%
<NA> 13
 
0.4%
8.4 2
 
0.1%
5.3 1
 
< 0.1%
5.6 1
 
< 0.1%
8.6 1
 
< 0.1%
8.2 1
 
< 0.1%
7.88 1
 
< 0.1%
Other values (6) 6
 
0.2%

Length

2024-04-18T00:47:20.175875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2793
83.4%
0 355
 
10.6%
0.0 175
 
5.2%
na 13
 
0.4%
8.4 2
 
0.1%
5.3 1
 
< 0.1%
5.6 1
 
< 0.1%
8.6 1
 
< 0.1%
8.2 1
 
< 0.1%
7.88 1
 
< 0.1%
Other values (6) 6
 
0.2%

soil21
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
-
3269 
0
 
28
0.000
 
15
<NA>
 
13
2021-02-01 06:08:03
 
13
Other values (11)
 
11

Length

Max length19
Median length1
Mean length1.1125709
Min length1

Unique

Unique11 ?
Unique (%)0.3%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 3269
97.6%
0 28
 
0.8%
0.000 15
 
0.4%
<NA> 13
 
0.4%
2021-02-01 06:08:03 13
 
0.4%
0.124 1
 
< 0.1%
0.340 1
 
< 0.1%
0.083 1
 
< 0.1%
0.028 1
 
< 0.1%
0.115 1
 
< 0.1%
Other values (6) 6
 
0.2%

Length

2024-04-18T00:47:20.270055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3269
97.2%
0 28
 
0.8%
0.000 15
 
0.4%
na 13
 
0.4%
2021-02-01 13
 
0.4%
06:08:03 13
 
0.4%
0.205 1
 
< 0.1%
0.894 1
 
< 0.1%
0.477 1
 
< 0.1%
0.007 1
 
< 0.1%
Other values (7) 7
 
0.2%

soil22
Text

Distinct314
Distinct (%)9.4%
Missing26
Missing (%)0.8%
Memory size26.3 KiB
2024-04-18T00:47:20.533831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8696961
Min length1

Characters and Unicode

Total characters6213
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)3.6%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
2081
62.6%
8.8 40
 
1.2%
8.5 38
 
1.1%
8.4 33
 
1.0%
8.2 30
 
0.9%
8.7 29
 
0.9%
7.8 29
 
0.9%
8.9 29
 
0.9%
8.1 28
 
0.8%
7.7 28
 
0.8%
Other values (304) 958
28.8%
2024-04-18T00:47:20.946878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2081
33.5%
. 1197
19.3%
8 687
 
11.1%
7 564
 
9.1%
9 352
 
5.7%
6 348
 
5.6%
5 205
 
3.3%
2 201
 
3.2%
1 179
 
2.9%
4 178
 
2.9%
Other values (2) 221
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2935
47.2%
Dash Punctuation 2081
33.5%
Other Punctuation 1197
19.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 687
23.4%
7 564
19.2%
9 352
12.0%
6 348
11.9%
5 205
 
7.0%
2 201
 
6.8%
1 179
 
6.1%
4 178
 
6.1%
3 144
 
4.9%
0 77
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 2081
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1197
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6213
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2081
33.5%
. 1197
19.3%
8 687
 
11.1%
7 564
 
9.1%
9 352
 
5.7%
6 348
 
5.6%
5 205
 
3.3%
2 201
 
3.2%
1 179
 
2.9%
4 178
 
2.9%
Other values (2) 221
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6213
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2081
33.5%
. 1197
19.3%
8 687
 
11.1%
7 564
 
9.1%
9 352
 
5.7%
6 348
 
5.6%
5 205
 
3.3%
2 201
 
3.2%
1 179
 
2.9%
4 178
 
2.9%
Other values (2) 221
 
3.6%

last_load_dttm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.3 KiB
2021-02-01 06:08:03
3323 
<NA>
 
26

Length

Max length19
Median length19
Mean length18.883547
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-01 06:08:03
2nd row2021-02-01 06:08:03
3rd row2021-02-01 06:08:03
4th row2021-02-01 06:08:03
5th row2021-02-01 06:08:03

Common Values

ValueCountFrequency (%)
2021-02-01 06:08:03 3323
99.2%
<NA> 26
 
0.8%

Length

2024-04-18T00:47:21.065738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:47:21.143499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-02-01 3323
49.8%
06:08:03 3323
49.8%
na 26
 
0.4%

Sample

skeyinspec_yyinspec_kbinspec_areasoil01soil02soil03soil04soil05soil06soil07soil08soil09soil10soil11soil12soil13soil14soil15soil16soil17soil18inspec_guinspec_deepsoil19soil20soil21soil22last_load_dttm
015158342002신호공단0.1756.7050.330.019.3500000004.433113.333271.852006.1------2021-02-01 06:08:03
115158352002화명매립장0.071.600.0042.2000.20500003.5186.667327.784007.3------2021-02-01 06:08:03
215158362002대지검역원0.28.0500.7096.50000000000008.1------2021-02-01 06:08:03
315158372002대지고려제강0.3443.10.710.0192000000011.333490441.207007.2------2021-02-01 06:08:03
415158382002공장용지염색단지조합0.070.5700.0081.500.02800000000008.5------2021-02-01 06:08:03
515158392002공장용지연합철강공업(주)000000000000000000------2021-02-01 06:08:03
615158402002공장용지신일금속공업0.321040.80.02231.100.1170000060.333556.667564.776007.5------2021-02-01 06:08:03
715158412002공원어울림공원0.16.190.240.0117.50000000000006.9------2021-02-01 06:08:03
815158422002공장용지(주)강남0.38169.050.350.0786.0500.11200000414500008.6------2021-02-01 06:08:03
915158432002공장용지(주)대우인터내셔날0.3455.860.230.0115.100.10200000000007.4------2021-02-01 06:08:03
skeyinspec_yyinspec_kbinspec_areasoil01soil02soil03soil04soil05soil06soil07soil08soil09soil10soil11soil12soil13soil14soil15soil16soil17soil18inspec_guinspec_deepsoil19soil20soil21soil22last_load_dttm
333915158942002대지유진화학공업(주)000000000000000000------2021-02-01 06:08:03
334015158952002대지일산실업(주)0.44519.450.950.05120.050000000000007.3------2021-02-01 06:08:03
334115158962002대지한국동도공업0.0850.7750.420.0120.800.0250000010.3332300008.2------2021-02-01 06:08:03
334215158972002도로구, 동국제강3.190.810.110.0980.300000004.933.3330009.1------2021-02-01 06:08:03
334315158982002도로송정해수욕장0.0750.21500.0032.1450000000000009.2------2021-02-01 06:08:03
334415158992002임야경창광산0.175.940.870.01226.900000004.433236.6670007.8------2021-02-01 06:08:03
334515159002002임야반룡매립장0.0650.510.060.0050.475000000010.83346.667265.609008.2------2021-02-01 06:08:03
334615159012002임야송정천0.184.75500.0086.950000000000006.2------2021-02-01 06:08:03
334715159022002임야일광광산1.27191.42.320.06218.8800000008.83386.6670005.2------2021-02-01 06:08:03
334815159032002잡종지한국공항부산지점000000000000000000------2021-02-01 06:08:03