Overview

Dataset statistics

Number of variables10
Number of observations5916
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory468.1 KiB
Average record size in memory81.0 B

Variable types

Categorical3
Numeric1
DateTime1
Text5

Dataset

Description골프장 농약 잔류량 분석결과로 토양(그린, 페어웨이)과 수질(유출구, 연못)의 농약 항목별 검출농도를 제공합니다. (그린 ,페어웨이 : mg/kg, 유출구, 연못 : mg/L)
URLhttps://www.data.go.kr/data/3075277/fileData.do

Alerts

골프장번호 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 골프장번호High correlation

Reproduction

Analysis started2023-12-12 19:50:22.814276
Analysis finished2023-12-12 19:50:24.013119
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
경기도
1289 
전라남도
748 
충청북도
634 
경상북도
616 
제주특별자치도
472 
Other values (12)
2157 

Length

Max length8
Median length7
Mean length4.1002366
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 1289
21.8%
전라남도 748
12.6%
충청북도 634
10.7%
경상북도 616
10.4%
제주특별자치도 472
 
8.0%
강원도 451
 
7.6%
충청남도 416
 
7.0%
경상남도 348
 
5.9%
인천광역시 227
 
3.8%
광주광역시 223
 
3.8%
Other values (7) 492
 
8.3%

Length

2023-12-13T04:50:24.119914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 1289
21.8%
전라남도 748
12.6%
충청북도 634
10.7%
경상북도 616
10.4%
제주특별자치도 472
 
8.0%
강원도 451
 
7.6%
충청남도 416
 
7.0%
경상남도 348
 
5.9%
인천광역시 227
 
3.8%
광주광역시 223
 
3.8%
Other values (7) 492
 
8.3%

골프장번호
Real number (ℝ)

HIGH CORRELATION 

Distinct522
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265.20639
Minimum1
Maximum522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size52.1 KiB
2023-12-13T04:50:24.309951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19
Q1131
median283
Q3389
95-th percentile495
Maximum522
Range521
Interquartile range (IQR)258

Descriptive statistics

Standard deviation153.25963
Coefficient of variation (CV)0.57788815
Kurtosis-1.1396749
Mean265.20639
Median Absolute Deviation (MAD)120
Skewness-0.18538587
Sum1568961
Variance23488.514
MonotonicityIncreasing
2023-12-13T04:50:24.503192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21 62
 
1.0%
28 59
 
1.0%
283 54
 
0.9%
20 48
 
0.8%
361 47
 
0.8%
19 44
 
0.7%
29 42
 
0.7%
18 41
 
0.7%
33 38
 
0.6%
258 38
 
0.6%
Other values (512) 5443
92.0%
ValueCountFrequency (%)
1 10
0.2%
2 19
0.3%
3 9
0.2%
4 16
0.3%
5 19
0.3%
6 16
0.3%
7 21
0.4%
8 11
0.2%
9 18
0.3%
10 6
 
0.1%
ValueCountFrequency (%)
522 15
0.3%
521 16
0.3%
520 15
0.3%
519 4
 
0.1%
518 7
0.1%
517 12
0.2%
516 11
0.2%
515 17
0.3%
514 12
0.2%
513 16
0.3%

시료채취일자
Date

Distinct121
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
Minimum2021-04-01 00:00:00
Maximum2021-10-19 00:00:00
2023-12-13T04:50:24.707943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:50:24.942389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시료채취_홀번호
Text

Distinct921
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
2023-12-13T04:50:25.367458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length2.2831305
Min length1

Characters and Unicode

Total characters13507
Distinct characters241
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique243 ?
Unique (%)4.1%

Sample

1st row17
2nd row3
3rd row4
4th row4
5th row4
ValueCountFrequency (%)
1 250
 
4.2%
9 221
 
3.7%
3 217
 
3.6%
4 211
 
3.5%
8 204
 
3.4%
7 199
 
3.3%
2 194
 
3.2%
6 184
 
3.1%
5 172
 
2.9%
18 123
 
2.1%
Other values (900) 4014
67.0%
2023-12-13T04:50:26.045295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1905
 
14.1%
2 758
 
5.6%
홀 729
 
5.4%
8 669
 
5.0%
9 663
 
4.9%
3 661
 
4.9%
4 605
 
4.5%
5 588
 
4.4%
7 579
 
4.3%
6 559
 
4.1%
Other values (231) 5791
42.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7137
52.8%
Other Letter 4934
36.5%
Uppercase Letter 914
 
6.8%
Dash Punctuation 221
 
1.6%
Close Punctuation 89
 
0.7%
Open Punctuation 89
 
0.7%
Space Separator 73
 
0.5%
Lowercase Letter 33
 
0.2%
Other Punctuation 17
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홀 729
 
14.8%
남 231
 
4.7%
번 197
 
4.0%
동 164
 
3.3%
서 151
 
3.1%
종 144
 
2.9%
최 142
 
2.9%
스 130
 
2.6%
크 119
 
2.4%
이 118
 
2.4%
Other values (182) 2809
56.9%
Uppercase Letter
ValueCountFrequency (%)
L 144
15.8%
S 111
12.1%
V 81
8.9%
M 63
 
6.9%
C 55
 
6.0%
A 54
 
5.9%
P 53
 
5.8%
N 53
 
5.8%
B 51
 
5.6%
H 51
 
5.6%
Other values (11) 198
21.7%
Lowercase Letter
ValueCountFrequency (%)
s 5
15.2%
e 5
15.2%
k 5
15.2%
u 5
15.2%
i 3
9.1%
a 2
 
6.1%
t 2
 
6.1%
l 2
 
6.1%
p 2
 
6.1%
v 1
 
3.0%
Decimal Number
ValueCountFrequency (%)
1 1905
26.7%
2 758
 
10.6%
8 669
 
9.4%
9 663
 
9.3%
3 661
 
9.3%
4 605
 
8.5%
5 588
 
8.2%
7 579
 
8.1%
6 559
 
7.8%
0 150
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/ 8
47.1%
, 8
47.1%
' 1
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 221
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 89
100.0%
Space Separator
ValueCountFrequency (%)
73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7626
56.5%
Hangul 4934
36.5%
Latin 947
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홀 729
 
14.8%
남 231
 
4.7%
번 197
 
4.0%
동 164
 
3.3%
서 151
 
3.1%
종 144
 
2.9%
최 142
 
2.9%
스 130
 
2.6%
크 119
 
2.4%
이 118
 
2.4%
Other values (182) 2809
56.9%
Latin
ValueCountFrequency (%)
L 144
15.2%
S 111
11.7%
V 81
 
8.6%
M 63
 
6.7%
C 55
 
5.8%
A 54
 
5.7%
P 53
 
5.6%
N 53
 
5.6%
B 51
 
5.4%
H 51
 
5.4%
Other values (22) 231
24.4%
Common
ValueCountFrequency (%)
1 1905
25.0%
2 758
 
9.9%
8 669
 
8.8%
9 663
 
8.7%
3 661
 
8.7%
4 605
 
7.9%
5 588
 
7.7%
7 579
 
7.6%
6 559
 
7.3%
- 221
 
2.9%
Other values (7) 418
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8573
63.5%
Hangul 4934
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1905
22.2%
2 758
 
8.8%
8 669
 
7.8%
9 663
 
7.7%
3 661
 
7.7%
4 605
 
7.1%
5 588
 
6.9%
7 579
 
6.8%
6 559
 
6.5%
- 221
 
2.6%
Other values (39) 1365
15.9%
Hangul
ValueCountFrequency (%)
홀 729
 
14.8%
남 231
 
4.7%
번 197
 
4.0%
동 164
 
3.3%
서 151
 
3.1%
종 144
 
2.9%
최 142
 
2.9%
스 130
 
2.6%
크 119
 
2.4%
이 118
 
2.4%
Other values (182) 2809
56.9%

검사항목
Categorical

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
Tebuconazole
1479 
Thifluzamide
1466 
Azoxystrobin
1038 
Flutolanil
930 
Carbendazim
409 
Other values (15)
594 

Length

Max length25
Median length12
Mean length11.529243
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFlutolanil
2nd rowPropamocarb-hydrochloride
3rd rowPropamocarb-hydrochloride
4th rowAzoxystrobin
5th rowFlutolanil

Common Values

ValueCountFrequency (%)
Tebuconazole 1479
25.0%
Thifluzamide 1466
24.8%
Azoxystrobin 1038
17.5%
Flutolanil 930
15.7%
Carbendazim 409
 
6.9%
Iprodione 194
 
3.3%
Fenitrothion 75
 
1.3%
Diazinon 54
 
0.9%
Acephate 51
 
0.9%
Thiophanate-methyl 41
 
0.7%
Other values (10) 179
 
3.0%

Length

2023-12-13T04:50:26.266538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tebuconazole 1479
25.0%
thifluzamide 1466
24.8%
azoxystrobin 1038
17.5%
flutolanil 930
15.7%
carbendazim 409
 
6.9%
iprodione 194
 
3.3%
fenitrothion 75
 
1.3%
diazinon 54
 
0.9%
acephate 51
 
0.9%
thiophanate-methyl 41
 
0.7%
Other values (10) 179
 
3.0%

검출농도_토양_그린
Text

Distinct83
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
2023-12-13T04:50:26.511804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3618999
Min length1

Characters and Unicode

Total characters19889
Distinct characters16
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

Unique30 ?
Unique (%)0.5%

Sample

1st row0.01
2nd row0.03
3rd row0.03
4th row0.02
5th row0.01
ValueCountFrequency (%)
불검출 1970
33.3%
미검사 1708
28.9%
0.01 450
 
7.6%
0.02 426
 
7.2%
0.03 220
 
3.7%
0.04 178
 
3.0%
0.05 146
 
2.5%
0.06 89
 
1.5%
0.07 66
 
1.1%
0.12 62
 
1.0%
Other values (73) 601
 
10.2%
2023-12-13T04:50:26.925085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3890
19.6%
검 3678
18.5%
. 2237
11.2%
불 1970
9.9%
출 1970
9.9%
미 1708
8.6%
사 1708
8.6%
1 895
 
4.5%
2 617
 
3.1%
3 317
 
1.6%
Other values (6) 899
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11034
55.5%
Decimal Number 6618
33.3%
Other Punctuation 2237
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3890
58.8%
1 895
 
13.5%
2 617
 
9.3%
3 317
 
4.8%
4 272
 
4.1%
5 208
 
3.1%
6 145
 
2.2%
7 109
 
1.6%
8 98
 
1.5%
9 67
 
1.0%
Other Letter
ValueCountFrequency (%)
검 3678
33.3%
불 1970
17.9%
출 1970
17.9%
미 1708
15.5%
사 1708
15.5%
Other Punctuation
ValueCountFrequency (%)
. 2237
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11034
55.5%
Common 8855
44.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3890
43.9%
. 2237
25.3%
1 895
 
10.1%
2 617
 
7.0%
3 317
 
3.6%
4 272
 
3.1%
5 208
 
2.3%
6 145
 
1.6%
7 109
 
1.2%
8 98
 
1.1%
Hangul
ValueCountFrequency (%)
검 3678
33.3%
불 1970
17.9%
출 1970
17.9%
미 1708
15.5%
사 1708
15.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11034
55.5%
ASCII 8855
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3890
43.9%
. 2237
25.3%
1 895
 
10.1%
2 617
 
7.0%
3 317
 
3.6%
4 272
 
3.1%
5 208
 
2.3%
6 145
 
1.6%
7 109
 
1.2%
8 98
 
1.1%
Hangul
ValueCountFrequency (%)
검 3678
33.3%
불 1970
17.9%
출 1970
17.9%
미 1708
15.5%
사 1708
15.5%

검출농도_토양_페어웨이
Text

Distinct112
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
2023-12-13T04:50:27.200774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.3742394
Min length1

Characters and Unicode

Total characters19962
Distinct characters16
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

Unique37 ?
Unique (%)0.6%

Sample

1st row0.01
2nd row불검출
3rd row불검출
4th row불검출
5th row0.01
ValueCountFrequency (%)
불검출 1888
31.9%
미검사 1711
28.9%
0.02 392
 
6.6%
0.01 375
 
6.3%
0.03 215
 
3.6%
0.04 163
 
2.8%
0.05 135
 
2.3%
0.06 96
 
1.6%
0.07 90
 
1.5%
0.08 77
 
1.3%
Other values (102) 774
13.1%
2023-12-13T04:50:27.606940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3905
19.6%
검 3599
18.0%
. 2316
11.6%
불 1888
9.5%
출 1888
9.5%
미 1711
8.6%
사 1711
8.6%
1 864
 
4.3%
2 625
 
3.1%
3 360
 
1.8%
Other values (6) 1095
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10797
54.1%
Decimal Number 6849
34.3%
Other Punctuation 2316
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3905
57.0%
1 864
 
12.6%
2 625
 
9.1%
3 360
 
5.3%
4 275
 
4.0%
5 213
 
3.1%
6 194
 
2.8%
7 147
 
2.1%
8 146
 
2.1%
9 120
 
1.8%
Other Letter
ValueCountFrequency (%)
검 3599
33.3%
불 1888
17.5%
출 1888
17.5%
미 1711
15.8%
사 1711
15.8%
Other Punctuation
ValueCountFrequency (%)
. 2316
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10797
54.1%
Common 9165
45.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3905
42.6%
. 2316
25.3%
1 864
 
9.4%
2 625
 
6.8%
3 360
 
3.9%
4 275
 
3.0%
5 213
 
2.3%
6 194
 
2.1%
7 147
 
1.6%
8 146
 
1.6%
Hangul
ValueCountFrequency (%)
검 3599
33.3%
불 1888
17.5%
출 1888
17.5%
미 1711
15.8%
사 1711
15.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10797
54.1%
ASCII 9165
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3905
42.6%
. 2316
25.3%
1 864
 
9.4%
2 625
 
6.8%
3 360
 
3.9%
4 275
 
3.0%
5 213
 
2.3%
6 194
 
2.1%
7 147
 
1.6%
8 146
 
1.6%
Hangul
ValueCountFrequency (%)
검 3599
33.3%
불 1888
17.5%
출 1888
17.5%
미 1711
15.8%
사 1711
15.8%

검출농도_수질_유출구
Text

Distinct125
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
2023-12-13T04:50:27.861633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.4213996
Min length3

Characters and Unicode

Total characters20241
Distinct characters16
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

Unique32 ?
Unique (%)0.5%

Sample

1st row미검사
2nd row미검사
3rd row미검사
4th row미검사
5th row미검사
ValueCountFrequency (%)
미검사 4620
78.1%
불검출 435
 
7.4%
0.0007 60
 
1.0%
0.0006 59
 
1.0%
0.0009 44
 
0.7%
0.0008 44
 
0.7%
0.0013 32
 
0.5%
0.0005 32
 
0.5%
0.001 31
 
0.5%
0.0011 30
 
0.5%
Other values (115) 529
 
8.9%
2023-12-13T04:50:28.360253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
검 5055
25.0%
미 4620
22.8%
사 4620
22.8%
0 2773
13.7%
. 861
 
4.3%
불 435
 
2.1%
출 435
 
2.1%
1 350
 
1.7%
2 210
 
1.0%
3 145
 
0.7%
Other values (6) 737
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15165
74.9%
Decimal Number 4215
 
20.8%
Other Punctuation 861
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2773
65.8%
1 350
 
8.3%
2 210
 
5.0%
3 145
 
3.4%
6 144
 
3.4%
5 134
 
3.2%
7 132
 
3.1%
8 115
 
2.7%
9 108
 
2.6%
4 104
 
2.5%
Other Letter
ValueCountFrequency (%)
검 5055
33.3%
미 4620
30.5%
사 4620
30.5%
불 435
 
2.9%
출 435
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 861
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15165
74.9%
Common 5076
 
25.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2773
54.6%
. 861
 
17.0%
1 350
 
6.9%
2 210
 
4.1%
3 145
 
2.9%
6 144
 
2.8%
5 134
 
2.6%
7 132
 
2.6%
8 115
 
2.3%
9 108
 
2.1%
Hangul
ValueCountFrequency (%)
검 5055
33.3%
미 4620
30.5%
사 4620
30.5%
불 435
 
2.9%
출 435
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15165
74.9%
ASCII 5076
 
25.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
검 5055
33.3%
미 4620
30.5%
사 4620
30.5%
불 435
 
2.9%
출 435
 
2.9%
ASCII
ValueCountFrequency (%)
0 2773
54.6%
. 861
 
17.0%
1 350
 
6.9%
2 210
 
4.1%
3 145
 
2.9%
6 144
 
2.8%
5 134
 
2.6%
7 132
 
2.6%
8 115
 
2.3%
9 108
 
2.1%

검출농도_수질_연못
Text

Distinct193
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
2023-12-13T04:50:28.636583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.8235294
Min length3

Characters and Unicode

Total characters22620
Distinct characters16
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

Unique79 ?
Unique (%)1.3%

Sample

1st row미검사
2nd row미검사
3rd row미검사
4th row미검사
5th row미검사
ValueCountFrequency (%)
미검사 3600
60.9%
불검출 634
 
10.7%
0.0007 119
 
2.0%
0.0006 105
 
1.8%
0.0008 105
 
1.8%
0.0009 74
 
1.3%
0.001 72
 
1.2%
0.0011 61
 
1.0%
0.0012 60
 
1.0%
0.0013 51
 
0.9%
Other values (183) 1035
 
17.5%
2023-12-13T04:50:29.065706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5362
23.7%
검 4234
18.7%
미 3600
15.9%
사 3600
15.9%
. 1682
 
7.4%
1 799
 
3.5%
불 634
 
2.8%
출 634
 
2.8%
2 412
 
1.8%
6 279
 
1.2%
Other values (6) 1384
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12702
56.2%
Decimal Number 8236
36.4%
Other Punctuation 1682
 
7.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5362
65.1%
1 799
 
9.7%
2 412
 
5.0%
6 279
 
3.4%
3 265
 
3.2%
7 252
 
3.1%
8 235
 
2.9%
4 223
 
2.7%
5 213
 
2.6%
9 196
 
2.4%
Other Letter
ValueCountFrequency (%)
검 4234
33.3%
미 3600
28.3%
사 3600
28.3%
불 634
 
5.0%
출 634
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 1682
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12702
56.2%
Common 9918
43.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5362
54.1%
. 1682
 
17.0%
1 799
 
8.1%
2 412
 
4.2%
6 279
 
2.8%
3 265
 
2.7%
7 252
 
2.5%
8 235
 
2.4%
4 223
 
2.2%
5 213
 
2.1%
Hangul
ValueCountFrequency (%)
검 4234
33.3%
미 3600
28.3%
사 3600
28.3%
불 634
 
5.0%
출 634
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12702
56.2%
ASCII 9918
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5362
54.1%
. 1682
 
17.0%
1 799
 
8.1%
2 412
 
4.2%
6 279
 
2.8%
3 265
 
2.7%
7 252
 
2.5%
8 235
 
2.4%
4 223
 
2.2%
5 213
 
2.1%
Hangul
ValueCountFrequency (%)
검 4234
33.3%
미 3600
28.3%
사 3600
28.3%
불 634
 
5.0%
출 634
 
5.0%

분기
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.3 KiB
상반기
3013 
하반기
2903 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상반기
2nd row하반기
3rd row상반기
4th row상반기
5th row상반기

Common Values

ValueCountFrequency (%)
상반기 3013
50.9%
하반기 2903
49.1%

Length

2023-12-13T04:50:29.262154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:29.376466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상반기 3013
50.9%
하반기 2903
49.1%

Interactions

2023-12-13T04:50:23.528021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:50:29.458234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역골프장번호검사항목검출농도_토양_그린분기
지역1.0000.9340.5650.4730.186
골프장번호0.9341.0000.4810.4000.219
검사항목0.5650.4811.0000.0000.161
검출농도_토양_그린0.4730.4000.0001.0000.145
분기0.1860.2190.1610.1451.000
2023-12-13T04:50:29.563858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분기검사항목
지역1.0000.1670.207
분기0.1671.0000.127
검사항목0.2070.1271.000
2023-12-13T04:50:29.952001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
골프장번호지역검사항목분기
골프장번호1.0000.7330.1710.168
지역0.7331.0000.2070.167
검사항목0.1710.2071.0000.127
분기0.1680.1670.1271.000

Missing values

2023-12-13T04:50:23.714425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:50:23.917630image/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

지역골프장번호시료채취일자시료채취_홀번호검사항목검출농도_토양_그린검출농도_토양_페어웨이검출농도_수질_유출구검출농도_수질_연못분기
0서울특별시12021-04-2317Flutolanil0.010.01미검사미검사상반기
1서울특별시12021-08-273Propamocarb-hydrochloride0.03불검출미검사미검사하반기
2서울특별시12021-04-234Propamocarb-hydrochloride0.03불검출미검사미검사상반기
3서울특별시12021-04-234Azoxystrobin0.02불검출미검사미검사상반기
4서울특별시12021-04-234Flutolanil0.010.01미검사미검사상반기
5서울특별시12021-04-236Flutolanil불검출0.01불검출미검사상반기
6서울특별시12021-04-236Thifluzamide불검출0.01불검출미검사상반기
7서울특별시12021-04-236Tebuconazole0.02불검출불검출미검사상반기
8서울특별시12021-04-237Tebuconazole미검사미검사0.0007미검사상반기
9서울특별시12021-08-277Propamocarb-hydrochloride0.02불검출미검사미검사하반기
지역골프장번호시료채취일자시료채취_홀번호검사항목검출농도_토양_그린검출농도_토양_페어웨이검출농도_수질_유출구검출농도_수질_연못분기
5906제주특별자치도5222021-04-22P4Azoxystrobin0.19불검출미검사0.001상반기
5907제주특별자치도5222021-09-24P4Tebuconazole미검사미검사미검사0.0007하반기
5908제주특별자치도5222021-09-24P4Azoxystrobin미검사미검사미검사0.0006하반기
5909제주특별자치도5222021-09-24P5Tebuconazole0.040.04미검사미검사하반기
5910제주특별자치도5222021-04-22P9Tebuconazole불검출0.15미검사0.0007상반기
5911제주특별자치도5222021-04-22P9Azoxystrobin불검출불검출미검사0.0008상반기
5912제주특별자치도5222021-04-22S1Tebuconazole0.16불검출미검사미검사상반기
5913제주특별자치도5222021-04-22S1Azoxystrobin0.18불검출미검사미검사상반기
5914제주특별자치도5222021-09-24S9Tebuconazole0.050.03미검사미검사하반기
5915제주특별자치도5222021-09-24S9Azoxystrobin0.040.04미검사미검사하반기