Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory878.9 KiB
Average record size in memory90.0 B

Variable types

Text3
Categorical5
Numeric2

Dataset

Description경상남도 농작물진단처방 분석의뢰 매칭 테이블 데이터입니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15049544

Alerts

단위 is highly overall correlated with 분류코드(대) and 3 other fieldsHigh correlation
비용 is highly overall correlated with 분류코드(대) and 2 other fieldsHigh correlation
분류코드(대) is highly overall correlated with 비용 and 2 other fieldsHigh correlation
분석기준 is highly overall correlated with 분류코드(대) and 2 other fieldsHigh correlation
기타항목여부 is highly overall correlated with 단위High correlation
분류코드(대) is highly imbalanced (77.4%)Imbalance
비용 is highly imbalanced (58.2%)Imbalance
분석기준 is highly imbalanced (58.7%)Imbalance
단위 is highly imbalanced (83.8%)Imbalance
기타항목여부 is highly imbalanced (94.1%)Imbalance

Reproduction

Analysis started2023-12-11 00:49:11.701310
Analysis finished2023-12-11 00:49:13.577398
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류코드(소)
Text

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:49:14.024430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.1837
Min length1

Characters and Unicode

Total characters11837
Distinct characters12
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row4
3rd row8
4th row5
5th row3
ValueCountFrequency (%)
4 940
9.4%
7 940
9.4%
3 925
9.2%
1 902
9.0%
2 901
9.0%
9 901
9.0%
5 900
9.0%
8 899
9.0%
6 894
8.9%
10 887
8.9%
Other values (48) 911
9.1%
2023-12-11T09:49:14.437313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2009
17.0%
4 1527
12.9%
5 1161
9.8%
3 1159
9.8%
2 1047
8.8%
8 1030
8.7%
7 1004
8.5%
9 951
8.0%
0 937
7.9%
6 934
7.9%
Other values (2) 78
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11759
99.3%
Uppercase Letter 78
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2009
17.1%
4 1527
13.0%
5 1161
9.9%
3 1159
9.9%
2 1047
8.9%
8 1030
8.8%
7 1004
8.5%
9 951
8.1%
0 937
8.0%
6 934
7.9%
Uppercase Letter
ValueCountFrequency (%)
I 39
50.0%
N 39
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11759
99.3%
Latin 78
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2009
17.1%
4 1527
13.0%
5 1161
9.9%
3 1159
9.9%
2 1047
8.9%
8 1030
8.8%
7 1004
8.5%
9 951
8.1%
0 937
8.0%
6 934
7.9%
Latin
ValueCountFrequency (%)
I 39
50.0%
N 39
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2009
17.0%
4 1527
12.9%
5 1161
9.8%
3 1159
9.8%
2 1047
8.8%
8 1030
8.7%
7 1004
8.5%
9 951
8.0%
0 937
7.9%
6 934
7.9%
Other values (2) 78
 
0.7%

분류코드(대)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
A
9107 
E
 
721
C
 
77
D
 
50
B
 
45

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
A 9107
91.1%
E 721
 
7.2%
C 77
 
0.8%
D 50
 
0.5%
B 45
 
0.4%

Length

2023-12-11T09:49:14.612964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:49:14.724888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 9107
91.1%
e 721
 
7.2%
c 77
 
0.8%
d 50
 
0.5%
b 45
 
0.4%

항목명
Text

Distinct60
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:49:14.972093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length7.711
Min length1

Characters and Unicode

Total characters77110
Distinct characters113
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

Unique10 ?
Unique (%)0.1%

Sample

1st row전기전도도(EC)
2nd row칼륨(K)
3rd row염소이온(Cl-)
4th row칼슘(Ca)
5th row질산성질소(NO3-N)
ValueCountFrequency (%)
칼륨(k 944
9.4%
나트륨(na 939
9.4%
질산성질소(no3-n 921
9.2%
칼슘(ca 903
9.0%
전기전도도(ec 902
9.0%
수소이온(ph 901
9.0%
황산이온(so4 901
9.0%
염소이온(cl 898
9.0%
마그네슘(mg 894
8.9%
중탄산(hco3 884
8.8%
Other values (51) 937
9.3%
2023-12-11T09:49:15.449007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 9164
 
11.9%
) 9164
 
11.9%
C 3601
 
4.7%
소 2814
 
3.6%
N 2783
 
3.6%
산 2729
 
3.5%
온 2716
 
3.5%
이 2716
 
3.5%
O 2715
 
3.5%
륨 1896
 
2.5%
Other values (103) 36812
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34933
45.3%
Uppercase Letter 14573
18.9%
Open Punctuation 9178
 
11.9%
Close Punctuation 9178
 
11.9%
Lowercase Letter 4602
 
6.0%
Decimal Number 2750
 
3.6%
Dash Punctuation 1830
 
2.4%
Other Punctuation 42
 
0.1%
Space Separator 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 2814
 
8.1%
산 2729
 
7.8%
온 2716
 
7.8%
이 2716
 
7.8%
륨 1896
 
5.4%
도 1870
 
5.4%
질 1869
 
5.4%
칼 1860
 
5.3%
전 1820
 
5.2%
슘 1805
 
5.2%
Other values (69) 12838
36.8%
Uppercase Letter
ValueCountFrequency (%)
C 3601
24.7%
N 2783
19.1%
O 2715
18.6%
H 1803
12.4%
K 944
 
6.5%
E 908
 
6.2%
M 904
 
6.2%
S 902
 
6.2%
F 7
 
< 0.1%
P 4
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
a 1842
40.0%
p 918
19.9%
l 906
19.7%
g 894
19.4%
v 28
 
0.6%
e 7
 
0.2%
n 6
 
0.1%
i 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
3 1805
65.6%
4 903
32.8%
5 16
 
0.6%
1 14
 
0.5%
6 10
 
0.4%
2 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 14
33.3%
/ 14
33.3%
: 14
33.3%
Open Punctuation
ValueCountFrequency (%)
( 9164
99.8%
[ 14
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 9164
99.8%
] 14
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 1830
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34933
45.3%
Common 23002
29.8%
Latin 19175
24.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 2814
 
8.1%
산 2729
 
7.8%
온 2716
 
7.8%
이 2716
 
7.8%
륨 1896
 
5.4%
도 1870
 
5.4%
질 1869
 
5.4%
칼 1860
 
5.3%
전 1820
 
5.2%
슘 1805
 
5.2%
Other values (69) 12838
36.8%
Latin
ValueCountFrequency (%)
C 3601
18.8%
N 2783
14.5%
O 2715
14.2%
a 1842
9.6%
H 1803
9.4%
K 944
 
4.9%
p 918
 
4.8%
E 908
 
4.7%
l 906
 
4.7%
M 904
 
4.7%
Other values (9) 1851
9.7%
Common
ValueCountFrequency (%)
( 9164
39.8%
) 9164
39.8%
- 1830
 
8.0%
3 1805
 
7.8%
4 903
 
3.9%
24
 
0.1%
5 16
 
0.1%
, 14
 
0.1%
/ 14
 
0.1%
] 14
 
0.1%
Other values (5) 54
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42177
54.7%
Hangul 34933
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 9164
21.7%
) 9164
21.7%
C 3601
 
8.5%
N 2783
 
6.6%
O 2715
 
6.4%
a 1842
 
4.4%
- 1830
 
4.3%
3 1805
 
4.3%
H 1803
 
4.3%
K 944
 
2.2%
Other values (24) 6526
15.5%
Hangul
ValueCountFrequency (%)
소 2814
 
8.1%
산 2729
 
7.8%
온 2716
 
7.8%
이 2716
 
7.8%
륨 1896
 
5.4%
도 1870
 
5.4%
질 1869
 
5.4%
칼 1860
 
5.3%
전 1820
 
5.2%
슘 1805
 
5.2%
Other values (69) 12838
36.8%

비용
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수질오염공정시험기준
7312 
STD. Method
1785 
농촌진흥청고시 제2017-19
 
726
농촌진흥청토양및식물체분석법
 
91
토양오염공정시험기준
 
76
Other values (2)
 
10

Length

Max length16
Median length10
Mean length10.6418
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
수질오염공정시험기준 7312
73.1%
STD. Method 1785
 
17.8%
농촌진흥청고시 제2017-19 726
 
7.3%
농촌진흥청토양및식물체분석법 91
 
0.9%
토양오염공정시험기준 76
 
0.8%
- 9
 
0.1%
오류점검 1
 
< 0.1%

Length

2023-12-11T09:49:15.612092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:49:15.736066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수질오염공정시험기준 7312
58.4%
std 1785
 
14.3%
method 1785
 
14.3%
농촌진흥청고시 726
 
5.8%
제2017-19 726
 
5.8%
농촌진흥청토양및식물체분석법 91
 
0.7%
토양오염공정시험기준 76
 
0.6%
9
 
0.1%
오류점검 1
 
< 0.1%

분석기준
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
mg/L
7302 
-
973 
dS/m
908 
mg/kg
 
510
%
 
264
Other values (5)
 
43

Length

Max length8
Median length4
Mean length3.6922
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowdS/m
2nd rowmg/L
3rd rowmg/L
4th rowmg/L
5th rowmg/L

Common Values

ValueCountFrequency (%)
mg/L 7302
73.0%
- 973
 
9.7%
dS/m 908
 
9.1%
mg/kg 510
 
5.1%
% 264
 
2.6%
cmolc/kg 21
 
0.2%
cmolc/L 14
 
0.1%
g/kg 6
 
0.1%
7.08 1
 
< 0.1%
` 1
 
< 0.1%

Length

2023-12-11T09:49:15.904263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:49:16.063411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mg/l 7302
73.0%
1238
 
12.4%
ds/m 908
 
9.1%
mg/kg 510
 
5.1%
cmolc/kg 21
 
0.2%
cmolc/l 14
 
0.1%
g/kg 6
 
0.1%
7.08 1
 
< 0.1%

단위
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
8,500
9096 
16,000
 
511
7,500
 
118
9,900
 
81
11,700
 
76
Other values (10)
 
118

Length

Max length6
Median length5
Mean length5.0652
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row8,500
2nd row8,500
3rd row8,500
4th row8,500
5th row8,500

Common Values

ValueCountFrequency (%)
8,500 9096
91.0%
16,000 511
 
5.1%
7,500 118
 
1.2%
9,900 81
 
0.8%
11,700 76
 
0.8%
14,300 50
 
0.5%
43,800 29
 
0.3%
- 9
 
0.1%
9,600 7
 
0.1%
22,900 6
 
0.1%
Other values (5) 17
 
0.2%

Length

2023-12-11T09:49:16.201430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
8,500 9096
91.0%
16,000 511
 
5.1%
7,500 118
 
1.2%
9,900 81
 
0.8%
11,700 76
 
0.8%
14,300 50
 
0.5%
43,800 29
 
0.3%
9
 
0.1%
9,600 7
 
0.1%
22,900 6
 
0.1%
Other values (5) 17
 
0.2%

매칭할고유키
Real number (ℝ)

Distinct1647
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1062.7617
Minimum237
Maximum1895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:49:16.342918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum237
5-th percentile312
Q1651
median1052
Q31488
95-th percentile1817
Maximum1895
Range1658
Interquartile range (IQR)837

Descriptive statistics

Standard deviation482.91169
Coefficient of variation (CV)0.4543932
Kurtosis-1.2035584
Mean1062.7617
Median Absolute Deviation (MAD)419
Skewness0.02489107
Sum10627617
Variance233203.7
MonotonicityNot monotonic
2023-12-11T09:49:16.500143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
297 16
 
0.2%
361 13
 
0.1%
580 13
 
0.1%
284 12
 
0.1%
1594 11
 
0.1%
396 11
 
0.1%
1399 11
 
0.1%
1230 11
 
0.1%
360 10
 
0.1%
266 10
 
0.1%
Other values (1637) 9882
98.8%
ValueCountFrequency (%)
237 7
0.1%
238 1
 
< 0.1%
239 6
0.1%
240 7
0.1%
241 7
0.1%
242 7
0.1%
243 5
0.1%
244 4
< 0.1%
245 5
0.1%
246 7
0.1%
ValueCountFrequency (%)
1895 8
0.1%
1894 5
0.1%
1893 5
0.1%
1892 7
0.1%
1891 7
0.1%
1890 6
0.1%
1889 6
0.1%
1888 8
0.1%
1887 1
 
< 0.1%
1886 5
0.1%

기타항목여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
9896 
Y
 
65
I
 
39

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 9896
99.0%
Y 65
 
0.7%
I 39
 
0.4%

Length

2023-12-11T09:49:16.641035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:49:16.774733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 9896
99.0%
y 65
 
0.7%
i 39
 
0.4%

항목번호
Real number (ℝ)

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.403
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:49:16.890921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile10
Maximum21
Range20
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9621392
Coefficient of variation (CV)0.54823971
Kurtosis-0.74339174
Mean5.403
Median Absolute Deviation (MAD)3
Skewness0.20670282
Sum54030
Variance8.7742684
MonotonicityNot monotonic
2023-12-11T09:49:17.075238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3 1084
10.8%
2 1071
10.7%
1 1067
10.7%
4 1038
10.4%
7 979
9.8%
5 952
9.5%
6 941
9.4%
8 938
9.4%
9 923
9.2%
10 900
9.0%
Other values (11) 107
 
1.1%
ValueCountFrequency (%)
1 1067
10.7%
2 1071
10.7%
3 1084
10.8%
4 1038
10.4%
5 952
9.5%
6 941
9.4%
7 979
9.8%
8 938
9.4%
9 923
9.2%
10 900
9.0%
ValueCountFrequency (%)
21 2
 
< 0.1%
20 2
 
< 0.1%
19 1
 
< 0.1%
18 1
 
< 0.1%
17 1
 
< 0.1%
16 3
 
< 0.1%
15 4
 
< 0.1%
14 10
 
0.1%
13 12
0.1%
12 26
0.3%

기타
Text

Distinct1930
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:49:17.423898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length4
Mean length3.3401
Min length1

Characters and Unicode

Total characters33401
Distinct characters31
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique492 ?
Unique (%)4.9%

Sample

1st row0.15
2nd row0.97
3rd row17.7
4th row28.4
5th row9.44
ValueCountFrequency (%)
968
 
9.7%
흔적 118
 
1.2%
7 69
 
0.7%
7.3 62
 
0.6%
6.9 60
 
0.6%
7.2 55
 
0.5%
6.7 54
 
0.5%
6.8 52
 
0.5%
6.6 50
 
0.5%
7.5 48
 
0.5%
Other values (1922) 8468
84.6%
2023-12-11T09:49:17.945505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7373
22.1%
1 4103
12.3%
2 3000
9.0%
3 2459
 
7.4%
4 2397
 
7.2%
0 2391
 
7.2%
7 2374
 
7.1%
6 2280
 
6.8%
5 2070
 
6.2%
8 1862
 
5.6%
Other values (21) 3092
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24690
73.9%
Other Punctuation 7375
 
22.1%
Dash Punctuation 968
 
2.9%
Other Letter 358
 
1.1%
Space Separator 4
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
흔 118
33.0%
적 118
33.0%
하 22
 
6.1%
이 22
 
6.1%
부 18
 
5.0%
숙 18
 
5.0%
완 17
 
4.7%
료 17
 
4.7%
체 2
 
0.6%
통 2
 
0.6%
Other values (3) 4
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 4103
16.6%
2 3000
12.2%
3 2459
10.0%
4 2397
9.7%
0 2391
9.7%
7 2374
9.6%
6 2280
9.2%
5 2070
8.4%
8 1862
7.5%
9 1754
7.1%
Other Punctuation
ValueCountFrequency (%)
. 7373
> 99.9%
, 2
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
㎜ 1
50.0%
㎛ 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 968
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33043
98.9%
Hangul 358
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7373
22.3%
1 4103
12.4%
2 3000
9.1%
3 2459
 
7.4%
4 2397
 
7.3%
0 2391
 
7.2%
7 2374
 
7.2%
6 2280
 
6.9%
5 2070
 
6.3%
8 1862
 
5.6%
Other values (8) 2734
 
8.3%
Hangul
ValueCountFrequency (%)
흔 118
33.0%
적 118
33.0%
하 22
 
6.1%
이 22
 
6.1%
부 18
 
5.0%
숙 18
 
5.0%
완 17
 
4.7%
료 17
 
4.7%
체 2
 
0.6%
통 2
 
0.6%
Other values (3) 4
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33041
98.9%
Hangul 358
 
1.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7373
22.3%
1 4103
12.4%
2 3000
9.1%
3 2459
 
7.4%
4 2397
 
7.3%
0 2391
 
7.2%
7 2374
 
7.2%
6 2280
 
6.9%
5 2070
 
6.3%
8 1862
 
5.6%
Other values (6) 2732
 
8.3%
Hangul
ValueCountFrequency (%)
흔 118
33.0%
적 118
33.0%
하 22
 
6.1%
이 22
 
6.1%
부 18
 
5.0%
숙 18
 
5.0%
완 17
 
4.7%
료 17
 
4.7%
체 2
 
0.6%
통 2
 
0.6%
Other values (3) 4
 
1.1%
CJK Compat
ValueCountFrequency (%)
㎜ 1
50.0%
㎛ 1
50.0%

Interactions

2023-12-11T09:49:13.046828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:49:12.799732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:49:13.172299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:49:12.919254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:49:18.116418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류코드(소)분류코드(대)항목명비용분석기준단위매칭할고유키기타항목여부항목번호
분류코드(소)1.0000.9940.9970.9700.9710.9780.2250.9520.954
분류코드(대)0.9941.0000.9630.8690.9160.9840.3010.2080.359
항목명0.9970.9631.0000.9880.9801.0000.2280.9880.974
비용0.9700.8690.9881.0000.7440.9760.1940.5020.694
분석기준0.9710.9160.9800.7441.0000.8810.2110.3050.750
단위0.9780.9841.0000.9760.8811.0000.2260.8320.543
매칭할고유키0.2250.3010.2280.1940.2110.2261.0000.1030.122
기타항목여부0.9520.2080.9880.5020.3050.8320.1031.0000.625
항목번호0.9540.3590.9740.6940.7500.5430.1220.6251.000
2023-12-11T09:49:18.288846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기타항목여부단위비용분석기준분류코드(대)
기타항목여부1.0000.5700.3900.1910.159
단위0.5701.0000.9060.5740.826
비용0.3900.9061.0000.5010.792
분석기준0.1910.5740.5011.0000.617
분류코드(대)0.1590.8260.7920.6171.000
2023-12-11T09:49:18.418372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
매칭할고유키항목번호분류코드(대)비용분석기준단위기타항목여부
매칭할고유키1.000-0.0100.1300.0990.0660.0860.061
항목번호-0.0101.0000.1340.3430.2480.2390.400
분류코드(대)0.1300.1341.0000.7920.6170.8260.159
비용0.0990.3430.7921.0000.5010.9060.390
분석기준0.0660.2480.6170.5011.0000.5740.191
단위0.0860.2390.8260.9060.5741.0000.570
기타항목여부0.0610.4000.1590.3900.1910.5701.000

Missing values

2023-12-11T09:49:13.344680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:49:13.504667image/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

분류코드(소)분류코드(대)항목명비용분석기준단위매칭할고유키기타항목여부항목번호기타
88062A전기전도도(EC)수질오염공정시험기준dS/m8,5001114N20.15
81054A칼륨(K)수질오염공정시험기준mg/L8,5001077N40.97
60888A염소이온(Cl-)수질오염공정시험기준mg/L8,500931N817.7
78085A칼슘(Ca)수질오염공정시험기준mg/L8,5001328N528.4
45003A질산성질소(NO3-N)수질오염공정시험기준mg/L8,500727N39.44
94706A마그네슘(Mg)수질오염공정시험기준mg/L8,5001504N624.3
48678A염소이온(Cl-)수질오염공정시험기준mg/L8,500742N811.8
134073A질산성질소(NO3-N)수질오염공정시험기준mg/L8,5001632N30.15
58931A수소이온(pH)수질오염공정시험기준-8,500919N17.3
36376A마그네슘(Mg)수질오염공정시험기준mg/L8,500539N65.8
분류코드(소)분류코드(대)항목명비용분석기준단위매칭할고유키기타항목여부항목번호기타
143611A수소이온(pH)수질오염공정시험기준-8,5001841N17.8
1029410A중탄산(HCO3)STD. Methodmg/L8,5001517N1051
33617A나트륨(Na)수질오염공정시험기준mg/L8,500635N723.3
114444A칼륨(K)수질오염공정시험기준mg/L8,5001220N41.89
1116243E수분농촌진흥청고시 제2017-19%7,5001092N330.5
122219A황산이온(SO4)STD. Methodmg/L8,5001742N99.81
57297A나트륨(Na)수질오염공정시험기준mg/L8,500845N712.8
118882A전기전도도(EC)수질오염공정시험기준dS/m8,5001270N20.13
111908A염소이온(Cl-)수질오염공정시험기준mg/L8,5001185N826
131175A칼슘(Ca)수질오염공정시험기준mg/L8,5001723N526.7