Overview

Dataset statistics

Number of variables7
Number of observations883
Missing cells36
Missing cells (%)0.6%
Duplicate rows5
Duplicate rows (%)0.6%
Total size in memory50.1 KiB
Average record size in memory58.1 B

Variable types

Text3
Categorical2
Numeric2

Dataset

Description시험구분(종별),시험항목,시험방법,단위,시험수수료(원),처리기간(일),비고
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20881/S/1/datasetView.do

Alerts

Dataset has 5 (0.6%) duplicate rowsDuplicates
단위 is highly imbalanced (50.9%)Imbalance
비고 is highly imbalanced (81.9%)Imbalance
시험방법 has 35 (4.0%) missing valuesMissing

Reproduction

Analysis started2024-03-13 09:36:02.967318
Analysis finished2024-03-13 09:36:04.193066
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시험구분(종별)
Text

Distinct107
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-03-13T18:36:04.358372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length9.3148358
Min length2

Characters and Unicode

Total characters8225
Distinct characters187
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.8%

Sample

1st rowH형강 말뚝
2nd rowH형강 말뚝
3rd rowH형강 말뚝
4th rowH형강 말뚝
5th rowH형강 말뚝
ValueCountFrequency (%)
콘크리트용 43
 
3.8%
아스팔트용부순골재 37
 
3.3%
건설용도막방수재 30
 
2.7%
일반구조용 30
 
2.7%
아스팔트콘크리트(표층_개질 30
 
2.7%
아스팔트콘크리트(표층_재생 27
 
2.4%
아스팔트콘크리트(표층 25
 
2.2%
용접구조용 23
 
2.0%
골재 22
 
1.9%
부순골재 21
 
1.9%
Other values (120) 844
74.6%
2024-03-13T18:36:04.758189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
트 575
 
7.0%
용 386
 
4.7%
리 283
 
3.4%
재 281
 
3.4%
콘 264
 
3.2%
크 264
 
3.2%
260
 
3.2%
아 245
 
3.0%
스 245
 
3.0%
팔 239
 
2.9%
Other values (177) 5183
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7413
90.1%
Space Separator 260
 
3.2%
Close Punctuation 188
 
2.3%
Open Punctuation 188
 
2.3%
Connector Punctuation 103
 
1.3%
Decimal Number 29
 
0.4%
Uppercase Letter 28
 
0.3%
Math Symbol 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 575
 
7.8%
용 386
 
5.2%
리 283
 
3.8%
재 281
 
3.8%
콘 264
 
3.6%
크 264
 
3.6%
아 245
 
3.3%
스 245
 
3.3%
팔 239
 
3.2%
강 238
 
3.2%
Other values (166) 4393
59.3%
Decimal Number
ValueCountFrequency (%)
5 24
82.8%
6 3
 
10.3%
1 2
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
H 16
57.1%
C 6
 
21.4%
P 6
 
21.4%
Space Separator
ValueCountFrequency (%)
260
100.0%
Close Punctuation
ValueCountFrequency (%)
) 188
100.0%
Open Punctuation
ValueCountFrequency (%)
( 188
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 103
100.0%
Math Symbol
ValueCountFrequency (%)
× 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7413
90.1%
Common 784
 
9.5%
Latin 28
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 575
 
7.8%
용 386
 
5.2%
리 283
 
3.8%
재 281
 
3.8%
콘 264
 
3.6%
크 264
 
3.6%
아 245
 
3.3%
스 245
 
3.3%
팔 239
 
3.2%
강 238
 
3.2%
Other values (166) 4393
59.3%
Common
ValueCountFrequency (%)
260
33.2%
) 188
24.0%
( 188
24.0%
_ 103
 
13.1%
5 24
 
3.1%
× 16
 
2.0%
6 3
 
0.4%
1 2
 
0.3%
Latin
ValueCountFrequency (%)
H 16
57.1%
C 6
 
21.4%
P 6
 
21.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7413
90.1%
ASCII 796
 
9.7%
None 16
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
트 575
 
7.8%
용 386
 
5.2%
리 283
 
3.8%
재 281
 
3.8%
콘 264
 
3.6%
크 264
 
3.6%
아 245
 
3.3%
스 245
 
3.3%
팔 239
 
3.2%
강 238
 
3.2%
Other values (166) 4393
59.3%
ASCII
ValueCountFrequency (%)
260
32.7%
) 188
23.6%
( 188
23.6%
_ 103
 
12.9%
5 24
 
3.0%
H 16
 
2.0%
C 6
 
0.8%
P 6
 
0.8%
6 3
 
0.4%
1 2
 
0.3%
None
ValueCountFrequency (%)
× 16
100.0%

시험항목
Text

Distinct322
Distinct (%)36.5%
Missing1
Missing (%)0.1%
Memory size7.0 KiB
2024-03-13T18:36:05.080371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length7.6972789
Min length2

Characters and Unicode

Total characters6789
Distinct characters284
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique190 ?
Unique (%)21.5%

Sample

1st row연신율
2nd row인장강도
3rd row탄소당량
4th row항복강도
5th row화학성분(구리 Cu)
ValueCountFrequency (%)
입도(골재 40
 
3.5%
인장강도 32
 
2.8%
연신율 29
 
2.6%
항복강도 26
 
2.3%
화학성분(인 23
 
2.0%
p 23
 
2.0%
화학성분(황 23
 
2.0%
s 23
 
2.0%
화학성분(탄소 21
 
1.9%
c 21
 
1.9%
Other values (339) 866
76.8%
2024-03-13T18:36:05.531626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 466
 
6.9%
( 466
 
6.9%
도 401
 
5.9%
246
 
3.6%
성 225
 
3.3%
화 171
 
2.5%
입 159
 
2.3%
강 154
 
2.3%
장 146
 
2.2%
학 141
 
2.1%
Other values (274) 4214
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4634
68.3%
Close Punctuation 466
 
6.9%
Open Punctuation 466
 
6.9%
Uppercase Letter 370
 
5.4%
Decimal Number 250
 
3.7%
Space Separator 246
 
3.6%
Lowercase Letter 145
 
2.1%
Other Punctuation 97
 
1.4%
Dash Punctuation 75
 
1.1%
Connector Punctuation 19
 
0.3%
Other values (3) 21
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 401
 
8.7%
성 225
 
4.9%
화 171
 
3.7%
입 159
 
3.4%
강 154
 
3.3%
장 146
 
3.2%
학 141
 
3.0%
분 140
 
3.0%
재 114
 
2.5%
인 111
 
2.4%
Other values (230) 2872
62.0%
Uppercase Letter
ValueCountFrequency (%)
C 86
23.2%
S 67
18.1%
B 51
13.8%
M 49
13.2%
W 36
9.7%
P 29
 
7.8%
A 21
 
5.7%
N 13
 
3.5%
R 12
 
3.2%
V 3
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
m 78
53.8%
i 23
 
15.9%
n 19
 
13.1%
o 8
 
5.5%
r 6
 
4.1%
u 5
 
3.4%
b 2
 
1.4%
h 1
 
0.7%
g 1
 
0.7%
l 1
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 49
19.6%
0 38
15.2%
3 36
14.4%
2 30
12.0%
5 21
8.4%
4 20
8.0%
7 20
8.0%
8 19
 
7.6%
6 17
 
6.8%
Other Punctuation
ValueCountFrequency (%)
# 40
41.2%
, 35
36.1%
. 13
 
13.4%
/ 6
 
6.2%
% 3
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 466
100.0%
Open Punctuation
ValueCountFrequency (%)
( 466
100.0%
Space Separator
ValueCountFrequency (%)
246
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 19
100.0%
Math Symbol
ValueCountFrequency (%)
+ 15
100.0%
Modifier Symbol
ValueCountFrequency (%)
˚ 4
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4634
68.3%
Common 1640
 
24.2%
Latin 515
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 401
 
8.7%
성 225
 
4.9%
화 171
 
3.7%
입 159
 
3.4%
강 154
 
3.3%
장 146
 
3.2%
학 141
 
3.0%
분 140
 
3.0%
재 114
 
2.5%
인 111
 
2.4%
Other values (230) 2872
62.0%
Common
ValueCountFrequency (%)
) 466
28.4%
( 466
28.4%
246
15.0%
- 75
 
4.6%
1 49
 
3.0%
# 40
 
2.4%
0 38
 
2.3%
3 36
 
2.2%
, 35
 
2.1%
2 30
 
1.8%
Other values (12) 159
 
9.7%
Latin
ValueCountFrequency (%)
C 86
16.7%
m 78
15.1%
S 67
13.0%
B 51
9.9%
M 49
9.5%
W 36
7.0%
P 29
 
5.6%
i 23
 
4.5%
A 21
 
4.1%
n 19
 
3.7%
Other values (12) 56
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4634
68.3%
ASCII 2149
31.7%
Modifier Letters 4
 
0.1%
Letterlike Symbols 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 466
21.7%
( 466
21.7%
246
11.4%
C 86
 
4.0%
m 78
 
3.6%
- 75
 
3.5%
S 67
 
3.1%
B 51
 
2.4%
1 49
 
2.3%
M 49
 
2.3%
Other values (32) 516
24.0%
Hangul
ValueCountFrequency (%)
도 401
 
8.7%
성 225
 
4.9%
화 171
 
3.7%
입 159
 
3.4%
강 154
 
3.3%
장 146
 
3.2%
학 141
 
3.0%
분 140
 
3.0%
재 114
 
2.5%
인 111
 
2.4%
Other values (230) 2872
62.0%
Modifier Letters
ValueCountFrequency (%)
˚ 4
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 2
100.0%

시험방법
Text

MISSING 

Distinct131
Distinct (%)15.4%
Missing35
Missing (%)4.0%
Memory size7.0 KiB
2024-03-13T18:36:05.794549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length16
Mean length16.166274
Min length3

Characters and Unicode

Total characters13709
Distinct characters68
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)5.5%

Sample

1st rowKS B 0802 : 2003
2nd rowKS B 0802 : 2003
3rd rowKS D 1652 : 2007
4th rowKS B 0802 : 2003
5th rowKS D 1652 : 2007
ValueCountFrequency (%)
ks 806
19.6%
785
19.1%
f 483
11.7%
2019 177
 
4.3%
d 150
 
3.6%
2007 144
 
3.5%
1652 140
 
3.4%
2502 136
 
3.3%
b 94
 
2.3%
0802 81
 
2.0%
Other values (139) 1123
27.3%
2024-03-13T18:36:06.171763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3287
24.0%
2 1908
13.9%
0 1723
12.6%
1 882
 
6.4%
S 851
 
6.2%
K 825
 
6.0%
: 807
 
5.9%
F 494
 
3.6%
5 470
 
3.4%
3 434
 
3.2%
Other values (58) 2028
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6656
48.6%
Space Separator 3287
24.0%
Uppercase Letter 2569
 
18.7%
Other Punctuation 807
 
5.9%
Other Letter 314
 
2.3%
Dash Punctuation 63
 
0.5%
Letter Number 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
 
9.2%
서 27
 
8.6%
트 26
 
8.3%
공 20
 
6.4%
속 14
 
4.5%
부 14
 
4.5%
침 14
 
4.5%
지 14
 
4.5%
스 13
 
4.1%
아 13
 
4.1%
Other values (31) 130
41.4%
Uppercase Letter
ValueCountFrequency (%)
S 851
33.1%
K 825
32.1%
F 494
19.2%
D 150
 
5.8%
B 97
 
3.8%
M 44
 
1.7%
L 31
 
1.2%
I 30
 
1.2%
O 18
 
0.7%
P 12
 
0.5%
Other values (3) 17
 
0.7%
Decimal Number
ValueCountFrequency (%)
2 1908
28.7%
0 1723
25.9%
1 882
13.3%
5 470
 
7.1%
3 434
 
6.5%
7 306
 
4.6%
6 276
 
4.1%
9 272
 
4.1%
4 226
 
3.4%
8 159
 
2.4%
Space Separator
ValueCountFrequency (%)
3287
100.0%
Other Punctuation
ValueCountFrequency (%)
: 807
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Letter Number
ValueCountFrequency (%)
Ⅳ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10813
78.9%
Latin 2582
 
18.8%
Hangul 314
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
 
9.2%
서 27
 
8.6%
트 26
 
8.3%
공 20
 
6.4%
속 14
 
4.5%
부 14
 
4.5%
침 14
 
4.5%
지 14
 
4.5%
스 13
 
4.1%
아 13
 
4.1%
Other values (31) 130
41.4%
Latin
ValueCountFrequency (%)
S 851
33.0%
K 825
32.0%
F 494
19.1%
D 150
 
5.8%
B 97
 
3.8%
M 44
 
1.7%
L 31
 
1.2%
I 30
 
1.2%
O 18
 
0.7%
Ⅳ 13
 
0.5%
Other values (4) 29
 
1.1%
Common
ValueCountFrequency (%)
3287
30.4%
2 1908
17.6%
0 1723
15.9%
1 882
 
8.2%
: 807
 
7.5%
5 470
 
4.3%
3 434
 
4.0%
7 306
 
2.8%
6 276
 
2.6%
9 272
 
2.5%
Other values (3) 448
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13382
97.6%
Hangul 314
 
2.3%
Number Forms 13
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3287
24.6%
2 1908
14.3%
0 1723
12.9%
1 882
 
6.6%
S 851
 
6.4%
K 825
 
6.2%
: 807
 
6.0%
F 494
 
3.7%
5 470
 
3.5%
3 434
 
3.2%
Other values (16) 1701
12.7%
Hangul
ValueCountFrequency (%)
시 29
 
9.2%
서 27
 
8.6%
트 26
 
8.3%
공 20
 
6.4%
속 14
 
4.5%
부 14
 
4.5%
침 14
 
4.5%
지 14
 
4.5%
스 13
 
4.1%
아 13
 
4.1%
Other values (31) 130
41.4%
Number Forms
ValueCountFrequency (%)
Ⅳ 13
100.0%

단위
Categorical

IMBALANCE 

Distinct35
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
%
486 
N/㎟
115 
--
101 
mm
 
41
ton/㎡
 
27
Other values (30)
113 

Length

Max length7
Median length1
Mean length1.8686297
Min length1

Unique

Unique8 ?
Unique (%)0.9%

Sample

1st row%
2nd rowN/㎟
3rd row%
4th rowN/㎟
5th row%

Common Values

ValueCountFrequency (%)
% 486
55.0%
N/㎟ 115
 
13.0%
-- 101
 
11.4%
mm 41
 
4.6%
ton/㎡ 27
 
3.1%
g/㎤ 14
 
1.6%
N 13
 
1.5%
1/100cm 10
 
1.1%
BPN 8
 
0.9%
N/㎠ 8
 
0.9%
Other values (25) 60
 
6.8%

Length

2024-03-13T18:36:06.307555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
587
66.3%
n/㎟ 115
 
13.0%
mm 41
 
4.6%
ton/㎡ 27
 
3.1%
g/㎤ 14
 
1.6%
n 13
 
1.5%
1/100cm 10
 
1.1%
bpn 8
 
0.9%
n/㎠ 8
 
0.9%
n/mm 7
 
0.8%
Other values (25) 55
 
6.2%

시험수수료(원)
Real number (ℝ)

Distinct299
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96977.633
Minimum6200
Maximum1261080
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-13T18:36:06.422487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6200
5-th percentile13468
Q125245
median52140
Q3172330
95-th percentile316870
Maximum1261080
Range1254880
Interquartile range (IQR)147085

Descriptive statistics

Standard deviation104247.57
Coefficient of variation (CV)1.0749651
Kurtosis18.547977
Mean96977.633
Median Absolute Deviation (MAD)29010
Skewness2.7845467
Sum85631250
Variance1.0867556 × 1010
MonotonicityNot monotonic
2024-03-13T18:36:06.559189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
176350 84
 
9.5%
52150 42
 
4.8%
23130 30
 
3.4%
23210 17
 
1.9%
23510 16
 
1.8%
23290 15
 
1.7%
51600 14
 
1.6%
138810 11
 
1.2%
261910 11
 
1.2%
150360 11
 
1.2%
Other values (289) 632
71.6%
ValueCountFrequency (%)
6200 5
0.6%
6390 3
0.3%
6880 2
 
0.2%
9510 2
 
0.2%
9590 1
 
0.1%
9600 2
 
0.2%
9650 5
0.6%
9690 1
 
0.1%
9840 2
 
0.2%
9900 2
 
0.2%
ValueCountFrequency (%)
1261080 1
 
0.1%
621490 1
 
0.1%
470120 2
 
0.2%
422460 5
0.6%
409010 4
0.5%
399590 2
 
0.2%
366640 3
 
0.3%
354620 8
0.9%
353560 2
 
0.2%
350420 3
 
0.3%

처리기간(일)
Real number (ℝ)

Distinct23
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3171008
Minimum0
Maximum34
Zeros5
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-13T18:36:06.687089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q14
median5
Q37
95-th percentile12
Maximum34
Range34
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.2262021
Coefficient of variation (CV)0.66900976
Kurtosis16.491657
Mean6.3171008
Median Absolute Deviation (MAD)1
Skewness3.7189622
Sum5578
Variance17.860784
MonotonicityNot monotonic
2024-03-13T18:36:06.806159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4 388
43.9%
7 285
32.3%
5 86
 
9.7%
12 29
 
3.3%
6 25
 
2.8%
10 18
 
2.0%
27 11
 
1.2%
14 6
 
0.7%
0 5
 
0.6%
3 4
 
0.5%
Other values (13) 26
 
2.9%
ValueCountFrequency (%)
0 5
 
0.6%
3 4
 
0.5%
4 388
43.9%
5 86
 
9.7%
6 25
 
2.8%
7 285
32.3%
8 3
 
0.3%
9 1
 
0.1%
10 18
 
2.0%
11 2
 
0.2%
ValueCountFrequency (%)
34 2
 
0.2%
32 1
 
0.1%
31 1
 
0.1%
30 2
 
0.2%
27 11
1.2%
25 3
 
0.3%
24 2
 
0.2%
20 3
 
0.3%
18 4
 
0.5%
16 1
 
0.1%

비고
Categorical

IMBALANCE 

Distinct45
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
788 
-
 
24
이상없을것
 
7
--
 
4
최고10%이하,최저5%이상
 
4
Other values (40)
 
56

Length

Max length24
Median length1
Mean length1.5243488
Min length1

Unique

Unique27 ?
Unique (%)3.1%

Sample

1st row17이상
2nd row410-550,550-700
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
788
89.2%
- 24
 
2.7%
이상없을것 7
 
0.8%
-- 4
 
0.5%
최고10%이하,최저5%이상 4
 
0.5%
5.0 이상 3
 
0.3%
8 이상 3
 
0.3%
6 이상 3
 
0.3%
최고10%이하, 최저5%이상 2
 
0.2%
밀도 : 2.5 이상 흡수율 : 3.0이하 2
 
0.2%
Other values (35) 43
 
4.9%

Length

2024-03-13T18:36:06.953257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
40
23.7%
이상 30
17.8%
이하 9
 
5.3%
이상없을것 7
 
4.1%
최고10%이하,최저5%이상 4
 
2.4%
10 4
 
2.4%
5.0 3
 
1.8%
8 3
 
1.8%
6 3
 
1.8%
75 2
 
1.2%
Other values (48) 64
37.9%

Interactions

2024-03-13T18:36:03.670217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:36:03.402336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:36:03.793710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:36:03.506363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T18:36:07.027351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단위시험수수료(원)처리기간(일)비고
단위1.0000.5320.5790.851
시험수수료(원)0.5321.0000.6270.000
처리기간(일)0.5790.6271.0000.000
비고0.8510.0000.0001.000
2024-03-13T18:36:07.125875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고단위
비고1.0000.311
단위0.3111.000
2024-03-13T18:36:07.249061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시험수수료(원)처리기간(일)단위비고
시험수수료(원)1.0000.1740.2620.000
처리기간(일)0.1741.0000.2520.000
단위0.2620.2521.0000.311
비고0.0000.0000.3111.000

Missing values

2024-03-13T18:36:03.913822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T18:36:04.038494image/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.
2024-03-13T18:36:04.146157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시험구분(종별)시험항목시험방법단위시험수수료(원)처리기간(일)비고
0H형강 말뚝연신율KS B 0802 : 2003%28640417이상
1H형강 말뚝인장강도KS B 0802 : 2003N/㎟286404410-550,550-700
2H형강 말뚝탄소당량KS D 1652 : 2007%242107
3H형강 말뚝항복강도KS B 0802 : 2003N/㎟286404
4H형강 말뚝화학성분(구리 Cu)KS D 1652 : 2007%331607
5H형강 말뚝화학성분(규소 Si)KS D 1652 : 2007%331607
6H형강 말뚝화학성분(망간 Mn)KS D 1652 : 2007%331607
7H형강 말뚝화학성분(인 P)KS D 1652 : 2007%331607
8H형강 말뚝화학성분(탄소 C)KS D 1652 : 2007%331607
9H형강 말뚝화학성분(황 S)KS D 1652 : 2007%331607
시험구분(종별)시험항목시험방법단위시험수수료(원)처리기간(일)비고
873합성고분자계 방수시트인장강도비(가열후)KS F 4911 : 2019%13221012
874합성고분자계 방수시트인장강도비(알칼리)KS F 4911 : 2019%3353012
875합성고분자계 방수시트접합성상(가열후)KS F 4911 : 2019--20032012
876합성고분자계 방수시트접합성상(무처리)KS F 4911 : 2019--309305
877합성고분자계 방수시트접합성상(알카리)KS F 4911 : 2019--3399012
878합성고분자계 방수시트치수(두께)(화학)KS F 4911 : 2019mm106505
879호안용블록압축강도시방서N/㎟570705
880호안용블록치수(가로,세로,두께)<NA>mm183100
881호안용블록휨강도시방서N/㎟485705
882호안용블록흡수율시방서%522607

Duplicate rows

Most frequently occurring

시험구분(종별)시험항목시험방법단위시험수수료(원)처리기간(일)비고# duplicates
1콘크리트벽돌압축강도KS F 4004 : 2013N/㎟5894053
0속빈콘크리트블록압축강도KS F 4002 : 2022N/㎟5444058 이상2
2콘크리트코아압축강도KS F 2422 : 2017N/㎟8154052
3투수기층입도(10mm)KS F 2502 : 2019%21507042
4투수기층입도(20mm)KS F 2502 : 2019%21507042