Overview

Dataset statistics

Number of variables21
Number of observations617
Missing cells1382
Missing cells (%)10.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory105.6 KiB
Average record size in memory175.2 B

Variable types

Numeric5
Categorical11
Unsupported1
Text4

Dataset

Description경기도 시험검사정보관리시스템 시약초자 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=BSWVB7GAWDBSDXZHJOP933019341&infSeq=1

Alerts

구분 is highly imbalanced (54.1%)Imbalance
품명 is highly imbalanced (66.9%)Imbalance
등급 is highly imbalanced (80.5%)Imbalance
단위 is highly imbalanced (60.4%)Imbalance
제조회사 is highly imbalanced (90.3%)Imbalance
적용명칭 is highly imbalanced (55.9%)Imbalance
참고사항 is highly imbalanced (60.3%)Imbalance
입출고구분 is highly imbalanced (68.6%)Imbalance
규격 has 617 (100.0%) missing valuesMissing
파트넘버 has 19 (3.1%) missing valuesMissing
품명영문 has 290 (47.0%) missing valuesMissing
단가 has 456 (73.9%) missing valuesMissing
입출고코드 has unique valuesUnique
규격 is an unsupported type, check if it needs cleaning or further analysisUnsupported
적정재고 has 38 (6.2%) zerosZeros
입고량 has 38 (6.2%) zerosZeros
출고량 has 582 (94.3%) zerosZeros

Reproduction

Analysis started2023-12-10 22:31:05.987991
Analysis finished2023-12-10 22:31:06.555042
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시약초자코드
Real number (ℝ)

Distinct544
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean416.10535
Minimum3
Maximum784
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T07:31:06.626117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile36.8
Q1180
median512
Q3656
95-th percentile752.2
Maximum784
Range781
Interquartile range (IQR)476

Descriptive statistics

Standard deviation252.97993
Coefficient of variation (CV)0.60797087
Kurtosis-1.5523473
Mean416.10535
Median Absolute Deviation (MAD)228
Skewness-0.13349867
Sum256737
Variance63998.844
MonotonicityNot monotonic
2023-12-11T07:31:06.776616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
568 9
 
1.5%
602 6
 
1.0%
540 5
 
0.8%
723 5
 
0.8%
550 5
 
0.8%
659 4
 
0.6%
660 4
 
0.6%
657 4
 
0.6%
658 4
 
0.6%
661 4
 
0.6%
Other values (534) 567
91.9%
ValueCountFrequency (%)
3 2
0.3%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
11 1
0.2%
12 1
0.2%
13 1
0.2%
14 1
0.2%
ValueCountFrequency (%)
784 1
0.2%
782 1
0.2%
781 1
0.2%
780 1
0.2%
779 1
0.2%
778 1
0.2%
777 1
0.2%
776 1
0.2%
775 1
0.2%
774 1
0.2%

구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
초자 및 기구
508 
기기소모품
51 
기타
 
46
컬럼
 
12

Length

Max length7
Median length7
Mean length6.3646677
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row초자 및 기구
3rd row초자 및 기구
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
초자 및 기구 508
82.3%
기기소모품 51
 
8.3%
기타 46
 
7.5%
컬럼 12
 
1.9%

Length

2023-12-11T07:31:06.904635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:31:06.999723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초자 508
31.1%
및 508
31.1%
기구 508
31.1%
기기소모품 51
 
3.1%
기타 46
 
2.8%
컬럼 12
 
0.7%

품명
Categorical

IMBALANCE 

Distinct50
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
479 
AG
 
17
HP
 
16
Waters
 
11
태민
 
10
Other values (45)
84 

Length

Max length50
Median length4
Mean length4.3517018
Min length2

Unique

Unique25 ?
Unique (%)4.1%

Sample

1st rowLG or SKC
2nd row하이비즈
3rd row독일 TESCO
4th row<NA>
5th row국산

Common Values

ValueCountFrequency (%)
<NA> 479
77.6%
AG 17
 
2.8%
HP 16
 
2.6%
Waters 11
 
1.8%
태민 10
 
1.6%
Whatman 5
 
0.8%
하이비즈 5
 
0.8%
Varian 5
 
0.8%
DIONEX 4
 
0.6%
영인과학 4
 
0.6%
Other values (40) 61
 
9.9%

Length

2023-12-11T07:31:07.128266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 479
75.7%
hp 18
 
2.8%
ag 17
 
2.7%
waters 11
 
1.7%
태민 10
 
1.6%
whatman 5
 
0.8%
하이비즈 5
 
0.8%
varian 5
 
0.8%
dionex 4
 
0.6%
영인과학 4
 
0.6%
Other values (48) 75
 
11.8%

등급
Categorical

IMBALANCE 

Distinct12
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
561 
GC
 
16
LC
 
14
Generator
 
6
ICP
 
6
Other values (7)
 
14

Length

Max length10
Median length4
Mean length4.0032415
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 561
90.9%
GC 16
 
2.6%
LC 14
 
2.3%
Generator 6
 
1.0%
ICP 6
 
1.0%
Microwave 3
 
0.5%
AA 3
 
0.5%
2
 
0.3%
pH meter 2
 
0.3%
초순수제조기 2
 
0.3%
Other values (2) 2
 
0.3%

Length

2023-12-11T07:31:07.263006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 561
90.8%
gc 16
 
2.6%
lc 14
 
2.3%
generator 6
 
1.0%
icp 6
 
1.0%
microwave 3
 
0.5%
aa 3
 
0.5%
ph 2
 
0.3%
meter 2
 
0.3%
초순수제조기 2
 
0.3%
Other values (3) 3
 
0.5%

단위
Categorical

IMBALANCE 

Distinct47
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
ea
438 
100/pk
 
25
10ea/pk
 
21
10/pk
 
20
set
 
11
Other values (42)
102 

Length

Max length10
Median length2
Mean length3.0324149
Min length2

Unique

Unique25 ?
Unique (%)4.1%

Sample

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

Common Values

ValueCountFrequency (%)
ea 438
71.0%
100/pk 25
 
4.1%
10ea/pk 21
 
3.4%
10/pk 20
 
3.2%
set 11
 
1.8%
<NA> 10
 
1.6%
50/pk 10
 
1.6%
pk 8
 
1.3%
1000/bx 6
 
1.0%
2/pk 6
 
1.0%
Other values (37) 62
 
10.0%

Length

2023-12-11T07:31:07.407274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ea 438
71.1%
100/pk 25
 
4.1%
10ea/pk 21
 
3.4%
10/pk 20
 
3.2%
set 11
 
1.8%
na 10
 
1.6%
50/pk 10
 
1.6%
pk 8
 
1.3%
100ea/pk 6
 
1.0%
2/pk 6
 
1.0%
Other values (37) 61
 
9.9%

규격
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing617
Missing (%)100.0%
Memory size5.6 KiB

파트넘버
Text

MISSING 

Distinct463
Distinct (%)77.4%
Missing19
Missing (%)3.1%
Memory size4.9 KiB
2023-12-11T07:31:07.659359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length11.428094
Min length1

Characters and Unicode

Total characters6834
Distinct characters243
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique406 ?
Unique (%)67.9%

Sample

1st rowMGC-19-UD
2nd row608HI
3rd row목재 2칸, 39*60cm
4th rowIdeal 2250
5th rowprolineXL (0.1~25ml)
ValueCountFrequency (%)
95/3cd 20
 
1.8%
bach 20
 
1.8%
mru 20
 
1.8%
가스텍 16
 
1.4%
500ml 14
 
1.2%
1l 11
 
1.0%
50ml 10
 
0.9%
한면코팅 9
 
0.8%
apex 9
 
0.8%
100ml 9
 
0.8%
Other values (648) 1003
87.9%
2023-12-11T07:31:08.098018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
571
 
8.4%
0 553
 
8.1%
1 346
 
5.1%
, 341
 
5.0%
m 318
 
4.7%
2 289
 
4.2%
5 271
 
4.0%
l 176
 
2.6%
3 162
 
2.4%
4 143
 
2.1%
Other values (233) 3664
53.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2178
31.9%
Lowercase Letter 1612
23.6%
Uppercase Letter 1029
15.1%
Other Punctuation 595
 
8.7%
Space Separator 571
 
8.4%
Other Letter 507
 
7.4%
Dash Punctuation 141
 
2.1%
Open Punctuation 80
 
1.2%
Close Punctuation 80
 
1.2%
Other Symbol 28
 
0.4%
Other values (2) 13
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 29
 
5.7%
면 21
 
4.1%
텍 17
 
3.4%
가 17
 
3.4%
용 15
 
3.0%
색 15
 
3.0%
코 13
 
2.6%
한 11
 
2.2%
팅 10
 
2.0%
산 9
 
1.8%
Other values (154) 350
69.0%
Uppercase Letter
ValueCountFrequency (%)
A 101
 
9.8%
S 90
 
8.7%
C 76
 
7.4%
D 74
 
7.2%
L 65
 
6.3%
M 63
 
6.1%
P 57
 
5.5%
R 50
 
4.9%
B 49
 
4.8%
U 44
 
4.3%
Other values (16) 360
35.0%
Lowercase Letter
ValueCountFrequency (%)
m 318
19.7%
l 176
10.9%
a 130
 
8.1%
e 114
 
7.1%
c 94
 
5.8%
o 88
 
5.5%
r 87
 
5.4%
t 86
 
5.3%
n 71
 
4.4%
s 63
 
3.9%
Other values (15) 385
23.9%
Decimal Number
ValueCountFrequency (%)
0 553
25.4%
1 346
15.9%
2 289
13.3%
5 271
12.4%
3 162
 
7.4%
4 143
 
6.6%
8 139
 
6.4%
9 102
 
4.7%
6 91
 
4.2%
7 82
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 341
57.3%
* 97
 
16.3%
/ 61
 
10.3%
. 49
 
8.2%
# 22
 
3.7%
" 20
 
3.4%
& 5
 
0.8%
Other Symbol
ValueCountFrequency (%)
㎖ 18
64.3%
㎜ 9
32.1%
㎛ 1
 
3.6%
Math Symbol
ValueCountFrequency (%)
~ 7
58.3%
+ 3
25.0%
→ 2
 
16.7%
Space Separator
ValueCountFrequency (%)
571
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3686
53.9%
Latin 2641
38.6%
Hangul 507
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 29
 
5.7%
면 21
 
4.1%
텍 17
 
3.4%
가 17
 
3.4%
용 15
 
3.0%
색 15
 
3.0%
코 13
 
2.6%
한 11
 
2.2%
팅 10
 
2.0%
산 9
 
1.8%
Other values (154) 350
69.0%
Latin
ValueCountFrequency (%)
m 318
 
12.0%
l 176
 
6.7%
a 130
 
4.9%
e 114
 
4.3%
A 101
 
3.8%
c 94
 
3.6%
S 90
 
3.4%
o 88
 
3.3%
r 87
 
3.3%
t 86
 
3.3%
Other values (41) 1357
51.4%
Common
ValueCountFrequency (%)
571
15.5%
0 553
15.0%
1 346
9.4%
, 341
9.3%
2 289
 
7.8%
5 271
 
7.4%
3 162
 
4.4%
4 143
 
3.9%
- 141
 
3.8%
8 139
 
3.8%
Other values (18) 730
19.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6296
92.1%
Hangul 507
 
7.4%
CJK Compat 28
 
0.4%
Arrows 2
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
571
 
9.1%
0 553
 
8.8%
1 346
 
5.5%
, 341
 
5.4%
m 318
 
5.1%
2 289
 
4.6%
5 271
 
4.3%
l 176
 
2.8%
3 162
 
2.6%
4 143
 
2.3%
Other values (64) 3126
49.7%
Hangul
ValueCountFrequency (%)
스 29
 
5.7%
면 21
 
4.1%
텍 17
 
3.4%
가 17
 
3.4%
용 15
 
3.0%
색 15
 
3.0%
코 13
 
2.6%
한 11
 
2.2%
팅 10
 
2.0%
산 9
 
1.8%
Other values (154) 350
69.0%
CJK Compat
ValueCountFrequency (%)
㎖ 18
64.3%
㎜ 9
32.1%
㎛ 1
 
3.6%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Punctuation
ValueCountFrequency (%)
” 1
100.0%

품명.1
Text

Distinct354
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-11T07:31:08.429714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length25
Mean length8.7341977
Min length1

Characters and Unicode

Total characters5389
Distinct characters372
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

Unique250 ?
Unique (%)40.5%

Sample

1st rowCD-RW
2nd row책장
3rd row온습도계
4th row책꽂이
5th row문서제단기
ValueCountFrequency (%)
flask 29
 
2.9%
메스 28
 
2.8%
센서 22
 
2.2%
플라스크(mess 18
 
1.8%
프린터 16
 
1.6%
프린트 12
 
1.2%
cartridge 12
 
1.2%
paper 12
 
1.2%
장갑(면 12
 
1.2%
카트리지(print 12
 
1.2%
Other values (456) 839
82.9%
2023-12-11T07:31:08.928530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
487
 
9.0%
e 267
 
5.0%
( 197
 
3.7%
) 197
 
3.7%
r 169
 
3.1%
t 138
 
2.6%
i 133
 
2.5%
스 130
 
2.4%
s 127
 
2.4%
l 122
 
2.3%
Other values (362) 3422
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2482
46.1%
Lowercase Letter 1657
30.7%
Space Separator 487
 
9.0%
Uppercase Letter 284
 
5.3%
Open Punctuation 197
 
3.7%
Close Punctuation 197
 
3.7%
Decimal Number 54
 
1.0%
Dash Punctuation 18
 
0.3%
Other Punctuation 13
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 130
 
5.2%
지 91
 
3.7%
이 84
 
3.4%
프 57
 
2.3%
크 56
 
2.3%
라 55
 
2.2%
트 54
 
2.2%
관 45
 
1.8%
린 45
 
1.8%
용 44
 
1.8%
Other values (297) 1821
73.4%
Lowercase Letter
ValueCountFrequency (%)
e 267
16.1%
r 169
10.2%
t 138
 
8.3%
i 133
 
8.0%
s 127
 
7.7%
l 122
 
7.4%
a 120
 
7.2%
p 93
 
5.6%
n 77
 
4.6%
o 53
 
3.2%
Other values (15) 358
21.6%
Uppercase Letter
ValueCountFrequency (%)
M 34
12.0%
S 26
 
9.2%
O 26
 
9.2%
P 24
 
8.5%
D 19
 
6.7%
B 18
 
6.3%
T 17
 
6.0%
C 16
 
5.6%
N 14
 
4.9%
H 11
 
3.9%
Other values (14) 79
27.8%
Decimal Number
ValueCountFrequency (%)
2 15
27.8%
0 14
25.9%
4 8
14.8%
1 5
 
9.3%
5 5
 
9.3%
6 2
 
3.7%
7 2
 
3.7%
3 2
 
3.7%
8 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 11
84.6%
. 1
 
7.7%
" 1
 
7.7%
Space Separator
ValueCountFrequency (%)
487
100.0%
Open Punctuation
ValueCountFrequency (%)
( 197
100.0%
Close Punctuation
ValueCountFrequency (%)
) 197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2482
46.1%
Latin 1941
36.0%
Common 966
 
17.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 130
 
5.2%
지 91
 
3.7%
이 84
 
3.4%
프 57
 
2.3%
크 56
 
2.3%
라 55
 
2.2%
트 54
 
2.2%
관 45
 
1.8%
린 45
 
1.8%
용 44
 
1.8%
Other values (297) 1821
73.4%
Latin
ValueCountFrequency (%)
e 267
13.8%
r 169
 
8.7%
t 138
 
7.1%
i 133
 
6.9%
s 127
 
6.5%
l 122
 
6.3%
a 120
 
6.2%
p 93
 
4.8%
n 77
 
4.0%
o 53
 
2.7%
Other values (39) 642
33.1%
Common
ValueCountFrequency (%)
487
50.4%
( 197
20.4%
) 197
20.4%
- 18
 
1.9%
2 15
 
1.6%
0 14
 
1.4%
, 11
 
1.1%
4 8
 
0.8%
1 5
 
0.5%
5 5
 
0.5%
Other values (6) 9
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2907
53.9%
Hangul 2482
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
487
16.8%
e 267
 
9.2%
( 197
 
6.8%
) 197
 
6.8%
r 169
 
5.8%
t 138
 
4.7%
i 133
 
4.6%
s 127
 
4.4%
l 122
 
4.2%
a 120
 
4.1%
Other values (55) 950
32.7%
Hangul
ValueCountFrequency (%)
스 130
 
5.2%
지 91
 
3.7%
이 84
 
3.4%
프 57
 
2.3%
크 56
 
2.3%
라 55
 
2.2%
트 54
 
2.2%
관 45
 
1.8%
린 45
 
1.8%
용 44
 
1.8%
Other values (297) 1821
73.4%

품명영문
Text

MISSING 

Distinct194
Distinct (%)59.3%
Missing290
Missing (%)47.0%
Memory size4.9 KiB
2023-12-11T07:31:09.294968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length13.917431
Min length3

Characters and Unicode

Total characters4551
Distinct characters62
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)40.1%

Sample

1st rowCalibration Weight Sets
2nd rowCD Case
3rd rowCDR
4th rowCharging Battery
5th rowCopy paper
ValueCountFrequency (%)
sensor 22
 
3.4%
printer 16
 
2.4%
paper 15
 
2.3%
gloves 14
 
2.1%
detector 14
 
2.1%
tube 10
 
1.5%
box 9
 
1.4%
dry 9
 
1.4%
pvc 9
 
1.4%
palm 9
 
1.4%
Other values (263) 528
80.6%
2023-12-11T07:31:09.849275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 509
 
11.2%
r 332
 
7.3%
329
 
7.2%
t 302
 
6.6%
a 253
 
5.6%
l 247
 
5.4%
i 233
 
5.1%
o 227
 
5.0%
s 211
 
4.6%
n 170
 
3.7%
Other values (52) 1738
38.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3372
74.1%
Uppercase Letter 572
 
12.6%
Space Separator 329
 
7.2%
Close Punctuation 116
 
2.5%
Open Punctuation 116
 
2.5%
Decimal Number 24
 
0.5%
Dash Punctuation 16
 
0.4%
Control 3
 
0.1%
Other Punctuation 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 509
15.1%
r 332
9.8%
t 302
 
9.0%
a 253
 
7.5%
l 247
 
7.3%
i 233
 
6.9%
o 227
 
6.7%
s 211
 
6.3%
n 170
 
5.0%
p 127
 
3.8%
Other values (15) 761
22.6%
Uppercase Letter
ValueCountFrequency (%)
P 74
12.9%
C 71
12.4%
S 63
11.0%
G 44
 
7.7%
D 39
 
6.8%
T 38
 
6.6%
B 37
 
6.5%
O 32
 
5.6%
F 26
 
4.5%
N 19
 
3.3%
Other values (15) 129
22.6%
Decimal Number
ValueCountFrequency (%)
2 18
75.0%
3 3
 
12.5%
4 2
 
8.3%
8 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 1
33.3%
# 1
33.3%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
329
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Control
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3944
86.7%
Common 607
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 509
 
12.9%
r 332
 
8.4%
t 302
 
7.7%
a 253
 
6.4%
l 247
 
6.3%
i 233
 
5.9%
o 227
 
5.8%
s 211
 
5.3%
n 170
 
4.3%
p 127
 
3.2%
Other values (40) 1333
33.8%
Common
ValueCountFrequency (%)
329
54.2%
) 116
 
19.1%
( 116
 
19.1%
2 18
 
3.0%
- 16
 
2.6%
3 3
 
0.5%
3
 
0.5%
4 2
 
0.3%
, 1
 
0.2%
# 1
 
0.2%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 509
 
11.2%
r 332
 
7.3%
329
 
7.2%
t 302
 
6.6%
a 253
 
5.6%
l 247
 
5.4%
i 233
 
5.1%
o 227
 
5.0%
s 211
 
4.6%
n 170
 
3.7%
Other values (52) 1738
38.2%

단가
Text

MISSING 

Distinct82
Distinct (%)50.9%
Missing456
Missing (%)73.9%
Memory size4.9 KiB
2023-12-11T07:31:10.137870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.8074534
Min length4

Characters and Unicode

Total characters935
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)34.2%

Sample

1st row231000
2nd row49500
3rd row506000
4th row200,000
5th row13000
ValueCountFrequency (%)
33,000 15
 
9.3%
462,000 9
 
5.6%
3,190 9
 
5.6%
440,000 9
 
5.6%
1,500 6
 
3.7%
181,500 5
 
3.1%
500000 5
 
3.1%
253,000 4
 
2.5%
10000 3
 
1.9%
40000 3
 
1.9%
Other values (72) 93
57.8%
2023-12-11T07:31:10.570753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 462
49.4%
, 104
 
11.1%
3 68
 
7.3%
1 63
 
6.7%
2 56
 
6.0%
5 50
 
5.3%
4 43
 
4.6%
6 29
 
3.1%
8 29
 
3.1%
9 21
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 831
88.9%
Other Punctuation 104
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 462
55.6%
3 68
 
8.2%
1 63
 
7.6%
2 56
 
6.7%
5 50
 
6.0%
4 43
 
5.2%
6 29
 
3.5%
8 29
 
3.5%
9 21
 
2.5%
7 10
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 935
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 462
49.4%
, 104
 
11.1%
3 68
 
7.3%
1 63
 
6.7%
2 56
 
6.0%
5 50
 
5.3%
4 43
 
4.6%
6 29
 
3.1%
8 29
 
3.1%
9 21
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 935
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 462
49.4%
, 104
 
11.1%
3 68
 
7.3%
1 63
 
6.7%
2 56
 
6.0%
5 50
 
5.3%
4 43
 
4.6%
6 29
 
3.1%
8 29
 
3.1%
9 21
 
2.2%

제조회사
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
598 
실험실
 
12
 
2
실험실(창고)
 
2
창고
 
2

Length

Max length50
Median length4
Mean length4.1377634
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 598
96.9%
실험실 12
 
1.9%
2
 
0.3%
실험실(창고) 2
 
0.3%
창고 2
 
0.3%
실험실(복도) 1
 
0.2%

Length

2023-12-11T07:31:10.762137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:31:10.878860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 598
97.2%
실험실 12
 
2.0%
실험실(창고 2
 
0.3%
창고 2
 
0.3%
실험실(복도 1
 
0.2%

적정재고
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.319287
Minimum0
Maximum1000
Zeros38
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T07:31:10.987164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q310
95-th percentile30
Maximum1000
Range1000
Interquartile range (IQR)9

Descriptive statistics

Standard deviation52.61259
Coefficient of variation (CV)4.6480481
Kurtosis227.14707
Mean11.319287
Median Absolute Deviation (MAD)2
Skewness13.782395
Sum6984
Variance2768.0846
MonotonicityNot monotonic
2023-12-11T07:31:11.098325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 171
27.7%
2 98
15.9%
10 80
13.0%
5 78
12.6%
0 38
 
6.2%
3 37
 
6.0%
20 24
 
3.9%
4 19
 
3.1%
30 12
 
1.9%
50 10
 
1.6%
Other values (18) 50
 
8.1%
ValueCountFrequency (%)
0 38
 
6.2%
1 171
27.7%
2 98
15.9%
3 37
 
6.0%
4 19
 
3.1%
5 78
12.6%
6 9
 
1.5%
7 7
 
1.1%
8 2
 
0.3%
9 1
 
0.2%
ValueCountFrequency (%)
1000 1
 
0.2%
500 2
 
0.3%
250 1
 
0.2%
200 2
 
0.3%
120 1
 
0.2%
100 5
0.8%
70 1
 
0.2%
60 2
 
0.3%
50 10
1.6%
40 3
 
0.5%

팀코드
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
11
327 
13
284 
12
 
4
14
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row13
4th row13
5th row13

Common Values

ValueCountFrequency (%)
11 327
53.0%
13 284
46.0%
12 4
 
0.6%
14 2
 
0.3%

Length

2023-12-11T07:31:11.212796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:31:11.302829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 327
53.0%
13 284
46.0%
12 4
 
0.6%
14 2
 
0.3%

팀명
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
대기화학팀
327 
토양분석팀
284 
산업폐수팀
 
4
환경연구기획팀
 
2

Length

Max length7
Median length5
Mean length5.006483
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기화학팀 327
53.0%
토양분석팀 284
46.0%
산업폐수팀 4
 
0.6%
환경연구기획팀 2
 
0.3%

Length

2023-12-11T07:31:11.413647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:31:11.519827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기화학팀 327
53.0%
토양분석팀 284
46.0%
산업폐수팀 4
 
0.6%
환경연구기획팀 2
 
0.3%

입출고코드
Real number (ℝ)

UNIQUE 

Distinct617
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean331.77472
Minimum4
Maximum655
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T07:31:11.632596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile34.8
Q1163
median344
Q3500
95-th percentile623.2
Maximum655
Range651
Interquartile range (IQR)337

Descriptive statistics

Standard deviation191.89523
Coefficient of variation (CV)0.57839015
Kurtosis-1.2655058
Mean331.77472
Median Absolute Deviation (MAD)169
Skewness-0.026956639
Sum204705
Variance36823.779
MonotonicityNot monotonic
2023-12-11T07:31:11.752028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
119 1
 
0.2%
537 1
 
0.2%
527 1
 
0.2%
528 1
 
0.2%
531 1
 
0.2%
532 1
 
0.2%
592 1
 
0.2%
533 1
 
0.2%
642 1
 
0.2%
538 1
 
0.2%
Other values (607) 607
98.4%
ValueCountFrequency (%)
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
11 1
0.2%
12 1
0.2%
13 1
0.2%
ValueCountFrequency (%)
655 1
0.2%
654 1
0.2%
653 1
0.2%
652 1
0.2%
651 1
0.2%
650 1
0.2%
649 1
0.2%
648 1
0.2%
647 1
0.2%
646 1
0.2%

적용일
Categorical

Distinct47
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2009-01-02
274 
2011-12-09
60 
2011-05-31
49 
2011-03-13
49 
2011-03-02
44 
Other values (42)
141 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique22 ?
Unique (%)3.6%

Sample

1st row2009-01-02
2nd row2009-01-02
3rd row2009-01-02
4th row2009-01-02
5th row2009-01-02

Common Values

ValueCountFrequency (%)
2009-01-02 274
44.4%
2011-12-09 60
 
9.7%
2011-05-31 49
 
7.9%
2011-03-13 49
 
7.9%
2011-03-02 44
 
7.1%
2011-03-01 26
 
4.2%
2011-03-18 22
 
3.6%
2011-03-06 11
 
1.8%
2011-03-05 8
 
1.3%
2009-02-02 7
 
1.1%
Other values (37) 67
 
10.9%

Length

2023-12-11T07:31:11.870354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2009-01-02 274
44.4%
2011-12-09 60
 
9.7%
2011-05-31 49
 
7.9%
2011-03-13 49
 
7.9%
2011-03-02 44
 
7.1%
2011-03-01 26
 
4.2%
2011-03-18 22
 
3.6%
2011-03-06 11
 
1.8%
2011-03-05 8
 
1.3%
2009-02-02 7
 
1.1%
Other values (37) 67
 
10.9%

입고량
Real number (ℝ)

ZEROS 

Distinct58
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.183144
Minimum0
Maximum1010
Zeros38
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T07:31:11.985941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q38
95-th percentile40
Maximum1010
Range1010
Interquartile range (IQR)7

Descriptive statistics

Standard deviation67.420303
Coefficient of variation (CV)4.7535512
Kurtosis159.56408
Mean14.183144
Median Absolute Deviation (MAD)1
Skewness11.813722
Sum8751
Variance4545.4972
MonotonicityNot monotonic
2023-12-11T07:31:12.328091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 182
29.5%
2 95
15.4%
3 50
 
8.1%
0 38
 
6.2%
10 36
 
5.8%
5 36
 
5.8%
4 24
 
3.9%
6 21
 
3.4%
8 17
 
2.8%
12 12
 
1.9%
Other values (48) 106
17.2%
ValueCountFrequency (%)
0 38
 
6.2%
1 182
29.5%
2 95
15.4%
3 50
 
8.1%
4 24
 
3.9%
5 36
 
5.8%
6 21
 
3.4%
7 9
 
1.5%
8 17
 
2.8%
9 5
 
0.8%
ValueCountFrequency (%)
1010 1
0.2%
1000 1
0.2%
500 2
0.3%
290 1
0.2%
200 2
0.3%
160 1
0.2%
150 1
0.2%
140 1
0.2%
130 1
0.2%
120 2
0.3%

출고량
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.16045381
Minimum0
Maximum20
Zeros582
Zeros (%)94.3%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T07:31:12.431168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0281075
Coefficient of variation (CV)6.4074981
Kurtosis232.00304
Mean0.16045381
Median Absolute Deviation (MAD)0
Skewness13.279997
Sum99
Variance1.057005
MonotonicityNot monotonic
2023-12-11T07:31:12.546571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 582
94.3%
2 14
 
2.3%
1 12
 
1.9%
6 3
 
0.5%
4 2
 
0.3%
5 2
 
0.3%
20 1
 
0.2%
3 1
 
0.2%
ValueCountFrequency (%)
0 582
94.3%
1 12
 
1.9%
2 14
 
2.3%
3 1
 
0.2%
4 2
 
0.3%
5 2
 
0.3%
6 3
 
0.5%
20 1
 
0.2%
ValueCountFrequency (%)
20 1
 
0.2%
6 3
 
0.5%
5 2
 
0.3%
4 2
 
0.3%
3 1
 
0.2%
2 14
 
2.3%
1 12
 
1.9%
0 582
94.3%

적용명칭
Categorical

IMBALANCE 

Distinct10
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
327 
1
234 
담당
40 
담당자
 
8
황선민
 
3
Other values (5)
 
5

Length

Max length4
Median length4
Mean length2.7050243
Min length1

Unique

Unique5 ?
Unique (%)0.8%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 327
53.0%
1 234
37.9%
담당 40
 
6.5%
담당자 8
 
1.3%
황선민 3
 
0.5%
. 1
 
0.2%
text 1
 
0.2%
민윤기 1
 
0.2%
나경호 1
 
0.2%
123 1
 
0.2%

Length

2023-12-11T07:31:12.683625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:31:12.825023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 327
53.0%
1 234
37.9%
담당 40
 
6.5%
담당자 8
 
1.3%
황선민 3
 
0.5%
1
 
0.2%
text 1
 
0.2%
민윤기 1
 
0.2%
나경호 1
 
0.2%
123 1
 
0.2%

참고사항
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
447 
이월
164 
구입
 
4
 
1
3M
 
1

Length

Max length200
Median length4
Mean length3.7698541
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 447
72.4%
이월 164
 
26.6%
구입 4
 
0.6%
1
 
0.2%
3M 1
 
0.2%

Length

2023-12-11T07:31:12.967571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:31:13.085954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 447
72.6%
이월 164
 
26.6%
구입 4
 
0.6%
3m 1
 
0.2%

입출고구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
입고
582 
출고
 
35

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
입고 582
94.3%
출고 35
 
5.7%

Length

2023-12-11T07:31:13.195395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:31:13.280805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입고 582
94.3%
출고 35
 
5.7%

Sample

시약초자코드구분품명등급단위규격파트넘버품명.1품명영문단가제조회사적정재고팀코드팀명입출고코드적용일입고량출고량적용명칭참고사항입출고구분
0133기타LG or SKC<NA>ea<NA><NA>CD-RW<NA><NA><NA>1013토양분석팀1192009-01-021001<NA>입고
1134초자 및 기구하이비즈<NA>ea<NA>MGC-19-UD책장<NA><NA><NA>213토양분석팀1202009-01-02201<NA>입고
2135초자 및 기구독일 TESCO<NA>ea<NA>608HI온습도계<NA><NA><NA>213토양분석팀1212009-01-02201<NA>입고
3136기타<NA><NA>ea<NA>목재 2칸, 39*60cm책꽂이<NA><NA><NA>513토양분석팀1222009-01-02501<NA>입고
4137기타국산<NA>ea<NA>Ideal 2250문서제단기<NA><NA><NA>113토양분석팀1232009-01-02101<NA>입고
5138초자 및 기구BIOHIT<NA>ea<NA>prolineXL (0.1~25ml)마이크로 피펫터<NA><NA><NA>113토양분석팀1242009-01-0210.<NA>입고
6139초자 및 기구Gilson 1000ul<NA>100/pk<NA><NA>마이크로 피펫팁<NA><NA><NA>6013토양분석팀1252009-01-024001<NA>입고
7140초자 및 기구Gilson<NA><NA><NA>100ul마이크로 피펫팁<NA><NA><NA>413토양분석팀1262009-01-02401<NA>입고
8141초자 및 기구<NA><NA>50/pk<NA>27.5*70mm(30ml)바이알(Vial)<NA><NA><NA>513토양분석팀1272009-01-021201<NA>입고
9142초자 및 기구태민<NA>100/pk<NA>BT1610(40ml)바이알<NA><NA><NA>213토양분석팀1282009-01-02201<NA>입고
시약초자코드구분품명등급단위규격파트넘버품명.1품명영문단가제조회사적정재고팀코드팀명입출고코드적용일입고량출고량적용명칭참고사항입출고구분
607597초자 및 기구<NA><NA>ea<NA>Apex, O-113V-DZ오링O-ring<NA><NA>1011대기화학팀4392011-03-13220<NA>이월입고
608598초자 및 기구<NA><NA>ea<NA>Apex, O-116V오링O-ring(impinger)<NA><NA>1011대기화학팀4402011-03-13240<NA>이월입고
609599초자 및 기구<NA><NA>ea<NA>Apex, O-126V오일O-ring(impinger)<NA><NA>1011대기화학팀4412011-03-1320<NA>이월입고
610601초자 및 기구<NA><NA>10/bx<NA>SUPELCO, 505285오존 스크러버Ozone scrubber66600<NA>211대기화학팀5232011-05-3110<NA><NA>입고
611601초자 및 기구<NA><NA>10/bx<NA>SUPELCO, 505285오존 스크러버Ozone scrubber66600<NA>211대기화학팀4422011-03-1310<NA>이월입고
612602초자 및 기구<NA><NA>1000/bx<NA>A4복사지Copy paper<NA><NA>1511대기화학팀6412011-12-2802<NA><NA>출고
613602초자 및 기구<NA><NA>1000/bx<NA>A4복사지Copy paper<NA><NA>1511대기화학팀6402011-11-0402<NA><NA>출고
614602초자 및 기구<NA><NA>1000/bx<NA>A4복사지Copy paper<NA><NA>1511대기화학팀6392011-09-1502<NA><NA>출고
615602초자 및 기구<NA><NA>1000/bx<NA>A4복사지Copy paper<NA><NA>1511대기화학팀6382011-07-0602<NA><NA>출고
616602초자 및 기구<NA><NA>1000/bx<NA>A4복사지Copy paper<NA><NA>1511대기화학팀6372011-05-0503<NA><NA>출고