Overview

Dataset statistics

Number of variables9
Number of observations137
Missing cells50
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.7 KiB
Average record size in memory80.0 B

Variable types

Numeric4
Text2
Categorical3

Dataset

Description보문산공원에 위치한 목재문화체험장 내 목재체험 목공도구 및 기계(톱, 클램프, 타카, 톱 등)의 현황을 체험실 별로 제공합니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15083716/fileData.do

Alerts

초급반 is highly overall correlated with 목공구실High correlation
아동반 is highly overall correlated with 자재실High correlation
자재실 is highly overall correlated with 아동반High correlation
목공구실 is highly overall correlated with 초급반High correlation
아동반 is highly imbalanced (88.3%)Imbalance
자재실 is highly imbalanced (89.3%)Imbalance
목공구실 is highly imbalanced (73.7%)Imbalance
규격 has 50 (36.5%) missing valuesMissing
순번 has unique valuesUnique
초급반 has 73 (53.3%) zerosZeros
중급반 has 50 (36.5%) zerosZeros
전문가반 has 42 (30.7%) zerosZeros

Reproduction

Analysis started2023-12-12 23:21:43.178808
Analysis finished2023-12-12 23:21:45.604637
Duration2.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct137
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69
Minimum1
Maximum137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:21:45.697055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.8
Q135
median69
Q3103
95-th percentile130.2
Maximum137
Range136
Interquartile range (IQR)68

Descriptive statistics

Standard deviation39.692569
Coefficient of variation (CV)0.57525462
Kurtosis-1.2
Mean69
Median Absolute Deviation (MAD)34
Skewness0
Sum9453
Variance1575.5
MonotonicityStrictly increasing
2023-12-13T08:21:45.848632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
95 1
 
0.7%
89 1
 
0.7%
90 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
96 1
 
0.7%
104 1
 
0.7%
Other values (127) 127
92.7%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%
128 1
0.7%

품 명
Text

Distinct93
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T08:21:46.162387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length4.919708
Min length1

Characters and Unicode

Total characters674
Distinct characters161
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)53.3%

Sample

1st row4인용 버닝기
2nd row6홀 드릴 블록
3rd row90도 코너바이스
4th rowDIY클램프
5th rowDIY클램프
ValueCountFrequency (%)
diy클램프 9
 
5.5%
끌 8
 
4.9%
클램프 5
 
3.0%
다이아블럭 4
 
2.4%
페이스클램프 4
 
2.4%
집게클램프 4
 
2.4%
퀵클램프 3
 
1.8%
전기 3
 
1.8%
타카 3
 
1.8%
k바디 3
 
1.8%
Other values (99) 118
72.0%
2023-12-13T08:21:46.632434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
클 42
 
6.2%
프 39
 
5.8%
램 38
 
5.6%
29
 
4.3%
이 24
 
3.6%
기 16
 
2.4%
드 14
 
2.1%
지 12
 
1.8%
스 12
 
1.8%
자 12
 
1.8%
Other values (151) 436
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 584
86.6%
Uppercase Letter 39
 
5.8%
Space Separator 29
 
4.3%
Decimal Number 8
 
1.2%
Close Punctuation 7
 
1.0%
Open Punctuation 7
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
클 42
 
7.2%
프 39
 
6.7%
램 38
 
6.5%
이 24
 
4.1%
기 16
 
2.7%
드 14
 
2.4%
지 12
 
2.1%
스 12
 
2.1%
자 12
 
2.1%
트 11
 
1.9%
Other values (134) 364
62.3%
Uppercase Letter
ValueCountFrequency (%)
I 9
23.1%
D 9
23.1%
Y 9
23.1%
K 4
10.3%
S 3
 
7.7%
T 2
 
5.1%
M 1
 
2.6%
P 1
 
2.6%
R 1
 
2.6%
Decimal Number
ValueCountFrequency (%)
4 3
37.5%
0 2
25.0%
9 1
 
12.5%
5 1
 
12.5%
6 1
 
12.5%
Space Separator
ValueCountFrequency (%)
29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 584
86.6%
Common 51
 
7.6%
Latin 39
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
클 42
 
7.2%
프 39
 
6.7%
램 38
 
6.5%
이 24
 
4.1%
기 16
 
2.7%
드 14
 
2.4%
지 12
 
2.1%
스 12
 
2.1%
자 12
 
2.1%
트 11
 
1.9%
Other values (134) 364
62.3%
Latin
ValueCountFrequency (%)
I 9
23.1%
D 9
23.1%
Y 9
23.1%
K 4
10.3%
S 3
 
7.7%
T 2
 
5.1%
M 1
 
2.6%
P 1
 
2.6%
R 1
 
2.6%
Common
ValueCountFrequency (%)
29
56.9%
) 7
 
13.7%
( 7
 
13.7%
4 3
 
5.9%
0 2
 
3.9%
9 1
 
2.0%
5 1
 
2.0%
6 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 584
86.6%
ASCII 90
 
13.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
클 42
 
7.2%
프 39
 
6.7%
램 38
 
6.5%
이 24
 
4.1%
기 16
 
2.7%
드 14
 
2.4%
지 12
 
2.1%
스 12
 
2.1%
자 12
 
2.1%
트 11
 
1.9%
Other values (134) 364
62.3%
ASCII
ValueCountFrequency (%)
29
32.2%
I 9
 
10.0%
D 9
 
10.0%
Y 9
 
10.0%
) 7
 
7.8%
( 7
 
7.8%
K 4
 
4.4%
S 3
 
3.3%
4 3
 
3.3%
T 2
 
2.2%
Other values (7) 8
 
8.9%

규격
Text

MISSING 

Distinct80
Distinct (%)92.0%
Missing50
Missing (%)36.5%
Memory size1.2 KiB
2023-12-13T08:21:46.922095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length5.5172414
Min length1

Characters and Unicode

Total characters480
Distinct characters103
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)86.2%

Sample

1st row220V/ 60HZ
2nd rowLM60/10
3rd rowLM30/8
4th rowLM30/5
5th rowLM30/10
ValueCountFrequency (%)
소 3
 
3.1%
대 3
 
3.1%
디월트 3
 
3.1%
102 2
 
2.0%
300mm 2
 
2.0%
6“ 2
 
2.0%
마끼다 1
 
1.0%
페스툴/17l 1
 
1.0%
60hz 1
 
1.0%
220v 1
 
1.0%
Other values (79) 79
80.6%
2023-12-13T08:21:47.402522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70
 
14.6%
1 31
 
6.5%
2 26
 
5.4%
3 25
 
5.2%
/ 20
 
4.2%
8 16
 
3.3%
m 15
 
3.1%
L 13
 
2.7%
5 13
 
2.7%
M 11
 
2.3%
Other values (93) 240
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 209
43.5%
Uppercase Letter 87
18.1%
Other Letter 86
17.9%
Other Punctuation 47
 
9.8%
Lowercase Letter 27
 
5.6%
Space Separator 11
 
2.3%
Dash Punctuation 7
 
1.5%
Initial Punctuation 5
 
1.0%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 6
 
7.0%
스 6
 
7.0%
디 3
 
3.5%
월 3
 
3.5%
대 3
 
3.5%
크 3
 
3.5%
마 3
 
3.5%
소 3
 
3.5%
일 3
 
3.5%
라 3
 
3.5%
Other values (42) 50
58.1%
Uppercase Letter
ValueCountFrequency (%)
L 13
14.9%
M 11
12.6%
K 11
12.6%
E 11
12.6%
S 5
 
5.7%
R 4
 
4.6%
C 4
 
4.6%
Z 4
 
4.6%
D 3
 
3.4%
I 3
 
3.4%
Other values (12) 18
20.7%
Decimal Number
ValueCountFrequency (%)
0 70
33.5%
1 31
14.8%
2 26
 
12.4%
3 25
 
12.0%
8 16
 
7.7%
5 13
 
6.2%
6 11
 
5.3%
4 9
 
4.3%
7 5
 
2.4%
9 3
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
m 15
55.6%
c 5
 
18.5%
h 1
 
3.7%
s 1
 
3.7%
r 1
 
3.7%
x 1
 
3.7%
a 1
 
3.7%
t 1
 
3.7%
o 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/ 20
42.6%
" 9
19.1%
, 8
 
17.0%
* 7
 
14.9%
· 2
 
4.3%
. 1
 
2.1%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 280
58.3%
Latin 114
23.8%
Hangul 86
 
17.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 6
 
7.0%
스 6
 
7.0%
디 3
 
3.5%
월 3
 
3.5%
대 3
 
3.5%
크 3
 
3.5%
마 3
 
3.5%
소 3
 
3.5%
일 3
 
3.5%
라 3
 
3.5%
Other values (42) 50
58.1%
Latin
ValueCountFrequency (%)
m 15
13.2%
L 13
11.4%
M 11
 
9.6%
K 11
 
9.6%
E 11
 
9.6%
c 5
 
4.4%
S 5
 
4.4%
R 4
 
3.5%
C 4
 
3.5%
Z 4
 
3.5%
Other values (21) 31
27.2%
Common
ValueCountFrequency (%)
0 70
25.0%
1 31
11.1%
2 26
 
9.3%
3 25
 
8.9%
/ 20
 
7.1%
8 16
 
5.7%
5 13
 
4.6%
11
 
3.9%
6 11
 
3.9%
4 9
 
3.2%
Other values (10) 48
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 387
80.6%
Hangul 86
 
17.9%
Punctuation 5
 
1.0%
None 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70
18.1%
1 31
 
8.0%
2 26
 
6.7%
3 25
 
6.5%
/ 20
 
5.2%
8 16
 
4.1%
m 15
 
3.9%
L 13
 
3.4%
5 13
 
3.4%
M 11
 
2.8%
Other values (39) 147
38.0%
Hangul
ValueCountFrequency (%)
트 6
 
7.0%
스 6
 
7.0%
디 3
 
3.5%
월 3
 
3.5%
대 3
 
3.5%
크 3
 
3.5%
마 3
 
3.5%
소 3
 
3.5%
일 3
 
3.5%
라 3
 
3.5%
Other values (42) 50
58.1%
Punctuation
ValueCountFrequency (%)
“ 5
100.0%
None
ValueCountFrequency (%)
· 2
100.0%

아동반
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
133 
2
 
2
1
 
1
20
 
1

Length

Max length2
Median length1
Mean length1.0072993
Min length1

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 133
97.1%
2 2
 
1.5%
1 1
 
0.7%
20 1
 
0.7%

Length

2023-12-13T08:21:47.541587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:47.631927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 133
97.1%
2 2
 
1.5%
1 1
 
0.7%
20 1
 
0.7%

초급반
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4233577
Minimum0
Maximum20
Zeros73
Zeros (%)53.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:21:47.712451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile15
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.6188912
Coefficient of variation (CV)1.9059883
Kurtosis6.8694124
Mean2.4233577
Median Absolute Deviation (MAD)0
Skewness2.6882512
Sum332
Variance21.334156
MonotonicityNot monotonic
2023-12-13T08:21:47.812393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 73
53.3%
2 18
 
13.1%
4 16
 
11.7%
1 13
 
9.5%
20 4
 
2.9%
10 3
 
2.2%
6 2
 
1.5%
5 2
 
1.5%
15 2
 
1.5%
18 1
 
0.7%
Other values (3) 3
 
2.2%
ValueCountFrequency (%)
0 73
53.3%
1 13
 
9.5%
2 18
 
13.1%
4 16
 
11.7%
5 2
 
1.5%
6 2
 
1.5%
8 1
 
0.7%
10 3
 
2.2%
12 1
 
0.7%
15 2
 
1.5%
ValueCountFrequency (%)
20 4
 
2.9%
19 1
 
0.7%
18 1
 
0.7%
15 2
 
1.5%
12 1
 
0.7%
10 3
 
2.2%
8 1
 
0.7%
6 2
 
1.5%
5 2
 
1.5%
4 16
11.7%

중급반
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4160584
Minimum0
Maximum29
Zeros50
Zeros (%)36.5%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:21:47.912554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile17
Maximum29
Range29
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.3627834
Coefficient of variation (CV)1.5698746
Kurtosis5.7234896
Mean3.4160584
Median Absolute Deviation (MAD)2
Skewness2.3731568
Sum468
Variance28.759446
MonotonicityNot monotonic
2023-12-13T08:21:48.000649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 50
36.5%
2 26
19.0%
1 17
 
12.4%
4 11
 
8.0%
10 6
 
4.4%
6 6
 
4.4%
5 5
 
3.6%
20 4
 
2.9%
3 3
 
2.2%
16 2
 
1.5%
Other values (5) 7
 
5.1%
ValueCountFrequency (%)
0 50
36.5%
1 17
 
12.4%
2 26
19.0%
3 3
 
2.2%
4 11
 
8.0%
5 5
 
3.6%
6 6
 
4.4%
8 2
 
1.5%
10 6
 
4.4%
15 1
 
0.7%
ValueCountFrequency (%)
29 1
 
0.7%
20 4
2.9%
19 1
 
0.7%
17 2
 
1.5%
16 2
 
1.5%
15 1
 
0.7%
10 6
4.4%
8 2
 
1.5%
6 6
4.4%
5 5
3.6%

전문가반
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2189781
Minimum0
Maximum20
Zeros42
Zeros (%)30.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:21:48.092386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile12
Maximum20
Range20
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.5660437
Coefficient of variation (CV)1.4184762
Kurtosis6.9951854
Mean3.2189781
Median Absolute Deviation (MAD)2
Skewness2.5844687
Sum441
Variance20.848755
MonotonicityNot monotonic
2023-12-13T08:21:48.190390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 42
30.7%
2 29
21.2%
5 17
12.4%
1 16
 
11.7%
4 12
 
8.8%
6 8
 
5.8%
20 7
 
5.1%
10 4
 
2.9%
3 2
 
1.5%
ValueCountFrequency (%)
0 42
30.7%
1 16
 
11.7%
2 29
21.2%
3 2
 
1.5%
4 12
 
8.8%
5 17
12.4%
6 8
 
5.8%
10 4
 
2.9%
20 7
 
5.1%
ValueCountFrequency (%)
20 7
 
5.1%
10 4
 
2.9%
6 8
 
5.8%
5 17
12.4%
4 12
 
8.8%
3 2
 
1.5%
2 29
21.2%
1 16
 
11.7%
0 42
30.7%

자재실
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
133 
5
 
1
1
 
1
33
 
1
10
 
1

Length

Max length2
Median length1
Mean length1.0145985
Min length1

Unique

Unique4 ?
Unique (%)2.9%

Sample

1st row5
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 133
97.1%
5 1
 
0.7%
1 1
 
0.7%
33 1
 
0.7%
10 1
 
0.7%

Length

2023-12-13T08:21:48.288782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:48.375777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 133
97.1%
5 1
 
0.7%
1 1
 
0.7%
33 1
 
0.7%
10 1
 
0.7%

목공구실
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
126 
1
 
5
2
 
3
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 126
92.0%
1 5
 
3.6%
2 3
 
2.2%
3 3
 
2.2%

Length

2023-12-13T08:21:48.461293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:48.549029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 126
92.0%
1 5
 
3.6%
2 3
 
2.2%
3 3
 
2.2%

Interactions

2023-12-13T08:21:44.958061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:43.742393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.165559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.605529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:45.055386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:43.861324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.267994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.694673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:45.153228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:43.971320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.389147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.782849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:45.241374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.069467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.502292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:44.873042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:21:48.611217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번품 명규격아동반초급반중급반전문가반자재실목공구실
순번1.0000.9900.0000.0000.3410.4280.4350.0000.287
품 명0.9901.0000.7640.9120.8730.9090.9671.0000.935
규격0.0000.7641.0000.0000.0000.0000.7381.0000.000
아동반0.0000.9120.0001.0000.0000.2450.0000.6310.000
초급반0.3410.8730.0000.0001.0000.7370.6010.0000.676
중급반0.4280.9090.0000.2450.7371.0000.7320.0000.367
전문가반0.4350.9670.7380.0000.6010.7321.0000.0000.318
자재실0.0001.0001.0000.6310.0000.0000.0001.0000.000
목공구실0.2870.9350.0000.0000.6760.3670.3180.0001.000
2023-12-13T08:21:48.714095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아동반자재실목공구실
아동반1.0000.5580.000
자재실0.5581.0000.000
목공구실0.0000.0001.000
2023-12-13T08:21:49.028960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번초급반중급반전문가반아동반자재실목공구실
순번1.000-0.038-0.0350.0270.0000.0000.171
초급반-0.0381.0000.4130.1680.0000.0000.550
중급반-0.0350.4131.0000.2340.1670.0000.256
전문가반0.0270.1680.2341.0000.0000.0000.198
아동반0.0000.0000.1670.0001.0000.5580.000
자재실0.0000.0000.0000.0000.5581.0000.000
목공구실0.1710.5500.2560.1980.0000.0001.000

Missing values

2023-12-13T08:21:45.382253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:21:45.547221image/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

순번품 명규격아동반초급반중급반전문가반자재실목공구실
014인용 버닝기220V/ 60HZ011050
126홀 드릴 블록<NA>000200
2390도 코너바이스<NA>062200
34DIY클램프LM60/10044400
45DIY클램프LM30/8020000
56DIY클램프LM30/5040000
67DIY클램프LM30/10044400
78DIY클램프LM15/8044400
89DIY클램프LM10/5044400
910DIY클램프LM80/10004400
순번품 명규격아동반초급반중급반전문가반자재실목공구실
127128핸드톱가이드<NA>020201000
128129형틀게이지6“010100
129130형틀게이지(대)<NA>000100
130131형틀게이지(소)<NA>000100
131132형판게이지<NA>000200
132133홀더<NA>000000
133134홀더심<NA>000200
134135홀클램프크레그, 127mm001500
135136휠마킹게이지<NA>010200
136137힌지보링지그<NA>000200