Overview

Dataset statistics

Number of variables13
Number of observations38
Missing cells27
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory110.5 B

Variable types

Text4
Categorical5
DateTime1
Numeric2
Boolean1

Dataset

Description재단이 홈페이지 관리에 필요한 트리관련(트리코드, 트리설명, 등록일, 수정일, 트리레벨 등) DB데이터 자료입니다.
URLhttps://www.data.go.kr/data/15042293/fileData.do

Alerts

보여주기여부 has constant value ""Constant
등록자 is highly overall correlated with 순서 and 2 other fieldsHigh correlation
등록일 is highly overall correlated with 등록자 and 1 other fieldsHigh correlation
수정자 is highly overall correlated with 그룹순서 and 5 other fieldsHigh correlation
카테고리 is highly overall correlated with 수정자High correlation
트리레벨 is highly overall correlated with 수정자High correlation
그룹순서 is highly overall correlated with 수정자High correlation
순서 is highly overall correlated with 등록자 and 1 other fieldsHigh correlation
트리설명 has 2 (5.3%) missing valuesMissing
수정일 has 25 (65.8%) missing valuesMissing
트리코드 has unique valuesUnique
상위트리코드 has unique valuesUnique
트리이름 has unique valuesUnique
그룹순서 has 21 (55.3%) zerosZeros
순서 has 14 (36.8%) zerosZeros

Reproduction

Analysis started2023-12-12 04:19:03.476484
Analysis finished2023-12-12 04:19:05.013347
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

트리코드
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T13:19:05.190444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.7368421
Min length2

Characters and Unicode

Total characters104
Distinct characters11
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

Unique38 ?
Unique (%)100.0%

Sample

1st rowT0
2nd rowT1
3rd rowT2
4th rowT3
5th rowT4
ValueCountFrequency (%)
t0 1
 
2.6%
t27 1
 
2.6%
t36 1
 
2.6%
t21 1
 
2.6%
t22 1
 
2.6%
t23 1
 
2.6%
t24 1
 
2.6%
t25 1
 
2.6%
t26 1
 
2.6%
t29 1
 
2.6%
Other values (28) 28
73.7%
2023-12-12T13:19:05.590672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 38
36.5%
1 14
 
13.5%
2 14
 
13.5%
3 12
 
11.5%
0 4
 
3.8%
7 4
 
3.8%
4 4
 
3.8%
5 4
 
3.8%
6 4
 
3.8%
8 3
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
63.5%
Uppercase Letter 38
36.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.2%
2 14
21.2%
3 12
18.2%
0 4
 
6.1%
7 4
 
6.1%
4 4
 
6.1%
5 4
 
6.1%
6 4
 
6.1%
8 3
 
4.5%
9 3
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
T 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66
63.5%
Latin 38
36.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
21.2%
2 14
21.2%
3 12
18.2%
0 4
 
6.1%
7 4
 
6.1%
4 4
 
6.1%
5 4
 
6.1%
6 4
 
6.1%
8 3
 
4.5%
9 3
 
4.5%
Latin
ValueCountFrequency (%)
T 38
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 38
36.5%
1 14
 
13.5%
2 14
 
13.5%
3 12
 
11.5%
0 4
 
3.8%
7 4
 
3.8%
4 4
 
3.8%
5 4
 
3.8%
6 4
 
3.8%
8 3
 
2.9%

상위트리코드
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T13:19:05.867216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.7368421
Min length3

Characters and Unicode

Total characters142
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

Unique38 ?
Unique (%)100.0%

Sample

1st rowUT0
2nd rowUT1
3rd rowUT2
4th rowUT3
5th rowUT4
ValueCountFrequency (%)
ut0 1
 
2.6%
ut27 1
 
2.6%
ut36 1
 
2.6%
ut21 1
 
2.6%
ut22 1
 
2.6%
ut23 1
 
2.6%
ut24 1
 
2.6%
ut25 1
 
2.6%
ut26 1
 
2.6%
ut29 1
 
2.6%
Other values (28) 28
73.7%
2023-12-12T13:19:06.299245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 38
26.8%
T 38
26.8%
1 14
 
9.9%
2 14
 
9.9%
3 12
 
8.5%
0 4
 
2.8%
7 4
 
2.8%
4 4
 
2.8%
5 4
 
2.8%
6 4
 
2.8%
Other values (2) 6
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 76
53.5%
Decimal Number 66
46.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.2%
2 14
21.2%
3 12
18.2%
0 4
 
6.1%
7 4
 
6.1%
4 4
 
6.1%
5 4
 
6.1%
6 4
 
6.1%
8 3
 
4.5%
9 3
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
U 38
50.0%
T 38
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 76
53.5%
Common 66
46.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
21.2%
2 14
21.2%
3 12
18.2%
0 4
 
6.1%
7 4
 
6.1%
4 4
 
6.1%
5 4
 
6.1%
6 4
 
6.1%
8 3
 
4.5%
9 3
 
4.5%
Latin
ValueCountFrequency (%)
U 38
50.0%
T 38
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 38
26.8%
T 38
26.8%
1 14
 
9.9%
2 14
 
9.9%
3 12
 
8.5%
0 4
 
2.8%
7 4
 
2.8%
4 4
 
2.8%
5 4
 
2.8%
6 4
 
2.8%
Other values (2) 6
 
4.2%

카테고리
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
NEWS_TYPE
9 
SURVEY_TYPE
8 
MARKETING_TYPE
6 
ADMIN_TYPE
5 
LETTER_TYPE
5 
Other values (2)
5 

Length

Max length14
Median length11
Mean length10.473684
Min length4

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
NEWS_TYPE 9
23.7%
SURVEY_TYPE 8
21.1%
MARKETING_TYPE 6
15.8%
ADMIN_TYPE 5
13.2%
LETTER_TYPE 5
13.2%
LINK_TYPE 4
10.5%
<NA> 1
 
2.6%

Length

2023-12-12T13:19:06.490968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:06.648806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
news_type 9
23.7%
survey_type 8
21.1%
marketing_type 6
15.8%
admin_type 5
13.2%
letter_type 5
13.2%
link_type 4
10.5%
na 1
 
2.6%

트리이름
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T13:19:06.943108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.0789474
Min length2

Characters and Unicode

Total characters193
Distinct characters96
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row트리관리
2nd row메일유형
3rd row설문조사
4th row뉴스레터
5th row이벤트메일
ValueCountFrequency (%)
에듀21 2
 
4.3%
btl/bto 2
 
4.3%
조사 2
 
4.3%
트리관리 1
 
2.2%
재업무별요청계정 1
 
2.2%
기타 1
 
2.2%
융자소식 1
 
2.2%
연수소식 1
 
2.2%
칼럼/이슈 1
 
2.2%
채용소식 1
 
2.2%
Other values (33) 33
71.7%
2023-12-12T13:19:07.668237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 8
 
4.1%
8
 
4.1%
식 6
 
3.1%
소 6
 
3.1%
재 5
 
2.6%
형 5
 
2.6%
정 5
 
2.6%
유 5
 
2.6%
이 5
 
2.6%
자 4
 
2.1%
Other values (86) 136
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151
78.2%
Uppercase Letter 16
 
8.3%
Space Separator 8
 
4.1%
Lowercase Letter 7
 
3.6%
Decimal Number 4
 
2.1%
Other Punctuation 3
 
1.6%
Open Punctuation 2
 
1.0%
Close Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 8
 
5.3%
식 6
 
4.0%
소 6
 
4.0%
재 5
 
3.3%
형 5
 
3.3%
정 5
 
3.3%
유 5
 
3.3%
이 5
 
3.3%
자 4
 
2.6%
리 3
 
2.0%
Other values (67) 99
65.6%
Uppercase Letter
ValueCountFrequency (%)
T 4
25.0%
B 4
25.0%
P 2
12.5%
L 2
12.5%
O 2
12.5%
F 1
 
6.2%
K 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
w 1
14.3%
b 1
14.3%
z 1
14.3%
i 1
14.3%
n 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
] 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151
78.2%
Latin 23
 
11.9%
Common 19
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 8
 
5.3%
식 6
 
4.0%
소 6
 
4.0%
재 5
 
3.3%
형 5
 
3.3%
정 5
 
3.3%
유 5
 
3.3%
이 5
 
3.3%
자 4
 
2.6%
리 3
 
2.0%
Other values (67) 99
65.6%
Latin
ValueCountFrequency (%)
T 4
17.4%
B 4
17.4%
P 2
8.7%
e 2
8.7%
L 2
8.7%
O 2
8.7%
F 1
 
4.3%
K 1
 
4.3%
w 1
 
4.3%
b 1
 
4.3%
Other values (3) 3
13.0%
Common
ValueCountFrequency (%)
8
42.1%
/ 3
 
15.8%
[ 2
 
10.5%
] 2
 
10.5%
1 2
 
10.5%
2 2
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151
78.2%
ASCII 42
 
21.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 8
 
5.3%
식 6
 
4.0%
소 6
 
4.0%
재 5
 
3.3%
형 5
 
3.3%
정 5
 
3.3%
유 5
 
3.3%
이 5
 
3.3%
자 4
 
2.6%
리 3
 
2.0%
Other values (67) 99
65.6%
ASCII
ValueCountFrequency (%)
8
19.0%
T 4
 
9.5%
B 4
 
9.5%
/ 3
 
7.1%
[ 2
 
4.8%
] 2
 
4.8%
P 2
 
4.8%
e 2
 
4.8%
1 2
 
4.8%
2 2
 
4.8%
Other values (9) 11
26.2%

트리설명
Text

MISSING 

Distinct35
Distinct (%)97.2%
Missing2
Missing (%)5.3%
Memory size436.0 B
2023-12-12T13:19:07.983126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.0833333
Min length2

Characters and Unicode

Total characters183
Distinct characters89
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)94.4%

Sample

1st row메일유형
2nd row설문조사
3rd row뉴스레터
4th row이벤트메일
5th row링크유형
ValueCountFrequency (%)
웹진 2
 
4.3%
클릭 2
 
4.3%
btl/bto 2
 
4.3%
조사 2
 
4.3%
에듀21 2
 
4.3%
링크유형 1
 
2.2%
뉴스 1
 
2.2%
없음 1
 
2.2%
재정정보 1
 
2.2%
kfpp 1
 
2.2%
Other values (31) 31
67.4%
2023-12-12T13:19:08.499674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
5.5%
사 8
 
4.4%
식 6
 
3.3%
소 6
 
3.3%
정 5
 
2.7%
형 5
 
2.7%
유 5
 
2.7%
B 4
 
2.2%
T 4
 
2.2%
자 4
 
2.2%
Other values (79) 126
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146
79.8%
Uppercase Letter 16
 
8.7%
Space Separator 10
 
5.5%
Decimal Number 4
 
2.2%
Other Punctuation 3
 
1.6%
Open Punctuation 2
 
1.1%
Close Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 8
 
5.5%
식 6
 
4.1%
소 6
 
4.1%
정 5
 
3.4%
형 5
 
3.4%
유 5
 
3.4%
자 4
 
2.7%
재 4
 
2.7%
진 4
 
2.7%
스 3
 
2.1%
Other values (66) 96
65.8%
Uppercase Letter
ValueCountFrequency (%)
B 4
25.0%
T 4
25.0%
L 2
12.5%
O 2
12.5%
P 2
12.5%
F 1
 
6.2%
K 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
] 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146
79.8%
Common 21
 
11.5%
Latin 16
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 8
 
5.5%
식 6
 
4.1%
소 6
 
4.1%
정 5
 
3.4%
형 5
 
3.4%
유 5
 
3.4%
자 4
 
2.7%
재 4
 
2.7%
진 4
 
2.7%
스 3
 
2.1%
Other values (66) 96
65.8%
Latin
ValueCountFrequency (%)
B 4
25.0%
T 4
25.0%
L 2
12.5%
O 2
12.5%
P 2
12.5%
F 1
 
6.2%
K 1
 
6.2%
Common
ValueCountFrequency (%)
10
47.6%
/ 3
 
14.3%
1 2
 
9.5%
2 2
 
9.5%
[ 2
 
9.5%
] 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146
79.8%
ASCII 37
 
20.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
27.0%
B 4
 
10.8%
T 4
 
10.8%
/ 3
 
8.1%
L 2
 
5.4%
1 2
 
5.4%
2 2
 
5.4%
[ 2
 
5.4%
O 2
 
5.4%
] 2
 
5.4%
Other values (3) 4
 
10.8%
Hangul
ValueCountFrequency (%)
사 8
 
5.5%
식 6
 
4.1%
소 6
 
4.1%
정 5
 
3.4%
형 5
 
3.4%
유 5
 
3.4%
자 4
 
2.7%
재 4
 
2.7%
진 4
 
2.7%
스 3
 
2.1%
Other values (66) 96
65.8%

등록자
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
admin
20 
login_id
17 
<NA>
 
1

Length

Max length8
Median length5
Mean length6.3157895
Min length4

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
admin 20
52.6%
login_id 17
44.7%
<NA> 1
 
2.6%

Length

2023-12-12T13:19:08.710244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:08.853668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
admin 20
52.6%
login_id 17
44.7%
na 1
 
2.6%

등록일
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)34.2%
Missing0
Missing (%)0.0%
Memory size436.0 B
2008/05/28 14:13
21 
2008/06/26 15:23
3 
2008/06/26 14:47
 
2
2008/06/26 14:48
 
2
2008/06/26 15:24
 
2
Other values (8)
8 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique8 ?
Unique (%)21.1%

Sample

1st row2008/05/28 14:13
2nd row2008/05/28 14:13
3rd row2008/05/28 14:13
4th row2008/05/28 14:13
5th row2008/05/28 14:13

Common Values

ValueCountFrequency (%)
2008/05/28 14:13 21
55.3%
2008/06/26 15:23 3
 
7.9%
2008/06/26 14:47 2
 
5.3%
2008/06/26 14:48 2
 
5.3%
2008/06/26 15:24 2
 
5.3%
2008/06/26 15:15 1
 
2.6%
2008/06/26 15:17 1
 
2.6%
2008/06/26 15:19 1
 
2.6%
2008/06/26 15:21 1
 
2.6%
2008/06/26 15:22 1
 
2.6%
Other values (3) 3
 
7.9%

Length

2023-12-12T13:19:08.997826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2008/05/28 21
27.6%
14:13 21
27.6%
2008/06/26 15
19.7%
15:23 3
 
3.9%
14:47 2
 
2.6%
14:48 2
 
2.6%
15:24 2
 
2.6%
16:34 1
 
1.3%
2009/09/07 1
 
1.3%
11:35 1
 
1.3%
Other values (7) 7
 
9.2%

수정자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
25 
admin
13 

Length

Max length5
Median length4
Mean length4.3421053
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
65.8%
admin 13
34.2%

Length

2023-12-12T13:19:09.137920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:09.257796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
65.8%
admin 13
34.2%

수정일
Date

MISSING 

Distinct10
Distinct (%)76.9%
Missing25
Missing (%)65.8%
Memory size436.0 B
Minimum2008-06-26 14:45:00
Maximum2009-09-14 14:34:00
2023-12-12T13:19:09.369279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:09.507259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

그룹순서
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.94736842
Minimum0
Maximum5
Zeros21
Zeros (%)55.3%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T13:19:09.614645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4.15
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4694615
Coefficient of variation (CV)1.5510983
Kurtosis1.9683673
Mean0.94736842
Median Absolute Deviation (MAD)0
Skewness1.7138559
Sum36
Variance2.1593172
MonotonicityNot monotonic
2023-12-12T13:19:09.715332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 21
55.3%
1 10
26.3%
3 2
 
5.3%
5 2
 
5.3%
4 2
 
5.3%
2 1
 
2.6%
ValueCountFrequency (%)
0 21
55.3%
1 10
26.3%
2 1
 
2.6%
3 2
 
5.3%
4 2
 
5.3%
5 2
 
5.3%
ValueCountFrequency (%)
5 2
 
5.3%
4 2
 
5.3%
3 2
 
5.3%
2 1
 
2.6%
1 10
26.3%
0 21
55.3%

순서
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1315789
Minimum0
Maximum8
Zeros14
Zeros (%)36.8%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T13:19:09.815570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33.75
95-th percentile6.15
Maximum8
Range8
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation2.3152964
Coefficient of variation (CV)1.0861884
Kurtosis-0.23173699
Mean2.1315789
Median Absolute Deviation (MAD)1
Skewness0.87948374
Sum81
Variance5.3605974
MonotonicityNot monotonic
2023-12-12T13:19:09.945944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 14
36.8%
1 6
15.8%
3 5
 
13.2%
2 3
 
7.9%
4 3
 
7.9%
5 3
 
7.9%
6 2
 
5.3%
7 1
 
2.6%
8 1
 
2.6%
ValueCountFrequency (%)
0 14
36.8%
1 6
15.8%
2 3
 
7.9%
3 5
 
13.2%
4 3
 
7.9%
5 3
 
7.9%
6 2
 
5.3%
7 1
 
2.6%
8 1
 
2.6%
ValueCountFrequency (%)
8 1
 
2.6%
7 1
 
2.6%
6 2
 
5.3%
5 3
 
7.9%
4 3
 
7.9%
3 5
 
13.2%
2 3
 
7.9%
1 6
15.8%
0 14
36.8%

트리레벨
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
2
31 
1
6 
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row0
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 31
81.6%
1 6
 
15.8%
0 1
 
2.6%

Length

2023-12-12T13:19:10.095963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:10.185889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 31
81.6%
1 6
 
15.8%
0 1
 
2.6%

보여주기여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size170.0 B
True
38 
ValueCountFrequency (%)
True 38
100.0%
2023-12-12T13:19:10.264299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T13:19:04.331320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:04.147475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:04.430573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:04.236592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:19:10.341700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
트리코드상위트리코드카테고리트리이름트리설명등록자등록일수정일그룹순서순서트리레벨
트리코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상위트리코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
카테고리1.0001.0001.0001.0000.8550.3460.6161.0000.8350.0000.000
트리이름1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
트리설명1.0001.0000.8551.0001.0001.0000.0001.0001.0000.8401.000
등록자1.0001.0000.3461.0001.0001.0001.0000.2600.0000.6190.443
등록일1.0001.0000.6161.0000.0001.0001.0000.4890.5980.8180.000
수정일1.0001.0001.0001.0001.0000.2600.4891.0000.7570.233NaN
그룹순서1.0001.0000.8351.0001.0000.0000.5980.7571.0000.0000.483
순서1.0001.0000.0001.0000.8400.6190.8180.2330.0001.0000.000
트리레벨1.0001.0000.0001.0001.0000.4430.000NaN0.4830.0001.000
2023-12-12T13:19:10.475521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록자등록일수정자카테고리트리레벨
등록자1.0000.8281.0000.2260.291
등록일0.8281.0001.0000.3050.000
수정자1.0001.0001.0001.0001.000
카테고리0.2260.3051.0001.0000.000
트리레벨0.2910.0001.0000.0001.000
2023-12-12T13:19:10.576398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그룹순서순서카테고리등록자등록일수정자트리레벨
그룹순서1.000-0.0400.4460.0000.2931.0000.209
순서-0.0401.0000.0000.5550.4881.0000.000
카테고리0.4460.0001.0000.2260.3051.0000.000
등록자0.0000.5550.2261.0000.8281.0000.291
등록일0.2930.4880.3050.8281.0001.0000.000
수정자1.0001.0001.0001.0001.0001.0001.000
트리레벨0.2090.0000.0000.2910.0001.0001.000

Missing values

2023-12-12T13:19:04.575320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:19:04.802050image/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.
2023-12-12T13:19:04.950330image/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

트리코드상위트리코드카테고리트리이름트리설명등록자등록일수정자수정일그룹순서순서트리레벨보여주기여부
0T0UT0<NA>트리관리<NA><NA>2008/05/28 14:13<NA><NA>000Y
1T1UT1MARKETING_TYPE메일유형메일유형admin2008/05/28 14:13<NA><NA>101Y
2T2UT2MARKETING_TYPE설문조사설문조사admin2008/05/28 14:13admin2008/06/26 15:20002Y
3T3UT3MARKETING_TYPE뉴스레터뉴스레터admin2008/05/28 14:13admin2008/06/26 15:20012Y
4T4UT4MARKETING_TYPE이벤트메일이벤트메일admin2008/05/28 14:13admin2008/06/26 15:21032Y
5T5UT5LINK_TYPE링크유형링크유형admin2008/05/28 14:13<NA><NA>201Y
6T6UT6LINK_TYPE뉴스뉴스 클릭admin2008/05/28 14:13<NA><NA>002Y
7T7UT7LINK_TYPE사진사진 클릭admin2008/05/28 14:13<NA><NA>012Y
8T8UT8LINK_TYPE광고광고클릭admin2008/05/28 14:13<NA><NA>032Y
9T9UT9SURVEY_TYPE설문유형설문 유형admin2008/05/28 14:13<NA><NA>001Y
트리코드상위트리코드카테고리트리이름트리설명등록자등록일수정자수정일그룹순서순서트리레벨보여주기여부
28T28UT28MARKETING_TYPE웹진웹진login_id2008/06/26 15:21<NA><NA>022Y
29T29UT29SURVEY_TYPE여론 조사여론 조사login_id2008/06/26 15:22<NA><NA>012Y
30T30UT30SURVEY_TYPE에듀21 BTL/BTO에듀21 BTL/BTOlogin_id2008/06/26 15:23<NA><NA>022Y
31T31UT31SURVEY_TYPE융자융자login_id2008/06/26 15:23<NA><NA>032Y
32T32UT32SURVEY_TYPE연수연수login_id2008/06/26 15:23<NA><NA>042Y
33T33UT33SURVEY_TYPE경영지원경영지원login_id2008/06/26 15:24<NA><NA>052Y
34T34UT34SURVEY_TYPE재정지원재정지원login_id2008/06/26 15:24<NA><NA>062Y
35T35UT35LETTER_TYPEwebzine웹진login_id2008/06/26 16:34<NA><NA>042Y
36T36UT36MARKETING_TYPE기타기타login_id2008/07/23 11:35<NA><NA>552Y
37T37UT37ADMIN_TYPE쓰이지 않는 아이디<NA>login_id2009/09/07 13:20admin2009/09/14 14:32402Y