Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells69607
Missing cells (%)63.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory966.8 KiB
Average record size in memory99.0 B

Variable types

Numeric3
Categorical1
Text4
Boolean1
DateTime2

Dataset

Description과학기술정보통신부와 한국과학창의재단이 사이언스 레벨업 사이트에서 제공하는 과학원리 인포그래픽에 대한 자료입니다. 한국과학창의재단에서 운영하는 사이언스 레벨업 홈페이지를 통해 더 다양한 과학 학습 콘텐츠를 접할 수 있음.
Author한국과학창의재단
URLhttps://www.data.go.kr/data/15071619/fileData.do

Alerts

순번 is highly overall correlated with 과학영역 and 1 other fieldsHigh correlation
과학영역 is highly overall correlated with 순번High correlation
사용여부 is highly overall correlated with 순번High correlation
과학영역 is highly imbalanced (97.8%)Imbalance
사용여부 is highly imbalanced (70.3%)Imbalance
인포그래픽명 has 9943 (99.4%) missing valuesMissing
인포그래픽내용 has 9943 (99.4%) missing valuesMissing
인포그래픽이미지파일명 has 9946 (99.5%) missing valuesMissing
인포그래픽썸네일이미지파일명 has 9946 (99.5%) missing valuesMissing
인포그래픽이미지파일사이즈 has 9943 (99.4%) missing valuesMissing
사용여부 has 9943 (99.4%) missing valuesMissing
등록일시 has 9943 (99.4%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:52:31.826738
Analysis finished2023-12-12 16:52:34.468238
Duration2.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11607.304
Minimum12
Maximum22963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:52:34.568538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile1273.85
Q15912.75
median11572.5
Q317338.75
95-th percentile21832.05
Maximum22963
Range22951
Interquartile range (IQR)11426

Descriptive statistics

Standard deviation6599.0509
Coefficient of variation (CV)0.56852571
Kurtosis-1.2013755
Mean11607.304
Median Absolute Deviation (MAD)5713.5
Skewness-0.0070413933
Sum1.1607304 × 108
Variance43547472
MonotonicityNot monotonic
2023-12-13T01:52:34.736567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18289 1
 
< 0.1%
8345 1
 
< 0.1%
14908 1
 
< 0.1%
20756 1
 
< 0.1%
11319 1
 
< 0.1%
3542 1
 
< 0.1%
7205 1
 
< 0.1%
1589 1
 
< 0.1%
5312 1
 
< 0.1%
827 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
12 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
20 1
< 0.1%
27 1
< 0.1%
38 1
< 0.1%
43 1
< 0.1%
ValueCountFrequency (%)
22963 1
< 0.1%
22962 1
< 0.1%
22960 1
< 0.1%
22959 1
< 0.1%
22958 1
< 0.1%
22957 1
< 0.1%
22955 1
< 0.1%
22953 1
< 0.1%
22951 1
< 0.1%
22950 1
< 0.1%

과학영역
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9943 
생활과학
 
26
ICT
 
11
화학
 
7
지구과학
 
5
Other values (2)
 
8

Length

Max length4
Median length4
Mean length3.9969
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9943
99.4%
생활과학 26
 
0.3%
ICT 11
 
0.1%
화학 7
 
0.1%
지구과학 5
 
0.1%
생명과학 5
 
0.1%
물리 3
 
< 0.1%

Length

2023-12-13T01:52:34.896987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:52:35.022958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9943
99.4%
생활과학 26
 
0.3%
ict 11
 
0.1%
화학 7
 
0.1%
지구과학 5
 
< 0.1%
생명과학 5
 
< 0.1%
물리 3
 
< 0.1%

인포그래픽명
Text

MISSING 

Distinct57
Distinct (%)100.0%
Missing9943
Missing (%)99.4%
Memory size156.2 KiB
2023-12-13T01:52:35.324357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length16.912281
Min length1

Characters and Unicode

Total characters964
Distinct characters253
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

Unique57 ?
Unique (%)100.0%

Sample

1st row자석
2nd row더 이상 우리나라는 지진 안전국이 아니다? - 지진
3rd row해류
4th row순환
5th row4. 국가대표를 위한 숨 쉬는 유니폼
ValueCountFrequency (%)
18
 
7.3%
첨단 3
 
1.2%
로봇 3
 
1.2%
속 2
 
0.8%
지진 2
 
0.8%
답을 2
 
0.8%
하이드레이트 2
 
0.8%
이제는 2
 
0.8%
우리 2
 
0.8%
방법 2
 
0.8%
Other values (198) 210
84.7%
2023-12-13T01:52:35.852787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
191
 
19.8%
이 28
 
2.9%
- 20
 
2.1%
는 19
 
2.0%
스 16
 
1.7%
하 16
 
1.7%
다 15
 
1.6%
로 14
 
1.5%
에 13
 
1.3%
리 13
 
1.3%
Other values (243) 619
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 715
74.2%
Space Separator 191
 
19.8%
Other Punctuation 26
 
2.7%
Dash Punctuation 20
 
2.1%
Decimal Number 6
 
0.6%
Uppercase Letter 5
 
0.5%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 28
 
3.9%
는 19
 
2.7%
스 16
 
2.2%
하 16
 
2.2%
다 15
 
2.1%
로 14
 
2.0%
에 13
 
1.8%
리 13
 
1.8%
과 12
 
1.7%
한 12
 
1.7%
Other values (227) 557
77.9%
Decimal Number
ValueCountFrequency (%)
6 1
16.7%
1 1
16.7%
3 1
16.7%
4 1
16.7%
2 1
16.7%
7 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 8
30.8%
, 8
30.8%
? 5
19.2%
! 5
19.2%
Uppercase Letter
ValueCountFrequency (%)
I 2
40.0%
T 2
40.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
191
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 715
74.2%
Common 243
 
25.2%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 28
 
3.9%
는 19
 
2.7%
스 16
 
2.2%
하 16
 
2.2%
다 15
 
2.1%
로 14
 
2.0%
에 13
 
1.8%
리 13
 
1.8%
과 12
 
1.7%
한 12
 
1.7%
Other values (227) 557
77.9%
Common
ValueCountFrequency (%)
191
78.6%
- 20
 
8.2%
. 8
 
3.3%
, 8
 
3.3%
? 5
 
2.1%
! 5
 
2.1%
6 1
 
0.4%
1 1
 
0.4%
3 1
 
0.4%
4 1
 
0.4%
Other values (2) 2
 
0.8%
Latin
ValueCountFrequency (%)
I 2
33.3%
T 2
33.3%
o 1
16.7%
C 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 715
74.2%
ASCII 249
 
25.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
191
76.7%
- 20
 
8.0%
. 8
 
3.2%
, 8
 
3.2%
? 5
 
2.0%
! 5
 
2.0%
I 2
 
0.8%
T 2
 
0.8%
o 1
 
0.4%
6 1
 
0.4%
Other values (6) 6
 
2.4%
Hangul
ValueCountFrequency (%)
이 28
 
3.9%
는 19
 
2.7%
스 16
 
2.2%
하 16
 
2.2%
다 15
 
2.1%
로 14
 
2.0%
에 13
 
1.8%
리 13
 
1.8%
과 12
 
1.7%
한 12
 
1.7%
Other values (227) 557
77.9%

인포그래픽내용
Text

MISSING 

Distinct57
Distinct (%)100.0%
Missing9943
Missing (%)99.4%
Memory size156.2 KiB
2023-12-13T01:52:36.180967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length16.649123
Min length1

Characters and Unicode

Total characters949
Distinct characters246
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

Unique57 ?
Unique (%)100.0%

Sample

1st row자석
2nd row더 이상 우리나라는 지진 안전국이 아니다?! - 지진
3rd row해양
4th row순환
5th row국가대표를 위한 숨 쉬는 유니폼
ValueCountFrequency (%)
18
 
7.4%
첨단 3
 
1.2%
로봇 3
 
1.2%
과학 2
 
0.8%
무한한 2
 
0.8%
상용화 2
 
0.8%
스포츠 2
 
0.8%
있다 2
 
0.8%
축구화 2
 
0.8%
우리 2
 
0.8%
Other values (194) 206
84.4%
2023-12-13T01:52:36.652110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
187
 
19.7%
이 28
 
3.0%
- 20
 
2.1%
는 19
 
2.0%
하 16
 
1.7%
스 16
 
1.7%
다 15
 
1.6%
로 14
 
1.5%
리 13
 
1.4%
에 13
 
1.4%
Other values (236) 608
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 715
75.3%
Space Separator 187
 
19.7%
Other Punctuation 21
 
2.2%
Dash Punctuation 20
 
2.1%
Uppercase Letter 5
 
0.5%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 28
 
3.9%
는 19
 
2.7%
하 16
 
2.2%
스 16
 
2.2%
다 15
 
2.1%
로 14
 
2.0%
리 13
 
1.8%
에 13
 
1.8%
과 12
 
1.7%
한 12
 
1.7%
Other values (226) 557
77.9%
Other Punctuation
ValueCountFrequency (%)
, 8
38.1%
! 6
28.6%
? 5
23.8%
. 2
 
9.5%
Uppercase Letter
ValueCountFrequency (%)
I 2
40.0%
T 2
40.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
187
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 715
75.3%
Common 228
 
24.0%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 28
 
3.9%
는 19
 
2.7%
하 16
 
2.2%
스 16
 
2.2%
다 15
 
2.1%
로 14
 
2.0%
리 13
 
1.8%
에 13
 
1.8%
과 12
 
1.7%
한 12
 
1.7%
Other values (226) 557
77.9%
Common
ValueCountFrequency (%)
187
82.0%
- 20
 
8.8%
, 8
 
3.5%
! 6
 
2.6%
? 5
 
2.2%
. 2
 
0.9%
Latin
ValueCountFrequency (%)
I 2
33.3%
T 2
33.3%
o 1
16.7%
C 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 715
75.3%
ASCII 234
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
187
79.9%
- 20
 
8.5%
, 8
 
3.4%
! 6
 
2.6%
? 5
 
2.1%
. 2
 
0.9%
I 2
 
0.9%
T 2
 
0.9%
o 1
 
0.4%
C 1
 
0.4%
Hangul
ValueCountFrequency (%)
이 28
 
3.9%
는 19
 
2.7%
하 16
 
2.2%
스 16
 
2.2%
다 15
 
2.1%
로 14
 
2.0%
리 13
 
1.8%
에 13
 
1.8%
과 12
 
1.7%
한 12
 
1.7%
Other values (226) 557
77.9%

인포그래픽이미지파일명
Text

MISSING 

Distinct54
Distinct (%)100.0%
Missing9946
Missing (%)99.5%
Memory size156.2 KiB
2023-12-13T01:52:36.922231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.777778
Min length10

Characters and Unicode

Total characters582
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st rowinfo16.jpg
2nd rowinfo262.jpg
3rd rowinfo48.jpg
4th rowinfo20.jpg
5th rowinfo213.jpg
ValueCountFrequency (%)
info256.jpg 1
 
1.9%
info255.jpg 1
 
1.9%
info136.jpg 1
 
1.9%
info197.jpg 1
 
1.9%
info17.jpg 1
 
1.9%
info138.jpg 1
 
1.9%
info15.jpg 1
 
1.9%
info43.jpg 1
 
1.9%
info212.jpg 1
 
1.9%
info38.jpg 1
 
1.9%
Other values (44) 44
81.5%
2023-12-13T01:52:37.332268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 54
9.3%
. 54
9.3%
g 54
9.3%
n 54
9.3%
j 54
9.3%
p 54
9.3%
o 54
9.3%
f 54
9.3%
1 38
6.5%
2 29
 
5.0%
Other values (8) 83
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 378
64.9%
Decimal Number 150
 
25.8%
Other Punctuation 54
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38
25.3%
2 29
19.3%
6 13
 
8.7%
5 12
 
8.0%
4 12
 
8.0%
8 11
 
7.3%
3 10
 
6.7%
7 9
 
6.0%
0 8
 
5.3%
9 8
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
i 54
14.3%
g 54
14.3%
n 54
14.3%
j 54
14.3%
p 54
14.3%
o 54
14.3%
f 54
14.3%
Other Punctuation
ValueCountFrequency (%)
. 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 378
64.9%
Common 204
35.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 54
26.5%
1 38
18.6%
2 29
14.2%
6 13
 
6.4%
5 12
 
5.9%
4 12
 
5.9%
8 11
 
5.4%
3 10
 
4.9%
7 9
 
4.4%
0 8
 
3.9%
Latin
ValueCountFrequency (%)
i 54
14.3%
g 54
14.3%
n 54
14.3%
j 54
14.3%
p 54
14.3%
o 54
14.3%
f 54
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 54
9.3%
. 54
9.3%
g 54
9.3%
n 54
9.3%
j 54
9.3%
p 54
9.3%
o 54
9.3%
f 54
9.3%
1 38
6.5%
2 29
 
5.0%
Other values (8) 83
14.3%

인포그래픽썸네일이미지파일명
Text

MISSING 

Distinct54
Distinct (%)100.0%
Missing9946
Missing (%)99.5%
Memory size156.2 KiB
2023-12-13T01:52:37.651179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length15.777778
Min length15

Characters and Unicode

Total characters852
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st rowthum_info16.jpg
2nd rowthum_info262.jpg
3rd rowthum_info48.jpg
4th rowthum_info20.jpg
5th rowthum_info213.jpg
ValueCountFrequency (%)
thum_info256.jpg 1
 
1.9%
thum_info255.jpg 1
 
1.9%
thum_info136.jpg 1
 
1.9%
thum_info197.jpg 1
 
1.9%
thum_info17.jpg 1
 
1.9%
thum_info138.jpg 1
 
1.9%
thum_info15.jpg 1
 
1.9%
thum_info43.jpg 1
 
1.9%
thum_info212.jpg 1
 
1.9%
thum_info38.jpg 1
 
1.9%
Other values (44) 44
81.5%
2023-12-13T01:52:38.102044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 54
 
6.3%
g 54
 
6.3%
u 54
 
6.3%
m 54
 
6.3%
_ 54
 
6.3%
i 54
 
6.3%
n 54
 
6.3%
f 54
 
6.3%
o 54
 
6.3%
h 54
 
6.3%
Other values (13) 312
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 594
69.7%
Decimal Number 150
 
17.6%
Connector Punctuation 54
 
6.3%
Other Punctuation 54
 
6.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 54
9.1%
g 54
9.1%
u 54
9.1%
m 54
9.1%
i 54
9.1%
n 54
9.1%
f 54
9.1%
o 54
9.1%
h 54
9.1%
j 54
9.1%
Decimal Number
ValueCountFrequency (%)
1 38
25.3%
2 29
19.3%
6 13
 
8.7%
4 12
 
8.0%
5 12
 
8.0%
8 11
 
7.3%
3 10
 
6.7%
7 9
 
6.0%
0 8
 
5.3%
9 8
 
5.3%
Connector Punctuation
ValueCountFrequency (%)
_ 54
100.0%
Other Punctuation
ValueCountFrequency (%)
. 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 594
69.7%
Common 258
30.3%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 54
20.9%
. 54
20.9%
1 38
14.7%
2 29
11.2%
6 13
 
5.0%
4 12
 
4.7%
5 12
 
4.7%
8 11
 
4.3%
3 10
 
3.9%
7 9
 
3.5%
Other values (2) 16
 
6.2%
Latin
ValueCountFrequency (%)
t 54
9.1%
g 54
9.1%
u 54
9.1%
m 54
9.1%
i 54
9.1%
n 54
9.1%
f 54
9.1%
o 54
9.1%
h 54
9.1%
j 54
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 54
 
6.3%
g 54
 
6.3%
u 54
 
6.3%
m 54
 
6.3%
_ 54
 
6.3%
i 54
 
6.3%
n 54
 
6.3%
f 54
 
6.3%
o 54
 
6.3%
h 54
 
6.3%
Other values (13) 312
36.6%

인포그래픽이미지파일사이즈
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)94.7%
Missing9943
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean2456216.9
Minimum0
Maximum34247926
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:52:38.280825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile248830.4
Q1547609
median1047888
Q33300349
95-th percentile4780796
Maximum34247926
Range34247926
Interquartile range (IQR)2752740

Descriptive statistics

Standard deviation4604883.1
Coefficient of variation (CV)1.8747868
Kurtosis42.041736
Mean2456216.9
Median Absolute Deviation (MAD)822791
Skewness6.0831621
Sum1.4000436 × 108
Variance2.1204948 × 1013
MonotonicityNot monotonic
2023-12-13T01:52:38.484211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
< 0.1%
2400095 2
 
< 0.1%
618528 1
 
< 0.1%
3543471 1
 
< 0.1%
597172 1
 
< 0.1%
547902 1
 
< 0.1%
600180 1
 
< 0.1%
657595 1
 
< 0.1%
593550 1
 
< 0.1%
783271 1
 
< 0.1%
Other values (44) 44
 
0.4%
(Missing) 9943
99.4%
ValueCountFrequency (%)
0 3
< 0.1%
311038 1
 
< 0.1%
336507 1
 
< 0.1%
337580 1
 
< 0.1%
357444 1
 
< 0.1%
368902 1
 
< 0.1%
370992 1
 
< 0.1%
426589 1
 
< 0.1%
518460 1
 
< 0.1%
522415 1
 
< 0.1%
ValueCountFrequency (%)
34247926 1
< 0.1%
7165229 1
< 0.1%
5732824 1
< 0.1%
4542789 1
< 0.1%
4469168 1
< 0.1%
4231450 1
< 0.1%
4162575 1
< 0.1%
4160470 1
< 0.1%
4112727 1
< 0.1%
4080181 1
< 0.1%

사용여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)3.5%
Missing9943
Missing (%)99.4%
Memory size97.7 KiB
True
 
54
False
 
3
(Missing)
9943 
ValueCountFrequency (%)
True 54
 
0.5%
False 3
 
< 0.1%
(Missing) 9943
99.4%
2023-12-13T01:52:38.646606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록일시
Date

MISSING 

Distinct49
Distinct (%)86.0%
Missing9943
Missing (%)99.4%
Memory size156.2 KiB
Minimum2015-11-30 09:50:00
Maximum2020-09-29 10:03:00
2023-12-13T01:52:38.758351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.966853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

인포그래픽순번
Real number (ℝ)

Distinct164
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.0586
Minimum1
Maximum264
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:52:39.184682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q110
median24
Q338
95-th percentile182
Maximum264
Range263
Interquartile range (IQR)28

Descriptive statistics

Standard deviation48.849473
Coefficient of variation (CV)1.3933663
Kurtosis10.156607
Mean35.0586
Median Absolute Deviation (MAD)14
Skewness3.2172699
Sum350586
Variance2386.271
MonotonicityNot monotonic
2023-12-13T01:52:39.337679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 562
 
5.6%
3 319
 
3.2%
1 318
 
3.2%
37 312
 
3.1%
2 286
 
2.9%
32 235
 
2.4%
7 234
 
2.3%
19 227
 
2.3%
10 227
 
2.3%
31 222
 
2.2%
Other values (154) 7058
70.6%
ValueCountFrequency (%)
1 318
3.2%
2 286
2.9%
3 319
3.2%
4 148
 
1.5%
5 562
5.6%
6 213
 
2.1%
7 234
2.3%
8 176
 
1.8%
9 197
 
2.0%
10 227
2.3%
ValueCountFrequency (%)
264 5
 
0.1%
263 21
0.2%
262 13
0.1%
261 8
 
0.1%
260 14
0.1%
259 11
0.1%
258 7
 
0.1%
257 8
 
0.1%
256 12
0.1%
255 14
0.1%

다운로드일시
Date

Distinct8011
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-12-17 15:02:00
Maximum2020-10-18 14:05:00
2023-12-13T01:52:39.528204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.723644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T01:52:33.614188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:32.978528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:33.320124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:33.719281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:33.097885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:33.408524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:33.815655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:33.209939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:33.514672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:52:39.848496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과학영역인포그래픽명인포그래픽내용인포그래픽이미지파일명인포그래픽썸네일이미지파일명인포그래픽이미지파일사이즈사용여부등록일시인포그래픽순번
순번1.000NaNNaNNaNNaNNaNNaNNaNNaN0.274
과학영역NaN1.0001.0001.0001.0001.0000.2330.0000.8890.000
인포그래픽명NaN1.0001.0001.0001.0001.0001.0001.0001.0001.000
인포그래픽내용NaN1.0001.0001.0001.0001.0001.0001.0001.0001.000
인포그래픽이미지파일명NaN1.0001.0001.0001.0001.0001.000NaN1.0001.000
인포그래픽썸네일이미지파일명NaN1.0001.0001.0001.0001.0001.000NaN1.0001.000
인포그래픽이미지파일사이즈NaN0.2331.0001.0001.0001.0001.0000.0001.0000.000
사용여부NaN0.0001.0001.000NaNNaN0.0001.0001.0000.000
등록일시NaN0.8891.0001.0001.0001.0001.0001.0001.0000.000
인포그래픽순번0.2740.0001.0001.0001.0001.0000.0000.0000.0001.000
2023-12-13T01:52:40.363649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용여부과학영역
사용여부1.0000.000
과학영역0.0001.000
2023-12-13T01:52:40.472934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번인포그래픽이미지파일사이즈인포그래픽순번과학영역사용여부
순번1.0000.3750.0171.0001.000
인포그래픽이미지파일사이즈0.3751.000-0.0110.1430.000
인포그래픽순번0.017-0.0111.0000.0000.000
과학영역1.0000.1430.0001.0000.000
사용여부1.0000.0000.0000.0001.000

Missing values

2023-12-13T01:52:33.956117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:52:34.122349image/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.
2023-12-13T01:52:34.347698image/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

순번과학영역인포그래픽명인포그래픽내용인포그래픽이미지파일명인포그래픽썸네일이미지파일명인포그래픽이미지파일사이즈사용여부등록일시인포그래픽순번다운로드일시
1819018289<NA><NA><NA><NA><NA><NA><NA><NA>242019-04-05 10:42
1562615725<NA><NA><NA><NA><NA><NA><NA><NA>2002018-08-25 14:36
1920019299<NA><NA><NA><NA><NA><NA><NA><NA>302019-06-13 1:27
1676216861<NA><NA><NA><NA><NA><NA><NA><NA>272018-10-31 10:26
25932692<NA><NA><NA><NA><NA><NA><NA><NA>212016-04-26 2:08
90329131<NA><NA><NA><NA><NA><NA><NA><NA>202017-02-16 14:15
79948093<NA><NA><NA><NA><NA><NA><NA><NA>32016-12-29 21:56
56235722<NA><NA><NA><NA><NA><NA><NA><NA>72016-10-10 7:06
1840018499<NA><NA><NA><NA><NA><NA><NA><NA>82019-04-16 10:32
32683367<NA><NA><NA><NA><NA><NA><NA><NA>352016-06-03 8:46
순번과학영역인포그래픽명인포그래픽내용인포그래픽이미지파일명인포그래픽썸네일이미지파일명인포그래픽이미지파일사이즈사용여부등록일시인포그래픽순번다운로드일시
22792378<NA><NA><NA><NA><NA><NA><NA><NA>252016-04-07 19:34
88088907<NA><NA><NA><NA><NA><NA><NA><NA>92017-02-10 0:44
98439942<NA><NA><NA><NA><NA><NA><NA><NA>352017-03-16 0:46
1119311292<NA><NA><NA><NA><NA><NA><NA><NA>22017-06-17 16:18
57145813<NA><NA><NA><NA><NA><NA><NA><NA>492016-10-13 10:13
1740317502<NA><NA><NA><NA><NA><NA><NA><NA>122019-01-09 14:43
2244922548<NA><NA><NA><NA><NA><NA><NA><NA>1282020-04-06 16:13
9761075<NA><NA><NA><NA><NA><NA><NA><NA>492016-02-11 11:57
2264022739<NA><NA><NA><NA><NA><NA><NA><NA>312020-05-22 0:27
1867318772<NA><NA><NA><NA><NA><NA><NA><NA>2112019-04-24 10:06