Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells69488
Missing cells (%)63.2%
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 (97.1%)Imbalance
사용여부 is highly imbalanced (75.5%)Imbalance
인포그래픽명 has 9926 (99.3%) missing valuesMissing
인포그래픽내용 has 9926 (99.3%) missing valuesMissing
인포그래픽이미지파일명 has 9929 (99.3%) missing valuesMissing
인포그래픽썸네일이미지파일명 has 9929 (99.3%) missing valuesMissing
인포그래픽이미지파일사이즈 has 9926 (99.3%) missing valuesMissing
사용여부 has 9926 (99.3%) missing valuesMissing
등록일시 has 9926 (99.3%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:52:42.335212
Analysis finished2023-12-12 16:52:44.776168
Duration2.44 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%
Mean11478.613
Minimum3
Maximum22964
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:52:44.858386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1259.9
Q15791.25
median11440.5
Q317136.5
95-th percentile21834.2
Maximum22964
Range22961
Interquartile range (IQR)11345.25

Descriptive statistics

Standard deviation6591.5308
Coefficient of variation (CV)0.57424451
Kurtosis-1.1879177
Mean11478.613
Median Absolute Deviation (MAD)5682
Skewness0.016984634
Sum1.1478614 × 108
Variance43448278
MonotonicityNot monotonic
2023-12-13T01:52:45.008192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6566 1
 
< 0.1%
18757 1
 
< 0.1%
16819 1
 
< 0.1%
20313 1
 
< 0.1%
2213 1
 
< 0.1%
11321 1
 
< 0.1%
4648 1
 
< 0.1%
4929 1
 
< 0.1%
11373 1
 
< 0.1%
722 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
14 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
21 1
< 0.1%
22 1
< 0.1%
24 1
< 0.1%
ValueCountFrequency (%)
22964 1
< 0.1%
22963 1
< 0.1%
22961 1
< 0.1%
22960 1
< 0.1%
22959 1
< 0.1%
22953 1
< 0.1%
22952 1
< 0.1%
22951 1
< 0.1%
22950 1
< 0.1%
22948 1
< 0.1%

과학영역
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9926 
생활과학
 
29
ICT
 
13
화학
 
11
지구과학
 
9
Other values (2)
 
12

Length

Max length4
Median length4
Mean length3.9957
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> 9926
99.3%
생활과학 29
 
0.3%
ICT 13
 
0.1%
화학 11
 
0.1%
지구과학 9
 
0.1%
생명과학 8
 
0.1%
물리 4
 
< 0.1%

Length

2023-12-13T01:52:45.190445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:52:45.343934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9926
99.3%
생활과학 29
 
0.3%
ict 13
 
0.1%
화학 11
 
0.1%
지구과학 9
 
0.1%
생명과학 8
 
0.1%
물리 4
 
< 0.1%

인포그래픽명
Text

MISSING 

Distinct74
Distinct (%)100.0%
Missing9926
Missing (%)99.3%
Memory size156.2 KiB
2023-12-13T01:52:45.690254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length23.5
Mean length16.297297
Min length1

Characters and Unicode

Total characters1206
Distinct characters306
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

Unique74 ?
Unique (%)100.0%

Sample

1st row얼굴이 지갑이고 열쇠가 된다!! - 안면인식결제 시스템
2nd row상태변화
3rd row5. 거미손으로 만들어주는 골키퍼 장갑
4th row이제는 로봇과 대화로 답을 찾는다?! - 챗봇
5th row8.오심을 줄여주는 제 3의 심판
ValueCountFrequency (%)
22
 
6.9%
첨단 5
 
1.6%
지진 3
 
0.9%
태양계 3
 
0.9%
스포츠 2
 
0.6%
로봇 2
 
0.6%
무한한 2
 
0.6%
방법 2
 
0.6%
챗봇 2
 
0.6%
알아 2
 
0.6%
Other values (263) 276
86.0%
2023-12-13T01:52:46.370202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
 
20.5%
이 24
 
2.0%
는 24
 
2.0%
- 24
 
2.0%
의 21
 
1.7%
스 18
 
1.5%
로 17
 
1.4%
을 16
 
1.3%
에 16
 
1.3%
지 16
 
1.3%
Other values (296) 783
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 885
73.4%
Space Separator 247
 
20.5%
Other Punctuation 33
 
2.7%
Dash Punctuation 24
 
2.0%
Decimal Number 11
 
0.9%
Uppercase Letter 5
 
0.4%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 24
 
2.7%
는 24
 
2.7%
의 21
 
2.4%
스 18
 
2.0%
로 17
 
1.9%
을 16
 
1.8%
에 16
 
1.8%
지 16
 
1.8%
다 15
 
1.7%
한 15
 
1.7%
Other values (279) 703
79.4%
Decimal Number
ValueCountFrequency (%)
6 2
18.2%
1 2
18.2%
0 2
18.2%
3 2
18.2%
7 1
9.1%
5 1
9.1%
8 1
9.1%
Other Punctuation
ValueCountFrequency (%)
! 13
39.4%
, 8
24.2%
? 6
18.2%
. 6
18.2%
Uppercase Letter
ValueCountFrequency (%)
I 2
40.0%
T 2
40.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 885
73.4%
Common 315
 
26.1%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 24
 
2.7%
는 24
 
2.7%
의 21
 
2.4%
스 18
 
2.0%
로 17
 
1.9%
을 16
 
1.8%
에 16
 
1.8%
지 16
 
1.8%
다 15
 
1.7%
한 15
 
1.7%
Other values (279) 703
79.4%
Common
ValueCountFrequency (%)
247
78.4%
- 24
 
7.6%
! 13
 
4.1%
, 8
 
2.5%
? 6
 
1.9%
. 6
 
1.9%
6 2
 
0.6%
1 2
 
0.6%
0 2
 
0.6%
3 2
 
0.6%
Other values (3) 3
 
1.0%
Latin
ValueCountFrequency (%)
I 2
33.3%
T 2
33.3%
C 1
16.7%
o 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 885
73.4%
ASCII 321
 
26.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
76.9%
- 24
 
7.5%
! 13
 
4.0%
, 8
 
2.5%
? 6
 
1.9%
. 6
 
1.9%
6 2
 
0.6%
I 2
 
0.6%
1 2
 
0.6%
0 2
 
0.6%
Other values (7) 9
 
2.8%
Hangul
ValueCountFrequency (%)
이 24
 
2.7%
는 24
 
2.7%
의 21
 
2.4%
스 18
 
2.0%
로 17
 
1.9%
을 16
 
1.8%
에 16
 
1.8%
지 16
 
1.8%
다 15
 
1.7%
한 15
 
1.7%
Other values (279) 703
79.4%

인포그래픽내용
Text

MISSING 

Distinct74
Distinct (%)100.0%
Missing9926
Missing (%)99.3%
Memory size156.2 KiB
2023-12-13T01:52:46.705199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length23
Mean length16.135135
Min length1

Characters and Unicode

Total characters1194
Distinct characters304
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

Unique74 ?
Unique (%)100.0%

Sample

1st row얼굴이 지갑이고 열쇠가 된다!! - 안면인식결제 시스템
2nd row상태변화
3rd row거미손으로 만들어주는 골키퍼 장갑
4th row이제는 로봇과 대화로 답을 찾는다?! - 챗봇
5th row오심을 줄여주는 제 3의 심판
ValueCountFrequency (%)
22
 
6.9%
첨단 5
 
1.6%
지진 3
 
0.9%
방법 2
 
0.6%
있는 2
 
0.6%
것이 2
 
0.6%
눈 2
 
0.6%
크리스퍼 2
 
0.6%
태양계 2
 
0.6%
과학으로 2
 
0.6%
Other values (263) 276
86.2%
2023-12-13T01:52:47.197642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
246
 
20.6%
- 24
 
2.0%
이 24
 
2.0%
는 24
 
2.0%
의 21
 
1.8%
스 18
 
1.5%
로 17
 
1.4%
지 16
 
1.3%
을 16
 
1.3%
에 16
 
1.3%
Other values (294) 772
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 884
74.0%
Space Separator 246
 
20.6%
Other Punctuation 29
 
2.4%
Dash Punctuation 24
 
2.0%
Uppercase Letter 5
 
0.4%
Decimal Number 5
 
0.4%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 24
 
2.7%
는 24
 
2.7%
의 21
 
2.4%
스 18
 
2.0%
로 17
 
1.9%
지 16
 
1.8%
을 16
 
1.8%
에 16
 
1.8%
다 15
 
1.7%
한 15
 
1.7%
Other values (280) 702
79.4%
Other Punctuation
ValueCountFrequency (%)
! 14
48.3%
, 8
27.6%
? 6
20.7%
. 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
6 1
20.0%
0 1
20.0%
1 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
I 2
40.0%
T 2
40.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
246
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 884
74.0%
Common 304
 
25.5%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 24
 
2.7%
는 24
 
2.7%
의 21
 
2.4%
스 18
 
2.0%
로 17
 
1.9%
지 16
 
1.8%
을 16
 
1.8%
에 16
 
1.8%
다 15
 
1.7%
한 15
 
1.7%
Other values (280) 702
79.4%
Common
ValueCountFrequency (%)
246
80.9%
- 24
 
7.9%
! 14
 
4.6%
, 8
 
2.6%
? 6
 
2.0%
3 2
 
0.7%
6 1
 
0.3%
0 1
 
0.3%
1 1
 
0.3%
. 1
 
0.3%
Latin
ValueCountFrequency (%)
I 2
33.3%
T 2
33.3%
C 1
16.7%
o 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 884
74.0%
ASCII 310
 
26.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
246
79.4%
- 24
 
7.7%
! 14
 
4.5%
, 8
 
2.6%
? 6
 
1.9%
I 2
 
0.6%
3 2
 
0.6%
T 2
 
0.6%
6 1
 
0.3%
0 1
 
0.3%
Other values (4) 4
 
1.3%
Hangul
ValueCountFrequency (%)
이 24
 
2.7%
는 24
 
2.7%
의 21
 
2.4%
스 18
 
2.0%
로 17
 
1.9%
지 16
 
1.8%
을 16
 
1.8%
에 16
 
1.8%
다 15
 
1.7%
한 15
 
1.7%
Other values (280) 702
79.4%

인포그래픽이미지파일명
Text

MISSING 

Distinct71
Distinct (%)100.0%
Missing9929
Missing (%)99.3%
Memory size156.2 KiB
2023-12-13T01:52:47.493868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.647887
Min length9

Characters and Unicode

Total characters756
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

Unique71 ?
Unique (%)100.0%

Sample

1st rowinfo192.jpg
2nd rowinfo10.jpg
3rd rowinfo214.jpg
4th rowinfo179.jpg
5th rowinfo217.jpg
ValueCountFrequency (%)
info192.jpg 1
 
1.4%
info22.jpg 1
 
1.4%
info243.jpg 1
 
1.4%
info162.jpg 1
 
1.4%
info133.jpg 1
 
1.4%
info255.jpg 1
 
1.4%
info38.jpg 1
 
1.4%
info215.jpg 1
 
1.4%
info167.jpg 1
 
1.4%
info6.jpg 1
 
1.4%
Other values (61) 61
85.9%
2023-12-13T01:52:47.935087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 71
9.4%
. 71
9.4%
g 71
9.4%
n 71
9.4%
j 71
9.4%
p 71
9.4%
o 71
9.4%
f 71
9.4%
1 43
 
5.7%
2 34
 
4.5%
Other values (8) 111
14.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 497
65.7%
Decimal Number 188
 
24.9%
Other Punctuation 71
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 43
22.9%
2 34
18.1%
4 18
9.6%
0 16
 
8.5%
3 15
 
8.0%
9 13
 
6.9%
7 13
 
6.9%
6 13
 
6.9%
5 12
 
6.4%
8 11
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
i 71
14.3%
g 71
14.3%
n 71
14.3%
j 71
14.3%
p 71
14.3%
o 71
14.3%
f 71
14.3%
Other Punctuation
ValueCountFrequency (%)
. 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 497
65.7%
Common 259
34.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 71
27.4%
1 43
16.6%
2 34
13.1%
4 18
 
6.9%
0 16
 
6.2%
3 15
 
5.8%
9 13
 
5.0%
7 13
 
5.0%
6 13
 
5.0%
5 12
 
4.6%
Latin
ValueCountFrequency (%)
i 71
14.3%
g 71
14.3%
n 71
14.3%
j 71
14.3%
p 71
14.3%
o 71
14.3%
f 71
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 71
9.4%
. 71
9.4%
g 71
9.4%
n 71
9.4%
j 71
9.4%
p 71
9.4%
o 71
9.4%
f 71
9.4%
1 43
 
5.7%
2 34
 
4.5%
Other values (8) 111
14.7%

인포그래픽썸네일이미지파일명
Text

MISSING 

Distinct71
Distinct (%)100.0%
Missing9929
Missing (%)99.3%
Memory size156.2 KiB
2023-12-13T01:52:48.205005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length15.647887
Min length14

Characters and Unicode

Total characters1111
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

Unique71 ?
Unique (%)100.0%

Sample

1st rowthum_info192.jpg
2nd rowthum_info10.jpg
3rd rowthum_info214.jpg
4th rowthum_info179.jpg
5th rowthum_info217.jpg
ValueCountFrequency (%)
thum_info192.jpg 1
 
1.4%
thum_info22.jpg 1
 
1.4%
thum_info243.jpg 1
 
1.4%
thum_info162.jpg 1
 
1.4%
thum_info133.jpg 1
 
1.4%
thum_info255.jpg 1
 
1.4%
thum_info38.jpg 1
 
1.4%
thum_info215.jpg 1
 
1.4%
thum_info167.jpg 1
 
1.4%
thum_info6.jpg 1
 
1.4%
Other values (61) 61
85.9%
2023-12-13T01:52:48.635537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 71
 
6.4%
p 71
 
6.4%
u 71
 
6.4%
m 71
 
6.4%
_ 71
 
6.4%
i 71
 
6.4%
n 71
 
6.4%
f 71
 
6.4%
o 71
 
6.4%
g 71
 
6.4%
Other values (13) 401
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 781
70.3%
Decimal Number 188
 
16.9%
Connector Punctuation 71
 
6.4%
Other Punctuation 71
 
6.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 71
9.1%
p 71
9.1%
u 71
9.1%
m 71
9.1%
i 71
9.1%
n 71
9.1%
f 71
9.1%
o 71
9.1%
g 71
9.1%
h 71
9.1%
Decimal Number
ValueCountFrequency (%)
1 43
22.9%
2 34
18.1%
4 18
9.6%
0 16
 
8.5%
3 15
 
8.0%
9 13
 
6.9%
7 13
 
6.9%
6 13
 
6.9%
5 12
 
6.4%
8 11
 
5.9%
Connector Punctuation
ValueCountFrequency (%)
_ 71
100.0%
Other Punctuation
ValueCountFrequency (%)
. 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 781
70.3%
Common 330
29.7%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 71
21.5%
. 71
21.5%
1 43
13.0%
2 34
10.3%
4 18
 
5.5%
0 16
 
4.8%
3 15
 
4.5%
9 13
 
3.9%
7 13
 
3.9%
6 13
 
3.9%
Other values (2) 23
 
7.0%
Latin
ValueCountFrequency (%)
t 71
9.1%
p 71
9.1%
u 71
9.1%
m 71
9.1%
i 71
9.1%
n 71
9.1%
f 71
9.1%
o 71
9.1%
g 71
9.1%
h 71
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 71
 
6.4%
p 71
 
6.4%
u 71
 
6.4%
m 71
 
6.4%
_ 71
 
6.4%
i 71
 
6.4%
n 71
 
6.4%
f 71
 
6.4%
o 71
 
6.4%
g 71
 
6.4%
Other values (13) 401
36.1%

인포그래픽이미지파일사이즈
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)97.3%
Missing9926
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean1834662.5
Minimum0
Maximum8170143
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:52:48.809564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile316693.65
Q1533659.25
median758967.5
Q33135837.5
95-th percentile4782685.9
Maximum8170143
Range8170143
Interquartile range (IQR)2602178.2

Descriptive statistics

Standard deviation1836405.4
Coefficient of variation (CV)1.00095
Kurtosis1.032631
Mean1834662.5
Median Absolute Deviation (MAD)413740.5
Skewness1.2506552
Sum1.3576502 × 108
Variance3.3723848 × 1012
MonotonicityNot monotonic
2023-12-13T01:52:48.978214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
< 0.1%
2444406 1
 
< 0.1%
594810 1
 
< 0.1%
3058169 1
 
< 0.1%
368902 1
 
< 0.1%
582263 1
 
< 0.1%
4542789 1
 
< 0.1%
593550 1
 
< 0.1%
426589 1
 
< 0.1%
343372 1
 
< 0.1%
Other values (62) 62
 
0.6%
(Missing) 9926
99.3%
ValueCountFrequency (%)
0 3
< 0.1%
311038 1
 
< 0.1%
319739 1
 
< 0.1%
336507 1
 
< 0.1%
343372 1
 
< 0.1%
347082 1
 
< 0.1%
363735 1
 
< 0.1%
368269 1
 
< 0.1%
368902 1
 
< 0.1%
370992 1
 
< 0.1%
ValueCountFrequency (%)
8170143 1
< 0.1%
6596394 1
< 0.1%
6350378 1
< 0.1%
4836489 1
< 0.1%
4753715 1
< 0.1%
4542789 1
< 0.1%
4469168 1
< 0.1%
4270528 1
< 0.1%
4216377 1
< 0.1%
4162575 1
< 0.1%

사용여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)2.7%
Missing9926
Missing (%)99.3%
Memory size97.7 KiB
True
 
71
False
 
3
(Missing)
9926 
ValueCountFrequency (%)
True 71
 
0.7%
False 3
 
< 0.1%
(Missing) 9926
99.3%
2023-12-13T01:52:49.108368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록일시
Date

MISSING 

Distinct58
Distinct (%)78.4%
Missing9926
Missing (%)99.3%
Memory size156.2 KiB
Minimum2015-10-23 16:03:00
Maximum2020-09-29 10:00:00
2023-12-13T01:52:49.206927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:49.343299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인포그래픽순번
Real number (ℝ)

Distinct161
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.9743
Minimum1
Maximum264
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:52:49.496969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q110
median24
Q339
95-th percentile181
Maximum264
Range263
Interquartile range (IQR)29

Descriptive statistics

Standard deviation48.186656
Coefficient of variation (CV)1.3777733
Kurtosis10.259285
Mean34.9743
Median Absolute Deviation (MAD)15
Skewness3.2243659
Sum349743
Variance2321.9538
MonotonicityNot monotonic
2023-12-13T01:52:49.898062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 614
 
6.1%
37 322
 
3.2%
3 320
 
3.2%
1 311
 
3.1%
2 258
 
2.6%
22 225
 
2.2%
39 221
 
2.2%
19 221
 
2.2%
10 216
 
2.2%
6 214
 
2.1%
Other values (151) 7078
70.8%
ValueCountFrequency (%)
1 311
3.1%
2 258
2.6%
3 320
3.2%
4 162
 
1.6%
5 614
6.1%
6 214
 
2.1%
7 203
 
2.0%
8 184
 
1.8%
9 180
 
1.8%
10 216
 
2.2%
ValueCountFrequency (%)
264 6
 
0.1%
263 19
0.2%
262 13
0.1%
261 3
 
< 0.1%
260 9
0.1%
259 12
0.1%
258 9
0.1%
257 4
 
< 0.1%
256 8
0.1%
255 14
0.1%

다운로드일시
Date

Distinct7926
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-12-14 13:59:00
Maximum2020-10-23 20:40:00
2023-12-13T01:52:50.055452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:50.194863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T01:52:43.952913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:43.323758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:43.633025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:44.044840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:43.422182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:43.744010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:44.149521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:43.541443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:43.854090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:52:50.304405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과학영역인포그래픽명인포그래픽내용인포그래픽이미지파일명인포그래픽썸네일이미지파일명인포그래픽이미지파일사이즈사용여부등록일시인포그래픽순번
순번1.000NaNNaNNaNNaNNaNNaNNaNNaN0.279
과학영역NaN1.0001.0001.0001.0001.0000.3200.3380.7250.000
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
인포그래픽이미지파일사이즈NaN0.3201.0001.0001.0001.0001.0000.0000.9850.000
사용여부NaN0.3381.0001.000NaNNaN0.0001.0001.0000.000
등록일시NaN0.7251.0001.0001.0001.0000.9851.0001.0000.157
인포그래픽순번0.2790.0001.0001.0001.0001.0000.0000.0000.1571.000
2023-12-13T01:52:50.451029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용여부과학영역
사용여부1.0000.234
과학영역0.2341.000
2023-12-13T01:52:50.531845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번인포그래픽이미지파일사이즈인포그래픽순번과학영역사용여부
순번1.0000.3940.0081.0001.000
인포그래픽이미지파일사이즈0.3941.0000.1160.1560.000
인포그래픽순번0.0080.1161.0000.0000.000
과학영역1.0000.1560.0001.0000.234
사용여부1.0000.0000.0000.2341.000

Missing values

2023-12-13T01:52:44.313029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:52:44.498751image/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.
2023-12-13T01:52:44.666954image/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
64676566<NA><NA><NA><NA><NA><NA><NA><NA>492016-11-05 09:24
1941719516<NA><NA><NA><NA><NA><NA><NA><NA>32019-07-12 01:04
60146113<NA><NA><NA><NA><NA><NA><NA><NA>222016-10-23 07:28
1082310922<NA><NA><NA><NA><NA><NA><NA><NA>122017-05-23 10:05
2117221271<NA><NA><NA><NA><NA><NA><NA><NA>2622019-11-26 00:03
97429841<NA><NA><NA><NA><NA><NA><NA><NA>322017-03-07 21:07
16381737<NA><NA><NA><NA><NA><NA><NA><NA>182016-03-06 01:32
998710086<NA><NA><NA><NA><NA><NA><NA><NA>12017-03-31 05:37
1713817237<NA><NA><NA><NA><NA><NA><NA><NA>82018-11-28 11:56
52825381<NA><NA><NA><NA><NA><NA><NA><NA>132016-09-27 00:28
순번과학영역인포그래픽명인포그래픽내용인포그래픽이미지파일명인포그래픽썸네일이미지파일명인포그래픽이미지파일사이즈사용여부등록일시인포그래픽순번다운로드일시
1214212241<NA><NA><NA><NA><NA><NA><NA><NA>472017-10-21 20:28
1215212251<NA><NA><NA><NA><NA><NA><NA><NA>72017-10-22 05:25
21822281<NA><NA><NA><NA><NA><NA><NA><NA>312016-04-03 10:57
1143811537<NA><NA><NA><NA><NA><NA><NA><NA>352017-07-18 15:42
55815680<NA><NA><NA><NA><NA><NA><NA><NA>442016-10-08 20:00
36843783<NA><NA><NA><NA><NA><NA><NA><NA>352016-06-29 22:42
98399938<NA><NA><NA><NA><NA><NA><NA><NA>412017-03-15 17:15
78517950<NA><NA><NA><NA><NA><NA><NA><NA>162016-12-21 18:57
1237812477<NA><NA><NA><NA><NA><NA><NA><NA>52017-10-28 22:48
2203622135<NA><NA><NA><NA><NA><NA><NA><NA>2062020-02-29 22:18