Overview

Dataset statistics

Number of variables7
Number of observations225
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.3 KiB
Average record size in memory60.6 B

Variable types

Numeric3
Categorical3
Text1

Dataset

Description2021년 2월 기준 기술과 관련된 정보입니다.
Author한국연구재단 정보통신기획평가원
URLhttps://www.data.go.kr/data/15092598/fileData.do

Alerts

생성자 has constant value ""Constant
생성일시 has constant value ""Constant
기술분류 코드 is highly overall correlated with 상위 기술분류 코드 and 1 other fieldsHigh correlation
상위 기술분류 코드 is highly overall correlated with 기술분류 코드 and 1 other fieldsHigh correlation
과제정보 기술분류 코드 is highly overall correlated with 기술분류 코드 and 1 other fieldsHigh correlation
기술분류 코드 has unique valuesUnique
과제정보 기술분류 코드 has unique valuesUnique
상위 기술분류 코드 has 11 (4.9%) zerosZeros

Reproduction

Analysis started2024-04-17 13:02:14.572941
Analysis finished2024-04-17 13:02:15.789019
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기술분류 코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct225
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72261.751
Minimum0
Maximum999999
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-17T22:02:15.870761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12241.6
Q140202
median60301
Q380603
95-th percentile100200.8
Maximum999999
Range999999
Interquartile range (IQR)40401

Descriptive statistics

Standard deviation110913.57
Coefficient of variation (CV)1.5348862
Kurtosis63.349505
Mean72261.751
Median Absolute Deviation (MAD)20200
Skewness7.7985944
Sum16258894
Variance1.2301819 × 1010
MonotonicityNot monotonic
2024-04-17T22:02:16.001906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100301 1
 
0.4%
80401 1
 
0.4%
70102 1
 
0.4%
70103 1
 
0.4%
70104 1
 
0.4%
70201 1
 
0.4%
70202 1
 
0.4%
70203 1
 
0.4%
70204 1
 
0.4%
70205 1
 
0.4%
Other values (215) 215
95.6%
ValueCountFrequency (%)
0 1
0.4%
10000 1
0.4%
10100 1
0.4%
10101 1
0.4%
10102 1
0.4%
10200 1
0.4%
10201 1
0.4%
10202 1
0.4%
10203 1
0.4%
10300 1
0.4%
ValueCountFrequency (%)
999999 1
0.4%
999900 1
0.4%
990000 1
0.4%
100303 1
0.4%
100302 1
0.4%
100301 1
0.4%
100300 1
0.4%
100205 1
0.4%
100204 1
0.4%
100203 1
0.4%

생성자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
SYSTEM
225 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
SYSTEM 225
100.0%

Length

2024-04-17T22:02:16.107012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:02:16.183825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
system 225
100.0%

생성일시
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2016-03-24 오후 5:04:53
225 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016-03-24 오후 5:04:53
2nd row2016-03-24 오후 5:04:53
3rd row2016-03-24 오후 5:04:53
4th row2016-03-24 오후 5:04:53
5th row2016-03-24 오후 5:04:53

Common Values

ValueCountFrequency (%)
2016-03-24 오후 5:04:53 225
100.0%

Length

2024-04-17T22:02:16.262744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:02:16.353817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016-03-24 225
33.3%
오후 225
33.3%
5:04:53 225
33.3%

상위 기술분류 코드
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct54
Distinct (%)24.1%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean65612.5
Minimum0
Maximum999900
Zeros11
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-17T22:02:16.459863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10000
Q140000
median60100
Q380525
95-th percentile100100
Maximum999900
Range999900
Interquartile range (IQR)40525

Descriptive statistics

Standard deviation92941.151
Coefficient of variation (CV)1.4165159
Kurtosis89.104652
Mean65612.5
Median Absolute Deviation (MAD)20400
Skewness9.0118542
Sum14697200
Variance8.6380575 × 109
MonotonicityNot monotonic
2024-04-17T22:02:16.587364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11
 
4.9%
90300 9
 
4.0%
80600 8
 
3.6%
30200 7
 
3.1%
80400 6
 
2.7%
90400 6
 
2.7%
80000 6
 
2.7%
90200 6
 
2.7%
50000 6
 
2.7%
60300 6
 
2.7%
Other values (44) 153
68.0%
ValueCountFrequency (%)
0 11
4.9%
10000 3
 
1.3%
10100 2
 
0.9%
10200 3
 
1.3%
10300 2
 
0.9%
20000 3
 
1.3%
20100 5
2.2%
20200 5
2.2%
20300 3
 
1.3%
30000 4
 
1.8%
ValueCountFrequency (%)
999900 1
 
0.4%
990000 1
 
0.4%
100300 3
 
1.3%
100200 5
2.2%
100100 3
 
1.3%
100000 3
 
1.3%
90500 1
 
0.4%
90400 6
2.7%
90300 9
4.0%
90200 6
2.7%

기술분류 레벨
Categorical

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
4
171 
3
42 
2
 
11
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row4
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
4 171
76.0%
3 42
 
18.7%
2 11
 
4.9%
1 1
 
0.4%

Length

2024-04-17T22:02:16.693135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:02:16.783683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 171
76.0%
3 42
 
18.7%
2 11
 
4.9%
1 1
 
0.4%

기술분류 이름
Text

Distinct218
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-17T22:02:17.069005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length9.2577778
Min length2

Characters and Unicode

Total characters2083
Distinct characters290
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique216 ?
Unique (%)96.0%

Sample

1st row센서·소자·소재
2nd row정보통신
3rd row이동통신
4th row네트워크
5th row방송·스마트미디어
ValueCountFrequency (%)
기타 17
 
3.5%
ict 16
 
3.3%
및 16
 
3.3%
콘텐츠 12
 
2.5%
응용 11
 
2.3%
기술 11
 
2.3%
서비스 10
 
2.1%
컴퓨팅 10
 
2.1%
sw 10
 
2.1%
플랫폼 9
 
1.9%
Other values (251) 362
74.8%
2024-04-17T22:02:17.493179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
260
 
12.5%
스 75
 
3.6%
기 47
 
2.3%
· 36
 
1.7%
이 35
 
1.7%
보 32
 
1.5%
T 32
 
1.5%
인 30
 
1.4%
트 29
 
1.4%
I 28
 
1.3%
Other values (280) 1479
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1471
70.6%
Space Separator 260
 
12.5%
Uppercase Letter 174
 
8.4%
Lowercase Letter 80
 
3.8%
Other Punctuation 75
 
3.6%
Close Punctuation 9
 
0.4%
Open Punctuation 9
 
0.4%
Decimal Number 3
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 75
 
5.1%
기 47
 
3.2%
이 35
 
2.4%
보 32
 
2.2%
인 30
 
2.0%
트 29
 
2.0%
서 28
 
1.9%
비 27
 
1.8%
안 26
 
1.8%
어 23
 
1.6%
Other values (234) 1119
76.1%
Lowercase Letter
ValueCountFrequency (%)
e 11
13.8%
r 10
12.5%
a 8
10.0%
o 8
10.0%
i 7
8.8%
t 6
 
7.5%
n 5
 
6.2%
u 4
 
5.0%
c 3
 
3.8%
v 3
 
3.8%
Other values (10) 15
18.8%
Uppercase Letter
ValueCountFrequency (%)
T 32
18.4%
I 28
16.1%
C 25
14.4%
S 23
13.2%
W 15
8.6%
D 9
 
5.2%
H 7
 
4.0%
V 6
 
3.4%
N 6
 
3.4%
U 5
 
2.9%
Other values (7) 18
10.3%
Other Punctuation
ValueCountFrequency (%)
· 36
48.0%
/ 28
37.3%
, 10
 
13.3%
. 1
 
1.3%
Space Separator
ValueCountFrequency (%)
260
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Decimal Number
ValueCountFrequency (%)
3 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1471
70.6%
Common 358
 
17.2%
Latin 254
 
12.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 75
 
5.1%
기 47
 
3.2%
이 35
 
2.4%
보 32
 
2.2%
인 30
 
2.0%
트 29
 
2.0%
서 28
 
1.9%
비 27
 
1.8%
안 26
 
1.8%
어 23
 
1.6%
Other values (234) 1119
76.1%
Latin
ValueCountFrequency (%)
T 32
 
12.6%
I 28
 
11.0%
C 25
 
9.8%
S 23
 
9.1%
W 15
 
5.9%
e 11
 
4.3%
r 10
 
3.9%
D 9
 
3.5%
a 8
 
3.1%
o 8
 
3.1%
Other values (27) 85
33.5%
Common
ValueCountFrequency (%)
260
72.6%
· 36
 
10.1%
/ 28
 
7.8%
, 10
 
2.8%
) 9
 
2.5%
( 9
 
2.5%
3 3
 
0.8%
- 2
 
0.6%
. 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1471
70.6%
ASCII 576
 
27.7%
None 36
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
260
45.1%
T 32
 
5.6%
I 28
 
4.9%
/ 28
 
4.9%
C 25
 
4.3%
S 23
 
4.0%
W 15
 
2.6%
e 11
 
1.9%
r 10
 
1.7%
, 10
 
1.7%
Other values (35) 134
23.3%
Hangul
ValueCountFrequency (%)
스 75
 
5.1%
기 47
 
3.2%
이 35
 
2.4%
보 32
 
2.2%
인 30
 
2.0%
트 29
 
2.0%
서 28
 
1.9%
비 27
 
1.8%
안 26
 
1.8%
어 23
 
1.6%
Other values (234) 1119
76.1%
None
ValueCountFrequency (%)
· 36
100.0%

과제정보 기술분류 코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct225
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean318067.53
Minimum300000
Maximum900999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-17T22:02:17.618702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300000
5-th percentile305441.6
Q1308202
median310301
Q3312603
95-th percentile314200.8
Maximum900999
Range600999
Interquartile range (IQR)4401

Descriptive statistics

Standard deviation67927.852
Coefficient of variation (CV)0.21356425
Kurtosis71.38071
Mean318067.53
Median Absolute Deviation (MAD)2200
Skewness8.5218247
Sum71565194
Variance4.614193 × 109
MonotonicityNot monotonic
2024-04-17T22:02:17.997666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
314301 1
 
0.4%
312401 1
 
0.4%
311102 1
 
0.4%
311103 1
 
0.4%
311104 1
 
0.4%
311201 1
 
0.4%
311202 1
 
0.4%
311203 1
 
0.4%
311204 1
 
0.4%
311205 1
 
0.4%
Other values (215) 215
95.6%
ValueCountFrequency (%)
300000 1
0.4%
305000 1
0.4%
305100 1
0.4%
305101 1
0.4%
305102 1
0.4%
305200 1
0.4%
305201 1
0.4%
305202 1
0.4%
305203 1
0.4%
305300 1
0.4%
ValueCountFrequency (%)
900999 1
0.4%
900900 1
0.4%
900000 1
0.4%
314303 1
0.4%
314302 1
0.4%
314301 1
0.4%
314300 1
0.4%
314205 1
0.4%
314204 1
0.4%
314203 1
0.4%

Interactions

2024-04-17T22:02:15.378630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:02:14.839783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:02:15.107019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:02:15.463525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:02:14.928673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:02:15.219706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:02:15.539216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:02:15.011912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:02:15.298444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T22:02:18.077571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기술분류 코드상위 기술분류 코드기술분류 레벨과제정보 기술분류 코드
기술분류 코드1.0000.9920.0321.000
상위 기술분류 코드0.9921.0000.0000.545
기술분류 레벨0.0320.0001.0000.082
과제정보 기술분류 코드1.0000.5450.0821.000
2024-04-17T22:02:18.157166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기술분류 코드상위 기술분류 코드과제정보 기술분류 코드기술분류 레벨
기술분류 코드1.0000.9071.0000.029
상위 기술분류 코드0.9071.0000.9070.000
과제정보 기술분류 코드1.0000.9071.0000.118
기술분류 레벨0.0290.0000.1181.000

Missing values

2024-04-17T22:02:15.642222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T22:02:15.744196image/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

기술분류 코드생성자생성일시상위 기술분류 코드기술분류 레벨기술분류 이름과제정보 기술분류 코드
0100301SYSTEM2016-03-24 오후 5:04:531003004센서·소자·소재314301
10SYSTEM2016-03-24 오후 5:04:53<NA>1정보통신300000
210000SYSTEM2016-03-24 오후 5:04:5302이동통신305000
320000SYSTEM2016-03-24 오후 5:04:5302네트워크306000
430000SYSTEM2016-03-24 오후 5:04:5302방송·스마트미디어307000
540000SYSTEM2016-03-24 오후 5:04:5302전파·위성308000
650000SYSTEM2016-03-24 오후 5:04:5302기반SW·컴퓨팅309000
760000SYSTEM2016-03-24 오후 5:04:5302SW310000
870000SYSTEM2016-03-24 오후 5:04:5302디지털콘텐츠311000
980000SYSTEM2016-03-24 오후 5:04:5302정보보호312000
기술분류 코드생성자생성일시상위 기술분류 코드기술분류 레벨기술분류 이름과제정보 기술분류 코드
215100103SYSTEM2016-03-24 오후 5:04:531001004기타314103
216100201SYSTEM2016-03-24 오후 5:04:5310020043D 프린터314201
217100202SYSTEM2016-03-24 오후 5:04:531002004무인비행체314202
218100203SYSTEM2016-03-24 오후 5:04:531002004ICT융합 단말 디바이스(소형로봇, 자율주행차 등)314203
219100204SYSTEM2016-03-24 오후 5:04:531002004ICT 융합 통신 디바이스314204
220100205SYSTEM2016-03-24 오후 5:04:531002004기타314205
221100302SYSTEM2016-03-24 오후 5:04:531003004배터리 및 전원부품314302
222100303SYSTEM2016-03-24 오후 5:04:531003004기타314303
223999900SYSTEM2016-03-24 오후 5:04:539900003기타900900
224999999SYSTEM2016-03-24 오후 5:04:539999004기타900999