Overview

Dataset statistics

Number of variables6
Number of observations67
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory51.0 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description국가인재원 베스트 강사 명단("12~"21)_67명. (연번, 년도, 소속, 성명, 과정명, 강의제목) 더 자세한 내용은 "국가인재원 홈페이지" > "새소식" > "베스트강사" 를 참고하시기 바랍니다.
Author인사혁신처
URLhttps://www.data.go.kr/data/15083414/fileData.do

Alerts

성명 has constant value ""Constant
연번 is highly overall correlated with 년도High correlation
년도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:30:49.956684
Analysis finished2023-12-12 14:30:50.735120
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct67
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34
Minimum1
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-12T23:30:50.838396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.3
Q117.5
median34
Q350.5
95-th percentile63.7
Maximum67
Range66
Interquartile range (IQR)33

Descriptive statistics

Standard deviation19.485037
Coefficient of variation (CV)0.57308932
Kurtosis-1.2
Mean34
Median Absolute Deviation (MAD)17
Skewness0
Sum2278
Variance379.66667
MonotonicityStrictly increasing
2023-12-12T23:30:50.968593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
44 1
 
1.5%
50 1
 
1.5%
49 1
 
1.5%
48 1
 
1.5%
47 1
 
1.5%
46 1
 
1.5%
45 1
 
1.5%
43 1
 
1.5%
2 1
 
1.5%
Other values (57) 57
85.1%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
67 1
1.5%
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%
58 1
1.5%

년도
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Memory size668.0 B
2018 2분기
9 
2021 2분기
 
4
2013
 
4
2014
 
4
2015
 
4
Other values (15)
42 

Length

Max length8
Median length8
Mean length6.6865672
Min length4

Unique

Unique1 ?
Unique (%)1.5%

Sample

1st row2021 4분기
2nd row2021 3분기
3rd row2021 3분기
4th row2021 3분기
5th row2021 2분기

Common Values

ValueCountFrequency (%)
2018 2분기 9
 
13.4%
2021 2분기 4
 
6.0%
2013 4
 
6.0%
2014 4
 
6.0%
2015 4
 
6.0%
2019 3분기 4
 
6.0%
2019 2분기 4
 
6.0%
2017 4
 
6.0%
2018 4분기 4
 
6.0%
2021 3분기 3
 
4.5%
Other values (10) 23
34.3%

Length

2023-12-12T23:30:51.121138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018 18
16.1%
2분기 17
15.2%
2019 12
10.7%
2021 11
9.8%
3분기 10
8.9%
4분기 7
 
6.2%
1분기 7
 
6.2%
2013 4
 
3.6%
2014 4
 
3.6%
2015 4
 
3.6%
Other values (6) 18
16.1%

소속
Text

Distinct49
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-12T23:30:51.359807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length5
Mean length5.880597
Min length3

Characters and Unicode

Total characters394
Distinct characters132
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

Unique40 ?
Unique (%)59.7%

Sample

1st row송프로
2nd row서울대학교
3rd row강원대학교
4th row고용노동부
5th row환경부
ValueCountFrequency (%)
서울대학교 7
 
9.1%
경희대학교 4
 
5.2%
외교부 3
 
3.9%
국립외교원 3
 
3.9%
카이스트 3
 
3.9%
한양대학교 2
 
2.6%
단국대학교 2
 
2.6%
고용노동부 2
 
2.6%
연세대학교 2
 
2.6%
건국대학교 2
 
2.6%
Other values (47) 47
61.0%
2023-12-12T23:30:51.744444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 36
 
9.1%
대 33
 
8.4%
학 30
 
7.6%
국 17
 
4.3%
원 14
 
3.6%
10
 
2.5%
서 8
 
2.0%
부 8
 
2.0%
울 7
 
1.8%
한 7
 
1.8%
Other values (122) 224
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 368
93.4%
Lowercase Letter 11
 
2.8%
Space Separator 10
 
2.5%
Uppercase Letter 3
 
0.8%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 36
 
9.8%
대 33
 
9.0%
학 30
 
8.2%
국 17
 
4.6%
원 14
 
3.8%
서 8
 
2.2%
부 8
 
2.2%
울 7
 
1.9%
한 7
 
1.9%
트 7
 
1.9%
Other values (107) 201
54.6%
Lowercase Letter
ValueCountFrequency (%)
n 2
18.2%
o 2
18.2%
i 1
9.1%
m 1
9.1%
g 1
9.1%
l 1
9.1%
e 1
9.1%
s 1
9.1%
p 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
B 1
33.3%
M 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 368
93.4%
Latin 14
 
3.6%
Common 12
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 36
 
9.8%
대 33
 
9.0%
학 30
 
8.2%
국 17
 
4.6%
원 14
 
3.8%
서 8
 
2.2%
부 8
 
2.2%
울 7
 
1.9%
한 7
 
1.9%
트 7
 
1.9%
Other values (107) 201
54.6%
Latin
ValueCountFrequency (%)
n 2
14.3%
o 2
14.3%
i 1
7.1%
m 1
7.1%
g 1
7.1%
l 1
7.1%
e 1
7.1%
s 1
7.1%
p 1
7.1%
C 1
7.1%
Other values (2) 2
14.3%
Common
ValueCountFrequency (%)
10
83.3%
( 1
 
8.3%
) 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 368
93.4%
ASCII 26
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 36
 
9.8%
대 33
 
9.0%
학 30
 
8.2%
국 17
 
4.6%
원 14
 
3.8%
서 8
 
2.2%
부 8
 
2.2%
울 7
 
1.9%
한 7
 
1.9%
트 7
 
1.9%
Other values (107) 201
54.6%
ASCII
ValueCountFrequency (%)
10
38.5%
n 2
 
7.7%
o 2
 
7.7%
i 1
 
3.8%
m 1
 
3.8%
g 1
 
3.8%
l 1
 
3.8%
e 1
 
3.8%
s 1
 
3.8%
( 1
 
3.8%
Other values (5) 5
19.2%

성명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
***
67 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row***
2nd row***
3rd row***
4th row***
5th row***

Common Values

ValueCountFrequency (%)
*** 67
100.0%

Length

2023-12-12T23:30:51.870591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:30:52.217996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
67
100.0%

과정명
Text

Distinct43
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-12T23:30:52.404138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length12.029851
Min length5

Characters and Unicode

Total characters806
Distinct characters140
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)53.7%

Sample

1st row고위정책과정
2nd row고위정책과정
3rd row정부혁신실천과정
4th row신임관리자과정(공채,경채)
5th row신임관리자과정(공채)
ValueCountFrequency (%)
고위정책과정 13
 
11.1%
신임관리자과정 10
 
8.5%
5급승진자 6
 
5.1%
5급승진자과정 5
 
4.3%
고위공무원단 4
 
3.4%
후보자과정 4
 
3.4%
신임관리자과정(공채 4
 
3.4%
7급신규자과정 3
 
2.6%
신규자과정 3
 
2.6%
7급 3
 
2.6%
Other values (50) 62
53.0%
2023-12-12T23:30:52.769946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 95
 
11.8%
과 86
 
10.7%
50
 
6.2%
자 47
 
5.8%
신 30
 
3.7%
급 24
 
3.0%
리 21
 
2.6%
임 21
 
2.6%
관 20
 
2.5%
, 20
 
2.5%
Other values (130) 392
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 672
83.4%
Space Separator 50
 
6.2%
Decimal Number 29
 
3.6%
Other Punctuation 21
 
2.6%
Lowercase Letter 13
 
1.6%
Open Punctuation 7
 
0.9%
Close Punctuation 7
 
0.9%
Uppercase Letter 7
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 95
 
14.1%
과 86
 
12.8%
자 47
 
7.0%
신 30
 
4.5%
급 24
 
3.6%
리 21
 
3.1%
임 21
 
3.1%
관 20
 
3.0%
위 17
 
2.5%
고 17
 
2.5%
Other values (105) 294
43.8%
Lowercase Letter
ValueCountFrequency (%)
l 3
23.1%
e 3
23.1%
o 1
 
7.7%
h 1
 
7.7%
p 1
 
7.7%
n 1
 
7.7%
s 1
 
7.7%
k 1
 
7.7%
i 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
5 18
62.1%
7 6
 
20.7%
3 2
 
6.9%
8 1
 
3.4%
9 1
 
3.4%
4 1
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
E 2
28.6%
D 2
28.6%
T 1
14.3%
S 1
14.3%
P 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 20
95.2%
· 1
 
4.8%
Space Separator
ValueCountFrequency (%)
50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 672
83.4%
Common 114
 
14.1%
Latin 20
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 95
 
14.1%
과 86
 
12.8%
자 47
 
7.0%
신 30
 
4.5%
급 24
 
3.6%
리 21
 
3.1%
임 21
 
3.1%
관 20
 
3.0%
위 17
 
2.5%
고 17
 
2.5%
Other values (105) 294
43.8%
Latin
ValueCountFrequency (%)
l 3
15.0%
e 3
15.0%
E 2
10.0%
D 2
10.0%
o 1
 
5.0%
h 1
 
5.0%
p 1
 
5.0%
T 1
 
5.0%
S 1
 
5.0%
n 1
 
5.0%
Other values (4) 4
20.0%
Common
ValueCountFrequency (%)
50
43.9%
, 20
 
17.5%
5 18
 
15.8%
( 7
 
6.1%
) 7
 
6.1%
7 6
 
5.3%
3 2
 
1.8%
8 1
 
0.9%
9 1
 
0.9%
· 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 672
83.4%
ASCII 133
 
16.5%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 95
 
14.1%
과 86
 
12.8%
자 47
 
7.0%
신 30
 
4.5%
급 24
 
3.6%
리 21
 
3.1%
임 21
 
3.1%
관 20
 
3.0%
위 17
 
2.5%
고 17
 
2.5%
Other values (105) 294
43.8%
ASCII
ValueCountFrequency (%)
50
37.6%
, 20
 
15.0%
5 18
 
13.5%
( 7
 
5.3%
) 7
 
5.3%
7 6
 
4.5%
l 3
 
2.3%
e 3
 
2.3%
E 2
 
1.5%
D 2
 
1.5%
Other values (14) 15
 
11.3%
None
ValueCountFrequency (%)
· 1
100.0%

강의제목
Text

Distinct65
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-12T23:30:53.140179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length25
Mean length16.238806
Min length7

Characters and Unicode

Total characters1088
Distinct characters260
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)94.0%

Sample

1st row개인정보 노출예방 비법
2nd row36.5도의 경제학
3rd row정부혁신과 그린뉴딜
4th row정책사례(청년내일채움공제)
5th row2050 탄소중립의 이해
ValueCountFrequency (%)
및 5
 
2.0%
이해 5
 
2.0%
한국의 4
 
1.6%
글로벌시대 3
 
1.2%
전략 3
 
1.2%
등 3
 
1.2%
기술 3
 
1.2%
공직자의 3
 
1.2%
다른 2
 
0.8%
삶 2
 
0.8%
Other values (204) 220
87.0%
2023-12-12T23:30:53.704308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
186
 
17.1%
의 32
 
2.9%
이 21
 
1.9%
정 21
 
1.9%
공 19
 
1.7%
한 18
 
1.7%
과 17
 
1.6%
전 15
 
1.4%
국 15
 
1.4%
사 14
 
1.3%
Other values (250) 730
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 844
77.6%
Space Separator 186
 
17.1%
Other Punctuation 21
 
1.9%
Decimal Number 16
 
1.5%
Uppercase Letter 11
 
1.0%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%
Letter Number 2
 
0.2%
Dash Punctuation 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 32
 
3.8%
이 21
 
2.5%
정 21
 
2.5%
공 19
 
2.3%
한 18
 
2.1%
과 17
 
2.0%
전 15
 
1.8%
국 15
 
1.8%
사 14
 
1.7%
가 13
 
1.5%
Other values (225) 659
78.1%
Decimal Number
ValueCountFrequency (%)
4 4
25.0%
2 3
18.8%
1 2
12.5%
5 2
12.5%
0 2
12.5%
3 2
12.5%
6 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
D 3
27.3%
I 2
18.2%
R 2
18.2%
H 2
18.2%
S 1
 
9.1%
T 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 14
66.7%
? 3
 
14.3%
' 2
 
9.5%
: 1
 
4.8%
. 1
 
4.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Space Separator
ValueCountFrequency (%)
186
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 844
77.6%
Common 230
 
21.1%
Latin 14
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 32
 
3.8%
이 21
 
2.5%
정 21
 
2.5%
공 19
 
2.3%
한 18
 
2.1%
과 17
 
2.0%
전 15
 
1.8%
국 15
 
1.8%
사 14
 
1.7%
가 13
 
1.5%
Other values (225) 659
78.1%
Common
ValueCountFrequency (%)
186
80.9%
, 14
 
6.1%
4 4
 
1.7%
? 3
 
1.3%
( 3
 
1.3%
) 3
 
1.3%
2 3
 
1.3%
' 2
 
0.9%
1 2
 
0.9%
5 2
 
0.9%
Other values (6) 8
 
3.5%
Latin
ValueCountFrequency (%)
D 3
21.4%
I 2
14.3%
R 2
14.3%
H 2
14.3%
Ⅱ 1
 
7.1%
Ⅰ 1
 
7.1%
S 1
 
7.1%
T 1
 
7.1%
o 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 844
77.6%
ASCII 242
 
22.2%
Number Forms 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
186
76.9%
, 14
 
5.8%
4 4
 
1.7%
D 3
 
1.2%
? 3
 
1.2%
( 3
 
1.2%
) 3
 
1.2%
2 3
 
1.2%
I 2
 
0.8%
' 2
 
0.8%
Other values (13) 19
 
7.9%
Hangul
ValueCountFrequency (%)
의 32
 
3.8%
이 21
 
2.5%
정 21
 
2.5%
공 19
 
2.3%
한 18
 
2.1%
과 17
 
2.0%
전 15
 
1.8%
국 15
 
1.8%
사 14
 
1.7%
가 13
 
1.5%
Other values (225) 659
78.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%

Interactions

2023-12-12T23:30:50.463701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:30:53.828331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번년도소속과정명강의제목
연번1.0000.9930.0000.6810.975
년도0.9931.0000.6800.8820.994
소속0.0000.6801.0000.8320.965
과정명0.6810.8820.8321.0000.994
강의제목0.9750.9940.9650.9941.000
2023-12-12T23:30:53.931359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번년도
연번1.0000.773
년도0.7731.000

Missing values

2023-12-12T23:30:50.578500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:30:50.697063image/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

연번년도소속성명과정명강의제목
012021 4분기송프로***고위정책과정개인정보 노출예방 비법
122021 3분기서울대학교***고위정책과정36.5도의 경제학
232021 3분기강원대학교***정부혁신실천과정정부혁신과 그린뉴딜
342021 3분기고용노동부***신임관리자과정(공채,경채)정책사례(청년내일채움공제)
452021 2분기환경부***신임관리자과정(공채)2050 탄소중립의 이해
562021 2분기한국지능정보사회진흥원***7급신규자과정공공데이터의 이해와 실습
672021 2분기보건복지부***9급지역인재채용자과정정책소통 우수사례
782021 2분기미국 센트럴미시간대***영어권장기국외훈련자과정성공적인 해외적응과 에티켓
892021 1분기천체사진가***고위정책과정, 신임국장과정천체사진가의 우주와 삶 이야기
9102021 1분기한국과학기술정보원***신임관리자과정(경채), 5급승진관리자과정4차 산업혁명과 포스트코로나 시대
연번년도소속성명과정명강의제목
57582014한양대학교***고위정책과정이슬람 문화의 이해
58592014국립생태원***인문학과학 통섭과정21세기 융합형 인재
59602014세브란스병원***고위정책과정선진국으로 가는 길
60612013서울대학교***5급승진자과정, 고위정책과정공직의 가치있는 삶
61622013단국대학교***미래예측과 신성장산업과정미래의 성정산업, 문화컨텐츠 산업의 전망과 대응
62632013포항공대***신임관리자과정마키아벨리와 21세기 제국경영
63642013동국대학교***5급승진자과정, 신임관리자과정행복한 가정을 위한 소통의 기술 인재혁명 : 글로벌시대 인재육성 공공행정의 창의적 리더십
64652012서강대학교***7급신규자과정, 과장후보자 핵심역량과정북한의 대남 전략 이해, 남북관계 변화와 전망
65662012이화여대***글로벌행정전문가과정한국의 지자체 변화와 도전, 한국의 역사와 사회문화
66672012인천국제공항***신임관리자과정뭔가 다른 인천공항, 무엇이 다른가?