Overview

Dataset statistics

Number of variables3
Number of observations345
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory25.4 B

Variable types

Numeric1
Categorical1
Text1

Dataset

Description한전KDN의 2023년 7월 3일 기준 중소기업지원센터에 등록된 교육과정 정보입니다. 교육기관과 교육과정명에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15116427/fileData.do

Alerts

순번 is highly overall correlated with 교육기관High correlation
교육기관 is highly overall correlated with 순번High correlation
교육기관 is highly imbalanced (79.6%)Imbalance
순번 has unique valuesUnique
교육명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:24:38.646573
Analysis finished2023-12-12 17:24:39.066282
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct345
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173
Minimum1
Maximum345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-13T02:24:39.130563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.2
Q187
median173
Q3259
95-th percentile327.8
Maximum345
Range344
Interquartile range (IQR)172

Descriptive statistics

Standard deviation99.737155
Coefficient of variation (CV)0.57651534
Kurtosis-1.2
Mean173
Median Absolute Deviation (MAD)86
Skewness0
Sum59685
Variance9947.5
MonotonicityStrictly increasing
2023-12-13T02:24:39.259347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
228 1
 
0.3%
236 1
 
0.3%
235 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
232 1
 
0.3%
231 1
 
0.3%
230 1
 
0.3%
229 1
 
0.3%
Other values (335) 335
97.1%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
345 1
0.3%
344 1
0.3%
343 1
0.3%
342 1
0.3%
341 1
0.3%
340 1
0.3%
339 1
0.3%
338 1
0.3%
337 1
0.3%
336 1
0.3%

교육기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
러닝허브
334 
(주)멀티캠퍼스
 
11

Length

Max length8
Median length4
Mean length4.1275362
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row러닝허브
2nd row(주)멀티캠퍼스
3rd row(주)멀티캠퍼스
4th row러닝허브
5th row(주)멀티캠퍼스

Common Values

ValueCountFrequency (%)
러닝허브 334
96.8%
(주)멀티캠퍼스 11
 
3.2%

Length

2023-12-13T02:24:39.399890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:24:39.497833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
러닝허브 334
96.8%
주)멀티캠퍼스 11
 
3.2%

교육명
Text

UNIQUE 

Distinct345
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-13T02:24:39.783472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length86
Median length54
Mean length33.942029
Min length8

Characters and Unicode

Total characters11710
Distinct characters466
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)100.0%

Sample

1st rowHDDreamweaver CC 2018 제대로 배우기 Part1
2nd rowR고 보면 쉬운 빅데이터 분석 실무 기초
3rd row4차산업과 IoT융합
4th rowHDMaxon_Cinema4D_Xpresso의_입문_PART2
5th rowVisual Basic 2015 프로그래밍 제대로 배우기Part2
ValueCountFrequency (%)
제대로 75
 
3.1%
배우기 70
 
2.9%
기초에서 56
 
2.3%
실무까지 54
 
2.3%
데이터 35
 
1.5%
hdpython(파이썬 31
 
1.3%
완전정복 30
 
1.3%
하기 30
 
1.3%
중급 30
 
1.3%
part1 28
 
1.2%
Other values (797) 1959
81.7%
2023-12-13T02:24:40.245491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2155
 
18.4%
기 313
 
2.7%
t 234
 
2.0%
P 219
 
1.9%
D 217
 
1.9%
이 202
 
1.7%
로 191
 
1.6%
a 188
 
1.6%
( 179
 
1.5%
) 179
 
1.5%
Other values (456) 7633
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6254
53.4%
Space Separator 2155
 
18.4%
Lowercase Letter 1340
 
11.4%
Uppercase Letter 1187
 
10.1%
Decimal Number 386
 
3.3%
Open Punctuation 179
 
1.5%
Close Punctuation 179
 
1.5%
Connector Punctuation 24
 
0.2%
Other Symbol 4
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 313
 
5.0%
이 202
 
3.2%
로 191
 
3.1%
지 142
 
2.3%
초 138
 
2.2%
터 122
 
2.0%
실 119
 
1.9%
스 107
 
1.7%
대 98
 
1.6%
배 96
 
1.5%
Other values (390) 4726
75.6%
Uppercase Letter
ValueCountFrequency (%)
P 219
18.4%
D 217
18.3%
H 174
14.7%
A 105
8.8%
C 75
 
6.3%
I 56
 
4.7%
R 52
 
4.4%
V 50
 
4.2%
S 50
 
4.2%
J 42
 
3.5%
Other values (15) 147
12.4%
Lowercase Letter
ValueCountFrequency (%)
t 234
17.5%
a 188
14.0%
r 177
13.2%
o 127
9.5%
n 108
8.1%
e 71
 
5.3%
i 65
 
4.9%
h 63
 
4.7%
s 62
 
4.6%
y 48
 
3.6%
Other values (14) 197
14.7%
Decimal Number
ValueCountFrequency (%)
2 110
28.5%
1 105
27.2%
4 43
 
11.1%
0 40
 
10.4%
3 37
 
9.6%
5 13
 
3.4%
6 11
 
2.8%
7 11
 
2.8%
9 9
 
2.3%
8 7
 
1.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Space Separator
ValueCountFrequency (%)
2155
100.0%
Open Punctuation
ValueCountFrequency (%)
( 179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 179
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 24
100.0%
Other Symbol
ValueCountFrequency (%)
ⓔ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6254
53.4%
Common 2927
25.0%
Latin 2529
21.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 313
 
5.0%
이 202
 
3.2%
로 191
 
3.1%
지 142
 
2.3%
초 138
 
2.2%
터 122
 
2.0%
실 119
 
1.9%
스 107
 
1.7%
대 98
 
1.6%
배 96
 
1.5%
Other values (390) 4726
75.6%
Latin
ValueCountFrequency (%)
t 234
 
9.3%
P 219
 
8.7%
D 217
 
8.6%
a 188
 
7.4%
r 177
 
7.0%
H 174
 
6.9%
o 127
 
5.0%
n 108
 
4.3%
A 105
 
4.2%
C 75
 
3.0%
Other values (41) 905
35.8%
Common
ValueCountFrequency (%)
2155
73.6%
( 179
 
6.1%
) 179
 
6.1%
2 110
 
3.8%
1 105
 
3.6%
4 43
 
1.5%
0 40
 
1.4%
3 37
 
1.3%
_ 24
 
0.8%
5 13
 
0.4%
Other values (5) 42
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6254
53.4%
ASCII 5450
46.5%
Enclosed Alphanum 4
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2155
39.5%
t 234
 
4.3%
P 219
 
4.0%
D 217
 
4.0%
a 188
 
3.4%
( 179
 
3.3%
) 179
 
3.3%
r 177
 
3.2%
H 174
 
3.2%
o 127
 
2.3%
Other values (53) 1601
29.4%
Hangul
ValueCountFrequency (%)
기 313
 
5.0%
이 202
 
3.2%
로 191
 
3.1%
지 142
 
2.3%
초 138
 
2.2%
터 122
 
2.0%
실 119
 
1.9%
스 107
 
1.7%
대 98
 
1.6%
배 96
 
1.5%
Other values (390) 4726
75.6%
Enclosed Alphanum
ValueCountFrequency (%)
ⓔ 4
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%

Interactions

2023-12-13T02:24:38.869671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:24:40.337923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번교육기관
순번1.0000.671
교육기관0.6711.000
2023-12-13T02:24:40.667254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번교육기관
순번1.0000.516
교육기관0.5161.000

Missing values

2023-12-13T02:24:38.979424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:24:39.040829image/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

순번교육기관교육명
01러닝허브HDDreamweaver CC 2018 제대로 배우기 Part1
12(주)멀티캠퍼스R고 보면 쉬운 빅데이터 분석 실무 기초
23(주)멀티캠퍼스4차산업과 IoT융합
34러닝허브HDMaxon_Cinema4D_Xpresso의_입문_PART2
45(주)멀티캠퍼스Visual Basic 2015 프로그래밍 제대로 배우기Part2
56러닝허브HD쉽게 따라하는 Rhino 50 for Architecture 응용
67(주)멀티캠퍼스Visual Basic 2015 프로그래밍 제대로 배우기Part1
78러닝허브HD쉽게 따라하는Enscape 241 for Rhino 6
89(주)멀티캠퍼스JSP 프로그래밍 활용 Part1
910러닝허브HD왕초보를 위한Adobe Photoshop CC 2019입문자 가이드Part1
순번교육기관교육명
335336러닝허브손수호 변호사의 현장 속으로_하도급법
336337러닝허브손수호 변호사의 현장 속으로_디지털 중독예방
337338러닝허브손수호 변호사의 현장 속으로_우울증 및 자살 방지
338339러닝허브손수호 변호사의 현장 속으로_재난대비
339340러닝허브손수호 변호사의 현장 속으로_저작권법
340341러닝허브10년해도 안되는 영어회화 첫걸음(1)
341342러닝허브10년해도 안되는 영어회화 첫걸음(2)
342343러닝허브입으로 하는 진짜 영어 스피킹 챌린지 I
343344러닝허브입으로 하는 진짜 영어 스피킹 챌린지 II
344345러닝허브입으로 하는 진짜 영어 스피킹 챌린지 III