Overview

Dataset statistics

Number of variables16
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory131.9 B

Variable types

Categorical10
Numeric2
Text4

Dataset

Description한국보건복지인재원 집합+사이버 혼합(교육방식) 교육의 운영정보 및 계획 정보 제공 (과정명, 교육기간, 교육대상, 교육방식, 교육시간, 계획인원, 권역구분 등의 항목 제공 ) 단, 계획이므로 변동될 수 있음
Author한국보건복지인재원
URLhttps://www.data.go.kr/data/15086200/fileData.do

Alerts

교육방식 has constant value ""Constant
부서 is highly overall correlated with 계획인원 and 6 other fieldsHigh correlation
세부교육분야 is highly overall correlated with 계획인원 and 7 other fieldsHigh correlation
분야 is highly overall correlated with 계획인원 and 7 other fieldsHigh correlation
본부 is highly overall correlated with 교육대상 and 6 other fieldsHigh correlation
계획인원 is highly overall correlated with 교육재원 and 5 other fieldsHigh correlation
교육재원 is highly overall correlated with 계획인원 and 5 other fieldsHigh correlation
교육대상 is highly overall correlated with 교육재원 and 6 other fieldsHigh correlation
교육일수 is highly overall correlated with 계획인원 and 7 other fieldsHigh correlation
교육시간 is highly overall correlated with 계획인원 and 7 other fieldsHigh correlation
권역구분 is highly overall correlated with 본부High correlation

Reproduction

Analysis started2023-12-11 23:46:25.639961
Analysis finished2023-12-11 23:46:27.416351
Duration1.78 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육방식
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
혼합
70 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
혼합 70
100.0%

Length

2023-12-12T08:46:27.473323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:46:27.559269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
혼합 70
100.0%

교육재원
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
민경
50 
출연
20 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민경 50
71.4%
출연 20
 
28.6%

Length

2023-12-12T08:46:27.652242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:46:27.740208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민경 50
71.4%
출연 20
 
28.6%

교육대상
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size692.0 B
공·민
27 
민간
18 
공무원
12 
공무원+민간
12 
공무원
 
1

Length

Max length6
Median length3
Mean length3.2714286
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row민간
2nd row민간
3rd row공무원
4th row공무원
5th row공무원

Common Values

ValueCountFrequency (%)
공·민 27
38.6%
민간 18
25.7%
공무원 12
17.1%
공무원+민간 12
17.1%
공무원 1
 
1.4%

Length

2023-12-12T08:46:27.839367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:46:27.944118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공·민 27
38.6%
민간 18
25.7%
공무원 13
18.6%
공무원+민간 12
17.1%

기수
Real number (ℝ)

Distinct9
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5428571
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-12T08:46:28.063704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile6
Maximum11
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.124295
Coefficient of variation (CV)0.83539692
Kurtosis4.2591676
Mean2.5428571
Median Absolute Deviation (MAD)1
Skewness1.9231469
Sum178
Variance4.5126294
MonotonicityNot monotonic
2023-12-12T08:46:28.157128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 31
44.3%
2 15
21.4%
3 7
 
10.0%
4 6
 
8.6%
5 4
 
5.7%
6 4
 
5.7%
7 1
 
1.4%
10 1
 
1.4%
11 1
 
1.4%
ValueCountFrequency (%)
1 31
44.3%
2 15
21.4%
3 7
 
10.0%
4 6
 
8.6%
5 4
 
5.7%
6 4
 
5.7%
7 1
 
1.4%
10 1
 
1.4%
11 1
 
1.4%
ValueCountFrequency (%)
11 1
 
1.4%
10 1
 
1.4%
7 1
 
1.4%
6 4
 
5.7%
5 4
 
5.7%
4 6
 
8.6%
3 7
 
10.0%
2 15
21.4%
1 31
44.3%

과정명
Text

Distinct35
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T08:46:28.396848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length25
Mean length17.342857
Min length7

Characters and Unicode

Total characters1214
Distinct characters125
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)27.1%

Sample

1st row가정위탁지원전문상담원과정
2nd row아동학대전문상담원과정
3rd row5급신규자과정
4th row6급핵심인재역량향상과정
5th row6급핵심인재역량향상과정
ValueCountFrequency (%)
6급핵심인재역량향상과정 7
 
9.7%
지역사회통합돌봄상담실무자기본교육-정책및대상자이해모듈 6
 
8.3%
역학조사관기본교육1 4
 
5.6%
주무관을위한행정역량강화과정 4
 
5.6%
지역사회통합돌봄상담실무자심화교육-서비스계획및모니터링모듈 4
 
5.6%
생물안전3등급시설신규관리자교육 4
 
5.6%
지역사회통합돌봄발전워크숍 3
 
4.2%
지역사회통합돌봄상담실무자기본교육-자원개발과네트워킹모듈 3
 
4.2%
의약품생산입문과정 2
 
2.8%
의약품마케팅입문과정 2
 
2.8%
Other values (26) 33
45.8%
2023-12-12T08:46:28.767517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 51
 
4.2%
역 47
 
3.9%
과 42
 
3.5%
사 42
 
3.5%
- 40
 
3.3%
육 34
 
2.8%
교 34
 
2.8%
자 33
 
2.7%
상 32
 
2.6%
합 29
 
2.4%
Other values (115) 830
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1152
94.9%
Dash Punctuation 40
 
3.3%
Decimal Number 18
 
1.5%
Other Punctuation 2
 
0.2%
Space Separator 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 51
 
4.4%
역 47
 
4.1%
과 42
 
3.6%
사 42
 
3.6%
육 34
 
3.0%
교 34
 
3.0%
자 33
 
2.9%
상 32
 
2.8%
합 29
 
2.5%
통 29
 
2.5%
Other values (107) 779
67.6%
Decimal Number
ValueCountFrequency (%)
6 7
38.9%
3 5
27.8%
1 4
22.2%
5 1
 
5.6%
2 1
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1152
94.9%
Common 62
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 51
 
4.4%
역 47
 
4.1%
과 42
 
3.6%
사 42
 
3.6%
육 34
 
3.0%
교 34
 
3.0%
자 33
 
2.9%
상 32
 
2.8%
합 29
 
2.5%
통 29
 
2.5%
Other values (107) 779
67.6%
Common
ValueCountFrequency (%)
- 40
64.5%
6 7
 
11.3%
3 5
 
8.1%
1 4
 
6.5%
, 2
 
3.2%
2
 
3.2%
5 1
 
1.6%
2 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1152
94.9%
ASCII 62
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 51
 
4.4%
역 47
 
4.1%
과 42
 
3.6%
사 42
 
3.6%
육 34
 
3.0%
교 34
 
3.0%
자 33
 
2.9%
상 32
 
2.8%
합 29
 
2.5%
통 29
 
2.5%
Other values (107) 779
67.6%
ASCII
ValueCountFrequency (%)
- 40
64.5%
6 7
 
11.3%
3 5
 
8.1%
1 4
 
6.5%
, 2
 
3.2%
2
 
3.2%
5 1
 
1.6%
2 1
 
1.6%

실과정명
Text

Distinct37
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T08:46:29.100797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length25
Mean length17.142857
Min length7

Characters and Unicode

Total characters1200
Distinct characters126
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)28.6%

Sample

1st row가정위탁지원전문상담원과정
2nd row아동학대전문상담원과정
3rd row5급신규자과정
4th row6급핵심인재역량향상과정
5th row6급핵심인재역량향상과정
ValueCountFrequency (%)
6급핵심인재역량향상과정 7
 
9.5%
지역사회통합돌봄상담실무자기본교육-정책및대상자이해 4
 
5.4%
지역사회통합돌봄상담실무자전문교육-서비스계획ⅱ및모니터링 4
 
5.4%
역학조사관기본교육1 4
 
5.4%
생물안전3등급시설신규관리자교육 4
 
5.4%
주무관을위한행정역량강화과정 4
 
5.4%
지역사회통합돌봄발전워크숍 3
 
4.1%
자원개발과네트워킹 2
 
2.7%
지역사회통합돌봄현장전문가강사양성과정 2
 
2.7%
의약품마케팅입문과정 2
 
2.7%
Other values (29) 38
51.4%
2023-12-12T08:46:29.542817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 51
 
4.2%
역 47
 
3.9%
사 42
 
3.5%
과 42
 
3.5%
- 40
 
3.3%
육 34
 
2.8%
교 34
 
2.8%
자 33
 
2.8%
상 32
 
2.7%
지 29
 
2.4%
Other values (116) 816
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1132
94.3%
Dash Punctuation 40
 
3.3%
Decimal Number 18
 
1.5%
Space Separator 4
 
0.3%
Letter Number 4
 
0.3%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 51
 
4.5%
역 47
 
4.2%
사 42
 
3.7%
과 42
 
3.7%
육 34
 
3.0%
교 34
 
3.0%
자 33
 
2.9%
상 32
 
2.8%
지 29
 
2.6%
합 29
 
2.6%
Other values (107) 759
67.0%
Decimal Number
ValueCountFrequency (%)
6 7
38.9%
3 5
27.8%
1 4
22.2%
5 1
 
5.6%
2 1
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1132
94.3%
Common 64
 
5.3%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 51
 
4.5%
역 47
 
4.2%
사 42
 
3.7%
과 42
 
3.7%
육 34
 
3.0%
교 34
 
3.0%
자 33
 
2.9%
상 32
 
2.8%
지 29
 
2.6%
합 29
 
2.6%
Other values (107) 759
67.0%
Common
ValueCountFrequency (%)
- 40
62.5%
6 7
 
10.9%
3 5
 
7.8%
4
 
6.2%
1 4
 
6.2%
, 2
 
3.1%
5 1
 
1.6%
2 1
 
1.6%
Latin
ValueCountFrequency (%)
Ⅱ 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1132
94.3%
ASCII 64
 
5.3%
Number Forms 4
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 51
 
4.5%
역 47
 
4.2%
사 42
 
3.7%
과 42
 
3.7%
육 34
 
3.0%
교 34
 
3.0%
자 33
 
2.9%
상 32
 
2.8%
지 29
 
2.6%
합 29
 
2.6%
Other values (107) 759
67.0%
ASCII
ValueCountFrequency (%)
- 40
62.5%
6 7
 
10.9%
3 5
 
7.8%
4
 
6.2%
1 4
 
6.2%
, 2
 
3.1%
5 1
 
1.6%
2 1
 
1.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
100.0%

본부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
복지인재양성본부
43 
보건인재양성본부
27 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
복지인재양성본부 43
61.4%
보건인재양성본부 27
38.6%

Length

2023-12-12T08:46:29.714761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:46:29.841686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복지인재양성본부 43
61.4%
보건인재양성본부 27
38.6%

부서
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size692.0 B
복지행정교육부
40 
보건산업교육부
15 
질병관리교육부
12 
사회서비스교육부
 
2
아동안전지원단
 
1

Length

Max length8
Median length7
Mean length7.0285714
Min length7

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row사회서비스교육부
2nd row사회서비스교육부
3rd row복지행정교육부
4th row복지행정교육부
5th row복지행정교육부

Common Values

ValueCountFrequency (%)
복지행정교육부 40
57.1%
보건산업교육부 15
 
21.4%
질병관리교육부 12
 
17.1%
사회서비스교육부 2
 
2.9%
아동안전지원단 1
 
1.4%

Length

2023-12-12T08:46:29.987140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:46:30.112594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복지행정교육부 40
57.1%
보건산업교육부 15
 
21.4%
질병관리교육부 12
 
17.1%
사회서비스교육부 2
 
2.9%
아동안전지원단 1
 
1.4%

분야
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size692.0 B
사회복지
30 
보건산업
15 
리더십역량
12 
보건생명
12 
특화교육
 
1

Length

Max length5
Median length4
Mean length4.1714286
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row사회복지
2nd row사회복지
3rd row리더십역량
4th row리더십역량
5th row리더십역량

Common Values

ValueCountFrequency (%)
사회복지 30
42.9%
보건산업 15
21.4%
리더십역량 12
 
17.1%
보건생명 12
 
17.1%
특화교육 1
 
1.4%

Length

2023-12-12T08:46:30.256284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:46:30.360548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사회복지 30
42.9%
보건산업 15
21.4%
리더십역량 12
 
17.1%
보건생명 12
 
17.1%
특화교육 1
 
1.4%

세부교육분야
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
복지행정
28 
중앙부처
12 
질병관리
12 
제약
8 
화장품
3 
Other values (4)
7 

Length

Max length6
Median length4
Mean length3.7857143
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row아동복지
2nd row아동복지
3rd row중앙부처
4th row중앙부처
5th row중앙부처

Common Values

ValueCountFrequency (%)
복지행정 28
40.0%
중앙부처 12
17.1%
질병관리 12
17.1%
제약 8
 
11.4%
화장품 3
 
4.3%
아동복지 2
 
2.9%
보건산업일반 2
 
2.9%
의료기기 2
 
2.9%
아동안전 1
 
1.4%

Length

2023-12-12T08:46:30.492478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:46:30.627853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복지행정 28
40.0%
중앙부처 12
17.1%
질병관리 12
17.1%
제약 8
 
11.4%
화장품 3
 
4.3%
아동복지 2
 
2.9%
보건산업일반 2
 
2.9%
의료기기 2
 
2.9%
아동안전 1
 
1.4%

교육기간(시작)
Text

Distinct49
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T08:46:30.869556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.5428571
Min length2

Characters and Unicode

Total characters668
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)45.7%

Sample

1st row2021-04-05
2nd row2021-04-13
3rd row2021-02-01
4th row2021-02-01
5th row2021-03-29
ValueCountFrequency (%)
미정 4
 
5.7%
2021-02-22 3
 
4.3%
2021-04-19 3
 
4.3%
2021-08-19 2
 
2.9%
2021-08-03 2
 
2.9%
2021-05-27 2
 
2.9%
2021-09-10 2
 
2.9%
2021-06-24 2
 
2.9%
2021-04-05 2
 
2.9%
2021-08-26 2
 
2.9%
Other values (39) 46
65.7%
2023-12-12T08:46:31.219296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 170
25.4%
0 151
22.6%
- 132
19.8%
1 107
16.0%
8 19
 
2.8%
5 18
 
2.7%
3 18
 
2.7%
4 12
 
1.8%
6 12
 
1.8%
9 11
 
1.6%
Other values (3) 18
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 528
79.0%
Dash Punctuation 132
 
19.8%
Other Letter 8
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 170
32.2%
0 151
28.6%
1 107
20.3%
8 19
 
3.6%
5 18
 
3.4%
3 18
 
3.4%
4 12
 
2.3%
6 12
 
2.3%
9 11
 
2.1%
7 10
 
1.9%
Other Letter
ValueCountFrequency (%)
미 4
50.0%
정 4
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 660
98.8%
Hangul 8
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 170
25.8%
0 151
22.9%
- 132
20.0%
1 107
16.2%
8 19
 
2.9%
5 18
 
2.7%
3 18
 
2.7%
4 12
 
1.8%
6 12
 
1.8%
9 11
 
1.7%
Hangul
ValueCountFrequency (%)
미 4
50.0%
정 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 660
98.8%
Hangul 8
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 170
25.8%
0 151
22.9%
- 132
20.0%
1 107
16.2%
8 19
 
2.9%
5 18
 
2.7%
3 18
 
2.7%
4 12
 
1.8%
6 12
 
1.8%
9 11
 
1.7%
Hangul
ValueCountFrequency (%)
미 4
50.0%
정 4
50.0%

교육기간(종료)
Text

Distinct48
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T08:46:31.434787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.5428571
Min length2

Characters and Unicode

Total characters668
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)47.1%

Sample

1st row2021-04-15
2nd row2021-04-30
3rd row2021-02-10
4th row2021-02-05
5th row2021-04-02
ValueCountFrequency (%)
2021-09-10 4
 
5.7%
미정 4
 
5.7%
2021-05-14 3
 
4.3%
2021-08-27 3
 
4.3%
2021-02-26 3
 
4.3%
2021-06-24 2
 
2.9%
2021-04-15 2
 
2.9%
2021-08-20 2
 
2.9%
2021-09-02 2
 
2.9%
2021-11-18 2
 
2.9%
Other values (38) 43
61.4%
2023-12-12T08:46:31.808365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 165
24.7%
0 156
23.4%
- 132
19.8%
1 102
15.3%
6 20
 
3.0%
8 19
 
2.8%
5 16
 
2.4%
4 14
 
2.1%
3 13
 
1.9%
9 12
 
1.8%
Other values (3) 19
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 528
79.0%
Dash Punctuation 132
 
19.8%
Other Letter 8
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 165
31.2%
0 156
29.5%
1 102
19.3%
6 20
 
3.8%
8 19
 
3.6%
5 16
 
3.0%
4 14
 
2.7%
3 13
 
2.5%
9 12
 
2.3%
7 11
 
2.1%
Other Letter
ValueCountFrequency (%)
미 4
50.0%
정 4
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 660
98.8%
Hangul 8
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 165
25.0%
0 156
23.6%
- 132
20.0%
1 102
15.5%
6 20
 
3.0%
8 19
 
2.9%
5 16
 
2.4%
4 14
 
2.1%
3 13
 
2.0%
9 12
 
1.8%
Hangul
ValueCountFrequency (%)
미 4
50.0%
정 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 660
98.8%
Hangul 8
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 165
25.0%
0 156
23.6%
- 132
20.0%
1 102
15.5%
6 20
 
3.0%
8 19
 
2.9%
5 16
 
2.4%
4 14
 
2.1%
3 13
 
2.0%
9 12
 
1.8%
Hangul
ValueCountFrequency (%)
미 4
50.0%
정 4
50.0%

교육일수
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size692.0 B
1
21 
5
18 
45
11 
2
8 
3
4 
Other values (6)
8 

Length

Max length2
Median length1
Mean length1.2285714
Min length1

Unique

Unique4 ?
Unique (%)5.7%

Sample

1st row9
2nd row14
3rd row8
4th row5
5th row5

Common Values

ValueCountFrequency (%)
1 21
30.0%
5 18
25.7%
45 11
15.7%
2 8
 
11.4%
3 4
 
5.7%
미정 2
 
2.9%
16 2
 
2.9%
9 1
 
1.4%
14 1
 
1.4%
8 1
 
1.4%

Length

2023-12-12T08:46:31.925385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 21
30.0%
5 18
25.7%
45 11
15.7%
2 8
 
11.4%
3 4
 
5.7%
미정 2
 
2.9%
16 2
 
2.9%
9 1
 
1.4%
14 1
 
1.4%
8 1
 
1.4%

교육시간
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
35
12 
8
7 
16
7 
10
6 
21
4 
Other values (15)
34 

Length

Max length3
Median length2
Mean length1.8
Min length1

Unique

Unique4 ?
Unique (%)5.7%

Sample

1st row76
2nd row109
3rd row57
4th row35
5th row35

Common Values

ValueCountFrequency (%)
35 12
17.1%
8 7
10.0%
16 7
10.0%
10 6
 
8.6%
21 4
 
5.7%
40 4
 
5.7%
66 4
 
5.7%
4 3
 
4.3%
7 3
 
4.3%
57 3
 
4.3%
Other values (10) 17
24.3%

Length

2023-12-12T08:46:32.032454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
35 12
17.1%
16 7
10.0%
8 7
10.0%
10 6
 
8.6%
21 4
 
5.7%
40 4
 
5.7%
66 4
 
5.7%
57 3
 
4.3%
76 3
 
4.3%
7 3
 
4.3%
Other values (10) 17
24.3%

계획인원
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.4
Minimum5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-12T08:46:32.131193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10
Q120
median20
Q330
95-th percentile30
Maximum100
Range95
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.404804
Coefficient of variation (CV)0.48738481
Kurtosis29.629167
Mean23.4
Median Absolute Deviation (MAD)0
Skewness4.4692504
Sum1638
Variance130.06957
MonotonicityNot monotonic
2023-12-12T08:46:32.211694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
20 39
55.7%
30 18
25.7%
10 3
 
4.3%
19 2
 
2.9%
25 2
 
2.9%
5 2
 
2.9%
100 1
 
1.4%
15 1
 
1.4%
29 1
 
1.4%
46 1
 
1.4%
ValueCountFrequency (%)
5 2
 
2.9%
10 3
 
4.3%
15 1
 
1.4%
19 2
 
2.9%
20 39
55.7%
25 2
 
2.9%
29 1
 
1.4%
30 18
25.7%
46 1
 
1.4%
100 1
 
1.4%
ValueCountFrequency (%)
100 1
 
1.4%
46 1
 
1.4%
30 18
25.7%
29 1
 
1.4%
25 2
 
2.9%
20 39
55.7%
19 2
 
2.9%
15 1
 
1.4%
10 3
 
4.3%
5 2
 
2.9%

권역구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
충북
45 
서울
19 
부산
 
2
미정
 
2
광주
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
충북 45
64.3%
서울 19
27.1%
부산 2
 
2.9%
미정 2
 
2.9%
광주 1
 
1.4%
대전 1
 
1.4%

Length

2023-12-12T08:46:32.302464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:46:32.389300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충북 45
64.3%
서울 19
27.1%
부산 2
 
2.9%
미정 2
 
2.9%
광주 1
 
1.4%
대전 1
 
1.4%

Interactions

2023-12-12T08:46:26.940621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:46:26.760530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:46:27.028179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:46:26.866743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:46:32.474045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육재원교육대상기수과정명실과정명본부부서분야세부교육분야교육기간(시작)교육기간(종료)교육일수교육시간계획인원권역구분
교육재원1.0000.6240.0661.0001.0000.0000.3210.6680.8440.8890.4810.8240.9940.4700.556
교육대상0.6241.0000.1300.9940.9880.5450.8830.9560.8550.9600.9140.7830.9310.6940.511
기수0.0660.1301.0000.0000.0000.1370.0000.2090.0000.0000.0000.0000.0000.0000.201
과정명1.0000.9940.0001.0001.0001.0001.0001.0001.0000.9370.9571.0000.9981.0000.000
실과정명1.0000.9880.0001.0001.0001.0001.0001.0001.0000.9510.9581.0000.9980.9970.000
본부0.0000.5450.1371.0001.0001.0001.0001.0001.0000.4920.4210.8370.9860.0000.728
부서0.3210.8830.0001.0001.0001.0001.0000.9911.0000.0000.8710.8960.9760.9290.563
분야0.6680.9560.2091.0001.0001.0000.9911.0001.0000.5280.8610.8680.9870.9220.578
세부교육분야0.8440.8550.0001.0001.0001.0001.0001.0001.0000.0000.8110.9290.9770.8880.558
교육기간(시작)0.8890.9600.0000.9370.9510.4920.0000.5280.0001.0000.9870.8150.8530.8000.626
교육기간(종료)0.4810.9140.0000.9570.9580.4210.8710.8610.8110.9871.0000.6830.9050.9580.000
교육일수0.8240.7830.0001.0001.0000.8370.8960.8680.9290.8150.6831.0000.9820.8810.527
교육시간0.9940.9310.0000.9980.9980.9860.9760.9870.9770.8530.9050.9821.0000.9710.476
계획인원0.4700.6940.0001.0000.9970.0000.9290.9220.8880.8000.9580.8810.9711.0000.145
권역구분0.5560.5110.2010.0000.0000.7280.5630.5780.5580.6260.0000.5270.4760.1451.000
2023-12-12T08:46:32.595273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서세부교육분야분야교육대상교육시간본부권역구분교육일수교육재원
부서1.0000.9690.8600.5360.7000.9780.4200.7250.382
세부교육분야0.9691.0000.9690.6880.8040.9470.3060.7650.827
분야0.8600.9691.0000.7030.7400.9780.4350.6760.781
교육대상0.5360.6880.7031.0000.5970.6450.3730.5510.734
교육시간0.7000.8040.7400.5971.0000.7730.2050.8230.800
본부0.9780.9470.9780.6450.7731.0000.5220.7780.000
권역구분0.4200.3060.4350.3730.2050.5221.0000.2880.390
교육일수0.7250.7650.6760.5510.8230.7780.2881.0000.764
교육재원0.3820.8270.7810.7340.8000.0000.3900.7641.000
2023-12-12T08:46:32.696249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기수계획인원교육재원교육대상본부부서분야세부교육분야교육일수교육시간권역구분
기수1.0000.1180.1210.1210.1680.0000.1620.0000.0000.0000.149
계획인원0.1181.0000.5580.3240.0000.6280.6130.7450.6980.6850.092
교육재원0.1210.5581.0000.7340.0000.3820.7810.8270.7640.8000.390
교육대상0.1210.3240.7341.0000.6450.5360.7030.6880.5510.5970.373
본부0.1680.0000.0000.6451.0000.9780.9780.9470.7780.7730.522
부서0.0000.6280.3820.5360.9781.0000.8600.9690.7250.7000.420
분야0.1620.6130.7810.7030.9780.8601.0000.9690.6760.7400.435
세부교육분야0.0000.7450.8270.6880.9470.9690.9691.0000.7650.8040.306
교육일수0.0000.6980.7640.5510.7780.7250.6760.7651.0000.8230.288
교육시간0.0000.6850.8000.5970.7730.7000.7400.8040.8231.0000.205
권역구분0.1490.0920.3900.3730.5220.4200.4350.3060.2880.2051.000

Missing values

2023-12-12T08:46:27.148200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:46:27.350201image/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

교육방식교육재원교육대상기수과정명실과정명본부부서분야세부교육분야교육기간(시작)교육기간(종료)교육일수교육시간계획인원권역구분
0혼합출연민간1가정위탁지원전문상담원과정가정위탁지원전문상담원과정복지인재양성본부사회서비스교육부사회복지아동복지2021-04-052021-04-1597630충북
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