Overview

Dataset statistics

Number of variables6
Number of observations633
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory31.7 KiB
Average record size in memory51.2 B

Variable types

Categorical1
Text2
Numeric3

Dataset

Description법무, 검찰 인재 양성을 위한 수요자 중심의 맞춤형 전문 교육, 타부처 직원들의 직무역량 향상을 위한 국가송무와 특별사법경찰 교육 등 법무연수원에서 실시되고 있는 사이버교육 및 집합교육 관련 연간교육 일정 제공
URLhttps://www.data.go.kr/data/15103253/fileData.do

Alerts

Dataset has 1 (0.2%) duplicate rowsDuplicates
정원수 is highly overall correlated with 교육횟수 and 2 other fieldsHigh correlation
교육횟수 is highly overall correlated with 정원수 and 1 other fieldsHigh correlation
교육일수 is highly overall correlated with 정원수 and 1 other fieldsHigh correlation
직렬명 is highly overall correlated with 정원수High correlation

Reproduction

Analysis started2023-12-12 05:08:52.786397
Analysis finished2023-12-12 05:08:54.691885
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

직렬명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
검찰
163 
교정
155 
공통
149 
보호
76 
출입국
40 
Other values (4)
50 

Length

Max length3
Median length2
Mean length2.107425
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검찰 163
25.8%
교정 155
24.5%
공통 149
23.5%
보호 76
12.0%
출입국 40
 
6.3%
검사 22
 
3.5%
타부처 22
 
3.5%
일반인 3
 
0.5%
외국인 3
 
0.5%

Length

2023-12-12T14:08:54.779218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:08:54.948523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검찰 163
25.8%
교정 155
24.5%
공통 149
23.5%
보호 76
12.0%
출입국 40
 
6.3%
검사 22
 
3.5%
타부처 22
 
3.5%
일반인 3
 
0.5%
외국인 3
 
0.5%

과정명
Text

Distinct620
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2023-12-12T14:08:55.332636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length13.611374
Min length2

Characters and Unicode

Total characters8616
Distinct characters432
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique608 ?
Unique (%)96.1%

Sample

1st row신임검사(사법 시험)
2nd row신임검사(법전원)
3rd row저년차 검사 역량강화 필수과정
4th row저년차 검사 역량강화 선택과정(경제범죄 심화 ·서민다중피해범죄)
5th row저년차 검사 역량강화 선택과정(조세·관세 특허·지재)
ValueCountFrequency (%)
실무 66
 
3.5%
이해 61
 
3.2%
및 39
 
2.0%
수사 19
 
1.0%
보호관찰 17
 
0.9%
위한 14
 
0.7%
국가송무 14
 
0.7%
관련 13
 
0.7%
향상 12
 
0.6%
쉬운 12
 
0.6%
Other values (1053) 1636
86.0%
2023-12-12T14:08:55.956050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1320
 
15.3%
사 234
 
2.7%
무 219
 
2.5%
기 167
 
1.9%
( 162
 
1.9%
) 162
 
1.9%
이 153
 
1.8%
실 148
 
1.7%
2 145
 
1.7%
의 135
 
1.6%
Other values (422) 5771
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6320
73.4%
Space Separator 1320
 
15.3%
Decimal Number 446
 
5.2%
Open Punctuation 179
 
2.1%
Close Punctuation 179
 
2.1%
Lowercase Letter 63
 
0.7%
Uppercase Letter 45
 
0.5%
Math Symbol 30
 
0.3%
Other Punctuation 25
 
0.3%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 234
 
3.7%
무 219
 
3.5%
기 167
 
2.6%
이 153
 
2.4%
실 148
 
2.3%
의 135
 
2.1%
정 130
 
2.1%
보 122
 
1.9%
법 118
 
1.9%
제 118
 
1.9%
Other values (366) 4776
75.6%
Lowercase Letter
ValueCountFrequency (%)
i 9
14.3%
n 8
12.7%
s 7
11.1%
l 6
9.5%
o 5
7.9%
w 4
 
6.3%
g 4
 
6.3%
t 4
 
6.3%
e 3
 
4.8%
k 2
 
3.2%
Other values (8) 11
17.5%
Uppercase Letter
ValueCountFrequency (%)
N 6
13.3%
S 5
11.1%
C 5
11.1%
E 5
11.1%
K 4
8.9%
O 3
6.7%
A 3
6.7%
T 3
6.7%
I 2
 
4.4%
P 2
 
4.4%
Other values (5) 7
15.6%
Decimal Number
ValueCountFrequency (%)
2 145
32.5%
1 91
20.4%
0 88
19.7%
6 23
 
5.2%
5 22
 
4.9%
4 21
 
4.7%
3 18
 
4.0%
9 17
 
3.8%
7 14
 
3.1%
8 7
 
1.6%
Other Punctuation
ValueCountFrequency (%)
· 21
84.0%
! 3
 
12.0%
& 1
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 162
90.5%
[ 17
 
9.5%
Close Punctuation
ValueCountFrequency (%)
) 162
90.5%
] 17
 
9.5%
Math Symbol
ValueCountFrequency (%)
~ 29
96.7%
+ 1
 
3.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
50.0%
Ⅱ 2
50.0%
Space Separator
ValueCountFrequency (%)
1320
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6317
73.3%
Common 2184
 
25.3%
Latin 112
 
1.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 234
 
3.7%
무 219
 
3.5%
기 167
 
2.6%
이 153
 
2.4%
실 148
 
2.3%
의 135
 
2.1%
정 130
 
2.1%
보 122
 
1.9%
법 118
 
1.9%
제 118
 
1.9%
Other values (363) 4773
75.6%
Latin
ValueCountFrequency (%)
i 9
 
8.0%
n 8
 
7.1%
s 7
 
6.2%
N 6
 
5.4%
l 6
 
5.4%
S 5
 
4.5%
C 5
 
4.5%
o 5
 
4.5%
E 5
 
4.5%
w 4
 
3.6%
Other values (25) 52
46.4%
Common
ValueCountFrequency (%)
1320
60.4%
( 162
 
7.4%
) 162
 
7.4%
2 145
 
6.6%
1 91
 
4.2%
0 88
 
4.0%
~ 29
 
1.3%
6 23
 
1.1%
5 22
 
1.0%
4 21
 
1.0%
Other values (11) 121
 
5.5%
Han
ValueCountFrequency (%)
下 1
33.3%
中 1
33.3%
上 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6317
73.3%
ASCII 2271
 
26.4%
None 21
 
0.2%
Number Forms 4
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1320
58.1%
( 162
 
7.1%
) 162
 
7.1%
2 145
 
6.4%
1 91
 
4.0%
0 88
 
3.9%
~ 29
 
1.3%
6 23
 
1.0%
5 22
 
1.0%
4 21
 
0.9%
Other values (43) 208
 
9.2%
Hangul
ValueCountFrequency (%)
사 234
 
3.7%
무 219
 
3.5%
기 167
 
2.6%
이 153
 
2.4%
실 148
 
2.3%
의 135
 
2.1%
정 130
 
2.1%
보 122
 
1.9%
법 118
 
1.9%
제 118
 
1.9%
Other values (363) 4773
75.6%
None
ValueCountFrequency (%)
· 21
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
50.0%
Ⅱ 2
50.0%
CJK
ValueCountFrequency (%)
下 1
33.3%
中 1
33.3%
上 1
33.3%

교육일정내용
Text

Distinct150
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2023-12-12T14:08:56.431029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length115
Median length11
Mean length12.296998
Min length2

Characters and Unicode

Total characters7784
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)20.4%

Sample

1st row5월~9월
2nd row22년5월~23년2월
3rd row3-14 ~3-18 9-19 ~9-23
4th row4-11 ~4-15 10-17 ~10-21
5th row3-21 ~3-25 11-7 ~11-11
ValueCountFrequency (%)
12-31 462
24.5%
462
24.5%
2-1 447
23.7%
3-1 15
 
0.8%
11-4 7
 
0.4%
3-4 6
 
0.3%
4-18 6
 
0.3%
3-25 6
 
0.3%
4-20 6
 
0.3%
중 6
 
0.3%
Other values (186) 463
24.5%
2023-12-12T14:08:57.141037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1831
23.5%
1423
18.3%
- 1397
17.9%
2 1176
15.1%
~ 704
 
9.0%
3 589
 
7.6%
4 111
 
1.4%
5 102
 
1.3%
8 97
 
1.2%
7 83
 
1.1%
Other values (9) 271
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4222
54.2%
Space Separator 1423
 
18.3%
Dash Punctuation 1397
 
17.9%
Math Symbol 706
 
9.1%
Other Letter 36
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1831
43.4%
2 1176
27.9%
3 589
 
14.0%
4 111
 
2.6%
5 102
 
2.4%
8 97
 
2.3%
7 83
 
2.0%
9 81
 
1.9%
0 77
 
1.8%
6 75
 
1.8%
Other Letter
ValueCountFrequency (%)
월 17
47.2%
중 7
19.4%
정 5
 
13.9%
미 5
 
13.9%
년 2
 
5.6%
Math Symbol
ValueCountFrequency (%)
~ 704
99.7%
∼ 2
 
0.3%
Space Separator
ValueCountFrequency (%)
1423
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1397
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7748
99.5%
Hangul 36
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1831
23.6%
1423
18.4%
- 1397
18.0%
2 1176
15.2%
~ 704
 
9.1%
3 589
 
7.6%
4 111
 
1.4%
5 102
 
1.3%
8 97
 
1.3%
7 83
 
1.1%
Other values (4) 235
 
3.0%
Hangul
ValueCountFrequency (%)
월 17
47.2%
중 7
19.4%
정 5
 
13.9%
미 5
 
13.9%
년 2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7746
99.5%
Hangul 36
 
0.5%
Math Operators 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1831
23.6%
1423
18.4%
- 1397
18.0%
2 1176
15.2%
~ 704
 
9.1%
3 589
 
7.6%
4 111
 
1.4%
5 102
 
1.3%
8 97
 
1.3%
7 83
 
1.1%
Other values (3) 233
 
3.0%
Hangul
ValueCountFrequency (%)
월 17
47.2%
중 7
19.4%
정 5
 
13.9%
미 5
 
13.9%
년 2
 
5.6%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%

정원수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278.20379
Minimum7
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-12T14:08:57.298643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile20
Q1100
median200
Q3500
95-th percentile500
Maximum1000
Range993
Interquartile range (IQR)400

Descriptive statistics

Standard deviation194.32014
Coefficient of variation (CV)0.69848129
Kurtosis-1.3457738
Mean278.20379
Median Absolute Deviation (MAD)175
Skewness0.1053632
Sum176103
Variance37760.318
MonotonicityNot monotonic
2023-12-12T14:08:57.463983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
500 246
38.9%
200 185
29.2%
20 45
 
7.1%
30 29
 
4.6%
300 28
 
4.4%
40 26
 
4.1%
50 19
 
3.0%
100 9
 
1.4%
25 9
 
1.4%
10 8
 
1.3%
Other values (16) 29
 
4.6%
ValueCountFrequency (%)
7 1
 
0.2%
10 8
 
1.3%
12 1
 
0.2%
14 1
 
0.2%
15 6
 
0.9%
17 2
 
0.3%
20 45
7.1%
25 9
 
1.4%
30 29
4.6%
35 2
 
0.3%
ValueCountFrequency (%)
1000 1
 
0.2%
500 246
38.9%
300 28
 
4.4%
250 1
 
0.2%
200 185
29.2%
180 1
 
0.2%
170 1
 
0.2%
130 2
 
0.3%
108 1
 
0.2%
100 9
 
1.4%

교육횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4470774
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-12T14:08:57.620468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median11
Q311
95-th percentile11
Maximum17
Range16
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.2071513
Coefficient of variation (CV)0.49805999
Kurtosis-0.74203015
Mean8.4470774
Median Absolute Deviation (MAD)0
Skewness-1.0742782
Sum5347
Variance17.700122
MonotonicityNot monotonic
2023-12-12T14:08:57.754126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
11 428
67.6%
1 113
 
17.9%
2 36
 
5.7%
10 34
 
5.4%
3 10
 
1.6%
5 5
 
0.8%
4 4
 
0.6%
14 1
 
0.2%
17 1
 
0.2%
12 1
 
0.2%
ValueCountFrequency (%)
1 113
 
17.9%
2 36
 
5.7%
3 10
 
1.6%
4 4
 
0.6%
5 5
 
0.8%
10 34
 
5.4%
11 428
67.6%
12 1
 
0.2%
14 1
 
0.2%
17 1
 
0.2%
ValueCountFrequency (%)
17 1
 
0.2%
14 1
 
0.2%
12 1
 
0.2%
11 428
67.6%
10 34
 
5.4%
5 5
 
0.8%
4 4
 
0.6%
3 10
 
1.6%
2 36
 
5.7%
1 113
 
17.9%

교육일수
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.627172
Minimum1
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-12T14:08:57.897760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q116
median30
Q330
95-th percentile30
Maximum200
Range199
Interquartile range (IQR)14

Descriptive statistics

Standard deviation15.205346
Coefficient of variation (CV)0.61742152
Kurtosis28.734427
Mean24.627172
Median Absolute Deviation (MAD)0
Skewness2.4447504
Sum15589
Variance231.20255
MonotonicityNot monotonic
2023-12-12T14:08:58.049164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
30 445
70.3%
3 72
 
11.4%
2 40
 
6.3%
5 29
 
4.6%
60 19
 
3.0%
1 7
 
1.1%
10 5
 
0.8%
20 3
 
0.5%
16 3
 
0.5%
15 3
 
0.5%
Other values (7) 7
 
1.1%
ValueCountFrequency (%)
1 7
 
1.1%
2 40
6.3%
3 72
11.4%
5 29
4.6%
10 5
 
0.8%
15 3
 
0.5%
16 3
 
0.5%
19 1
 
0.2%
20 3
 
0.5%
22 1
 
0.2%
ValueCountFrequency (%)
200 1
 
0.2%
110 1
 
0.2%
60 19
 
3.0%
48 1
 
0.2%
30 445
70.3%
25 1
 
0.2%
24 1
 
0.2%
22 1
 
0.2%
20 3
 
0.5%
19 1
 
0.2%

Interactions

2023-12-12T14:08:54.007404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:53.176734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:53.537218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:54.149137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:53.284147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:53.675796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:54.296305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:53.408134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:53.818341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:08:58.197666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직렬명정원수교육횟수교육일수
직렬명1.0000.7920.5040.394
정원수0.7921.0000.6770.846
교육횟수0.5040.6771.0000.732
교육일수0.3940.8460.7321.000
2023-12-12T14:08:58.339126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원수교육횟수교육일수직렬명
정원수1.0000.7400.7440.613
교육횟수0.7401.0000.7560.295
교육일수0.7440.7561.0000.240
직렬명0.6130.2950.2401.000

Missing values

2023-12-12T14:08:54.480491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:08:54.636116image/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

직렬명과정명교육일정내용정원수교육횟수교육일수
0검사신임검사(사법 시험)5월~9월1001110
1검사신임검사(법전원)22년5월~23년2월1001200
2검사저년차 검사 역량강화 필수과정3-14 ~3-18 9-19 ~9-234025
3검사저년차 검사 역량강화 선택과정(경제범죄 심화 ·서민다중피해범죄)4-11 ~4-15 10-17 ~10-212025
4검사저년차 검사 역량강화 선택과정(조세·관세 특허·지재)3-21 ~3-25 11-7 ~11-112525
5검사저년차 검사 역량강화 선택과정(아동학대·성폭력범죄)3-2 ~3-42513
6검사경력검사 리더십5-9 ~5-13 9-19 ~9-233525
7검사부장검사 리더십 (부부장검사)4-4 ~4-1535110
8검사부장검사 리더십 (신임부장검사)10-17 ~10-213015
9검사차장검사 리더십8 29 ~9 21515
직렬명과정명교육일정내용정원수교육횟수교육일수
623타부처[국가송무] 보전처분 실무3-1 ~ 12-312001030
624타부처[국가송무] 부동산 소송3-1 ~ 12-312001030
625타부처[국가송무] 사행행위 취소3-1 ~ 12-312001030
626타부처[국가송무] 손해배상소송3-1 ~ 12-312001030
627타부처[국가송무] 영업허가 및 운전면허 소송 실무3-1 ~ 12-312001030
628타부처[국가송무] 정보공개 소송3-1 ~ 12-312001030
629타부처[국가송무] 국고손실 환수송무의 이해3-1 ~ 12-312001030
630타부처특별사법경찰 수사실무3-1 ~ 12-311000560
631타부처셉테드3-1 ~ 12-313001030
632타부처재한 외국인이 들려주는 상호문화의 이해2-1 ~ 12-313001230

Duplicate rows

Most frequently occurring

직렬명과정명교육일정내용정원수교육횟수교육일수# duplicates
0공통정부 규제혁신(2019)2-1 ~ 12-3150011302