Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory654.3 KiB
Average record size in memory67.0 B

Variable types

Text3
Numeric3
Categorical1

Dataset

Description농촌인적자원개발센터 시험정보를 관리하는 공공데이터입니다. 강의코드,강의명, 강의차수,문제번호,문제타입,문제내용,답변인원을 제공합니다.
Author농촌진흥청
URLhttps://www.data.go.kr/data/15084792/fileData.do

Alerts

문제타입 is highly imbalanced (76.2%)Imbalance
답변인원 is highly skewed (γ1 = 20.30608194)Skewed

Reproduction

Analysis started2023-12-12 12:12:10.108286
Analysis finished2023-12-12 12:12:12.672894
Duration2.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강의코드
Text

Distinct196
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:12:12.941525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowE1Y200035
2nd rowE1Y160002
3rd rowE1Y190033
4th rowE1Y150001
5th rowE1Y200106
ValueCountFrequency (%)
e1y140004 453
 
4.5%
e1y140005 421
 
4.2%
e1y140002 403
 
4.0%
e1y140003 394
 
3.9%
e1y150001 299
 
3.0%
e1y170001 266
 
2.7%
e1y160001 261
 
2.6%
e1y160002 255
 
2.5%
e1y140013 222
 
2.2%
e1y200138 137
 
1.4%
Other values (186) 6889
68.9%
2023-12-12T21:12:13.472470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26886
29.9%
1 20958
23.3%
E 10000
 
11.1%
Y 10000
 
11.1%
2 8021
 
8.9%
4 3522
 
3.9%
3 3021
 
3.4%
9 1868
 
2.1%
5 1743
 
1.9%
6 1557
 
1.7%
Other values (2) 2424
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70000
77.8%
Uppercase Letter 20000
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26886
38.4%
1 20958
29.9%
2 8021
 
11.5%
4 3522
 
5.0%
3 3021
 
4.3%
9 1868
 
2.7%
5 1743
 
2.5%
6 1557
 
2.2%
7 1255
 
1.8%
8 1169
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
E 10000
50.0%
Y 10000
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70000
77.8%
Latin 20000
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26886
38.4%
1 20958
29.9%
2 8021
 
11.5%
4 3522
 
5.0%
3 3021
 
4.3%
9 1868
 
2.7%
5 1743
 
2.5%
6 1557
 
2.2%
7 1255
 
1.8%
8 1169
 
1.7%
Latin
ValueCountFrequency (%)
E 10000
50.0%
Y 10000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26886
29.9%
1 20958
23.3%
E 10000
 
11.1%
Y 10000
 
11.1%
2 8021
 
8.9%
4 3522
 
3.9%
3 3021
 
3.4%
9 1868
 
2.1%
5 1743
 
1.9%
6 1557
 
1.7%
Other values (2) 2424
 
2.7%

강의명
Text

Distinct159
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:12:13.783542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length13.283
Min length7

Characters and Unicode

Total characters132830
Distinct characters247
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowe-러닝(FTA활용을통한수출확대전략)
2nd row사이버(고품질한우생산)
3rd row사이버(양봉)
4th row사이버(양잠산업의 이해)
5th rowe-러닝(마인드프로세싱-일잘하는사람의전략스킬)
ValueCountFrequency (%)
관리 718
 
4.8%
new 691
 
4.6%
특성과 639
 
4.3%
사이버(양봉 526
 
3.5%
이해 519
 
3.5%
사이버(귀농귀촌 510
 
3.4%
사이버(농작업재해의 488
 
3.3%
사이버(발효식품-전통주 485
 
3.2%
사이버(쌈채소 472
 
3.2%
공무원 305
 
2.0%
Other values (197) 9606
64.2%
2023-12-12T21:12:14.208461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 10129
 
7.6%
) 10129
 
7.6%
5946
 
4.5%
이 5711
 
4.3%
- 5371
 
4.0%
사 5150
 
3.9%
버 4864
 
3.7%
e 4758
 
3.6%
닝 4470
 
3.4%
러 4470
 
3.4%
Other values (237) 71832
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90818
68.4%
Open Punctuation 10129
 
7.6%
Close Punctuation 10129
 
7.6%
Space Separator 5946
 
4.5%
Dash Punctuation 5371
 
4.0%
Lowercase Letter 5046
 
3.8%
Uppercase Letter 4033
 
3.0%
Other Punctuation 708
 
0.5%
Connector Punctuation 646
 
0.5%
Decimal Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 5711
 
6.3%
사 5150
 
5.7%
버 4864
 
5.4%
닝 4470
 
4.9%
러 4470
 
4.9%
농 2127
 
2.3%
업 1637
 
1.8%
해 1636
 
1.8%
의 1569
 
1.7%
기 1552
 
1.7%
Other values (215) 57632
63.5%
Uppercase Letter
ValueCountFrequency (%)
N 774
19.2%
L 662
16.4%
B 662
16.4%
W 486
12.1%
E 486
12.1%
A 321
8.0%
F 321
8.0%
T 321
8.0%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
0 1
25.0%
1 1
25.0%
4 1
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 662
93.5%
, 34
 
4.8%
? 12
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
e 4758
94.3%
w 288
 
5.7%
Open Punctuation
ValueCountFrequency (%)
( 10129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10129
100.0%
Space Separator
ValueCountFrequency (%)
5946
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5371
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 646
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90818
68.4%
Common 32933
 
24.8%
Latin 9079
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 5711
 
6.3%
사 5150
 
5.7%
버 4864
 
5.4%
닝 4470
 
4.9%
러 4470
 
4.9%
농 2127
 
2.3%
업 1637
 
1.8%
해 1636
 
1.8%
의 1569
 
1.7%
기 1552
 
1.7%
Other values (215) 57632
63.5%
Common
ValueCountFrequency (%)
( 10129
30.8%
) 10129
30.8%
5946
18.1%
- 5371
16.3%
/ 662
 
2.0%
_ 646
 
2.0%
, 34
 
0.1%
? 12
 
< 0.1%
2 1
 
< 0.1%
0 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Latin
ValueCountFrequency (%)
e 4758
52.4%
N 774
 
8.5%
L 662
 
7.3%
B 662
 
7.3%
W 486
 
5.4%
E 486
 
5.4%
A 321
 
3.5%
F 321
 
3.5%
T 321
 
3.5%
w 288
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90818
68.4%
ASCII 42012
31.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 10129
24.1%
) 10129
24.1%
5946
14.2%
- 5371
12.8%
e 4758
11.3%
N 774
 
1.8%
/ 662
 
1.6%
L 662
 
1.6%
B 662
 
1.6%
_ 646
 
1.5%
Other values (12) 2273
 
5.4%
Hangul
ValueCountFrequency (%)
이 5711
 
6.3%
사 5150
 
5.7%
버 4864
 
5.4%
닝 4470
 
4.9%
러 4470
 
4.9%
농 2127
 
2.3%
업 1637
 
1.8%
해 1636
 
1.8%
의 1569
 
1.7%
기 1552
 
1.7%
Other values (215) 57632
63.5%

기수
Real number (ℝ)

Distinct59
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.1591
Minimum1
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:12:14.366019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q314
95-th percentile39
Maximum76
Range75
Interquartile range (IQR)11

Descriptive statistics

Standard deviation11.849955
Coefficient of variation (CV)1.0619095
Kurtosis1.8226613
Mean11.1591
Median Absolute Deviation (MAD)4
Skewness1.6044282
Sum111591
Variance140.42143
MonotonicityNot monotonic
2023-12-12T21:12:14.513830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1027
 
10.3%
1 1000
 
10.0%
3 849
 
8.5%
5 838
 
8.4%
6 726
 
7.3%
4 684
 
6.8%
7 561
 
5.6%
8 412
 
4.1%
9 391
 
3.9%
10 295
 
2.9%
Other values (49) 3217
32.2%
ValueCountFrequency (%)
1 1000
10.0%
2 1027
10.3%
3 849
8.5%
4 684
6.8%
5 838
8.4%
6 726
7.3%
7 561
5.6%
8 412
4.1%
9 391
 
3.9%
10 295
 
2.9%
ValueCountFrequency (%)
76 1
 
< 0.1%
74 1
 
< 0.1%
73 1
 
< 0.1%
65 1
 
< 0.1%
62 1
 
< 0.1%
58 1
 
< 0.1%
56 1
 
< 0.1%
52 13
0.1%
51 11
0.1%
50 9
0.1%

문제번호
Real number (ℝ)

Distinct198
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.5859
Minimum1
Maximum237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:12:14.698902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q112
median25
Q349
95-th percentile177
Maximum237
Range236
Interquartile range (IQR)37

Descriptive statistics

Standard deviation50.824979
Coefficient of variation (CV)1.1660876
Kurtosis3.1272573
Mean43.5859
Median Absolute Deviation (MAD)16
Skewness1.9555104
Sum435859
Variance2583.1785
MonotonicityNot monotonic
2023-12-12T21:12:14.872268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 277
 
2.8%
5 262
 
2.6%
9 243
 
2.4%
17 237
 
2.4%
15 224
 
2.2%
13 222
 
2.2%
3 219
 
2.2%
16 218
 
2.2%
7 217
 
2.2%
8 213
 
2.1%
Other values (188) 7668
76.7%
ValueCountFrequency (%)
1 277
2.8%
2 207
2.1%
3 219
2.2%
4 203
2.0%
5 262
2.6%
6 189
1.9%
7 217
2.2%
8 213
2.1%
9 243
2.4%
10 209
2.1%
ValueCountFrequency (%)
237 1
 
< 0.1%
233 3
 
< 0.1%
229 3
 
< 0.1%
225 11
0.1%
223 16
0.2%
222 1
 
< 0.1%
221 25
0.2%
220 1
 
< 0.1%
219 25
0.2%
217 20
0.2%

문제타입
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4지선다형
9082 
O/X
 
860
5지선다형
 
55
단답서술형
 
3

Length

Max length5
Median length5
Mean length4.828
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4지선다형
2nd row4지선다형
3rd row4지선다형
4th row4지선다형
5th row4지선다형

Common Values

ValueCountFrequency (%)
4지선다형 9082
90.8%
O/X 860
 
8.6%
5지선다형 55
 
0.5%
단답서술형 3
 
< 0.1%

Length

2023-12-12T21:12:15.031584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:12:15.148560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4지선다형 9082
90.8%
o/x 860
 
8.6%
5지선다형 55
 
0.5%
단답서술형 3
 
< 0.1%

문제
Text

Distinct2308
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:12:15.519181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length372
Median length152
Mean length36.8716
Min length3

Characters and Unicode

Total characters368716
Distinct characters980
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique647 ?
Unique (%)6.5%

Sample

1st row다음에서 FTA협정에서 기술무역장벽을 뜻하는 용어는?
2nd row초음파로 육질 및 육량을 진단할 때 알 수 있는 형질이 아닌 것은?
3rd row수벌번데기에 대한 설명으로 옳지 않은 것은?
4th row수번데기 생산에 가장 알맞은 누에품종은?
5th row다음중 브레인스토밍의 4가지 원칙에 해당하지 않는 것은?
ValueCountFrequency (%)
것은 6870
 
7.3%
중 3798
 
4.1%
다음 2865
 
3.1%
대한 1960
 
2.1%
아닌 1724
 
1.8%
않은 1526
 
1.6%
설명으로 1358
 
1.4%
틀린 1121
 
1.2%
않는 902
 
1.0%
옳지 865
 
0.9%
Other values (8778) 70740
75.5%
2023-12-12T21:12:16.308409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84362
 
22.9%
은 11136
 
3.0%
? 8979
 
2.4%
것 7704
 
2.1%
에 6686
 
1.8%
의 6603
 
1.8%
는 6287
 
1.7%
이 5870
 
1.6%
다 5746
 
1.6%
한 5032
 
1.4%
Other values (970) 220311
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 264555
71.8%
Space Separator 84362
 
22.9%
Other Punctuation 12350
 
3.3%
Uppercase Letter 2279
 
0.6%
Decimal Number 2026
 
0.5%
Close Punctuation 787
 
0.2%
Open Punctuation 784
 
0.2%
Lowercase Letter 722
 
0.2%
Initial Punctuation 230
 
0.1%
Final Punctuation 215
 
0.1%
Other values (5) 406
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
은 11136
 
4.2%
것 7704
 
2.9%
에 6686
 
2.5%
의 6603
 
2.5%
는 6287
 
2.4%
이 5870
 
2.2%
다 5746
 
2.2%
한 5032
 
1.9%
로 4712
 
1.8%
중 4561
 
1.7%
Other values (870) 200218
75.7%
Lowercase Letter
ValueCountFrequency (%)
m 78
10.8%
g 72
 
10.0%
e 68
 
9.4%
a 55
 
7.6%
i 49
 
6.8%
c 45
 
6.2%
p 43
 
6.0%
r 42
 
5.8%
t 39
 
5.4%
o 39
 
5.4%
Other values (15) 192
26.6%
Uppercase Letter
ValueCountFrequency (%)
O 401
17.6%
X 339
14.9%
T 335
14.7%
A 248
10.9%
F 198
8.7%
C 147
 
6.5%
I 97
 
4.3%
P 93
 
4.1%
M 55
 
2.4%
R 53
 
2.3%
Other values (14) 313
13.7%
Other Punctuation
ValueCountFrequency (%)
? 8979
72.7%
. 1957
 
15.8%
, 1025
 
8.3%
· 138
 
1.1%
" 64
 
0.5%
% 61
 
0.5%
' 38
 
0.3%
？ 30
 
0.2%
/ 28
 
0.2%
: 17
 
0.1%
Other values (3) 13
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 516
25.5%
1 428
21.1%
3 246
12.1%
2 229
11.3%
5 178
 
8.8%
4 161
 
7.9%
6 115
 
5.7%
9 70
 
3.5%
8 45
 
2.2%
7 38
 
1.9%
Math Symbol
ValueCountFrequency (%)
~ 76
45.5%
∼ 36
21.6%
> 23
 
13.8%
～ 15
 
9.0%
< 9
 
5.4%
= 7
 
4.2%
× 1
 
0.6%
Other Symbol
ValueCountFrequency (%)
℃ 68
73.9%
° 18
 
19.6%
㎖ 3
 
3.3%
□ 2
 
2.2%
○ 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 648
82.3%
] 90
 
11.4%
」 27
 
3.4%
』 22
 
2.8%
Open Punctuation
ValueCountFrequency (%)
( 644
82.1%
[ 91
 
11.6%
「 27
 
3.4%
『 22
 
2.8%
Initial Punctuation
ValueCountFrequency (%)
“ 141
61.3%
‘ 89
38.7%
Final Punctuation
ValueCountFrequency (%)
” 134
62.3%
’ 81
37.7%
Space Separator
ValueCountFrequency (%)
84362
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 30
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 264477
71.7%
Common 101154
 
27.4%
Latin 3007
 
0.8%
Han 78
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
은 11136
 
4.2%
것 7704
 
2.9%
에 6686
 
2.5%
의 6603
 
2.5%
는 6287
 
2.4%
이 5870
 
2.2%
다 5746
 
2.2%
한 5032
 
1.9%
로 4712
 
1.8%
중 4561
 
1.7%
Other values (846) 200140
75.7%
Common
ValueCountFrequency (%)
84362
83.4%
? 8979
 
8.9%
. 1957
 
1.9%
, 1025
 
1.0%
) 648
 
0.6%
( 644
 
0.6%
0 516
 
0.5%
1 428
 
0.4%
3 246
 
0.2%
2 229
 
0.2%
Other values (40) 2120
 
2.1%
Latin
ValueCountFrequency (%)
O 401
13.3%
X 339
 
11.3%
T 335
 
11.1%
A 248
 
8.2%
F 198
 
6.6%
C 147
 
4.9%
I 97
 
3.2%
P 93
 
3.1%
m 78
 
2.6%
g 72
 
2.4%
Other values (40) 999
33.2%
Han
ValueCountFrequency (%)
蠶 13
16.7%
家 13
16.7%
甘 5
 
6.4%
川 5
 
6.4%
芎 5
 
6.4%
草 5
 
6.4%
朮 4
 
5.1%
白 4
 
5.1%
美 2
 
2.6%
必 2
 
2.6%
Other values (14) 20
25.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 264453
71.7%
ASCII 103297
 
28.0%
Punctuation 448
 
0.1%
None 300
 
0.1%
CJK 78
 
< 0.1%
Letterlike Symbols 68
 
< 0.1%
Math Operators 36
 
< 0.1%
Compat Jamo 24
 
< 0.1%
Number Forms 6
 
< 0.1%
CJK Compat 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84362
81.7%
? 8979
 
8.7%
. 1957
 
1.9%
, 1025
 
1.0%
) 648
 
0.6%
( 644
 
0.6%
0 516
 
0.5%
1 428
 
0.4%
O 401
 
0.4%
X 339
 
0.3%
Other values (70) 3998
 
3.9%
Hangul
ValueCountFrequency (%)
은 11136
 
4.2%
것 7704
 
2.9%
에 6686
 
2.5%
의 6603
 
2.5%
는 6287
 
2.4%
이 5870
 
2.2%
다 5746
 
2.2%
한 5032
 
1.9%
로 4712
 
1.8%
중 4561
 
1.7%
Other values (841) 200116
75.7%
Punctuation
ValueCountFrequency (%)
“ 141
31.5%
” 134
29.9%
‘ 89
19.9%
’ 81
18.1%
… 3
 
0.7%
None
ValueCountFrequency (%)
· 138
46.0%
？ 30
 
10.0%
」 27
 
9.0%
「 27
 
9.0%
『 22
 
7.3%
』 22
 
7.3%
° 18
 
6.0%
～ 15
 
5.0%
× 1
 
0.3%
Letterlike Symbols
ValueCountFrequency (%)
℃ 68
100.0%
Math Operators
ValueCountFrequency (%)
∼ 36
100.0%
CJK
ValueCountFrequency (%)
蠶 13
16.7%
家 13
16.7%
甘 5
 
6.4%
川 5
 
6.4%
芎 5
 
6.4%
草 5
 
6.4%
朮 4
 
5.1%
白 4
 
5.1%
美 2
 
2.6%
必 2
 
2.6%
Other values (14) 20
25.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 12
50.0%
ㄹ 3
 
12.5%
ㄷ 3
 
12.5%
ㄱ 3
 
12.5%
ㄴ 3
 
12.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
100.0%
CJK Compat
ValueCountFrequency (%)
㎖ 3
100.0%
Geometric Shapes
ValueCountFrequency (%)
□ 2
66.7%
○ 1
33.3%

답변인원
Real number (ℝ)

SKEWED 

Distinct163
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.5021
Minimum1
Maximum3347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:12:16.516615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113
median25
Q342
95-th percentile96
Maximum3347
Range3346
Interquartile range (IQR)29

Descriptive statistics

Standard deviation133.56554
Coefficient of variation (CV)3.2977435
Kurtosis470.99457
Mean40.5021
Median Absolute Deviation (MAD)13
Skewness20.306082
Sum405021
Variance17839.753
MonotonicityNot monotonic
2023-12-12T21:12:16.728811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 260
 
2.6%
25 254
 
2.5%
1 248
 
2.5%
23 242
 
2.4%
9 241
 
2.4%
22 230
 
2.3%
10 227
 
2.3%
21 224
 
2.2%
18 223
 
2.2%
5 221
 
2.2%
Other values (153) 7630
76.3%
ValueCountFrequency (%)
1 248
2.5%
2 168
1.7%
3 197
2.0%
4 167
1.7%
5 221
2.2%
6 187
1.9%
7 152
1.5%
8 183
1.8%
9 241
2.4%
10 227
2.3%
ValueCountFrequency (%)
3347 12
0.1%
1681 8
0.1%
1309 5
0.1%
696 3
 
< 0.1%
680 4
 
< 0.1%
567 9
0.1%
419 7
0.1%
325 4
 
< 0.1%
315 1
 
< 0.1%
304 8
0.1%

Interactions

2023-12-12T21:12:11.793781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:11.108792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:11.446466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:12.240782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:11.218955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:11.575765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:12.362228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:11.327464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:11.674994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:12:16.844307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기수문제번호문제타입답변인원
기수1.0000.4170.3370.000
문제번호0.4171.0000.2660.027
문제타입0.3370.2661.0000.042
답변인원0.0000.0270.0421.000
2023-12-12T21:12:16.969631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기수문제번호답변인원문제타입
기수1.0000.192-0.0590.206
문제번호0.1921.000-0.0000.161
답변인원-0.059-0.0001.0000.027
문제타입0.2060.1610.0271.000

Missing values

2023-12-12T21:12:12.491837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:12:12.615033image/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

강의코드강의명기수문제번호문제타입문제답변인원
17788E1Y200035e-러닝(FTA활용을통한수출확대전략)7264지선다형다음에서 FTA협정에서 기술무역장벽을 뜻하는 용어는?8
48637E1Y160002사이버(고품질한우생산)12114지선다형초음파로 육질 및 육량을 진단할 때 알 수 있는 형질이 아닌 것은?10
36430E1Y190033사이버(양봉)1594지선다형수벌번데기에 대한 설명으로 옳지 않은 것은?29
51597E1Y150001사이버(양잠산업의 이해)29254지선다형수번데기 생산에 가장 알맞은 누에품종은?3
21681E1Y200106e-러닝(마인드프로세싱-일잘하는사람의전략스킬)1384지선다형다음중 브레인스토밍의 4가지 원칙에 해당하지 않는 것은?7
45772E1Y170006사이버(포도)18174지선다형청포도는 과피에 동녹이 발생되면 상품성이 떨어지므로 동녹에 주의해야 하는데, 기상환경에 따른 동녹 발생형태로 옳은 것은?16
14989E1Y200024e-러닝(쌈채소)10344지선다형고추냉이의 맛에 해당하지 않는 것은?55
42513E1Y170001사이버(농작업재해의 특성과 관리) New26324지선다형다음 중 농약중독 시 행동요령으로 틀린 것은?20
63801E1Y140013사이버(농작업재해의 특성과 관리)101774지선다형다음 중 자비 또는 사업주 부담으로 치료 받은 경우 산재보상 신청 시 고려해야 할 사항으로 옳지 않은 것은?13
31120E1Y190010사이버(마늘) NEW16O/X다음의 설명을 읽고 OX를 선택해 보세요. 우리나라의 마늘 소비량은 세계 최고 수준이다.20
강의코드강의명기수문제번호문제타입문제답변인원
53491E1Y140002사이버(발효식품-전통주)19165O/X다음의 설명을 읽고 맞으면 O, 틀리면 X를 선택하세요. 증류식 소주의 숙성기간은 3개월 이하로 하여야 한다.37
18171E1Y200036e-러닝(고품질한우생산)6324지선다형우사시설 배치에 관해 설명한 것 중 틀린 것은?19
8819E1Y200009e-러닝(양봉)4104지선다형꿀벌 조직사회의 핵심이 되는 것은?67
25902E1Y200141e-러닝(마인드프로세싱-일잘하는사람의전략스킬) 공무원514지선다형정보 DB구축에 필요한 File Server의 구비요건이 아닌 것은?1
28757E1Y210024e-러닝(병해충진단과 방제)3164지선다형다음 중 식물체에 감염 후 잠복기를 가지는 병원균이 아닌 것은?186
2493E1Y210036e-러닝(복숭아)744지선다형복숭아 재배에 적합한 토양조건으로 옳지 않은 것은?15
22738E1Y200126e-러닝(개인정보보호법 이해하기)_공무원4414지선다형다음 중 개인정보 파기에 관한 설명으로 적절하지 않은 것은?21
5368E1Y210164e-러닝(청렴_세상을 바꾸는 힘, 공익신고)194지선다형다음 중 조사를 하지 않거나 중단하고 끝낼 수 있는 경우가 아닌 것은?71
35538E1Y190031사이버(복숭아)444지선다형우리나라와 FTA가 타결될 경우 복숭아 산업에 가장 큰 위협이 될 것으로 전망되는 국가는?16
15222E1Y200025e-러닝(발효식품-전통주)3304지선다형미생물의 존재를 증명하여 와인제조 등 발효산업을 획기적으로 발전시킨 사람은?24