Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory927.7 KiB
Average record size in memory95.0 B

Variable types

Numeric7
Text1
Categorical1
DateTime1

Dataset

Description교육운영시스템 수강내역 관련입니다.(예, 수강번호, 평가항목,id, 과정차수id, 평가항목코드, 평가항목명 등)
URLhttps://www.data.go.kr/data/15083480/fileData.do

Alerts

평가항목아이디 is highly overall correlated with 평가항목코드 and 1 other fieldsHigh correlation
평가항목코드 is highly overall correlated with 평가항목아이디 and 1 other fieldsHigh correlation
평가항목반영율 is highly overall correlated with 평가총점 and 1 other fieldsHigh correlation
평가총점 is highly overall correlated with 평가항목반영율 and 1 other fieldsHigh correlation
평가원점수 is highly overall correlated with 평가총점High correlation
평가항목명 is highly overall correlated with 평가항목아이디 and 2 other fieldsHigh correlation
평가항목반영율 has 415 (4.2%) zerosZeros
평가총점 has 6621 (66.2%) zerosZeros
평가원점수 has 8281 (82.8%) zerosZeros

Reproduction

Analysis started2023-12-12 09:07:41.924123
Analysis finished2023-12-12 09:07:49.812383
Duration7.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수강번호
Real number (ℝ)

Distinct7447
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1722714.4
Minimum928585
Maximum3218732
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:07:49.892894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum928585
5-th percentile1070019.6
Q11436447
median1786324
Q31981550.2
95-th percentile2178854.1
Maximum3218732
Range2290147
Interquartile range (IQR)545103.25

Descriptive statistics

Standard deviation358384.57
Coefficient of variation (CV)0.20803481
Kurtosis1.7344864
Mean1722714.4
Median Absolute Deviation (MAD)271600.5
Skewness0.25298353
Sum1.7227144 × 1010
Variance1.284395 × 1011
MonotonicityNot monotonic
2023-12-12T18:07:50.051378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1880606 5
 
0.1%
1964902 5
 
0.1%
2002827 5
 
0.1%
1964942 5
 
0.1%
1744978 5
 
0.1%
1505181 5
 
0.1%
2144119 5
 
0.1%
1803708 4
 
< 0.1%
1786249 4
 
< 0.1%
1745287 4
 
< 0.1%
Other values (7437) 9953
99.5%
ValueCountFrequency (%)
928585 1
< 0.1%
928598 1
< 0.1%
930650 1
< 0.1%
931197 1
< 0.1%
931198 1
< 0.1%
931199 1
< 0.1%
931246 1
< 0.1%
931346 1
< 0.1%
931347 1
< 0.1%
931565 1
< 0.1%
ValueCountFrequency (%)
3218732 1
< 0.1%
3218726 1
< 0.1%
3218724 1
< 0.1%
3218647 1
< 0.1%
3209017 1
< 0.1%
3208973 1
< 0.1%
3208972 1
< 0.1%
3208970 1
< 0.1%
3208851 1
< 0.1%
3208679 1
< 0.1%

평가항목아이디
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.2631
Minimum19
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:07:50.194431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile19
Q122
median23
Q367
95-th percentile92
Maximum124
Range105
Interquartile range (IQR)45

Descriptive statistics

Standard deviation29.413255
Coefficient of variation (CV)0.66450961
Kurtosis-0.30940621
Mean44.2631
Median Absolute Deviation (MAD)4
Skewness0.89927852
Sum442631
Variance865.13959
MonotonicityNot monotonic
2023-12-12T18:07:50.336931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
22 3757
37.6%
19 1153
 
11.5%
92 1000
 
10.0%
66 976
 
9.8%
67 841
 
8.4%
23 415
 
4.2%
64 389
 
3.9%
68 344
 
3.4%
124 314
 
3.1%
25 292
 
2.9%
Other values (9) 519
 
5.2%
ValueCountFrequency (%)
19 1153
 
11.5%
20 83
 
0.8%
21 3
 
< 0.1%
22 3757
37.6%
23 415
 
4.2%
24 158
 
1.6%
25 292
 
2.9%
26 62
 
0.6%
63 3
 
< 0.1%
64 389
 
3.9%
ValueCountFrequency (%)
124 314
 
3.1%
92 1000
10.0%
71 19
 
0.2%
70 10
 
0.1%
69 27
 
0.3%
68 344
 
3.4%
67 841
8.4%
66 976
9.8%
65 154
 
1.5%
64 389
 
3.9%

과정차수아이디
Text

Distinct616
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:07:50.839499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters170000
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

Unique28 ?
Unique (%)0.3%

Sample

1st rowNL000000571145844
2nd rowNL000003563900001
3rd rowNL000000580345925
4th rowNL000000571145879
5th rowNL000000571145851
ValueCountFrequency (%)
nl000000571145862 250
 
2.5%
nl000000571145879 232
 
2.3%
nl000000571145881 226
 
2.3%
nl000000571145878 226
 
2.3%
nl000000571145871 224
 
2.2%
nl000000571145876 223
 
2.2%
nl000000571145877 222
 
2.2%
nl000000571145861 217
 
2.2%
nl000000571145870 198
 
2.0%
nl000000571145858 187
 
1.9%
Other values (606) 7795
78.0%
2023-12-12T18:07:51.172330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70591
41.5%
5 17804
 
10.5%
1 16704
 
9.8%
4 11323
 
6.7%
N 10000
 
5.9%
L 10000
 
5.9%
7 9749
 
5.7%
8 9741
 
5.7%
6 3828
 
2.3%
9 3593
 
2.1%
Other values (2) 6667
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150000
88.2%
Uppercase Letter 20000
 
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 70591
47.1%
5 17804
 
11.9%
1 16704
 
11.1%
4 11323
 
7.5%
7 9749
 
6.5%
8 9741
 
6.5%
6 3828
 
2.6%
9 3593
 
2.4%
2 3406
 
2.3%
3 3261
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
N 10000
50.0%
L 10000
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 150000
88.2%
Latin 20000
 
11.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 70591
47.1%
5 17804
 
11.9%
1 16704
 
11.1%
4 11323
 
7.5%
7 9749
 
6.5%
8 9741
 
6.5%
6 3828
 
2.6%
9 3593
 
2.4%
2 3406
 
2.3%
3 3261
 
2.2%
Latin
ValueCountFrequency (%)
N 10000
50.0%
L 10000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70591
41.5%
5 17804
 
10.5%
1 16704
 
9.8%
4 11323
 
6.7%
N 10000
 
5.9%
L 10000
 
5.9%
7 9749
 
5.7%
8 9741
 
5.7%
6 3828
 
2.3%
9 3593
 
2.1%
Other values (2) 6667
 
3.9%

평가항목코드
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.3029
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:07:51.304732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median5
Q399
95-th percentile99
Maximum99
Range98
Interquartile range (IQR)94

Descriptive statistics

Standard deviation46.629724
Coefficient of variation (CV)1.0768268
Kurtosis-1.8708695
Mean43.3029
Median Absolute Deviation (MAD)3
Skewness0.35609695
Sum433029
Variance2174.3312
MonotonicityNot monotonic
2023-12-12T18:07:51.413554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
99 4119
41.2%
5 3757
37.6%
2 1153
 
11.5%
6 415
 
4.2%
1 314
 
3.1%
7 156
 
1.6%
3 83
 
0.8%
4 3
 
< 0.1%
ValueCountFrequency (%)
1 314
 
3.1%
2 1153
 
11.5%
3 83
 
0.8%
4 3
 
< 0.1%
5 3757
37.6%
6 415
 
4.2%
7 156
 
1.6%
99 4119
41.2%
ValueCountFrequency (%)
99 4119
41.2%
7 156
 
1.6%
6 415
 
4.2%
5 3757
37.6%
4 3
 
< 0.1%
3 83
 
0.8%
2 1153
 
11.5%
1 314
 
3.1%

평가항목명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
출석
3757 
과제
1153 
이러닝
1000 
행정실무
976 
근태
841 
Other values (14)
2273 

Length

Max length11
Median length2
Mean length3.0713
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사이버선행
2nd row출석
3rd row출석
4th row과제
5th row분임활동

Common Values

ValueCountFrequency (%)
출석 3757
37.6%
과제 1153
 
11.5%
이러닝 1000
 
10.0%
행정실무 976
 
9.8%
근태 841
 
8.4%
설문 415
 
4.2%
분임활동 389
 
3.9%
디자인씽킹 해결과제 344
 
3.4%
학습진도 314
 
3.1%
분임별 정책과제연구 292
 
2.9%
Other values (9) 519
 
5.2%

Length

2023-12-12T18:07:51.561069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
출석 3757
35.1%
과제 1153
 
10.8%
이러닝 1000
 
9.3%
행정실무 976
 
9.1%
근태 841
 
7.9%
설문 415
 
3.9%
분임활동 389
 
3.6%
디자인씽킹 344
 
3.2%
해결과제 344
 
3.2%
학습진도 314
 
2.9%
Other values (12) 1165
 
10.9%

평가항목반영율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.0524
Minimum0
Maximum100
Zeros415
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:07:51.684296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q110
median30
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)90

Descriptive statistics

Standard deviation39.648156
Coefficient of variation (CV)0.80828167
Kurtosis-1.6423421
Mean49.0524
Median Absolute Deviation (MAD)20
Skewness0.36823533
Sum490524
Variance1571.9763
MonotonicityNot monotonic
2023-12-12T18:07:51.800282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
100 3556
35.6%
10 2655
26.6%
30 1285
 
12.8%
20 827
 
8.3%
40 777
 
7.8%
0 415
 
4.2%
60 119
 
1.2%
50 117
 
1.2%
15 65
 
0.7%
45 43
 
0.4%
Other values (8) 141
 
1.4%
ValueCountFrequency (%)
0 415
 
4.2%
2 1
 
< 0.1%
5 27
 
0.3%
10 2655
26.6%
15 65
 
0.7%
20 827
 
8.3%
23 4
 
< 0.1%
25 25
 
0.2%
30 1285
12.8%
35 22
 
0.2%
ValueCountFrequency (%)
100 3556
35.6%
90 4
 
< 0.1%
80 26
 
0.3%
70 32
 
0.3%
60 119
 
1.2%
50 117
 
1.2%
45 43
 
0.4%
40 777
 
7.8%
35 22
 
0.2%
30 1285
 
12.8%

평가총점
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct145
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.938749
Minimum0
Maximum100
Zeros6621
Zeros (%)66.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:07:51.959242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q333.33
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)33.33

Descriptive statistics

Standard deviation41.470698
Coefficient of variation (CV)1.6629021
Kurtosis-0.48286425
Mean24.938749
Median Absolute Deviation (MAD)0
Skewness1.199676
Sum249387.49
Variance1719.8188
MonotonicityNot monotonic
2023-12-12T18:07:52.200657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6621
66.2%
100.0 2240
 
22.4%
10.0 340
 
3.4%
20.0 259
 
2.6%
3.71 34
 
0.3%
9.77 29
 
0.3%
50.0 26
 
0.3%
3.33 23
 
0.2%
7.85 23
 
0.2%
60.0 21
 
0.2%
Other values (135) 384
 
3.8%
ValueCountFrequency (%)
0.0 6621
66.2%
0.23 1
 
< 0.1%
0.45 1
 
< 0.1%
0.5 8
 
0.1%
1.0 10
 
0.1%
1.5 3
 
< 0.1%
2.0 1
 
< 0.1%
2.14 2
 
< 0.1%
2.28 2
 
< 0.1%
2.5 1
 
< 0.1%
ValueCountFrequency (%)
100.0 2240
22.4%
90.9 1
 
< 0.1%
90.0 5
 
0.1%
88.89 2
 
< 0.1%
88.5 1
 
< 0.1%
85.71 10
 
0.1%
83.5 1
 
< 0.1%
81.81 12
 
0.1%
80.0 8
 
0.1%
78.57 1
 
< 0.1%

작성자번호
Real number (ℝ)

Distinct232
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343933.83
Minimum0
Maximum1084450
Zeros63
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:07:52.458938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100767
Q1156295
median364736
Q3370087
95-th percentile1017973.6
Maximum1084450
Range1084450
Interquartile range (IQR)213792

Descriptive statistics

Standard deviation244478.67
Coefficient of variation (CV)0.71083053
Kurtosis2.0996475
Mean343933.83
Median Absolute Deviation (MAD)195427
Skewness1.5292726
Sum3.4393383 × 109
Variance5.9769819 × 1010
MonotonicityNot monotonic
2023-12-12T18:07:52.684158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
370087 1060
 
10.6%
165492 982
 
9.8%
368746 856
 
8.6%
140358 679
 
6.8%
586592 648
 
6.5%
364721 385
 
3.9%
169309 354
 
3.5%
116129 301
 
3.0%
1017952 299
 
3.0%
101297 253
 
2.5%
Other values (222) 4183
41.8%
ValueCountFrequency (%)
0 63
 
0.6%
73073 1
 
< 0.1%
73098 20
 
0.2%
73476 1
 
< 0.1%
73698 1
 
< 0.1%
73945 164
1.6%
74069 1
 
< 0.1%
76383 1
 
< 0.1%
76500 1
 
< 0.1%
76542 1
 
< 0.1%
ValueCountFrequency (%)
1084450 18
 
0.2%
1076285 1
 
< 0.1%
1075921 1
 
< 0.1%
1074149 1
 
< 0.1%
1073999 1
 
< 0.1%
1024059 143
1.4%
1023521 232
2.3%
1023328 1
 
< 0.1%
1022272 1
 
< 0.1%
1022182 81
 
0.8%

작성일자
Date

Distinct562
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-01-10 00:00:00
Maximum2023-07-06 00:00:00
2023-12-12T18:07:52.909198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:53.104222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

평가원점수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct54
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.508359
Minimum0
Maximum100
Zeros8281
Zeros (%)82.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:07:53.292415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation34.649598
Coefficient of variation (CV)2.3882506
Kurtosis2.1952177
Mean14.508359
Median Absolute Deviation (MAD)0
Skewness2.0377537
Sum145083.59
Variance1200.5946
MonotonicityNot monotonic
2023-12-12T18:07:53.510235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8281
82.8%
100.0 1390
 
13.9%
10.0 70
 
0.7%
20.0 66
 
0.7%
7.61 52
 
0.5%
7.85 29
 
0.3%
3.33 23
 
0.2%
18.0 8
 
0.1%
50.0 6
 
0.1%
45.0 4
 
< 0.1%
Other values (44) 71
 
0.7%
ValueCountFrequency (%)
0.0 8281
82.8%
0.23 1
 
< 0.1%
2.14 2
 
< 0.1%
2.85 1
 
< 0.1%
3.09 4
 
< 0.1%
3.33 23
 
0.2%
6.66 1
 
< 0.1%
7.14 1
 
< 0.1%
7.38 3
 
< 0.1%
7.61 52
 
0.5%
ValueCountFrequency (%)
100.0 1390
13.9%
88.89 2
 
< 0.1%
77.78 3
 
< 0.1%
75.0 3
 
< 0.1%
66.67 1
 
< 0.1%
60.0 3
 
< 0.1%
57.0 3
 
< 0.1%
55.56 3
 
< 0.1%
54.0 2
 
< 0.1%
51.0 2
 
< 0.1%

Interactions

2023-12-12T18:07:48.810349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:43.772563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:44.620542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:45.641914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.441304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.182921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.987888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:48.912048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:43.878058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:44.755340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:45.751796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.570200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.296570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:48.099989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:49.006736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:43.977106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:44.881652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:45.883116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.665301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.421750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:48.244927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:49.121240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:44.085514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:45.072854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:45.987557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.771800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.523588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:48.362189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:49.237067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:44.209709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:45.260911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.113658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.875791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.623947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:48.473853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:49.340574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:44.322938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:45.391041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.246887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.978849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.730119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:48.578189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:49.438149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:44.472404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:45.541052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:46.346142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.081889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:47.853423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:48.702601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:07:53.645779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수강번호평가항목아이디평가항목코드평가항목명평가항목반영율평가총점작성자번호평가원점수
수강번호1.0000.2760.1790.5410.4570.3520.5970.201
평가항목아이디0.2761.0000.9941.0000.6860.4690.4360.435
평가항목코드0.1790.9941.0000.9940.8750.6150.3260.426
평가항목명0.5411.0000.9941.0000.8900.6900.5210.543
평가항목반영율0.4570.6860.8750.8901.0000.8480.3970.623
평가총점0.3520.4690.6150.6900.8481.0000.3420.884
작성자번호0.5970.4360.3260.5210.3970.3421.0000.283
평가원점수0.2010.4350.4260.5430.6230.8840.2831.000
2023-12-12T18:07:53.784161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수강번호평가항목아이디평가항목코드평가항목반영율평가총점작성자번호평가원점수평가항목명
수강번호1.000-0.088-0.060-0.062-0.027-0.1940.1440.275
평가항목아이디-0.0881.0000.763-0.231-0.1900.062-0.0550.999
평가항목코드-0.0600.7631.000-0.319-0.3540.070-0.2830.999
평가항목반영율-0.062-0.231-0.3191.0000.517-0.0720.3030.562
평가총점-0.027-0.190-0.3540.5171.000-0.0890.6050.274
작성자번호-0.1940.0620.070-0.072-0.0891.000-0.0880.249
평가원점수0.144-0.055-0.2830.3030.605-0.0881.0000.215
평가항목명0.2750.9990.9990.5620.2740.2490.2151.000

Missing values

2023-12-12T18:07:49.562774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:07:49.721586image/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

수강번호평가항목아이디과정차수아이디평가항목코드평가항목명평가항목반영율평가총점작성자번호작성일자평가원점수
5026139891465NL00000057114584499사이버선행1010.03647212020-11-070.0
34107220411622NL0000035639000015출석100100.0778192023-06-16100.0
3362107994822NL0000005803459255출석1000.01557222020-09-080.0
32130214422619NL0000005711458792과제100.03088792023-04-200.0
8346143297164NL00000057114585199분임활동300.03700872021-02-090.0
28284200283622NL0000005711458755출석103.33739452022-12-193.33
4813139891319NL0000005711458442과제5044.03647212020-11-070.0
17920180361968NL00000057114586399디자인씽킹 해결과제300.01654922022-01-100.0
10272145822267NL00000057114585499근태100.03700872021-04-130.0
24086194214392NL00000057114587199이러닝100.01161292022-08-170.0
수강번호평가항목아이디과정차수아이디평가항목코드평가항목명평가항목반영율평가총점작성자번호작성일자평가원점수
725106772322NL0000014395000015출석100100.03647362020-06-020.0
16381174784722NL0000005723458845출석100100.03725932021-11-11100.0
16811178628367NL00000057114586299근태100.03700872021-11-280.0
128891716687124NL0000018897000061학습진도100100.0730982021-08-13100.0
12675151290822NL0000014163000055출석1000.03685832021-07-120.0
28408204254222NL0000005711458765출석103.7110235212023-01-060.0
137341724219124NL0000018897000091학습진도1000.07468572021-09-020.0
29931204618119NL0000005711458772과제100.01403582023-02-020.0
8444143310666NL00000057114585199행정실무300.03700872021-02-090.0
20751183034966NL00000057114586799행정실무400.05865922022-04-030.0