Overview

Dataset statistics

Number of variables9
Number of observations301
Missing cells18
Missing cells (%)0.7%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory21.3 KiB
Average record size in memory72.4 B

Variable types

Text4
Categorical4
Unsupported1

Dataset

Description철도관련대학의 교수진 정보를 제공합니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15067581/fileData.do

Alerts

Dataset has 1 (0.3%) duplicate rowsDuplicates
Unnamed: 4 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 1 is highly overall correlated with Unnamed: 2 and 2 other fieldsHigh correlation
Unnamed: 2 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 5 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 3 has 4 (1.3%) missing valuesMissing
Unnamed: 6 has 4 (1.3%) missing valuesMissing
Unnamed: 7 has 4 (1.3%) missing valuesMissing
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 17:08:17.820222
Analysis finished2023-12-12 17:08:18.884214
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교수진정보 목록
Text

Distinct298
Distinct (%)100.0%
Missing3
Missing (%)1.0%
Memory size2.5 KiB
2023-12-13T02:08:19.315953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length3
Mean length2.8959732
Min length1

Characters and Unicode

Total characters863
Distinct characters33
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)100.0%

Sample

1st row번호
2nd row278
3rd row279
4th row280
5th row281
ValueCountFrequency (%)
293 1
 
0.3%
197 1
 
0.3%
205 1
 
0.3%
194 1
 
0.3%
190 1
 
0.3%
189 1
 
0.3%
188 1
 
0.3%
186 1
 
0.3%
185 1
 
0.3%
184 1
 
0.3%
Other values (293) 293
96.7%
2023-12-13T02:08:20.016865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 152
17.6%
1 152
17.6%
3 117
13.6%
5 61
7.1%
9 60
 
7.0%
4 59
 
6.8%
7 58
 
6.7%
0 57
 
6.6%
6 55
 
6.4%
8 54
 
6.3%
Other values (23) 38
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 825
95.6%
Lowercase Letter 21
 
2.4%
Uppercase Letter 8
 
0.9%
Space Separator 5
 
0.6%
Other Letter 2
 
0.2%
Other Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3
14.3%
g 2
9.5%
l 2
9.5%
t 2
9.5%
h 2
9.5%
r 2
9.5%
i 2
9.5%
y 1
 
4.8%
p 1
 
4.8%
o 1
 
4.8%
Other values (3) 3
14.3%
Decimal Number
ValueCountFrequency (%)
2 152
18.4%
1 152
18.4%
3 117
14.2%
5 61
7.4%
9 60
 
7.3%
4 59
 
7.2%
7 58
 
7.0%
0 57
 
6.9%
6 55
 
6.7%
8 54
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
R 3
37.5%
C 2
25.0%
K 1
 
12.5%
I 1
 
12.5%
A 1
 
12.5%
Other Letter
ValueCountFrequency (%)
호 1
50.0%
번 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Symbol
ValueCountFrequency (%)
ⓒ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 832
96.4%
Latin 29
 
3.4%
Hangul 2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3
 
10.3%
R 3
 
10.3%
g 2
 
6.9%
l 2
 
6.9%
t 2
 
6.9%
h 2
 
6.9%
r 2
 
6.9%
i 2
 
6.9%
C 2
 
6.9%
y 1
 
3.4%
Other values (8) 8
27.6%
Common
ValueCountFrequency (%)
2 152
18.3%
1 152
18.3%
3 117
14.1%
5 61
7.3%
9 60
 
7.2%
4 59
 
7.1%
7 58
 
7.0%
0 57
 
6.9%
6 55
 
6.6%
8 54
 
6.5%
Other values (3) 7
 
0.8%
Hangul
ValueCountFrequency (%)
호 1
50.0%
번 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 860
99.7%
Hangul 2
 
0.2%
Enclosed Alphanum 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 152
17.7%
1 152
17.7%
3 117
13.6%
5 61
7.1%
9 60
 
7.0%
4 59
 
6.9%
7 58
 
6.7%
0 57
 
6.6%
6 55
 
6.4%
8 54
 
6.3%
Other values (20) 35
 
4.1%
Enclosed Alphanum
ValueCountFrequency (%)
ⓒ 1
100.0%
Hangul
ValueCountFrequency (%)
호 1
50.0%
번 1
50.0%

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
우송대학교
71 
우송정보대학교
55 
한국교통대학교
35 
대원대학교
34 
동양대학교
26 
Other values (10)
80 

Length

Max length8
Median length5
Mean length5.8870432
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row대학이름
3rd row대원대학교
4th row대원대학교
5th row대원대학교

Common Values

ValueCountFrequency (%)
우송대학교 71
23.6%
우송정보대학교 55
18.3%
한국교통대학교 35
11.6%
대원대학교 34
11.3%
동양대학교 26
 
8.6%
경북전문대학교 24
 
8.0%
송원대학교 22
 
7.3%
경북보건대학교 7
 
2.3%
순천제일대학교 6
 
2.0%
가톨릭상지대학교 6
 
2.0%
Other values (5) 15
 
5.0%

Length

2023-12-13T02:08:20.242072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
우송대학교 71
23.6%
우송정보대학교 55
18.3%
한국교통대학교 35
11.6%
대원대학교 34
11.3%
동양대학교 26
 
8.6%
경북전문대학교 24
 
8.0%
송원대학교 22
 
7.3%
경북보건대학교 7
 
2.3%
순천제일대학교 6
 
2.0%
가톨릭상지대학교 6
 
2.0%
Other values (5) 15
 
5.0%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
A050110010
71 
A050110011
55 
A050110012
35 
A050110013
34 
A050110006
26 
Other values (10)
80 

Length

Max length10
Median length10
Mean length9.89701
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row과코드
3rd rowA050110013
4th rowA050110013
5th rowA050110013

Common Values

ValueCountFrequency (%)
A050110010 71
23.6%
A050110011 55
18.3%
A050110012 35
11.6%
A050110013 34
11.3%
A050110006 26
 
8.6%
A050110002 24
 
8.0%
A050110008 22
 
7.3%
A050110005 7
 
2.3%
A050110009 6
 
2.0%
A050110001 6
 
2.0%
Other values (5) 15
 
5.0%

Length

2023-12-13T02:08:20.411223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a050110010 71
23.6%
a050110011 55
18.3%
a050110012 35
11.6%
a050110013 34
11.3%
a050110006 26
 
8.6%
a050110002 24
 
8.0%
a050110008 22
 
7.3%
a050110005 7
 
2.3%
a050110009 6
 
2.0%
a050110001 6
 
2.0%
Other values (5) 15
 
5.0%

Unnamed: 3
Text

MISSING 

Distinct240
Distinct (%)80.8%
Missing4
Missing (%)1.3%
Memory size2.5 KiB
2023-12-13T02:08:20.895402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length3
Mean length3.5050505
Min length2

Characters and Unicode

Total characters1041
Distinct characters171
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique212 ?
Unique (%)71.4%

Sample

1st row교수이름
2nd row김수연
3rd row전윤희
4th row유은정
5th row장지혜
ValueCountFrequency (%)
조준호 6
 
1.9%
권선상 5
 
1.6%
엄상용 5
 
1.6%
이정숙 4
 
1.3%
김만주 4
 
1.3%
곽정호 4
 
1.3%
김미라 4
 
1.3%
주용준 4
 
1.3%
이승희 4
 
1.3%
박두성 4
 
1.3%
Other values (240) 266
85.8%
2023-12-13T02:08:21.533976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 63
 
6.1%
이 45
 
4.3%
38
 
3.7%
정 34
 
3.3%
호 29
 
2.8%
박 27
 
2.6%
성 26
 
2.5%
상 22
 
2.1%
영 17
 
1.6%
재 17
 
1.6%
Other values (161) 723
69.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 864
83.0%
Lowercase Letter 113
 
10.9%
Space Separator 38
 
3.7%
Uppercase Letter 22
 
2.1%
Dash Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 63
 
7.3%
이 45
 
5.2%
정 34
 
3.9%
호 29
 
3.4%
박 27
 
3.1%
성 26
 
3.0%
상 22
 
2.5%
영 17
 
2.0%
재 17
 
2.0%
승 17
 
2.0%
Other values (127) 567
65.6%
Lowercase Letter
ValueCountFrequency (%)
a 12
10.6%
e 12
10.6%
r 12
10.6%
h 11
9.7%
n 10
8.8%
o 9
 
8.0%
s 6
 
5.3%
i 6
 
5.3%
d 6
 
5.3%
u 5
 
4.4%
Other values (10) 24
21.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
13.6%
A 3
13.6%
J 3
13.6%
S 3
13.6%
R 2
9.1%
C 2
9.1%
W 2
9.1%
F 2
9.1%
H 2
9.1%
Space Separator
ValueCountFrequency (%)
38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 864
83.0%
Latin 135
 
13.0%
Common 42
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 63
 
7.3%
이 45
 
5.2%
정 34
 
3.9%
호 29
 
3.4%
박 27
 
3.1%
성 26
 
3.0%
상 22
 
2.5%
영 17
 
2.0%
재 17
 
2.0%
승 17
 
2.0%
Other values (127) 567
65.6%
Latin
ValueCountFrequency (%)
a 12
 
8.9%
e 12
 
8.9%
r 12
 
8.9%
h 11
 
8.1%
n 10
 
7.4%
o 9
 
6.7%
s 6
 
4.4%
i 6
 
4.4%
d 6
 
4.4%
u 5
 
3.7%
Other values (19) 46
34.1%
Common
ValueCountFrequency (%)
38
90.5%
- 1
 
2.4%
( 1
 
2.4%
) 1
 
2.4%
. 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 864
83.0%
ASCII 177
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 63
 
7.3%
이 45
 
5.2%
정 34
 
3.9%
호 29
 
3.4%
박 27
 
3.1%
성 26
 
3.0%
상 22
 
2.5%
영 17
 
2.0%
재 17
 
2.0%
승 17
 
2.0%
Other values (127) 567
65.6%
ASCII
ValueCountFrequency (%)
38
21.5%
a 12
 
6.8%
e 12
 
6.8%
r 12
 
6.8%
h 11
 
6.2%
n 10
 
5.6%
o 9
 
5.1%
s 6
 
3.4%
i 6
 
3.4%
d 6
 
3.4%
Other values (24) 55
31.1%

Unnamed: 4
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
철도경영학과
 
20
철도건설과
 
19
철도교통학부(철도운수경영전공)
 
17
철도경영과
 
17
철도전기시스템학과
 
16
Other values (32)
212 

Length

Max length19
Median length16
Mean length9.7043189
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row과명
3rd row철도항공교통계열(철도운전경영전공)
4th row철도항공교통계열(철도운전경영전공)
5th row철도항공교통계열(철도운전경영전공)

Common Values

ValueCountFrequency (%)
철도경영학과 20
 
6.6%
철도건설과 19
 
6.3%
철도교통학부(철도운수경영전공) 17
 
5.6%
철도경영과 17
 
5.6%
철도전기시스템학과 16
 
5.3%
철도교통학부(기관사전공) 16
 
5.3%
철도교통학부(철도기계전공) 15
 
5.0%
철도건설시스템학부 14
 
4.7%
철도항공교통계열(철도운전경영전공) 14
 
4.7%
철도전기기관사과 11
 
3.7%
Other values (27) 142
47.2%

Length

2023-12-13T02:08:21.762513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철도경영학과 20
 
6.4%
철도건설과 19
 
6.1%
철도교통학부(철도운수경영전공 17
 
5.5%
철도경영과 17
 
5.5%
철도전기시스템학과 16
 
5.1%
철도교통학부(기관사전공 16
 
5.1%
철도교통학부(철도기계전공 15
 
4.8%
철도건설시스템학부 14
 
4.5%
철도항공교통계열(철도운전경영전공 14
 
4.5%
철도전기기관사과 11
 
3.5%
Other values (28) 152
48.9%

Unnamed: 5
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2019-02-18
200 
2020-02-10
96 
<NA>
 
4
등록일
 
1

Length

Max length10
Median length10
Mean length9.89701
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row등록일
3rd row2020-02-10
4th row2020-02-10
5th row2020-02-10

Common Values

ValueCountFrequency (%)
2019-02-18 200
66.4%
2020-02-10 96
31.9%
<NA> 4
 
1.3%
등록일 1
 
0.3%

Length

2023-12-13T02:08:21.961176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:08:22.091758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-02-18 200
66.4%
2020-02-10 96
31.9%
na 4
 
1.3%
등록일 1
 
0.3%

Unnamed: 6
Text

MISSING 

Distinct297
Distinct (%)100.0%
Missing4
Missing (%)1.3%
Memory size2.5 KiB
2023-12-13T02:08:22.551378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.7912458
Min length1

Characters and Unicode

Total characters829
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique297 ?
Unique (%)100.0%

Sample

1st row교수번호
2nd row278
3rd row279
4th row280
5th row281
ValueCountFrequency (%)
278 1
 
0.3%
189 1
 
0.3%
186 1
 
0.3%
185 1
 
0.3%
184 1
 
0.3%
183 1
 
0.3%
182 1
 
0.3%
181 1
 
0.3%
180 1
 
0.3%
179 1
 
0.3%
Other values (287) 287
96.6%
2023-12-13T02:08:23.165230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 152
18.3%
1 152
18.3%
3 117
14.1%
5 61
7.4%
9 60
 
7.2%
4 59
 
7.1%
7 58
 
7.0%
0 57
 
6.9%
6 55
 
6.6%
8 54
 
6.5%
Other values (4) 4
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 825
99.5%
Other Letter 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 152
18.4%
1 152
18.4%
3 117
14.2%
5 61
7.4%
9 60
 
7.3%
4 59
 
7.2%
7 58
 
7.0%
0 57
 
6.9%
6 55
 
6.7%
8 54
 
6.5%
Other Letter
ValueCountFrequency (%)
교 1
25.0%
수 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 825
99.5%
Hangul 4
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 152
18.4%
1 152
18.4%
3 117
14.2%
5 61
7.4%
9 60
 
7.3%
4 59
 
7.2%
7 58
 
7.0%
0 57
 
6.9%
6 55
 
6.7%
8 54
 
6.5%
Hangul
ValueCountFrequency (%)
교 1
25.0%
수 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 825
99.5%
Hangul 4
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 152
18.4%
1 152
18.4%
3 117
14.2%
5 61
7.4%
9 60
 
7.3%
4 59
 
7.2%
7 58
 
7.0%
0 57
 
6.9%
6 55
 
6.7%
8 54
 
6.5%
Hangul
ValueCountFrequency (%)
교 1
25.0%
수 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 7
Text

MISSING 

Distinct292
Distinct (%)98.3%
Missing4
Missing (%)1.3%
Memory size2.5 KiB
2023-12-13T02:08:23.615826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.989899
Min length4

Characters and Unicode

Total characters2076
Distinct characters17
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique287 ?
Unique (%)96.6%

Sample

1st row교수코드
2nd rowR-U-278
3rd rowR-U-279
4th rowR-U-280
5th rowR-U-281
ValueCountFrequency (%)
r-u-331 2
 
0.7%
r-u-333 2
 
0.7%
r-u-334 2
 
0.7%
r-u-335 2
 
0.7%
r-u-332 2
 
0.7%
r-u-179 1
 
0.3%
r-u-272 1
 
0.3%
r-u-175 1
 
0.3%
r-u-176 1
 
0.3%
r-u-177 1
 
0.3%
Other values (282) 282
94.9%
2023-12-13T02:08:24.179389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 592
28.5%
R 296
14.3%
U 296
14.3%
1 152
 
7.3%
2 152
 
7.3%
3 122
 
5.9%
0 119
 
5.7%
5 61
 
2.9%
4 60
 
2.9%
9 59
 
2.8%
Other values (7) 167
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 888
42.8%
Dash Punctuation 592
28.5%
Uppercase Letter 592
28.5%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 152
17.1%
2 152
17.1%
3 122
13.7%
0 119
13.4%
5 61
6.9%
4 60
 
6.8%
9 59
 
6.6%
7 58
 
6.5%
8 54
 
6.1%
6 51
 
5.7%
Other Letter
ValueCountFrequency (%)
교 1
25.0%
수 1
25.0%
코 1
25.0%
드 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
R 296
50.0%
U 296
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 592
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1480
71.3%
Latin 592
 
28.5%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
- 592
40.0%
1 152
 
10.3%
2 152
 
10.3%
3 122
 
8.2%
0 119
 
8.0%
5 61
 
4.1%
4 60
 
4.1%
9 59
 
4.0%
7 58
 
3.9%
8 54
 
3.6%
Hangul
ValueCountFrequency (%)
교 1
25.0%
수 1
25.0%
코 1
25.0%
드 1
25.0%
Latin
ValueCountFrequency (%)
R 296
50.0%
U 296
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2072
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 592
28.6%
R 296
14.3%
U 296
14.3%
1 152
 
7.3%
2 152
 
7.3%
3 122
 
5.9%
0 119
 
5.7%
5 61
 
2.9%
4 60
 
2.9%
9 59
 
2.8%
Other values (3) 163
 
7.9%
Hangul
ValueCountFrequency (%)
교 1
25.0%
수 1
25.0%
코 1
25.0%
드 1
25.0%

Unnamed: 8
Unsupported

REJECTED  UNSUPPORTED 

Missing3
Missing (%)1.0%
Memory size2.5 KiB

Correlations

2023-12-13T02:08:24.313140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 4Unnamed: 5
Unnamed: 11.0001.0000.9950.876
Unnamed: 21.0001.0000.9950.876
Unnamed: 40.9950.9951.0000.980
Unnamed: 50.8760.8760.9801.000
2023-12-13T02:08:24.416592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 1Unnamed: 5Unnamed: 2
Unnamed: 41.0000.9030.8100.903
Unnamed: 10.9031.0000.7521.000
Unnamed: 50.8100.7521.0000.752
Unnamed: 20.9031.0000.7521.000
2023-12-13T02:08:24.517492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 4Unnamed: 5
Unnamed: 11.0001.0000.9030.752
Unnamed: 21.0001.0000.9030.752
Unnamed: 40.9030.9031.0000.810
Unnamed: 50.7520.7520.8101.000

Missing values

2023-12-13T02:08:18.363129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:08:18.576963image/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.
2023-12-13T02:08:18.760955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

교수진정보 목록Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0<NA><NA><NA><NA><NA><NA><NA><NA>NaN
1번호대학이름과코드교수이름과명등록일교수번호교수코드대학코드
2278대원대학교A050110013김수연철도항공교통계열(철도운전경영전공)2020-02-10278R-U-278S01013003
3279대원대학교A050110013전윤희철도항공교통계열(철도운전경영전공)2020-02-10279R-U-279S01013003
4280대원대학교A050110013유은정철도항공교통계열(철도운전경영전공)2020-02-10280R-U-280S01013003
5281대원대학교A050110013장지혜철도항공교통계열(철도운전경영전공)2020-02-10281R-U-281S01013003
6282순천제일대학교A050110009안길순철도운수설비과2020-02-10282R-U-282S01009001
7283순천제일대학교A050110009윤정훈철도운수설비과2020-02-10283R-U-283S01009001
8284동양대학교A050110006민승곤철도운전제어학과2020-02-10284R-U-284S01006002
9285우송대학교A050110010박종흠물류시스템학과2020-02-10285R-U-285S01010002
교수진정보 목록Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
291357한국교통대학교A050110012송문석철도시스템 공학과2020-02-10357R-U-357S01012006
292358한국교통대학교A050110012안승호철도시스템 공학과2020-02-10358R-U-358S01012006
293359한국교통대학교A050110012김백철도시스템 공학과2020-02-10359R-U-331S01012006
294360한국교통대학교A050110012정광우철도시스템 공학과2020-02-10360R-U-332S01012006
295361한국교통대학교A050110012강주석철도시스템 공학과2020-02-10361R-U-333S01012006
296362한국교통대학교A050110012김철수철도시스템 공학과2020-02-10362R-U-334S01012006
297363한국교통대학교A050110012박찬배철도시스템 공학과2020-02-10363R-U-335S01012006
298<NA><NA><NA><NA><NA><NA><NA><NA>NaN
299<NA><NA><NA><NA><NA><NA><NA><NA>NaN
300Copyright ⓒ KRIC All Right Reserved.<NA><NA><NA><NA><NA><NA><NA>2022-05-24 09:46:55.853000

Duplicate rows

Most frequently occurring

교수진정보 목록Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA>3