Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells61680
Missing cells (%)38.6%
Duplicate rows3183
Duplicate rows (%)31.8%
Total size in memory1.4 MiB
Average record size in memory145.0 B

Variable types

Categorical6
Text1
Boolean3
Numeric6

Dataset

Descriptionㅇ 대학정보공시 공시항목인 8-차-2.등록금 납부 제도 현황임 - 학교별 등록금 납부 제도의 실시 현황과 이용 현황(금액, 인원)을 조사한 항목
Author한국장학재단
URLhttps://www.data.go.kr/data/15073565/fileData.do

Alerts

조사년도 has constant value ""Constant
적용년도 has constant value ""Constant
Dataset has 3183 (31.8%) duplicate rowsDuplicates
납부방법명 is highly overall correlated with 학교부담카드수수료율 and 4 other fieldsHigh correlation
금년도계획 is highly overall correlated with 이용학생수 and 5 other fieldsHigh correlation
실시여부 is highly overall correlated with 이용학생수 and 5 other fieldsHigh correlation
납부구분 is highly overall correlated with 학교부담카드수수료율 and 1 other fieldsHigh correlation
추가여부 is highly overall correlated with 분납횟수 and 3 other fieldsHigh correlation
최초시행년도 is highly overall correlated with 이용학생수 and 3 other fieldsHigh correlation
이용학생수 is highly overall correlated with 최초시행년도 and 4 other fieldsHigh correlation
이용금액 is highly overall correlated with 최초시행년도 and 4 other fieldsHigh correlation
분납횟수 is highly overall correlated with 최초시행년도 and 5 other fieldsHigh correlation
분납개월수 is highly overall correlated with 최초시행년도 and 5 other fieldsHigh correlation
학교부담카드수수료율 is highly overall correlated with 차수 and 3 other fieldsHigh correlation
차수 is highly overall correlated with 이용학생수 and 4 other fieldsHigh correlation
본분교구분 is highly imbalanced (79.8%)Imbalance
추가여부 is highly imbalanced (65.3%)Imbalance
실시여부 has 4082 (40.8%) missing valuesMissing
최초시행년도 has 5738 (57.4%) missing valuesMissing
이용학생수 has 7029 (70.3%) missing valuesMissing
이용금액 has 7027 (70.3%) missing valuesMissing
분납횟수 has 9435 (94.3%) missing valuesMissing
분납개월수 has 9447 (94.5%) missing valuesMissing
학교부담카드수수료율 has 9695 (97.0%) missing valuesMissing
추가여부 has 5145 (51.4%) missing valuesMissing
금년도계획 has 4082 (40.8%) missing valuesMissing
분납횟수 is highly skewed (γ1 = 20.96251725)Skewed
이용학생수 has 427 (4.3%) zerosZeros
이용금액 has 424 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-12 13:43:07.109564
Analysis finished2023-12-12 13:43:13.518539
Duration6.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조사년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2013
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2013
3rd row2013
4th row2013
5th row2013

Common Values

ValueCountFrequency (%)
2013 10000
100.0%

Length

2023-12-12T22:43:13.599963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:13.706491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 10000
100.0%

차수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5874 
2
4126 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 5874
58.7%
2 4126
41.3%

Length

2023-12-12T22:43:13.834789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:13.955735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5874
58.7%
2 4126
41.3%

학교명
Text

Distinct450
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:43:14.208610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length7.0233
Min length4

Characters and Unicode

Total characters70233
Distinct characters212
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

Unique0 ?
Unique (%)0.0%

Sample

1st row주안대학원대학교
2nd row극동대학교
3rd row동신대학교
4th row국제사이버대학교
5th row창원문성대학
ValueCountFrequency (%)
한국폴리텍 225
 
2.0%
대학 208
 
1.9%
한국폴리텍대학 112
 
1.0%
경운대학교 74
 
0.7%
iv 71
 
0.6%
경인교육대학교 71
 
0.6%
한밭대학교 70
 
0.6%
강릉원주대학교 63
 
0.6%
경동대학교 63
 
0.6%
영산대학교 58
 
0.5%
Other values (450) 9969
90.8%
2023-12-12T22:43:14.705892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 11783
16.8%
대 11260
 
16.0%
교 9313
 
13.3%
한 1756
 
2.5%
원 1690
 
2.4%
국 1662
 
2.4%
984
 
1.4%
신 968
 
1.4%
경 955
 
1.4%
서 917
 
1.3%
Other values (202) 28945
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68773
97.9%
Space Separator 984
 
1.4%
Uppercase Letter 459
 
0.7%
Decimal Number 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 11783
17.1%
대 11260
16.4%
교 9313
 
13.5%
한 1756
 
2.6%
원 1690
 
2.5%
국 1662
 
2.4%
신 968
 
1.4%
경 955
 
1.4%
서 917
 
1.3%
산 770
 
1.1%
Other values (198) 27699
40.3%
Uppercase Letter
ValueCountFrequency (%)
I 309
67.3%
V 150
32.7%
Space Separator
ValueCountFrequency (%)
984
100.0%
Decimal Number
ValueCountFrequency (%)
1 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68773
97.9%
Common 1001
 
1.4%
Latin 459
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 11783
17.1%
대 11260
16.4%
교 9313
 
13.5%
한 1756
 
2.6%
원 1690
 
2.5%
국 1662
 
2.4%
신 968
 
1.4%
경 955
 
1.4%
서 917
 
1.3%
산 770
 
1.1%
Other values (198) 27699
40.3%
Common
ValueCountFrequency (%)
984
98.3%
1 17
 
1.7%
Latin
ValueCountFrequency (%)
I 309
67.3%
V 150
32.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68773
97.9%
ASCII 1460
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 11783
17.1%
대 11260
16.4%
교 9313
 
13.5%
한 1756
 
2.6%
원 1690
 
2.5%
국 1662
 
2.4%
신 968
 
1.4%
경 955
 
1.4%
서 917
 
1.3%
산 770
 
1.1%
Other values (198) 27699
40.3%
ASCII
ValueCountFrequency (%)
984
67.4%
I 309
 
21.2%
V 150
 
10.3%
1 17
 
1.2%

본분교구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본교
9394 
제2캠퍼스
 
361
캠퍼스
 
207
제3캠퍼스
 
38

Length

Max length5
Median length2
Mean length2.1404
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
본교 9394
93.9%
제2캠퍼스 361
 
3.6%
캠퍼스 207
 
2.1%
제3캠퍼스 38
 
0.4%

Length

2023-12-12T22:43:14.885624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:15.010320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본교 9394
93.9%
제2캠퍼스 361
 
3.6%
캠퍼스 207
 
2.1%
제3캠퍼스 38
 
0.4%

납부구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
납부방법
6074 
납부제도
3926 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row납부방법
2nd row납부제도
3rd row납부제도
4th row납부방법
5th row납부방법

Common Values

ValueCountFrequency (%)
납부방법 6074
60.7%
납부제도 3926
39.3%

Length

2023-12-12T22:43:15.133449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:15.237266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
납부방법 6074
60.7%
납부제도 3926
39.3%

납부방법명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일시납부
1975 
분할납부
1951 
계좌이체납부제
1911 
카드납부제
1884 
학교창구납부제
1856 
Other values (15)
423 

Length

Max length18
Median length17
Mean length5.3075
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row학교창구납부제
2nd row일시납부
3rd row일시납부
4th row계좌이체납부제
5th row기타3

Common Values

ValueCountFrequency (%)
일시납부 1975
19.8%
분할납부 1951
19.5%
계좌이체납부제 1911
19.1%
카드납부제 1884
18.8%
학교창구납부제 1856
18.6%
기타1 77
 
0.8%
기타2 62
 
0.6%
기타4 62
 
0.6%
기타5 58
 
0.6%
기타6 57
 
0.6%
Other values (10) 107
 
1.1%

Length

2023-12-12T22:43:15.359556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일시납부 1975
19.7%
분할납부 1951
19.4%
계좌이체납부제 1911
19.0%
카드납부제 1884
18.8%
학교창구납부제 1856
18.5%
기타1 77
 
0.8%
기타2 62
 
0.6%
기타4 62
 
0.6%
기타5 58
 
0.6%
기타6 57
 
0.6%
Other values (16) 143
 
1.4%

적용년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2013
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2013
3rd row2013
4th row2013
5th row2013

Common Values

ValueCountFrequency (%)
2013 10000
100.0%

Length

2023-12-12T22:43:15.515834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:15.622398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 10000
100.0%

실시여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing4082
Missing (%)40.8%
Memory size97.7 KiB
True
4235 
False
1683 
(Missing)
4082 
ValueCountFrequency (%)
True 4235
42.4%
False 1683
 
16.8%
(Missing) 4082
40.8%
2023-12-12T22:43:15.715858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최초시행년도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct77
Distinct (%)1.8%
Missing5738
Missing (%)57.4%
Infinite0
Infinite (%)0.0%
Mean1993.4901
Minimum1900
Maximum2013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:43:15.838636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1900
5-th percentile1952
Q11991
median1998
Q32005
95-th percentile2011
Maximum2013
Range113
Interquartile range (IQR)14

Descriptive statistics

Standard deviation17.966076
Coefficient of variation (CV)0.0090123726
Kurtosis4.4679648
Mean1993.4901
Median Absolute Deviation (MAD)7
Skewness-1.9362514
Sum8496255
Variance322.77988
MonotonicityNot monotonic
2023-12-12T22:43:16.012712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1998 278
 
2.8%
2003 257
 
2.6%
2005 194
 
1.9%
1997 191
 
1.9%
2011 184
 
1.8%
2002 166
 
1.7%
1999 160
 
1.6%
2004 148
 
1.5%
2009 141
 
1.4%
2000 141
 
1.4%
Other values (67) 2402
24.0%
(Missing) 5738
57.4%
ValueCountFrequency (%)
1900 7
0.1%
1905 3
 
< 0.1%
1906 10
0.1%
1914 12
0.1%
1918 3
 
< 0.1%
1919 4
 
< 0.1%
1937 5
 
0.1%
1938 2
 
< 0.1%
1939 14
0.1%
1940 14
0.1%
ValueCountFrequency (%)
2013 35
 
0.4%
2012 109
1.1%
2011 184
1.8%
2010 130
1.3%
2009 141
1.4%
2008 112
1.1%
2007 99
1.0%
2006 101
1.0%
2005 194
1.9%
2004 148
1.5%

이용학생수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct982
Distinct (%)33.1%
Missing7029
Missing (%)70.3%
Infinite0
Infinite (%)0.0%
Mean2779.7816
Minimum0
Maximum157353
Zeros427
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:43:16.190841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123
median317
Q33091
95-th percentile12802
Maximum157353
Range157353
Interquartile range (IQR)3068

Descriptive statistics

Standard deviation6857.4376
Coefficient of variation (CV)2.466898
Kurtosis199.50269
Mean2779.7816
Median Absolute Deviation (MAD)317
Skewness10.71215
Sum8258731
Variance47024450
MonotonicityNot monotonic
2023-12-12T22:43:16.346977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 427
 
4.3%
8 27
 
0.3%
2 22
 
0.2%
1 19
 
0.2%
7 19
 
0.2%
4 18
 
0.2%
3 18
 
0.2%
97 17
 
0.2%
15 16
 
0.2%
11 16
 
0.2%
Other values (972) 2372
 
23.7%
(Missing) 7029
70.3%
ValueCountFrequency (%)
0 427
4.3%
1 19
 
0.2%
2 22
 
0.2%
3 18
 
0.2%
4 18
 
0.2%
5 14
 
0.1%
6 14
 
0.1%
7 19
 
0.2%
8 27
 
0.3%
9 10
 
0.1%
ValueCountFrequency (%)
157353 2
< 0.1%
94412 2
< 0.1%
62941 2
< 0.1%
30028 1
< 0.1%
29003 1
< 0.1%
28702 2
< 0.1%
28352 1
< 0.1%
28175 2
< 0.1%
28134 1
< 0.1%
27978 1
< 0.1%

이용금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct1423
Distinct (%)47.9%
Missing7027
Missing (%)70.3%
Infinite0
Infinite (%)0.0%
Mean74545160
Minimum0
Maximum8.4692507 × 109
Zeros424
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:43:16.497036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q145234
median771271
Q38469251
95-th percentile52538556
Maximum8.4692507 × 109
Range8.4692507 × 109
Interquartile range (IQR)8424017

Descriptive statistics

Standard deviation5.9305642 × 108
Coefficient of variation (CV)7.9556663
Kurtosis122.43761
Mean74545160
Median Absolute Deviation (MAD)771271
Skewness10.688045
Sum2.2162276 × 1011
Variance3.5171591 × 1017
MonotonicityNot monotonic
2023-12-12T22:43:16.635270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 424
 
4.2%
6886 7
 
0.1%
12280214 6
 
0.1%
80034 6
 
0.1%
40000 6
 
0.1%
722004 5
 
0.1%
3160181 5
 
0.1%
101809 5
 
0.1%
7783761 5
 
0.1%
46000 5
 
0.1%
Other values (1413) 2499
 
25.0%
(Missing) 7027
70.3%
ValueCountFrequency (%)
0 424
4.2%
900 2
 
< 0.1%
1000 1
 
< 0.1%
1248 4
 
< 0.1%
1260 2
 
< 0.1%
1339 3
 
< 0.1%
1558 3
 
< 0.1%
1635 2
 
< 0.1%
1894 1
 
< 0.1%
2100 1
 
< 0.1%
ValueCountFrequency (%)
8469250710 1
< 0.1%
8200186810 1
< 0.1%
7988168930 2
< 0.1%
7622007240 2
< 0.1%
7422775290 2
< 0.1%
7311152820 2
< 0.1%
6218125000 1
< 0.1%
6217654080 1
< 0.1%
6205585000 2
< 0.1%
6089809560 2
< 0.1%

분납횟수
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct8
Distinct (%)1.4%
Missing9435
Missing (%)94.3%
Infinite0
Infinite (%)0.0%
Mean2.8654867
Minimum0
Maximum99
Zeros49
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:43:16.758705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile4
Maximum99
Range99
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.223746
Coefficient of variation (CV)1.4740065
Kurtosis477.92436
Mean2.8654867
Median Absolute Deviation (MAD)1
Skewness20.962517
Sum1619
Variance17.84003
MonotonicityNot monotonic
2023-12-12T22:43:16.891912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3 227
 
2.3%
2 167
 
1.7%
4 92
 
0.9%
0 49
 
0.5%
5 17
 
0.2%
6 8
 
0.1%
1 4
 
< 0.1%
99 1
 
< 0.1%
(Missing) 9435
94.3%
ValueCountFrequency (%)
0 49
 
0.5%
1 4
 
< 0.1%
2 167
1.7%
3 227
2.3%
4 92
0.9%
5 17
 
0.2%
6 8
 
0.1%
99 1
 
< 0.1%
ValueCountFrequency (%)
99 1
 
< 0.1%
6 8
 
0.1%
5 17
 
0.2%
4 92
0.9%
3 227
2.3%
2 167
1.7%
1 4
 
< 0.1%
0 49
 
0.5%

분납개월수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)1.4%
Missing9447
Missing (%)94.5%
Infinite0
Infinite (%)0.0%
Mean2.7341772
Minimum0
Maximum8
Zeros50
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:43:17.015332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2895371
Coefficient of variation (CV)0.47163625
Kurtosis0.71528676
Mean2.7341772
Median Absolute Deviation (MAD)1
Skewness-0.18703945
Sum1512
Variance1.6629059
MonotonicityNot monotonic
2023-12-12T22:43:17.136836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3 216
 
2.2%
2 142
 
1.4%
4 92
 
0.9%
0 50
 
0.5%
5 28
 
0.3%
1 16
 
0.2%
6 8
 
0.1%
8 1
 
< 0.1%
(Missing) 9447
94.5%
ValueCountFrequency (%)
0 50
 
0.5%
1 16
 
0.2%
2 142
1.4%
3 216
2.2%
4 92
0.9%
5 28
 
0.3%
6 8
 
0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 8
 
0.1%
5 28
 
0.3%
4 92
0.9%
3 216
2.2%
2 142
1.4%
1 16
 
0.2%
0 50
 
0.5%

학교부담카드수수료율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)8.5%
Missing9695
Missing (%)97.0%
Infinite0
Infinite (%)0.0%
Mean6.2534426
Minimum0
Maximum664
Zeros66
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:43:17.280758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.4
median1.5
Q31.9
95-th percentile2.5
Maximum664
Range664
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation54.979171
Coefficient of variation (CV)8.7918246
Kurtosis135.19463
Mean6.2534426
Median Absolute Deviation (MAD)0.6
Skewness11.533253
Sum1907.3
Variance3022.7092
MonotonicityNot monotonic
2023-12-12T22:43:17.402648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 66
 
0.7%
1.5 66
 
0.7%
1.9 26
 
0.3%
1.0 17
 
0.2%
0.8 14
 
0.1%
1.7 13
 
0.1%
0.5 10
 
0.1%
0.4 10
 
0.1%
1.6 10
 
0.1%
2.3 10
 
0.1%
Other values (16) 63
 
0.6%
(Missing) 9695
97.0%
ValueCountFrequency (%)
0.0 66
0.7%
0.2 6
 
0.1%
0.4 10
 
0.1%
0.5 10
 
0.1%
0.7 4
 
< 0.1%
0.8 14
 
0.1%
1.0 17
 
0.2%
1.1 2
 
< 0.1%
1.3 6
 
0.1%
1.4 1
 
< 0.1%
ValueCountFrequency (%)
664.0 2
 
< 0.1%
220.0 1
 
< 0.1%
2.8 4
 
< 0.1%
2.7 1
 
< 0.1%
2.6 6
0.1%
2.5 9
0.1%
2.4 7
0.1%
2.3 10
0.1%
2.2 2
 
< 0.1%
2.1 4
 
< 0.1%

추가여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing5145
Missing (%)51.4%
Memory size97.7 KiB
False
4539 
True
 
316
(Missing)
5145 
ValueCountFrequency (%)
False 4539
45.4%
True 316
 
3.2%
(Missing) 5145
51.4%
2023-12-12T22:43:17.876438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

금년도계획
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing4082
Missing (%)40.8%
Memory size97.7 KiB
True
4200 
False
1718 
(Missing)
4082 
ValueCountFrequency (%)
True 4200
42.0%
False 1718
17.2%
(Missing) 4082
40.8%
2023-12-12T22:43:17.979818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T22:43:12.093044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:08.448947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.134540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.801111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:10.419763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:11.308185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:12.191238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:08.556903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.230908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.903220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:10.821193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:11.430087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:12.300520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:08.655612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.354962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:10.020465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:10.900275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:11.616859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:12.415083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:08.760828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.470654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:10.103254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:10.999053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:11.737390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:12.516549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:08.880037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.574267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:10.217349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:11.085946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:11.850454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:12.637280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.027175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:09.709526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:10.315715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:11.200330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:11.987505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:43:18.069453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차수본분교구분납부구분납부방법명실시여부최초시행년도이용학생수이용금액분납횟수분납개월수학교부담카드수수료율추가여부금년도계획
차수1.0000.0130.0140.1480.0000.030NaNNaNNaNNaNNaN0.0660.000
본분교구분0.0131.0000.0000.0970.0000.1650.0000.0650.0000.2540.0000.0820.026
납부구분0.0140.0001.0001.0000.5740.3090.0260.0280.0000.377NaN0.3210.579
납부방법명0.1480.0971.0001.0000.7950.4450.1400.3190.0000.377NaN1.0000.806
실시여부0.0000.0000.5740.7951.0000.082NaNNaNNaNNaNNaN0.4100.998
최초시행년도0.0300.1650.3090.4450.0821.000NaNNaNNaNNaNNaN0.0000.080
이용학생수NaN0.0000.0260.140NaNNaN1.0000.000NaNNaNNaN0.032NaN
이용금액NaN0.0650.0280.319NaNNaN0.0001.0000.0000.3920.0000.000NaN
분납횟수NaN0.0000.0000.000NaNNaNNaN0.0001.0000.000NaNNaNNaN
분납개월수NaN0.2540.3770.377NaNNaNNaN0.3920.0001.000NaNNaNNaN
학교부담카드수수료율NaN0.000NaNNaNNaNNaNNaN0.000NaNNaN1.000NaNNaN
추가여부0.0660.0820.3211.0000.4100.0000.0320.000NaNNaNNaN1.0000.406
금년도계획0.0000.0260.5790.8060.9980.080NaNNaNNaNNaNNaN0.4061.000
2023-12-12T22:43:18.246088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부방법명금년도계획차수실시여부납부구분추가여부본분교구분
납부방법명1.0000.6620.1170.6510.9990.9980.046
금년도계획0.6621.0000.0000.9560.3930.2660.017
차수0.1170.0001.0000.0000.0090.0420.009
실시여부0.6510.9560.0001.0000.3890.2690.000
납부구분0.9990.3930.0090.3891.0000.2080.000
추가여부0.9980.2660.0420.2690.2081.0000.054
본분교구분0.0460.0170.0090.0000.0000.0541.000
2023-12-12T22:43:18.378244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초시행년도이용학생수이용금액분납횟수분납개월수학교부담카드수수료율차수본분교구분납부구분납부방법명실시여부추가여부금년도계획
최초시행년도1.000-0.509-0.5170.5660.671NaN0.0300.1710.3070.2090.0820.0000.097
이용학생수-0.5091.0000.9450.3810.3590.4821.0000.0000.0310.0711.0000.0391.000
이용금액-0.5170.9451.0000.3970.3750.4561.0000.0410.0280.1111.0000.0001.000
분납횟수0.5660.3810.3971.0000.763NaN1.0000.0000.0000.0001.0001.0001.000
분납개월수0.6710.3590.3750.7631.000NaN1.0000.1150.2820.2821.0001.0001.000
학교부담카드수수료율NaN0.4820.456NaNNaN1.0001.0000.0001.0001.0000.0001.0000.000
차수0.0301.0001.0001.0001.0001.0001.0000.0090.0090.1170.0000.0420.000
본분교구분0.1710.0000.0410.0000.1150.0000.0091.0000.0000.0460.0000.0540.017
납부구분0.3070.0310.0280.0000.2821.0000.0090.0001.0000.9990.3890.2080.393
납부방법명0.2090.0710.1110.0000.2821.0000.1170.0460.9991.0000.6510.9980.662
실시여부0.0821.0001.0001.0001.0000.0000.0000.0000.3890.6511.0000.2690.956
추가여부0.0000.0390.0001.0001.0001.0000.0420.0540.2080.9980.2691.0000.266
금년도계획0.0971.0001.0001.0001.0000.0000.0000.0170.3930.6620.9560.2661.000

Missing values

2023-12-12T22:43:12.816328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:43:13.127866image/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.
2023-12-12T22:43:13.362294image/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

조사년도차수학교명본분교구분납부구분납부방법명적용년도실시여부최초시행년도이용학생수이용금액분납횟수분납개월수학교부담카드수수료율추가여부금년도계획
356520131주안대학원대학교본교납부방법학교창구납부제2013N<NA><NA><NA><NA><NA><NA>NN
153520131극동대학교본교납부제도일시납부2013Y1998<NA><NA><NA><NA><NA><NA>Y
546920131동신대학교본교납부제도일시납부2013Y1987<NA><NA><NA><NA><NA><NA>Y
21820131국제사이버대학교본교납부방법계좌이체납부제2013Y2003<NA><NA><NA><NA><NA><NA>Y
727720131창원문성대학본교납부방법기타32013N<NA><NA><NA><NA><NA><NA><NA>N
789820131한중대학교본교납부방법학교창구납부제2013N<NA><NA><NA><NA><NA><NA><NA>N
783120131한국상담대학원대학교본교납부방법계좌이체납부제2013Y2010<NA><NA><NA><NA><NA><NA>Y
1406220132제주산업정보대학본교납부방법카드납부제2013<NA><NA>36387<NA><NA>1.5N<NA>
1205820132제주한라대학교본교납부방법학교창구납부제2013<NA><NA><NA><NA><NA><NA><NA>N<NA>
616420131우송정보대학본교납부방법학교창구납부제2013Y1963<NA><NA><NA><NA><NA><NA>Y
조사년도차수학교명본분교구분납부구분납부방법명적용년도실시여부최초시행년도이용학생수이용금액분납횟수분납개월수학교부담카드수수료율추가여부금년도계획
959720132경남도립남해대학본교납부제도분할납부2013<NA><NA><NA><NA><NA><NA><NA>N<NA>
1078120132한국폴리텍대학 서울정수캠퍼스본교납부방법학교창구납부제2013<NA><NA><NA><NA><NA><NA><NA>N<NA>
101120131한국복지사이버대학본교납부방법카드납부제2013Y2011<NA><NA><NA><NA><NA><NA>Y
359020131한국폴리텍 I 대학 성남캠퍼스본교납부방법계좌이체납부제2013Y2008<NA><NA><NA><NA><NA>NY
362220132한경대학교본교납부방법학교창구납부제2013<NA><NA><NA><NA><NA><NA><NA>N<NA>
831520131경운대학교본교납부제도분할납부2013Y1998<NA><NA><NA><NA><NA><NA>Y
112120131강남대학교본교납부제도분할납부2013Y1990<NA><NA><NA><NA><NA><NA>Y
1428120132안동과학대학교본교납부방법학교창구납부제2013<NA><NA><NA><NA><NA><NA><NA>N<NA>
1412720132중앙대학교 서울캠퍼스본교납부방법계좌이체납부제2013<NA><NA>2797896822451<NA><NA><NA>N<NA>
158520131고구려대학교본교납부방법카드납부제2013Y2011<NA><NA><NA><NA><NA><NA>Y

Duplicate rows

Most frequently occurring

조사년도차수학교명본분교구분납부구분납부방법명적용년도실시여부최초시행년도이용학생수이용금액분납횟수분납개월수학교부담카드수수료율추가여부금년도계획# duplicates
174720131한밭대학교본교납부제도분할납부2013Y2002<NA><NA><NA><NA><NA><NA>Y9
17620131경운대학교본교납부방법카드납부제2013Y2003<NA><NA><NA><NA><NA><NA>N7
78620131서울과학기술대학교본교납부방법계좌이체납부제2013Y2005<NA><NA><NA><NA><NA><NA>Y7
78820131서울과학기술대학교본교납부제도분할납부2013Y1999<NA><NA><NA><NA><NA><NA>Y7
143820131초당대학교본교납부방법카드납부제2013Y2012<NA><NA><NA><NA><NA><NA>Y7
151420131한경대학교본교납부방법학교창구납부제2013N<NA><NA><NA><NA><NA><NA><NA>N7
151520131한경대학교본교납부제도분할납부2013Y1995<NA><NA><NA><NA><NA><NA>Y7
174820131한밭대학교본교납부제도일시납부2013Y1979<NA><NA><NA><NA><NA><NA>Y7
17820131경운대학교본교납부제도분할납부2013Y1998<NA><NA><NA><NA><NA><NA>Y6
143720131초당대학교본교납부방법계좌이체납부제2013Y1994<NA><NA><NA><NA><NA><NA>Y6