Overview

Dataset statistics

Number of variables11
Number of observations39
Missing cells4
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory100.3 B

Variable types

Categorical1
Text1
Numeric9

Dataset

Description전북특별자치도 선호교육방법(학교 정규수업,학원 수강,방문학습지 등) 제공해당 데이터는 기관에서 더이상 생성할 수 없는 파일입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15051298/fileData.do

Alerts

학교 정규수업 is highly overall correlated with 개인 과외 and 4 other fieldsHigh correlation
개인 과외 is highly overall correlated with 학교 정규수업 and 4 other fieldsHigh correlation
그룹 과외 is highly overall correlated with 학교 정규수업 and 4 other fieldsHigh correlation
학원 수강 is highly overall correlated with 학교 정규수업 and 3 other fieldsHigh correlation
무료 방송강의 is highly overall correlated with 학교 정규수업 and 4 other fieldsHigh correlation
유료 인터넷 및 통신강좌 is highly overall correlated with 학교 정규수업 and 3 other fieldsHigh correlation
그룹 과외 has 1 (2.6%) missing valuesMissing
방문학습지 has 2 (5.1%) missing valuesMissing
유료 인터넷 및 통신강좌 has 1 (2.6%) missing valuesMissing
상세구분 has unique valuesUnique

Reproduction

Analysis started2024-03-15 01:13:28.414841
Analysis finished2024-03-15 01:13:50.406047
Duration21.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct9
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size440.0 B
학력
7 
연령
6 
취업상태
5 
결혼
5 
주택형태
5 
Other values (4)
11 

Length

Max length5
Median length2
Mean length2.9230769
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군
2nd row시군
3rd row성별
4th row성별
5th row연령

Common Values

ValueCountFrequency (%)
학력 7
17.9%
연령 6
15.4%
취업상태 5
12.8%
결혼 5
12.8%
주택형태 5
12.8%
세대구분 5
12.8%
시군 2
 
5.1%
성별 2
 
5.1%
조사구구분 2
 
5.1%

Length

2024-03-15T10:13:50.652422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:13:51.072077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학력 7
17.9%
연령 6
15.4%
취업상태 5
12.8%
결혼 5
12.8%
주택형태 5
12.8%
세대구분 5
12.8%
시군 2
 
5.1%
성별 2
 
5.1%
조사구구분 2
 
5.1%

상세구분
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size440.0 B
2024-03-15T10:13:52.143919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.025641
Min length2

Characters and Unicode

Total characters157
Distinct characters69
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row시부
2nd row군부
3rd row남자
4th row여자
5th row15~19세
ValueCountFrequency (%)
시부 1
 
2.4%
아파트 1
 
2.4%
배우자 1
 
2.4%
있음 1
 
2.4%
사별 1
 
2.4%
이혼 1
 
2.4%
별거 1
 
2.4%
가구주 1
 
2.4%
가구원 1
 
2.4%
기능/기타 1
 
2.4%
Other values (31) 31
75.6%
2024-03-15T10:13:53.452568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 10
 
6.4%
구 8
 
5.1%
가 8
 
5.1%
대 7
 
4.5%
학 6
 
3.8%
~ 5
 
3.2%
9 5
 
3.2%
0 5
 
3.2%
자 4
 
2.5%
1 4
 
2.5%
Other values (59) 95
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121
77.1%
Decimal Number 26
 
16.6%
Math Symbol 5
 
3.2%
Other Punctuation 3
 
1.9%
Space Separator 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 10
 
8.3%
구 8
 
6.6%
가 8
 
6.6%
대 7
 
5.8%
학 6
 
5.0%
자 4
 
3.3%
주 4
 
3.3%
교 4
 
3.3%
사 3
 
2.5%
비 3
 
2.5%
Other values (48) 64
52.9%
Decimal Number
ValueCountFrequency (%)
9 5
19.2%
0 5
19.2%
1 4
15.4%
3 3
11.5%
5 3
11.5%
2 3
11.5%
4 2
 
7.7%
6 1
 
3.8%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121
77.1%
Common 36
 
22.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 10
 
8.3%
구 8
 
6.6%
가 8
 
6.6%
대 7
 
5.8%
학 6
 
5.0%
자 4
 
3.3%
주 4
 
3.3%
교 4
 
3.3%
사 3
 
2.5%
비 3
 
2.5%
Other values (48) 64
52.9%
Common
ValueCountFrequency (%)
~ 5
13.9%
9 5
13.9%
0 5
13.9%
1 4
11.1%
/ 3
8.3%
3 3
8.3%
5 3
8.3%
2 3
8.3%
2
 
5.6%
4 2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121
77.1%
ASCII 36
 
22.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 10
 
8.3%
구 8
 
6.6%
가 8
 
6.6%
대 7
 
5.8%
학 6
 
5.0%
자 4
 
3.3%
주 4
 
3.3%
교 4
 
3.3%
사 3
 
2.5%
비 3
 
2.5%
Other values (48) 64
52.9%
ASCII
ValueCountFrequency (%)
~ 5
13.9%
9 5
13.9%
0 5
13.9%
1 4
11.1%
/ 3
8.3%
3 3
8.3%
5 3
8.3%
2 3
8.3%
2
 
5.6%
4 2
 
5.6%

학교 정규수업
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.825641
Minimum40.7
Maximum76.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:13:53.844834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40.7
5-th percentile44.82
Q151.5
median56.9
Q362
95-th percentile71.55
Maximum76.1
Range35.4
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation8.2635763
Coefficient of variation (CV)0.14541985
Kurtosis-0.1431825
Mean56.825641
Median Absolute Deviation (MAD)5.3
Skewness0.31529316
Sum2216.2
Variance68.286694
MonotonicityNot monotonic
2024-03-15T10:13:54.279959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
59.4 2
 
5.1%
56.9 1
 
2.6%
63.9 1
 
2.6%
45.7 1
 
2.6%
71.4 1
 
2.6%
63.0 1
 
2.6%
49.6 1
 
2.6%
61.5 1
 
2.6%
54.7 1
 
2.6%
62.9 1
 
2.6%
Other values (28) 28
71.8%
ValueCountFrequency (%)
40.7 1
2.6%
43.2 1
2.6%
45.0 1
2.6%
45.7 1
2.6%
47.3 1
2.6%
48.3 1
2.6%
48.7 1
2.6%
49.3 1
2.6%
49.6 1
2.6%
51.2 1
2.6%
ValueCountFrequency (%)
76.1 1
2.6%
72.9 1
2.6%
71.4 1
2.6%
71.0 1
2.6%
66.0 1
2.6%
63.9 1
2.6%
63.3 1
2.6%
63.0 1
2.6%
62.9 1
2.6%
62.2 1
2.6%

방과 후 학교 프로그램
Real number (ℝ)

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.879487
Minimum9.3
Maximum31.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:13:54.690985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.3
5-th percentile13.49
Q115.9
median17.7
Q319.4
95-th percentile22.18
Maximum31.3
Range22
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation3.5253353
Coefficient of variation (CV)0.19717206
Kurtosis5.0197176
Mean17.879487
Median Absolute Deviation (MAD)1.8
Skewness1.128402
Sum697.3
Variance12.427989
MonotonicityNot monotonic
2024-03-15T10:13:55.307995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
15.8 2
 
5.1%
16.5 2
 
5.1%
20.2 2
 
5.1%
18.9 2
 
5.1%
18.5 2
 
5.1%
17.4 1
 
2.6%
15.3 1
 
2.6%
14.1 1
 
2.6%
31.3 1
 
2.6%
18.1 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
9.3 1
2.6%
12.5 1
2.6%
13.6 1
2.6%
14.1 1
2.6%
14.6 1
2.6%
15.1 1
2.6%
15.3 1
2.6%
15.6 1
2.6%
15.8 2
5.1%
16.0 1
2.6%
ValueCountFrequency (%)
31.3 1
2.6%
23.8 1
2.6%
22.0 1
2.6%
21.7 1
2.6%
20.6 1
2.6%
20.3 1
2.6%
20.2 2
5.1%
19.6 1
2.6%
19.5 1
2.6%
19.3 1
2.6%

개인 과외
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3333333
Minimum0.9
Maximum11.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:13:55.539315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile1.39
Q12.75
median4.1
Q35.05
95-th percentile8.45
Maximum11.3
Range10.4
Interquartile range (IQR)2.3

Descriptive statistics

Standard deviation2.3184992
Coefficient of variation (CV)0.53503828
Kurtosis1.9513938
Mean4.3333333
Median Absolute Deviation (MAD)1
Skewness1.2593505
Sum169
Variance5.3754386
MonotonicityNot monotonic
2024-03-15T10:13:55.924262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
4.1 3
 
7.7%
3.7 2
 
5.1%
3.9 2
 
5.1%
7.3 2
 
5.1%
5.1 2
 
5.1%
4.2 2
 
5.1%
2.5 2
 
5.1%
3.1 2
 
5.1%
2.0 2
 
5.1%
6.2 1
 
2.6%
Other values (19) 19
48.7%
ValueCountFrequency (%)
0.9 1
2.6%
1.3 1
2.6%
1.4 1
2.6%
1.9 1
2.6%
2.0 2
5.1%
2.4 1
2.6%
2.5 2
5.1%
2.7 1
2.6%
2.8 1
2.6%
3.1 2
5.1%
ValueCountFrequency (%)
11.3 1
2.6%
10.7 1
2.6%
8.2 1
2.6%
7.3 2
5.1%
6.5 1
2.6%
6.4 1
2.6%
6.2 1
2.6%
5.1 2
5.1%
5.0 1
2.6%
4.8 1
2.6%

그룹 과외
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)57.9%
Missing1
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean1.6657895
Minimum0.3
Maximum3.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:13:56.297757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.385
Q11.125
median1.55
Q32.1
95-th percentile3.03
Maximum3.9
Range3.6
Interquartile range (IQR)0.975

Descriptive statistics

Standard deviation0.82798235
Coefficient of variation (CV)0.49705101
Kurtosis0.25190273
Mean1.6657895
Median Absolute Deviation (MAD)0.45
Skewness0.6100382
Sum63.3
Variance0.68555477
MonotonicityNot monotonic
2024-03-15T10:13:56.702533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1.7 5
12.8%
1.5 4
 
10.3%
1.2 4
 
10.3%
1.1 3
 
7.7%
2.1 2
 
5.1%
1.8 2
 
5.1%
0.3 2
 
5.1%
2.8 2
 
5.1%
3.0 1
 
2.6%
2.7 1
 
2.6%
Other values (12) 12
30.8%
ValueCountFrequency (%)
0.3 2
5.1%
0.4 1
 
2.6%
0.6 1
 
2.6%
0.8 1
 
2.6%
0.9 1
 
2.6%
1.0 1
 
2.6%
1.1 3
7.7%
1.2 4
10.3%
1.3 1
 
2.6%
1.5 4
10.3%
ValueCountFrequency (%)
3.9 1
2.6%
3.2 1
2.6%
3.0 1
2.6%
2.8 2
5.1%
2.7 1
2.6%
2.6 1
2.6%
2.5 1
2.6%
2.2 1
2.6%
2.1 2
5.1%
1.8 2
5.1%

학원 수강
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5769231
Minimum3.9
Maximum14.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:13:57.115304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.9
5-th percentile4.68
Q17.05
median9.5
Q312.55
95-th percentile13.63
Maximum14.1
Range10.2
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.0899209
Coefficient of variation (CV)0.32264235
Kurtosis-1.2436567
Mean9.5769231
Median Absolute Deviation (MAD)3
Skewness-0.12806114
Sum373.5
Variance9.5476113
MonotonicityNot monotonic
2024-03-15T10:13:57.546260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
13.4 2
 
5.1%
8.4 2
 
5.1%
8.0 2
 
5.1%
10.9 1
 
2.6%
13.1 1
 
2.6%
9.5 1
 
2.6%
5.8 1
 
2.6%
6.5 1
 
2.6%
6.1 1
 
2.6%
11.1 1
 
2.6%
Other values (26) 26
66.7%
ValueCountFrequency (%)
3.9 1
2.6%
4.5 1
2.6%
4.7 1
2.6%
5.3 1
2.6%
5.6 1
2.6%
5.8 1
2.6%
6.1 1
2.6%
6.4 1
2.6%
6.5 1
2.6%
6.9 1
2.6%
ValueCountFrequency (%)
14.1 1
2.6%
13.9 1
2.6%
13.6 1
2.6%
13.5 1
2.6%
13.4 2
5.1%
13.3 1
2.6%
13.1 1
2.6%
12.8 1
2.6%
12.6 1
2.6%
12.5 1
2.6%

방문학습지
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)40.5%
Missing2
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean0.9
Minimum0.1
Maximum4.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:13:57.944731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.5
median0.8
Q31.1
95-th percentile1.7
Maximum4.3
Range4.2
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.72915476
Coefficient of variation (CV)0.81017196
Kurtosis13.223281
Mean0.9
Median Absolute Deviation (MAD)0.3
Skewness3.1341555
Sum33.3
Variance0.53166667
MonotonicityNot monotonic
2024-03-15T10:13:58.314459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.8 6
15.4%
1.1 5
12.8%
0.7 5
12.8%
0.2 4
10.3%
0.9 3
7.7%
0.4 3
7.7%
0.5 2
 
5.1%
1.2 2
 
5.1%
2.5 1
 
2.6%
0.6 1
 
2.6%
Other values (5) 5
12.8%
(Missing) 2
 
5.1%
ValueCountFrequency (%)
0.1 1
 
2.6%
0.2 4
10.3%
0.4 3
7.7%
0.5 2
 
5.1%
0.6 1
 
2.6%
0.7 5
12.8%
0.8 6
15.4%
0.9 3
7.7%
1.0 1
 
2.6%
1.1 5
12.8%
ValueCountFrequency (%)
4.3 1
 
2.6%
2.5 1
 
2.6%
1.5 1
 
2.6%
1.4 1
 
2.6%
1.2 2
 
5.1%
1.1 5
12.8%
1.0 1
 
2.6%
0.9 3
7.7%
0.8 6
15.4%
0.7 5
12.8%

무료 방송강의
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1564103
Minimum1.8
Maximum14.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:13:58.686576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.8
5-th percentile2.7
Q14.7
median6.2
Q36.75
95-th percentile11.17
Maximum14.7
Range12.9
Interquartile range (IQR)2.05

Descriptive statistics

Standard deviation2.7066968
Coefficient of variation (CV)0.43965505
Kurtosis2.6099557
Mean6.1564103
Median Absolute Deviation (MAD)1.2
Skewness1.3097219
Sum240.1
Variance7.3262078
MonotonicityNot monotonic
2024-03-15T10:13:59.112362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
5.0 4
 
10.3%
6.6 3
 
7.7%
6.5 2
 
5.1%
5.7 2
 
5.1%
6.4 2
 
5.1%
2.7 2
 
5.1%
6.3 1
 
2.6%
3.0 1
 
2.6%
3.6 1
 
2.6%
7.4 1
 
2.6%
Other values (20) 20
51.3%
ValueCountFrequency (%)
1.8 1
2.6%
2.7 2
5.1%
3.0 1
2.6%
3.1 1
2.6%
3.5 1
2.6%
3.6 1
2.6%
3.8 1
2.6%
4.0 1
2.6%
4.6 1
2.6%
4.8 1
2.6%
ValueCountFrequency (%)
14.7 1
2.6%
13.6 1
2.6%
10.9 1
2.6%
10.2 1
2.6%
8.3 1
2.6%
8.1 1
2.6%
7.6 1
2.6%
7.4 1
2.6%
7.2 1
2.6%
6.8 1
2.6%

유료 인터넷 및 통신강좌
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)52.6%
Missing1
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean1.6763158
Minimum0.3
Maximum4.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:13:59.484542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.585
Q11.225
median1.5
Q31.775
95-th percentile3.33
Maximum4.1
Range3.8
Interquartile range (IQR)0.55

Descriptive statistics

Standard deviation0.84002388
Coefficient of variation (CV)0.50111314
Kurtosis1.0264442
Mean1.6763158
Median Absolute Deviation (MAD)0.3
Skewness1.001684
Sum63.7
Variance0.70564011
MonotonicityNot monotonic
2024-03-15T10:13:59.873344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1.5 6
15.4%
1.6 4
 
10.3%
1.0 3
 
7.7%
1.4 3
 
7.7%
1.7 3
 
7.7%
0.6 2
 
5.1%
2.7 2
 
5.1%
1.3 2
 
5.1%
2.5 2
 
5.1%
0.3 1
 
2.6%
Other values (10) 10
25.6%
ValueCountFrequency (%)
0.3 1
 
2.6%
0.5 1
 
2.6%
0.6 2
 
5.1%
0.8 1
 
2.6%
1.0 3
7.7%
1.1 1
 
2.6%
1.2 1
 
2.6%
1.3 2
 
5.1%
1.4 3
7.7%
1.5 6
15.4%
ValueCountFrequency (%)
4.1 1
 
2.6%
3.5 1
 
2.6%
3.3 1
 
2.6%
2.8 1
 
2.6%
2.7 2
5.1%
2.5 2
5.1%
2.4 1
 
2.6%
1.8 1
 
2.6%
1.7 3
7.7%
1.6 4
10.3%

기타
Real number (ℝ)

Distinct19
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1461538
Minimum0.3
Maximum2.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size479.0 B
2024-03-15T10:14:00.207423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.4
Q10.8
median1
Q31.4
95-th percentile2.71
Maximum2.9
Range2.6
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.6512523
Coefficient of variation (CV)0.5682067
Kurtosis1.6337968
Mean1.1461538
Median Absolute Deviation (MAD)0.3
Skewness1.348735
Sum44.7
Variance0.42412955
MonotonicityNot monotonic
2024-03-15T10:14:00.415558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.8 5
12.8%
1.1 5
12.8%
0.9 3
 
7.7%
1.0 3
 
7.7%
0.4 3
 
7.7%
1.4 3
 
7.7%
0.5 3
 
7.7%
1.2 2
 
5.1%
1.6 2
 
5.1%
0.3 1
 
2.6%
Other values (9) 9
23.1%
ValueCountFrequency (%)
0.3 1
 
2.6%
0.4 3
7.7%
0.5 3
7.7%
0.6 1
 
2.6%
0.7 1
 
2.6%
0.8 5
12.8%
0.9 3
7.7%
1.0 3
7.7%
1.1 5
12.8%
1.2 2
 
5.1%
ValueCountFrequency (%)
2.9 1
 
2.6%
2.8 1
 
2.6%
2.7 1
 
2.6%
2.5 1
 
2.6%
1.7 1
 
2.6%
1.6 2
5.1%
1.5 1
 
2.6%
1.4 3
7.7%
1.3 1
 
2.6%
1.2 2
5.1%

Interactions

2024-03-15T10:13:46.793576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:29.182699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:30.947332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:33.153287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:35.069483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:37.333964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:39.359133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:41.835544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:44.115974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:47.104978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:29.439620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:31.199638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:33.402246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:35.313555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:37.573393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:39.608056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:42.099893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:44.380898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:47.370718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:29.702935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:31.429265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:33.631496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:35.642619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:37.818535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:39.856153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:42.352664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:44.716038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:47.735594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:29.892132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:31.658154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:33.814730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:35.890445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:38.060837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:40.085994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:42.598609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:45.032257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:48.005789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:30.073450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:31.930619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:34.049934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:36.157699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:38.227831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:40.548543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:42.864750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:45.341695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:48.262143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:30.223185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:32.174113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:34.288878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:36.406497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:38.369046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:40.784881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:43.108297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:45.602405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:48.511526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:30.363778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:32.415809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:34.515229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:36.651069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:38.582734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:41.017815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:43.346311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:45.850381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:48.664058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:30.528019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:32.662068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:34.671617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:36.915753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:38.840903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:41.262628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:43.592893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:46.131222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:48.834309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:30.692585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:32.936487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:34.930854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:37.185926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:39.101766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:41.597035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:43.869237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:13:46.462961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:14:00.577578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상세구분학교 정규수업방과 후 학교 프로그램개인 과외그룹 과외학원 수강방문학습지무료 방송강의유료 인터넷 및 통신강좌기타
구분1.0001.0000.0000.0000.0000.0000.5760.0000.0000.0000.000
상세구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
학교 정규수업0.0001.0001.0000.5880.7070.9090.8620.1980.7990.7910.177
방과 후 학교 프로그램0.0001.0000.5881.0000.7100.7710.2300.8570.3670.6230.541
개인 과외0.0001.0000.7070.7101.0000.8330.3260.6200.8620.8920.000
그룹 과외0.0001.0000.9090.7710.8331.0000.7440.4510.8280.8040.000
학원 수강0.5761.0000.8620.2300.3260.7441.0000.0000.4290.4880.466
방문학습지0.0001.0000.1980.8570.6200.4510.0001.0000.0000.0000.442
무료 방송강의0.0001.0000.7990.3670.8620.8280.4290.0001.0000.9560.000
유료 인터넷 및 통신강좌0.0001.0000.7910.6230.8920.8040.4880.0000.9561.0000.453
기타0.0001.0000.1770.5410.0000.0000.4660.4420.0000.4531.000
2024-03-15T10:14:00.819551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학교 정규수업방과 후 학교 프로그램개인 과외그룹 과외학원 수강방문학습지무료 방송강의유료 인터넷 및 통신강좌기타구분
학교 정규수업1.000-0.116-0.879-0.790-0.734-0.293-0.886-0.7230.2650.000
방과 후 학교 프로그램-0.1161.000-0.143-0.179-0.0200.225-0.020-0.134-0.4010.000
개인 과외-0.879-0.1431.0000.8840.6730.2720.8620.825-0.1520.000
그룹 과외-0.790-0.1790.8841.0000.7910.4290.7230.642-0.2120.000
학원 수강-0.734-0.0200.6730.7911.0000.3760.6070.443-0.4810.326
방문학습지-0.2930.2250.2720.4290.3761.0000.095-0.0360.0670.000
무료 방송강의-0.886-0.0200.8620.7230.6070.0951.0000.837-0.2430.000
유료 인터넷 및 통신강좌-0.723-0.1340.8250.6420.443-0.0360.8371.000-0.2200.000
기타0.265-0.401-0.152-0.212-0.4810.067-0.243-0.2201.0000.000
구분0.0000.0000.0000.0000.3260.0000.0000.0000.0001.000

Missing values

2024-03-15T10:13:49.304464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:13:49.854210image/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.
2024-03-15T10:13:50.238577image/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

구분상세구분학교 정규수업방과 후 학교 프로그램개인 과외그룹 과외학원 수강방문학습지무료 방송강의유료 인터넷 및 통신강좌기타
0시군시부56.916.94.11.710.90.86.31.60.9
1시군군부63.321.72.41.14.71.13.11.01.6
2성별남자57.918.43.71.59.90.75.71.50.8
3성별여자58.117.23.91.79.71.15.71.51.2
4연령15~19세40.712.510.73.913.40.213.64.11.0
5연령20~29세45.016.67.33.214.10.710.22.50.4
6연령30~39세43.223.85.12.213.92.56.61.41.4
7연령40~49세52.318.94.21.613.50.96.41.70.4
8연령50~59세62.218.52.51.28.40.44.81.40.5
9연령60세이상72.915.11.40.64.50.62.70.61.7
구분상세구분학교 정규수업방과 후 학교 프로그램개인 과외그룹 과외학원 수강방문학습지무료 방송강의유료 인터넷 및 통신강좌기타
29주택형태단독주택62.918.73.11.56.40.74.01.31.4
30주택형태아파트54.616.54.21.713.11.26.51.50.8
31주택형태연립주택55.820.24.61.59.10.26.61.60.5
32주택형태다세대주택47.320.34.81.27.70.114.73.50.5
33주택형태기타54.417.16.21.28.00.88.12.81.5
34세대구분1인가구61.815.82.71.07.20.26.22.42.5
35세대구분1세대가구66.019.32.00.85.30.73.81.01.1
36세대구분2세대가구52.717.75.02.112.41.16.81.60.7
37세대구분3세대가구57.216.13.61.813.61.15.00.80.8
38세대구분비혈연가구48.314.611.32.76.94.36.52.72.7