Overview

Dataset statistics

Number of variables5
Number of observations543
Missing cells88
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.4 KiB
Average record size in memory42.2 B

Variable types

Numeric2
Text3

Dataset

Description한국언론진흥재단 미디어이슈 (20년 4호)에 기재된 한-일 갈등에 대한 양국 시민 인식 조사에 대한 설문조사 데이터입니다.
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15086456/fileData.do

Alerts

중분류 has 66 (12.2%) missing valuesMissing
소분류 has 22 (4.1%) missing valuesMissing
번호 has unique valuesUnique
대분류 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:24:51.609248
Analysis finished2023-12-12 05:24:52.729527
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct543
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean272
Minimum1
Maximum543
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-12T14:24:52.834080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile28.1
Q1136.5
median272
Q3407.5
95-th percentile515.9
Maximum543
Range542
Interquartile range (IQR)271

Descriptive statistics

Standard deviation156.89487
Coefficient of variation (CV)0.57681937
Kurtosis-1.2
Mean272
Median Absolute Deviation (MAD)136
Skewness0
Sum147696
Variance24616
MonotonicityStrictly increasing
2023-12-12T14:24:53.307384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
366 1
 
0.2%
360 1
 
0.2%
361 1
 
0.2%
362 1
 
0.2%
363 1
 
0.2%
364 1
 
0.2%
365 1
 
0.2%
367 1
 
0.2%
2 1
 
0.2%
Other values (533) 533
98.2%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
543 1
0.2%
542 1
0.2%
541 1
0.2%
540 1
0.2%
539 1
0.2%
538 1
0.2%
537 1
0.2%
536 1
0.2%
535 1
0.2%
534 1
0.2%

대분류
Text

UNIQUE 

Distinct543
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2023-12-12T14:24:53.611666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length22.596685
Min length3

Characters and Unicode

Total characters12270
Distinct characters137
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique543 ?
Unique (%)100.0%

Sample

1st row성별1
2nd row성별2
3rd row연령1
4th row연령2
5th row연령3
ValueCountFrequency (%)
대한 200
 
6.3%
일본 198
 
6.2%
한·일 185
 
5.8%
동의 170
 
5.3%
관련 155
 
4.8%
우리나라 130
 
4.1%
뉴스 120
 
3.8%
책임 100
 
3.1%
나빠진 95
 
3.0%
관계에 93
 
2.9%
Other values (319) 1750
54.8%
2023-12-12T14:24:54.115857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2653
21.6%
일 472
 
3.8%
도 457
 
3.7%
· 397
 
3.2%
한 395
 
3.2%
정 375
 
3.1%
의 363
 
3.0%
에 331
 
2.7%
관 300
 
2.4%
나 263
 
2.1%
Other values (127) 6264
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8234
67.1%
Space Separator 2653
 
21.6%
Decimal Number 881
 
7.2%
Other Punctuation 428
 
3.5%
Open Punctuation 37
 
0.3%
Close Punctuation 37
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 472
 
5.7%
도 457
 
5.6%
한 395
 
4.8%
정 375
 
4.6%
의 363
 
4.4%
에 331
 
4.0%
관 300
 
3.6%
나 263
 
3.2%
본 251
 
3.0%
대 203
 
2.5%
Other values (112) 4824
58.6%
Decimal Number
ValueCountFrequency (%)
1 260
29.5%
2 144
16.3%
3 105
11.9%
4 75
 
8.5%
5 61
 
6.9%
0 56
 
6.4%
6 48
 
5.4%
7 46
 
5.2%
8 45
 
5.1%
9 41
 
4.7%
Other Punctuation
ValueCountFrequency (%)
· 397
92.8%
, 31
 
7.2%
Space Separator
ValueCountFrequency (%)
2653
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8234
67.1%
Common 4036
32.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 472
 
5.7%
도 457
 
5.6%
한 395
 
4.8%
정 375
 
4.6%
의 363
 
4.4%
에 331
 
4.0%
관 300
 
3.6%
나 263
 
3.2%
본 251
 
3.0%
대 203
 
2.5%
Other values (112) 4824
58.6%
Common
ValueCountFrequency (%)
2653
65.7%
· 397
 
9.8%
1 260
 
6.4%
2 144
 
3.6%
3 105
 
2.6%
4 75
 
1.9%
5 61
 
1.5%
0 56
 
1.4%
6 48
 
1.2%
7 46
 
1.1%
Other values (5) 191
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8234
67.1%
ASCII 3639
29.7%
None 397
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2653
72.9%
1 260
 
7.1%
2 144
 
4.0%
3 105
 
2.9%
4 75
 
2.1%
5 61
 
1.7%
0 56
 
1.5%
6 48
 
1.3%
7 46
 
1.3%
8 45
 
1.2%
Other values (4) 146
 
4.0%
Hangul
ValueCountFrequency (%)
일 472
 
5.7%
도 457
 
5.6%
한 395
 
4.8%
정 375
 
4.6%
의 363
 
4.4%
에 331
 
4.0%
관 300
 
3.6%
나 263
 
3.2%
본 251
 
3.0%
대 203
 
2.5%
Other values (112) 4824
58.6%
None
ValueCountFrequency (%)
· 397
100.0%

중분류
Text

MISSING 

Distinct468
Distinct (%)98.1%
Missing66
Missing (%)12.2%
Memory size4.4 KiB
2023-12-12T14:24:54.421583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length37
Mean length23.685535
Min length3

Characters and Unicode

Total characters11298
Distinct characters247
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique459 ?
Unique (%)96.2%

Sample

1st row일본1
2nd row일본2
3rd row일본3
4th row일본4
5th row미국1
ValueCountFrequency (%)
일본 192
 
7.2%
우리나라 140
 
5.2%
관련 103
 
3.8%
2 92
 
3.4%
1 92
 
3.4%
3 72
 
2.7%
보도되는 70
 
2.6%
뉴스는 70
 
2.6%
언론·언론인은 50
 
1.9%
4 48
 
1.8%
Other values (414) 1755
65.4%
2023-12-12T14:24:54.896218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2207
 
19.5%
) 653
 
5.8%
일 328
 
2.9%
본 250
 
2.2%
1 225
 
2.0%
나 224
 
2.0%
다 212
 
1.9%
라 211
 
1.9%
( 208
 
1.8%
. 205
 
1.8%
Other values (237) 6575
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6708
59.4%
Space Separator 2207
 
19.5%
Decimal Number 948
 
8.4%
Close Punctuation 653
 
5.8%
Other Punctuation 422
 
3.7%
Open Punctuation 208
 
1.8%
Uppercase Letter 70
 
0.6%
Connector Punctuation 50
 
0.4%
Dash Punctuation 12
 
0.1%
Final Punctuation 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 328
 
4.9%
본 250
 
3.7%
나 224
 
3.3%
다 212
 
3.2%
라 211
 
3.1%
리 199
 
3.0%
우 190
 
2.8%
는 186
 
2.8%
인 178
 
2.7%
한 166
 
2.5%
Other values (205) 4564
68.0%
Uppercase Letter
ValueCountFrequency (%)
C 13
18.6%
B 10
14.3%
T 10
14.3%
P 9
12.9%
V 6
8.6%
S 6
8.6%
M 4
 
5.7%
N 4
 
5.7%
J 2
 
2.9%
A 2
 
2.9%
Other values (2) 4
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 225
23.7%
2 191
20.1%
3 167
17.6%
4 138
14.6%
5 117
12.3%
6 30
 
3.2%
7 29
 
3.1%
8 19
 
2.0%
0 18
 
1.9%
9 14
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 205
48.6%
· 115
27.3%
, 102
24.2%
Space Separator
ValueCountFrequency (%)
2207
100.0%
Close Punctuation
ValueCountFrequency (%)
) 653
100.0%
Open Punctuation
ValueCountFrequency (%)
( 208
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 10
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6708
59.4%
Common 4520
40.0%
Latin 70
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 328
 
4.9%
본 250
 
3.7%
나 224
 
3.3%
다 212
 
3.2%
라 211
 
3.1%
리 199
 
3.0%
우 190
 
2.8%
는 186
 
2.8%
인 178
 
2.7%
한 166
 
2.5%
Other values (205) 4564
68.0%
Common
ValueCountFrequency (%)
2207
48.8%
) 653
 
14.4%
1 225
 
5.0%
( 208
 
4.6%
. 205
 
4.5%
2 191
 
4.2%
3 167
 
3.7%
4 138
 
3.1%
5 117
 
2.6%
· 115
 
2.5%
Other values (10) 294
 
6.5%
Latin
ValueCountFrequency (%)
C 13
18.6%
B 10
14.3%
T 10
14.3%
P 9
12.9%
V 6
8.6%
S 6
8.6%
M 4
 
5.7%
N 4
 
5.7%
J 2
 
2.9%
A 2
 
2.9%
Other values (2) 4
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6708
59.4%
ASCII 4455
39.4%
None 115
 
1.0%
Punctuation 20
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2207
49.5%
) 653
 
14.7%
1 225
 
5.1%
( 208
 
4.7%
. 205
 
4.6%
2 191
 
4.3%
3 167
 
3.7%
4 138
 
3.1%
5 117
 
2.6%
, 102
 
2.3%
Other values (19) 242
 
5.4%
Hangul
ValueCountFrequency (%)
일 328
 
4.9%
본 250
 
3.7%
나 224
 
3.3%
다 212
 
3.2%
라 211
 
3.1%
리 199
 
3.0%
우 190
 
2.8%
는 186
 
2.8%
인 178
 
2.7%
한 166
 
2.5%
Other values (205) 4564
68.0%
None
ValueCountFrequency (%)
· 115
100.0%
Punctuation
ValueCountFrequency (%)
’ 10
50.0%
‘ 10
50.0%

소분류
Text

MISSING 

Distinct109
Distinct (%)20.9%
Missing22
Missing (%)4.1%
Memory size4.4 KiB
2023-12-12T14:24:55.135512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length11.161228
Min length4

Characters and Unicode

Total characters5815
Distinct characters154
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)12.7%

Sample

1st row1) 남성
2nd row2)여성
3rd row1) 만20-29세
4th row2) 만30-39세
5th row3) 만40-49세
ValueCountFrequency (%)
편이다 172
 
9.7%
1 106
 
6.0%
2 105
 
5.9%
3 99
 
5.6%
4 98
 
5.5%
보통이다 83
 
4.7%
전혀 83
 
4.7%
5 79
 
4.5%
매우 79
 
4.5%
그렇지 78
 
4.4%
Other values (143) 791
44.6%
2023-12-12T14:24:55.537119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1315
22.6%
) 521
 
9.0%
다 443
 
7.6%
이 355
 
6.1%
편 174
 
3.0%
그 161
 
2.8%
1 141
 
2.4%
지 130
 
2.2%
않 130
 
2.2%
렇 122
 
2.1%
Other values (144) 2323
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3284
56.5%
Space Separator 1315
22.6%
Decimal Number 656
 
11.3%
Close Punctuation 521
 
9.0%
Dash Punctuation 30
 
0.5%
Other Punctuation 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 443
 
13.5%
이 355
 
10.8%
편 174
 
5.3%
그 161
 
4.9%
지 130
 
4.0%
않 130
 
4.0%
렇 122
 
3.7%
전 87
 
2.6%
보 87
 
2.6%
혀 83
 
2.5%
Other values (129) 1512
46.0%
Decimal Number
ValueCountFrequency (%)
1 141
21.5%
2 119
18.1%
3 113
17.2%
4 104
15.9%
5 94
14.3%
0 33
 
5.0%
9 23
 
3.5%
6 13
 
2.0%
7 9
 
1.4%
8 7
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
, 3
33.3%
Space Separator
ValueCountFrequency (%)
1315
100.0%
Close Punctuation
ValueCountFrequency (%)
) 521
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3284
56.5%
Common 2531
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 443
 
13.5%
이 355
 
10.8%
편 174
 
5.3%
그 161
 
4.9%
지 130
 
4.0%
않 130
 
4.0%
렇 122
 
3.7%
전 87
 
2.6%
보 87
 
2.6%
혀 83
 
2.5%
Other values (129) 1512
46.0%
Common
ValueCountFrequency (%)
1315
52.0%
) 521
 
20.6%
1 141
 
5.6%
2 119
 
4.7%
3 113
 
4.5%
4 104
 
4.1%
5 94
 
3.7%
0 33
 
1.3%
- 30
 
1.2%
9 23
 
0.9%
Other values (5) 38
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3284
56.5%
ASCII 2531
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1315
52.0%
) 521
 
20.6%
1 141
 
5.6%
2 119
 
4.7%
3 113
 
4.5%
4 104
 
4.1%
5 94
 
3.7%
0 33
 
1.3%
- 30
 
1.2%
9 23
 
0.9%
Other values (5) 38
 
1.5%
Hangul
ValueCountFrequency (%)
다 443
 
13.5%
이 355
 
10.8%
편 174
 
5.3%
그 161
 
4.9%
지 130
 
4.0%
않 130
 
4.0%
렇 122
 
3.7%
전 87
 
2.6%
보 87
 
2.6%
혀 83
 
2.5%
Other values (129) 1512
46.0%

사례수
Real number (ℝ)

Distinct315
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202.1326
Minimum0
Maximum1000
Zeros4
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-12T14:24:55.692615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.1
Q150.5
median174
Q3305
95-th percentile515.5
Maximum1000
Range1000
Interquartile range (IQR)254.5

Descriptive statistics

Standard deviation176.49834
Coefficient of variation (CV)0.873181
Kurtosis1.5663971
Mean202.1326
Median Absolute Deviation (MAD)127
Skewness1.1260347
Sum109758
Variance31151.665
MonotonicityNot monotonic
2023-12-12T14:24:55.827521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34 8
 
1.5%
26 6
 
1.1%
40 6
 
1.1%
47 5
 
0.9%
2 5
 
0.9%
29 5
 
0.9%
20 5
 
0.9%
73 5
 
0.9%
66 5
 
0.9%
249 5
 
0.9%
Other values (305) 488
89.9%
ValueCountFrequency (%)
0 4
0.7%
1 1
 
0.2%
2 5
0.9%
3 2
 
0.4%
4 3
0.6%
5 3
0.6%
6 5
0.9%
7 3
0.6%
8 2
 
0.4%
9 1
 
0.2%
ValueCountFrequency (%)
1000 1
0.2%
965 1
0.2%
910 1
0.2%
831 1
0.2%
808 1
0.2%
806 1
0.2%
751 1
0.2%
675 1
0.2%
673 1
0.2%
663 1
0.2%

Interactions

2023-12-12T14:24:52.226866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:52.015764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:52.334893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:52.113195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:24:55.910659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호사례수
번호1.0000.282
사례수0.2821.000
2023-12-12T14:24:55.979456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호사례수
번호1.000-0.125
사례수-0.1251.000

Missing values

2023-12-12T14:24:52.484812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:24:52.581717image/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.
2023-12-12T14:24:52.677447image/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

번호대분류중분류소분류사례수
01성별1<NA>1) 남성511
12성별2<NA>2)여성489
23연령1<NA>1) 만20-29세183
34연령2<NA>2) 만30-39세187
45연령3<NA>3) 만40-49세222
56연령4<NA>4) 만50-59세234
67연령5<NA>5) 만60-69세174
78거주 지역1<NA>1) 서울194
89거주 지역2<NA>2) 부산194
910거주 지역3<NA>3) 대구67
번호대분류중분류소분류사례수
533534직업11<NA>11) 학생64
534535직업12<NA>12) 무직, 취업준비생82
535536월 평균 소득(용돈 포함)1<NA>1) 199만 원 이하300
536537월 평균 소득(용돈 포함)2<NA>2) 200-299만 원239
537538월 평균 소득(용돈 포함)3<NA>3) 300-399만 원197
538539월 평균 소득(용돈 포함)4<NA>4) 400-499만 원101
539540월 평균 소득(용돈 포함)5<NA>5) 500-599만 원71
540541월 평균 소득(용돈 포함)6<NA>6) 600-699만 원40
541542월 평균 소득(용돈 포함)7<NA>7) 700-799만 원18
542543월 평균 소득(용돈 포함)8<NA>8) 800만 원 이상34