Overview

Dataset statistics

Number of variables5
Number of observations145
Missing cells115
Missing cells (%)15.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory42.9 B

Variable types

Numeric2
Text3

Dataset

Description한국언론진흥재단 미디어 이슈(20년 6호)에 개재된 "네이버 많이 본 뉴스 개편에 대한 이용자 인식"을 정리한 데이터입니다. 자세한 내용은 홈페이지 참고바랍니다.
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15086565/fileData.do

Alerts

중분류 has 115 (79.3%) missing valuesMissing
번호 has unique valuesUnique
대분류 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:44:34.580085
Analysis finished2023-12-12 21:44:35.506185
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73
Minimum1
Maximum145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T06:44:35.593452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.2
Q137
median73
Q3109
95-th percentile137.8
Maximum145
Range144
Interquartile range (IQR)72

Descriptive statistics

Standard deviation42.001984
Coefficient of variation (CV)0.57536964
Kurtosis-1.2
Mean73
Median Absolute Deviation (MAD)36
Skewness0
Sum10585
Variance1764.1667
MonotonicityStrictly increasing
2023-12-13T06:44:35.750924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
110 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
Other values (135) 135
93.1%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%

대분류
Text

UNIQUE 

Distinct145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:44:36.175523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length26
Mean length17.248276
Min length3

Characters and Unicode

Total characters2501
Distinct characters129
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)100.0%

Sample

1st row성별1
2nd row성별2
3rd row연령1
4th row연령2
5th row연령3
ValueCountFrequency (%)
‘네이버뉴스’가 30
 
4.9%
생각하는 30
 
4.9%
개편을 30
 
4.9%
뉴스 20
 
3.3%
댓글 16
 
2.6%
포털 16
 
2.6%
인터넷 16
 
2.6%
잘했다고 15
 
2.5%
대한 15
 
2.5%
못했다고 15
 
2.5%
Other values (166) 409
66.8%
2023-12-13T06:44:36.769897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
467
 
18.7%
이 130
 
5.2%
스 110
 
4.4%
뉴 88
 
3.5%
네 62
 
2.5%
버 62
 
2.5%
개 55
 
2.2%
편 55
 
2.2%
‘ 53
 
2.1%
1 50
 
2.0%
Other values (119) 1369
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1710
68.4%
Space Separator 467
 
18.7%
Decimal Number 167
 
6.7%
Initial Punctuation 53
 
2.1%
Final Punctuation 48
 
1.9%
Modifier Symbol 28
 
1.1%
Math Symbol 10
 
0.4%
Other Punctuation 8
 
0.3%
Close Punctuation 5
 
0.2%
Open Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 130
 
7.6%
스 110
 
6.4%
뉴 88
 
5.1%
네 62
 
3.6%
버 62
 
3.6%
개 55
 
3.2%
편 55
 
3.2%
가 42
 
2.5%
는 40
 
2.3%
지 37
 
2.2%
Other values (100) 1029
60.2%
Decimal Number
ValueCountFrequency (%)
1 50
29.9%
2 28
16.8%
3 27
16.2%
4 23
13.8%
5 15
 
9.0%
6 6
 
3.6%
8 5
 
3.0%
7 5
 
3.0%
0 4
 
2.4%
9 4
 
2.4%
Math Symbol
ValueCountFrequency (%)
< 5
50.0%
> 5
50.0%
Space Separator
ValueCountFrequency (%)
467
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 53
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 48
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1710
68.4%
Common 791
31.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 130
 
7.6%
스 110
 
6.4%
뉴 88
 
5.1%
네 62
 
3.6%
버 62
 
3.6%
개 55
 
3.2%
편 55
 
3.2%
가 42
 
2.5%
는 40
 
2.3%
지 37
 
2.2%
Other values (100) 1029
60.2%
Common
ValueCountFrequency (%)
467
59.0%
‘ 53
 
6.7%
1 50
 
6.3%
’ 48
 
6.1%
2 28
 
3.5%
` 28
 
3.5%
3 27
 
3.4%
4 23
 
2.9%
5 15
 
1.9%
, 8
 
1.0%
Other values (9) 44
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1710
68.4%
ASCII 690
27.6%
Punctuation 101
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
467
67.7%
1 50
 
7.2%
2 28
 
4.1%
` 28
 
4.1%
3 27
 
3.9%
4 23
 
3.3%
5 15
 
2.2%
, 8
 
1.2%
6 6
 
0.9%
) 5
 
0.7%
Other values (7) 33
 
4.8%
Hangul
ValueCountFrequency (%)
이 130
 
7.6%
스 110
 
6.4%
뉴 88
 
5.1%
네 62
 
3.6%
버 62
 
3.6%
개 55
 
3.2%
편 55
 
3.2%
가 42
 
2.5%
는 40
 
2.3%
지 37
 
2.2%
Other values (100) 1029
60.2%
Punctuation
ValueCountFrequency (%)
‘ 53
52.5%
’ 48
47.5%

중분류
Text

MISSING 

Distinct30
Distinct (%)100.0%
Missing115
Missing (%)79.3%
Memory size1.3 KiB
2023-12-13T06:44:37.070107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.7
Min length13

Characters and Unicode

Total characters621
Distinct characters78
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

Unique30 ?
Unique (%)100.0%

Sample

1st row1) 다양한 기사 제공1
2nd row1) 다양한 기사 제공2
3rd row1) 다양한 기사 제공3
4th row2) 성별, 세대별로 가르는 부작용1
5th row2) 성별, 세대별로 가르는 부작용2
ValueCountFrequency (%)
1 6
 
3.6%
성별 6
 
3.6%
경쟁 6
 
3.6%
클릭수(페이지뷰 6
 
3.6%
4 6
 
3.6%
3 6
 
3.6%
파악 6
 
3.6%
2 6
 
3.6%
더 6
 
3.6%
기사 6
 
3.6%
Other values (49) 108
64.3%
2023-12-13T06:44:37.436113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
141
22.7%
) 36
 
5.8%
이 18
 
2.9%
2 16
 
2.6%
3 16
 
2.6%
1 16
 
2.6%
별 12
 
1.9%
다 12
 
1.9%
는 9
 
1.4%
개 9
 
1.4%
Other values (68) 336
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 372
59.9%
Space Separator 141
 
22.7%
Decimal Number 60
 
9.7%
Close Punctuation 36
 
5.8%
Open Punctuation 6
 
1.0%
Other Punctuation 6
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 18
 
4.8%
별 12
 
3.2%
다 12
 
3.2%
는 9
 
2.4%
개 9
 
2.4%
지 9
 
2.4%
하 9
 
2.4%
성 9
 
2.4%
함 9
 
2.4%
사 9
 
2.4%
Other values (59) 267
71.8%
Decimal Number
ValueCountFrequency (%)
2 16
26.7%
3 16
26.7%
1 16
26.7%
5 6
 
10.0%
4 6
 
10.0%
Space Separator
ValueCountFrequency (%)
141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 372
59.9%
Common 249
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 18
 
4.8%
별 12
 
3.2%
다 12
 
3.2%
는 9
 
2.4%
개 9
 
2.4%
지 9
 
2.4%
하 9
 
2.4%
성 9
 
2.4%
함 9
 
2.4%
사 9
 
2.4%
Other values (59) 267
71.8%
Common
ValueCountFrequency (%)
141
56.6%
) 36
 
14.5%
2 16
 
6.4%
3 16
 
6.4%
1 16
 
6.4%
( 6
 
2.4%
5 6
 
2.4%
4 6
 
2.4%
, 6
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 372
59.9%
ASCII 249
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
141
56.6%
) 36
 
14.5%
2 16
 
6.4%
3 16
 
6.4%
1 16
 
6.4%
( 6
 
2.4%
5 6
 
2.4%
4 6
 
2.4%
, 6
 
2.4%
Hangul
ValueCountFrequency (%)
이 18
 
4.8%
별 12
 
3.2%
다 12
 
3.2%
는 9
 
2.4%
개 9
 
2.4%
지 9
 
2.4%
하 9
 
2.4%
성 9
 
2.4%
함 9
 
2.4%
사 9
 
2.4%
Other values (59) 267
71.8%

소분류
Text

Distinct106
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:44:37.759588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length36
Mean length14.489655
Min length3

Characters and Unicode

Total characters2101
Distinct characters228
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)62.8%

Sample

1st row남자1
2nd row남자2
3rd row 1) 만20-29세
4th row 2) 만30-39세
5th row 3) 만40-49세
ValueCountFrequency (%)
1 31
 
5.8%
3 31
 
5.8%
2 31
 
5.8%
4 18
 
3.4%
그렇다 14
 
2.6%
아니다 10
 
1.9%
무응답 10
 
1.9%
5 10
 
1.9%
종사자 8
 
1.5%
미만 7
 
1.3%
Other values (218) 366
68.3%
2023-12-13T06:44:38.192972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
667
31.7%
) 149
 
7.1%
다 64
 
3.0%
1 45
 
2.1%
2 39
 
1.9%
3 38
 
1.8%
0 35
 
1.7%
이 33
 
1.6%
만 29
 
1.4%
4 24
 
1.1%
Other values (218) 978
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1011
48.1%
Space Separator 667
31.7%
Decimal Number 223
 
10.6%
Close Punctuation 149
 
7.1%
Dash Punctuation 14
 
0.7%
Math Symbol 10
 
0.5%
Other Punctuation 9
 
0.4%
Open Punctuation 6
 
0.3%
Initial Punctuation 4
 
0.2%
Final Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 64
 
6.3%
이 33
 
3.3%
만 29
 
2.9%
지 21
 
2.1%
기 19
 
1.9%
스 19
 
1.9%
렇 18
 
1.8%
그 18
 
1.8%
원 17
 
1.7%
사 17
 
1.7%
Other values (197) 756
74.8%
Decimal Number
ValueCountFrequency (%)
1 45
20.2%
2 39
17.5%
3 38
17.0%
0 35
15.7%
4 24
10.8%
5 16
 
7.2%
6 9
 
4.0%
9 7
 
3.1%
8 5
 
2.2%
7 5
 
2.2%
Math Symbol
ValueCountFrequency (%)
> 5
50.0%
< 5
50.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
P 2
50.0%
Space Separator
ValueCountFrequency (%)
667
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1086
51.7%
Hangul 1011
48.1%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 64
 
6.3%
이 33
 
3.3%
만 29
 
2.9%
지 21
 
2.1%
기 19
 
1.9%
스 19
 
1.9%
렇 18
 
1.8%
그 18
 
1.8%
원 17
 
1.7%
사 17
 
1.7%
Other values (197) 756
74.8%
Common
ValueCountFrequency (%)
667
61.4%
) 149
 
13.7%
1 45
 
4.1%
2 39
 
3.6%
3 38
 
3.5%
0 35
 
3.2%
4 24
 
2.2%
5 16
 
1.5%
- 14
 
1.3%
6 9
 
0.8%
Other values (9) 50
 
4.6%
Latin
ValueCountFrequency (%)
C 2
50.0%
P 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1082
51.5%
Hangul 1011
48.1%
Punctuation 8
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
667
61.6%
) 149
 
13.8%
1 45
 
4.2%
2 39
 
3.6%
3 38
 
3.5%
0 35
 
3.2%
4 24
 
2.2%
5 16
 
1.5%
- 14
 
1.3%
6 9
 
0.8%
Other values (9) 46
 
4.3%
Hangul
ValueCountFrequency (%)
다 64
 
6.3%
이 33
 
3.3%
만 29
 
2.9%
지 21
 
2.1%
기 19
 
1.9%
스 19
 
1.9%
렇 18
 
1.8%
그 18
 
1.8%
원 17
 
1.7%
사 17
 
1.7%
Other values (197) 756
74.8%
Punctuation
ValueCountFrequency (%)
‘ 4
50.0%
’ 4
50.0%

사례수
Real number (ℝ)

Distinct119
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean259.22759
Minimum1
Maximum1202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T06:44:38.362805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile23.2
Q169
median161
Q3379
95-th percentile793.8
Maximum1202
Range1201
Interquartile range (IQR)310

Descriptive statistics

Standard deviation250.3703
Coefficient of variation (CV)0.96583202
Kurtosis1.1221037
Mean259.22759
Median Absolute Deviation (MAD)122
Skewness1.2878763
Sum37588
Variance62685.288
MonotonicityNot monotonic
2023-12-13T06:44:38.543313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
889 5
 
3.4%
379 5
 
3.4%
39 3
 
2.1%
57 3
 
2.1%
116 3
 
2.1%
82 2
 
1.4%
224 2
 
1.4%
293 2
 
1.4%
34 2
 
1.4%
31 2
 
1.4%
Other values (109) 116
80.0%
ValueCountFrequency (%)
1 1
0.7%
5 1
0.7%
6 1
0.7%
19 1
0.7%
20 1
0.7%
21 1
0.7%
22 1
0.7%
23 1
0.7%
24 1
0.7%
26 2
1.4%
ValueCountFrequency (%)
1202 1
 
0.7%
889 5
3.4%
813 1
 
0.7%
795 1
 
0.7%
789 1
 
0.7%
745 1
 
0.7%
695 1
 
0.7%
692 1
 
0.7%
690 1
 
0.7%
666 1
 
0.7%

Interactions

2023-12-13T06:44:35.077907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:34.886802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:35.210487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:34.986877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:44:38.657225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호중분류사례수
번호1.0001.0000.406
중분류1.0001.0001.000
사례수0.4061.0001.000
2023-12-13T06:44:38.756944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호사례수
번호1.000-0.033
사례수-0.0331.000

Missing values

2023-12-13T06:44:35.361489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:44:35.468345image/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

번호대분류중분류소분류사례수
01성별1<NA>남자1613
12성별2<NA>남자2589
23연령1<NA>1) 만20-29세262
34연령2<NA>2) 만30-39세267
45연령3<NA>3) 만40-49세260
56연령4<NA>4) 만50-59세268
67연령5<NA>5) 만60-69세145
78거주 지역1<NA>1) 서울217
89거주 지역2<NA>2) 부산76
910거주 지역3<NA>3) 대구57
번호대분류중분류소분류사례수
135136월 평균 가구 소득8<NA>8) 800만원 이상116
136137사회계층1<NA>1) 하층115
137138사회계층2<NA>2) 중하층450
138139사회계층3<NA>3) 중간층561
139140사회계층4<NA>4) 중상층76
140141정치적 성향1<NA>1) 보수31
141142정치적 성향2<NA>2) 보수에 가까움173
142143정치적 성향3<NA>3) 중도692
143144정치적 성향4<NA>4) 진보에 가까움280
144145정치적 성향5<NA>5) 진보26