Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory76.3 B

Variable types

Numeric3
Categorical5
Text1

Dataset

Description샘플 데이터
Author성균관대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=f0997ad0-e841-11ea-a0ba-57da34c93da2

Alerts

연월일 has constant value ""Constant
환경플랫폼 하위 도메인명 has constant value ""Constant
도메인 하위 카테고리명 has constant value ""Constant
SNS 채널명 has constant value ""Constant
일간연관어언급량 is highly overall correlated with 일간연관어단어량High correlation
일간연관어단어량 is highly overall correlated with 일간연관어언급량High correlation
일간연관어연번 has unique valuesUnique
연관어명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:03:10.778736
Analysis finished2023-12-10 13:03:12.112671
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일간연관어연번
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:03:12.193935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T22:03:12.369042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

연월일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2021-01-01
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-01
2nd row2021-01-01
3rd row2021-01-01
4th row2021-01-01
5th row2021-01-01

Common Values

ValueCountFrequency (%)
2021-01-01 100
100.0%

Length

2023-12-10T22:03:12.516179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:03:12.614189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-01 100
100.0%

환경플랫폼 하위 도메인명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
물환경
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물환경 100
100.0%

Length

2023-12-10T22:03:12.719831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:03:12.806730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물환경 100
100.0%

도메인 하위 카테고리명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
물재난
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물재난 100
100.0%

Length

2023-12-10T22:03:12.896260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:03:12.984468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물재난 100
100.0%

SNS 채널명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
news
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
news 100
100.0%

Length

2023-12-10T22:03:13.069906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:03:13.154086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
news 100
100.0%

단어속성명
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
속성
31 
라이프
24 
기타
20 
장소
15 
상품
4 
Other values (4)
6 

Length

Max length4
Median length2
Mean length2.3
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row장소
2nd row라이프
3rd row속성
4th row기타
5th row장소

Common Values

ValueCountFrequency (%)
속성 31
31.0%
라이프 24
24.0%
기타 20
20.0%
장소 15
15.0%
상품 4
 
4.0%
사회이슈 2
 
2.0%
브랜드 2
 
2.0%
인물 1
 
1.0%
시간 1
 
1.0%

Length

2023-12-10T22:03:13.264208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:03:13.405522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
속성 31
31.0%
라이프 24
24.0%
기타 20
20.0%
장소 15
15.0%
상품 4
 
4.0%
사회이슈 2
 
2.0%
브랜드 2
 
2.0%
인물 1
 
1.0%
시간 1
 
1.0%

연관어명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:03:13.723773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.6
Min length2

Characters and Unicode

Total characters260
Distinct characters119
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row가게
2nd row가계
3rd row가금
4th row가꾸다
5th row가맹점
ValueCountFrequency (%)
가게 1
 
1.0%
검정고시 1
 
1.0%
경로당 1
 
1.0%
경고 1
 
1.0%
겹치다 1
 
1.0%
결혼 1
 
1.0%
결별 1
 
1.0%
견학 1
 
1.0%
견인 1
 
1.0%
견고 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T22:03:14.200486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 18
 
6.9%
가 15
 
5.8%
강 11
 
4.2%
고 10
 
3.8%
감 9
 
3.5%
개 7
 
2.7%
계 6
 
2.3%
다 6
 
2.3%
거 5
 
1.9%
건 5
 
1.9%
Other values (109) 168
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 260
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 18
 
6.9%
가 15
 
5.8%
강 11
 
4.2%
고 10
 
3.8%
감 9
 
3.5%
개 7
 
2.7%
계 6
 
2.3%
다 6
 
2.3%
거 5
 
1.9%
건 5
 
1.9%
Other values (109) 168
64.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 18
 
6.9%
가 15
 
5.8%
강 11
 
4.2%
고 10
 
3.8%
감 9
 
3.5%
개 7
 
2.7%
계 6
 
2.3%
다 6
 
2.3%
거 5
 
1.9%
건 5
 
1.9%
Other values (109) 168
64.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 260
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 18
 
6.9%
가 15
 
5.8%
강 11
 
4.2%
고 10
 
3.8%
감 9
 
3.5%
개 7
 
2.7%
계 6
 
2.3%
다 6
 
2.3%
거 5
 
1.9%
건 5
 
1.9%
Other values (109) 168
64.6%

일간연관어언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.31
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:03:14.365829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile6.05
Maximum13
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.0582183
Coefficient of variation (CV)0.8910036
Kurtosis7.3835831
Mean2.31
Median Absolute Deviation (MAD)0
Skewness2.3524203
Sum231
Variance4.2362626
MonotonicityNot monotonic
2023-12-10T22:03:14.505218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 53
53.0%
2 18
 
18.0%
4 10
 
10.0%
3 7
 
7.0%
5 4
 
4.0%
7 3
 
3.0%
6 3
 
3.0%
13 1
 
1.0%
9 1
 
1.0%
ValueCountFrequency (%)
1 53
53.0%
2 18
 
18.0%
3 7
 
7.0%
4 10
 
10.0%
5 4
 
4.0%
6 3
 
3.0%
7 3
 
3.0%
9 1
 
1.0%
13 1
 
1.0%
ValueCountFrequency (%)
13 1
 
1.0%
9 1
 
1.0%
7 3
 
3.0%
6 3
 
3.0%
5 4
 
4.0%
4 10
 
10.0%
3 7
 
7.0%
2 18
 
18.0%
1 53
53.0%

일간연관어단어량
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.24
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:03:14.623465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile9.05
Maximum29
Range28
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.9494789
Coefficient of variation (CV)1.218975
Kurtosis19.922017
Mean3.24
Median Absolute Deviation (MAD)1
Skewness3.8592775
Sum324
Variance15.598384
MonotonicityNot monotonic
2023-12-10T22:03:14.731614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 40
40.0%
2 22
22.0%
3 11
 
11.0%
4 9
 
9.0%
8 4
 
4.0%
5 3
 
3.0%
7 3
 
3.0%
6 2
 
2.0%
10 1
 
1.0%
29 1
 
1.0%
Other values (4) 4
 
4.0%
ValueCountFrequency (%)
1 40
40.0%
2 22
22.0%
3 11
 
11.0%
4 9
 
9.0%
5 3
 
3.0%
6 2
 
2.0%
7 3
 
3.0%
8 4
 
4.0%
9 1
 
1.0%
10 1
 
1.0%
ValueCountFrequency (%)
29 1
 
1.0%
19 1
 
1.0%
13 1
 
1.0%
11 1
 
1.0%
10 1
 
1.0%
9 1
 
1.0%
8 4
4.0%
7 3
3.0%
6 2
2.0%
5 3
3.0%

Interactions

2023-12-10T22:03:11.581203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:11.048564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:11.312667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:11.677883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:11.148470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:11.412651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:11.776014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:11.234749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:11.492083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:03:14.812112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간연관어연번단어속성명연관어명일간연관어언급량일간연관어단어량
일간연관어연번1.0000.0001.0000.2180.212
단어속성명0.0001.0001.0000.0000.000
연관어명1.0001.0001.0001.0001.000
일간연관어언급량0.2180.0001.0001.0000.893
일간연관어단어량0.2120.0001.0000.8931.000
2023-12-10T22:03:14.923272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간연관어연번일간연관어언급량일간연관어단어량단어속성명
일간연관어연번1.000-0.041-0.0910.000
일간연관어언급량-0.0411.0000.8600.000
일간연관어단어량-0.0910.8601.0000.000
단어속성명0.0000.0000.0001.000

Missing values

2023-12-10T22:03:11.913395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:03:12.049436image/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

일간연관어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명단어속성명연관어명일간연관어언급량일간연관어단어량
012021-01-01물환경물재난news장소가게11
122021-01-01물환경물재난news라이프가계11
232021-01-01물환경물재난news속성가금44
342021-01-01물환경물재난news기타가꾸다45
452021-01-01물환경물재난news장소가맹점11
562021-01-01물환경물재난news기타가선11
672021-01-01물환경물재난news속성가슴710
782021-01-01물환경물재난news속성가시22
892021-01-01물환경물재난news속성가옥11
9102021-01-01물환경물재난news속성가이드라인33
일간연관어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명단어속성명연관어명일간연관어언급량일간연관어단어량
90912021-01-01물환경물재난news기타계량화33
91922021-01-01물환경물재난news기타계시다22
92932021-01-01물환경물재난news라이프계획서11
93942021-01-01물환경물재난news속성고갈11
94952021-01-01물환경물재난news기타고경호11
95962021-01-01물환경물재난news라이프고구려23
96972021-01-01물환경물재난news속성고난68
97982021-01-01물환경물재난news기타고도처리11
98992021-01-01물환경물재난news장소고등학교22
991002021-01-01물환경물재난news라이프고령자33