Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory67.3 B

Variable types

Numeric1
Categorical6
Text1

Dataset

Description샘플 데이터
Author성균관대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=0d7f33b0-2fce-11ea-94b6-73a02796bba4

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 imbalanced (68.1%)Imbalance
일간연관어연번 has unique valuesUnique
연관어명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:42:48.341053
Analysis finished2023-12-10 12:42:48.867372
Duration0.53 seconds
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
2023-12-10T21:42:48.950195image/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
2023-12-10T21:42:49.111214image/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

2023-12-10T21:42:49.242482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:42:49.328444image/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

2023-12-10T21:42:49.435191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:42:49.523719image/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

2023-12-10T21:42:49.626274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:42:49.722572image/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
All
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
All 100
100.0%

Length

2023-12-10T21:42:49.809265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:42:49.893443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 100
100.0%

단어속성명
Categorical

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
속성
32 
라이프
22 
장소
17 
기타
16 
상품
5 
Other values (5)
8 

Length

Max length6
Median length2
Mean length2.33
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row사회이슈
2nd row라이프
3rd row기타
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
속성 32
32.0%
라이프 22
22.0%
장소 17
17.0%
기타 16
16.0%
상품 5
 
5.0%
엔터테인먼트 2
 
2.0%
단체 2
 
2.0%
인물 2
 
2.0%
사회이슈 1
 
1.0%
브랜드 1
 
1.0%

Length

2023-12-10T21:42:50.024833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:42:50.174050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
속성 32
32.0%
라이프 22
22.0%
장소 17
17.0%
기타 16
16.0%
상품 5
 
5.0%
엔터테인먼트 2
 
2.0%
단체 2
 
2.0%
인물 2
 
2.0%
사회이슈 1
 
1.0%
브랜드 1
 
1.0%

연관어명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:42:50.480101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.7
Min length2

Characters and Unicode

Total characters270
Distinct characters130
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row4대강사업
2nd row4차산업혁명
3rd row가꾸다
4th row가름
5th row가리키다
ValueCountFrequency (%)
4대강사업 1
 
1.0%
교통편 1
 
1.0%
그늘막 1
 
1.0%
그늘 1
 
1.0%
국회의원 1
 
1.0%
국토교통부 1
 
1.0%
국무총리 1
 
1.0%
국공립 1
 
1.0%
구파발 1
 
1.0%
구성원 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T21:42:50.916025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 11
 
4.1%
기 10
 
3.7%
가 9
 
3.3%
광 8
 
3.0%
다 8
 
3.0%
리 6
 
2.2%
강 6
 
2.2%
고 6
 
2.2%
구 6
 
2.2%
양 6
 
2.2%
Other values (120) 194
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 268
99.3%
Decimal Number 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 11
 
4.1%
기 10
 
3.7%
가 9
 
3.4%
광 8
 
3.0%
다 8
 
3.0%
리 6
 
2.2%
강 6
 
2.2%
고 6
 
2.2%
구 6
 
2.2%
양 6
 
2.2%
Other values (119) 192
71.6%
Decimal Number
ValueCountFrequency (%)
4 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 268
99.3%
Common 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 11
 
4.1%
기 10
 
3.7%
가 9
 
3.4%
광 8
 
3.0%
다 8
 
3.0%
리 6
 
2.2%
강 6
 
2.2%
고 6
 
2.2%
구 6
 
2.2%
양 6
 
2.2%
Other values (119) 192
71.6%
Common
ValueCountFrequency (%)
4 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 268
99.3%
ASCII 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 11
 
4.1%
기 10
 
3.7%
가 9
 
3.4%
광 8
 
3.0%
다 8
 
3.0%
리 6
 
2.2%
강 6
 
2.2%
고 6
 
2.2%
구 6
 
2.2%
양 6
 
2.2%
Other values (119) 192
71.6%
ASCII
ValueCountFrequency (%)
4 2
100.0%

일간연관어언급량
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
91 
2
 
7
3
 
2

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 91
91.0%
2 7
 
7.0%
3 2
 
2.0%

Length

2023-12-10T21:42:51.046282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:42:51.215678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 91
91.0%
2 7
 
7.0%
3 2
 
2.0%

Interactions

2023-12-10T21:42:48.554526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:42:51.278214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간연관어연번단어속성명연관어명일간연관어언급량
일간연관어연번1.0000.4531.0000.400
단어속성명0.4531.0001.0000.000
연관어명1.0001.0001.0001.000
일간연관어언급량0.4000.0001.0001.000
2023-12-10T21:42:51.366126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간연관어언급량단어속성명
일간연관어언급량1.0000.000
단어속성명0.0001.000
2023-12-10T21:42:51.455493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간연관어연번단어속성명일간연관어언급량
일간연관어연번1.0000.1510.251
단어속성명0.1511.0000.000
일간연관어언급량0.2510.0001.000

Missing values

2023-12-10T21:42:48.662414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:42:48.804711image/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 채널명단어속성명연관어명일간연관어언급량
012021-01-01물환경물재난All사회이슈4대강사업1
122021-01-01물환경물재난All라이프4차산업혁명1
232021-01-01물환경물재난All기타가꾸다1
342021-01-01물환경물재난All기타가름1
452021-01-01물환경물재난All기타가리키다1
562021-01-01물환경물재난All속성가슴1
672021-01-01물환경물재난All속성가시1
782021-01-01물환경물재난All기타가져가다1
892021-01-01물환경물재난All라이프가파르다1
9102021-01-01물환경물재난All속성각계각층1
일간연관어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명단어속성명연관어명일간연관어언급량
90912021-01-01물환경물재난All기타기하다1
91922021-01-01물환경물재난All인물김상도1
92932021-01-01물환경물재난All인물김성원1
93942021-01-01물환경물재난All상품김치1
94952021-01-01물환경물재난All장소김포1
95962021-01-01물환경물재난All기타꺼지다1
96972021-01-01물환경물재난All속성끈기1
97982021-01-01물환경물재난All속성나래1
98992021-01-01물환경물재난All기타나무판1
991002021-01-01물환경물재난All속성낙후1