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

Numeric2
DateTime1
Categorical4
Text1

Dataset

Description샘플 데이터
Author성균관대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=94072cf0-2fd1-11ea-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
주간연관어연번 has unique valuesUnique
연관어명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 11:06:19.342675
Analysis finished2023-12-10 11:06:20.742669
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주간연관어연번
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
2023-12-10T20:06:20.888873image/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
2023-12-10T20:06:21.200259image/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
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-01-06 00:00:00
Maximum2020-01-06 00:00:00
2023-12-10T20:06:21.414354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:06:21.960133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

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

2023-12-10T20:06:22.150565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:22.346142image/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

2023-12-10T20:06:22.594785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:22.760494image/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

2023-12-10T20:06:22.944614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:23.112266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 100
100.0%

단어속성명
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
속성
38 
기타
25 
라이프
16 
상품
9 
장소
6 
Other values (4)
6 

Length

Max length6
Median length2
Mean length2.26
Min length2

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row장소
2nd row사회이슈
3rd row인물
4th row장소
5th row속성

Common Values

ValueCountFrequency (%)
속성 38
38.0%
기타 25
25.0%
라이프 16
16.0%
상품 9
 
9.0%
장소 6
 
6.0%
사회이슈 3
 
3.0%
인물 1
 
1.0%
시간 1
 
1.0%
엔터테인먼트 1
 
1.0%

Length

2023-12-10T20:06:23.342017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:23.563304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
속성 38
38.0%
기타 25
25.0%
라이프 16
16.0%
상품 9
 
9.0%
장소 6
 
6.0%
사회이슈 3
 
3.0%
인물 1
 
1.0%
시간 1
 
1.0%
엔터테인먼트 1
 
1.0%

연관어명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T20:06:24.106489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.63
Min length2

Characters and Unicode

Total characters263
Distinct characters103
Distinct categories2 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 row4대강
2nd row4대강사업
3rd row矛盾
4th row가게
5th row가격
ValueCountFrequency (%)
4대강 1
 
1.0%
간병 1
 
1.0%
갈고리 1
 
1.0%
간헐 1
 
1.0%
간판 1
 
1.0%
간청 1
 
1.0%
간첩 1
 
1.0%
간지럽다 1
 
1.0%
간여 1
 
1.0%
간언 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T20:06:24.971362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 55
20.9%
다 19
 
7.2%
감 16
 
6.1%
간 13
 
4.9%
갈 12
 
4.6%
각 4
 
1.5%
무 4
 
1.5%
기 4
 
1.5%
리 4
 
1.5%
르 4
 
1.5%
Other values (93) 128
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 261
99.2%
Decimal Number 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 55
21.1%
다 19
 
7.3%
감 16
 
6.1%
간 13
 
5.0%
갈 12
 
4.6%
각 4
 
1.5%
무 4
 
1.5%
기 4
 
1.5%
리 4
 
1.5%
르 4
 
1.5%
Other values (92) 126
48.3%
Decimal Number
ValueCountFrequency (%)
4 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 259
98.5%
Common 2
 
0.8%
Han 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 55
21.2%
다 19
 
7.3%
감 16
 
6.2%
간 13
 
5.0%
갈 12
 
4.6%
각 4
 
1.5%
무 4
 
1.5%
기 4
 
1.5%
리 4
 
1.5%
르 4
 
1.5%
Other values (90) 124
47.9%
Han
ValueCountFrequency (%)
盾 1
50.0%
矛 1
50.0%
Common
ValueCountFrequency (%)
4 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 259
98.5%
ASCII 2
 
0.8%
CJK 2
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 55
21.2%
다 19
 
7.3%
감 16
 
6.2%
간 13
 
5.0%
갈 12
 
4.6%
각 4
 
1.5%
무 4
 
1.5%
기 4
 
1.5%
리 4
 
1.5%
르 4
 
1.5%
Other values (90) 124
47.9%
ASCII
ValueCountFrequency (%)
4 2
100.0%
CJK
ValueCountFrequency (%)
盾 1
50.0%
矛 1
50.0%

주간연관어언급량
Real number (ℝ)

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.23
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:06:25.203633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile13.1
Maximum32
Range31
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.100713
Coefficient of variation (CV)1.5791681
Kurtosis14.187311
Mean3.23
Median Absolute Deviation (MAD)0
Skewness3.5745114
Sum323
Variance26.017273
MonotonicityNot monotonic
2023-12-10T20:06:25.414204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 56
56.0%
2 15
 
15.0%
3 9
 
9.0%
4 6
 
6.0%
9 3
 
3.0%
5 2
 
2.0%
25 1
 
1.0%
6 1
 
1.0%
13 1
 
1.0%
32 1
 
1.0%
Other values (5) 5
 
5.0%
ValueCountFrequency (%)
1 56
56.0%
2 15
 
15.0%
3 9
 
9.0%
4 6
 
6.0%
5 2
 
2.0%
6 1
 
1.0%
7 1
 
1.0%
9 3
 
3.0%
12 1
 
1.0%
13 1
 
1.0%
ValueCountFrequency (%)
32 1
 
1.0%
25 1
 
1.0%
20 1
 
1.0%
19 1
 
1.0%
15 1
 
1.0%
13 1
 
1.0%
12 1
 
1.0%
9 3
3.0%
7 1
 
1.0%
6 1
 
1.0%

Interactions

2023-12-10T20:06:20.055629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:06:19.715001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:06:20.217620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:06:19.885378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:06:25.581459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간연관어연번단어속성명연관어명주간연관어언급량
주간연관어연번1.0000.1961.0000.224
단어속성명0.1961.0001.0000.767
연관어명1.0001.0001.0001.000
주간연관어언급량0.2240.7671.0001.000
2023-12-10T20:06:25.826345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간연관어연번주간연관어언급량단어속성명
주간연관어연번1.000-0.2870.084
주간연관어언급량-0.2871.0000.342
단어속성명0.0840.3421.000

Missing values

2023-12-10T20:06:20.424205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:06:20.649990image/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

주간연관어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명단어속성명연관어명주간연관어언급량
012020-01-06물환경물재난All장소4대강25
122020-01-06물환경물재난All사회이슈4대강사업9
232020-01-06물환경물재난All인물矛盾1
342020-01-06물환경물재난All장소가게9
452020-01-06물환경물재난All속성가격6
562020-01-06물환경물재난All상품가구3
672020-01-06물환경물재난All기타가꾸다3
782020-01-06물환경물재난All속성가나안1
892020-01-06물환경물재난All라이프가난5
9102020-01-06물환경물재난All속성가넷1
주간연관어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명단어속성명연관어명주간연관어언급량
90912020-01-06물환경물재난All속성감나무1
91922020-01-06물환경물재난All라이프감내2
92932020-01-06물환경물재난All속성감도1
93942020-01-06물환경물재난All라이프감동12
94952020-01-06물환경물재난All기타감만동1
95962020-01-06물환경물재난All장소감방1
96972020-01-06물환경물재난All장소감비아1
97982020-01-06물환경물재난All기타감염1
98992020-01-06물환경물재난All장소감옥3
991002020-01-06물환경물재난All상품감자2