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
Categorical5
Text1

Dataset

Description샘플 데이터
Author성균관대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=3f9648c0-2fd3-11ea-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
감성타입 has constant value ""Constant
일간감성어연번 is highly overall correlated with 일간감성어언급량High correlation
일간감성어언급량 is highly overall correlated with 일간감성어연번High correlation
일간감성어연번 has unique valuesUnique
감성어명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:07:29.382530
Analysis finished2023-12-10 12:07:30.420278
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일간감성어연번
Real number (ℝ)

HIGH CORRELATION  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
2023-12-10T21:07:30.536441image/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
2023-12-10T21:07:30.756812image/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
2017-01-02
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-01-02
2nd row2017-01-02
3rd row2017-01-02
4th row2017-01-02
5th row2017-01-02

Common Values

ValueCountFrequency (%)
2017-01-02 100
100.0%

Length

2023-12-10T21:07:30.972079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:31.100798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-01-02 100
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

2023-12-10T21:07:31.226821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:31.353140image/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
하천
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
하천 100
100.0%

Length

2023-12-10T21:07:31.509518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:31.622908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하천 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

2023-12-10T21:07:31.788599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:31.914323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 100
100.0%

감성어명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:07:32.266977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.15
Min length2

Characters and Unicode

Total characters315
Distinct characters137
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 row새로운
2nd row좋은데
3rd row다양한
4th row행복한
5th row예쁜
ValueCountFrequency (%)
새로운 1
 
1.0%
신나게 1
 
1.0%
감사드립니다 1
 
1.0%
감사하고 1
 
1.0%
공정한 1
 
1.0%
공평한 1
 
1.0%
귀여운 1
 
1.0%
긍정적 1
 
1.0%
기대하고 1
 
1.0%
다양하게 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T21:07:32.737500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
한 21
 
6.7%
고 16
 
5.1%
하 14
 
4.4%
다 12
 
3.8%
좋 11
 
3.5%
는 9
 
2.9%
운 7
 
2.2%
게 7
 
2.2%
아 5
 
1.6%
요 5
 
1.6%
Other values (127) 208
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 315
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 21
 
6.7%
고 16
 
5.1%
하 14
 
4.4%
다 12
 
3.8%
좋 11
 
3.5%
는 9
 
2.9%
운 7
 
2.2%
게 7
 
2.2%
아 5
 
1.6%
요 5
 
1.6%
Other values (127) 208
66.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 315
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 21
 
6.7%
고 16
 
5.1%
하 14
 
4.4%
다 12
 
3.8%
좋 11
 
3.5%
는 9
 
2.9%
운 7
 
2.2%
게 7
 
2.2%
아 5
 
1.6%
요 5
 
1.6%
Other values (127) 208
66.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 315
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
한 21
 
6.7%
고 16
 
5.1%
하 14
 
4.4%
다 12
 
3.8%
좋 11
 
3.5%
는 9
 
2.9%
운 7
 
2.2%
게 7
 
2.2%
아 5
 
1.6%
요 5
 
1.6%
Other values (127) 208
66.0%

감성타입
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
p 100
100.0%

Length

2023-12-10T21:07:32.874979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:32.991073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
p 100
100.0%

일간감성어언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.54
Minimum6
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:07:33.109042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6
Q16.75
median8
Q313
95-th percentile32
Maximum62
Range56
Interquartile range (IQR)6.25

Descriptive statistics

Standard deviation8.986432
Coefficient of variation (CV)0.77872027
Kurtosis11.524301
Mean11.54
Median Absolute Deviation (MAD)2
Skewness3.0161638
Sum1154
Variance80.75596
MonotonicityDecreasing
2023-12-10T21:07:33.294406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
6 25
25.0%
7 21
21.0%
8 9
 
9.0%
9 9
 
9.0%
11 4
 
4.0%
13 4
 
4.0%
14 3
 
3.0%
32 3
 
3.0%
10 3
 
3.0%
16 2
 
2.0%
Other values (13) 17
17.0%
ValueCountFrequency (%)
6 25
25.0%
7 21
21.0%
8 9
 
9.0%
9 9
 
9.0%
10 3
 
3.0%
11 4
 
4.0%
12 2
 
2.0%
13 4
 
4.0%
14 3
 
3.0%
15 2
 
2.0%
ValueCountFrequency (%)
62 1
 
1.0%
46 1
 
1.0%
35 1
 
1.0%
32 3
3.0%
26 1
 
1.0%
24 1
 
1.0%
23 1
 
1.0%
22 2
2.0%
20 2
2.0%
19 1
 
1.0%

Interactions

2023-12-10T21:07:29.874658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:29.642195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:29.999388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:29.754817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:07:33.395482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간감성어연번감성어명일간감성어언급량
일간감성어연번1.0001.0000.743
감성어명1.0001.0001.000
일간감성어언급량0.7431.0001.000
2023-12-10T21:07:33.519053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간감성어연번일간감성어언급량
일간감성어연번1.000-0.987
일간감성어언급량-0.9871.000

Missing values

2023-12-10T21:07:30.158280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:07:30.343587image/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

일간감성어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명감성어명감성타입일간감성어언급량
012017-01-02물환경하천All새로운p62
122017-01-02물환경하천All좋은데p46
232017-01-02물환경하천All다양한p35
342017-01-02물환경하천All행복한p32
452017-01-02물환경하천All예쁜p32
562017-01-02물환경하천All아름다운p32
672017-01-02물환경하천All감사합니다p26
782017-01-02물환경하천All사랑하는p24
892017-01-02물환경하천All좋아하는p23
9102017-01-02물환경하천All필요한p22
일간감성어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명감성어명감성타입일간감성어언급량
90912017-01-02물환경하천All부담없는p6
91922017-01-02물환경하천All뛰어난p6
92932017-01-02물환경하천All듬뿍p6
93942017-01-02물환경하천All녹색성장p6
94952017-01-02물환경하천All낫다p6
95962017-01-02물환경하천All귀한p6
96972017-01-02물환경하천All공평하고p6
97982017-01-02물환경하천All공정하게p6
98992017-01-02물환경하천All고맙습니다p6
991002017-01-02물환경하천All견고한p6