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=fdecf030-2fd3-11ea-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
주간감성어연번 is highly overall correlated with 주간감성어언급량High correlation
주간감성어언급량 is highly overall correlated with 주간감성어연번High correlation
주간감성어연번 has unique valuesUnique
감성어명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:13:55.457302
Analysis finished2023-12-10 13:13:56.699411
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주간감성어연번
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
2023-12-10T22:13:56.877837image/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
2023-12-10T22:13:57.139121image/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
Minimum2017-01-02 00:00:00
Maximum2017-01-02 00:00:00
2023-12-10T22:13:57.495308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:13:57.689532image/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

2023-12-10T22:13:57.874571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:13:58.008234image/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

2023-12-10T22:13:58.159647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:13:58.309698image/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

2023-12-10T22:13:58.447167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:13:58.582120image/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
2023-12-10T22:13:59.029419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.94
Min length2

Characters and Unicode

Total characters294
Distinct characters137
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 row좋은데
2nd row멋진
3rd row새로운
4th row다양한
5th row감사합니다
ValueCountFrequency (%)
좋은데 1
 
1.0%
넉넉 1
 
1.0%
깨끗이 1
 
1.0%
더좋은 1
 
1.0%
사랑하고 1
 
1.0%
이쁘게 1
 
1.0%
쉬운 1
 
1.0%
천국 1
 
1.0%
건강하게 1
 
1.0%
시원한 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T22:13:59.924257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
한 20
 
6.8%
고 13
 
4.4%
하 12
 
4.1%
게 10
 
3.4%
다 10
 
3.4%
운 9
 
3.1%
좋 9
 
3.1%
는 8
 
2.7%
이 6
 
2.0%
적 5
 
1.7%
Other values (127) 192
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 290
98.6%
Lowercase Letter 4
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 20
 
6.9%
고 13
 
4.5%
하 12
 
4.1%
게 10
 
3.4%
다 10
 
3.4%
운 9
 
3.1%
좋 9
 
3.1%
는 8
 
2.8%
이 6
 
2.1%
적 5
 
1.7%
Other values (124) 188
64.8%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
g 1
25.0%
d 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 290
98.6%
Latin 4
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 20
 
6.9%
고 13
 
4.5%
하 12
 
4.1%
게 10
 
3.4%
다 10
 
3.4%
운 9
 
3.1%
좋 9
 
3.1%
는 8
 
2.8%
이 6
 
2.1%
적 5
 
1.7%
Other values (124) 188
64.8%
Latin
ValueCountFrequency (%)
o 2
50.0%
g 1
25.0%
d 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 290
98.6%
ASCII 4
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
한 20
 
6.9%
고 13
 
4.5%
하 12
 
4.1%
게 10
 
3.4%
다 10
 
3.4%
운 9
 
3.1%
좋 9
 
3.1%
는 8
 
2.8%
이 6
 
2.1%
적 5
 
1.7%
Other values (124) 188
64.8%
ASCII
ValueCountFrequency (%)
o 2
50.0%
g 1
25.0%
d 1
25.0%

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

2023-12-10T22:14:00.171079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:14:00.335448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
p 100
100.0%

주간감성어언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.28
Minimum26
Maximum341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:14:00.575311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile27
Q135.75
median47.5
Q377.5
95-th percentile192.3
Maximum341
Range315
Interquartile range (IQR)41.75

Descriptive statistics

Standard deviation55.934319
Coefficient of variation (CV)0.83136622
Kurtosis9.3176364
Mean67.28
Median Absolute Deviation (MAD)14.5
Skewness2.8364132
Sum6728
Variance3128.6481
MonotonicityDecreasing
2023-12-10T22:14:00.854952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27 8
 
8.0%
36 5
 
5.0%
56 4
 
4.0%
47 4
 
4.0%
45 4
 
4.0%
34 3
 
3.0%
38 3
 
3.0%
35 3
 
3.0%
42 3
 
3.0%
33 3
 
3.0%
Other values (45) 60
60.0%
ValueCountFrequency (%)
26 1
 
1.0%
27 8
8.0%
28 2
 
2.0%
30 2
 
2.0%
31 3
 
3.0%
33 3
 
3.0%
34 3
 
3.0%
35 3
 
3.0%
36 5
5.0%
37 2
 
2.0%
ValueCountFrequency (%)
341 1
1.0%
313 1
1.0%
221 1
1.0%
220 1
1.0%
217 1
1.0%
191 1
1.0%
160 1
1.0%
147 1
1.0%
132 1
1.0%
120 1
1.0%

Interactions

2023-12-10T22:13:56.027246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:13:55.733805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:13:56.177385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:13:55.887999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:14:01.027645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간감성어연번감성어명주간감성어언급량
주간감성어연번1.0001.0000.766
감성어명1.0001.0001.000
주간감성어언급량0.7661.0001.000
2023-12-10T22:14:01.176897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간감성어연번주간감성어언급량
주간감성어연번1.000-0.999
주간감성어언급량-0.9991.000

Missing values

2023-12-10T22:13:56.416423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:13:56.615001image/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

주간감성어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명감성어명감성타입주간감성어언급량
012017-01-02물환경하천All좋은데p341
122017-01-02물환경하천All멋진p313
232017-01-02물환경하천All새로운p221
342017-01-02물환경하천All다양한p220
452017-01-02물환경하천All감사합니다p217
562017-01-02물환경하천All아름다운p191
672017-01-02물환경하천All좋아요p160
782017-01-02물환경하천All고마운p147
892017-01-02물환경하천All필요한p132
9102017-01-02물환경하천All행복한p120
주간감성어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명감성어명감성타입주간감성어언급량
90912017-01-02물환경하천All뿌듯p28
91922017-01-02물환경하천All환상적p27
92932017-01-02물환경하천All탁월p27
93942017-01-02물환경하천All착한p27
94952017-01-02물환경하천All좋아해p27
95962017-01-02물환경하천All자부심p27
96972017-01-02물환경하천All부드러운p27
97982017-01-02물환경하천All낫다p27
98992017-01-02물환경하천All고운p27
991002017-01-02물환경하천All흥미p26