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
Categorical6

Dataset

Description샘플 데이터
Author성균관대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=d58abcc0-2fca-11ea-94b6-73a02796bba4

Alerts

연월일 has constant value ""Constant
환경플랫폼 하위 도메인명 has constant value ""Constant
도메인 하위 카테고리명 has constant value ""Constant
주간지역언급량연번 is highly overall correlated with SNS 채널명 and 1 other fieldsHigh correlation
주간시도언급량 is highly overall correlated with 시군구명High correlation
SNS 채널명 is highly overall correlated with 주간지역언급량연번High correlation
시도명 is highly overall correlated with 주간지역언급량연번 and 1 other fieldsHigh correlation
시군구명 is highly overall correlated with 주간시도언급량 and 1 other fieldsHigh correlation
주간지역언급량연번 has unique valuesUnique

Reproduction

Analysis started2024-04-17 19:20:11.262084
Analysis finished2024-04-17 19:20:11.873048
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주간지역언급량연번
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
2024-04-18T04:20:11.931269image/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
2024-04-18T04:20:12.035616image/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
2020-10-05
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-10-05
2nd row2020-10-05
3rd row2020-10-05
4th row2020-10-05
5th row2020-10-05

Common Values

ValueCountFrequency (%)
2020-10-05 100
100.0%

Length

2024-04-18T04:20:12.128327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:20:12.193833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-10-05 100
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

2024-04-18T04:20:12.265443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:20:12.331168image/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

2024-04-18T04:20:12.400083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:20:12.464939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물재난 100
100.0%

SNS 채널명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
All
57 
blog
43 

Length

Max length4
Median length3
Mean length3.43
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
All 57
57.0%
blog 43
43.0%

Length

2024-04-18T04:20:12.535479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:20:12.608322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 57
57.0%
blog 43
43.0%

시도명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기
20 
부산
12 
강원
8 
서울
8 
경북
6 
Other values (11)
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row강원
2nd row강원
3rd row강원
4th row강원
5th row경기

Common Values

ValueCountFrequency (%)
경기 20
20.0%
부산 12
12.0%
강원 8
 
8.0%
서울 8
 
8.0%
경북 6
 
6.0%
광주 6
 
6.0%
대구 6
 
6.0%
충북 6
 
6.0%
전남 5
 
5.0%
경남 4
 
4.0%
Other values (6) 19
19.0%

Length

2024-04-18T04:20:12.679992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 20
20.0%
부산 12
12.0%
강원 8
 
8.0%
서울 8
 
8.0%
경북 6
 
6.0%
광주 6
 
6.0%
대구 6
 
6.0%
충북 6
 
6.0%
전남 5
 
5.0%
경남 4
 
4.0%
Other values (6) 19
19.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
동구
12 
북구
10 
서구
10 
강서구
 
4
창녕군
 
2
Other values (38)
62 

Length

Max length4
Median length3
Mean length2.68
Min length2

Unique

Unique14 ?
Unique (%)14.0%

Sample

1st row삼척시
2nd row영월군
3rd row철원군
4th row춘천시
5th row가평군

Common Values

ValueCountFrequency (%)
동구 12
 
12.0%
북구 10
 
10.0%
서구 10
 
10.0%
강서구 4
 
4.0%
창녕군 2
 
2.0%
포천시 2
 
2.0%
파주시 2
 
2.0%
일산 2
 
2.0%
연천군 2
 
2.0%
양주시 2
 
2.0%
Other values (33) 52
52.0%

Length

2024-04-18T04:20:12.773952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
동구 12
 
12.0%
서구 10
 
10.0%
북구 10
 
10.0%
강서구 4
 
4.0%
가평군 2
 
2.0%
영양군 2
 
2.0%
영월군 2
 
2.0%
사하구 2
 
2.0%
수영구 2
 
2.0%
강동구 2
 
2.0%
Other values (33) 52
52.0%

주간시도언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.74
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-18T04:20:12.859212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile11
Maximum11
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2648109
Coefficient of variation (CV)0.68877866
Kurtosis-0.89771439
Mean4.74
Median Absolute Deviation (MAD)3
Skewness0.52272247
Sum474
Variance10.65899
MonotonicityNot monotonic
2024-04-18T04:20:12.954053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
7 23
23.0%
1 21
21.0%
3 14
14.0%
2 13
13.0%
11 10
10.0%
4 6
 
6.0%
5 4
 
4.0%
6 4
 
4.0%
9 2
 
2.0%
10 2
 
2.0%
ValueCountFrequency (%)
1 21
21.0%
2 13
13.0%
3 14
14.0%
4 6
 
6.0%
5 4
 
4.0%
6 4
 
4.0%
7 23
23.0%
8 1
 
1.0%
9 2
 
2.0%
10 2
 
2.0%
ValueCountFrequency (%)
11 10
10.0%
10 2
 
2.0%
9 2
 
2.0%
8 1
 
1.0%
7 23
23.0%
6 4
 
4.0%
5 4
 
4.0%
4 6
 
6.0%
3 14
14.0%
2 13
13.0%

Interactions

2024-04-18T04:20:11.594029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:20:11.461084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:20:11.650318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:20:11.527094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T04:20:13.018029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간지역언급량연번SNS 채널명시도명시군구명주간시도언급량
주간지역언급량연번1.0000.9970.8620.0000.446
SNS 채널명0.9971.0000.0000.0000.000
시도명0.8620.0001.0000.9530.828
시군구명0.0000.0000.9531.0001.000
주간시도언급량0.4460.0000.8281.0001.000
2024-04-18T04:20:13.092415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명SNS 채널명
시도명1.0000.5380.000
시군구명0.5381.0000.000
SNS 채널명0.0000.0001.000
2024-04-18T04:20:13.158219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간지역언급량연번주간시도언급량SNS 채널명시도명시군구명
주간지역언급량연번1.0000.1170.9120.5480.000
주간시도언급량0.1171.0000.0000.4930.796
SNS 채널명0.9120.0001.0000.0000.000
시도명0.5480.4930.0001.0000.538
시군구명0.0000.7960.0000.5381.000

Missing values

2024-04-18T04:20:11.728974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T04:20:11.835635image/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

주간지역언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명시도명시군구명주간시도언급량
012020-10-05물환경물재난All강원삼척시1
122020-10-05물환경물재난All강원영월군1
232020-10-05물환경물재난All강원철원군4
342020-10-05물환경물재난All강원춘천시1
452020-10-05물환경물재난All경기가평군4
562020-10-05물환경물재난All경기광주시2
672020-10-05물환경물재난All경기동두천시3
782020-10-05물환경물재난All경기안성시5
892020-10-05물환경물재난All경기양주시3
9102020-10-05물환경물재난All경기연천군3
주간지역언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명시도명시군구명주간시도언급량
90912020-10-05물환경물재난blog서울강동구9
91922020-10-05물환경물재난blog서울강서구1
92932020-10-05물환경물재난blog서울서초구2
93942020-10-05물환경물재난blog서울용산구2
94952020-10-05물환경물재난blog울산동구7
95962020-10-05물환경물재난blog울산북구11
96972020-10-05물환경물재난blog인천동구7
97982020-10-05물환경물재난blog인천서구7
98992020-10-05물환경물재난blog전남고흥군3
991002020-10-05물환경물재난blog전남곡성군2