Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory76.3 B

Variable types

Numeric3
Categorical5
Text1

Dataset

Description샘플 데이터
Author성균관대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=369aed70-e842-11ea-a837-83d4a69b8aa7

Alerts

연월일 has constant value ""Constant
환경플랫폼 하위 도메인명 has constant value ""Constant
SNS 채널명 has constant value ""Constant
일간지역언급량연번 is highly overall correlated with 도메인 하위 카테고리명 and 1 other fieldsHigh correlation
일간시도언급량 is highly overall correlated with 일간시도단어량High correlation
일간시도단어량 is highly overall correlated with 일간시도언급량High correlation
도메인 하위 카테고리명 is highly overall correlated with 일간지역언급량연번High correlation
시도명 is highly overall correlated with 일간지역언급량연번High correlation
일간지역언급량연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 13:33:31.104556
Analysis finished2024-04-21 13:33:34.419288
Duration3.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일간지역언급량연번
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
2024-04-21T22:33:34.633517image/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
2024-04-21T22:33:35.066230image/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 size928.0 B
2020-07-01
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-07-01
2nd row2020-07-01
3rd row2020-07-01
4th row2020-07-01
5th row2020-07-01

Common Values

ValueCountFrequency (%)
2020-07-01 100
100.0%

Length

2024-04-21T22:33:35.468903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:33:35.753268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-07-01 100
100.0%

환경플랫폼 하위 도메인명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size928.0 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

2024-04-21T22:33:36.051227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:33:36.339514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물환경 100
100.0%

도메인 하위 카테고리명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
물재난
69 
지하수
12 
상수도
11 
하수도
 
6
하천
 
2

Length

Max length3
Median length3
Mean length2.98
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물재난 69
69.0%
지하수 12
 
12.0%
상수도 11
 
11.0%
하수도 6
 
6.0%
하천 2
 
2.0%

Length

2024-04-21T22:33:36.652478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:33:36.980979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물재난 69
69.0%
지하수 12
 
12.0%
상수도 11
 
11.0%
하수도 6
 
6.0%
하천 2
 
2.0%

SNS 채널명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
news
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
news 100
100.0%

Length

2024-04-21T22:33:37.324837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:33:37.614835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
news 100
100.0%

시도명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
충남
21 
부산
11 
강원
10 
경기
10 
경북
9 
Other values (10)
39 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
충남 21
21.0%
부산 11
11.0%
강원 10
10.0%
경기 10
10.0%
경북 9
9.0%
대전 7
 
7.0%
서울 6
 
6.0%
대구 5
 
5.0%
인천 5
 
5.0%
광주 4
 
4.0%
Other values (5) 12
12.0%

Length

2024-04-21T22:33:37.922539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충남 21
21.0%
부산 11
11.0%
강원 10
10.0%
경기 10
10.0%
경북 9
9.0%
대전 7
 
7.0%
서울 6
 
6.0%
대구 5
 
5.0%
인천 5
 
5.0%
광주 4
 
4.0%
Other values (5) 12
12.0%

시군구명
Text

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2024-04-21T22:33:38.725630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.76
Min length2

Characters and Unicode

Total characters276
Distinct characters69
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

Unique50 ?
Unique (%)50.0%

Sample

1st row강릉시
2nd row고성군
3rd row양양군
4th row인제군
5th row홍천군
ValueCountFrequency (%)
서구 10
 
10.0%
동구 6
 
6.0%
중구 6
 
6.0%
남구 5
 
5.0%
아산시 3
 
3.0%
청양군 3
 
3.0%
포항시 3
 
3.0%
강릉시 3
 
3.0%
공주시 3
 
3.0%
고성군 2
 
2.0%
Other values (53) 56
56.0%
2024-04-21T22:33:40.000274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 41
 
14.9%
시 32
 
11.6%
군 27
 
9.8%
서 16
 
5.8%
천 9
 
3.3%
산 8
 
2.9%
동 8
 
2.9%
양 8
 
2.9%
주 8
 
2.9%
포 6
 
2.2%
Other values (59) 113
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 276
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 41
 
14.9%
시 32
 
11.6%
군 27
 
9.8%
서 16
 
5.8%
천 9
 
3.3%
산 8
 
2.9%
동 8
 
2.9%
양 8
 
2.9%
주 8
 
2.9%
포 6
 
2.2%
Other values (59) 113
40.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 276
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 41
 
14.9%
시 32
 
11.6%
군 27
 
9.8%
서 16
 
5.8%
천 9
 
3.3%
산 8
 
2.9%
동 8
 
2.9%
양 8
 
2.9%
주 8
 
2.9%
포 6
 
2.2%
Other values (59) 113
40.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 276
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 41
 
14.9%
시 32
 
11.6%
군 27
 
9.8%
서 16
 
5.8%
천 9
 
3.3%
산 8
 
2.9%
동 8
 
2.9%
양 8
 
2.9%
주 8
 
2.9%
포 6
 
2.2%
Other values (59) 113
40.9%

일간시도언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.82
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T22:33:40.341137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile6
Maximum17
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4303635
Coefficient of variation (CV)0.63622081
Kurtosis9.4119218
Mean3.82
Median Absolute Deviation (MAD)1
Skewness2.1915929
Sum382
Variance5.9066667
MonotonicityNot monotonic
2024-04-21T22:33:40.688788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
5 31
31.0%
2 19
19.0%
4 17
17.0%
1 16
16.0%
3 7
 
7.0%
6 6
 
6.0%
12 2
 
2.0%
17 1
 
1.0%
7 1
 
1.0%
ValueCountFrequency (%)
1 16
16.0%
2 19
19.0%
3 7
 
7.0%
4 17
17.0%
5 31
31.0%
6 6
 
6.0%
7 1
 
1.0%
12 2
 
2.0%
17 1
 
1.0%
ValueCountFrequency (%)
17 1
 
1.0%
12 2
 
2.0%
7 1
 
1.0%
6 6
 
6.0%
5 31
31.0%
4 17
17.0%
3 7
 
7.0%
2 19
19.0%
1 16
16.0%

일간시도단어량
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.11
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T22:33:41.052997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median5.5
Q310
95-th percentile11.05
Maximum44
Range43
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.3003848
Coefficient of variation (CV)0.88613007
Kurtosis17.82831
Mean7.11
Median Absolute Deviation (MAD)4
Skewness3.4860706
Sum711
Variance39.694848
MonotonicityNot monotonic
2024-04-21T22:33:41.407066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
10 29
29.0%
4 25
25.0%
2 11
 
11.0%
1 9
 
9.0%
11 7
 
7.0%
6 5
 
5.0%
5 3
 
3.0%
3 2
 
2.0%
9 2
 
2.0%
19 1
 
1.0%
Other values (6) 6
 
6.0%
ValueCountFrequency (%)
1 9
 
9.0%
2 11
 
11.0%
3 2
 
2.0%
4 25
25.0%
5 3
 
3.0%
6 5
 
5.0%
7 1
 
1.0%
8 1
 
1.0%
9 2
 
2.0%
10 29
29.0%
ValueCountFrequency (%)
44 1
 
1.0%
40 1
 
1.0%
19 1
 
1.0%
14 1
 
1.0%
12 1
 
1.0%
11 7
 
7.0%
10 29
29.0%
9 2
 
2.0%
8 1
 
1.0%
7 1
 
1.0%

Interactions

2024-04-21T22:33:32.986839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:33:31.528844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:33:32.246543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:33:33.219857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:33:31.763298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:33:32.492431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:33:33.469233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:33:32.016089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:33:32.747126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T22:33:41.644823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간지역언급량연번도메인 하위 카테고리명시도명시군구명일간시도언급량일간시도단어량
일간지역언급량연번1.0000.9750.8920.7520.5720.477
도메인 하위 카테고리명0.9751.0000.5180.3180.4070.310
시도명0.8920.5181.0000.8320.5110.329
시군구명0.7520.3180.8321.0000.6670.000
일간시도언급량0.5720.4070.5110.6671.0000.948
일간시도단어량0.4770.3100.3290.0000.9481.000
2024-04-21T22:33:41.911725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명도메인 하위 카테고리명
시도명1.0000.231
도메인 하위 카테고리명0.2311.000
2024-04-21T22:33:42.152511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간지역언급량연번일간시도언급량일간시도단어량도메인 하위 카테고리명시도명
일간지역언급량연번1.000-0.1070.0300.7580.579
일간시도언급량-0.1071.0000.8590.2880.251
일간시도단어량0.0300.8591.0000.2140.147
도메인 하위 카테고리명0.7580.2880.2141.0000.231
시도명0.5790.2510.1470.2311.000

Missing values

2024-04-21T22:33:33.794066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T22:33:34.243876image/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

일간지역언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명시도명시군구명일간시도언급량일간시도단어량
012020-07-01물환경물재난news강원강릉시1744
122020-07-01물환경물재난news강원고성군36
232020-07-01물환경물재난news강원양양군710
342020-07-01물환경물재난news강원인제군22
452020-07-01물환경물재난news강원홍천군22
562020-07-01물환경물재난news강원화천군11
672020-07-01물환경물재난news강원횡성군24
782020-07-01물환경물재난news경기광주시44
892020-07-01물환경물재난news경기연천군11
9102020-07-01물환경물재난news경기용인시22
일간지역언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명시도명시군구명일간시도언급량일간시도단어량
90912020-07-01물환경지하수news충남아산시44
91922020-07-01물환경지하수news충남청양군512
92932020-07-01물환경하수도news강원강릉시24
93942020-07-01물환경하수도news경기과천시110
94952020-07-01물환경하수도news경기김포시22
95962020-07-01물환경하수도news경기양평군311
96972020-07-01물환경하수도news경북포항시14
97982020-07-01물환경하수도news충남아산시44
98992020-07-01물환경하천news강원강릉시11
991002020-07-01물환경하천news강원동해시25