Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory76.3 B

Variable types

Numeric2
Categorical6
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 카테고리명High correlation
일간시도단어량 is highly overall correlated with 일간시도언급량High correlation
도메인 하위 카테고리명 is highly overall correlated with 일간지역언급량연번High correlation
일간시도언급량 is highly overall correlated with 일간시도단어량High correlation
일간시도언급량 is highly imbalanced (65.7%)Imbalance
일간지역언급량연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:43:48.350934
Analysis finished2023-12-10 12:43:49.491379
Duration1.14 second
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
2023-12-10T21:43:49.553602image/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
2023-12-10T21:43:49.670690image/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
2021-01-01
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-01
2nd row2021-01-01
3rd row2021-01-01
4th row2021-01-01
5th row2021-01-01

Common Values

ValueCountFrequency (%)
2021-01-01 100
100.0%

Length

2023-12-10T21:43:49.780284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:43:50.132673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-01 100
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

2023-12-10T21:43:50.222327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:43:50.311121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물환경 100
100.0%

도메인 하위 카테고리명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
상수도
53 
물재난
37 
하수도
6 
지하수
 
4

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 (%)
상수도 53
53.0%
물재난 37
37.0%
하수도 6
 
6.0%
지하수 4
 
4.0%

Length

2023-12-10T21:43:50.419892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:43:50.518018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도 53
53.0%
물재난 37
37.0%
하수도 6
 
6.0%
지하수 4
 
4.0%

SNS 채널명
Categorical

CONSTANT 

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

2023-12-10T21:43:50.609209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:43:50.695736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
news 100
100.0%

시도명
Categorical

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기
24 
충남
9 
강원
9 
경북
8 
충북
8 
Other values (11)
42 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기 24
24.0%
충남 9
 
9.0%
강원 9
 
9.0%
경북 8
 
8.0%
충북 8
 
8.0%
전남 7
 
7.0%
경남 6
 
6.0%
제주 5
 
5.0%
광주 4
 
4.0%
대구 4
 
4.0%
Other values (6) 16
16.0%

Length

2023-12-10T21:43:50.785935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 24
24.0%
충남 9
 
9.0%
강원 9
 
9.0%
경북 8
 
8.0%
충북 8
 
8.0%
전남 7
 
7.0%
경남 6
 
6.0%
제주 5
 
5.0%
광주 4
 
4.0%
대구 4
 
4.0%
Other values (6) 16
16.0%

시군구명
Text

Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:43:51.001859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.87
Min length2

Characters and Unicode

Total characters287
Distinct characters74
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

Unique48 ?
Unique (%)48.0%

Sample

1st row가평군
2nd row고양시
3rd row광주시
4th row남양주시
5th row성남시
ValueCountFrequency (%)
동구 6
 
6.0%
서구 5
 
5.0%
북구 5
 
5.0%
가평군 3
 
3.0%
서귀포시 3
 
3.0%
남양주시 2
 
2.0%
서천군 2
 
2.0%
횡성군 2
 
2.0%
태백시 2
 
2.0%
고양시 2
 
2.0%
Other values (58) 68
68.0%
2023-12-10T21:43:51.343432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 36
 
12.5%
시 35
 
12.2%
구 31
 
10.8%
서 13
 
4.5%
양 11
 
3.8%
동 10
 
3.5%
천 9
 
3.1%
성 9
 
3.1%
주 8
 
2.8%
평 8
 
2.8%
Other values (64) 117
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 287
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 36
 
12.5%
시 35
 
12.2%
구 31
 
10.8%
서 13
 
4.5%
양 11
 
3.8%
동 10
 
3.5%
천 9
 
3.1%
성 9
 
3.1%
주 8
 
2.8%
평 8
 
2.8%
Other values (64) 117
40.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 287
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 36
 
12.5%
시 35
 
12.2%
구 31
 
10.8%
서 13
 
4.5%
양 11
 
3.8%
동 10
 
3.5%
천 9
 
3.1%
성 9
 
3.1%
주 8
 
2.8%
평 8
 
2.8%
Other values (64) 117
40.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 287
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 36
 
12.5%
시 35
 
12.2%
구 31
 
10.8%
서 13
 
4.5%
양 11
 
3.8%
동 10
 
3.5%
천 9
 
3.1%
성 9
 
3.1%
주 8
 
2.8%
평 8
 
2.8%
Other values (64) 117
40.8%

일간시도언급량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
87 
2
10 
4
 
2
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 87
87.0%
2 10
 
10.0%
4 2
 
2.0%
3 1
 
1.0%

Length

2023-12-10T21:43:51.463825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:43:51.545622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 87
87.0%
2 10
 
10.0%
4 2
 
2.0%
3 1
 
1.0%

일간시도단어량
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:43:51.632679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q37
95-th percentile13
Maximum44
Range43
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.8663567
Coefficient of variation (CV)1.248161
Kurtosis19.322763
Mean4.7
Median Absolute Deviation (MAD)1
Skewness3.4438757
Sum470
Variance34.414141
MonotonicityNot monotonic
2023-12-10T21:43:51.731053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 43
43.0%
2 12
 
12.0%
3 7
 
7.0%
10 7
 
7.0%
13 5
 
5.0%
4 5
 
5.0%
7 5
 
5.0%
9 3
 
3.0%
5 3
 
3.0%
11 2
 
2.0%
Other values (6) 8
 
8.0%
ValueCountFrequency (%)
1 43
43.0%
2 12
 
12.0%
3 7
 
7.0%
4 5
 
5.0%
5 3
 
3.0%
6 1
 
1.0%
7 5
 
5.0%
8 1
 
1.0%
9 3
 
3.0%
10 7
 
7.0%
ValueCountFrequency (%)
44 1
 
1.0%
16 2
 
2.0%
14 1
 
1.0%
13 5
5.0%
12 2
 
2.0%
11 2
 
2.0%
10 7
7.0%
9 3
3.0%
8 1
 
1.0%
7 5
5.0%

Interactions

2023-12-10T21:43:49.173419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:43:49.041026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:43:49.239852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:43:49.107753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:43:51.804352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간지역언급량연번도메인 하위 카테고리명시도명시군구명일간시도언급량일간시도단어량
일간지역언급량연번1.0000.8950.8180.7390.2900.451
도메인 하위 카테고리명0.8951.0000.6200.0000.1540.000
시도명0.8180.6201.0000.8170.0000.000
시군구명0.7390.0000.8171.0000.9990.998
일간시도언급량0.2900.1540.0000.9991.0000.590
일간시도단어량0.4510.0000.0000.9980.5901.000
2023-12-10T21:43:51.912615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간시도언급량도메인 하위 카테고리명시도명
일간시도언급량1.0000.0590.000
도메인 하위 카테고리명0.0591.0000.312
시도명0.0000.3121.000
2023-12-10T21:43:51.993394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간지역언급량연번일간시도단어량도메인 하위 카테고리명시도명일간시도언급량
일간지역언급량연번1.0000.0070.7490.4800.169
일간시도단어량0.0071.0000.0000.0000.514
도메인 하위 카테고리명0.7490.0001.0000.3120.059
시도명0.4800.0000.3121.0000.000
일간시도언급량0.1690.5140.0590.0001.000

Missing values

2023-12-10T21:43:49.331881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:43:49.444171image/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
012021-01-01물환경물재난news경기가평군13
122021-01-01물환경물재난news경기고양시11
232021-01-01물환경물재난news경기광주시11
342021-01-01물환경물재난news경기남양주시11
452021-01-01물환경물재난news경기성남시11
562021-01-01물환경물재난news경기시흥시11
672021-01-01물환경물재난news경기양평군444
782021-01-01물환경물재난news경기연천군17
892021-01-01물환경물재난news경기하남시11
9102021-01-01물환경물재난news경남마산12
일간지역언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명시도명시군구명일간시도언급량일간시도단어량
90912021-01-01물환경지하수news경북김천시14
91922021-01-01물환경지하수news제주서귀포시22
92932021-01-01물환경지하수news제주제주시12
93942021-01-01물환경지하수news충남서산시15
94952021-01-01물환경하수도news강원양구군12
95962021-01-01물환경하수도news강원인제군110
96972021-01-01물환경하수도news강원태백시12
97982021-01-01물환경하수도news강원평창군114
98992021-01-01물환경하수도news강원횡성군11
991002021-01-01물환경하수도news경기가평군13