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=94072cf0-2fd1-11ea-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
주간연관어연번 is highly overall correlated with 주간연관어언급량High correlation
주간연관어언급량 is highly overall correlated with 주간연관어연번High correlation
주간연관어연번 has unique valuesUnique
연관어명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 11:06:35.677174
Analysis finished2023-12-10 11:06:37.724239
Duration2.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주간연관어연번
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
2023-12-10T20:06:37.869263image/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
2023-12-10T20:06:38.110824image/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

2023-12-10T20:06:38.365368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:38.555354image/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

2023-12-10T20:06:38.787512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:38.989606image/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

2023-12-10T20:06:39.186941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:39.578408image/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

2023-12-10T20:06:39.755477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:39.942023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 100
100.0%

단어속성명
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
속성
28 
장소
25 
라이프
25 
시간
8 
인물
5 
Other values (4)
9 

Length

Max length6
Median length2
Mean length2.39
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row장소
2nd row장소
3rd row라이프
4th row사회이슈
5th row장소

Common Values

ValueCountFrequency (%)
속성 28
28.0%
장소 25
25.0%
라이프 25
25.0%
시간 8
 
8.0%
인물 5
 
5.0%
단체 3
 
3.0%
사회이슈 2
 
2.0%
브랜드 2
 
2.0%
엔터테인먼트 2
 
2.0%

Length

2023-12-10T20:06:40.193853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:06:40.450528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
속성 28
28.0%
장소 25
25.0%
라이프 25
25.0%
시간 8
 
8.0%
인물 5
 
5.0%
단체 3
 
3.0%
사회이슈 2
 
2.0%
브랜드 2
 
2.0%
엔터테인먼트 2
 
2.0%

연관어명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T20:06:41.050679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.34
Min length1

Characters and Unicode

Total characters234
Distinct characters144
Distinct categories3 ?
Distinct scripts3 ?
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 row서울
2nd row한국
3rd row국민
4th row4대강사업
5th row공원
ValueCountFrequency (%)
서울 1
 
1.0%
참고 1
 
1.0%
지방 1
 
1.0%
전국 1
 
1.0%
seoul 1
 
1.0%
건설 1
 
1.0%
버스 1
 
1.0%
조선 1
 
1.0%
한강대교 1
 
1.0%
수도 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T20:06:41.865794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 6
 
2.6%
인 6
 
2.6%
국 6
 
2.6%
강 6
 
2.6%
대 5
 
2.1%
사 5
 
2.1%
교 4
 
1.7%
한 4
 
1.7%
정 4
 
1.7%
도 4
 
1.7%
Other values (134) 184
78.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 223
95.3%
Decimal Number 6
 
2.6%
Lowercase Letter 5
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 6
 
2.7%
인 6
 
2.7%
국 6
 
2.7%
강 6
 
2.7%
대 5
 
2.2%
사 5
 
2.2%
교 4
 
1.8%
한 4
 
1.8%
정 4
 
1.8%
도 4
 
1.8%
Other values (124) 173
77.6%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
7 1
16.7%
0 1
16.7%
2 1
16.7%
4 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
l 1
20.0%
u 1
20.0%
o 1
20.0%
e 1
20.0%
s 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 223
95.3%
Common 6
 
2.6%
Latin 5
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 6
 
2.7%
인 6
 
2.7%
국 6
 
2.7%
강 6
 
2.7%
대 5
 
2.2%
사 5
 
2.2%
교 4
 
1.8%
한 4
 
1.8%
정 4
 
1.8%
도 4
 
1.8%
Other values (124) 173
77.6%
Common
ValueCountFrequency (%)
1 2
33.3%
7 1
16.7%
0 1
16.7%
2 1
16.7%
4 1
16.7%
Latin
ValueCountFrequency (%)
l 1
20.0%
u 1
20.0%
o 1
20.0%
e 1
20.0%
s 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 223
95.3%
ASCII 11
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 6
 
2.7%
인 6
 
2.7%
국 6
 
2.7%
강 6
 
2.7%
대 5
 
2.2%
사 5
 
2.2%
교 4
 
1.8%
한 4
 
1.8%
정 4
 
1.8%
도 4
 
1.8%
Other values (124) 173
77.6%
ASCII
ValueCountFrequency (%)
1 2
18.2%
l 1
9.1%
u 1
9.1%
o 1
9.1%
e 1
9.1%
s 1
9.1%
7 1
9.1%
0 1
9.1%
2 1
9.1%
4 1
9.1%

주간연관어언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean352.44
Minimum231
Maximum1423
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:06:42.144528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum231
5-th percentile235.95
Q1253
median287
Q3373.25
95-th percentile689.8
Maximum1423
Range1192
Interquartile range (IQR)120.25

Descriptive statistics

Standard deviation176.14568
Coefficient of variation (CV)0.49978912
Kurtosis14.469871
Mean352.44
Median Absolute Deviation (MAD)39.5
Skewness3.2781267
Sum35244
Variance31027.299
MonotonicityDecreasing
2023-12-10T20:06:42.405119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
253 4
 
4.0%
249 3
 
3.0%
247 3
 
3.0%
276 2
 
2.0%
251 2
 
2.0%
437 2
 
2.0%
250 2
 
2.0%
292 2
 
2.0%
242 2
 
2.0%
469 2
 
2.0%
Other values (68) 76
76.0%
ValueCountFrequency (%)
231 1
 
1.0%
232 1
 
1.0%
233 2
2.0%
235 1
 
1.0%
236 1
 
1.0%
237 1
 
1.0%
238 1
 
1.0%
241 2
2.0%
242 2
2.0%
247 3
3.0%
ValueCountFrequency (%)
1423 1
1.0%
951 1
1.0%
819 1
1.0%
753 1
1.0%
743 1
1.0%
687 1
1.0%
642 1
1.0%
614 1
1.0%
577 1
1.0%
565 1
1.0%

Interactions

2023-12-10T20:06:36.555331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:06:36.100450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:06:36.735060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:06:36.290127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:06:42.606411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간연관어연번단어속성명연관어명주간연관어언급량
주간연관어연번1.0000.0001.0000.747
단어속성명0.0001.0001.0000.127
연관어명1.0001.0001.0001.000
주간연관어언급량0.7470.1271.0001.000
2023-12-10T20:06:42.854631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간연관어연번주간연관어언급량단어속성명
주간연관어연번1.000-1.0000.000
주간연관어언급량-1.0001.0000.063
단어속성명0.0000.0631.000

Missing values

2023-12-10T20:06:37.025010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:06:37.256262image/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

주간연관어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명단어속성명연관어명주간연관어언급량
012017-01-02물환경하천All장소서울1423
122017-01-02물환경하천All장소한국951
232017-01-02물환경하천All라이프국민819
342017-01-02물환경하천All사회이슈4대강사업753
452017-01-02물환경하천All장소공원743
562017-01-02물환경하천All인물이명박687
672017-01-02물환경하천All시간겨울642
782017-01-02물환경하천All시간2017년614
892017-01-02물환경하천All시간새해577
9102017-01-02물환경하천All장소집565
주간연관어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명단어속성명연관어명주간연관어언급량
90912017-01-02물환경하천All속성전투241
91922017-01-02물환경하천All시간여름241
92932017-01-02물환경하천All장소인천238
93942017-01-02물환경하천All속성기본237
94952017-01-02물환경하천All속성분신236
95962017-01-02물환경하천All속성산업235
96972017-01-02물환경하천All라이프노래233
97982017-01-02물환경하천All브랜드한강성심병원233
98992017-01-02물환경하천All속성기억232
991002017-01-02물환경하천All장소공간231