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=fdecf030-2fd3-11ea-94b6-73a02796bba4

Alerts

연월일 has constant value ""Constant
환경플랫폼 하위 도메인명 has constant value ""Constant
SNS 채널명 has constant value ""Constant
주간감성어연번 is highly overall correlated with 도메인 하위 카테고리명High correlation
도메인 하위 카테고리명 is highly overall correlated with 주간감성어연번High correlation
주간감성어연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 15:32:47.590123
Analysis finished2024-04-21 15:32:49.113468
Duration1.52 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
2024-04-22T00:32:49.279975image/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
2024-04-22T00:32:49.548717image/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

2024-04-22T00:32:49.779320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:32:49.938925image/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

2024-04-22T00:32:50.130300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:32:50.298236image/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 size928.0 B
물재난
53 
상수도
21 
지하수
16 
하수도
10 

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 53
53.0%
상수도 21
 
21.0%
지하수 16
 
16.0%
하수도 10
 
10.0%

Length

2024-04-22T00:32:50.467776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:32:50.640699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물재난 53
53.0%
상수도 21
 
21.0%
지하수 16
 
16.0%
하수도 10
 
10.0%

SNS 채널명
Categorical

CONSTANT 

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

2024-04-22T00:32:50.834441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:32:50.989064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 100
100.0%

감성어명
Text

Distinct76
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
2024-04-22T00:32:51.881885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3.5
Mean length2.6
Min length2

Characters and Unicode

Total characters260
Distinct characters120
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

Unique57 ?
Unique (%)57.0%

Sample

1st row감사
2nd row갖추다
3rd row거짓말
4th row거칠다
5th row걱정
ValueCountFrequency (%)
감사 3
 
3.0%
기대 3
 
3.0%
먼지 3
 
3.0%
걱정 3
 
3.0%
갖추다 3
 
3.0%
안타깝다 2
 
2.0%
노후화 2
 
2.0%
막히다 2
 
2.0%
고맙다 2
 
2.0%
우려 2
 
2.0%
Other values (66) 75
75.0%
2024-04-22T00:32:53.036729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
다 33
 
12.7%
지 8
 
3.1%
안 7
 
2.7%
전 6
 
2.3%
정 6
 
2.3%
고 6
 
2.3%
가 5
 
1.9%
성 5
 
1.9%
기 5
 
1.9%
대 5
 
1.9%
Other values (110) 174
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 260
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 33
 
12.7%
지 8
 
3.1%
안 7
 
2.7%
전 6
 
2.3%
정 6
 
2.3%
고 6
 
2.3%
가 5
 
1.9%
성 5
 
1.9%
기 5
 
1.9%
대 5
 
1.9%
Other values (110) 174
66.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 33
 
12.7%
지 8
 
3.1%
안 7
 
2.7%
전 6
 
2.3%
정 6
 
2.3%
고 6
 
2.3%
가 5
 
1.9%
성 5
 
1.9%
기 5
 
1.9%
대 5
 
1.9%
Other values (110) 174
66.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 260
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
다 33
 
12.7%
지 8
 
3.1%
안 7
 
2.7%
전 6
 
2.3%
정 6
 
2.3%
고 6
 
2.3%
가 5
 
1.9%
성 5
 
1.9%
기 5
 
1.9%
대 5
 
1.9%
Other values (110) 174
66.9%

감성타입
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size928.0 B
p
56 
n
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowp
2nd rowp
3rd rown
4th rown
5th rown

Common Values

ValueCountFrequency (%)
p 56
56.0%
n 44
44.0%

Length

2024-04-22T00:32:53.254276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:32:53.413956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
p 56
56.0%
n 44
44.0%

주간감성어언급량
Real number (ℝ)

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.04
Minimum1
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-22T00:32:53.558143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile6.05
Maximum16
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.2559461
Coefficient of variation (CV)1.1058559
Kurtosis17.935774
Mean2.04
Median Absolute Deviation (MAD)0
Skewness3.7952426
Sum204
Variance5.0892929
MonotonicityNot monotonic
2024-04-22T00:32:53.737363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 64
64.0%
2 15
 
15.0%
4 9
 
9.0%
3 6
 
6.0%
7 2
 
2.0%
6 1
 
1.0%
16 1
 
1.0%
12 1
 
1.0%
8 1
 
1.0%
ValueCountFrequency (%)
1 64
64.0%
2 15
 
15.0%
3 6
 
6.0%
4 9
 
9.0%
6 1
 
1.0%
7 2
 
2.0%
8 1
 
1.0%
12 1
 
1.0%
16 1
 
1.0%
ValueCountFrequency (%)
16 1
 
1.0%
12 1
 
1.0%
8 1
 
1.0%
7 2
 
2.0%
6 1
 
1.0%
4 9
 
9.0%
3 6
 
6.0%
2 15
 
15.0%
1 64
64.0%

Interactions

2024-04-22T00:32:48.429461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:32:48.130774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:32:48.579058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:32:48.272430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T00:32:53.890875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간감성어연번도메인 하위 카테고리명감성어명감성타입주간감성어언급량
주간감성어연번1.0000.9760.0000.0000.305
도메인 하위 카테고리명0.9761.0000.0000.0000.119
감성어명0.0000.0001.0001.0000.930
감성타입0.0000.0001.0001.0000.144
주간감성어언급량0.3050.1190.9300.1441.000
2024-04-22T00:32:54.056923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
감성타입도메인 하위 카테고리명
감성타입1.0000.000
도메인 하위 카테고리명0.0001.000
2024-04-22T00:32:54.196710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간감성어연번주간감성어언급량도메인 하위 카테고리명감성타입
주간감성어연번1.000-0.2440.8940.000
주간감성어언급량-0.2441.0000.0950.118
도메인 하위 카테고리명0.8940.0951.0000.000
감성타입0.0000.1180.0001.000

Missing values

2024-04-22T00:32:48.795207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T00:32:49.025132image/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
012020-07-01물환경물재난All감사p3
122020-07-01물환경물재난All갖추다p2
232020-07-01물환경물재난All거짓말n3
342020-07-01물환경물재난All거칠다n1
452020-07-01물환경물재난All걱정n1
562020-07-01물환경물재난All고급p1
672020-07-01물환경물재난All고맙다p1
782020-07-01물환경물재난All고통n2
892020-07-01물환경물재난All괜찮다p1
9102020-07-01물환경물재난All귀찮다n1
주간감성어연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명감성어명감성타입주간감성어언급량
90912020-07-01물환경하수도All감사p2
91922020-07-01물환경하수도All갖추다p4
92932020-07-01물환경하수도All걱정n1
93942020-07-01물환경하수도All고맙다p1
94952020-07-01물환경하수도All고통n1
95962020-07-01물환경하수도All곰팡이n1
96972020-07-01물환경하수도All기대p4
97982020-07-01물환경하수도All깨지다n1
98992020-07-01물환경하수도All난장판n1
991002020-07-01물환경하수도All노후화n1