Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory81.4 B

Variable types

Numeric5
DateTime1
Categorical2
Text1

Dataset

Description샘플 데이터
Author성균관대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=98e41c80-2fd4-11ea-94b6-73a02796bba4

Alerts

연월일 has constant value ""Constant
주간언급량연번 is highly overall correlated with 환경플랫폼 하위 도메인명High correlation
긍정언급량 is highly overall correlated with 부정언급량 and 2 other fieldsHigh correlation
부정언급량 is highly overall correlated with 긍정언급량 and 3 other fieldsHigh correlation
중립언급량 is highly overall correlated with 긍정언급량 and 2 other fieldsHigh correlation
총언급량 is highly overall correlated with 긍정언급량 and 2 other fieldsHigh correlation
환경플랫폼 하위 도메인명 is highly overall correlated with 주간언급량연번 and 1 other fieldsHigh correlation
주간언급량연번 has unique valuesUnique

Reproduction

Analysis started2024-04-17 04:41:36.317411
Analysis finished2024-04-17 04:41:38.313971
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주간언급량연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-17T13:41:38.363999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2024-04-17T13:41:38.459244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

연월일
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2020-10-05 00:00:00
Maximum2020-10-05 00:00:00
2024-04-17T13:41:38.543267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:38.612465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

환경플랫폼 하위 도메인명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
물환경
12 
자연환경
12 
생활환경
6 

Length

Max length4
Median length4
Mean length3.6
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물환경 12
40.0%
자연환경 12
40.0%
생활환경 6
20.0%

Length

2024-04-17T13:41:38.711572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:41:38.812792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물환경 12
40.0%
자연환경 12
40.0%
생활환경 6
20.0%

도메인 하위 카테고리명
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-17T13:41:38.952158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8
Min length2

Characters and Unicode

Total characters84
Distinct characters25
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

Unique0 ?
Unique (%)0.0%

Sample

1st row물재난
2nd row물재난
3rd row상수도
4th row상수도
5th row지하수
ValueCountFrequency (%)
물재난 2
 
6.7%
상수도 2
 
6.7%
지하수 2
 
6.7%
하수도 2
 
6.7%
하천 2
 
6.7%
호소 2
 
6.7%
대기 2
 
6.7%
폐기물 2
 
6.7%
화학물질 2
 
6.7%
기상변화 2
 
6.7%
Other values (5) 10
33.3%
2024-04-17T13:41:39.210965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 8
 
9.5%
지 6
 
7.1%
화 6
 
7.1%
하 6
 
7.1%
물 6
 
7.1%
수 6
 
7.1%
도 4
 
4.8%
질 4
 
4.8%
상 4
 
4.8%
변 4
 
4.8%
Other values (15) 30
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 8
 
9.5%
지 6
 
7.1%
화 6
 
7.1%
하 6
 
7.1%
물 6
 
7.1%
수 6
 
7.1%
도 4
 
4.8%
질 4
 
4.8%
상 4
 
4.8%
변 4
 
4.8%
Other values (15) 30
35.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 8
 
9.5%
지 6
 
7.1%
화 6
 
7.1%
하 6
 
7.1%
물 6
 
7.1%
수 6
 
7.1%
도 4
 
4.8%
질 4
 
4.8%
상 4
 
4.8%
변 4
 
4.8%
Other values (15) 30
35.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 8
 
9.5%
지 6
 
7.1%
화 6
 
7.1%
하 6
 
7.1%
물 6
 
7.1%
수 6
 
7.1%
도 4
 
4.8%
질 4
 
4.8%
상 4
 
4.8%
변 4
 
4.8%
Other values (15) 30
35.7%

SNS 채널명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
All
15 
blog
15 

Length

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

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
All 15
50.0%
blog 15
50.0%

Length

2024-04-17T13:41:39.316125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:41:39.391353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 15
50.0%
blog 15
50.0%

긍정언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1094.7333
Minimum167
Maximum2598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-17T13:41:39.461152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum167
5-th percentile171.95
Q1323.5
median825
Q31895.25
95-th percentile2570.1
Maximum2598
Range2431
Interquartile range (IQR)1571.75

Descriptive statistics

Standard deviation873.42019
Coefficient of variation (CV)0.7978383
Kurtosis-1.0010992
Mean1094.7333
Median Absolute Deviation (MAD)567
Skewness0.71394811
Sum32842
Variance762862.82
MonotonicityNot monotonic
2024-04-17T13:41:39.774033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
718 2
 
6.7%
302 2
 
6.7%
178 2
 
6.7%
230 2
 
6.7%
2598 2
 
6.7%
828 2
 
6.7%
825 2
 
6.7%
2536 2
 
6.7%
812 2
 
6.7%
970 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
167 2
6.7%
178 2
6.7%
230 2
6.7%
302 2
6.7%
388 2
6.7%
718 2
6.7%
812 2
6.7%
825 2
6.7%
828 2
6.7%
970 2
6.7%
ValueCountFrequency (%)
2598 2
6.7%
2536 2
6.7%
2414 2
6.7%
2063 2
6.7%
1392 2
6.7%
970 2
6.7%
828 2
6.7%
825 2
6.7%
812 2
6.7%
718 2
6.7%

부정언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean523.13333
Minimum62
Maximum1317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-17T13:41:39.856584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62
5-th percentile77.3
Q1162.75
median498
Q3850.5
95-th percentile1190.55
Maximum1317
Range1255
Interquartile range (IQR)687.75

Descriptive statistics

Standard deviation390.02049
Coefficient of variation (CV)0.745547
Kurtosis-0.90946045
Mean523.13333
Median Absolute Deviation (MAD)344
Skewness0.54887541
Sum15694
Variance152115.98
MonotonicityNot monotonic
2024-04-17T13:41:39.943259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
335 2
 
6.7%
189 2
 
6.7%
62 2
 
6.7%
154 2
 
6.7%
960 2
 
6.7%
231 2
 
6.7%
508 2
 
6.7%
1317 2
 
6.7%
498 2
 
6.7%
616 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
62 2
6.7%
96 2
6.7%
151 2
6.7%
154 2
6.7%
189 2
6.7%
231 2
6.7%
335 2
6.7%
498 2
6.7%
508 2
6.7%
616 2
6.7%
ValueCountFrequency (%)
1317 2
6.7%
1036 2
6.7%
960 2
6.7%
854 2
6.7%
840 2
6.7%
616 2
6.7%
508 2
6.7%
498 2
6.7%
335 2
6.7%
231 2
6.7%

중립언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45294
Minimum9205
Maximum113384
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-17T13:41:40.034792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9205
5-th percentile10061.8
Q114814.5
median29522
Q380401
95-th percentile107806.7
Maximum113384
Range104179
Interquartile range (IQR)65586.5

Descriptive statistics

Standard deviation36297.693
Coefficient of variation (CV)0.80137972
Kurtosis-0.93331191
Mean45294
Median Absolute Deviation (MAD)18234
Skewness0.82227257
Sum1358820
Variance1.3175225 × 109
MonotonicityNot monotonic
2024-04-17T13:41:40.119071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
29522 2
 
6.7%
13155 2
 
6.7%
9205 2
 
6.7%
11109 2
 
6.7%
113384 2
 
6.7%
29132 2
 
6.7%
30767 2
 
6.7%
99689 2
 
6.7%
26880 2
 
6.7%
37308 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
9205 2
6.7%
11109 2
6.7%
11288 2
6.7%
13155 2
6.7%
19793 2
6.7%
26880 2
6.7%
29132 2
6.7%
29522 2
6.7%
30767 2
6.7%
37308 2
6.7%
ValueCountFrequency (%)
113384 2
6.7%
100990 2
6.7%
99689 2
6.7%
87208 2
6.7%
59980 2
6.7%
37308 2
6.7%
30767 2
6.7%
29522 2
6.7%
29132 2
6.7%
26880 2
6.7%

총언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46911.867
Minimum9445
Maximum116942
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-17T13:41:40.202995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9445
5-th percentile10366.6
Q115317.5
median30575
Q383146.75
95-th percentile111316.1
Maximum116942
Range107497
Interquartile range (IQR)67829.25

Descriptive statistics

Standard deviation37531.204
Coefficient of variation (CV)0.80003647
Kurtosis-0.94339141
Mean46911.867
Median Absolute Deviation (MAD)19024
Skewness0.81559851
Sum1407356
Variance1.4085913 × 109
MonotonicityNot monotonic
2024-04-17T13:41:40.290398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
30575 2
 
6.7%
13646 2
 
6.7%
9445 2
 
6.7%
11493 2
 
6.7%
116942 2
 
6.7%
30191 2
 
6.7%
32100 2
 
6.7%
103542 2
 
6.7%
28190 2
 
6.7%
38894 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
9445 2
6.7%
11493 2
6.7%
11551 2
6.7%
13646 2
6.7%
20332 2
6.7%
28190 2
6.7%
30191 2
6.7%
30575 2
6.7%
32100 2
6.7%
38894 2
6.7%
ValueCountFrequency (%)
116942 2
6.7%
104440 2
6.7%
103542 2
6.7%
90125 2
6.7%
62212 2
6.7%
38894 2
6.7%
32100 2
6.7%
30575 2
6.7%
30191 2
6.7%
28190 2
6.7%

Interactions

2024-04-17T13:41:37.815942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:36.545442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:36.861781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.188785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.515181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.880815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:36.610560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:36.933160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.260553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.577252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.939644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:36.668056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:36.992428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.324757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.638980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:38.013463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:36.732275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.056588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.388692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.699908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:38.077298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:36.792033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.120784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.452924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T13:41:37.757778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T13:41:40.356757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간언급량연번환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
주간언급량연번1.0001.0000.9690.0000.7500.8110.6750.675
환경플랫폼 하위 도메인명1.0001.0001.0000.0000.8110.8620.5130.513
도메인 하위 카테고리명0.9691.0001.0000.0001.0001.0001.0001.000
SNS 채널명0.0000.0000.0001.0000.0000.0000.0000.000
긍정언급량0.7500.8111.0000.0001.0000.9210.9270.927
부정언급량0.8110.8621.0000.0000.9211.0000.8140.814
중립언급량0.6750.5131.0000.0000.9270.8141.0001.000
총언급량0.6750.5131.0000.0000.9270.8141.0001.000
2024-04-17T13:41:40.449180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환경플랫폼 하위 도메인명SNS 채널명
환경플랫폼 하위 도메인명1.0000.000
SNS 채널명0.0001.000
2024-04-17T13:41:40.518782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주간언급량연번긍정언급량부정언급량중립언급량총언급량환경플랫폼 하위 도메인명SNS 채널명
주간언급량연번1.0000.2100.2210.2710.2710.8610.000
긍정언급량0.2101.0000.9540.9680.9680.4090.000
부정언급량0.2210.9541.0000.9570.9570.7390.000
중립언급량0.2710.9680.9571.0001.0000.3980.000
총언급량0.2710.9680.9571.0001.0000.3980.000
환경플랫폼 하위 도메인명0.8610.4090.7390.3980.3981.0000.000
SNS 채널명0.0000.0000.0000.0000.0000.0001.000

Missing values

2024-04-17T13:41:38.164364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T13:41:38.271508image/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

주간언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
012020-10-05물환경물재난All7183352952230575
122020-10-05물환경물재난blog7183352952230575
232020-10-05물환경상수도All3021891315513646
342020-10-05물환경상수도blog3021891315513646
452020-10-05물환경지하수All1786292059445
562020-10-05물환경지하수blog1786292059445
672020-10-05물환경하수도All2301541110911493
782020-10-05물환경하수도blog2301541110911493
892020-10-05물환경하천All2598960113384116942
9102020-10-05물환경하천blog2598960113384116942
주간언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
20212020-10-05자연환경기후변화All13928405998062212
21222020-10-05자연환경기후변화blog13928405998062212
22232020-10-05자연환경생태계All20638548720890125
23242020-10-05자연환경생태계blog20638548720890125
24252020-10-05자연환경지질All3881511979320332
25262020-10-05자연환경지질blog3881511979320332
26272020-10-05자연환경지형All24141036100990104440
27282020-10-05자연환경지형blog24141036100990104440
28292020-10-05자연환경토양All167961128811551
29302020-10-05자연환경토양blog167961128811551