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
Categorical3
Text1

Dataset

Description샘플 데이터
Author성균관대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=663752c0-2fb1-11ea-94b6-73a02796bba4

Alerts

연월일 has constant value ""Constant
일간언급량연번 is highly overall correlated with 환경플랫폼 하위 도메인명 and 1 other fieldsHigh correlation
긍정언급량 is highly overall correlated with 부정언급량 and 3 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 일간언급량연번 and 2 other fieldsHigh correlation
SNS 채널명 is highly overall correlated with 일간언급량연번High correlation
일간언급량연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:25:50.987852
Analysis finished2023-12-10 13:25:56.700255
Duration5.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일간언급량연번
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
2023-12-10T22:25:56.818172image/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
2023-12-10T22:25:57.153741image/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
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2020-07-01
30 

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 30
100.0%

Length

2023-12-10T22:25:57.496375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:25:57.646097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-07-01 30
100.0%

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

2023-12-10T22:25:57.809853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:25:57.968671image/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
2023-12-10T22:25:58.265647image/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 row상수도
3rd row지하수
4th row하수도
5th row하천
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%
2023-12-10T22:25:58.783420image/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

HIGH CORRELATION 

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 rowAll
3rd rowAll
4th rowAll
5th rowAll

Common Values

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

Length

2023-12-10T22:25:58.979188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:25:59.144290image/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%
Mean187.8
Minimum11
Maximum559
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:25:59.312258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11.45
Q153.25
median134
Q3297.75
95-th percentile484.3
Maximum559
Range548
Interquartile range (IQR)244.5

Descriptive statistics

Standard deviation156.77755
Coefficient of variation (CV)0.83481123
Kurtosis0.10695817
Mean187.8
Median Absolute Deviation (MAD)88
Skewness0.88453582
Sum5634
Variance24579.2
MonotonicityNot monotonic
2023-12-10T22:25:59.485895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
102 2
 
6.7%
12 2
 
6.7%
11 2
 
6.7%
63 2
 
6.7%
303 2
 
6.7%
134 2
 
6.7%
282 2
 
6.7%
337 2
 
6.7%
127 2
 
6.7%
176 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
11 2
6.7%
12 2
6.7%
46 2
6.7%
50 2
6.7%
63 2
6.7%
102 2
6.7%
127 2
6.7%
134 2
6.7%
176 2
6.7%
222 2
6.7%
ValueCountFrequency (%)
559 2
6.7%
393 2
6.7%
337 2
6.7%
303 2
6.7%
282 2
6.7%
222 2
6.7%
176 2
6.7%
134 2
6.7%
127 2
6.7%
102 2
6.7%

부정언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.666667
Minimum7
Maximum217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:25:59.666395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7.45
Q117.25
median88
Q3134.25
95-th percentile208.45
Maximum217
Range210
Interquartile range (IQR)117

Descriptive statistics

Standard deviation72.320805
Coefficient of variation (CV)0.81564818
Kurtosis-1.1047633
Mean88.666667
Median Absolute Deviation (MAD)64
Skewness0.47402741
Sum2660
Variance5230.2989
MonotonicityNot monotonic
2023-12-10T22:25:59.956703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
42 2
 
6.7%
12 2
 
6.7%
8 2
 
6.7%
15 2
 
6.7%
113 2
 
6.7%
53 2
 
6.7%
140 2
 
6.7%
194 2
 
6.7%
102 2
 
6.7%
117 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
7 2
6.7%
8 2
6.7%
12 2
6.7%
15 2
6.7%
24 2
6.7%
42 2
6.7%
53 2
6.7%
88 2
6.7%
102 2
6.7%
113 2
6.7%
ValueCountFrequency (%)
217 2
6.7%
198 2
6.7%
194 2
6.7%
140 2
6.7%
117 2
6.7%
113 2
6.7%
102 2
6.7%
88 2
6.7%
53 2
6.7%
42 2
6.7%

중립언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7064.7333
Minimum820
Maximum20391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:26:00.150898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum820
5-th percentile911.35
Q11735.5
median5198
Q311768.25
95-th percentile18114.9
Maximum20391
Range19571
Interquartile range (IQR)10032.75

Descriptive statistics

Standard deviation6009.7085
Coefficient of variation (CV)0.85066317
Kurtosis-0.33689165
Mean7064.7333
Median Absolute Deviation (MAD)3756
Skewness0.87566041
Sum211942
Variance36116596
MonotonicityNot monotonic
2023-12-10T22:26:00.358832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3436 2
 
6.7%
1023 2
 
6.7%
820 2
 
6.7%
2289 2
 
6.7%
12608 2
 
6.7%
5198 2
 
6.7%
9249 2
 
6.7%
15333 2
 
6.7%
4554 2
 
6.7%
6468 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
820 2
6.7%
1023 2
6.7%
1442 2
6.7%
1551 2
6.7%
2289 2
6.7%
3436 2
6.7%
4554 2
6.7%
5198 2
6.7%
6468 2
6.7%
6891 2
6.7%
ValueCountFrequency (%)
20391 2
6.7%
15333 2
6.7%
14718 2
6.7%
12608 2
6.7%
9249 2
6.7%
6891 2
6.7%
6468 2
6.7%
5198 2
6.7%
4554 2
6.7%
3436 2
6.7%

총언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7341.2
Minimum839
Maximum21167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:26:00.565476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum839
5-th percentile932.6
Q11807.5
median5385
Q312185.75
95-th percentile18780.65
Maximum21167
Range20328
Interquartile range (IQR)10378.25

Descriptive statistics

Standard deviation6233.1877
Coefficient of variation (CV)0.84906932
Kurtosis-0.3371796
Mean7341.2
Median Absolute Deviation (MAD)3886
Skewness0.87030882
Sum220236
Variance38852629
MonotonicityNot monotonic
2023-12-10T22:26:00.763641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3580 2
 
6.7%
1047 2
 
6.7%
839 2
 
6.7%
2367 2
 
6.7%
13024 2
 
6.7%
5385 2
 
6.7%
9671 2
 
6.7%
15864 2
 
6.7%
4783 2
 
6.7%
6761 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
839 2
6.7%
1047 2
6.7%
1499 2
6.7%
1621 2
6.7%
2367 2
6.7%
3580 2
6.7%
4783 2
6.7%
5385 2
6.7%
6761 2
6.7%
7201 2
6.7%
ValueCountFrequency (%)
21167 2
6.7%
15864 2
6.7%
15309 2
6.7%
13024 2
6.7%
9671 2
6.7%
7201 2
6.7%
6761 2
6.7%
5385 2
6.7%
4783 2
6.7%
3580 2
6.7%

Interactions

2023-12-10T22:25:54.918244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:51.516882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:52.528096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:53.360343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:54.078871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:55.060859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:51.796190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:52.692469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:53.488842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:54.223589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:55.212993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:51.996454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:52.822415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:53.637166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:54.446475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:55.347796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:52.117773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:52.950802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:53.749629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:54.605602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:55.634172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:52.341647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:53.205552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:53.907043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:25:54.764881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:26:00.939856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간언급량연번환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
일간언급량연번1.0001.0000.0001.0000.3670.0000.0000.000
환경플랫폼 하위 도메인명1.0001.0001.0000.0000.7430.9670.6600.660
도메인 하위 카테고리명0.0001.0001.0000.0001.0001.0001.0001.000
SNS 채널명1.0000.0000.0001.0000.0000.0000.0000.000
긍정언급량0.3670.7431.0000.0001.0000.9480.9830.983
부정언급량0.0000.9671.0000.0000.9481.0000.9460.946
중립언급량0.0000.6601.0000.0000.9830.9461.0001.000
총언급량0.0000.6601.0000.0000.9830.9461.0001.000
2023-12-10T22:26:01.138570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SNS 채널명환경플랫폼 하위 도메인명
SNS 채널명1.0000.000
환경플랫폼 하위 도메인명0.0001.000
2023-12-10T22:26:01.650445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간언급량연번긍정언급량부정언급량중립언급량총언급량환경플랫폼 하위 도메인명SNS 채널명
일간언급량연번1.0000.1710.1660.1690.1690.8610.845
긍정언급량0.1711.0000.9390.9930.9930.5760.000
부정언급량0.1660.9391.0000.9500.9500.6880.000
중립언급량0.1690.9930.9501.0001.0000.4920.000
총언급량0.1690.9930.9501.0001.0000.4920.000
환경플랫폼 하위 도메인명0.8610.5760.6880.4920.4921.0000.000
SNS 채널명0.8450.0000.0000.0000.0000.0001.000

Missing values

2023-12-10T22:25:56.072052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:25:56.585707image/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

일간언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
012020-07-01물환경물재난All1024234363580
122020-07-01물환경상수도All121210231047
232020-07-01물환경지하수All118820839
342020-07-01물환경하수도All631522892367
452020-07-01물환경하천All3031131260813024
562020-07-01물환경호소All1345351985385
672020-07-01생활환경대기All28214092499671
782020-07-01생활환경폐기물All3371941533315864
892020-07-01생활환경화학물질All12710245544783
9102020-07-01자연환경기상변화All17611764686761
일간언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
20212020-07-01물환경호소blog1345351985385
21222020-07-01생활환경대기blog28214092499671
22232020-07-01생활환경폐기물blog3371941533315864
23242020-07-01생활환경화학물질blog12710245544783
24252020-07-01자연환경기상변화blog17611764686761
25262020-07-01자연환경기후변화blog3931981471815309
26272020-07-01자연환경생태계blog2228868917201
27282020-07-01자연환경지질blog50714421499
28292020-07-01자연환경지형blog5592172039121167
29302020-07-01자연환경토양blog462415511621