Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory78.3 B

Variable types

Numeric5
Categorical4

Dataset

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

Alerts

환경플랫폼 하위 도메인명 has constant value ""Constant
일간언급량연번 is highly overall correlated with 긍정언급량 and 5 other fieldsHigh correlation
긍정언급량 is highly overall correlated with 일간언급량연번 and 4 other fieldsHigh correlation
부정언급량 is highly overall correlated with 일간언급량연번 and 3 other fieldsHigh correlation
중립언급량 is highly overall correlated with 일간언급량연번 and 3 other fieldsHigh correlation
총언급량 is highly overall correlated with 일간언급량연번 and 4 other fieldsHigh correlation
도메인 하위 카테고리명 is highly overall correlated with 일간언급량연번High correlation
SNS 채널명 is highly overall correlated with 일간언급량연번 and 2 other fieldsHigh correlation
일간언급량연번 has unique valuesUnique
긍정언급량 has 6 (6.0%) zerosZeros
부정언급량 has 12 (12.0%) zerosZeros
중립언급량 has 2 (2.0%) zerosZeros
총언급량 has 2 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:26:24.358128
Analysis finished2023-12-10 13:26:30.686564
Duration6.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일간언급량연번
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
2023-12-10T22:26:30.829016image/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
2023-12-10T22:26:31.097691image/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

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2017-01-02
15 
2017-01-03
15 
2017-01-04
14 
2017-01-05
14 
2017-01-06
14 
Other values (2)
28 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-01-02
2nd row2017-01-03
3rd row2017-01-04
4th row2017-01-05
5th row2017-01-06

Common Values

ValueCountFrequency (%)
2017-01-02 15
15.0%
2017-01-03 15
15.0%
2017-01-04 14
14.0%
2017-01-05 14
14.0%
2017-01-06 14
14.0%
2017-01-07 14
14.0%
2017-01-08 14
14.0%

Length

2023-12-10T22:26:31.325425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:26:31.501965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-01-02 15
15.0%
2017-01-03 15
15.0%
2017-01-04 14
14.0%
2017-01-05 14
14.0%
2017-01-06 14
14.0%
2017-01-07 14
14.0%
2017-01-08 14
14.0%

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

2023-12-10T22:26:31.718871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:26:31.970409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물환경 100
100.0%

도메인 하위 카테고리명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
하천
42 
호소
42 
지하수
16 

Length

Max length3
Median length2
Mean length2.16
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
하천 42
42.0%
호소 42
42.0%
지하수 16
 
16.0%

Length

2023-12-10T22:26:32.127780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:26:32.269352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하천 42
42.0%
호소 42
42.0%
지하수 16
 
16.0%

SNS 채널명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
All
21 
Twitter
21 
Facebook
16 
Instagram
14 
blog
14 

Length

Max length9
Median length7
Mean length6.46
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
All 21
21.0%
Twitter 21
21.0%
Facebook 16
16.0%
Instagram 14
14.0%
blog 14
14.0%
community 14
14.0%

Length

2023-12-10T22:26:32.514997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:26:32.747773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 21
21.0%
twitter 21
21.0%
facebook 16
16.0%
instagram 14
14.0%
blog 14
14.0%
community 14
14.0%

긍정언급량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean155.64
Minimum0
Maximum855
Zeros6
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:26:32.972455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median102.5
Q3208.75
95-th percentile639.1
Maximum855
Range855
Interquartile range (IQR)202.75

Descriptive statistics

Standard deviation194.35049
Coefficient of variation (CV)1.2487181
Kurtosis2.7908519
Mean155.64
Median Absolute Deviation (MAD)97
Skewness1.7362787
Sum15564
Variance37772.112
MonotonicityNot monotonic
2023-12-10T22:26:33.356607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 7
 
7.0%
0 6
 
6.0%
2 4
 
4.0%
1 4
 
4.0%
6 3
 
3.0%
5 3
 
3.0%
22 2
 
2.0%
381 2
 
2.0%
103 2
 
2.0%
189 2
 
2.0%
Other values (63) 65
65.0%
ValueCountFrequency (%)
0 6
6.0%
1 4
4.0%
2 4
4.0%
3 7
7.0%
5 3
3.0%
6 3
3.0%
7 1
 
1.0%
8 1
 
1.0%
14 1
 
1.0%
17 1
 
1.0%
ValueCountFrequency (%)
855 1
1.0%
821 1
1.0%
670 1
1.0%
660 1
1.0%
641 1
1.0%
639 1
1.0%
630 1
1.0%
431 1
1.0%
406 1
1.0%
405 1
1.0%

부정언급량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct62
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.65
Minimum0
Maximum439
Zeros12
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:26:33.666422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median25
Q385
95-th percentile289.15
Maximum439
Range439
Interquartile range (IQR)82

Descriptive statistics

Standard deviation92.796114
Coefficient of variation (CV)1.4579122
Kurtosis4.0791493
Mean63.65
Median Absolute Deviation (MAD)24
Skewness2.0790053
Sum6365
Variance8611.1187
MonotonicityNot monotonic
2023-12-10T22:26:34.069311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
12.0%
1 7
 
7.0%
7 5
 
5.0%
3 4
 
4.0%
10 4
 
4.0%
34 3
 
3.0%
2 3
 
3.0%
13 2
 
2.0%
81 2
 
2.0%
26 2
 
2.0%
Other values (52) 56
56.0%
ValueCountFrequency (%)
0 12
12.0%
1 7
7.0%
2 3
 
3.0%
3 4
 
4.0%
4 1
 
1.0%
5 2
 
2.0%
7 5
5.0%
8 1
 
1.0%
9 1
 
1.0%
10 4
 
4.0%
ValueCountFrequency (%)
439 1
1.0%
367 1
1.0%
336 1
1.0%
319 1
1.0%
292 1
1.0%
289 1
1.0%
283 1
1.0%
278 1
1.0%
209 1
1.0%
197 1
1.0%

중립언급량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct78
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean339.22
Minimum0
Maximum1744
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:26:34.433160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.95
Q113
median109.5
Q3515.75
95-th percentile1512.95
Maximum1744
Range1744
Interquartile range (IQR)502.75

Descriptive statistics

Standard deviation492.23778
Coefficient of variation (CV)1.4510871
Kurtosis1.19401
Mean339.22
Median Absolute Deviation (MAD)100.5
Skewness1.5639817
Sum33922
Variance242298.03
MonotonicityNot monotonic
2023-12-10T22:26:34.798750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 4
 
4.0%
4 4
 
4.0%
9 4
 
4.0%
3 3
 
3.0%
18 3
 
3.0%
16 2
 
2.0%
118 2
 
2.0%
1 2
 
2.0%
17 2
 
2.0%
105 2
 
2.0%
Other values (68) 72
72.0%
ValueCountFrequency (%)
0 2
2.0%
1 2
2.0%
2 1
 
1.0%
3 3
3.0%
4 4
4.0%
5 1
 
1.0%
7 4
4.0%
8 1
 
1.0%
9 4
4.0%
10 1
 
1.0%
ValueCountFrequency (%)
1744 1
1.0%
1680 1
1.0%
1658 1
1.0%
1638 1
1.0%
1531 1
1.0%
1512 1
1.0%
1503 1
1.0%
1260 1
1.0%
1256 1
1.0%
1233 1
1.0%

총언급량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean558.51
Minimum0
Maximum2935
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:26:35.199362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.95
Q126.5
median257
Q3702
95-th percentile2592.05
Maximum2935
Range2935
Interquartile range (IQR)675.5

Descriptive statistics

Standard deviation755.1972
Coefficient of variation (CV)1.3521642
Kurtosis1.906036
Mean558.51
Median Absolute Deviation (MAD)244.5
Skewness1.6721242
Sum55851
Variance570322.82
MonotonicityNot monotonic
2023-12-10T22:26:35.920235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 5
 
5.0%
7 3
 
3.0%
0 2
 
2.0%
313 2
 
2.0%
18 2
 
2.0%
3 2
 
2.0%
4 2
 
2.0%
2592 1
 
1.0%
326 1
 
1.0%
351 1
 
1.0%
Other values (79) 79
79.0%
ValueCountFrequency (%)
0 2
 
2.0%
2 1
 
1.0%
3 2
 
2.0%
4 2
 
2.0%
6 1
 
1.0%
7 3
3.0%
8 1
 
1.0%
10 1
 
1.0%
11 1
 
1.0%
12 5
5.0%
ValueCountFrequency (%)
2935 1
1.0%
2691 1
1.0%
2616 1
1.0%
2600 1
1.0%
2593 1
1.0%
2592 1
1.0%
2469 1
1.0%
1863 1
1.0%
1701 1
1.0%
1620 1
1.0%

Interactions

2023-12-10T22:26:29.422035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:25.476314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:26.756892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:28.101557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:28.756047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:29.564268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:25.749258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:27.182143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:28.235702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:28.891778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:29.716422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:25.914239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:27.371439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:28.352251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:29.014771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:29.862737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:26.084488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:27.705906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:28.477486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:29.142747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:29.999574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:26.392204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:27.858487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:28.623137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:29.294138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:26:36.186704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간언급량연번연월일도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
일간언급량연번1.0000.0000.9370.8260.7370.6610.8390.758
연월일0.0001.0000.0000.0000.0000.0000.0000.000
도메인 하위 카테고리명0.9370.0001.0000.4340.5750.5200.5300.693
SNS 채널명0.8260.0000.4341.0000.7390.6050.6540.774
긍정언급량0.7370.0000.5750.7391.0000.8460.7830.901
부정언급량0.6610.0000.5200.6050.8461.0000.8270.950
중립언급량0.8390.0000.5300.6540.7830.8271.0000.902
총언급량0.7580.0000.6930.7740.9010.9500.9021.000
2023-12-10T22:26:36.432255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월일SNS 채널명도메인 하위 카테고리명
연월일1.0000.0000.000
SNS 채널명0.0001.0000.195
도메인 하위 카테고리명0.0000.1951.000
2023-12-10T22:26:36.680488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간언급량연번긍정언급량부정언급량중립언급량총언급량연월일도메인 하위 카테고리명SNS 채널명
일간언급량연번1.000-0.540-0.581-0.578-0.5560.0000.8850.611
긍정언급량-0.5401.0000.9150.8820.9480.0000.4290.524
부정언급량-0.5810.9151.0000.9210.9600.0000.2580.346
중립언급량-0.5780.8820.9211.0000.9690.0000.3600.408
총언급량-0.5560.9480.9600.9691.0000.0000.3890.510
연월일0.0000.0000.0000.0000.0001.0000.0000.000
도메인 하위 카테고리명0.8850.4290.2580.3600.3890.0001.0000.195
SNS 채널명0.6110.5240.3460.4080.5100.0000.1951.000

Missing values

2023-12-10T22:26:30.184358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:26:30.584711image/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
012017-01-02물환경하천All64143915122592
122017-01-03물환경하천All82136715032691
232017-01-04물환경하천All63931916582616
342017-01-05물환경하천All63028316802593
452017-01-06물환경하천All66027815312469
562017-01-07물환경하천All67029216382600
672017-01-08물환경하천All85533617442935
782017-01-02물환경하천Twitter18928911421620
892017-01-03물환경하천Twitter39620910961701
9102017-01-04물환경하천Twitter18917112561616
일간언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
90912017-01-08물환경지하수All1471334
91922017-01-02물환경지하수Twitter311317
92932017-01-03물환경지하수Twitter011718
93942017-01-04물환경지하수Twitter30912
94952017-01-05물환경지하수Twitter2201032
95962017-01-06물환경지하수Twitter20911
96972017-01-07물환경지하수Twitter11810
97982017-01-08물환경지하수Twitter13913
98992017-01-02물환경지하수Facebook0000
991002017-01-03물환경지하수Facebook0000