Overview

Dataset statistics

Number of variables9
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory80.0 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

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 2 other fieldsHigh correlation
부정언급량 is highly overall correlated with 긍정언급량 and 2 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 1 other fieldsHigh correlation
도메인 하위 카테고리명 is highly overall correlated with 환경플랫폼 하위 도메인명High correlation
SNS 채널명 is highly overall correlated with 일간언급량연번High correlation
일간언급량연번 has unique valuesUnique
부정언급량 has 5 (11.4%) zerosZeros

Reproduction

Analysis started2023-12-10 13:26:03.075875
Analysis finished2023-12-10 13:26:07.352052
Duration4.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일간언급량연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-10T22:26:07.493163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q111.75
median22.5
Q333.25
95-th percentile41.85
Maximum44
Range43
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation12.845233
Coefficient of variation (CV)0.57089923
Kurtosis-1.2
Mean22.5
Median Absolute Deviation (MAD)11
Skewness0
Sum990
Variance165
MonotonicityStrictly increasing
2023-12-10T22:26:07.893429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 1
 
2.3%
24 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
33 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
44 1
2.3%
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%

연월일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
2020-01-01
44 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-01-01
2nd row2020-01-01
3rd row2020-01-01
4th row2020-01-01
5th row2020-01-01

Common Values

ValueCountFrequency (%)
2020-01-01 44
100.0%

Length

2023-12-10T22:26:08.168267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:26:08.365045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-01-01 44
100.0%

환경플랫폼 하위 도메인명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
물환경
18 
자연환경
17 
생활환경
9 

Length

Max length4
Median length4
Mean length3.5909091
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물환경 18
40.9%
자연환경 17
38.6%
생활환경 9
20.5%

Length

2023-12-10T22:26:08.661296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:26:08.888995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물환경 18
40.9%
자연환경 17
38.6%
생활환경 9
20.5%

도메인 하위 카테고리명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
물재난
3 
상수도
3 
지하수
3 
하수도
3 
하천
3 
Other values (10)
29 

Length

Max length4
Median length3
Mean length2.7727273
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row물재난
2nd row상수도
3rd row지하수
4th row하수도
5th row하천

Common Values

ValueCountFrequency (%)
물재난 3
 
6.8%
상수도 3
 
6.8%
지하수 3
 
6.8%
하수도 3
 
6.8%
하천 3
 
6.8%
호소 3
 
6.8%
대기 3
 
6.8%
폐기물 3
 
6.8%
화학물질 3
 
6.8%
기후변화 3
 
6.8%
Other values (5) 14
31.8%

Length

2023-12-10T22:26:09.115597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
물재난 3
 
6.8%
상수도 3
 
6.8%
지하수 3
 
6.8%
하수도 3
 
6.8%
하천 3
 
6.8%
호소 3
 
6.8%
대기 3
 
6.8%
폐기물 3
 
6.8%
화학물질 3
 
6.8%
기후변화 3
 
6.8%
Other values (5) 14
31.8%

SNS 채널명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size484.0 B
All
15 
twitter
15 
blog
14 

Length

Max length7
Median length4
Mean length4.6818182
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
All 15
34.1%
twitter 15
34.1%
blog 14
31.8%

Length

2023-12-10T22:26:09.430229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:26:09.765262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
all 15
34.1%
twitter 15
34.1%
blog 14
31.8%

긍정언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.5
Minimum1
Maximum301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-10T22:26:09.966283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16
median31.5
Q399.75
95-th percentile253.55
Maximum301
Range300
Interquartile range (IQR)93.75

Descriptive statistics

Standard deviation84.385191
Coefficient of variation (CV)1.1969531
Kurtosis0.87963891
Mean70.5
Median Absolute Deviation (MAD)28
Skewness1.3547399
Sum3102
Variance7120.8605
MonotonicityNot monotonic
2023-12-10T22:26:10.226907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
10 3
 
6.8%
5 3
 
6.8%
43 2
 
4.5%
27 2
 
4.5%
3 2
 
4.5%
1 2
 
4.5%
17 2
 
4.5%
4 2
 
4.5%
6 2
 
4.5%
108 1
 
2.3%
Other values (23) 23
52.3%
ValueCountFrequency (%)
1 2
4.5%
2 1
 
2.3%
3 2
4.5%
4 2
4.5%
5 3
6.8%
6 2
4.5%
10 3
6.8%
13 1
 
2.3%
17 2
4.5%
20 1
 
2.3%
ValueCountFrequency (%)
301 1
2.3%
286 1
2.3%
260 1
2.3%
217 1
2.3%
205 1
2.3%
188 1
2.3%
162 1
2.3%
153 1
2.3%
152 1
2.3%
148 1
2.3%

부정언급량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.954545
Minimum0
Maximum160
Zeros5
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-10T22:26:10.491925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median16
Q358.75
95-th percentile137.95
Maximum160
Range160
Interquartile range (IQR)53.75

Descriptive statistics

Standard deviation45.964574
Coefficient of variation (CV)1.1504216
Kurtosis0.46787874
Mean39.954545
Median Absolute Deviation (MAD)16
Skewness1.2258697
Sum1758
Variance2112.7421
MonotonicityNot monotonic
2023-12-10T22:26:10.760223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 5
 
11.4%
5 4
 
9.1%
16 2
 
4.5%
4 2
 
4.5%
13 2
 
4.5%
15 2
 
4.5%
58 2
 
4.5%
1 1
 
2.3%
47 1
 
2.3%
49 1
 
2.3%
Other values (22) 22
50.0%
ValueCountFrequency (%)
0 5
11.4%
1 1
 
2.3%
2 1
 
2.3%
3 1
 
2.3%
4 2
 
4.5%
5 4
9.1%
6 1
 
2.3%
7 1
 
2.3%
12 1
 
2.3%
13 2
 
4.5%
ValueCountFrequency (%)
160 1
2.3%
147 1
2.3%
139 1
2.3%
132 1
2.3%
112 1
2.3%
111 1
2.3%
105 1
2.3%
78 1
2.3%
74 1
2.3%
62 1
2.3%

중립언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2033.4091
Minimum10
Maximum8922
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-10T22:26:11.041374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile91.5
Q1224
median940
Q33005.75
95-th percentile6675.75
Maximum8922
Range8912
Interquartile range (IQR)2781.75

Descriptive statistics

Standard deviation2348.4324
Coefficient of variation (CV)1.1549237
Kurtosis0.90359832
Mean2033.4091
Median Absolute Deviation (MAD)833.5
Skewness1.3162783
Sum89470
Variance5515134.9
MonotonicityNot monotonic
2023-12-10T22:26:11.343677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1034 2
 
4.5%
1953 1
 
2.3%
5070 1
 
2.3%
129 1
 
2.3%
2631 1
 
2.3%
2508 1
 
2.3%
813 1
 
2.3%
1209 1
 
2.3%
119 1
 
2.3%
90 1
 
2.3%
Other values (33) 33
75.0%
ValueCountFrequency (%)
10 1
2.3%
78 1
2.3%
90 1
2.3%
100 1
2.3%
113 1
2.3%
118 1
2.3%
119 1
2.3%
124 1
2.3%
129 1
2.3%
140 1
2.3%
ValueCountFrequency (%)
8922 1
2.3%
7495 1
2.3%
6678 1
2.3%
6663 1
2.3%
5539 1
2.3%
5432 1
2.3%
5070 1
2.3%
4041 1
2.3%
3852 1
2.3%
3710 1
2.3%

총언급량
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2143.8636
Minimum11
Maximum9383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-10T22:26:11.563401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile96.65
Q1237.75
median988
Q33181.75
95-th percentile7065.45
Maximum9383
Range9372
Interquartile range (IQR)2944

Descriptive statistics

Standard deviation2476.7879
Coefficient of variation (CV)1.1552917
Kurtosis0.89328526
Mean2143.8636
Median Absolute Deviation (MAD)878
Skewness1.3154171
Sum94330
Variance6134478.2
MonotonicityNot monotonic
2023-12-10T22:26:11.781619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1077 2
 
4.5%
2098 1
 
2.3%
5330 1
 
2.3%
134 1
 
2.3%
2775 1
 
2.3%
2624 1
 
2.3%
866 1
 
2.3%
1293 1
 
2.3%
124 1
 
2.3%
95 1
 
2.3%
Other values (33) 33
75.0%
ValueCountFrequency (%)
11 1
2.3%
86 1
2.3%
95 1
2.3%
106 1
2.3%
114 1
2.3%
124 1
2.3%
128 1
2.3%
134 1
2.3%
135 1
2.3%
145 1
2.3%
ValueCountFrequency (%)
9383 1
2.3%
7928 1
2.3%
7077 1
2.3%
7000 1
2.3%
5832 1
2.3%
5760 1
2.3%
5330 1
2.3%
4277 1
2.3%
4053 1
2.3%
3923 1
2.3%

Interactions

2023-12-10T22:26:06.379801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:03.664420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:04.356931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:05.107701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:05.827781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:06.487415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:03.796798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:04.524837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:05.232304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:05.933425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:06.600311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:03.922188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:04.695677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:05.382557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:06.044510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:06.725601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:04.085430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:04.857262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:05.556446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:06.164821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:06.836652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:04.217814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:04.983091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:05.700127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:26:06.282613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:26:11.932988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간언급량연번환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
일간언급량연번1.0000.8030.0000.9210.6650.3930.7200.720
환경플랫폼 하위 도메인명0.8031.0001.0000.0000.0000.3800.0000.000
도메인 하위 카테고리명0.0001.0001.0000.0000.6990.6570.5020.502
SNS 채널명0.9210.0000.0001.0000.4220.0000.4090.409
긍정언급량0.6650.0000.6990.4221.0000.9030.9760.976
부정언급량0.3930.3800.6570.0000.9031.0000.9400.940
중립언급량0.7200.0000.5020.4090.9760.9401.0001.000
총언급량0.7200.0000.5020.4090.9760.9401.0001.000
2023-12-10T22:26:12.479110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SNS 채널명환경플랫폼 하위 도메인명도메인 하위 카테고리명
SNS 채널명1.0000.0000.000
환경플랫폼 하위 도메인명0.0001.0000.841
도메인 하위 카테고리명0.0000.8411.000
2023-12-10T22:26:12.644288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일간언급량연번긍정언급량부정언급량중립언급량총언급량환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명
일간언급량연번1.000-0.223-0.143-0.181-0.1810.6310.0000.810
긍정언급량-0.2231.0000.9530.9680.9690.0000.2400.219
부정언급량-0.1430.9531.0000.9680.9700.0000.2650.000
중립언급량-0.1810.9680.9681.0001.0000.0000.1720.236
총언급량-0.1810.9690.9701.0001.0000.0000.1720.236
환경플랫폼 하위 도메인명0.6310.0000.0000.0000.0001.0000.8410.000
도메인 하위 카테고리명0.0000.2400.2650.1720.1720.8411.0000.000
SNS 채널명0.8100.2190.0000.2360.2360.0000.0001.000

Missing values

2023-12-10T22:26:07.010345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:26:07.237161image/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
012020-01-01물환경물재난All895619532098
122020-01-01물환경상수도All106243259
232020-01-01물환경지하수All60100106
342020-01-01물환경하수도All44280288
452020-01-01물환경하천All30116089229383
562020-01-01물환경호소All26013966787077
672020-01-01생활환경대기All20513266637000
782020-01-01생활환경폐기물All2315927965
892020-01-01생활환경화학물질All2012582614
9102020-01-01자연환경기상변화All271610341077
일간언급량연번연월일환경플랫폼 하위 도메인명도메인 하위 카테고리명SNS 채널명긍정언급량부정언급량중립언급량총언급량
34352020-01-01물환경호소twitter1087829683154
35362020-01-01생활환경대기twitter435826222723
36372020-01-01생활환경폐기물twitter1013553576
37382020-01-01생활환경화학물질twitter357886
38392020-01-01자연환경기상변화twitter271610341077
39402020-01-01자연환경기후변화twitter693620632168
40412020-01-01자연환경생태계twitter55118128
41422020-01-01자연환경지질twitter915829083057
42432020-01-01자연환경지형twitter1713611641
43442020-01-01자연환경토양twitter23140145