Overview

Dataset statistics

Number of variables5
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory42.3 B

Variable types

DateTime1
Categorical3
Numeric1

Alerts

Country_CD has constant value ""Constant
Collection_CH_NM has constant value ""Constant

Reproduction

Analysis started2023-12-10 09:52:48.258376
Analysis finished2023-12-10 09:52:48.839978
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2017-01-01 00:00:00
Maximum2017-12-01 00:00:00
2023-12-10T18:52:48.912697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:52:49.041235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Country_CD
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
id
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
id 100
100.0%

Length

2023-12-10T18:52:49.216122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:52:49.469151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
id 100
100.0%

Collection_CH_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
community
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
community 100
100.0%

Length

2023-12-10T18:52:49.658464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:52:49.819717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
community 100
100.0%

Community_KEY_W
Categorical

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
kpop
12 
youtube
12 
bts
11 
suka
saya
Other values (27)
51 

Length

Max length12
Median length10
Mean length4.94
Min length3

Unique

Unique16 ?
Unique (%)16.0%

Sample

1st rowkpop
2nd rowyoutube
3rd rowbts
4th rowcnblue
5th rowexo

Common Values

ValueCountFrequency (%)
kpop 12
12.0%
youtube 12
12.0%
bts 11
 
11.0%
suka 7
 
7.0%
saya 7
 
7.0%
exo 6
 
6.0%
allkpop 5
 
5.0%
btstwt 4
 
4.0%
jackson 4
 
4.0%
song 3
 
3.0%
Other values (22) 29
29.0%

Length

2023-12-10T18:52:50.003904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
kpop 12
12.0%
youtube 12
12.0%
bts 11
 
11.0%
suka 7
 
7.0%
saya 7
 
7.0%
exo 6
 
6.0%
allkpop 5
 
5.0%
btstwt 4
 
4.0%
jackson 4
 
4.0%
song 3
 
3.0%
Other values (22) 29
29.0%

Keyword_FQ
Real number (ℝ)

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.53
Minimum4
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:52:50.226005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q16
median8.5
Q323.5
95-th percentile79.3
Maximum102
Range98
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation24.33622
Coefficient of variation (CV)1.185398
Kurtosis2.1018773
Mean20.53
Median Absolute Deviation (MAD)3.5
Skewness1.7818289
Sum2053
Variance592.25162
MonotonicityNot monotonic
2023-12-10T18:52:50.561069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
6 14
14.0%
5 11
 
11.0%
4 11
 
11.0%
7 8
 
8.0%
8 6
 
6.0%
10 4
 
4.0%
11 4
 
4.0%
9 3
 
3.0%
12 3
 
3.0%
85 2
 
2.0%
Other values (29) 34
34.0%
ValueCountFrequency (%)
4 11
11.0%
5 11
11.0%
6 14
14.0%
7 8
8.0%
8 6
6.0%
9 3
 
3.0%
10 4
 
4.0%
11 4
 
4.0%
12 3
 
3.0%
13 1
 
1.0%
ValueCountFrequency (%)
102 1
1.0%
88 1
1.0%
87 1
1.0%
85 2
2.0%
79 1
1.0%
77 1
1.0%
73 1
1.0%
70 1
1.0%
63 1
1.0%
62 1
1.0%

Interactions

2023-12-10T18:52:48.443833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:52:50.747826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Social_Data_Collection_Date_YMCommunity_KEY_WKeyword_FQ
Social_Data_Collection_Date_YM1.0000.0000.000
Community_KEY_W0.0001.0000.000
Keyword_FQ0.0000.0001.000
2023-12-10T18:52:50.915996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Keyword_FQCommunity_KEY_W
Keyword_FQ1.0000.000
Community_KEY_W0.0001.000

Missing values

2023-12-10T18:52:48.594940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:52:48.776506image/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

Social_Data_Collection_Date_YMCountry_CDCollection_CH_NMCommunity_KEY_WKeyword_FQ
02017-01idcommunitykpop85
12017-01idcommunityyoutube36
22017-01idcommunitybts25
32017-01idcommunitycnblue10
42017-01idcommunityexo8
52017-01idcommunityamp5
62017-01idcommunitynct5
72017-01idcommunityseohyun5
82017-02idcommunitykpop77
92017-02idcommunityyoutube63
Social_Data_Collection_Date_YMCountry_CDCollection_CH_NMCommunity_KEY_WKeyword_FQ
902017-11idcommunityexo7
912017-11idcommunityjackson7
922017-12idcommunitykpop102
932017-12idcommunityyoutube40
942017-12idcommunitybts8
952017-12idcommunityfans7
962017-12idcommunitybtstwt6
972017-12idcommunitysaya6
982017-12idcommunitysongs6
992017-12idcommunitysuka6