Overview

Dataset statistics

Number of variables16
Number of observations199
Missing cells799
Missing cells (%)25.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.8 KiB
Average record size in memory137.7 B

Variable types

Categorical5
Unsupported4
Numeric5
Text2

Dataset

DescriptionSample
Author(주)넥스트이지
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=NXEGODSSNSANL

Alerts

SNS has constant value ""Constant
facebook has constant value ""Constant
관광지 is highly overall correlated with 가파도정기여객선High correlation
가파도정기여객선 is highly overall correlated with 62 and 4 other fieldsHigh correlation
62 is highly overall correlated with 20190830 and 1 other fieldsHigh correlation
0 is highly overall correlated with 가파도정기여객선High correlation
20190830 is highly overall correlated with 62 and 1 other fieldsHigh correlation
20190902 is highly overall correlated with 가파도정기여객선High correlation
Unnamed: 2 has 199 (100.0%) missing valuesMissing
Unnamed: 4 has 199 (100.0%) missing valuesMissing
Unnamed: 13 has 199 (100.0%) missing valuesMissing
Unnamed: 14 has 199 (100.0%) missing valuesMissing
https://facebook.com/watch?v=925876464421481^https://facebook.com/watch?v=377131432914716 has 3 (1.5%) missing valuesMissing
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
0 has 137 (68.8%) zerosZeros

Reproduction

Analysis started2023-12-10 06:13:58.801561
Analysis finished2023-12-10 06:14:03.745662
Duration4.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가파도정기여객선
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
세화카페
25 
핫플레이스
14 
동문시장
13 
비체올린
 
10
목스키친
 
10
Other values (31)
127 

Length

Max length11
Median length9
Mean length5.1407035
Min length3

Unique

Unique3 ?
Unique (%)1.5%

Sample

1st row가파도정기여객선
2nd row가파도정기여객선
3rd row비체올린
4th row비체올린
5th row비체올린

Common Values

ValueCountFrequency (%)
세화카페 25
 
12.6%
핫플레이스 14
 
7.0%
동문시장 13
 
6.5%
비체올린 10
 
5.0%
목스키친 10
 
5.0%
코코마마 10
 
5.0%
카페새빌 9
 
4.5%
서귀포중문 9
 
4.5%
세계자동차박물관 7
 
3.5%
에코랜드 7
 
3.5%
Other values (26) 85
42.7%

Length

2023-12-10T15:14:03.877450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
세화카페 25
 
12.6%
핫플레이스 14
 
7.0%
동문시장 13
 
6.5%
비체올린 10
 
5.0%
목스키친 10
 
5.0%
코코마마 10
 
5.0%
카페새빌 9
 
4.5%
서귀포중문 9
 
4.5%
에코랜드 7
 
3.5%
세계자동차박물관 7
 
3.5%
Other values (26) 85
42.7%

SNS
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
SNS
199 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
SNS 199
100.0%

Length

2023-12-10T15:14:04.070951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:04.217581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sns 199
100.0%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

62
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean227.72864
Minimum4
Maximum1109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:04.363043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile13
Q141
median107
Q3338
95-th percentile1109
Maximum1109
Range1105
Interquartile range (IQR)297

Descriptive statistics

Standard deviation278.81757
Coefficient of variation (CV)1.2243413
Kurtosis3.9115887
Mean227.72864
Median Absolute Deviation (MAD)86
Skewness2.0377162
Sum45318
Variance77739.239
MonotonicityNot monotonic
2023-12-10T15:14:04.571669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
338 25
 
12.6%
41 14
 
7.0%
1109 13
 
6.5%
107 10
 
5.0%
496 10
 
5.0%
298 10
 
5.0%
13 9
 
4.5%
39 9
 
4.5%
42 9
 
4.5%
75 8
 
4.0%
Other values (22) 82
41.2%
ValueCountFrequency (%)
4 5
 
2.5%
11 2
 
1.0%
13 9
4.5%
14 1
 
0.5%
21 7
3.5%
23 3
 
1.5%
27 6
3.0%
39 9
4.5%
41 14
7.0%
42 9
4.5%
ValueCountFrequency (%)
1109 13
6.5%
524 7
 
3.5%
496 10
 
5.0%
371 2
 
1.0%
338 25
12.6%
298 10
 
5.0%
263 3
 
1.5%
258 2
 
1.0%
215 6
 
3.0%
208 2
 
1.0%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

0
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8090452
Minimum0
Maximum122
Zeros137
Zeros (%)68.8%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:04.771742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile18.3
Maximum122
Range122
Interquartile range (IQR)6

Descriptive statistics

Standard deviation14.851239
Coefficient of variation (CV)2.5565715
Kurtosis38.367486
Mean5.8090452
Median Absolute Deviation (MAD)0
Skewness5.5366226
Sum1156
Variance220.55931
MonotonicityNot monotonic
2023-12-10T15:14:04.947788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 137
68.8%
18 27
 
13.6%
6 10
 
5.0%
9 10
 
5.0%
21 6
 
3.0%
5 4
 
2.0%
63 2
 
1.0%
122 2
 
1.0%
4 1
 
0.5%
ValueCountFrequency (%)
0 137
68.8%
4 1
 
0.5%
5 4
 
2.0%
6 10
 
5.0%
9 10
 
5.0%
18 27
 
13.6%
21 6
 
3.0%
63 2
 
1.0%
122 2
 
1.0%
ValueCountFrequency (%)
122 2
 
1.0%
63 2
 
1.0%
21 6
 
3.0%
18 27
 
13.6%
9 10
 
5.0%
6 10
 
5.0%
5 4
 
2.0%
4 1
 
0.5%
0 137
68.8%

관광지
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
관광지
144 
음식점
33 
숙박지
22 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광지 144
72.4%
음식점 33
 
16.6%
숙박지 22
 
11.1%

Length

2023-12-10T15:14:05.126179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:05.280799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 144
72.4%
음식점 33
 
16.6%
숙박지 22
 
11.1%

관광지.1
Categorical

Distinct6
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
키워드
93 
관광지
71 
주소지
23 
음식점
 
8
숙박지
 
3

Length

Max length3
Median length3
Mean length2.9949749
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row키워드
2nd row키워드
3rd row관광지
4th row키워드
5th row키워드

Common Values

ValueCountFrequency (%)
키워드 93
46.7%
관광지 71
35.7%
주소지 23
 
11.6%
음식점 8
 
4.0%
숙박지 3
 
1.5%
행사 1
 
0.5%

Length

2023-12-10T15:14:05.462969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:05.643924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
키워드 93
46.7%
관광지 71
35.7%
주소지 23
 
11.6%
음식점 8
 
4.0%
숙박지 3
 
1.5%
행사 1
 
0.5%

facebook
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
facebook
199 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
facebook 199
100.0%

Length

2023-12-10T15:14:05.822852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:05.968871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
facebook 199
100.0%

20190830
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20175748
Minimum20150325
Maximum20191229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:06.120039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20150325
5-th percentile20160113
Q120170105
median20180624
Q320181218
95-th percentile20191108
Maximum20191229
Range40904
Interquartile range (IQR)11113

Descriptive statistics

Standard deviation11736.237
Coefficient of variation (CV)0.00058170022
Kurtosis-0.97820259
Mean20175748
Median Absolute Deviation (MAD)9890
Skewness-0.29726102
Sum4.0149738 × 109
Variance1.3773925 × 108
MonotonicityNot monotonic
2023-12-10T15:14:06.317230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
20160916 25
 
12.6%
20181124 14
 
7.0%
20160113 13
 
6.5%
20170511 10
 
5.0%
20170105 10
 
5.0%
20190514 10
 
5.0%
20191229 9
 
4.5%
20171004 9
 
4.5%
20171114 7
 
3.5%
20150325 7
 
3.5%
Other values (25) 85
42.7%
ValueCountFrequency (%)
20150325 7
 
3.5%
20160113 13
6.5%
20160612 3
 
1.5%
20160916 25
12.6%
20170105 10
 
5.0%
20170511 10
 
5.0%
20171004 9
 
4.5%
20171022 6
 
3.0%
20171114 7
 
3.5%
20171205 2
 
1.0%
ValueCountFrequency (%)
20191229 9
4.5%
20191108 5
2.5%
20190830 2
 
1.0%
20190716 3
 
1.5%
20190715 3
 
1.5%
20190708 2
 
1.0%
20190514 10
5.0%
20190418 3
 
1.5%
20190305 1
 
0.5%
20190222 1
 
0.5%

20190902
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20188132
Minimum20180718
Maximum20191230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:06.464315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20180718
5-th percentile20180819
Q120181166
median20190418
Q320190822
95-th percentile20191229
Maximum20191230
Range10512
Interquartile range (IQR)9656

Descriptive statistics

Standard deviation4286.3187
Coefficient of variation (CV)0.00021231874
Kurtosis-0.81511119
Mean20188132
Median Absolute Deviation (MAD)404
Skewness-1.0812752
Sum4.0174383 × 109
Variance18372528
MonotonicityNot monotonic
2023-12-10T15:14:06.634590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
20190822 25
 
12.6%
20190322 14
 
7.0%
20190311 13
 
6.5%
20190805 10
 
5.0%
20190626 10
 
5.0%
20181102 10
 
5.0%
20191229 9
 
4.5%
20180822 9
 
4.5%
20190715 8
 
4.0%
20191013 7
 
3.5%
Other values (25) 84
42.2%
ValueCountFrequency (%)
20180718 2
 
1.0%
20180725 2
 
1.0%
20180808 2
 
1.0%
20180814 2
 
1.0%
20180819 4
 
2.0%
20180822 9
4.5%
20180904 4
 
2.0%
20181012 6
3.0%
20181102 10
5.0%
20181105 6
3.0%
ValueCountFrequency (%)
20191230 6
 
3.0%
20191229 9
 
4.5%
20191220 2
 
1.0%
20191108 5
 
2.5%
20191013 7
 
3.5%
20190902 2
 
1.0%
20190822 25
12.6%
20190805 10
 
5.0%
20190716 3
 
1.5%
20190715 8
 
4.0%

가파도
Text

Distinct102
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:14:06.933514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.2512563
Min length2

Characters and Unicode

Total characters647
Distinct characters157
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)37.7%

Sample

1st row여행
2nd row여행지
3rd row비체올린
4th row캠핑장
5th row캠핑
ValueCountFrequency (%)
여행 21
 
10.6%
제주도 14
 
7.0%
제주시 8
 
4.0%
서귀포 7
 
3.5%
레이 6
 
3.0%
바다 6
 
3.0%
서귀 6
 
3.0%
여행지 5
 
2.5%
중문 5
 
2.5%
오름 4
 
2.0%
Other values (92) 117
58.8%
2023-12-10T15:14:07.417943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
행 31
 
4.8%
여 30
 
4.6%
주 29
 
4.5%
제 27
 
4.2%
도 21
 
3.2%
산 18
 
2.8%
로 17
 
2.6%
서 15
 
2.3%
해 14
 
2.2%
관 14
 
2.2%
Other values (147) 431
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 630
97.4%
Decimal Number 15
 
2.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
행 31
 
4.9%
여 30
 
4.8%
주 29
 
4.6%
제 27
 
4.3%
도 21
 
3.3%
산 18
 
2.9%
로 17
 
2.7%
서 15
 
2.4%
해 14
 
2.2%
관 14
 
2.2%
Other values (137) 414
65.7%
Decimal Number
ValueCountFrequency (%)
1 5
33.3%
5 2
 
13.3%
2 2
 
13.3%
0 2
 
13.3%
7 1
 
6.7%
8 1
 
6.7%
4 1
 
6.7%
6 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
M 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 630
97.4%
Common 15
 
2.3%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
행 31
 
4.9%
여 30
 
4.8%
주 29
 
4.6%
제 27
 
4.3%
도 21
 
3.3%
산 18
 
2.9%
로 17
 
2.7%
서 15
 
2.4%
해 14
 
2.2%
관 14
 
2.2%
Other values (137) 414
65.7%
Common
ValueCountFrequency (%)
1 5
33.3%
5 2
 
13.3%
2 2
 
13.3%
0 2
 
13.3%
7 1
 
6.7%
8 1
 
6.7%
4 1
 
6.7%
6 1
 
6.7%
Latin
ValueCountFrequency (%)
T 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 630
97.4%
ASCII 17
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
행 31
 
4.9%
여 30
 
4.8%
주 29
 
4.6%
제 27
 
4.3%
도 21
 
3.3%
산 18
 
2.9%
로 17
 
2.7%
서 15
 
2.4%
해 14
 
2.2%
관 14
 
2.2%
Other values (137) 414
65.7%
ASCII
ValueCountFrequency (%)
1 5
29.4%
5 2
 
11.8%
2 2
 
11.8%
0 2
 
11.8%
7 1
 
5.9%
T 1
 
5.9%
M 1
 
5.9%
8 1
 
5.9%
4 1
 
5.9%
6 1
 
5.9%

27
Real number (ℝ)

Distinct20
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0452261
Minimum2
Maximum111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:07.608016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median6
Q312
95-th percentile24
Maximum111
Range109
Interquartile range (IQR)9

Descriptive statistics

Standard deviation10.995085
Coefficient of variation (CV)1.2155677
Kurtosis40.794928
Mean9.0452261
Median Absolute Deviation (MAD)3
Skewness5.337969
Sum1800
Variance120.89188
MonotonicityNot monotonic
2023-12-10T15:14:07.774968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
3 59
29.6%
6 57
28.6%
12 18
 
9.0%
18 14
 
7.0%
9 13
 
6.5%
2 7
 
3.5%
24 6
 
3.0%
4 5
 
2.5%
15 5
 
2.5%
5 2
 
1.0%
Other values (10) 13
 
6.5%
ValueCountFrequency (%)
2 7
 
3.5%
3 59
29.6%
4 5
 
2.5%
5 2
 
1.0%
6 57
28.6%
7 1
 
0.5%
8 1
 
0.5%
9 13
 
6.5%
11 1
 
0.5%
12 18
 
9.0%
ValueCountFrequency (%)
111 1
 
0.5%
63 1
 
0.5%
50 2
 
1.0%
30 1
 
0.5%
27 2
 
1.0%
24 6
3.0%
21 1
 
0.5%
18 14
7.0%
15 5
 
2.5%
14 2
 
1.0%

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

https://facebook.com/watch?v=925876464421481^https://facebook.com/watch?v=377131432914716
Text

MISSING 

Distinct89
Distinct (%)45.4%
Missing3
Missing (%)1.5%
Memory size1.7 KiB
2023-12-10T15:14:08.075308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length941
Median length483
Mean length127.64796
Min length44

Characters and Unicode

Total characters25019
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)20.9%

Sample

1st rowhttps://facebook.com/watch?v=925876464421481^https://facebook.com/watch?v=377131432914716
2nd rowhttps://facebook.com/watch?v=377131432914716
3rd rowhttps://facebook.com/watch?v=436542190536436^https://facebook.com/story.php?story_fbid=2384232621851526&id=2140496859558438^https://facebook.com/story.php?story_fbid=2348162585458530&id=2140496859558438^https://facebook.com/watch?v=671078649731338
4th rowhttps://facebook.com/watch?v=436542190536436^https://facebook.com/story.php?story_fbid=2384232621851526&id=2140496859558438
5th rowhttps://facebook.com/watch?v=436542190536436^https://facebook.com/story.php?story_fbid=2384232621851526&id=2140496859558438
ValueCountFrequency (%)
https://facebook.com/story.php?story_fbid=2219761794965277&id=2140496859558438 11
 
5.6%
https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153 9
 
4.6%
https://facebook.com/watch?v=285828725596689^https://facebook.com/watch?v=463268457517218 8
 
4.1%
https://facebook.com/story.php?story_fbid=630012557440308&id=439681209806778^https://facebook.com/story.php?story_fbid=517280405380191&id=439681209806778 6
 
3.1%
https://facebook.com/story.php?story_fbid=420767538614518&id=134632230561385 5
 
2.6%
https://facebook.com/story.php?story_fbid=561282357724707&id=517367602116183 5
 
2.6%
https://facebook.com/story.php?story_fbid=349130229111583&id=134632230561385^https://facebook.com/story.php?story_fbid=328312297860043&id=134632230561385^https://facebook.com/story.php?story_fbid=2281666578751443&id=1915833195334785 5
 
2.6%
https://facebook.com/story.php?story_fbid=231128300911777&id=134632230561385^https://facebook.com/story.php?story_fbid=530933270681571&id=439681209806778 4
 
2.0%
https://facebook.com/story.php?story_fbid=333090597382213&id=134632230561385 4
 
2.0%
https://facebook.com/watch?v=224133634944577^^https://facebook.com/story.php?story_fbid=2152119278372841&id=1915833195334785 4
 
2.0%
Other values (78) 135
68.9%
2023-12-10T15:14:08.614801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1619
 
6.5%
5 1364
 
5.5%
t 1342
 
5.4%
1 1234
 
4.9%
2 1193
 
4.8%
3 1148
 
4.6%
/ 1065
 
4.3%
8 980
 
3.9%
p 909
 
3.6%
s 909
 
3.6%
Other values (26) 13256
53.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11411
45.6%
Decimal Number 9847
39.4%
Other Punctuation 2684
 
10.7%
Math Symbol 632
 
2.5%
Connector Punctuation 277
 
1.1%
Modifier Symbol 168
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1619
14.2%
t 1342
11.8%
p 909
 
8.0%
s 909
 
8.0%
c 788
 
6.9%
h 710
 
6.2%
b 632
 
5.5%
f 632
 
5.5%
y 554
 
4.9%
i 554
 
4.9%
Other values (8) 2762
24.2%
Decimal Number
ValueCountFrequency (%)
5 1364
13.9%
1 1234
12.5%
2 1193
12.1%
3 1148
11.7%
8 980
10.0%
4 896
9.1%
6 852
8.7%
9 768
7.8%
7 721
7.3%
0 691
7.0%
Other Punctuation
ValueCountFrequency (%)
/ 1065
39.7%
. 632
23.5%
? 355
 
13.2%
: 355
 
13.2%
& 277
 
10.3%
Math Symbol
ValueCountFrequency (%)
= 632
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 277
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13608
54.4%
Latin 11411
45.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1619
14.2%
t 1342
11.8%
p 909
 
8.0%
s 909
 
8.0%
c 788
 
6.9%
h 710
 
6.2%
b 632
 
5.5%
f 632
 
5.5%
y 554
 
4.9%
i 554
 
4.9%
Other values (8) 2762
24.2%
Common
ValueCountFrequency (%)
5 1364
10.0%
1 1234
 
9.1%
2 1193
 
8.8%
3 1148
 
8.4%
/ 1065
 
7.8%
8 980
 
7.2%
4 896
 
6.6%
6 852
 
6.3%
9 768
 
5.6%
7 721
 
5.3%
Other values (8) 3387
24.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1619
 
6.5%
5 1364
 
5.5%
t 1342
 
5.4%
1 1234
 
4.9%
2 1193
 
4.8%
3 1148
 
4.6%
/ 1065
 
4.3%
8 980
 
3.9%
p 909
 
3.6%
s 909
 
3.6%
Other values (26) 13256
53.0%

Interactions

2023-12-10T15:14:02.391533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:59.368379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:59.929426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:00.531830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:01.668390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:02.510689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:59.468518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:00.055149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:00.652655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:01.786753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:02.627734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:59.586855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:00.165884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:01.187441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:01.955914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:02.802433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:59.741992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:00.296292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:01.417379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:02.118578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:02.925666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:59.839613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:00.414505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:01.544961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:02.249548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:14:08.764863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가파도정기여객선620관광지관광지.1201908302019090227https://facebook.com/watch?v=925876464421481^https://facebook.com/watch?v=377131432914716
가파도정기여객선1.0001.0001.0001.0000.0001.0001.0000.0001.000
621.0001.0000.7050.7540.0000.7040.6460.4801.000
01.0000.7051.0000.1800.0000.4300.2600.0001.000
관광지1.0000.7540.1801.0000.5740.4850.4290.0001.000
관광지.10.0000.0000.0000.5741.0000.0250.3470.0000.466
201908301.0000.7040.4300.4850.0251.0000.4720.1581.000
201909021.0000.6460.2600.4290.3470.4721.0000.0001.000
270.0000.4800.0000.0000.0000.1580.0001.0000.902
https://facebook.com/watch?v=925876464421481^https://facebook.com/watch?v=3771314329147161.0001.0001.0001.0000.4661.0001.0000.9021.000
2023-12-10T15:14:08.966977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지.1관광지가파도정기여객선
관광지.11.0000.2830.000
관광지0.2831.0000.912
가파도정기여객선0.0000.9121.000
2023-12-10T15:14:09.169196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
620201908302019090227가파도정기여객선관광지관광지.1
621.0000.448-0.5690.0510.0720.9190.4290.000
00.4481.000-0.4270.0200.0510.9140.1700.000
20190830-0.569-0.4271.0000.197-0.0690.9190.4180.000
201909020.0510.0200.1971.000-0.0560.9120.1590.166
270.0720.051-0.069-0.0561.0000.0000.0000.000
가파도정기여객선0.9190.9140.9190.9120.0001.0000.9120.000
관광지0.4290.1700.4180.1590.0000.9121.0000.283
관광지.10.0000.0000.0000.1660.0000.0000.2831.000

Missing values

2023-12-10T15:14:03.147666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:14:03.603092image/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

가파도정기여객선SNSUnnamed: 262Unnamed: 40관광지관광지.1facebook2019083020190902가파도27Unnamed: 13Unnamed: 14https://facebook.com/watch?v=925876464421481^https://facebook.com/watch?v=377131432914716
0가파도정기여객선SNS<NA>62<NA>0관광지키워드facebook2019083020190902여행6<NA><NA>https://facebook.com/watch?v=925876464421481^https://facebook.com/watch?v=377131432914716
1가파도정기여객선SNS<NA>62<NA>0관광지키워드facebook2019083020190902여행지2<NA><NA>https://facebook.com/watch?v=377131432914716
2비체올린SNS<NA>107<NA>6관광지관광지facebook2017010520190805비체올린18<NA><NA>https://facebook.com/watch?v=436542190536436^https://facebook.com/story.php?story_fbid=2384232621851526&id=2140496859558438^https://facebook.com/story.php?story_fbid=2348162585458530&id=2140496859558438^https://facebook.com/watch?v=671078649731338
3비체올린SNS<NA>107<NA>6관광지키워드facebook2017010520190805캠핑장18<NA><NA>https://facebook.com/watch?v=436542190536436^https://facebook.com/story.php?story_fbid=2384232621851526&id=2140496859558438
4비체올린SNS<NA>107<NA>6관광지키워드facebook2017010520190805캠핑18<NA><NA>https://facebook.com/watch?v=436542190536436^https://facebook.com/story.php?story_fbid=2384232621851526&id=2140496859558438
5비체올린SNS<NA>107<NA>6관광지키워드facebook2017010520190805여행27<NA><NA>https://facebook.com/watch?v=436542190536436^https://facebook.com/story.php?story_fbid=2384232621851526&id=2140496859558438^https://facebook.com/story.php?story_fbid=2348162585458530&id=2140496859558438
6비체올린SNS<NA>107<NA>6관광지키워드facebook2017010520190805제주도3<NA><NA>https://facebook.com/watch?v=436542190536436
7비체올린SNS<NA>107<NA>6관광지키워드facebook2017010520190805가족여행6<NA><NA>https://facebook.com/story.php?story_fbid=2348162585458530&id=2140496859558438
8비체올린SNS<NA>107<NA>6관광지키워드facebook2017010520190805여행지3<NA><NA>https://facebook.com/story.php?story_fbid=2348162585458530&id=2140496859558438
9비체올린SNS<NA>107<NA>6관광지주소지facebook2017010520190805판조로3<NA><NA>https://facebook.com/watch?v=671078649731338
가파도정기여객선SNSUnnamed: 262Unnamed: 40관광지관광지.1facebook2019083020190902가파도27Unnamed: 13Unnamed: 14https://facebook.com/watch?v=925876464421481^https://facebook.com/watch?v=377131432914716
189카페새빌SNS<NA>39<NA>0음식점음식점facebook2019122920191229새빌12<NA><NA>https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153
190카페새빌SNS<NA>39<NA>0음식점주소지facebook2019122920191229애월읍3<NA><NA>https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153
191카페새빌SNS<NA>39<NA>0음식점주소지facebook2019122920191229평화로3<NA><NA>https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153
192카페새빌SNS<NA>39<NA>0음식점키워드facebook2019122920191229제주시6<NA><NA>https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153
193카페새빌SNS<NA>39<NA>0음식점키워드facebook2019122920191229애월12<NA><NA>https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153
194카페새빌SNS<NA>39<NA>0음식점키워드facebook2019122920191229여행3<NA><NA>https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153
195카페새빌SNS<NA>39<NA>0음식점키워드facebook2019122920191229오름3<NA><NA>https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153
196카페새빌SNS<NA>39<NA>0음식점키워드facebook2019122920191229제주도3<NA><NA>https://facebook.com/story.php?story_fbid=2584959478447411&id=1614182155525153
197중문술집SNS<NA>208<NA>0관광지관광지facebook2017120520191220서귀포6<NA><NA>https://facebook.com/story.php?story_fbid=2577767499166609&id=1614182155525153^https://facebook.com/story.php?story_fbid=1956945224556915&id=1915833195334785
198중문술집SNS<NA>208<NA>0관광지관광지facebook2017120520191220중문18<NA><NA>https://facebook.com/story.php?story_fbid=2577767499166609&id=1614182155525153^https://facebook.com/story.php?story_fbid=1956945224556915&id=1915833195334785