Overview

Dataset statistics

Number of variables11
Number of observations28
Missing cells40
Missing cells (%)13.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory98.7 B

Variable types

Text5
Numeric4
Categorical2

Dataset

Description샘플 데이터
Author경기도경제과학진흥원
URLhttps://bigdata-region.kr/#/dataset/30998966-7e2a-4d2f-87cb-bb643665bfba

Alerts

덧글수 has constant value ""Constant
부정평가비율 has constant value ""Constant
구독자수 is highly overall correlated with 영상수 and 2 other fieldsHigh correlation
영상수 is highly overall correlated with 구독자수 and 1 other fieldsHigh correlation
조회수 is highly overall correlated with 구독자수 and 2 other fieldsHigh correlation
긍정평가비율 is highly overall correlated with 구독자수 and 1 other fieldsHigh correlation
키워드1명 has 14 (50.0%) missing valuesMissing
키워드2명 has 26 (92.9%) missing valuesMissing
채널ID has unique valuesUnique
채널명 has unique valuesUnique
구독자수 has 7 (25.0%) zerosZeros
영상수 has 2 (7.1%) zerosZeros
조회수 has 3 (10.7%) zerosZeros
긍정평가비율 has 8 (28.6%) zerosZeros

Reproduction

Analysis started2023-12-10 14:01:26.273756
Analysis finished2023-12-10 14:01:30.171325
Duration3.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

채널ID
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T23:01:30.479638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length56
Mean length56
Min length56

Characters and Unicode

Total characters1568
Distinct characters67
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

Unique28 ?
Unique (%)100.0%

Sample

1st rowhttps://www.youtube.com/channel/UC--DRzpNwUKutByTr3-aIGw
2nd rowhttps://www.youtube.com/channel/UC--K42RqMIaemoYb4du7djg
3rd rowhttps://www.youtube.com/channel/UC--bmnt1Y_syiANwBKQtFOQ
4th rowhttps://www.youtube.com/channel/UC-0fPeo4F1q43YndRgFuYog
5th rowhttps://www.youtube.com/channel/UC-0v-M5WQUQQGPDFZeLTknA
ValueCountFrequency (%)
https://www.youtube.com/channel/uc--drzpnwukutbytr3-aigw 1
 
3.6%
https://www.youtube.com/channel/uc--k42rqmiaemoyb4du7djg 1
 
3.6%
https://www.youtube.com/channel/uc-dddqjn7kojorujbnpaqjq 1
 
3.6%
https://www.youtube.com/channel/uc-byxiqteu3ugy6ainu_5gq 1
 
3.6%
https://www.youtube.com/channel/uc-bqpabol7c7rr5eojjz0ua 1
 
3.6%
https://www.youtube.com/channel/uc-bavrxooe9dve1wwweiofa 1
 
3.6%
https://www.youtube.com/channel/uc-ajxxepozpvxuie1ikmzfq 1
 
3.6%
https://www.youtube.com/channel/uc-apcmqjwwpzbdeqdfroeyg 1
 
3.6%
https://www.youtube.com/channel/uc-9q-muzukchcgjmtrglg8w 1
 
3.6%
https://www.youtube.com/channel/uc-8vgtzzywen5-c7ddj-dmq 1
 
3.6%
Other values (18) 18
64.3%
2023-12-10T23:01:31.511636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 112
 
7.1%
w 96
 
6.1%
t 89
 
5.7%
o 69
 
4.4%
u 66
 
4.2%
e 64
 
4.1%
n 62
 
4.0%
c 62
 
4.0%
h 61
 
3.9%
. 56
 
3.6%
Other values (57) 831
53.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 919
58.6%
Uppercase Letter 317
 
20.2%
Other Punctuation 196
 
12.5%
Decimal Number 92
 
5.9%
Dash Punctuation 41
 
2.6%
Connector Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 96
 
10.4%
t 89
 
9.7%
o 69
 
7.5%
u 66
 
7.2%
e 64
 
7.0%
n 62
 
6.7%
c 62
 
6.7%
h 61
 
6.6%
a 39
 
4.2%
m 38
 
4.1%
Other values (16) 273
29.7%
Uppercase Letter
ValueCountFrequency (%)
U 37
 
11.7%
C 33
 
10.4%
Q 22
 
6.9%
A 16
 
5.0%
F 14
 
4.4%
B 13
 
4.1%
G 13
 
4.1%
E 12
 
3.8%
T 12
 
3.8%
O 12
 
3.8%
Other values (16) 133
42.0%
Decimal Number
ValueCountFrequency (%)
1 15
16.3%
8 14
15.2%
2 11
12.0%
7 11
12.0%
5 10
10.9%
4 9
9.8%
0 9
9.8%
3 6
 
6.5%
9 5
 
5.4%
6 2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 112
57.1%
. 56
28.6%
: 28
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1236
78.8%
Common 332
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 96
 
7.8%
t 89
 
7.2%
o 69
 
5.6%
u 66
 
5.3%
e 64
 
5.2%
n 62
 
5.0%
c 62
 
5.0%
h 61
 
4.9%
a 39
 
3.2%
m 38
 
3.1%
Other values (42) 590
47.7%
Common
ValueCountFrequency (%)
/ 112
33.7%
. 56
16.9%
- 41
 
12.3%
: 28
 
8.4%
1 15
 
4.5%
8 14
 
4.2%
2 11
 
3.3%
7 11
 
3.3%
5 10
 
3.0%
4 9
 
2.7%
Other values (5) 25
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 112
 
7.1%
w 96
 
6.1%
t 89
 
5.7%
o 69
 
4.4%
u 66
 
4.2%
e 64
 
4.1%
n 62
 
4.0%
c 62
 
4.0%
h 61
 
3.9%
. 56
 
3.6%
Other values (57) 831
53.0%

채널범주명
Text

Distinct16
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T23:01:31.787190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.3214286
Min length2

Characters and Unicode

Total characters65
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)35.7%

Sample

1st row환경
2nd row관람객
3rd row상권
4th row상권
5th row상생
ValueCountFrequency (%)
구매 5
17.9%
여행 4
14.3%
환경 3
10.7%
상권 2
 
7.1%
상인 2
 
7.1%
구인 2
 
7.1%
관람객 1
 
3.6%
상생 1
 
3.6%
소비자 1
 
3.6%
구인/구직 1
 
3.6%
Other values (6) 6
21.4%
2023-12-10T23:01:32.227963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 9
13.8%
상 6
 
9.2%
매 5
 
7.7%
인 5
 
7.7%
관 4
 
6.2%
행 4
 
6.2%
여 4
 
6.2%
경 3
 
4.6%
환 3
 
4.6%
광 3
 
4.6%
Other values (17) 19
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
96.9%
Other Punctuation 2
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 9
14.3%
상 6
 
9.5%
매 5
 
7.9%
인 5
 
7.9%
관 4
 
6.3%
행 4
 
6.3%
여 4
 
6.3%
경 3
 
4.8%
환 3
 
4.8%
광 3
 
4.8%
Other values (16) 17
27.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63
96.9%
Common 2
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 9
14.3%
상 6
 
9.5%
매 5
 
7.9%
인 5
 
7.9%
관 4
 
6.3%
행 4
 
6.3%
여 4
 
6.3%
경 3
 
4.8%
환 3
 
4.8%
광 3
 
4.8%
Other values (16) 17
27.0%
Common
ValueCountFrequency (%)
/ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
96.9%
ASCII 2
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 9
14.3%
상 6
 
9.5%
매 5
 
7.9%
인 5
 
7.9%
관 4
 
6.3%
행 4
 
6.3%
여 4
 
6.3%
경 3
 
4.8%
환 3
 
4.8%
광 3
 
4.8%
Other values (16) 17
27.0%
ASCII
ValueCountFrequency (%)
/ 2
100.0%

채널명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T23:01:32.574513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length16
Mean length9
Min length2

Characters and Unicode

Total characters252
Distinct characters135
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row환경
2nd row타임뉴스
3rd row부동산사피엔스
4th row한정우공인중개사
5th rowmampan7
ValueCountFrequency (%)
환경 1
 
2.1%
타임뉴스 1
 
2.1%
하는 1
 
2.1%
사람 1
 
2.1%
신기루의 1
 
2.1%
춤 1
 
2.1%
여행 1
 
2.1%
mirage 1
 
2.1%
dance 1
 
2.1%
story 1
 
2.1%
Other values (38) 38
79.2%
2023-12-10T23:01:33.124304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
7.9%
n 9
 
3.6%
a 9
 
3.6%
e 8
 
3.2%
r 5
 
2.0%
s 5
 
2.0%
i 5
 
2.0%
사 5
 
2.0%
여 4
 
1.6%
o 4
 
1.6%
Other values (125) 178
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
55.2%
Lowercase Letter 63
25.0%
Space Separator 20
 
7.9%
Uppercase Letter 18
 
7.1%
Decimal Number 8
 
3.2%
Other Punctuation 2
 
0.8%
Dash Punctuation 1
 
0.4%
Connector Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 5
 
3.6%
여 4
 
2.9%
행 4
 
2.9%
광 3
 
2.2%
리 3
 
2.2%
스 3
 
2.2%
는 3
 
2.2%
구 2
 
1.4%
의 2
 
1.4%
카 2
 
1.4%
Other values (86) 108
77.7%
Lowercase Letter
ValueCountFrequency (%)
n 9
14.3%
a 9
14.3%
e 8
12.7%
r 5
7.9%
s 5
7.9%
i 5
7.9%
o 4
6.3%
u 3
 
4.8%
k 3
 
4.8%
m 3
 
4.8%
Other values (7) 9
14.3%
Uppercase Letter
ValueCountFrequency (%)
T 3
16.7%
V 2
11.1%
D 2
11.1%
G 1
 
5.6%
A 1
 
5.6%
R 1
 
5.6%
I 1
 
5.6%
E 1
 
5.6%
M 1
 
5.6%
C 1
 
5.6%
Other values (4) 4
22.2%
Decimal Number
ValueCountFrequency (%)
7 4
50.0%
2 2
25.0%
8 2
25.0%
Other Punctuation
ValueCountFrequency (%)
; 1
50.0%
? 1
50.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
55.2%
Latin 81
32.1%
Common 32
 
12.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 5
 
3.6%
여 4
 
2.9%
행 4
 
2.9%
광 3
 
2.2%
리 3
 
2.2%
스 3
 
2.2%
는 3
 
2.2%
구 2
 
1.4%
의 2
 
1.4%
카 2
 
1.4%
Other values (86) 108
77.7%
Latin
ValueCountFrequency (%)
n 9
 
11.1%
a 9
 
11.1%
e 8
 
9.9%
r 5
 
6.2%
s 5
 
6.2%
i 5
 
6.2%
o 4
 
4.9%
u 3
 
3.7%
T 3
 
3.7%
k 3
 
3.7%
Other values (21) 27
33.3%
Common
ValueCountFrequency (%)
20
62.5%
7 4
 
12.5%
2 2
 
6.2%
8 2
 
6.2%
- 1
 
3.1%
; 1
 
3.1%
_ 1
 
3.1%
? 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
55.2%
ASCII 113
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
17.7%
n 9
 
8.0%
a 9
 
8.0%
e 8
 
7.1%
r 5
 
4.4%
s 5
 
4.4%
i 5
 
4.4%
o 4
 
3.5%
7 4
 
3.5%
u 3
 
2.7%
Other values (29) 41
36.3%
Hangul
ValueCountFrequency (%)
사 5
 
3.6%
여 4
 
2.9%
행 4
 
2.9%
광 3
 
2.2%
리 3
 
2.2%
스 3
 
2.2%
는 3
 
2.2%
구 2
 
1.4%
의 2
 
1.4%
카 2
 
1.4%
Other values (86) 108
77.7%

구독자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8305.9643
Minimum0
Maximum192000
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T23:01:33.345583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.75
median11.5
Q3949.75
95-th percentile13440
Maximum192000
Range192000
Interquartile range (IQR)949

Descriptive statistics

Standard deviation36178.841
Coefficient of variation (CV)4.3557665
Kurtosis27.387826
Mean8305.9643
Median Absolute Deviation (MAD)11.5
Skewness5.2105579
Sum232567
Variance1.3089085 × 109
MonotonicityNot monotonic
2023-12-10T23:01:33.681943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
25.0%
13 1
 
3.6%
14000 1
 
3.6%
1400 1
 
3.6%
7 1
 
3.6%
6 1
 
3.6%
192000 1
 
3.6%
8 1
 
3.6%
976 1
 
3.6%
217 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
0 7
25.0%
1 1
 
3.6%
3 1
 
3.6%
5 1
 
3.6%
6 1
 
3.6%
7 1
 
3.6%
8 1
 
3.6%
10 1
 
3.6%
13 1
 
3.6%
60 1
 
3.6%
ValueCountFrequency (%)
192000 1
3.6%
14000 1
3.6%
12400 1
3.6%
7060 1
3.6%
1960 1
3.6%
1400 1
3.6%
976 1
3.6%
941 1
3.6%
711 1
3.6%
632 1
3.6%

영상수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean115.57143
Minimum0
Maximum1422
Zeros2
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T23:01:33.838326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.35
Q12.75
median16
Q337
95-th percentile719.35
Maximum1422
Range1422
Interquartile range (IQR)34.25

Descriptive statistics

Standard deviation314.51202
Coefficient of variation (CV)2.7213648
Kurtosis12.719121
Mean115.57143
Median Absolute Deviation (MAD)15
Skewness3.5786336
Sum3236
Variance98917.81
MonotonicityNot monotonic
2023-12-10T23:01:33.998404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
16 4
14.3%
1 3
 
10.7%
0 2
 
7.1%
2 2
 
7.1%
7 2
 
7.1%
37 2
 
7.1%
34 1
 
3.6%
4 1
 
3.6%
291 1
 
3.6%
113 1
 
3.6%
Other values (9) 9
32.1%
ValueCountFrequency (%)
0 2
7.1%
1 3
10.7%
2 2
7.1%
3 1
 
3.6%
4 1
 
3.6%
7 2
7.1%
13 1
 
3.6%
16 4
14.3%
17 1
 
3.6%
25 1
 
3.6%
ValueCountFrequency (%)
1422 1
3.6%
950 1
3.6%
291 1
3.6%
113 1
3.6%
104 1
3.6%
69 1
3.6%
37 2
7.1%
34 1
3.6%
32 1
3.6%
25 1
3.6%

조회수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1808543.8
Minimum0
Maximum33065489
Zeros3
Zeros (%)10.7%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T23:01:34.175573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1226.25
median7101
Q3310983
95-th percentile8123540.8
Maximum33065489
Range33065489
Interquartile range (IQR)310756.75

Descriptive statistics

Standard deviation6492540.9
Coefficient of variation (CV)3.5899273
Kurtosis21.709625
Mean1808543.8
Median Absolute Deviation (MAD)7101
Skewness4.5585254
Sum50639227
Variance4.2153087 × 1013
MonotonicityNot monotonic
2023-12-10T23:01:34.321117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 3
 
10.7%
1146842 1
 
3.6%
137795 1
 
3.6%
1164 1
 
3.6%
303 1
 
3.6%
33065489 1
 
3.6%
975 1
 
3.6%
395643 1
 
3.6%
282763 1
 
3.6%
46924 1
 
3.6%
Other values (16) 16
57.1%
ValueCountFrequency (%)
0 3
10.7%
10 1
 
3.6%
18 1
 
3.6%
23 1
 
3.6%
149 1
 
3.6%
252 1
 
3.6%
303 1
 
3.6%
325 1
 
3.6%
975 1
 
3.6%
1164 1
 
3.6%
ValueCountFrequency (%)
33065489 1
3.6%
11330363 1
3.6%
2168014 1
3.6%
1146842 1
3.6%
1018372 1
3.6%
823456 1
3.6%
395643 1
3.6%
282763 1
3.6%
152119 1
3.6%
137795 1
3.6%

덧글수
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
0
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 28
100.0%

Length

2023-12-10T23:01:34.491560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:01:34.585984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 28
100.0%

긍정평가비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.613571
Minimum0
Maximum200
Zeros8
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T23:01:34.682252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median72.525
Q397.52
95-th percentile113.883
Maximum200
Range200
Interquartile range (IQR)97.52

Descriptive statistics

Standard deviation51.83189
Coefficient of variation (CV)0.86946459
Kurtosis0.060698539
Mean59.613571
Median Absolute Deviation (MAD)28.84
Skewness0.46335087
Sum1669.18
Variance2686.5448
MonotonicityNot monotonic
2023-12-10T23:01:34.821276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 8
28.6%
18.78 1
 
3.6%
97.88 1
 
3.6%
23.3 1
 
3.6%
62.13 1
 
3.6%
99.96 1
 
3.6%
11.17 1
 
3.6%
121.38 1
 
3.6%
88.1 1
 
3.6%
93.27 1
 
3.6%
Other values (11) 11
39.3%
ValueCountFrequency (%)
0.0 8
28.6%
11.17 1
 
3.6%
18.78 1
 
3.6%
23.3 1
 
3.6%
42.28 1
 
3.6%
56.85 1
 
3.6%
62.13 1
 
3.6%
82.92 1
 
3.6%
85.81 1
 
3.6%
88.1 1
 
3.6%
ValueCountFrequency (%)
200.0 1
3.6%
121.38 1
3.6%
99.96 1
3.6%
99.95 1
3.6%
99.57 1
3.6%
99.31 1
3.6%
97.88 1
3.6%
97.4 1
3.6%
94.94 1
3.6%
94.18 1
3.6%

부정평가비율
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
0
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 28
100.0%

Length

2023-12-10T23:01:35.100116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:01:35.240451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 28
100.0%

키워드1명
Text

MISSING 

Distinct13
Distinct (%)92.9%
Missing14
Missing (%)50.0%
Memory size356.0 B
2023-12-10T23:01:35.433624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2142857
Min length1

Characters and Unicode

Total characters31
Distinct characters27
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

Unique12 ?
Unique (%)85.7%

Sample

1st row부동산
2nd row중개
3rd row중고
4th row사진
5th row이야기
ValueCountFrequency (%)
여행 2
14.3%
부동산 1
 
7.1%
중개 1
 
7.1%
중고 1
 
7.1%
사진 1
 
7.1%
이야기 1
 
7.1%
유튜브 1
 
7.1%
카 1
 
7.1%
사용 1
 
7.1%
판매 1
 
7.1%
Other values (3) 3
21.4%
2023-12-10T23:01:36.023434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
여 2
 
6.5%
중 2
 
6.5%
사 2
 
6.5%
행 2
 
6.5%
브 1
 
3.2%
서 1
 
3.2%
달 1
 
3.2%
니 1
 
3.2%
언 1
 
3.2%
조 1
 
3.2%
Other values (17) 17
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 2
 
6.5%
중 2
 
6.5%
사 2
 
6.5%
행 2
 
6.5%
브 1
 
3.2%
서 1
 
3.2%
달 1
 
3.2%
니 1
 
3.2%
언 1
 
3.2%
조 1
 
3.2%
Other values (17) 17
54.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 2
 
6.5%
중 2
 
6.5%
사 2
 
6.5%
행 2
 
6.5%
브 1
 
3.2%
서 1
 
3.2%
달 1
 
3.2%
니 1
 
3.2%
언 1
 
3.2%
조 1
 
3.2%
Other values (17) 17
54.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
여 2
 
6.5%
중 2
 
6.5%
사 2
 
6.5%
행 2
 
6.5%
브 1
 
3.2%
서 1
 
3.2%
달 1
 
3.2%
니 1
 
3.2%
언 1
 
3.2%
조 1
 
3.2%
Other values (17) 17
54.8%

키워드2명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing26
Missing (%)92.9%
Memory size356.0 B
2023-12-10T23:01:36.240536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Characters and Unicode

Total characters5
Distinct characters5
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

Unique2 ?
Unique (%)100.0%

Sample

1st row사무소
2nd row피트
ValueCountFrequency (%)
사무소 1
50.0%
피트 1
50.0%
2023-12-10T23:01:36.772251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1
20.0%
무 1
20.0%
소 1
20.0%
피 1
20.0%
트 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1
20.0%
무 1
20.0%
소 1
20.0%
피 1
20.0%
트 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1
20.0%
무 1
20.0%
소 1
20.0%
피 1
20.0%
트 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1
20.0%
무 1
20.0%
소 1
20.0%
피 1
20.0%
트 1
20.0%

Interactions

2023-12-10T23:01:28.897167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:26.861115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:27.519615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:28.229161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:29.197612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:27.010513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:27.711220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:28.399056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:29.336764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:27.149845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:27.850543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:28.541912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:29.497246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:27.292336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:28.023582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:01:28.723692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:01:36.941196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채널ID채널범주명채널명구독자수영상수조회수긍정평가비율키워드1명키워드2명
채널ID1.0001.0001.0001.0001.0001.0001.0001.0000.000
채널범주명1.0001.0001.0000.0000.0000.5100.7140.6560.000
채널명1.0001.0001.0001.0001.0001.0001.0001.0000.000
구독자수1.0000.0001.0001.0001.0001.0000.0001.000NaN
영상수1.0000.0001.0001.0001.0000.6420.0001.000NaN
조회수1.0000.5101.0001.0000.6421.0000.0001.000NaN
긍정평가비율1.0000.7141.0000.0000.0000.0001.0001.0000.000
키워드1명1.0000.6561.0001.0001.0001.0001.0001.0000.000
키워드2명0.0000.0000.000NaNNaNNaN0.0000.0001.000
2023-12-10T23:01:37.136726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구독자수영상수조회수긍정평가비율
구독자수1.0000.6770.7940.537
영상수0.6771.0000.7930.410
조회수0.7940.7931.0000.701
긍정평가비율0.5370.4100.7011.000

Missing values

2023-12-10T23:01:29.750490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:01:29.982240image/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.
2023-12-10T23:01:30.111202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

채널ID채널범주명채널명구독자수영상수조회수덧글수긍정평가비율부정평가비율키워드1명키워드2명
0https://www.youtube.com/channel/UC--DRzpNwUKutByTr3-aIGw환경환경130000.00<NA><NA>
1https://www.youtube.com/channel/UC--K42RqMIaemoYb4du7djg관람객타임뉴스1163593018.780<NA><NA>
2https://www.youtube.com/channel/UC--bmnt1Y_syiANwBKQtFOQ상권부동산사피엔스6321628588097.40부동산<NA>
3https://www.youtube.com/channel/UC-0fPeo4F1q43YndRgFuYog상권한정우공인중개사31725200.00중개<NA>
4https://www.youtube.com/channel/UC-0v-M5WQUQQGPDFZeLTknA상생mampan7124001611330363099.950<NA><NA>
5https://www.youtube.com/channel/UC-10iF5IE81NV20mPR3Y8dg소비자Pissed Consumer19609501018372085.810<NA><NA>
6https://www.youtube.com/channel/UC-1FjaoXAnoIT8uQy8kmk8g구인/구직광주중고나라52149042.280중고<NA>
7https://www.youtube.com/channel/UC-1MAoVxI7hjEVJ4YSicHTg구매텔레그램 kaka8282구매문의 카톡 ka77700000.00<NA><NA>
8https://www.youtube.com/channel/UC-2MOePjeo8Fl3Blg11QipA구매TV디갤706014222168014082.920사진<NA>
9https://www.youtube.com/channel/UC-2PvcAb72Lg-at1x0jaDkQ환경최환경012300.00<NA><NA>
채널ID채널범주명채널명구독자수영상수조회수덧글수긍정평가비율부정평가비율키워드1명키워드2명
18https://www.youtube.com/channel/UC-8grir9vKHNYTHsYrxSGvg여행신기루의 춤 여행 MIRAGE Dance story157347846056.850<NA><NA>
19https://www.youtube.com/channel/UC-8vGTZzYWEn5-c7Ddj-dmQ구인인천수길대형렉카2172546924093.270카<NA>
20https://www.youtube.com/channel/UC-9q-muZukChcGJmTRGlG8w환경raonsquare976104282763088.10사용<NA>
21https://www.youtube.com/channel/UC-APCmqJwwPzBdEQDFROeYg상품쿠팡 마켓플레이스0373956430121.380판매<NA>
22https://www.youtube.com/channel/UC-AjXxePOZpvXuiE1iKMZFQ채용권용채용돌01000.00<NA><NA>
23https://www.youtube.com/channel/UC-BaVrxOoE9dvE1wwWEIOFA구인범구리8113975011.170게조<NA>
24https://www.youtube.com/channel/UC-BqPABOl7c7rR5EoJJZ0UA구매방언니 - 방송국에 사는 언니들19200029133065489099.960언니<NA>
25https://www.youtube.com/channel/UC-ByXIQTEU3UGy6aINU_5gQ상인강상모64303062.130달서구사무소
26https://www.youtube.com/channel/UC-DDDQJN7KoJorUjBNPaQJQ여행마술여행7161164023.30<NA><NA>
27https://www.youtube.com/channel/UC-FSbbslVr9uDABVMdHcoPQ볼거리오늘모해?140037137795097.880여행피트