Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells8
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory634.8 KiB
Average record size in memory65.0 B

Variable types

Numeric1
Text4
DateTime1
Categorical1

Dataset

Description경상남도 진주시 관광상품 후기 게시물을 바탕으로 생성된 관광상품별 키워드 해시태그 및 게시물 url에 대한 데이터를 제공합니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15097739

Alerts

번호 is highly overall correlated with 관광상품분류High correlation
관광상품분류 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:23:16.558366
Analysis finished2023-12-11 00:23:18.215824
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6042991.7
Minimum6000001
Maximum6085811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:23:18.291673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6000001
5-th percentile6004510.1
Q16021206.5
median6043480.5
Q36064427.5
95-th percentile6081468.5
Maximum6085811
Range85810
Interquartile range (IQR)43221

Descriptive statistics

Standard deviation24732.61
Coefficient of variation (CV)0.0040927757
Kurtosis-1.2062801
Mean6042991.7
Median Absolute Deviation (MAD)21557
Skewness-0.01678441
Sum6.0429917 × 1010
Variance6.1170198 × 108
MonotonicityNot monotonic
2023-12-11T09:23:18.417419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6006105 1
 
< 0.1%
6026949 1
 
< 0.1%
6053801 1
 
< 0.1%
6079367 1
 
< 0.1%
6002837 1
 
< 0.1%
6071395 1
 
< 0.1%
6052568 1
 
< 0.1%
6052838 1
 
< 0.1%
6056628 1
 
< 0.1%
6050551 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
6000001 1
< 0.1%
6000003 1
< 0.1%
6000033 1
< 0.1%
6000037 1
< 0.1%
6000046 1
< 0.1%
6000047 1
< 0.1%
6000049 1
< 0.1%
6000065 1
< 0.1%
6000066 1
< 0.1%
6000068 1
< 0.1%
ValueCountFrequency (%)
6085811 1
< 0.1%
6085796 1
< 0.1%
6085783 1
< 0.1%
6085781 1
< 0.1%
6085756 1
< 0.1%
6085752 1
< 0.1%
6085747 1
< 0.1%
6085731 1
< 0.1%
6085722 1
< 0.1%
6085713 1
< 0.1%

홈페이지주소(URL)
Text

Distinct3663
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:23:18.686731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length635
Median length323
Mean length56.5221
Min length26

Characters and Unicode

Total characters565221
Distinct characters71
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique968 ?
Unique (%)9.7%

Sample

1st rowhttps://bezzera.tistory.com/1641?category=11359
2nd rowhttps://blog.naver.com/1117cslee?Redirect=Log&logNo=221668095895
3rd rowhttps://wishbeen.tistory.com/2623
4th rowhttps://waegwanlife.tistory.com/6031
5th rowhttps://blog.naver.com/goodkyt?Redirect=Log&logNo=222340317800
ValueCountFrequency (%)
https://blog.naver.com/ydl1?redirect=log&logno=221420598601 19
 
0.2%
https://blog.naver.com/ellyura?redirect=log&logno=221706752476 15
 
0.1%
https://blog.naver.com/nadongyup?redirect=log&logno=222388508046 14
 
0.1%
https://blog.naver.com/wnsdud3310?redirect=log&logno=222377447780 14
 
0.1%
https://blog.naver.com/pearl286?redirect=log&logno=221556451580 13
 
0.1%
https://blog.naver.com/hsj1191?redirect=log&logno=222293699251 13
 
0.1%
https://blog.naver.com/skeksk_2000?redirect=log&logno=222305144218 11
 
0.1%
https://blog.naver.com/min__0_0?redirect=log&logno=222287953105 11
 
0.1%
https://blog.naver.com/eoiw?redirect=log&logno=222043122840 11
 
0.1%
https://blog.naver.com/echo78?redirect=log&logno=222140573799 11
 
0.1%
Other values (3653) 9868
98.7%
2023-12-11T09:23:19.196616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 41717
 
7.4%
t 33834
 
6.0%
/ 33014
 
5.8%
2 26084
 
4.6%
e 25163
 
4.5%
g 22999
 
4.1%
. 20000
 
3.5%
c 18534
 
3.3%
r 18056
 
3.2%
l 17083
 
3.0%
Other values (61) 308737
54.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 322076
57.0%
Decimal Number 106497
 
18.8%
Other Punctuation 83202
 
14.7%
Uppercase Letter 37709
 
6.7%
Math Symbol 13739
 
2.4%
Dash Punctuation 1128
 
0.2%
Connector Punctuation 870
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 41717
13.0%
t 33834
 
10.5%
e 25163
 
7.8%
g 22999
 
7.1%
c 18534
 
5.8%
r 18056
 
5.6%
l 17083
 
5.3%
s 15512
 
4.8%
a 14372
 
4.5%
m 13644
 
4.2%
Other values (16) 101162
31.4%
Uppercase Letter
ValueCountFrequency (%)
R 6932
18.4%
N 6857
18.2%
L 6753
17.9%
C 2973
7.9%
E 2539
 
6.7%
B 2404
 
6.4%
A 1846
 
4.9%
D 848
 
2.2%
M 621
 
1.6%
F 591
 
1.6%
Other values (16) 5345
14.2%
Decimal Number
ValueCountFrequency (%)
2 26084
24.5%
1 12064
11.3%
0 9413
 
8.8%
3 9165
 
8.6%
9 9052
 
8.5%
8 8895
 
8.4%
4 8855
 
8.3%
7 7817
 
7.3%
5 7589
 
7.1%
6 7563
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/ 33014
39.7%
. 20000
24.0%
: 10000
 
12.0%
? 7307
 
8.8%
% 6449
 
7.8%
& 6432
 
7.7%
Math Symbol
ValueCountFrequency (%)
= 13739
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1128
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 870
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 359785
63.7%
Common 205436
36.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 41717
 
11.6%
t 33834
 
9.4%
e 25163
 
7.0%
g 22999
 
6.4%
c 18534
 
5.2%
r 18056
 
5.0%
l 17083
 
4.7%
s 15512
 
4.3%
a 14372
 
4.0%
m 13644
 
3.8%
Other values (42) 138871
38.6%
Common
ValueCountFrequency (%)
/ 33014
16.1%
2 26084
12.7%
. 20000
 
9.7%
= 13739
 
6.7%
1 12064
 
5.9%
: 10000
 
4.9%
0 9413
 
4.6%
3 9165
 
4.5%
9 9052
 
4.4%
8 8895
 
4.3%
Other values (9) 54010
26.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 565221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 41717
 
7.4%
t 33834
 
6.0%
/ 33014
 
5.8%
2 26084
 
4.6%
e 25163
 
4.5%
g 22999
 
4.1%
. 20000
 
3.5%
c 18534
 
3.3%
r 18056
 
3.2%
l 17083
 
3.0%
Other values (61) 308737
54.6%

관광상품명
Text

Distinct1123
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:23:19.541937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length82
Mean length6.668
Min length1

Characters and Unicode

Total characters66680
Distinct characters645
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

Unique213 ?
Unique (%)2.1%

Sample

1st row국립진주박물관
2nd row밥통 진주점
3rd row봉선당
4th row중앙집
5th row서박사냉면
ValueCountFrequency (%)
진주성 659
 
5.5%
경상남도수목원 345
 
2.9%
진양호 274
 
2.3%
진주레일바이크놀이공원 271
 
2.3%
월아산 223
 
1.9%
진주점 197
 
1.7%
진주 183
 
1.5%
숲속의 180
 
1.5%
진주익룡발자국전시관 158
 
1.3%
본점 144
 
1.2%
Other values (1199) 9276
77.9%
2023-12-11T09:23:20.099559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
진 3471
 
5.2%
주 2967
 
4.4%
1917
 
2.9%
이 1863
 
2.8%
호 1642
 
2.5%
원 1434
 
2.2%
점 1117
 
1.7%
성 993
 
1.5%
산 951
 
1.4%
스 843
 
1.3%
Other values (635) 49482
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62349
93.5%
Space Separator 1917
 
2.9%
Other Punctuation 586
 
0.9%
Decimal Number 459
 
0.7%
Close Punctuation 353
 
0.5%
Open Punctuation 353
 
0.5%
Uppercase Letter 341
 
0.5%
Lowercase Letter 322
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 3471
 
5.6%
주 2967
 
4.8%
이 1863
 
3.0%
호 1642
 
2.6%
원 1434
 
2.3%
점 1117
 
1.8%
성 993
 
1.6%
산 951
 
1.5%
스 843
 
1.4%
남 839
 
1.3%
Other values (583) 46229
74.1%
Uppercase Letter
ValueCountFrequency (%)
A 85
24.9%
M 41
12.0%
B 38
11.1%
I 32
 
9.4%
S 24
 
7.0%
O 21
 
6.2%
K 19
 
5.6%
E 13
 
3.8%
C 11
 
3.2%
N 10
 
2.9%
Other values (9) 47
13.8%
Lowercase Letter
ValueCountFrequency (%)
o 72
22.4%
e 45
14.0%
r 37
11.5%
f 32
9.9%
m 29
9.0%
a 26
 
8.1%
c 22
 
6.8%
s 15
 
4.7%
i 9
 
2.8%
t 7
 
2.2%
Other values (7) 28
 
8.7%
Decimal Number
ValueCountFrequency (%)
5 113
24.6%
0 82
17.9%
2 71
15.5%
6 59
12.9%
1 49
10.7%
4 38
 
8.3%
9 14
 
3.1%
3 14
 
3.1%
7 12
 
2.6%
8 7
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 523
89.2%
& 55
 
9.4%
. 8
 
1.4%
Space Separator
ValueCountFrequency (%)
1917
100.0%
Close Punctuation
ValueCountFrequency (%)
) 353
100.0%
Open Punctuation
ValueCountFrequency (%)
( 353
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62349
93.5%
Common 3668
 
5.5%
Latin 663
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 3471
 
5.6%
주 2967
 
4.8%
이 1863
 
3.0%
호 1642
 
2.6%
원 1434
 
2.3%
점 1117
 
1.8%
성 993
 
1.6%
산 951
 
1.5%
스 843
 
1.4%
남 839
 
1.3%
Other values (583) 46229
74.1%
Latin
ValueCountFrequency (%)
A 85
 
12.8%
o 72
 
10.9%
e 45
 
6.8%
M 41
 
6.2%
B 38
 
5.7%
r 37
 
5.6%
f 32
 
4.8%
I 32
 
4.8%
m 29
 
4.4%
a 26
 
3.9%
Other values (26) 226
34.1%
Common
ValueCountFrequency (%)
1917
52.3%
/ 523
 
14.3%
) 353
 
9.6%
( 353
 
9.6%
5 113
 
3.1%
0 82
 
2.2%
2 71
 
1.9%
6 59
 
1.6%
& 55
 
1.5%
1 49
 
1.3%
Other values (6) 93
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62349
93.5%
ASCII 4331
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
진 3471
 
5.6%
주 2967
 
4.8%
이 1863
 
3.0%
호 1642
 
2.6%
원 1434
 
2.3%
점 1117
 
1.8%
성 993
 
1.6%
산 951
 
1.5%
스 843
 
1.4%
남 839
 
1.3%
Other values (583) 46229
74.1%
ASCII
ValueCountFrequency (%)
1917
44.3%
/ 523
 
12.1%
) 353
 
8.2%
( 353
 
8.2%
5 113
 
2.6%
A 85
 
2.0%
0 82
 
1.9%
o 72
 
1.7%
2 71
 
1.6%
6 59
 
1.4%
Other values (42) 703
 
16.2%

해시태그
Text

Distinct4920
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:23:20.466505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length3.6506
Min length1

Characters and Unicode

Total characters36506
Distinct characters943
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3645 ?
Unique (%)36.4%

Sample

1st row박물관
2nd row돈까스
3rd row가격이저렴
4th row초밥백반달인
5th row어린이날
ValueCountFrequency (%)
진주 279
 
2.8%
진주맛집 90
 
0.9%
맛집 80
 
0.8%
진주성 75
 
0.7%
진주여행 73
 
0.7%
남강 64
 
0.6%
여행 62
 
0.6%
진주가볼만한곳 52
 
0.5%
카페 45
 
0.4%
진양호 41
 
0.4%
Other values (4908) 9140
91.4%
2023-12-11T09:23:20.956336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1983
 
5.4%
진 1972
 
5.4%
이 728
 
2.0%
집 632
 
1.7%
맛 611
 
1.7%
스 492
 
1.3%
장 418
 
1.1%
동 413
 
1.1%
시 386
 
1.1%
가 382
 
1.0%
Other values (933) 28489
78.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36171
99.1%
Lowercase Letter 194
 
0.5%
Decimal Number 82
 
0.2%
Uppercase Letter 57
 
0.2%
Connector Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1983
 
5.5%
진 1972
 
5.5%
이 728
 
2.0%
집 632
 
1.7%
맛 611
 
1.7%
스 492
 
1.4%
장 418
 
1.2%
동 413
 
1.1%
시 386
 
1.1%
가 382
 
1.1%
Other values (876) 28154
77.8%
Lowercase Letter
ValueCountFrequency (%)
a 24
 
12.4%
n 13
 
6.7%
u 12
 
6.2%
i 12
 
6.2%
s 11
 
5.7%
m 11
 
5.7%
r 11
 
5.7%
e 11
 
5.7%
g 11
 
5.7%
o 11
 
5.7%
Other values (14) 67
34.5%
Uppercase Letter
ValueCountFrequency (%)
R 5
 
8.8%
P 5
 
8.8%
V 5
 
8.8%
B 5
 
8.8%
I 4
 
7.0%
T 4
 
7.0%
D 3
 
5.3%
N 3
 
5.3%
Q 3
 
5.3%
J 2
 
3.5%
Other values (11) 18
31.6%
Decimal Number
ValueCountFrequency (%)
2 13
15.9%
0 12
14.6%
1 11
13.4%
3 11
13.4%
4 9
11.0%
5 7
8.5%
8 7
8.5%
6 5
 
6.1%
7 4
 
4.9%
9 3
 
3.7%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36171
99.1%
Latin 251
 
0.7%
Common 84
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1983
 
5.5%
진 1972
 
5.5%
이 728
 
2.0%
집 632
 
1.7%
맛 611
 
1.7%
스 492
 
1.4%
장 418
 
1.2%
동 413
 
1.1%
시 386
 
1.1%
가 382
 
1.1%
Other values (876) 28154
77.8%
Latin
ValueCountFrequency (%)
a 24
 
9.6%
n 13
 
5.2%
u 12
 
4.8%
i 12
 
4.8%
s 11
 
4.4%
m 11
 
4.4%
r 11
 
4.4%
e 11
 
4.4%
g 11
 
4.4%
o 11
 
4.4%
Other values (35) 124
49.4%
Common
ValueCountFrequency (%)
2 13
15.5%
0 12
14.3%
1 11
13.1%
3 11
13.1%
4 9
10.7%
5 7
8.3%
8 7
8.3%
6 5
 
6.0%
7 4
 
4.8%
9 3
 
3.6%
Other values (2) 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36171
99.1%
ASCII 335
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1983
 
5.5%
진 1972
 
5.5%
이 728
 
2.0%
집 632
 
1.7%
맛 611
 
1.7%
스 492
 
1.4%
장 418
 
1.2%
동 413
 
1.1%
시 386
 
1.1%
가 382
 
1.1%
Other values (876) 28154
77.8%
ASCII
ValueCountFrequency (%)
a 24
 
7.2%
2 13
 
3.9%
n 13
 
3.9%
u 12
 
3.6%
i 12
 
3.6%
0 12
 
3.6%
1 11
 
3.3%
s 11
 
3.3%
3 11
 
3.3%
m 11
 
3.3%
Other values (47) 205
61.2%

정렬순서
Text

Distinct7123
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:23:21.290704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length5.7321
Min length2

Characters and Unicode

Total characters57321
Distinct characters943
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5876 ?
Unique (%)58.8%

Sample

1st row박물관:5
2nd row돈까스:4
3rd row가격이저렴:1
4th row초밥백반달인:4
5th row어린이날:1
ValueCountFrequency (%)
진주맛집:1 41
 
0.4%
진주가볼만한곳:1 38
 
0.4%
진주여행:1 35
 
0.3%
진주:1 31
 
0.3%
진주레일바이크:1 29
 
0.3%
진주성:1 19
 
0.2%
진주맛집:2 19
 
0.2%
진주여행:2 19
 
0.2%
레일바이크:1 18
 
0.2%
진주:4 18
 
0.2%
Other values (7113) 9734
97.3%
2023-12-11T09:23:21.700701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 9999
 
17.4%
1 5506
 
9.6%
2 2116
 
3.7%
주 1982
 
3.5%
진 1971
 
3.4%
3 1058
 
1.8%
이 727
 
1.3%
4 688
 
1.2%
집 632
 
1.1%
맛 611
 
1.1%
Other values (933) 32031
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36167
63.1%
Decimal Number 10902
 
19.0%
Other Punctuation 9999
 
17.4%
Lowercase Letter 191
 
0.3%
Uppercase Letter 60
 
0.1%
Connector Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1982
 
5.5%
진 1971
 
5.4%
이 727
 
2.0%
집 632
 
1.7%
맛 611
 
1.7%
스 492
 
1.4%
장 418
 
1.2%
동 412
 
1.1%
시 386
 
1.1%
가 382
 
1.1%
Other values (875) 28154
77.8%
Lowercase Letter
ValueCountFrequency (%)
a 24
 
12.6%
n 13
 
6.8%
u 12
 
6.3%
r 11
 
5.8%
s 11
 
5.8%
m 11
 
5.8%
o 11
 
5.8%
g 11
 
5.8%
i 11
 
5.8%
e 11
 
5.8%
Other values (14) 65
34.0%
Uppercase Letter
ValueCountFrequency (%)
V 6
 
10.0%
P 6
 
10.0%
B 5
 
8.3%
R 5
 
8.3%
I 5
 
8.3%
T 4
 
6.7%
N 3
 
5.0%
Q 3
 
5.0%
D 3
 
5.0%
O 2
 
3.3%
Other values (11) 18
30.0%
Decimal Number
ValueCountFrequency (%)
1 5506
50.5%
2 2116
 
19.4%
3 1058
 
9.7%
4 688
 
6.3%
5 444
 
4.1%
6 320
 
2.9%
7 247
 
2.3%
8 219
 
2.0%
9 161
 
1.5%
0 143
 
1.3%
Other Punctuation
ValueCountFrequency (%)
: 9999
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36167
63.1%
Common 20903
36.5%
Latin 251
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1982
 
5.5%
진 1971
 
5.4%
이 727
 
2.0%
집 632
 
1.7%
맛 611
 
1.7%
스 492
 
1.4%
장 418
 
1.2%
동 412
 
1.1%
시 386
 
1.1%
가 382
 
1.1%
Other values (875) 28154
77.8%
Latin
ValueCountFrequency (%)
a 24
 
9.6%
n 13
 
5.2%
u 12
 
4.8%
r 11
 
4.4%
s 11
 
4.4%
m 11
 
4.4%
o 11
 
4.4%
g 11
 
4.4%
i 11
 
4.4%
e 11
 
4.4%
Other values (35) 125
49.8%
Common
ValueCountFrequency (%)
: 9999
47.8%
1 5506
26.3%
2 2116
 
10.1%
3 1058
 
5.1%
4 688
 
3.3%
5 444
 
2.1%
6 320
 
1.5%
7 247
 
1.2%
8 219
 
1.0%
9 161
 
0.8%
Other values (3) 145
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36167
63.1%
ASCII 21154
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 9999
47.3%
1 5506
26.0%
2 2116
 
10.0%
3 1058
 
5.0%
4 688
 
3.3%
5 444
 
2.1%
6 320
 
1.5%
7 247
 
1.2%
8 219
 
1.0%
9 161
 
0.8%
Other values (48) 396
 
1.9%
Hangul
ValueCountFrequency (%)
주 1982
 
5.5%
진 1971
 
5.4%
이 727
 
2.0%
집 632
 
1.7%
맛 611
 
1.7%
스 492
 
1.4%
장 418
 
1.2%
동 412
 
1.1%
시 386
 
1.1%
가 382
 
1.1%
Other values (875) 28154
77.8%

해시태그생성일
Date

Distinct52
Distinct (%)0.5%
Missing8
Missing (%)0.1%
Memory size156.2 KiB
Minimum2021-08-09 00:00:00
Maximum2121-10-07 00:00:00
2023-12-11T09:23:21.818222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:23:21.935018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관광상품분류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
음식점
4599 
관광지
4249 
숙소
1142 
행사
 
10

Length

Max length3
Median length3
Mean length2.8848
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
음식점 4599
46.0%
관광지 4249
42.5%
숙소 1142
 
11.4%
행사 10
 
0.1%

Length

2023-12-11T09:23:22.053705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:23:22.142513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식점 4599
46.0%
관광지 4249
42.5%
숙소 1142
 
11.4%
행사 10
 
0.1%

Interactions

2023-12-11T09:23:17.944961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:23:22.199909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호해시태그생성일관광상품분류
번호1.0000.6630.853
해시태그생성일0.6631.0000.690
관광상품분류0.8530.6901.000
2023-12-11T09:23:22.497383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호관광상품분류
번호1.0000.702
관광상품분류0.7021.000

Missing values

2023-12-11T09:23:18.057736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:23:18.162415image/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

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