Overview

Dataset statistics

Number of variables12
Number of observations543
Missing cells1455
Missing cells (%)22.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory52.6 KiB
Average record size in memory99.2 B

Variable types

Text7
Numeric3
DateTime1
Categorical1

Dataset

Description경상남도 사천시 문화관광홈페이지 전시내용 테이블 자료(제목,조회수,등록일, 주소,위도, 경도 등)에 대한 자료(영어) 입니다.
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15084121

Alerts

계절 is highly imbalanced (86.5%)Imbalance
위치 has 454 (83.6%) missing valuesMissing
시간 has 386 (71.1%) missing valuesMissing
홈페이지 has 494 (91.0%) missing valuesMissing
지도 주소 has 10 (1.8%) missing valuesMissing
값1 has 77 (14.2%) missing valuesMissing
위도 has 17 (3.1%) missing valuesMissing
경도 has 17 (3.1%) missing valuesMissing

Reproduction

Analysis started2023-12-10 23:41:34.011423
Analysis finished2023-12-10 23:41:36.317422
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제목
Text

Distinct534
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2023-12-11T08:41:36.559973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length31
Mean length11.657459
Min length1

Characters and Unicode

Total characters6330
Distinct characters339
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique525 ?
Unique (%)96.7%

Sample

1st rowMt. Waryongsan
2nd rowMt. Bongmyeongsan
3rd rowMt. Gaksan
4th rowHallyeosudo
5th rowNamildae Beach
ValueCountFrequency (%)
park 13
 
1.8%
12
 
1.7%
mt 11
 
1.5%
sacheon 10
 
1.4%
experience 9
 
1.3%
village 8
 
1.1%
market 7
 
1.0%
samcheonpo 6
 
0.8%
temple 4
 
0.6%
bridge 4
 
0.6%
Other values (591) 633
88.3%
2023-12-11T08:41:37.063175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 609
 
9.6%
o 529
 
8.4%
n 463
 
7.3%
a 448
 
7.1%
g 280
 
4.4%
i 260
 
4.1%
t 241
 
3.8%
l 210
 
3.3%
m 191
 
3.0%
174
 
2.7%
Other values (329) 2925
46.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4525
71.5%
Other Letter 1084
 
17.1%
Uppercase Letter 483
 
7.6%
Space Separator 174
 
2.7%
Dash Punctuation 16
 
0.3%
Other Punctuation 16
 
0.3%
Close Punctuation 14
 
0.2%
Open Punctuation 14
 
0.2%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 34
 
3.1%
당 29
 
2.7%
가 21
 
1.9%
집 21
 
1.9%
장 20
 
1.8%
정 17
 
1.6%
산 16
 
1.5%
구 15
 
1.4%
사 15
 
1.4%
한 14
 
1.3%
Other values (269) 882
81.4%
Lowercase Letter
ValueCountFrequency (%)
e 609
13.5%
o 529
11.7%
n 463
10.2%
a 448
 
9.9%
g 280
 
6.2%
i 260
 
5.7%
t 241
 
5.3%
l 210
 
4.6%
m 191
 
4.2%
h 158
 
3.5%
Other values (15) 1136
25.1%
Uppercase Letter
ValueCountFrequency (%)
S 88
18.2%
G 43
 
8.9%
B 39
 
8.1%
D 37
 
7.7%
M 35
 
7.2%
P 31
 
6.4%
J 30
 
6.2%
H 29
 
6.0%
T 16
 
3.3%
C 16
 
3.3%
Other values (13) 119
24.6%
Other Punctuation
ValueCountFrequency (%)
. 11
68.8%
& 3
 
18.8%
· 1
 
6.2%
/ 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
0 1
25.0%
7 1
25.0%
3 1
25.0%
Space Separator
ValueCountFrequency (%)
174
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5008
79.1%
Hangul 1084
 
17.1%
Common 238
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 34
 
3.1%
당 29
 
2.7%
가 21
 
1.9%
집 21
 
1.9%
장 20
 
1.8%
정 17
 
1.6%
산 16
 
1.5%
구 15
 
1.4%
사 15
 
1.4%
한 14
 
1.3%
Other values (269) 882
81.4%
Latin
ValueCountFrequency (%)
e 609
 
12.2%
o 529
 
10.6%
n 463
 
9.2%
a 448
 
8.9%
g 280
 
5.6%
i 260
 
5.2%
t 241
 
4.8%
l 210
 
4.2%
m 191
 
3.8%
h 158
 
3.2%
Other values (38) 1619
32.3%
Common
ValueCountFrequency (%)
174
73.1%
- 16
 
6.7%
) 14
 
5.9%
( 14
 
5.9%
. 11
 
4.6%
& 3
 
1.3%
· 1
 
0.4%
2 1
 
0.4%
/ 1
 
0.4%
0 1
 
0.4%
Other values (2) 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5245
82.9%
Hangul 1084
 
17.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 609
 
11.6%
o 529
 
10.1%
n 463
 
8.8%
a 448
 
8.5%
g 280
 
5.3%
i 260
 
5.0%
t 241
 
4.6%
l 210
 
4.0%
m 191
 
3.6%
174
 
3.3%
Other values (49) 1840
35.1%
Hangul
ValueCountFrequency (%)
식 34
 
3.1%
당 29
 
2.7%
가 21
 
1.9%
집 21
 
1.9%
장 20
 
1.8%
정 17
 
1.6%
산 16
 
1.5%
구 15
 
1.4%
사 15
 
1.4%
한 14
 
1.3%
Other values (269) 882
81.4%
None
ValueCountFrequency (%)
· 1
100.0%

조회수
Real number (ℝ)

Distinct235
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean261.1639
Minimum1
Maximum1903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-11T08:41:37.594997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q119
median39
Q3494.5
95-th percentile1083.2
Maximum1903
Range1902
Interquartile range (IQR)475.5

Descriptive statistics

Standard deviation373.15331
Coefficient of variation (CV)1.4288089
Kurtosis3.1494977
Mean261.1639
Median Absolute Deviation (MAD)35
Skewness1.7757282
Sum141812
Variance139243.39
MonotonicityNot monotonic
2023-12-11T08:41:37.766383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 23
 
4.2%
3 22
 
4.1%
4 18
 
3.3%
35 17
 
3.1%
32 17
 
3.1%
1 14
 
2.6%
5 13
 
2.4%
33 13
 
2.4%
31 12
 
2.2%
38 12
 
2.2%
Other values (225) 382
70.3%
ValueCountFrequency (%)
1 14
2.6%
2 23
4.2%
3 22
4.1%
4 18
3.3%
5 13
2.4%
6 7
 
1.3%
7 4
 
0.7%
8 4
 
0.7%
10 4
 
0.7%
11 4
 
0.7%
ValueCountFrequency (%)
1903 1
0.2%
1851 1
0.2%
1759 1
0.2%
1726 1
0.2%
1622 1
0.2%
1607 1
0.2%
1589 1
0.2%
1524 1
0.2%
1493 1
0.2%
1475 1
0.2%

등록일
Date

Distinct22
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum2013-04-30 00:00:00
Maximum2013-07-10 00:00:00
2023-12-11T08:41:37.914021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:38.043894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

주소
Text

Distinct524
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2023-12-11T08:41:38.392760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length14.088398
Min length6

Characters and Unicode

Total characters7650
Distinct characters139
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique512 ?
Unique (%)94.3%

Sample

1st row노룡동 1번지
2nd row곤명면 용산리 86일원
3rd row사천시 동림동 190일원
4th row늑도동 477 일원(초양휴게소)
5th row향촌동 710 일원
ValueCountFrequency (%)
사천읍 124
 
7.0%
수석리 49
 
2.8%
동금동 49
 
2.8%
서금동 45
 
2.5%
벌리동 42
 
2.4%
1호 41
 
2.3%
용현면 37
 
2.1%
곤명면 35
 
2.0%
4호 34
 
1.9%
3호 32
 
1.8%
Other values (520) 1292
72.6%
2023-12-11T08:41:38.917903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1564
20.4%
지 420
 
5.5%
번 407
 
5.3%
1 405
 
5.3%
동 377
 
4.9%
호 342
 
4.5%
리 311
 
4.1%
4 297
 
3.9%
2 267
 
3.5%
3 233
 
3.0%
Other values (129) 3027
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3855
50.4%
Decimal Number 2084
27.2%
Space Separator 1564
20.4%
Dash Punctuation 97
 
1.3%
Close Punctuation 16
 
0.2%
Open Punctuation 16
 
0.2%
Other Punctuation 16
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 420
 
10.9%
번 407
 
10.6%
동 377
 
9.8%
호 342
 
8.9%
리 311
 
8.1%
사 193
 
5.0%
천 169
 
4.4%
면 151
 
3.9%
읍 126
 
3.3%
금 103
 
2.7%
Other values (112) 1256
32.6%
Decimal Number
ValueCountFrequency (%)
1 405
19.4%
4 297
14.3%
2 267
12.8%
3 233
11.2%
8 174
8.3%
6 163
7.8%
7 152
 
7.3%
5 151
 
7.2%
9 142
 
6.8%
0 100
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 15
93.8%
/ 1
 
6.2%
Space Separator
ValueCountFrequency (%)
1564
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3855
50.4%
Common 3795
49.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 420
 
10.9%
번 407
 
10.6%
동 377
 
9.8%
호 342
 
8.9%
리 311
 
8.1%
사 193
 
5.0%
천 169
 
4.4%
면 151
 
3.9%
읍 126
 
3.3%
금 103
 
2.7%
Other values (112) 1256
32.6%
Common
ValueCountFrequency (%)
1564
41.2%
1 405
 
10.7%
4 297
 
7.8%
2 267
 
7.0%
3 233
 
6.1%
8 174
 
4.6%
6 163
 
4.3%
7 152
 
4.0%
5 151
 
4.0%
9 142
 
3.7%
Other values (7) 247
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3855
50.4%
ASCII 3795
49.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1564
41.2%
1 405
 
10.7%
4 297
 
7.8%
2 267
 
7.0%
3 233
 
6.1%
8 174
 
4.6%
6 163
 
4.3%
7 152
 
4.0%
5 151
 
4.0%
9 142
 
3.7%
Other values (7) 247
 
6.5%
Hangul
ValueCountFrequency (%)
지 420
 
10.9%
번 407
 
10.6%
동 377
 
9.8%
호 342
 
8.9%
리 311
 
8.1%
사 193
 
5.0%
천 169
 
4.4%
면 151
 
3.9%
읍 126
 
3.3%
금 103
 
2.7%
Other values (112) 1256
32.6%

위치
Text

MISSING 

Distinct82
Distinct (%)92.1%
Missing454
Missing (%)83.6%
Memory size4.4 KiB
2023-12-11T08:41:39.171738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length13.966292
Min length4

Characters and Unicode

Total characters1243
Distinct characters129
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)85.4%

Sample

1st row사천시 사남면, 용현면, 벌용동, 남양동
2nd row사천공항에서 22km
3rd row사천공항에서 18Km
4th row삼천포항 일원
5th row삼천포항에서 동쪽으로 3.5㎞
ValueCountFrequency (%)
사천ic에서 30
 
12.7%
삼천포항 14
 
5.9%
곤양ic에서 11
 
4.6%
방향으로 10
 
4.2%
일원 7
 
3.0%
사남면 7
 
3.0%
사천시 7
 
3.0%
22km 5
 
2.1%
사천공항에서 4
 
1.7%
벌용동 4
 
1.7%
Other values (102) 138
58.2%
2023-12-11T08:41:39.632456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
193
 
15.5%
천 73
 
5.9%
서 61
 
4.9%
사 58
 
4.7%
에 56
 
4.5%
m 53
 
4.3%
I 42
 
3.4%
C 42
 
3.4%
k 39
 
3.1%
2 27
 
2.2%
Other values (119) 599
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 723
58.2%
Space Separator 193
 
15.5%
Decimal Number 100
 
8.0%
Uppercase Letter 97
 
7.8%
Lowercase Letter 92
 
7.4%
Other Punctuation 29
 
2.3%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%
Other Symbol 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 73
 
10.1%
서 61
 
8.4%
사 58
 
8.0%
에 56
 
7.7%
포 25
 
3.5%
항 24
 
3.3%
삼 22
 
3.0%
동 21
 
2.9%
양 20
 
2.8%
곤 19
 
2.6%
Other values (97) 344
47.6%
Decimal Number
ValueCountFrequency (%)
2 27
27.0%
1 17
17.0%
5 15
15.0%
0 11
11.0%
3 9
 
9.0%
6 9
 
9.0%
4 7
 
7.0%
9 2
 
2.0%
7 2
 
2.0%
8 1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
I 42
43.3%
C 42
43.3%
K 13
 
13.4%
Lowercase Letter
ValueCountFrequency (%)
m 53
57.6%
k 39
42.4%
Other Punctuation
ValueCountFrequency (%)
, 19
65.5%
. 10
34.5%
Space Separator
ValueCountFrequency (%)
193
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Symbol
ValueCountFrequency (%)
㎞ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 723
58.2%
Common 331
26.6%
Latin 189
 
15.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 73
 
10.1%
서 61
 
8.4%
사 58
 
8.0%
에 56
 
7.7%
포 25
 
3.5%
항 24
 
3.3%
삼 22
 
3.0%
동 21
 
2.9%
양 20
 
2.8%
곤 19
 
2.6%
Other values (97) 344
47.6%
Common
ValueCountFrequency (%)
193
58.3%
2 27
 
8.2%
, 19
 
5.7%
1 17
 
5.1%
5 15
 
4.5%
0 11
 
3.3%
. 10
 
3.0%
3 9
 
2.7%
6 9
 
2.7%
4 7
 
2.1%
Other values (7) 14
 
4.2%
Latin
ValueCountFrequency (%)
m 53
28.0%
I 42
22.2%
C 42
22.2%
k 39
20.6%
K 13
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 723
58.2%
ASCII 518
41.7%
CJK Compat 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
193
37.3%
m 53
 
10.2%
I 42
 
8.1%
C 42
 
8.1%
k 39
 
7.5%
2 27
 
5.2%
, 19
 
3.7%
1 17
 
3.3%
5 15
 
2.9%
K 13
 
2.5%
Other values (11) 58
 
11.2%
Hangul
ValueCountFrequency (%)
천 73
 
10.1%
서 61
 
8.4%
사 58
 
8.0%
에 56
 
7.7%
포 25
 
3.5%
항 24
 
3.3%
삼 22
 
3.0%
동 21
 
2.9%
양 20
 
2.8%
곤 19
 
2.6%
Other values (97) 344
47.6%
CJK Compat
ValueCountFrequency (%)
㎞ 2
100.0%

시간
Text

MISSING 

Distinct54
Distinct (%)34.4%
Missing386
Missing (%)71.1%
Memory size4.4 KiB
2023-12-11T08:41:39.865464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length13.063694
Min length7

Characters and Unicode

Total characters2051
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)22.9%

Sample

1st row09:00 ~ 22:00
2nd row10:00 ~ 22:00
3rd row10:00 ~ 22:00
4th row10:00 ~ 22:00
5th row10:00 ~ 22:00
ValueCountFrequency (%)
156
33.3%
22:00 90
19.2%
10:00 61
 
13.0%
11:00 36
 
7.7%
21:00 26
 
5.5%
09:00 18
 
3.8%
12:00 8
 
1.7%
20:00 7
 
1.5%
20:30 7
 
1.5%
21:30 6
 
1.3%
Other values (23) 54
 
11.5%
2023-12-11T08:41:40.244172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 718
35.0%
318
15.5%
: 315
15.4%
2 249
 
12.1%
1 199
 
9.7%
~ 158
 
7.7%
3 38
 
1.9%
9 24
 
1.2%
6 8
 
0.4%
8 7
 
0.3%
Other values (4) 17
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1259
61.4%
Space Separator 318
 
15.5%
Other Punctuation 316
 
15.4%
Math Symbol 158
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 718
57.0%
2 249
 
19.8%
1 199
 
15.8%
3 38
 
3.0%
9 24
 
1.9%
6 8
 
0.6%
8 7
 
0.6%
7 7
 
0.6%
4 6
 
0.5%
5 3
 
0.2%
Other Punctuation
ValueCountFrequency (%)
: 315
99.7%
, 1
 
0.3%
Space Separator
ValueCountFrequency (%)
318
100.0%
Math Symbol
ValueCountFrequency (%)
~ 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2051
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 718
35.0%
318
15.5%
: 315
15.4%
2 249
 
12.1%
1 199
 
9.7%
~ 158
 
7.7%
3 38
 
1.9%
9 24
 
1.2%
6 8
 
0.4%
8 7
 
0.3%
Other values (4) 17
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2051
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 718
35.0%
318
15.5%
: 315
15.4%
2 249
 
12.1%
1 199
 
9.7%
~ 158
 
7.7%
3 38
 
1.9%
9 24
 
1.2%
6 8
 
0.4%
8 7
 
0.3%
Other values (4) 17
 
0.8%

홈페이지
Text

MISSING 

Distinct32
Distinct (%)65.3%
Missing494
Missing (%)91.0%
Memory size4.4 KiB
2023-12-11T08:41:40.490057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length35
Mean length24.734694
Min length12

Characters and Unicode

Total characters1212
Distinct characters48
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)63.3%

Sample

1st rowhttp://bekchunsa.org/
2nd row서동 346번지 26호
3rd rowhttp://www.namiltte.com
4th rowhttp://blog.naver.com/guswn7262/50025659189
5th rowhttp://myhome.naver.com/kwonwoop
ValueCountFrequency (%)
http://www.4000mall.com 19
37.3%
http://www.namiltte.com 2
 
3.9%
http://www.seapensun.net 1
 
2.0%
http://www.dajayeon.com 1
 
2.0%
http://www.beebong.co.kr/index1.php 1
 
2.0%
http://barian.go2vil.org 1
 
2.0%
http://www.moogo.kr 1
 
2.0%
http://blog.naver.com/ddak56 1
 
2.0%
http://cafe.daum.net/jinjuwinds 1
 
2.0%
http://www.parkjaesam.com 1
 
2.0%
Other values (22) 22
43.1%
2023-12-11T08:41:41.003799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 114
 
9.4%
w 111
 
9.2%
t 105
 
8.7%
. 99
 
8.2%
0 66
 
5.4%
o 64
 
5.3%
m 64
 
5.3%
a 56
 
4.6%
h 54
 
4.5%
p 53
 
4.4%
Other values (38) 426
35.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 797
65.8%
Other Punctuation 260
 
21.5%
Decimal Number 115
 
9.5%
Space Separator 31
 
2.6%
Other Letter 9
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 111
13.9%
t 105
13.2%
o 64
 
8.0%
m 64
 
8.0%
a 56
 
7.0%
h 54
 
6.8%
p 53
 
6.6%
l 46
 
5.8%
c 43
 
5.4%
n 33
 
4.1%
Other values (15) 168
21.1%
Decimal Number
ValueCountFrequency (%)
0 66
57.4%
4 23
 
20.0%
2 6
 
5.2%
6 5
 
4.3%
5 4
 
3.5%
3 4
 
3.5%
1 3
 
2.6%
9 2
 
1.7%
8 1
 
0.9%
7 1
 
0.9%
Other Letter
ValueCountFrequency (%)
엔 1
11.1%
밸 1
11.1%
씨 1
11.1%
호 1
11.1%
서 1
11.1%
동 1
11.1%
번 1
11.1%
지 1
11.1%
리 1
11.1%
Other Punctuation
ValueCountFrequency (%)
/ 114
43.8%
. 99
38.1%
: 47
18.1%
Space Separator
ValueCountFrequency (%)
31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 797
65.8%
Common 406
33.5%
Hangul 9
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 111
13.9%
t 105
13.2%
o 64
 
8.0%
m 64
 
8.0%
a 56
 
7.0%
h 54
 
6.8%
p 53
 
6.6%
l 46
 
5.8%
c 43
 
5.4%
n 33
 
4.1%
Other values (15) 168
21.1%
Common
ValueCountFrequency (%)
/ 114
28.1%
. 99
24.4%
0 66
16.3%
: 47
11.6%
31
 
7.6%
4 23
 
5.7%
2 6
 
1.5%
6 5
 
1.2%
5 4
 
1.0%
3 4
 
1.0%
Other values (4) 7
 
1.7%
Hangul
ValueCountFrequency (%)
엔 1
11.1%
밸 1
11.1%
씨 1
11.1%
호 1
11.1%
서 1
11.1%
동 1
11.1%
번 1
11.1%
지 1
11.1%
리 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1203
99.3%
Hangul 9
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 114
 
9.5%
w 111
 
9.2%
t 105
 
8.7%
. 99
 
8.2%
0 66
 
5.5%
o 64
 
5.3%
m 64
 
5.3%
a 56
 
4.7%
h 54
 
4.5%
p 53
 
4.4%
Other values (29) 417
34.7%
Hangul
ValueCountFrequency (%)
엔 1
11.1%
밸 1
11.1%
씨 1
11.1%
호 1
11.1%
서 1
11.1%
동 1
11.1%
번 1
11.1%
지 1
11.1%
리 1
11.1%

지도 주소
Text

MISSING 

Distinct510
Distinct (%)95.7%
Missing10
Missing (%)1.8%
Memory size4.4 KiB
2023-12-11T08:41:41.329268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length15.440901
Min length3

Characters and Unicode

Total characters8230
Distinct characters117
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique495 ?
Unique (%)92.9%

Sample

1st row노룡동 1번지
2nd row사천시 곤명면 용산리 86
3rd row사천시 동림동 190
4th row사천시 늑도동 477
5th row향촌동 710
ValueCountFrequency (%)
사천시 304
 
15.5%
사천읍 122
 
6.2%
동금동 50
 
2.5%
수석리 48
 
2.4%
서금동 45
 
2.3%
벌리동 42
 
2.1%
1호 41
 
2.1%
용현면 37
 
1.9%
곤명면 34
 
1.7%
4호 33
 
1.7%
Other values (480) 1206
61.5%
2023-12-11T08:41:41.844764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1719
20.9%
사 470
 
5.7%
천 440
 
5.3%
지 403
 
4.9%
번 395
 
4.8%
1 377
 
4.6%
동 366
 
4.4%
호 327
 
4.0%
시 304
 
3.7%
리 303
 
3.7%
Other values (107) 3126
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4407
53.5%
Decimal Number 2004
24.3%
Space Separator 1719
 
20.9%
Dash Punctuation 98
 
1.2%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 470
10.7%
천 440
 
10.0%
지 403
 
9.1%
번 395
 
9.0%
동 366
 
8.3%
호 327
 
7.4%
시 304
 
6.9%
리 303
 
6.9%
면 142
 
3.2%
읍 124
 
2.8%
Other values (93) 1133
25.7%
Decimal Number
ValueCountFrequency (%)
1 377
18.8%
4 290
14.5%
2 263
13.1%
3 223
11.1%
8 171
8.5%
6 155
7.7%
5 147
 
7.3%
7 145
 
7.2%
9 137
 
6.8%
0 96
 
4.8%
Space Separator
ValueCountFrequency (%)
1719
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4407
53.5%
Common 3823
46.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 470
10.7%
천 440
 
10.0%
지 403
 
9.1%
번 395
 
9.0%
동 366
 
8.3%
호 327
 
7.4%
시 304
 
6.9%
리 303
 
6.9%
면 142
 
3.2%
읍 124
 
2.8%
Other values (93) 1133
25.7%
Common
ValueCountFrequency (%)
1719
45.0%
1 377
 
9.9%
4 290
 
7.6%
2 263
 
6.9%
3 223
 
5.8%
8 171
 
4.5%
6 155
 
4.1%
5 147
 
3.8%
7 145
 
3.8%
9 137
 
3.6%
Other values (4) 196
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4407
53.5%
ASCII 3823
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1719
45.0%
1 377
 
9.9%
4 290
 
7.6%
2 263
 
6.9%
3 223
 
5.8%
8 171
 
4.5%
6 155
 
4.1%
5 147
 
3.8%
7 145
 
3.8%
9 137
 
3.6%
Other values (4) 196
 
5.1%
Hangul
ValueCountFrequency (%)
사 470
10.7%
천 440
 
10.0%
지 403
 
9.1%
번 395
 
9.0%
동 366
 
8.3%
호 327
 
7.4%
시 304
 
6.9%
리 303
 
6.9%
면 142
 
3.2%
읍 124
 
2.8%
Other values (93) 1133
25.7%

값1
Text

MISSING 

Distinct435
Distinct (%)93.3%
Missing77
Missing (%)14.2%
Memory size4.4 KiB
2023-12-11T08:41:42.245903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.72103
Min length3

Characters and Unicode

Total characters3598
Distinct characters155
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique410 ?
Unique (%)88.0%

Sample

1st row진삼로 406
2nd row다솔사길 417
3rd row수도골안길 24
4th row삼천포대교로 112
5th row남일대길 55
ValueCountFrequency (%)
진삼로 37
 
4.0%
목섬길 26
 
2.8%
사천대로 14
 
1.5%
선진공원길 12
 
1.3%
남일로 11
 
1.2%
동금2길 10
 
1.1%
69 10
 
1.1%
해안관광로 9
 
1.0%
사주길 9
 
1.0%
어시장길 9
 
1.0%
Other values (435) 783
84.2%
2023-12-11T08:41:42.909574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
464
 
12.9%
길 299
 
8.3%
1 294
 
8.2%
로 169
 
4.7%
2 166
 
4.6%
3 148
 
4.1%
4 145
 
4.0%
7 118
 
3.3%
5 118
 
3.3%
- 108
 
3.0%
Other values (145) 1569
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1645
45.7%
Decimal Number 1373
38.2%
Space Separator 464
 
12.9%
Dash Punctuation 108
 
3.0%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 299
 
18.2%
로 169
 
10.3%
진 55
 
3.3%
사 53
 
3.2%
삼 51
 
3.1%
동 47
 
2.9%
선 36
 
2.2%
대 36
 
2.2%
천 33
 
2.0%
공 30
 
1.8%
Other values (131) 836
50.8%
Decimal Number
ValueCountFrequency (%)
1 294
21.4%
2 166
12.1%
3 148
10.8%
4 145
10.6%
7 118
8.6%
5 118
8.6%
9 103
 
7.5%
8 101
 
7.4%
6 95
 
6.9%
0 85
 
6.2%
Space Separator
ValueCountFrequency (%)
464
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1953
54.3%
Hangul 1645
45.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 299
 
18.2%
로 169
 
10.3%
진 55
 
3.3%
사 53
 
3.2%
삼 51
 
3.1%
동 47
 
2.9%
선 36
 
2.2%
대 36
 
2.2%
천 33
 
2.0%
공 30
 
1.8%
Other values (131) 836
50.8%
Common
ValueCountFrequency (%)
464
23.8%
1 294
15.1%
2 166
 
8.5%
3 148
 
7.6%
4 145
 
7.4%
7 118
 
6.0%
5 118
 
6.0%
- 108
 
5.5%
9 103
 
5.3%
8 101
 
5.2%
Other values (4) 188
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1953
54.3%
Hangul 1645
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
464
23.8%
1 294
15.1%
2 166
 
8.5%
3 148
 
7.6%
4 145
 
7.4%
7 118
 
6.0%
5 118
 
6.0%
- 108
 
5.5%
9 103
 
5.3%
8 101
 
5.2%
Other values (4) 188
9.6%
Hangul
ValueCountFrequency (%)
길 299
 
18.2%
로 169
 
10.3%
진 55
 
3.3%
사 53
 
3.2%
삼 51
 
3.1%
동 47
 
2.9%
선 36
 
2.2%
대 36
 
2.2%
천 33
 
2.0%
공 30
 
1.8%
Other values (131) 836
50.8%

위도
Real number (ℝ)

MISSING 

Distinct520
Distinct (%)98.9%
Missing17
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean35.004548
Minimum34.903455
Maximum35.716281
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-11T08:41:43.088870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.903455
5-th percentile34.924686
Q134.932123
median34.986562
Q335.080483
95-th percentile35.107365
Maximum35.716281
Range0.81282555
Interquartile range (IQR)0.14835983

Descriptive statistics

Standard deviation0.078900663
Coefficient of variation (CV)0.0022540118
Kurtosis10.807826
Mean35.004548
Median Absolute Deviation (MAD)0.05959905
Skewness1.579417
Sum18412.392
Variance0.0062253147
MonotonicityNot monotonic
2023-12-11T08:41:43.251616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.9321312 2
 
0.4%
35.1311659 2
 
0.4%
34.92575544 2
 
0.4%
35.0828152 2
 
0.4%
35.0937117 2
 
0.4%
35.08291666 2
 
0.4%
35.0788524 1
 
0.2%
34.9259107 1
 
0.2%
35.0756486 1
 
0.2%
35.0769005 1
 
0.2%
Other values (510) 510
93.9%
(Missing) 17
 
3.1%
ValueCountFrequency (%)
34.90345531 1
0.2%
34.92043612 1
0.2%
34.9216096 1
0.2%
34.9235074 1
0.2%
34.92361806 1
0.2%
34.9238013 1
0.2%
34.92398487 1
0.2%
34.9240215 1
0.2%
34.9241097 1
0.2%
34.9241143 1
0.2%
ValueCountFrequency (%)
35.71628086 1
0.2%
35.2033947 1
0.2%
35.1567286 1
0.2%
35.1456269 1
0.2%
35.1415786 1
0.2%
35.141459 1
0.2%
35.1412945 1
0.2%
35.1411386 1
0.2%
35.1411131 1
0.2%
35.14089502 1
0.2%

경도
Real number (ℝ)

MISSING 

Distinct521
Distinct (%)99.0%
Missing17
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean128.0622
Minimum126.98104
Maximum128.90066
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-11T08:41:43.413752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.98104
5-th percentile127.95981
Q1128.05362
median128.07633
Q3128.0857
95-th percentile128.09924
Maximum128.90066
Range1.9196177
Interquartile range (IQR)0.032082175

Descriptive statistics

Standard deviation0.073495858
Coefficient of variation (CV)0.00057390752
Kurtosis120.47538
Mean128.0622
Median Absolute Deviation (MAD)0.010609
Skewness-3.5836285
Sum67360.716
Variance0.0054016412
MonotonicityNot monotonic
2023-12-11T08:41:43.556449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.919915 2
 
0.4%
128.0743632 2
 
0.4%
128.0755978 2
 
0.4%
128.0565336 2
 
0.4%
127.9198928 2
 
0.4%
128.0856262 1
 
0.2%
128.0751099 1
 
0.2%
128.0836853 1
 
0.2%
128.0845443 1
 
0.2%
128.0796127 1
 
0.2%
Other values (511) 511
94.1%
(Missing) 17
 
3.1%
ValueCountFrequency (%)
126.9810447 1
0.2%
127.9107193 1
0.2%
127.9198928 2
0.4%
127.919915 2
0.4%
127.9233052 1
0.2%
127.9252683 1
0.2%
127.9265295 1
0.2%
127.926769 1
0.2%
127.9273487 1
0.2%
127.9339527 1
0.2%
ValueCountFrequency (%)
128.9006624 1
0.2%
128.1620994 1
0.2%
128.133157 1
0.2%
128.1310635 1
0.2%
128.1281526 1
0.2%
128.1272603 1
0.2%
128.1242936 1
0.2%
128.1232971 1
0.2%
128.1200263 1
0.2%
128.1191791 1
0.2%

계절
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
<NA>
522 
spring
 
6
summer
 
6
autumm
 
5
winter
 
4

Length

Max length6
Median length4
Mean length4.0773481
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowspring
2nd row<NA>
3rd rowspring
4th row<NA>
5th rowsummer

Common Values

ValueCountFrequency (%)
<NA> 522
96.1%
spring 6
 
1.1%
summer 6
 
1.1%
autumm 5
 
0.9%
winter 4
 
0.7%

Length

2023-12-11T08:41:43.706584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:41:43.835176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 522
96.1%
spring 6
 
1.1%
summer 6
 
1.1%
autumm 5
 
0.9%
winter 4
 
0.7%

Interactions

2023-12-11T08:41:35.581453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:34.888313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:35.256365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:35.677497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:35.020608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:35.372885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:35.788352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:35.135715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:35.483021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:41:43.925157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조회수등록일위치시간홈페이지위도경도계절
조회수1.0000.7790.9680.5731.0000.2740.0590.182
등록일0.7791.0000.9720.8781.0000.5070.2360.531
위치0.9680.9721.000NaN1.0000.9741.0001.000
시간0.5730.878NaN1.000NaN0.0000.753NaN
홈페이지1.0001.0001.000NaN1.0000.0000.000NaN
위도0.2740.5070.9740.0000.0001.0000.9240.274
경도0.0590.2361.0000.7530.0000.9241.0000.213
계절0.1820.5311.000NaNNaN0.2740.2131.000
2023-12-11T08:41:44.038368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조회수위도경도계절
조회수1.000-0.057-0.1400.100
위도-0.0571.0000.1100.240
경도-0.1400.1101.0000.103
계절0.1000.2400.1031.000

Missing values

2023-12-11T08:41:35.913306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:41:36.061203image/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.
2023-12-11T08:41:36.211301image/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

제목조회수등록일주소위치시간홈페이지지도 주소값1위도경도계절
0Mt. Waryongsan15892013-04-30노룡동 1번지사천시 사남면, 용현면, 벌용동, 남양동<NA><NA>노룡동 1번지진삼로 40634.985498128.113926spring
1Mt. Bongmyeongsan9642013-04-30곤명면 용산리 86일원사천공항에서 22km<NA><NA>사천시 곤명면 용산리 86다솔사길 41735.082917127.919893<NA>
2Mt. Gaksan11722013-04-30사천시 동림동 190일원사천공항에서 18Km<NA><NA>사천시 동림동 190수도골안길 2434.943346128.058944spring
3Hallyeosudo10582013-04-30늑도동 477 일원(초양휴게소)삼천포항 일원<NA><NA>사천시 늑도동 477삼천포대교로 11234.925257128.045093<NA>
4Namildae Beach14932013-04-30향촌동 710 일원삼천포항에서 동쪽으로 3.5㎞<NA><NA>향촌동 710남일대길 5534.926287128.096633summer
5Elephant Rock14752013-04-30향촌동 710 일원내삼천포항에서 동쪽으로 3.5Km<NA><NA>향촌동 710남일대길 53-2434.925688128.097345summer
6Daebangjin military port16072013-04-30대방동 250삼천포 시외버스터미널에서 3Km<NA><NA>대방동 250굴항길34.929053128.056777spring
7bamboo weirs12162013-04-30삼천포항 일대삼천포항(실안해안)<NA><NA>동금동 579-7팔포3길 56-5134.925684128.079627winter
8Samcheonpo Port13742013-04-30서동 삼천포항 일대사천IC에서 22km<NA><NA>서동 311-89어시장길 34-434.926532128.069654<NA>
9ilannakjo coastal road (Sunset)18512013-04-30실안동 1254일원실안해안도로 일원<NA><NA>실안동 1254노을길34.938405128.043115autumm
제목조회수등록일주소위치시간홈페이지지도 주소값1위도경도계절
533주공칼국수572013-06-17동금동 62번지 14호<NA><NA><NA>사천시 동금동 62번지 14호동금5길 3334.934123128.082374<NA>
534털보해물전골442013-06-17동동 173번지 27호<NA>12:00 ~ 20:00<NA>사천시 동동 173번지 27호수남3길 3134.928124128.070879<NA>
535풍년식당372013-06-17동금동 88번지 4호 경남상가 라동동 13<NA><NA><NA>사천시 동금동 88번지 4호동금2길 1534.932122128.078632<NA>
536할매식당642013-06-17동금동 40번지 2호<NA><NA><NA>사천시 동금동 40번지 2호남일로 9434.931771128.086544<NA>
537행운선지국밥452013-06-17동금동 88번지 4호 경남상가 다동 7호<NA><NA><NA>사천시 동금동 88번지 4호동금2길 1534.932131128.078635<NA>
538향촌복집502013-06-17동금동 40번지 1호<NA><NA><NA>사천시 동금동 40번지 1호남일로 94-134.931678128.08672<NA>
539Hongcheonttukbaegi5102013-06-17동금동 336번지 5호<NA><NA><NA>동금동 336번지 5호동금로 3034.930635128.078279<NA>
540황소막창1062013-06-17동금동 65번지 5호<NA>17:00 ~ 05:00<NA>사천시 동금동 65번지 5호삼상로 42-134.934937128.08085<NA>
541모닝썬펜션342013-07-10송포동 1478번지<NA><NA>http://www.rmorningsun.com/송포동 1478번지해안관광로 303-1534.960211128.03649<NA>
542씨&밸리펜션162013-07-10선구동 314-1<NA><NA>http://www.씨엔밸리.kr/삼천포대교로 385-32삼천포대교로 385-3234.937725128.069484<NA>