Overview

Dataset statistics

Number of variables17
Number of observations657
Missing cells3646
Missing cells (%)32.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory89.3 KiB
Average record size in memory139.2 B

Variable types

Text11
Categorical2
Numeric3
DateTime1

Dataset

Description경상남도 사천시 문화관광홈페이지 전시내용 테이블 자료(제목,이름,조회수,등록일, 주소 등)에 대한 자료 입니다.
Author경상남도 사천시
URLhttps://www.data.go.kr/data/15084117/fileData.do

Alerts

이름 has a high cardinality: 51 distinct valuesHigh cardinality
이름 is highly imbalanced (66.9%)Imbalance
계절 is highly imbalanced (88.0%)Imbalance
위치 has 507 (77.2%) missing valuesMissing
시간 has 498 (75.8%) missing valuesMissing
전화번호 has 34 (5.2%) missing valuesMissing
홈페이지 has 571 (86.9%) missing valuesMissing
지도 주소 has 12 (1.8%) missing valuesMissing
동영상 링크 has 639 (97.3%) missing valuesMissing
vr 링크 has 638 (97.1%) missing valuesMissing
값1 has 54 (8.2%) missing valuesMissing
값2 has 652 (99.2%) missing valuesMissing
위도 has 19 (2.9%) missing valuesMissing
경도 has 19 (2.9%) missing valuesMissing

Reproduction

Analysis started2024-04-20 23:16:05.903903
Analysis finished2024-04-20 23:16:12.852602
Duration6.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제목
Text

Distinct647
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-04-21T08:16:13.463419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length5.8432268
Min length1

Characters and Unicode

Total characters3839
Distinct characters460
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

Unique637 ?
Unique (%)97.0%

Sample

1st row삼천포항 해안탐방로
2nd row곤명요 도자기 체험
3rd row홍천뚝배기
4th row감말랭이
5th row삼정횟집
ValueCountFrequency (%)
사천 25
 
3.0%
12
 
1.4%
예능 8
 
0.9%
삼천포 8
 
0.9%
촬영장소 8
 
0.9%
1박2일 8
 
0.9%
다솔사 6
 
0.7%
백천사 4
 
0.5%
모텔 3
 
0.4%
백운암 3
 
0.4%
Other values (722) 762
90.0%
2024-04-21T08:16:14.675645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
190
 
4.9%
천 98
 
2.6%
텔 94
 
2.4%
모 94
 
2.4%
장 89
 
2.3%
사 83
 
2.2%
집 76
 
2.0%
횟 59
 
1.5%
리 56
 
1.5%
대 55
 
1.4%
Other values (450) 2945
76.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3535
92.1%
Space Separator 190
 
4.9%
Decimal Number 37
 
1.0%
Uppercase Letter 29
 
0.8%
Close Punctuation 12
 
0.3%
Open Punctuation 12
 
0.3%
Dash Punctuation 11
 
0.3%
Other Punctuation 7
 
0.2%
Lowercase Letter 5
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 98
 
2.8%
텔 94
 
2.7%
모 94
 
2.7%
장 89
 
2.5%
사 83
 
2.3%
집 76
 
2.1%
횟 59
 
1.7%
리 56
 
1.6%
대 55
 
1.6%
식 54
 
1.5%
Other values (414) 2777
78.6%
Uppercase Letter
ValueCountFrequency (%)
S 4
 
13.8%
F 2
 
6.9%
V 2
 
6.9%
L 2
 
6.9%
Q 2
 
6.9%
O 2
 
6.9%
W 2
 
6.9%
B 1
 
3.4%
X 1
 
3.4%
N 1
 
3.4%
Other values (10) 10
34.5%
Decimal Number
ValueCountFrequency (%)
1 10
27.0%
2 10
27.0%
0 5
13.5%
4 4
 
10.8%
3 3
 
8.1%
7 3
 
8.1%
8 2
 
5.4%
Other Punctuation
ValueCountFrequency (%)
& 4
57.1%
. 2
28.6%
: 1
 
14.3%
Space Separator
ValueCountFrequency (%)
190
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3535
92.1%
Common 269
 
7.0%
Latin 35
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 98
 
2.8%
텔 94
 
2.7%
모 94
 
2.7%
장 89
 
2.5%
사 83
 
2.3%
집 76
 
2.1%
횟 59
 
1.7%
리 56
 
1.6%
대 55
 
1.6%
식 54
 
1.5%
Other values (414) 2777
78.6%
Latin
ValueCountFrequency (%)
m 5
14.3%
S 4
 
11.4%
F 2
 
5.7%
V 2
 
5.7%
L 2
 
5.7%
Q 2
 
5.7%
O 2
 
5.7%
W 2
 
5.7%
B 1
 
2.9%
Ⅱ 1
 
2.9%
Other values (12) 12
34.3%
Common
ValueCountFrequency (%)
190
70.6%
) 12
 
4.5%
( 12
 
4.5%
- 11
 
4.1%
1 10
 
3.7%
2 10
 
3.7%
0 5
 
1.9%
4 4
 
1.5%
& 4
 
1.5%
3 3
 
1.1%
Other values (4) 8
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3535
92.1%
ASCII 303
 
7.9%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
190
62.7%
) 12
 
4.0%
( 12
 
4.0%
- 11
 
3.6%
1 10
 
3.3%
2 10
 
3.3%
0 5
 
1.7%
m 5
 
1.7%
S 4
 
1.3%
4 4
 
1.3%
Other values (25) 40
 
13.2%
Hangul
ValueCountFrequency (%)
천 98
 
2.8%
텔 94
 
2.7%
모 94
 
2.7%
장 89
 
2.5%
사 83
 
2.3%
집 76
 
2.1%
횟 59
 
1.7%
리 56
 
1.6%
대 55
 
1.6%
식 54
 
1.5%
Other values (414) 2777
78.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

이름
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct51
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
500 
연중무휴
 
31
무휴
 
25
매주 일요일
 
11
둘째주 수요일
 
9
Other values (46)
81 

Length

Max length14
Median length4
Mean length4.5327245
Min length2

Unique

Unique33 ?
Unique (%)5.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row둘째주 수요일

Common Values

ValueCountFrequency (%)
<NA> 500
76.1%
연중무휴 31
 
4.7%
무휴 25
 
3.8%
매주 일요일 11
 
1.7%
둘째주 수요일 9
 
1.4%
1,3째 일요일 7
 
1.1%
둘째주 화요일 6
 
0.9%
2,4째 일요일 5
 
0.8%
매주 일요일 휴무 4
 
0.6%
연중무휴 (명절제외) 4
 
0.6%
Other values (41) 55
 
8.4%

Length

2024-04-21T08:16:15.108562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 500
64.7%
일요일 41
 
5.3%
연중무휴 40
 
5.2%
무휴 27
 
3.5%
매주 16
 
2.1%
둘째주 16
 
2.1%
1,3째 13
 
1.7%
화요일 13
 
1.7%
2,4째 13
 
1.7%
월요일 13
 
1.7%
Other values (42) 81
 
10.5%

조회수
Real number (ℝ)

Distinct395
Distinct (%)60.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean535.93151
Minimum16
Maximum5732
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-04-21T08:16:15.490710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile82
Q1113
median201
Q3585
95-th percentile2197
Maximum5732
Range5716
Interquartile range (IQR)472

Descriptive statistics

Standard deviation811.20254
Coefficient of variation (CV)1.513631
Kurtosis11.171185
Mean535.93151
Median Absolute Deviation (MAD)110
Skewness3.120881
Sum352107
Variance658049.55
MonotonicityNot monotonic
2024-04-21T08:16:15.914380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
108 11
 
1.7%
86 8
 
1.2%
92 8
 
1.2%
102 7
 
1.1%
94 7
 
1.1%
80 7
 
1.1%
123 6
 
0.9%
82 6
 
0.9%
113 6
 
0.9%
91 6
 
0.9%
Other values (385) 585
89.0%
ValueCountFrequency (%)
16 1
 
0.2%
69 2
 
0.3%
70 3
0.5%
71 1
 
0.2%
72 1
 
0.2%
73 1
 
0.2%
74 1
 
0.2%
76 3
0.5%
77 1
 
0.2%
78 5
0.8%
ValueCountFrequency (%)
5732 1
0.2%
5147 1
0.2%
5073 1
0.2%
4543 1
0.2%
4507 1
0.2%
4299 1
0.2%
4274 1
0.2%
4168 1
0.2%
4060 1
0.2%
3954 1
0.2%

등록일
Date

Distinct65
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum2013-04-30 00:00:00
Maximum2017-11-26 00:00:00
2024-04-21T08:16:16.302120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:16.715883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주소
Text

Distinct621
Distinct (%)95.0%
Missing3
Missing (%)0.5%
Memory size5.3 KiB
2024-04-21T08:16:17.832603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length23
Mean length13.807339
Min length6

Characters and Unicode

Total characters9030
Distinct characters161
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

Unique597 ?
Unique (%)91.3%

Sample

1st row향촌동 678-1 일원
2nd row곤명면 성방리 192-2
3rd row동금동 54-4
4th row이금동 88번지
5th row서금동 144번지 6호
ValueCountFrequency (%)
사천읍 131
 
6.2%
사천시 75
 
3.5%
벌리동 50
 
2.4%
동금동 49
 
2.3%
수석리 48
 
2.3%
서금동 44
 
2.1%
용현면 42
 
2.0%
곤명면 41
 
1.9%
1호 37
 
1.7%
서포면 37
 
1.7%
Other values (678) 1563
73.8%
2024-04-21T08:16:19.408732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1813
20.1%
1 491
 
5.4%
동 421
 
4.7%
지 379
 
4.2%
번 367
 
4.1%
리 350
 
3.9%
4 329
 
3.6%
2 315
 
3.5%
호 298
 
3.3%
3 264
 
2.9%
Other values (151) 4003
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4568
50.6%
Decimal Number 2418
26.8%
Space Separator 1813
 
20.1%
Dash Punctuation 173
 
1.9%
Close Punctuation 20
 
0.2%
Open Punctuation 20
 
0.2%
Other Punctuation 16
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 421
 
9.2%
지 379
 
8.3%
번 367
 
8.0%
리 350
 
7.7%
호 298
 
6.5%
사 262
 
5.7%
천 233
 
5.1%
면 198
 
4.3%
읍 134
 
2.9%
금 106
 
2.3%
Other values (134) 1820
39.8%
Decimal Number
ValueCountFrequency (%)
1 491
20.3%
4 329
13.6%
2 315
13.0%
3 264
10.9%
8 189
 
7.8%
6 185
 
7.7%
5 180
 
7.4%
7 176
 
7.3%
9 153
 
6.3%
0 136
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 15
93.8%
/ 1
 
6.2%
Space Separator
ValueCountFrequency (%)
1813
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 173
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4568
50.6%
Common 4462
49.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 421
 
9.2%
지 379
 
8.3%
번 367
 
8.0%
리 350
 
7.7%
호 298
 
6.5%
사 262
 
5.7%
천 233
 
5.1%
면 198
 
4.3%
읍 134
 
2.9%
금 106
 
2.3%
Other values (134) 1820
39.8%
Common
ValueCountFrequency (%)
1813
40.6%
1 491
 
11.0%
4 329
 
7.4%
2 315
 
7.1%
3 264
 
5.9%
8 189
 
4.2%
6 185
 
4.1%
5 180
 
4.0%
7 176
 
3.9%
- 173
 
3.9%
Other values (7) 347
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4568
50.6%
ASCII 4462
49.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1813
40.6%
1 491
 
11.0%
4 329
 
7.4%
2 315
 
7.1%
3 264
 
5.9%
8 189
 
4.2%
6 185
 
4.1%
5 180
 
4.0%
7 176
 
3.9%
- 173
 
3.9%
Other values (7) 347
 
7.8%
Hangul
ValueCountFrequency (%)
동 421
 
9.2%
지 379
 
8.3%
번 367
 
8.0%
리 350
 
7.7%
호 298
 
6.5%
사 262
 
5.7%
천 233
 
5.1%
면 198
 
4.3%
읍 134
 
2.9%
금 106
 
2.3%
Other values (134) 1820
39.8%

위치
Text

MISSING 

Distinct129
Distinct (%)86.0%
Missing507
Missing (%)77.2%
Memory size5.3 KiB
2024-04-21T08:16:20.344576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length13.833333
Min length4

Characters and Unicode

Total characters2075
Distinct characters157
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)74.7%

Sample

1st row남일대해수욕장 해안주변가
2nd row곤양IC에서 6.5km
3rd row사천IC에서 3km
4th row사천IC에서 3.5km
5th row사천IC에서 20km
ValueCountFrequency (%)
사천ic에서 48
 
12.0%
곤양ic에서 20
 
5.0%
삼천포항 18
 
4.5%
사천시 15
 
3.7%
방향으로 13
 
3.2%
일원 10
 
2.5%
22km 8
 
2.0%
사남면 7
 
1.7%
1km 6
 
1.5%
15km 6
 
1.5%
Other values (164) 250
62.3%
2024-04-21T08:16:21.905387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
331
 
16.0%
천 118
 
5.7%
서 104
 
5.0%
에 97
 
4.7%
사 93
 
4.5%
m 88
 
4.2%
I 75
 
3.6%
C 75
 
3.6%
k 71
 
3.4%
2 42
 
2.0%
Other values (147) 981
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1170
56.4%
Space Separator 331
 
16.0%
Decimal Number 188
 
9.1%
Uppercase Letter 166
 
8.0%
Lowercase Letter 159
 
7.7%
Other Punctuation 39
 
1.9%
Close Punctuation 7
 
0.3%
Open Punctuation 7
 
0.3%
Other Symbol 4
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 118
 
10.1%
서 104
 
8.9%
에 97
 
8.3%
사 93
 
7.9%
포 39
 
3.3%
양 35
 
3.0%
항 33
 
2.8%
삼 33
 
2.8%
곤 33
 
2.8%
동 33
 
2.8%
Other values (123) 552
47.2%
Decimal Number
ValueCountFrequency (%)
2 42
22.3%
1 41
21.8%
5 27
14.4%
0 17
9.0%
6 17
9.0%
3 16
 
8.5%
4 14
 
7.4%
7 6
 
3.2%
9 5
 
2.7%
8 3
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
I 75
45.2%
C 75
45.2%
K 16
 
9.6%
Other Punctuation
ValueCountFrequency (%)
, 20
51.3%
. 18
46.2%
· 1
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
m 88
55.3%
k 71
44.7%
Space Separator
ValueCountFrequency (%)
331
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Symbol
ValueCountFrequency (%)
㎞ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1170
56.4%
Common 580
28.0%
Latin 325
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 118
 
10.1%
서 104
 
8.9%
에 97
 
8.3%
사 93
 
7.9%
포 39
 
3.3%
양 35
 
3.0%
항 33
 
2.8%
삼 33
 
2.8%
곤 33
 
2.8%
동 33
 
2.8%
Other values (123) 552
47.2%
Common
ValueCountFrequency (%)
331
57.1%
2 42
 
7.2%
1 41
 
7.1%
5 27
 
4.7%
, 20
 
3.4%
. 18
 
3.1%
0 17
 
2.9%
6 17
 
2.9%
3 16
 
2.8%
4 14
 
2.4%
Other values (9) 37
 
6.4%
Latin
ValueCountFrequency (%)
m 88
27.1%
I 75
23.1%
C 75
23.1%
k 71
21.8%
K 16
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1170
56.4%
ASCII 900
43.4%
CJK Compat 4
 
0.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
331
36.8%
m 88
 
9.8%
I 75
 
8.3%
C 75
 
8.3%
k 71
 
7.9%
2 42
 
4.7%
1 41
 
4.6%
5 27
 
3.0%
, 20
 
2.2%
. 18
 
2.0%
Other values (12) 112
 
12.4%
Hangul
ValueCountFrequency (%)
천 118
 
10.1%
서 104
 
8.9%
에 97
 
8.3%
사 93
 
7.9%
포 39
 
3.3%
양 35
 
3.0%
항 33
 
2.8%
삼 33
 
2.8%
곤 33
 
2.8%
동 33
 
2.8%
Other values (123) 552
47.2%
CJK Compat
ValueCountFrequency (%)
㎞ 4
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

시간
Text

MISSING 

Distinct59
Distinct (%)37.1%
Missing498
Missing (%)75.8%
Memory size5.3 KiB
2024-04-21T08:16:22.550431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length13
Mean length13.050314
Min length3

Characters and Unicode

Total characters2075
Distinct characters43
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

Unique40 ?
Unique (%)25.2%

Sample

1st row10:00 ~ 22:00
2nd row10:30 ~ 22:00
3rd row11:00 ~ 22:00
4th row12:00 ~ 21:00
5th row10:00 ~ 22:00
ValueCountFrequency (%)
149
32.1%
22:00 84
18.1%
10:00 59
 
12.7%
11:00 33
 
7.1%
21:00 27
 
5.8%
09:00 18
 
3.9%
12:00 7
 
1.5%
20:00 7
 
1.5%
20:30 7
 
1.5%
09:30 6
 
1.3%
Other values (40) 67
14.4%
2024-04-21T08:16:23.608032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 688
33.2%
314
15.1%
: 296
14.3%
2 243
 
11.7%
1 203
 
9.8%
~ 152
 
7.3%
3 39
 
1.9%
9 30
 
1.4%
8 14
 
0.7%
시 12
 
0.6%
Other values (33) 84
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1253
60.4%
Space Separator 314
 
15.1%
Other Punctuation 300
 
14.5%
Math Symbol 152
 
7.3%
Other Letter 44
 
2.1%
Dash Punctuation 8
 
0.4%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 12
27.3%
차 3
 
6.8%
방 2
 
4.5%
주 2
 
4.5%
지 2
 
4.5%
까 2
 
4.5%
가 2
 
4.5%
능 2
 
4.5%
동 1
 
2.3%
오 1
 
2.3%
Other values (15) 15
34.1%
Decimal Number
ValueCountFrequency (%)
0 688
54.9%
2 243
 
19.4%
1 203
 
16.2%
3 39
 
3.1%
9 30
 
2.4%
8 14
 
1.1%
7 11
 
0.9%
6 10
 
0.8%
4 9
 
0.7%
5 6
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 296
98.7%
/ 2
 
0.7%
, 2
 
0.7%
Space Separator
ValueCountFrequency (%)
314
100.0%
Math Symbol
ValueCountFrequency (%)
~ 152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2031
97.9%
Hangul 44
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 12
27.3%
차 3
 
6.8%
방 2
 
4.5%
주 2
 
4.5%
지 2
 
4.5%
까 2
 
4.5%
가 2
 
4.5%
능 2
 
4.5%
동 1
 
2.3%
오 1
 
2.3%
Other values (15) 15
34.1%
Common
ValueCountFrequency (%)
0 688
33.9%
314
15.5%
: 296
14.6%
2 243
 
12.0%
1 203
 
10.0%
~ 152
 
7.5%
3 39
 
1.9%
9 30
 
1.5%
8 14
 
0.7%
7 11
 
0.5%
Other values (8) 41
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2031
97.9%
Hangul 44
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 688
33.9%
314
15.5%
: 296
14.6%
2 243
 
12.0%
1 203
 
10.0%
~ 152
 
7.5%
3 39
 
1.9%
9 30
 
1.5%
8 14
 
0.7%
7 11
 
0.5%
Other values (8) 41
 
2.0%
Hangul
ValueCountFrequency (%)
시 12
27.3%
차 3
 
6.8%
방 2
 
4.5%
주 2
 
4.5%
지 2
 
4.5%
까 2
 
4.5%
가 2
 
4.5%
능 2
 
4.5%
동 1
 
2.3%
오 1
 
2.3%
Other values (15) 15
34.1%

전화번호
Text

MISSING 

Distinct527
Distinct (%)84.6%
Missing34
Missing (%)5.2%
Memory size5.3 KiB
2024-04-21T08:16:24.639529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length12
Mean length12.423756
Min length8

Characters and Unicode

Total characters7740
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique501 ?
Unique (%)80.4%

Sample

1st row055-831-3125
2nd row055-852-8378
3rd row055 -833 -8332
4th row070-7747-6400
5th row055-835-3378
ValueCountFrequency (%)
055-831-2716 42
 
6.0%
055 42
 
6.0%
055-835-1023 13
 
1.9%
055-832-9610 9
 
1.3%
055-831-2420 9
 
1.3%
055-831-3415 9
 
1.3%
055-833-8826 7
 
1.0%
853 6
 
0.9%
055-831-2730 4
 
0.6%
055-831-3425~6 4
 
0.6%
Other values (521) 552
79.2%
2024-04-21T08:16:26.090768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1861
24.0%
- 1247
16.1%
0 939
12.1%
8 859
11.1%
3 758
9.8%
2 507
 
6.6%
1 412
 
5.3%
4 304
 
3.9%
7 243
 
3.1%
6 236
 
3.0%
Other values (6) 374
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6293
81.3%
Dash Punctuation 1247
 
16.1%
Space Separator 178
 
2.3%
Close Punctuation 8
 
0.1%
Other Punctuation 8
 
0.1%
Math Symbol 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1861
29.6%
0 939
14.9%
8 859
13.7%
3 758
12.0%
2 507
 
8.1%
1 412
 
6.5%
4 304
 
4.8%
7 243
 
3.9%
6 236
 
3.8%
9 174
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
/ 2
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 1247
100.0%
Space Separator
ValueCountFrequency (%)
178
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7740
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1861
24.0%
- 1247
16.1%
0 939
12.1%
8 859
11.1%
3 758
9.8%
2 507
 
6.6%
1 412
 
5.3%
4 304
 
3.9%
7 243
 
3.1%
6 236
 
3.0%
Other values (6) 374
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1861
24.0%
- 1247
16.1%
0 939
12.1%
8 859
11.1%
3 758
9.8%
2 507
 
6.6%
1 412
 
5.3%
4 304
 
3.9%
7 243
 
3.1%
6 236
 
3.0%
Other values (6) 374
 
4.8%

홈페이지
Text

MISSING 

Distinct68
Distinct (%)79.1%
Missing571
Missing (%)86.9%
Memory size5.3 KiB
2024-04-21T08:16:27.041054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length33
Mean length25.081395
Min length12

Characters and Unicode

Total characters2157
Distinct characters71
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

Unique66 ?
Unique (%)76.7%

Sample

1st rowhttp://blog.naver.com/ddak56
2nd rowhttp://www.4000mall.com
3rd rowhttp://goeup.invil.org
4th rowhttp://www.4000cc.co.kr
5th rowhttp://www.3004hotel.com
ValueCountFrequency (%)
http://www.4000mall.com 19
 
21.6%
http://blog.naver.com/sara1646 2
 
2.3%
http://bitoresort.co.kr 2
 
2.3%
http://www.namiltte.com 2
 
2.3%
http://ilmarepension.co.kr 2
 
2.3%
www.dajayeon.com 1
 
1.1%
http://freshsw.co.kr 1
 
1.1%
http://www.khsea.kr 1
 
1.1%
http://cafe.naver.com/gaya900 1
 
1.1%
http://www.noeulps.com 1
 
1.1%
Other values (56) 56
63.6%
2024-04-21T08:16:28.430517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 213
 
9.9%
t 194
 
9.0%
. 178
 
8.3%
w 172
 
8.0%
o 131
 
6.1%
h 100
 
4.6%
p 100
 
4.6%
a 97
 
4.5%
m 95
 
4.4%
c 93
 
4.3%
Other values (61) 784
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1464
67.9%
Other Punctuation 475
 
22.0%
Decimal Number 148
 
6.9%
Other Letter 36
 
1.7%
Space Separator 32
 
1.5%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 3
 
8.3%
펜 2
 
5.6%
호 2
 
5.6%
션 2
 
5.6%
든 1
 
2.8%
저 1
 
2.8%
언 1
 
2.8%
수 1
 
2.8%
월 1
 
2.8%
라 1
 
2.8%
Other values (21) 21
58.3%
Lowercase Letter
ValueCountFrequency (%)
t 194
13.3%
w 172
11.7%
o 131
 
8.9%
h 100
 
6.8%
p 100
 
6.8%
a 97
 
6.6%
m 95
 
6.5%
c 93
 
6.4%
r 70
 
4.8%
e 68
 
4.6%
Other values (15) 344
23.5%
Decimal Number
ValueCountFrequency (%)
0 78
52.7%
4 27
 
18.2%
1 9
 
6.1%
6 9
 
6.1%
2 8
 
5.4%
3 7
 
4.7%
9 4
 
2.7%
5 4
 
2.7%
7 1
 
0.7%
8 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
/ 213
44.8%
. 178
37.5%
: 84
 
17.7%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1464
67.9%
Common 657
30.5%
Hangul 36
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 3
 
8.3%
펜 2
 
5.6%
호 2
 
5.6%
션 2
 
5.6%
든 1
 
2.8%
저 1
 
2.8%
언 1
 
2.8%
수 1
 
2.8%
월 1
 
2.8%
라 1
 
2.8%
Other values (21) 21
58.3%
Latin
ValueCountFrequency (%)
t 194
13.3%
w 172
11.7%
o 131
 
8.9%
h 100
 
6.8%
p 100
 
6.8%
a 97
 
6.6%
m 95
 
6.5%
c 93
 
6.4%
r 70
 
4.8%
e 68
 
4.6%
Other values (15) 344
23.5%
Common
ValueCountFrequency (%)
/ 213
32.4%
. 178
27.1%
: 84
 
12.8%
0 78
 
11.9%
32
 
4.9%
4 27
 
4.1%
1 9
 
1.4%
6 9
 
1.4%
2 8
 
1.2%
3 7
 
1.1%
Other values (5) 12
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2121
98.3%
Hangul 36
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 213
 
10.0%
t 194
 
9.1%
. 178
 
8.4%
w 172
 
8.1%
o 131
 
6.2%
h 100
 
4.7%
p 100
 
4.7%
a 97
 
4.6%
m 95
 
4.5%
c 93
 
4.4%
Other values (30) 748
35.3%
Hangul
ValueCountFrequency (%)
리 3
 
8.3%
펜 2
 
5.6%
호 2
 
5.6%
션 2
 
5.6%
든 1
 
2.8%
저 1
 
2.8%
언 1
 
2.8%
수 1
 
2.8%
월 1
 
2.8%
라 1
 
2.8%
Other values (21) 21
58.3%

지도 주소
Text

MISSING 

Distinct600
Distinct (%)93.0%
Missing12
Missing (%)1.8%
Memory size5.3 KiB
2024-04-21T08:16:29.500635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length14.843411
Min length3

Characters and Unicode

Total characters9574
Distinct characters128
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique573 ?
Unique (%)88.8%

Sample

1st row사천시 향촌동 678-1
2nd row곤명면 성방리 192-2
3rd row동금동 새시장길 84-4
4th row이금동 88번지
5th row서금동 144번지 6호
ValueCountFrequency (%)
사천시 339
 
14.8%
사천읍 130
 
5.7%
벌리동 51
 
2.2%
동금동 51
 
2.2%
수석리 50
 
2.2%
서금동 44
 
1.9%
곤명면 42
 
1.8%
용현면 42
 
1.8%
1호 38
 
1.7%
서포면 36
 
1.6%
Other values (615) 1461
64.0%
2024-04-21T08:16:30.977850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1924
20.1%
사 525
 
5.5%
천 496
 
5.2%
1 458
 
4.8%
동 424
 
4.4%
지 364
 
3.8%
리 359
 
3.7%
번 357
 
3.7%
시 341
 
3.6%
4 331
 
3.5%
Other values (118) 3995
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5070
53.0%
Decimal Number 2372
24.8%
Space Separator 1924
 
20.1%
Dash Punctuation 189
 
2.0%
Close Punctuation 9
 
0.1%
Open Punctuation 9
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 525
 
10.4%
천 496
 
9.8%
동 424
 
8.4%
지 364
 
7.2%
리 359
 
7.1%
번 357
 
7.0%
시 341
 
6.7%
호 288
 
5.7%
면 189
 
3.7%
읍 133
 
2.6%
Other values (103) 1594
31.4%
Decimal Number
ValueCountFrequency (%)
1 458
19.3%
4 331
14.0%
2 327
13.8%
3 258
10.9%
8 200
8.4%
5 178
 
7.5%
7 173
 
7.3%
6 167
 
7.0%
9 147
 
6.2%
0 133
 
5.6%
Space Separator
ValueCountFrequency (%)
1924
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5070
53.0%
Common 4504
47.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 525
 
10.4%
천 496
 
9.8%
동 424
 
8.4%
지 364
 
7.2%
리 359
 
7.1%
번 357
 
7.0%
시 341
 
6.7%
호 288
 
5.7%
면 189
 
3.7%
읍 133
 
2.6%
Other values (103) 1594
31.4%
Common
ValueCountFrequency (%)
1924
42.7%
1 458
 
10.2%
4 331
 
7.3%
2 327
 
7.3%
3 258
 
5.7%
8 200
 
4.4%
- 189
 
4.2%
5 178
 
4.0%
7 173
 
3.8%
6 167
 
3.7%
Other values (5) 299
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5070
53.0%
ASCII 4504
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1924
42.7%
1 458
 
10.2%
4 331
 
7.3%
2 327
 
7.3%
3 258
 
5.7%
8 200
 
4.4%
- 189
 
4.2%
5 178
 
4.0%
7 173
 
3.8%
6 167
 
3.7%
Other values (5) 299
 
6.6%
Hangul
ValueCountFrequency (%)
사 525
 
10.4%
천 496
 
9.8%
동 424
 
8.4%
지 364
 
7.2%
리 359
 
7.1%
번 357
 
7.0%
시 341
 
6.7%
호 288
 
5.7%
면 189
 
3.7%
읍 133
 
2.6%
Other values (103) 1594
31.4%

동영상 링크
Text

MISSING 

Distinct17
Distinct (%)94.4%
Missing639
Missing (%)97.3%
Memory size5.3 KiB
2024-04-21T08:16:31.685007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length32.333333
Min length32

Characters and Unicode

Total characters582
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)88.9%

Sample

1st row/mtour/Common/Data/movie/757.mp4
2nd row/mtour/Common/Data/movie/755.mp4
3rd row/mtour/Common/Data/movie/890.mp4
4th row/mtour/Common/Data/movie/bak.mp4
5th row/mtour/Common/Data/movie/740.mp4
ValueCountFrequency (%)
mtour/common/data/movie/789.mp4 2
 
11.1%
mtour/common/data/movie/825.mp4 1
 
5.6%
mtour/common/data/movie/779.mp4 1
 
5.6%
mtour/common/data/movie/620.mp4 1
 
5.6%
mtour/common/data/movie/632.mp4 1
 
5.6%
mtour/common/data/movie/840.mp4 1
 
5.6%
mtour/common/data/movie/895.mp4 1
 
5.6%
mtour/common/data/movie/631.mp4 1
 
5.6%
mtour/common/data/movie/897.mp4 1
 
5.6%
mtour/common/data/movie/755.mp4 1
 
5.6%
Other values (7) 7
38.9%
2024-04-21T08:16:32.812939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 90
15.5%
m 90
15.5%
o 72
12.4%
a 38
 
6.5%
t 37
 
6.4%
4 20
 
3.4%
v 19
 
3.3%
i 19
 
3.3%
e 19
 
3.3%
u 18
 
3.1%
Other values (20) 160
27.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 371
63.7%
Other Punctuation 108
 
18.6%
Decimal Number 67
 
11.5%
Uppercase Letter 36
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 90
24.3%
o 72
19.4%
a 38
10.2%
t 37
10.0%
v 19
 
5.1%
i 19
 
5.1%
e 19
 
5.1%
u 18
 
4.9%
r 18
 
4.9%
n 18
 
4.9%
Other values (6) 23
 
6.2%
Decimal Number
ValueCountFrequency (%)
4 20
29.9%
7 10
14.9%
8 9
13.4%
9 8
 
11.9%
5 5
 
7.5%
0 5
 
7.5%
3 3
 
4.5%
2 3
 
4.5%
6 3
 
4.5%
1 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 90
83.3%
. 18
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
C 18
50.0%
D 18
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 407
69.9%
Common 175
30.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 90
22.1%
o 72
17.7%
a 38
9.3%
t 37
9.1%
v 19
 
4.7%
i 19
 
4.7%
e 19
 
4.7%
u 18
 
4.4%
r 18
 
4.4%
C 18
 
4.4%
Other values (8) 59
14.5%
Common
ValueCountFrequency (%)
/ 90
51.4%
4 20
 
11.4%
. 18
 
10.3%
7 10
 
5.7%
8 9
 
5.1%
9 8
 
4.6%
5 5
 
2.9%
0 5
 
2.9%
3 3
 
1.7%
2 3
 
1.7%
Other values (2) 4
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 90
15.5%
m 90
15.5%
o 72
12.4%
a 38
 
6.5%
t 37
 
6.4%
4 20
 
3.4%
v 19
 
3.3%
i 19
 
3.3%
e 19
 
3.3%
u 18
 
3.1%
Other values (20) 160
27.5%

vr 링크
Text

MISSING 

Distinct17
Distinct (%)89.5%
Missing638
Missing (%)97.1%
Memory size5.3 KiB
2024-04-21T08:16:33.564411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters684
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)84.2%

Sample

1st row/mtour/Common/Data/panorama/757.html
2nd row/mtour/Common/Data/panorama/761.html
3rd row/mtour/Common/Data/panorama/761.html
4th row/mtour/Common/Data/panorama/bak.html
5th row/mtour/Common/Data/panorama/637.html
ValueCountFrequency (%)
mtour/common/data/panorama/761.html 3
15.8%
mtour/common/data/panorama/758.html 1
 
5.3%
mtour/common/data/panorama/625.html 1
 
5.3%
mtour/common/data/panorama/911.html 1
 
5.3%
mtour/common/data/panorama/628.html 1
 
5.3%
mtour/common/data/panorama/776.html 1
 
5.3%
mtour/common/data/panorama/825.html 1
 
5.3%
mtour/common/data/panorama/779.html 1
 
5.3%
mtour/common/data/panorama/859.html 1
 
5.3%
mtour/common/data/panorama/bak.html 1
 
5.3%
Other values (7) 7
36.8%
2024-04-21T08:16:34.381319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 96
14.0%
m 95
13.9%
/ 95
13.9%
o 76
11.1%
t 57
8.3%
r 38
 
5.6%
n 38
 
5.6%
u 19
 
2.8%
C 19
 
2.8%
D 19
 
2.8%
Other values (16) 132
19.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 478
69.9%
Other Punctuation 114
 
16.7%
Decimal Number 54
 
7.9%
Uppercase Letter 38
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 96
20.1%
m 95
19.9%
o 76
15.9%
t 57
11.9%
r 38
 
7.9%
n 38
 
7.9%
u 19
 
4.0%
p 19
 
4.0%
h 19
 
4.0%
l 19
 
4.0%
Other values (2) 2
 
0.4%
Decimal Number
ValueCountFrequency (%)
7 11
20.4%
6 10
18.5%
8 7
13.0%
9 7
13.0%
1 6
11.1%
5 5
9.3%
2 4
 
7.4%
3 2
 
3.7%
4 1
 
1.9%
0 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/ 95
83.3%
. 19
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
C 19
50.0%
D 19
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 516
75.4%
Common 168
 
24.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 96
18.6%
m 95
18.4%
o 76
14.7%
t 57
11.0%
r 38
 
7.4%
n 38
 
7.4%
u 19
 
3.7%
C 19
 
3.7%
D 19
 
3.7%
p 19
 
3.7%
Other values (4) 40
7.8%
Common
ValueCountFrequency (%)
/ 95
56.5%
. 19
 
11.3%
7 11
 
6.5%
6 10
 
6.0%
8 7
 
4.2%
9 7
 
4.2%
1 6
 
3.6%
5 5
 
3.0%
2 4
 
2.4%
3 2
 
1.2%
Other values (2) 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 96
14.0%
m 95
13.9%
/ 95
13.9%
o 76
11.1%
t 57
8.3%
r 38
 
5.6%
n 38
 
5.6%
u 19
 
2.8%
C 19
 
2.8%
D 19
 
2.8%
Other values (16) 132
19.3%

값1
Text

MISSING 

Distinct554
Distinct (%)91.9%
Missing54
Missing (%)8.2%
Memory size5.3 KiB
2024-04-21T08:16:35.724086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length9.119403
Min length3

Characters and Unicode

Total characters5499
Distinct characters182
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique518 ?
Unique (%)85.9%

Sample

1st row신항1길 34-14
2nd row사천시 숲뫼길 115 (향촌동)
3rd row모정길 25-1
4th row목섬길 69
5th row벌리2길 69
ValueCountFrequency (%)
사천시 74
 
5.3%
진삼로 41
 
2.9%
사천읍 25
 
1.8%
목섬길 25
 
1.8%
해안관광로 18
 
1.3%
사천대로 17
 
1.2%
어시장길 15
 
1.1%
남일로 14
 
1.0%
선진공원길 11
 
0.8%
사남면 10
 
0.7%
Other values (564) 1144
82.1%
2024-04-21T08:16:37.354697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
807
 
14.7%
1 388
 
7.1%
길 357
 
6.5%
로 221
 
4.0%
2 219
 
4.0%
3 194
 
3.5%
4 189
 
3.4%
사 182
 
3.3%
5 150
 
2.7%
7 148
 
2.7%
Other values (172) 2644
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2709
49.3%
Decimal Number 1766
32.1%
Space Separator 807
 
14.7%
Dash Punctuation 148
 
2.7%
Close Punctuation 33
 
0.6%
Open Punctuation 33
 
0.6%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 357
 
13.2%
로 221
 
8.2%
사 182
 
6.7%
천 144
 
5.3%
동 101
 
3.7%
시 100
 
3.7%
진 59
 
2.2%
남 58
 
2.1%
삼 57
 
2.1%
리 55
 
2.0%
Other values (157) 1375
50.8%
Decimal Number
ValueCountFrequency (%)
1 388
22.0%
2 219
12.4%
3 194
11.0%
4 189
10.7%
5 150
 
8.5%
7 148
 
8.4%
8 132
 
7.5%
9 125
 
7.1%
6 121
 
6.9%
0 100
 
5.7%
Space Separator
ValueCountFrequency (%)
807
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2790
50.7%
Hangul 2709
49.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 357
 
13.2%
로 221
 
8.2%
사 182
 
6.7%
천 144
 
5.3%
동 101
 
3.7%
시 100
 
3.7%
진 59
 
2.2%
남 58
 
2.1%
삼 57
 
2.1%
리 55
 
2.0%
Other values (157) 1375
50.8%
Common
ValueCountFrequency (%)
807
28.9%
1 388
13.9%
2 219
 
7.8%
3 194
 
7.0%
4 189
 
6.8%
5 150
 
5.4%
7 148
 
5.3%
- 148
 
5.3%
8 132
 
4.7%
9 125
 
4.5%
Other values (5) 290
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2790
50.7%
Hangul 2709
49.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
807
28.9%
1 388
13.9%
2 219
 
7.8%
3 194
 
7.0%
4 189
 
6.8%
5 150
 
5.4%
7 148
 
5.3%
- 148
 
5.3%
8 132
 
4.7%
9 125
 
4.5%
Other values (5) 290
 
10.4%
Hangul
ValueCountFrequency (%)
길 357
 
13.2%
로 221
 
8.2%
사 182
 
6.7%
천 144
 
5.3%
동 101
 
3.7%
시 100
 
3.7%
진 59
 
2.2%
남 58
 
2.1%
삼 57
 
2.1%
리 55
 
2.0%
Other values (157) 1375
50.8%

값2
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing652
Missing (%)99.2%
Memory size5.3 KiB
2024-04-21T08:16:37.842135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length28.4
Min length4

Characters and Unicode

Total characters142
Distinct characters37
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

Unique5 ?
Unique (%)100.0%

Sample

1st row일반휠체어(2개), 장애인전용 엘리베이터(1개), 장애인 전용 화장실(2개)
2nd row주차가능
3rd row8대 주차가능
4th row일반휠체어(1개), 유모차(4개), 장애인전용 엘리베이터(2개), 장애인전용 화장실(4개)
5th row장애인전용 엘리베이터(1개), 장애인전용 화장실(2개), 어린이 도서관
ValueCountFrequency (%)
장애인전용 5
23.8%
엘리베이터(1개 2
 
9.5%
화장실(2개 2
 
9.5%
주차가능 2
 
9.5%
일반휠체어(2개 1
 
4.8%
장애인 1
 
4.8%
전용 1
 
4.8%
8대 1
 
4.8%
일반휠체어(1개 1
 
4.8%
유모차(4개 1
 
4.8%
Other values (4) 4
19.0%
2024-04-21T08:16:38.521067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
11.3%
( 9
 
6.3%
개 9
 
6.3%
) 9
 
6.3%
장 9
 
6.3%
, 7
 
4.9%
애 6
 
4.2%
인 6
 
4.2%
전 6
 
4.2%
용 6
 
4.2%
Other values (27) 59
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
64.1%
Space Separator 16
 
11.3%
Decimal Number 10
 
7.0%
Open Punctuation 9
 
6.3%
Close Punctuation 9
 
6.3%
Other Punctuation 7
 
4.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 9
 
9.9%
장 9
 
9.9%
애 6
 
6.6%
인 6
 
6.6%
전 6
 
6.6%
용 6
 
6.6%
이 4
 
4.4%
리 3
 
3.3%
화 3
 
3.3%
터 3
 
3.3%
Other values (19) 36
39.6%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
1 3
30.0%
4 2
20.0%
8 1
 
10.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
64.1%
Common 51
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 9
 
9.9%
장 9
 
9.9%
애 6
 
6.6%
인 6
 
6.6%
전 6
 
6.6%
용 6
 
6.6%
이 4
 
4.4%
리 3
 
3.3%
화 3
 
3.3%
터 3
 
3.3%
Other values (19) 36
39.6%
Common
ValueCountFrequency (%)
16
31.4%
( 9
17.6%
) 9
17.6%
, 7
13.7%
2 4
 
7.8%
1 3
 
5.9%
4 2
 
3.9%
8 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
64.1%
ASCII 51
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
31.4%
( 9
17.6%
) 9
17.6%
, 7
13.7%
2 4
 
7.8%
1 3
 
5.9%
4 2
 
3.9%
8 1
 
2.0%
Hangul
ValueCountFrequency (%)
개 9
 
9.9%
장 9
 
9.9%
애 6
 
6.6%
인 6
 
6.6%
전 6
 
6.6%
용 6
 
6.6%
이 4
 
4.4%
리 3
 
3.3%
화 3
 
3.3%
터 3
 
3.3%
Other values (19) 36
39.6%

위도
Real number (ℝ)

MISSING 

Distinct615
Distinct (%)96.4%
Missing19
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean35.003596
Minimum34.66211
Maximum35.716281
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-04-21T08:16:38.761011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.66211
5-th percentile34.924568
Q134.932453
median34.98646
Q335.080385
95-th percentile35.107781
Maximum35.716281
Range1.0541709
Interquartile range (IQR)0.147932

Descriptive statistics

Standard deviation0.078256827
Coefficient of variation (CV)0.0022356797
Kurtosis9.6062274
Mean35.003596
Median Absolute Deviation (MAD)0.05875185
Skewness1.2880042
Sum22332.294
Variance0.006124131
MonotonicityNot monotonic
2024-04-21T08:16:39.014019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.0828152 5
 
0.8%
34.9961626 3
 
0.5%
35.0964872 3
 
0.5%
34.99515347 2
 
0.3%
35.08291666 2
 
0.3%
34.937936 2
 
0.3%
35.0808874 2
 
0.3%
34.9042565 2
 
0.3%
35.1311659 2
 
0.3%
35.0714409 2
 
0.3%
Other values (605) 613
93.3%
(Missing) 19
 
2.9%
ValueCountFrequency (%)
34.66211 1
0.2%
34.9007263 1
0.2%
34.90345531 1
0.2%
34.9040527 1
0.2%
34.90411 1
0.2%
34.9042565 2
0.3%
34.92043612 1
0.2%
34.920943 1
0.2%
34.9216096 1
0.2%
34.9226366 1
0.2%
ValueCountFrequency (%)
35.71628086 1
0.2%
35.2062918 1
0.2%
35.2033947 1
0.2%
35.1567286 1
0.2%
35.1468126 1
0.2%
35.1456269 1
0.2%
35.1451368 1
0.2%
35.1415786 1
0.2%
35.141459 1
0.2%
35.1412945 1
0.2%

경도
Real number (ℝ)

MISSING 

Distinct616
Distinct (%)96.6%
Missing19
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean128.05504
Minimum126.70022
Maximum128.90066
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-04-21T08:16:39.267004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.70022
5-th percentile127.94952
Q1128.04549
median128.07558
Q3128.08567
95-th percentile128.10548
Maximum128.90066
Range2.2004454
Interquartile range (IQR)0.040180275

Descriptive statistics

Standard deviation0.099844763
Coefficient of variation (CV)0.00077970192
Kurtosis107.44053
Mean128.05504
Median Absolute Deviation (MAD)0.0134512
Skewness-7.4153499
Sum81699.118
Variance0.0099689768
MonotonicityNot monotonic
2024-04-21T08:16:39.511642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.919915 5
 
0.8%
128.1063003 3
 
0.5%
128.0916992 3
 
0.5%
128.0841148 2
 
0.3%
128.0654368 2
 
0.3%
127.9198928 2
 
0.3%
128.0308091 2
 
0.3%
128.0755978 2
 
0.3%
128.0736828 2
 
0.3%
128.0521274 2
 
0.3%
Other values (606) 613
93.3%
(Missing) 19
 
2.9%
ValueCountFrequency (%)
126.700217 1
 
0.2%
126.9125123 1
 
0.2%
126.9810447 1
 
0.2%
127.8985364 1
 
0.2%
127.9064275 1
 
0.2%
127.9107193 1
 
0.2%
127.9192247 1
 
0.2%
127.9198928 2
 
0.3%
127.919915 5
0.8%
127.9252683 1
 
0.2%
ValueCountFrequency (%)
128.9006624 1
0.2%
128.1660193 1
0.2%
128.1620994 1
0.2%
128.133157 1
0.2%
128.1330029 1
0.2%
128.1310635 1
0.2%
128.1257303 1
0.2%
128.1246648 1
0.2%
128.1232971 1
0.2%
128.1223316 1
0.2%

계절
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
635 
spring
 
7
summer
 
6
autumm
 
5
winter
 
4

Length

Max length6
Median length4
Mean length4.0669711
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 635
96.7%
spring 7
 
1.1%
summer 6
 
0.9%
autumm 5
 
0.8%
winter 4
 
0.6%

Length

2024-04-21T08:16:39.752683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:16:39.956645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 635
96.7%
spring 7
 
1.1%
summer 6
 
0.9%
autumm 5
 
0.8%
winter 4
 
0.6%

Interactions

2024-04-21T08:16:10.490953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:08.986731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:09.751626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:10.746263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:09.249048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:10.004314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:10.989091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:09.499601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:16:10.248714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T08:16:40.100064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이름조회수등록일시간홈페이지동영상 링크vr 링크값2위도경도계절
이름1.0000.6260.9400.9021.000NaNNaN0.0000.7300.690NaN
조회수0.6261.0000.7380.4911.0001.0000.9521.0000.0000.0000.000
등록일0.9400.7381.0000.9661.0000.9020.0001.0000.2910.2560.249
시간0.9020.4910.9661.0001.000NaNNaN0.0000.8590.895NaN
홈페이지1.0001.0001.0001.0001.0001.0000.0001.0000.0000.0001.000
동영상 링크NaN1.0000.902NaN1.0001.0001.0000.0001.0001.0001.000
vr 링크NaN0.9520.000NaN0.0001.0001.000NaN1.0001.0001.000
값20.0001.0001.0000.0001.0000.000NaN1.0001.0001.000NaN
위도0.7300.0000.2910.8590.0001.0001.0001.0001.0000.8540.247
경도0.6900.0000.2560.8950.0001.0001.0001.0000.8541.0000.423
계절NaN0.0000.249NaN1.0001.0001.000NaN0.2470.4231.000
2024-04-21T08:16:40.318382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계절이름
계절1.000NaN
이름NaN1.000
2024-04-21T08:16:40.469256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조회수위도경도이름계절
조회수1.000-0.122-0.2230.4180.000
위도-0.1221.0000.0440.4090.214
경도-0.2230.0441.0000.4640.258
이름0.4180.4090.4641.0000.000
계절0.0000.2140.2580.0001.000

Missing values

2024-04-21T08:16:11.367464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T08:16:12.019052image/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.
2024-04-21T08:16:12.514483image/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

제목이름조회수등록일주소위치시간전화번호홈페이지지도 주소동영상 링크vr 링크값1값2위도경도계절
0삼천포항 해안탐방로<NA>45432013-05-08향촌동 678-1 일원남일대해수욕장 해안주변가<NA>055-831-3125<NA>사천시 향촌동 678-1<NA><NA>신항1길 34-14<NA>34.923618128.09332<NA>
1곤명요 도자기 체험<NA>4702013-05-08곤명면 성방리 192-2곤양IC에서 6.5km<NA>055-852-8378http://blog.naver.com/ddak56곤명면 성방리 192-2<NA><NA><NA><NA>35.100193127.969792<NA>
2홍천뚝배기<NA>5072013-06-17동금동 54-4<NA><NA>055 -833 -8332<NA>동금동 새시장길 84-4<NA><NA>사천시 숲뫼길 115 (향촌동)<NA>34.931106128.081993<NA>
3감말랭이<NA>2972013-05-02이금동 88번지<NA><NA>070-7747-6400http://www.4000mall.com이금동 88번지<NA><NA>모정길 25-1<NA>34.947202128.115753<NA>
4삼정횟집둘째주 수요일2452013-05-06서금동 144번지 6호<NA>10:00 ~ 22:00055-835-3378<NA>서금동 144번지 6호<NA><NA>목섬길 69<NA>34.924154128.075204<NA>
5고읍녹색농촌체험마을<NA>3812013-05-08정동면 고읍리 263-1사천IC에서 3km<NA>055-852-7634http://goeup.invil.org정동면 고읍리 263-1<NA><NA><NA><NA>35.067465128.097881<NA>
6정가네아쿠찜2,4째 월요일1482013-06-07사천시 벌리동 245번지 7호<NA>10:30 ~ 22:00055-832-1305<NA>사천시 벌리동 245번지 7호<NA><NA>벌리2길 69<NA>34.939742128.084325<NA>
7산해횟집초밥<NA>1492013-06-17동금동 64번지 12호<NA><NA>055-832-8500<NA>사천시 동금동 64번지 12호<NA><NA>동금1길 74<NA>34.934921128.08169<NA>
8조선비식육숯불갈비2째 화요일3872013-06-07벌리동 247번지 5호<NA>11:00 ~ 22:00055- 832-9929<NA>사천시 벌리동 247번지 5호<NA><NA>사천시 벌리7길 7 (벌리동)<NA>34.938793128.084826<NA>
9양자강2,4째 화요일1272013-06-05사천읍 수석리 497번지 6호<NA><NA>055-852-5565<NA>사천읍 수석리 497번지 6호<NA><NA>동성길 31<NA>35.086846128.08557<NA>
제목이름조회수등록일주소위치시간전화번호홈페이지지도 주소동영상 링크vr 링크값1값2위도경도계절
647이덕밥상<NA>712017-11-15경상남도 사천시 선구2길 12 (선구동)<NA><NA>055 -833 -0888<NA>경상남도 사천시 선구2길 12 (선구동)<NA><NA>사천시 선구2길 12 (선구동)<NA>34.930711128.072867<NA>
648풍년복집<NA>922017-11-15경상남도 사천시 수남길 82 (동동)<NA><NA>055- 832-8909<NA>경상남도 사천시 수남길 82 (동동)<NA><NA>사천시 수남길 82 (동동)<NA>34.928566128.070465<NA>
649지명전골<NA>1082017-11-15경상남도 사천시 사천읍 사천읍성로 20<NA><NA>055-854-5775<NA>경상남도 사천시 사천읍 사천읍성로 20<NA><NA>사천시 사천읍 사천읍성로 20<NA>35.085064128.086711<NA>
650하연옥<NA>1012017-11-15경상남도 사천시 사남면 하동길 8-11<NA><NA>055-853-9005<NA>경상남도 사천시 사남면 하동길 8-11<NA><NA>사천시 사남면 하동길 8-11<NA>35.067683128.076146<NA>
651파피쉪<NA>1132017-11-15경상남도 사천시 사천읍 구암두문로 163<NA><NA>055-854-1188<NA>경상남도 사천시 사천읍 구암두문로 163<NA><NA>사천시 사천읍 구암두문로 163<NA>35.091618128.121249<NA>
652가고파명가<NA>1002017-11-15경상남도 사천시 사천읍 항공로 18<NA><NA>055 -834 -0100<NA>경상남도 사천시 사천읍 항공로 18<NA><NA>사천시 사천읍 항공로 18<NA>35.080961128.080913<NA>
653큰손식당<NA>1132017-11-15경상남도 사천시 문선7길 23-7 (벌리동)<NA><NA>055-835 -5959<NA>경상남도 사천시 문선7길 23-7 (벌리동)<NA><NA>사천시 문선7길 23-7 (벌리동)<NA>34.936689128.082643<NA>
654아나정고기한점<NA>1032017-11-15경상남도 사천시 벌리5길 29 (벌리동)<NA><NA>055- 833-1454<NA>경상남도 사천시 벌리5길 29 (벌리동)<NA><NA>사천시 벌리5길 29 (벌리동)<NA>34.939481128.084197<NA>
655다이닝센삼천포점<NA>1132017-11-15경상남도 사천시 주공로 41, 3층 (벌리동)<NA><NA>055-835-5200<NA>경상남도 사천시 주공로 41, 3층 (벌리동)<NA><NA>사천시 주공로 41, 3층 (벌리동)<NA>34.940648128.087935<NA>
656비토국민여가캠핑장<NA>902017-11-26사천시 서포면 비토리 산40번지 일원<NA><NA>070-8988-4000http://www.bitocamping.co사천시 서포면 비토리 산40번지<NA><NA>사천시 서포면 비토리 산40번지<NA>34.965511127.982754<NA>