Overview

Dataset statistics

Number of variables12
Number of observations100
Missing cells93
Missing cells (%)7.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory99.3 B

Variable types

Categorical5
Text4
Numeric2
DateTime1

Alerts

eng_lang_area_nm has constant value ""Constant
kor_lang_area_nm has constant value ""Constant
jan_lang_area_nm has constant value ""Constant
chg_lang_area_nm has constant value ""Constant
BASE_YMD has constant value ""Constant
lo is highly overall correlated with laHigh correlation
la is highly overall correlated with loHigh correlation
eng_lang_hotel_nm has 4 (4.0%) missing valuesMissing
kor_lang_hotel_nm has 10 (10.0%) missing valuesMissing
tel_no has 79 (79.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 10:05:11.253949
Analysis finished2023-12-10 10:05:14.446659
Duration3.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

se_nm
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
호텔
73 
게스트하우스
19 
기타
8 

Length

Max length6
Median length2
Mean length2.76
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row호텔
2nd row게스트하우스
3rd row호텔
4th row기타
5th row게스트하우스

Common Values

ValueCountFrequency (%)
호텔 73
73.0%
게스트하우스 19
 
19.0%
기타 8
 
8.0%

Length

2023-12-10T19:05:14.613908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:14.833315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
호텔 73
73.0%
게스트하우스 19
 
19.0%
기타 8
 
8.0%

eng_lang_hotel_nm
Text

MISSING 

Distinct95
Distinct (%)99.0%
Missing4
Missing (%)4.0%
Memory size932.0 B
2023-12-10T19:05:15.481042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length34
Mean length22.166667
Min length10

Characters and Unicode

Total characters2128
Distinct characters62
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)97.9%

Sample

1st rowCATS Porto hostel : Tattva Design hostel
2nd rowYes! Porto Hostel
3rd rowMercure Porto Centro Hotel
4th rowBluesock Hostels Porto
5th rowTravellers House
ValueCountFrequency (%)
hotel 37
 
10.8%
hostel 28
 
8.1%
porto 27
 
7.8%
lisbon 13
 
3.8%
12
 
3.5%
apartments 7
 
2.0%
house 7
 
2.0%
the 7
 
2.0%
suites 6
 
1.7%
lisboa 6
 
1.7%
Other values (153) 194
56.4%
2023-12-10T19:05:16.403421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 249
11.7%
248
11.7%
e 192
 
9.0%
t 190
 
8.9%
s 129
 
6.1%
a 116
 
5.5%
l 111
 
5.2%
r 97
 
4.6%
n 90
 
4.2%
i 89
 
4.2%
Other values (52) 617
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1526
71.7%
Uppercase Letter 325
 
15.3%
Space Separator 248
 
11.7%
Other Punctuation 13
 
0.6%
Decimal Number 10
 
0.5%
Dash Punctuation 6
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 249
16.3%
e 192
12.6%
t 190
12.5%
s 129
8.5%
a 116
7.6%
l 111
7.3%
r 97
 
6.4%
n 90
 
5.9%
i 89
 
5.8%
u 51
 
3.3%
Other values (16) 212
13.9%
Uppercase Letter
ValueCountFrequency (%)
H 59
18.2%
P 36
11.1%
L 29
8.9%
S 28
8.6%
T 22
 
6.8%
A 21
 
6.5%
C 19
 
5.8%
B 16
 
4.9%
D 13
 
4.0%
R 13
 
4.0%
Other values (12) 69
21.2%
Other Punctuation
ValueCountFrequency (%)
& 5
38.5%
. 2
 
15.4%
, 2
 
15.4%
: 2
 
15.4%
! 1
 
7.7%
' 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
8 3
30.0%
0 1
 
10.0%
2 1
 
10.0%
9 1
 
10.0%
6 1
 
10.0%
Space Separator
ValueCountFrequency (%)
248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1851
87.0%
Common 277
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 249
13.5%
e 192
 
10.4%
t 190
 
10.3%
s 129
 
7.0%
a 116
 
6.3%
l 111
 
6.0%
r 97
 
5.2%
n 90
 
4.9%
i 89
 
4.8%
H 59
 
3.2%
Other values (38) 529
28.6%
Common
ValueCountFrequency (%)
248
89.5%
- 6
 
2.2%
& 5
 
1.8%
1 3
 
1.1%
8 3
 
1.1%
. 2
 
0.7%
, 2
 
0.7%
: 2
 
0.7%
! 1
 
0.4%
0 1
 
0.4%
Other values (4) 4
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2128
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 249
11.7%
248
11.7%
e 192
 
9.0%
t 190
 
8.9%
s 129
 
6.1%
a 116
 
5.5%
l 111
 
5.2%
r 97
 
4.6%
n 90
 
4.2%
i 89
 
4.2%
Other values (52) 617
29.0%

kor_lang_hotel_nm
Text

MISSING 

Distinct89
Distinct (%)98.9%
Missing10
Missing (%)10.0%
Memory size932.0 B
2023-12-10T19:05:16.888441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length19
Mean length12.5
Min length5

Characters and Unicode

Total characters1125
Distinct characters169
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

Unique88 ?
Unique (%)97.8%

Sample

1st row타트바 디자인 호스텔
2nd row예스! 포르토 호스텔
3rd row머큐어 포르토 센트로 호텔
4th row블루삭 호스텔 포르투
5th row트레블러스 하우스 호스텔
ValueCountFrequency (%)
호텔 35
 
11.1%
호스텔 28
 
8.9%
포르토 14
 
4.4%
리스본 12
 
3.8%
포르투 11
 
3.5%
더 8
 
2.5%
8
 
2.5%
스위트 6
 
1.9%
아파트먼트 4
 
1.3%
리스보아 4
 
1.3%
Other values (149) 186
58.9%
2023-12-10T19:05:17.604863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
226
20.1%
스 95
 
8.4%
텔 65
 
5.8%
호 64
 
5.7%
트 40
 
3.6%
리 36
 
3.2%
포 31
 
2.8%
르 31
 
2.8%
아 27
 
2.4%
이 23
 
2.0%
Other values (159) 487
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 868
77.2%
Space Separator 226
 
20.1%
Uppercase Letter 10
 
0.9%
Decimal Number 8
 
0.7%
Dash Punctuation 7
 
0.6%
Other Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 95
 
10.9%
텔 65
 
7.5%
호 64
 
7.4%
트 40
 
4.6%
리 36
 
4.1%
포 31
 
3.6%
르 31
 
3.6%
아 27
 
3.1%
이 23
 
2.6%
토 19
 
2.2%
Other values (141) 437
50.3%
Uppercase Letter
ValueCountFrequency (%)
H 2
20.0%
B 2
20.0%
F 2
20.0%
L 1
10.0%
X 1
10.0%
S 1
10.0%
A 1
10.0%
Decimal Number
ValueCountFrequency (%)
8 3
37.5%
1 2
25.0%
0 1
 
12.5%
9 1
 
12.5%
2 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
33.3%
& 2
33.3%
/ 1
16.7%
! 1
16.7%
Space Separator
ValueCountFrequency (%)
226
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 868
77.2%
Common 247
 
22.0%
Latin 10
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 95
 
10.9%
텔 65
 
7.5%
호 64
 
7.4%
트 40
 
4.6%
리 36
 
4.1%
포 31
 
3.6%
르 31
 
3.6%
아 27
 
3.1%
이 23
 
2.6%
토 19
 
2.2%
Other values (141) 437
50.3%
Common
ValueCountFrequency (%)
226
91.5%
- 7
 
2.8%
8 3
 
1.2%
. 2
 
0.8%
1 2
 
0.8%
& 2
 
0.8%
0 1
 
0.4%
/ 1
 
0.4%
! 1
 
0.4%
9 1
 
0.4%
Latin
ValueCountFrequency (%)
H 2
20.0%
B 2
20.0%
F 2
20.0%
L 1
10.0%
X 1
10.0%
S 1
10.0%
A 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 868
77.2%
ASCII 257
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
226
87.9%
- 7
 
2.7%
8 3
 
1.2%
. 2
 
0.8%
1 2
 
0.8%
H 2
 
0.8%
B 2
 
0.8%
F 2
 
0.8%
& 2
 
0.8%
0 1
 
0.4%
Other values (8) 8
 
3.1%
Hangul
ValueCountFrequency (%)
스 95
 
10.9%
텔 65
 
7.5%
호 64
 
7.4%
트 40
 
4.6%
리 36
 
4.1%
포 31
 
3.6%
르 31
 
3.6%
아 27
 
3.1%
이 23
 
2.6%
토 19
 
2.2%
Other values (141) 437
50.3%

eng_lang_area_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Portugal
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Portugal 100
100.0%

Length

2023-12-10T19:05:18.011878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:18.266521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
portugal 100
100.0%

kor_lang_area_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
포르투갈
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
포르투갈 100
100.0%

Length

2023-12-10T19:05:18.441832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:18.610862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
포르투갈 100
100.0%

jan_lang_area_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
ポルトガル
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowポルトガル
2nd rowポルトガル
3rd rowポルトガル
4th rowポルトガル
5th rowポルトガル

Common Values

ValueCountFrequency (%)
ポルトガル 100
100.0%

Length

2023-12-10T19:05:18.813091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:19.091630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ポルトガル 100
100.0%

chg_lang_area_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
葡萄牙
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row葡萄牙
2nd row葡萄牙
3rd row葡萄牙
4th row葡萄牙
5th row葡萄牙

Common Values

ValueCountFrequency (%)
葡萄牙 100
100.0%

Length

2023-12-10T19:05:19.314652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:05:19.504837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
葡萄牙 100
100.0%

rn_adres
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:05:20.273804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length51.5
Mean length44.03
Min length31

Characters and Unicode

Total characters4403
Distinct characters80
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

Unique98 ?
Unique (%)98.0%

Sample

1st rowRua do Cativo 26, 4000-098 Porto, 포르투갈
2nd rowRua Arquitecto Nicolau Nazoni 31, 4000 포르토 포르투갈
3rd rowRua da Madeira 31, 4000 Porto, 포르투갈
4th rowR. de São João 40, 4050-492 Porto, 포르투갈
5th rowR. Augusta 89, 1100-053 Lisboa, 포르투갈
ValueCountFrequency (%)
포르투갈 99
 
12.9%
lisboa 41
 
5.3%
r 40
 
5.2%
de 36
 
4.7%
porto 33
 
4.3%
rua 28
 
3.6%
do 20
 
2.6%
da 17
 
2.2%
4000 8
 
1.0%
são 8
 
1.0%
Other values (311) 439
57.1%
2023-12-10T19:05:21.236553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
669
 
15.2%
a 269
 
6.1%
0 266
 
6.0%
o 264
 
6.0%
, 189
 
4.3%
i 156
 
3.5%
1 153
 
3.5%
r 140
 
3.2%
e 136
 
3.1%
d 118
 
2.7%
Other values (70) 2043
46.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1704
38.7%
Decimal Number 868
19.7%
Space Separator 669
 
15.2%
Other Letter 435
 
9.9%
Uppercase Letter 391
 
8.9%
Other Punctuation 245
 
5.6%
Dash Punctuation 89
 
2.0%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 269
15.8%
o 264
15.5%
i 156
9.2%
r 140
8.2%
e 136
8.0%
d 118
 
6.9%
s 98
 
5.8%
t 86
 
5.0%
u 69
 
4.0%
b 58
 
3.4%
Other values (22) 310
18.2%
Uppercase Letter
ValueCountFrequency (%)
R 80
20.5%
L 54
13.8%
P 51
13.0%
A 36
9.2%
S 28
 
7.2%
C 24
 
6.1%
M 18
 
4.6%
D 14
 
3.6%
N 13
 
3.3%
G 12
 
3.1%
Other values (10) 61
15.6%
Other Letter
ValueCountFrequency (%)
르 105
24.1%
포 105
24.1%
갈 99
22.8%
투 99
22.8%
토 6
 
1.4%
본 5
 
1.1%
스 5
 
1.1%
리 5
 
1.1%
º 3
 
0.7%
신 1
 
0.2%
Other values (2) 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 266
30.6%
1 153
17.6%
4 108
12.4%
2 83
 
9.6%
5 60
 
6.9%
9 56
 
6.5%
6 42
 
4.8%
3 42
 
4.8%
8 31
 
3.6%
7 27
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 189
77.1%
. 56
 
22.9%
Space Separator
ValueCountFrequency (%)
669
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2098
47.6%
Common 1873
42.5%
Hangul 432
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 269
 
12.8%
o 264
 
12.6%
i 156
 
7.4%
r 140
 
6.7%
e 136
 
6.5%
d 118
 
5.6%
s 98
 
4.7%
t 86
 
4.1%
R 80
 
3.8%
u 69
 
3.3%
Other values (43) 682
32.5%
Common
ValueCountFrequency (%)
669
35.7%
0 266
 
14.2%
, 189
 
10.1%
1 153
 
8.2%
4 108
 
5.8%
- 89
 
4.8%
2 83
 
4.4%
5 60
 
3.2%
. 56
 
3.0%
9 56
 
3.0%
Other values (6) 144
 
7.7%
Hangul
ValueCountFrequency (%)
르 105
24.3%
포 105
24.3%
갈 99
22.9%
투 99
22.9%
토 6
 
1.4%
본 5
 
1.2%
스 5
 
1.2%
리 5
 
1.2%
신 1
 
0.2%
트 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3907
88.7%
Hangul 432
 
9.8%
None 64
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
669
17.1%
a 269
 
6.9%
0 266
 
6.8%
o 264
 
6.8%
, 189
 
4.8%
i 156
 
4.0%
1 153
 
3.9%
r 140
 
3.6%
e 136
 
3.5%
d 118
 
3.0%
Other values (49) 1547
39.6%
Hangul
ValueCountFrequency (%)
르 105
24.3%
포 105
24.3%
갈 99
22.9%
투 99
22.9%
토 6
 
1.4%
본 5
 
1.2%
스 5
 
1.2%
리 5
 
1.2%
신 1
 
0.2%
트 1
 
0.2%
None
ValueCountFrequency (%)
ã 22
34.4%
ç 10
15.6%
é 8
 
12.5%
á 6
 
9.4%
ó 6
 
9.4%
º 3
 
4.7%
â 3
 
4.7%
í 3
 
4.7%
õ 2
 
3.1%
ú 1
 
1.6%

lo
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.8667408
Minimum-9.3830047
Maximum-8.4314792
Zeros0
Zeros (%)0.0%
Negative100
Negative (%)100.0%
Memory size1.0 KiB
2023-12-10T19:05:21.630024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9.3830047
5-th percentile-9.1482877
Q1-9.1392942
median-8.6745507
Q3-8.6114889
95-th percentile-8.6039502
Maximum-8.4314792
Range0.9515255
Interquartile range (IQR)0.52780528

Descriptive statistics

Standard deviation0.27309684
Coefficient of variation (CV)-0.030800137
Kurtosis-1.8644638
Mean-8.8667408
Median Absolute Deviation (MAD)0.24190845
Skewness-0.041588677
Sum-886.67408
Variance0.074581882
MonotonicityNot monotonic
2023-12-10T19:05:21.887955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-8.6402293 2
 
2.0%
-9.1250729 2
 
2.0%
-8.6089902 1
 
1.0%
-9.1369984 1
 
1.0%
-9.1362763 1
 
1.0%
-9.1400229 1
 
1.0%
-9.1370713 1
 
1.0%
-9.1481556 1
 
1.0%
-8.6065954 1
 
1.0%
-9.169425 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
-9.3830047 1
1.0%
-9.169425 1
1.0%
-9.1619033 1
1.0%
-9.1523775 1
1.0%
-9.1507979 1
1.0%
-9.1481556 1
1.0%
-9.1477716 1
1.0%
-9.1470636 1
1.0%
-9.1462283 1
1.0%
-9.1446287 1
1.0%
ValueCountFrequency (%)
-8.4314792 1
1.0%
-8.4316016 1
1.0%
-8.4336829 1
1.0%
-8.6017023 1
1.0%
-8.6036881 1
1.0%
-8.603964 1
1.0%
-8.6046728 1
1.0%
-8.6046759 1
1.0%
-8.6050036 1
1.0%
-8.6050901 1
1.0%

la
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.83139
Minimum37.094729
Maximum41.153629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:05:22.119456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.094729
5-th percentile38.709049
Q138.713849
median38.785838
Q341.144729
95-th percentile41.151067
Maximum41.153629
Range4.0588994
Interquartile range (IQR)2.4308807

Descriptive statistics

Standard deviation1.2469652
Coefficient of variation (CV)0.031306093
Kurtosis-1.6671692
Mean39.83139
Median Absolute Deviation (MAD)1.1304723
Skewness-0.034060135
Sum3983.139
Variance1.5549222
MonotonicityNot monotonic
2023-12-10T19:05:22.366888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.1439028 2
 
2.0%
38.7709829 2
 
2.0%
41.1442306 1
 
1.0%
38.7131223 1
 
1.0%
38.7141751 1
 
1.0%
38.7139188 1
 
1.0%
38.7116138 1
 
1.0%
38.7321959 1
 
1.0%
41.1478226 1
 
1.0%
38.7158954 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
37.0947292 1
1.0%
37.1074491 1
1.0%
38.53625 1
1.0%
38.7058809 1
1.0%
38.7070427 1
1.0%
38.7091545 1
1.0%
38.7098649 1
1.0%
38.7099688 1
1.0%
38.7102416 1
1.0%
38.7103968 1
1.0%
ValueCountFrequency (%)
41.1536286 1
1.0%
41.1530674 1
1.0%
41.1526776 1
1.0%
41.1521308 1
1.0%
41.151148 1
1.0%
41.151063 1
1.0%
41.1506321 1
1.0%
41.149862 1
1.0%
41.1495789 1
1.0%
41.1495088 1
1.0%

tel_no
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing79
Missing (%)79.0%
Memory size932.0 B
2023-12-10T19:05:22.685812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length15.571429
Min length13

Characters and Unicode

Total characters327
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row+351 227 664 171
2nd row+351 21 011 5922
3rd row+351211931646
4th row+351 22 340 0700
5th row+351 21 346 1078
ValueCountFrequency (%)
351 18
24.0%
22 7
 
9.3%
21 6
 
8.0%
0800 1
 
1.3%
1391 1
 
1.3%
203 1
 
1.3%
9062 1
 
1.3%
013 1
 
1.3%
3100 1
 
1.3%
239 1
 
1.3%
Other values (37) 37
49.3%
2023-12-10T19:05:23.257236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
16.5%
1 45
13.8%
3 43
13.1%
0 37
11.3%
2 36
11.0%
5 31
9.5%
+ 21
 
6.4%
9 16
 
4.9%
7 13
 
4.0%
4 11
 
3.4%
Other values (2) 20
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 252
77.1%
Space Separator 54
 
16.5%
Math Symbol 21
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 45
17.9%
3 43
17.1%
0 37
14.7%
2 36
14.3%
5 31
12.3%
9 16
 
6.3%
7 13
 
5.2%
4 11
 
4.4%
8 11
 
4.4%
6 9
 
3.6%
Space Separator
ValueCountFrequency (%)
54
100.0%
Math Symbol
ValueCountFrequency (%)
+ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 327
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
54
16.5%
1 45
13.8%
3 43
13.1%
0 37
11.3%
2 36
11.0%
5 31
9.5%
+ 21
 
6.4%
9 16
 
4.9%
7 13
 
4.0%
4 11
 
3.4%
Other values (2) 20
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
16.5%
1 45
13.8%
3 43
13.1%
0 37
11.3%
2 36
11.0%
5 31
9.5%
+ 21
 
6.4%
9 16
 
4.9%
7 13
 
4.0%
4 11
 
3.4%
Other values (2) 20
 
6.1%

BASE_YMD
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-12-09 00:00:00
Maximum2020-12-09 00:00:00
2023-12-10T19:05:23.462320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:05:23.611332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-10T19:05:13.296851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:05:12.974846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:05:13.456977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:05:13.127757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:05:23.731811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
se_nmeng_lang_hotel_nmkor_lang_hotel_nmrn_adreslolatel_no
se_nm1.0000.6900.6011.0000.0000.0001.000
eng_lang_hotel_nm0.6901.0001.0000.9990.0000.0001.000
kor_lang_hotel_nm0.6011.0001.0000.9990.0000.0001.000
rn_adres1.0000.9990.9991.0001.0001.0001.000
lo0.0000.0000.0001.0001.0000.9611.000
la0.0000.0000.0001.0000.9611.0001.000
tel_no1.0001.0001.0001.0001.0001.0001.000
2023-12-10T19:05:23.923916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
lolase_nm
lo1.0000.7220.000
la0.7221.0000.000
se_nm0.0000.0001.000

Missing values

2023-12-10T19:05:13.740810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:05:14.137012image/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.
2023-12-10T19:05:14.353865image/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

se_nmeng_lang_hotel_nmkor_lang_hotel_nmeng_lang_area_nmkor_lang_area_nmjan_lang_area_nmchg_lang_area_nmrn_adreslolatel_noBASE_YMD
0호텔CATS Porto hostel : Tattva Design hostel타트바 디자인 호스텔Portugal포르투갈ポルトガル葡萄牙Rua do Cativo 26, 4000-098 Porto, 포르투갈-8.6089941.144231<NA>2020-12-09
1게스트하우스Yes! Porto Hostel예스! 포르토 호스텔Portugal포르투갈ポルトガル葡萄牙Rua Arquitecto Nicolau Nazoni 31, 4000 포르토 포르투갈-8.61358741.145742<NA>2020-12-09
2호텔Mercure Porto Centro Hotel머큐어 포르토 센트로 호텔Portugal포르투갈ポルトガル葡萄牙Rua da Madeira 31, 4000 Porto, 포르투갈-8.60784941.145571<NA>2020-12-09
3기타Bluesock Hostels Porto블루삭 호스텔 포르투Portugal포르투갈ポルトガル葡萄牙R. de São João 40, 4050-492 Porto, 포르투갈-8.61332941.141385+351 227 664 1712020-12-09
4게스트하우스Travellers House트레블러스 하우스 호스텔Portugal포르투갈ポルトガル葡萄牙R. Augusta 89, 1100-053 Lisboa, 포르투갈-9.13753338.709969+351 21 011 59222020-12-09
5호텔Goodmorning hostel굿모닝 호스텔Portugal포르투갈ポルトガル葡萄牙Praça dos Restauradores 69, 1150-265 Lisboa, 포르투갈-9.14094838.715624<NA>2020-12-09
6호텔Sunset Destination hostel선셋 데스티네이션 호스텔Portugal포르투갈ポルトガル葡萄牙Cais do Sodré, 1200-161 Lisboa, 포르투갈-9.14388638.705881<NA>2020-12-09
7호텔Yes Lisbon hostel예스 리스본 호스텔Portugal포르투갈ポルトガル葡萄牙Rua de São Julião 144, 1100-154 Lisboa, 포르투갈-9.13764538.709154<NA>2020-12-09
8게스트하우스Home Lisbon hostel홈 리스본 호스텔Portugal포르투갈ポルトガル葡萄牙Rua de São Nicolau, 1100-151 리스본 포르투갈-9.13711538.710397<NA>2020-12-09
9호텔Hotel Tryp Lisboa Aeroporto트립 리스보아 아에로포르토Portugal포르투갈ポルトガル葡萄牙Lisbon Portela Airport (LIS), Rua C 124, 1700-111 리스본 포르투갈-9.12507338.770983<NA>2020-12-09
se_nmeng_lang_hotel_nmkor_lang_hotel_nmeng_lang_area_nmkor_lang_area_nmjan_lang_area_nmchg_lang_area_nmrn_adreslolatel_noBASE_YMD
90게스트하우스Porto Wine hostel포르투 와인 호스텔Portugal포르투갈ポルトガル葡萄牙Rua Campo dos Mártires da Pátria 55, 4050-011 Porto, 포르투갈-8.61700641.146645<NA>2020-12-09
91호텔Hotel Cruz Alta호텔 크루즈 알타Portugal포르투갈ポルトガル葡萄牙R. Cónego Nunes Formigão 40, 2495-402 Fátima, 포르투갈-8.67361139.629167<NA>2020-12-09
92호텔Novotel Setubal<NA>Portugal포르투갈ポルトガル葡萄牙Avenida Antero de Quental, 2910 Setubal, 포르투갈-8.87573138.53625<NA>2020-12-09
93기타Teatro Boutique B&B테아트로 부티크 B&BPortugal포르투갈ポルトガル葡萄牙R. Trindade 36, 1200-122 Lisboa, 포르투갈-9.14210838.711894<NA>2020-12-09
94게스트하우스guest House Santa Clara산타 클라라 게스트하우스Portugal포르투갈ポルトガル葡萄牙Avenida João das Regras, 3040-242 Coimbra, 포르투갈-8.43368340.203454<NA>2020-12-09
95게스트하우스New Lisbon Concept hostel뉴 리스본 콘셉트 호스텔Portugal포르투갈ポルトガル葡萄牙Av. da Liberdade 204, 1250-147 Lisboa, 포르투갈-9.14622838.721765<NA>2020-12-09
96호텔Shiado hostel<NA>Portugal포르투갈ポルトガル葡萄牙R. Anchieta 3, 1200-224 Lisboa, 포르투갈-9.14105638.709865<NA>2020-12-09
97게스트하우스hostel Gaia Porto호스텔 가이아 포르토Portugal포르투갈ポルトガル葡萄牙R. Cândido dos Reis 374, 4430-999 Vila Nova de Gaia, 포르투갈-8.61153641.134006+351 933 709 5012020-12-09
98호텔6Only guest House<NA>Portugal포르투갈ポルトガル葡萄牙Rua Duque Loulé 170-174, 4000-324 포르토 포르투갈-8.60467341.144407<NA>2020-12-09
99호텔<NA>HF페닉스 뮤직Portugal포르투갈ポルトガル葡萄牙R. Joaquim António de Aguiar 25, 1250-096 Lisboa, 포르투갈-9.15237838.725009<NA>2020-12-09