Overview

Dataset statistics

Number of variables10
Number of observations300
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.4 KiB
Average record size in memory83.4 B

Variable types

Numeric3
Text4
Categorical3

Alerts

CRNCY_CD has constant value ""Constant
COUNTRY_NM has constant value ""Constant
CTY_NM has constant value ""Constant
MENU_ID has unique valuesUnique
MENU_PRC has 13 (4.3%) zerosZeros

Reproduction

Analysis started2023-12-10 10:00:01.438856
Analysis finished2023-12-10 10:00:04.670964
Duration3.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

MENU_ID
Real number (ℝ)

UNIQUE 

Distinct300
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6300.3933
Minimum19
Maximum19904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-10T19:00:04.795891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile688.95
Q11583.75
median2971.5
Q38712.25
95-th percentile19885.05
Maximum19904
Range19885
Interquartile range (IQR)7128.5

Descriptive statistics

Standard deviation6655.0053
Coefficient of variation (CV)1.0562841
Kurtosis-0.17853701
Mean6300.3933
Median Absolute Deviation (MAD)1992
Skewness1.1738529
Sum1890118
Variance44289096
MonotonicityStrictly increasing
2023-12-10T19:00:05.108232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 1
 
0.3%
6098 1
 
0.3%
6079 1
 
0.3%
6075 1
 
0.3%
6074 1
 
0.3%
6073 1
 
0.3%
6064 1
 
0.3%
6062 1
 
0.3%
5928 1
 
0.3%
5385 1
 
0.3%
Other values (290) 290
96.7%
ValueCountFrequency (%)
19 1
0.3%
22 1
0.3%
117 1
0.3%
618 1
0.3%
620 1
0.3%
629 1
0.3%
633 1
0.3%
639 1
0.3%
640 1
0.3%
641 1
0.3%
ValueCountFrequency (%)
19904 1
0.3%
19903 1
0.3%
19901 1
0.3%
19900 1
0.3%
19898 1
0.3%
19895 1
0.3%
19894 1
0.3%
19893 1
0.3%
19892 1
0.3%
19891 1
0.3%

MENU_JLANG_NM
Text

Distinct264
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-10T19:00:05.595145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length7.62
Min length2

Characters and Unicode

Total characters2286
Distinct characters294
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique234 ?
Unique (%)78.0%

Sample

1st rowレアチーズケーキ
2nd rowシュークリーム
3rd rowおまかせコース
4th rowキャビア
5th rowオマール海老パスタ
ValueCountFrequency (%)
menu 5
 
1.6%
パスタ 3
 
0.9%
ロース 3
 
0.9%
マルゲリータ 3
 
0.9%
おまかせコース 3
 
0.9%
ディナーコース 3
 
0.9%
らーめん 3
 
0.9%
地鶏半羽のタンドリーチキン 2
 
0.6%
たいやき 2
 
0.6%
水牛のモッツァレラチーズのマルゲリータ 2
 
0.6%
Other values (266) 289
90.9%
2023-12-10T19:00:06.297067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
ー 212
 
9.3%
ン 107
 
4.7%
ラ 63
 
2.8%
ス 62
 
2.7%
カ 55
 
2.4%
チ 53
 
2.3%
ッ 50
 
2.2%
タ 47
 
2.1%
レ 45
 
2.0%
リ 45
 
2.0%
Other values (284) 1547
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1952
85.4%
Modifier Letter 212
 
9.3%
Uppercase Letter 25
 
1.1%
Space Separator 21
 
0.9%
Open Punctuation 18
 
0.8%
Close Punctuation 18
 
0.8%
Other Punctuation 14
 
0.6%
Lowercase Letter 11
 
0.5%
Decimal Number 11
 
0.5%
Math Symbol 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 107
 
5.5%
ラ 63
 
3.2%
ス 62
 
3.2%
カ 55
 
2.8%
チ 53
 
2.7%
ッ 50
 
2.6%
タ 47
 
2.4%
レ 45
 
2.3%
リ 45
 
2.3%
ト 44
 
2.3%
Other values (253) 1381
70.7%
Uppercase Letter
ValueCountFrequency (%)
M 6
24.0%
B 5
20.0%
A 4
16.0%
C 2
 
8.0%
U 2
 
8.0%
N 2
 
8.0%
E 2
 
8.0%
Q 1
 
4.0%
Ｃ 1
 
4.0%
Decimal Number
ValueCountFrequency (%)
0 2
18.2%
5 2
18.2%
1 2
18.2%
4 2
18.2%
3 2
18.2%
9 1
9.1%
Other Punctuation
ValueCountFrequency (%)
・ 10
71.4%
、 2
 
14.3%
/ 1
 
7.1%
＆ 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
u 3
27.3%
n 3
27.3%
e 3
27.3%
g 2
18.2%
Space Separator
ValueCountFrequency (%)
20
95.2%
　 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 17
94.4%
「 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 17
94.4%
」 1
 
5.6%
Modifier Letter
ValueCountFrequency (%)
ー 212
100.0%
Math Symbol
ValueCountFrequency (%)
＋ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Katakana 1239
54.2%
Han 401
 
17.5%
Hiragana 312
 
13.6%
Common 298
 
13.0%
Latin 36
 
1.6%

Most frequent character per script

Han
ValueCountFrequency (%)
麺 23
 
5.7%
子 17
 
4.2%
特 14
 
3.5%
焼 13
 
3.2%
定 11
 
2.7%
日 11
 
2.7%
餃 10
 
2.5%
塩 10
 
2.5%
食 9
 
2.2%
本 8
 
2.0%
Other values (130) 275
68.6%
Katakana
ValueCountFrequency (%)
ン 107
 
8.6%
ラ 63
 
5.1%
ス 62
 
5.0%
カ 55
 
4.4%
チ 53
 
4.3%
ッ 50
 
4.0%
タ 47
 
3.8%
レ 45
 
3.6%
リ 45
 
3.6%
ト 44
 
3.6%
Other values (62) 668
53.9%
Hiragana
ValueCountFrequency (%)
の 36
 
11.5%
つ 21
 
6.7%
き 18
 
5.8%
り 17
 
5.4%
そ 15
 
4.8%
ら 15
 
4.8%
ん 14
 
4.5%
め 14
 
4.5%
か 14
 
4.5%
や 10
 
3.2%
Other values (41) 138
44.2%
Common
ValueCountFrequency (%)
ー 212
71.1%
20
 
6.7%
( 17
 
5.7%
) 17
 
5.7%
・ 10
 
3.4%
＋ 4
 
1.3%
0 2
 
0.7%
5 2
 
0.7%
1 2
 
0.7%
4 2
 
0.7%
Other values (8) 10
 
3.4%
Latin
ValueCountFrequency (%)
M 6
16.7%
B 5
13.9%
A 4
11.1%
u 3
8.3%
n 3
8.3%
e 3
8.3%
g 2
 
5.6%
C 2
 
5.6%
U 2
 
5.6%
N 2
 
5.6%
Other values (3) 4
11.1%

Most occurring blocks

ValueCountFrequency (%)
Katakana 1461
63.9%
CJK 401
 
17.5%
Hiragana 312
 
13.6%
ASCII 101
 
4.4%
None 11
 
0.5%

Most frequent character per block

Katakana
ValueCountFrequency (%)
ー 212
 
14.5%
ン 107
 
7.3%
ラ 63
 
4.3%
ス 62
 
4.2%
カ 55
 
3.8%
チ 53
 
3.6%
ッ 50
 
3.4%
タ 47
 
3.2%
レ 45
 
3.1%
リ 45
 
3.1%
Other values (64) 722
49.4%
Hiragana
ValueCountFrequency (%)
の 36
 
11.5%
つ 21
 
6.7%
き 18
 
5.8%
り 17
 
5.4%
そ 15
 
4.8%
ら 15
 
4.8%
ん 14
 
4.5%
め 14
 
4.5%
か 14
 
4.5%
や 10
 
3.2%
Other values (41) 138
44.2%
CJK
ValueCountFrequency (%)
麺 23
 
5.7%
子 17
 
4.2%
特 14
 
3.5%
焼 13
 
3.2%
定 11
 
2.7%
日 11
 
2.7%
餃 10
 
2.5%
塩 10
 
2.5%
食 9
 
2.2%
本 8
 
2.0%
Other values (130) 275
68.6%
ASCII
ValueCountFrequency (%)
20
19.8%
( 17
16.8%
) 17
16.8%
M 6
 
5.9%
B 5
 
5.0%
A 4
 
4.0%
u 3
 
3.0%
n 3
 
3.0%
e 3
 
3.0%
g 2
 
2.0%
Other values (12) 21
20.8%
None
ValueCountFrequency (%)
＋ 4
36.4%
、 2
18.2%
」 1
 
9.1%
「 1
 
9.1%
　 1
 
9.1%
＆ 1
 
9.1%
Ｃ 1
 
9.1%

MENU_KLANG_NM
Text

Distinct256
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-10T19:00:07.062109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length21
Mean length7.5566667
Min length2

Characters and Unicode

Total characters2267
Distinct characters223
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique221 ?
Unique (%)73.7%

Sample

1st row레어 치즈케이크
2nd row슈크리무
3rd row오마카세 코스
4th row캐비어
5th row오마르 에비 파스타
ValueCountFrequency (%)
카레 25
 
4.2%
라멘 20
 
3.4%
코스 10
 
1.7%
런치 8
 
1.4%
파스타 7
 
1.2%
노 7
 
1.2%
시오 6
 
1.0%
로스 6
 
1.0%
에비 6
 
1.0%
치킨 6
 
1.0%
Other values (358) 491
82.9%
2023-12-10T19:00:07.836291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
292
 
12.9%
이 79
 
3.5%
카 66
 
2.9%
라 60
 
2.6%
스 59
 
2.6%
멘 58
 
2.6%
리 56
 
2.5%
레 48
 
2.1%
타 44
 
1.9%
치 42
 
1.9%
Other values (213) 1463
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1895
83.6%
Space Separator 292
 
12.9%
Uppercase Letter 25
 
1.1%
Open Punctuation 17
 
0.7%
Close Punctuation 17
 
0.7%
Decimal Number 7
 
0.3%
Other Punctuation 5
 
0.2%
Lowercase Letter 5
 
0.2%
Math Symbol 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 79
 
4.2%
카 66
 
3.5%
라 60
 
3.2%
스 59
 
3.1%
멘 58
 
3.1%
리 56
 
3.0%
레 48
 
2.5%
타 44
 
2.3%
치 42
 
2.2%
쿠 40
 
2.1%
Other values (192) 1343
70.9%
Uppercase Letter
ValueCountFrequency (%)
M 6
24.0%
N 4
16.0%
U 4
16.0%
E 4
16.0%
C 3
12.0%
A 2
 
8.0%
B 2
 
8.0%
Decimal Number
ValueCountFrequency (%)
0 2
28.6%
5 2
28.6%
1 2
28.6%
9 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
g 2
40.0%
u 1
20.0%
n 1
20.0%
e 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
/ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
292
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1895
83.6%
Common 342
 
15.1%
Latin 30
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 79
 
4.2%
카 66
 
3.5%
라 60
 
3.2%
스 59
 
3.1%
멘 58
 
3.1%
리 56
 
3.0%
레 48
 
2.5%
타 44
 
2.3%
치 42
 
2.2%
쿠 40
 
2.1%
Other values (192) 1343
70.9%
Latin
ValueCountFrequency (%)
M 6
20.0%
N 4
13.3%
U 4
13.3%
E 4
13.3%
C 3
10.0%
A 2
 
6.7%
g 2
 
6.7%
B 2
 
6.7%
u 1
 
3.3%
n 1
 
3.3%
Common
ValueCountFrequency (%)
292
85.4%
( 17
 
5.0%
) 17
 
5.0%
+ 4
 
1.2%
, 4
 
1.2%
0 2
 
0.6%
5 2
 
0.6%
1 2
 
0.6%
9 1
 
0.3%
/ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1895
83.6%
ASCII 372
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
292
78.5%
( 17
 
4.6%
) 17
 
4.6%
M 6
 
1.6%
+ 4
 
1.1%
, 4
 
1.1%
N 4
 
1.1%
U 4
 
1.1%
E 4
 
1.1%
C 3
 
0.8%
Other values (11) 17
 
4.6%
Hangul
ValueCountFrequency (%)
이 79
 
4.2%
카 66
 
3.5%
라 60
 
3.2%
스 59
 
3.1%
멘 58
 
3.1%
리 56
 
3.0%
레 48
 
2.5%
타 44
 
2.3%
치 42
 
2.2%
쿠 40
 
2.1%
Other values (192) 1343
70.9%

MENU_CHNLNG_NM
Text

Distinct254
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-10T19:00:08.369710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length5.0166667
Min length1

Characters and Unicode

Total characters1505
Distinct characters337
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique218 ?
Unique (%)72.7%

Sample

1st row软奶酪果冻蛋糕
2nd row奶油泡芙
3rd row厨师安排套餐
4th row鱼子酱
5th row龙虾意面
ValueCountFrequency (%)
menu 5
 
1.6%
拉面 4
 
1.3%
蔬菜咖喱 4
 
1.3%
意大利面 3
 
1.0%
4中芝士披萨 3
 
1.0%
里脊肉 3
 
1.0%
盐味拉面 3
 
1.0%
晚餐套餐 3
 
1.0%
玛格丽特披萨 3
 
1.0%
咖啡 2
 
0.7%
Other values (245) 272
89.2%
2023-12-10T19:00:09.770573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
面 81
 
5.4%
餐 41
 
2.7%
拉 36
 
2.4%
咖 32
 
2.1%
肉 31
 
2.1%
喱 30
 
2.0%
牛 25
 
1.7%
套 23
 
1.5%
排 22
 
1.5%
特 19
 
1.3%
Other values (327) 1165
77.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1417
94.2%
Uppercase Letter 31
 
2.1%
Close Punctuation 15
 
1.0%
Open Punctuation 15
 
1.0%
Other Punctuation 9
 
0.6%
Decimal Number 8
 
0.5%
Space Separator 5
 
0.3%
Math Symbol 4
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
面 81
 
5.7%
餐 41
 
2.9%
拉 36
 
2.5%
咖 32
 
2.3%
肉 31
 
2.2%
喱 30
 
2.1%
牛 25
 
1.8%
套 23
 
1.6%
排 22
 
1.6%
特 19
 
1.3%
Other values (307) 1077
76.0%
Uppercase Letter
ValueCountFrequency (%)
M 6
19.4%
U 5
16.1%
N 5
16.1%
E 5
16.1%
A 4
12.9%
B 3
9.7%
C 3
9.7%
Decimal Number
ValueCountFrequency (%)
4 3
37.5%
5 2
25.0%
9 1
 
12.5%
1 1
 
12.5%
0 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
， 4
44.4%
· 4
44.4%
・ 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 1417
94.2%
Common 56
 
3.7%
Latin 32
 
2.1%

Most frequent character per script

Han
ValueCountFrequency (%)
面 81
 
5.7%
餐 41
 
2.9%
拉 36
 
2.5%
咖 32
 
2.3%
肉 31
 
2.2%
喱 30
 
2.1%
牛 25
 
1.8%
套 23
 
1.6%
排 22
 
1.6%
特 19
 
1.3%
Other values (307) 1077
76.0%
Common
ValueCountFrequency (%)
) 15
26.8%
( 15
26.8%
5
 
8.9%
+ 4
 
7.1%
， 4
 
7.1%
· 4
 
7.1%
4 3
 
5.4%
5 2
 
3.6%
・ 1
 
1.8%
9 1
 
1.8%
Other values (2) 2
 
3.6%
Latin
ValueCountFrequency (%)
M 6
18.8%
U 5
15.6%
N 5
15.6%
E 5
15.6%
A 4
12.5%
B 3
9.4%
C 3
9.4%
g 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 1417
94.2%
ASCII 79
 
5.2%
None 8
 
0.5%
Katakana 1
 
0.1%

Most frequent character per block

CJK
ValueCountFrequency (%)
面 81
 
5.7%
餐 41
 
2.9%
拉 36
 
2.5%
咖 32
 
2.3%
肉 31
 
2.2%
喱 30
 
2.1%
牛 25
 
1.8%
套 23
 
1.6%
排 22
 
1.6%
特 19
 
1.3%
Other values (307) 1077
76.0%
ASCII
ValueCountFrequency (%)
) 15
19.0%
( 15
19.0%
M 6
 
7.6%
5
 
6.3%
U 5
 
6.3%
N 5
 
6.3%
E 5
 
6.3%
+ 4
 
5.1%
A 4
 
5.1%
B 3
 
3.8%
Other values (7) 12
15.2%
None
ValueCountFrequency (%)
， 4
50.0%
· 4
50.0%
Katakana
ValueCountFrequency (%)
・ 1
100.0%

MENU_ENGL_NM
Text

Distinct254
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-10T19:00:10.431074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length35
Mean length15.283333
Min length4

Characters and Unicode

Total characters4585
Distinct characters68
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

Unique218 ?
Unique (%)72.7%

Sample

1st rowRare cheese cake
2nd rowChoux cream
3rd rowOmakase course
4th rowCaviar
5th rowOmaru ebi pasta
ValueCountFrequency (%)
curry 29
 
4.0%
ramen 28
 
3.9%
no 16
 
2.2%
lunch 13
 
1.8%
course 11
 
1.5%
shio 9
 
1.2%
teishoku 9
 
1.2%
katsu 9
 
1.2%
tsukemen 9
 
1.2%
chicken 9
 
1.2%
Other values (344) 581
80.4%
2023-12-10T19:00:11.387290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 476
 
10.4%
423
 
9.2%
e 327
 
7.1%
i 323
 
7.0%
o 320
 
7.0%
r 273
 
6.0%
u 271
 
5.9%
n 260
 
5.7%
s 234
 
5.1%
t 197
 
4.3%
Other values (58) 1481
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3768
82.2%
Space Separator 423
 
9.2%
Uppercase Letter 331
 
7.2%
Close Punctuation 17
 
0.4%
Open Punctuation 17
 
0.4%
Decimal Number 11
 
0.2%
Dash Punctuation 8
 
0.2%
Math Symbol 4
 
0.1%
Other Punctuation 4
 
0.1%
Other Letter 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 476
12.6%
e 327
 
8.7%
i 323
 
8.6%
o 320
 
8.5%
r 273
 
7.2%
u 271
 
7.2%
n 260
 
6.9%
s 234
 
6.2%
t 197
 
5.2%
k 155
 
4.1%
Other values (16) 932
24.7%
Uppercase Letter
ValueCountFrequency (%)
C 37
 
11.2%
M 34
 
10.3%
T 33
 
10.0%
S 29
 
8.8%
H 18
 
5.4%
B 18
 
5.4%
G 16
 
4.8%
N 16
 
4.8%
R 15
 
4.5%
K 14
 
4.2%
Other values (16) 101
30.5%
Decimal Number
ValueCountFrequency (%)
3 2
18.2%
4 2
18.2%
1 2
18.2%
5 2
18.2%
0 2
18.2%
9 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
& 1
25.0%
/ 1
25.0%
Other Letter
ValueCountFrequency (%)
五 1
50.0%
個 1
50.0%
Space Separator
ValueCountFrequency (%)
423
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4099
89.4%
Common 484
 
10.6%
Han 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 476
 
11.6%
e 327
 
8.0%
i 323
 
7.9%
o 320
 
7.8%
r 273
 
6.7%
u 271
 
6.6%
n 260
 
6.3%
s 234
 
5.7%
t 197
 
4.8%
k 155
 
3.8%
Other values (42) 1263
30.8%
Common
ValueCountFrequency (%)
423
87.4%
) 17
 
3.5%
( 17
 
3.5%
- 8
 
1.7%
+ 4
 
0.8%
, 2
 
0.4%
3 2
 
0.4%
4 2
 
0.4%
1 2
 
0.4%
5 2
 
0.4%
Other values (4) 5
 
1.0%
Han
ValueCountFrequency (%)
五 1
50.0%
個 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4577
99.8%
None 6
 
0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 476
 
10.4%
423
 
9.2%
e 327
 
7.1%
i 323
 
7.1%
o 320
 
7.0%
r 273
 
6.0%
u 271
 
5.9%
n 260
 
5.7%
s 234
 
5.1%
t 197
 
4.3%
Other values (54) 1473
32.2%
None
ValueCountFrequency (%)
ō 5
83.3%
Ō 1
 
16.7%
CJK
ValueCountFrequency (%)
五 1
50.0%
個 1
50.0%

MENU_PRC
Real number (ℝ)

ZEROS 

Distinct127
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1628.23
Minimum0
Maximum16800
Zeros13
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-10T19:00:11.679169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile139
Q1700
median900
Q31470
95-th percentile6320
Maximum16800
Range16800
Interquartile range (IQR)770

Descriptive statistics

Standard deviation2363.9994
Coefficient of variation (CV)1.451883
Kurtosis15.744392
Mean1628.23
Median Absolute Deviation (MAD)330
Skewness3.7340584
Sum488469
Variance5588493.1
MonotonicityNot monotonic
2023-12-10T19:00:11.988997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 13
 
4.3%
800 13
 
4.3%
850 11
 
3.7%
900 10
 
3.3%
750 10
 
3.3%
950 8
 
2.7%
700 8
 
2.7%
650 8
 
2.7%
880 8
 
2.7%
1000 7
 
2.3%
Other values (117) 204
68.0%
ValueCountFrequency (%)
0 13
4.3%
105 1
 
0.3%
120 1
 
0.3%
140 1
 
0.3%
150 1
 
0.3%
170 1
 
0.3%
185 1
 
0.3%
190 2
 
0.7%
200 2
 
0.7%
205 1
 
0.3%
ValueCountFrequency (%)
16800 1
0.3%
15000 1
0.3%
14400 1
0.3%
13200 1
0.3%
12600 1
0.3%
10500 1
0.3%
10200 1
0.3%
8800 1
0.3%
8500 1
0.3%
8200 1
0.3%

CRNCY_CD
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
JPY
300 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
JPY 300
100.0%

Length

2023-12-10T19:00:12.276734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:00:12.481178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
jpy 300
100.0%

COUNTRY_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
JAPAN
300 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
JAPAN 300
100.0%

Length

2023-12-10T19:00:12.657077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:00:12.813925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
japan 300
100.0%

CTY_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Tokyo
300 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Tokyo 300
100.0%

Length

2023-12-10T19:00:12.982904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:00:13.162475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
tokyo 300
100.0%

RSTRNT_ID
Real number (ℝ)

Distinct88
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean379.81667
Minimum3
Maximum959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-10T19:00:13.379247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile32
Q1143
median362
Q3529
95-th percentile889.25
Maximum959
Range956
Interquartile range (IQR)386

Descriptive statistics

Standard deviation264.58821
Coefficient of variation (CV)0.69662085
Kurtosis-0.70628679
Mean379.81667
Median Absolute Deviation (MAD)218
Skewness0.45771685
Sum113945
Variance70006.919
MonotonicityNot monotonic
2023-12-10T19:00:13.647791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
529 11
 
3.7%
143 11
 
3.7%
401 7
 
2.3%
144 7
 
2.3%
433 7
 
2.3%
504 6
 
2.0%
302 6
 
2.0%
362 6
 
2.0%
503 6
 
2.0%
477 5
 
1.7%
Other values (78) 228
76.0%
ValueCountFrequency (%)
3 4
1.3%
4 4
1.3%
9 1
 
0.3%
18 4
1.3%
32 4
1.3%
41 4
1.3%
50 5
1.7%
52 4
1.3%
55 4
1.3%
60 4
1.3%
ValueCountFrequency (%)
959 3
1.0%
952 3
1.0%
929 4
1.3%
922 3
1.0%
894 2
0.7%
889 2
0.7%
876 4
1.3%
850 2
0.7%
833 4
1.3%
800 1
 
0.3%

Interactions

2023-12-10T19:00:03.689516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:00:02.482391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:00:03.152095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:00:03.864876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:00:02.777710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:00:03.340355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:00:04.027106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:00:02.974684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:00:03.518804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:00:13.817793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
MENU_IDMENU_PRCRSTRNT_ID
MENU_ID1.0000.4890.671
MENU_PRC0.4891.0000.297
RSTRNT_ID0.6710.2971.000
2023-12-10T19:00:13.982039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
MENU_IDMENU_PRCRSTRNT_ID
MENU_ID1.000-0.088-0.115
MENU_PRC-0.0881.0000.020
RSTRNT_ID-0.1150.0201.000

Missing values

2023-12-10T19:00:04.276990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:00:04.560645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

MENU_IDMENU_JLANG_NMMENU_KLANG_NMMENU_CHNLNG_NMMENU_ENGL_NMMENU_PRCCRNCY_CDCOUNTRY_NMCTY_NMRSTRNT_ID
019レアチーズケーキ레어 치즈케이크软奶酪果冻蛋糕Rare cheese cake250JPYJAPANTokyo244
122シュークリーム슈크리무奶油泡芙Choux cream170JPYJAPANTokyo244
2117おまかせコース오마카세 코스厨师安排套餐Omakase course5250JPYJAPANTokyo377
3618キャビア캐비어鱼子酱Caviar14400JPYJAPANTokyo504
4620オマール海老パスタ오마르 에비 파스타龙虾意面Omaru ebi pasta7800JPYJAPANTokyo504
5629特選和牛フィレ도쿠센 와규 필레特选和牛里脊Tokusen wagyu filet13200JPYJAPANTokyo504
6633フレーズ후레즈文具Fraise2500JPYJAPANTokyo504
7639MENU AMENU AMENU AMENU A10200JPYJAPANTokyo504
8640MENU BMENU BMENU BMENU B8200JPYJAPANTokyo504
9641本日のコース혼지츠 노 코스今日套餐Honjitsu no course8800JPYJAPANTokyo889
MENU_IDMENU_JLANG_NMMENU_KLANG_NMMENU_CHNLNG_NMMENU_ENGL_NMMENU_PRCCRNCY_CDCOUNTRY_NMCTY_NMRSTRNT_ID
29019891クイッティオナムサイ タイの汁そば퀵 티오 남 사이 타이노 시루 소바泰国汤面Quick tio nam sai thai no shiru soba950JPYJAPANTokyo4
29119892特製ラーメン토쿠세이라멘特制拉面tokusei ramen900JPYJAPANTokyo18
29219893濃厚らー麺노우코라멘浓汤拉面Noko Ramen670JPYJAPANTokyo18
29319894らー麺라멘拉面Ramen650JPYJAPANTokyo18
29419895煮玉子ガーリックまぜそば니타마고 갈릭 마제소바煮鸡蛋蒜香拌面Nitamago garlic mazesoba870JPYJAPANTokyo18
29519898イートイン「浮島」잇토인 우키시마巧克力绿茶甜品Eat-in Ukishima1240JPYJAPANTokyo718
29619900ジャン・ピエール장 피에르约翰・皮埃尔Jean pierre500JPYJAPANTokyo718
29719901メロンパフェ메론 파르페哈密瓜冰淇淋Melon parfait1350JPYJAPANTokyo718
29819903パンペルデュー・ベルジュ판 페루듀 베루주巧克力布丁Pain perdu berge1240JPYJAPANTokyo718
29919904初夏のご馳走定食쇼카노 고치소테이쇼쿠初夏套餐Shokano gochiso teishoku1480JPYJAPANTokyo9