Overview

Dataset statistics

Number of variables18
Number of observations646
Missing cells760
Missing cells (%)6.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory92.2 KiB
Average record size in memory146.2 B

Variable types

Text13
Numeric2
Categorical2
DateTime1

Alerts

last_load_dttm has constant value ""Constant
cn_cd is highly overall correlated with cn and 1 other fieldsHigh correlation
cn is highly overall correlated with cn_cd and 1 other fieldsHigh correlation
parkng_at is highly overall correlated with cn_cd and 1 other fieldsHigh correlation
cn is highly imbalanced (66.4%)Imbalance
tel has 8 (1.2%) missing valuesMissing
img_file1 has 41 (6.3%) missing valuesMissing
img_name1 has 41 (6.3%) missing valuesMissing
img_file2 has 315 (48.8%) missing valuesMissing
img_name2 has 315 (48.8%) missing valuesMissing
idx has 8 (1.2%) missing valuesMissing
last_load_dttm has 8 (1.2%) missing valuesMissing

Reproduction

Analysis started2024-04-16 04:58:01.516405
Analysis finished2024-04-16 04:58:03.911963
Duration2.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

sj
Text

Distinct635
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-16T13:58:04.091730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.1795666
Min length1

Characters and Unicode

Total characters3346
Distinct characters436
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

Unique624 ?
Unique (%)96.6%

Sample

1st row서울칼국수
2nd row밀양삼대국밥
3rd row무진장횟집
4th row맛진고기
5th row밀양가마솥추어탕
ValueCountFrequency (%)
손칼국수 4
 
0.6%
서울칼국수 2
 
0.3%
대가호 2
 
0.3%
칼국수 2
 
0.3%
장터국밥 2
 
0.3%
우정분식 2
 
0.3%
까꼬뽀꼬 2
 
0.3%
카페 2
 
0.3%
유식당 2
 
0.3%
시골집 2
 
0.3%
Other values (664) 668
96.8%
2024-04-16T13:58:04.523817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 99
 
3.0%
수 79
 
2.4%
식 74
 
2.2%
당 62
 
1.9%
밥 62
 
1.9%
어 61
 
1.8%
가 54
 
1.6%
미 54
 
1.6%
이 54
 
1.6%
리 52
 
1.6%
Other values (426) 2695
80.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3225
96.4%
Space Separator 45
 
1.3%
Decimal Number 36
 
1.1%
Close Punctuation 10
 
0.3%
Open Punctuation 10
 
0.3%
Other Punctuation 6
 
0.2%
Lowercase Letter 6
 
0.2%
Uppercase Letter 5
 
0.1%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 99
 
3.1%
수 79
 
2.4%
식 74
 
2.3%
당 62
 
1.9%
밥 62
 
1.9%
어 61
 
1.9%
가 54
 
1.7%
미 54
 
1.7%
이 54
 
1.7%
리 52
 
1.6%
Other values (399) 2574
79.8%
Decimal Number
ValueCountFrequency (%)
1 10
27.8%
7 7
19.4%
0 7
19.4%
2 4
 
11.1%
6 2
 
5.6%
5 2
 
5.6%
8 1
 
2.8%
3 1
 
2.8%
4 1
 
2.8%
9 1
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
y 2
33.3%
g 1
16.7%
u 1
16.7%
o 1
16.7%
b 1
16.7%
Other Punctuation
ValueCountFrequency (%)
& 3
50.0%
/ 1
 
16.7%
. 1
 
16.7%
, 1
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
J 2
40.0%
C 1
20.0%
R 1
20.0%
H 1
20.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3225
96.4%
Common 110
 
3.3%
Latin 11
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 99
 
3.1%
수 79
 
2.4%
식 74
 
2.3%
당 62
 
1.9%
밥 62
 
1.9%
어 61
 
1.9%
가 54
 
1.7%
미 54
 
1.7%
이 54
 
1.7%
리 52
 
1.6%
Other values (399) 2574
79.8%
Common
ValueCountFrequency (%)
45
40.9%
1 10
 
9.1%
) 10
 
9.1%
( 10
 
9.1%
7 7
 
6.4%
0 7
 
6.4%
2 4
 
3.6%
- 3
 
2.7%
& 3
 
2.7%
6 2
 
1.8%
Other values (8) 9
 
8.2%
Latin
ValueCountFrequency (%)
J 2
18.2%
y 2
18.2%
g 1
9.1%
u 1
9.1%
o 1
9.1%
b 1
9.1%
C 1
9.1%
R 1
9.1%
H 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3225
96.4%
ASCII 121
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 99
 
3.1%
수 79
 
2.4%
식 74
 
2.3%
당 62
 
1.9%
밥 62
 
1.9%
어 61
 
1.9%
가 54
 
1.7%
미 54
 
1.7%
이 54
 
1.7%
리 52
 
1.6%
Other values (399) 2574
79.8%
ASCII
ValueCountFrequency (%)
45
37.2%
1 10
 
8.3%
) 10
 
8.3%
( 10
 
8.3%
7 7
 
5.8%
0 7
 
5.8%
2 4
 
3.3%
- 3
 
2.5%
& 3
 
2.5%
6 2
 
1.7%
Other values (17) 20
16.5%

m_nm
Text

Distinct627
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-16T13:58:04.814399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length3.0727554
Min length2

Characters and Unicode

Total characters1985
Distinct characters207
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique609 ?
Unique (%)94.3%

Sample

1st row김경애
2nd row박민호
3rd row옥둘선
4th row이경희
5th row유인숙
ValueCountFrequency (%)
이영자 3
 
0.5%
김경수 2
 
0.3%
이명호 2
 
0.3%
한경화 2
 
0.3%
김혜정 2
 
0.3%
이영우 2
 
0.3%
김영식 2
 
0.3%
김명희 2
 
0.3%
2
 
0.3%
김정현 2
 
0.3%
Other values (620) 628
96.8%
2024-04-16T13:58:05.227168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 125
 
6.3%
정 99
 
5.0%
이 93
 
4.7%
순 59
 
3.0%
희 54
 
2.7%
영 53
 
2.7%
숙 53
 
2.7%
자 46
 
2.3%
박 44
 
2.2%
경 42
 
2.1%
Other values (197) 1317
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1925
97.0%
Decimal Number 43
 
2.2%
Dash Punctuation 8
 
0.4%
Other Punctuation 6
 
0.3%
Space Separator 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 125
 
6.5%
정 99
 
5.1%
이 93
 
4.8%
순 59
 
3.1%
희 54
 
2.8%
영 53
 
2.8%
숙 53
 
2.8%
자 46
 
2.4%
박 44
 
2.3%
경 42
 
2.2%
Other values (184) 1257
65.3%
Decimal Number
ValueCountFrequency (%)
3 8
18.6%
2 6
14.0%
1 6
14.0%
5 6
14.0%
0 5
11.6%
6 3
 
7.0%
4 3
 
7.0%
7 2
 
4.7%
9 2
 
4.7%
8 2
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
* 6
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1925
97.0%
Common 60
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 125
 
6.5%
정 99
 
5.1%
이 93
 
4.8%
순 59
 
3.1%
희 54
 
2.8%
영 53
 
2.8%
숙 53
 
2.8%
자 46
 
2.4%
박 44
 
2.3%
경 42
 
2.2%
Other values (184) 1257
65.3%
Common
ValueCountFrequency (%)
3 8
13.3%
- 8
13.3%
* 6
10.0%
2 6
10.0%
1 6
10.0%
5 6
10.0%
0 5
8.3%
3
 
5.0%
6 3
 
5.0%
4 3
 
5.0%
Other values (3) 6
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1924
96.9%
ASCII 60
 
3.0%
Compat Jamo 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 125
 
6.5%
정 99
 
5.1%
이 93
 
4.8%
순 59
 
3.1%
희 54
 
2.8%
영 53
 
2.8%
숙 53
 
2.8%
자 46
 
2.4%
박 44
 
2.3%
경 42
 
2.2%
Other values (183) 1256
65.3%
ASCII
ValueCountFrequency (%)
3 8
13.3%
- 8
13.3%
* 6
10.0%
2 6
10.0%
1 6
10.0%
5 6
10.0%
0 5
8.3%
3
 
5.0%
6 3
 
5.0%
4 3
 
5.0%
Other values (3) 6
10.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%

adres
Text

Distinct642
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-04-16T13:58:05.569576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length47
Mean length29.244582
Min length3

Characters and Unicode

Total characters18892
Distinct characters259
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique640 ?
Unique (%)99.1%

Sample

1st row(47864) 부산광역시 동래구 사직북로 23-3 (사직동)
2nd row(47786) 부산광역시 동래구 충렬대로359번길 23 (안락동)
3rd row(47813) 부산광역시 동래구 명륜로98번길 41 (수안동)
4th row(47728) 부산광역시 동래구 중앙대로1367번길 36 (온천동)
5th row(46506) 부산광역시 북구 효열로219번길 42 (금곡동)
ValueCountFrequency (%)
부산광역시 430
 
12.6%
부산시 126
 
3.7%
서구 63
 
1.8%
동래구 57
 
1.7%
사상구 54
 
1.6%
영도구 50
 
1.5%
연제구 46
 
1.3%
북구 41
 
1.2%
수영구 37
 
1.1%
사하구 34
 
1.0%
Other values (1307) 2488
72.6%
2024-04-16T13:58:06.073484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2852
 
15.1%
( 921
 
4.9%
) 920
 
4.9%
4 751
 
4.0%
동 697
 
3.7%
1 686
 
3.6%
산 637
 
3.4%
부 628
 
3.3%
로 614
 
3.3%
구 597
 
3.2%
Other values (249) 9589
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9239
48.9%
Decimal Number 4720
25.0%
Space Separator 2852
 
15.1%
Open Punctuation 921
 
4.9%
Close Punctuation 920
 
4.9%
Dash Punctuation 135
 
0.7%
Other Punctuation 104
 
0.6%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 697
 
7.5%
산 637
 
6.9%
부 628
 
6.8%
로 614
 
6.6%
구 597
 
6.5%
시 586
 
6.3%
광 466
 
5.0%
역 430
 
4.7%
길 396
 
4.3%
번 380
 
4.1%
Other values (233) 3808
41.2%
Decimal Number
ValueCountFrequency (%)
4 751
15.9%
1 686
14.5%
2 570
12.1%
3 462
9.8%
7 401
8.5%
6 396
8.4%
9 390
8.3%
5 385
8.2%
8 363
7.7%
0 316
6.7%
Space Separator
ValueCountFrequency (%)
2852
100.0%
Open Punctuation
ValueCountFrequency (%)
( 921
100.0%
Close Punctuation
ValueCountFrequency (%)
) 920
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 135
100.0%
Other Punctuation
ValueCountFrequency (%)
, 104
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9652
51.1%
Hangul 9239
48.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 697
 
7.5%
산 637
 
6.9%
부 628
 
6.8%
로 614
 
6.6%
구 597
 
6.5%
시 586
 
6.3%
광 466
 
5.0%
역 430
 
4.7%
길 396
 
4.3%
번 380
 
4.1%
Other values (233) 3808
41.2%
Common
ValueCountFrequency (%)
2852
29.5%
( 921
 
9.5%
) 920
 
9.5%
4 751
 
7.8%
1 686
 
7.1%
2 570
 
5.9%
3 462
 
4.8%
7 401
 
4.2%
6 396
 
4.1%
9 390
 
4.0%
Other values (5) 1303
13.5%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9653
51.1%
Hangul 9239
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2852
29.5%
( 921
 
9.5%
) 920
 
9.5%
4 751
 
7.8%
1 686
 
7.1%
2 570
 
5.9%
3 462
 
4.8%
7 401
 
4.2%
6 396
 
4.1%
9 390
 
4.0%
Other values (6) 1304
13.5%
Hangul
ValueCountFrequency (%)
동 697
 
7.5%
산 637
 
6.9%
부 628
 
6.8%
로 614
 
6.6%
구 597
 
6.5%
시 586
 
6.3%
광 466
 
5.0%
역 430
 
4.7%
길 396
 
4.3%
번 380
 
4.1%
Other values (233) 3808
41.2%

tel
Text

MISSING 

Distinct630
Distinct (%)98.7%
Missing8
Missing (%)1.2%
Memory size5.2 KiB
2024-04-16T13:58:06.296819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.970219
Min length3

Characters and Unicode

Total characters7637
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique626 ?
Unique (%)98.1%

Sample

1st row051-502-2093
2nd row051-529-9825
3rd row051-553-2078
4th row051-557-8885
5th row051-365-3434
ValueCountFrequency (%)
음식점 4
 
0.6%
010-0000-0000 4
 
0.6%
051-756-0815 2
 
0.3%
051-255-8336 2
 
0.3%
051-247-7773 1
 
0.2%
051-231-9407 1
 
0.2%
051-781-3708 1
 
0.2%
051-628-2824 1
 
0.2%
051-623-1977 1
 
0.2%
051-759-8449 1
 
0.2%
Other values (620) 620
97.2%
2024-04-16T13:58:06.618523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1254
16.4%
5 1165
15.3%
0 1090
14.3%
1 1025
13.4%
2 565
7.4%
3 504
6.6%
4 468
 
6.1%
7 440
 
5.8%
6 424
 
5.6%
8 415
 
5.4%
Other values (4) 287
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6371
83.4%
Dash Punctuation 1254
 
16.4%
Other Letter 12
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1165
18.3%
0 1090
17.1%
1 1025
16.1%
2 565
8.9%
3 504
7.9%
4 468
7.3%
7 440
 
6.9%
6 424
 
6.7%
8 415
 
6.5%
9 275
 
4.3%
Other Letter
ValueCountFrequency (%)
음 4
33.3%
식 4
33.3%
점 4
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1254
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7625
99.8%
Hangul 12
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1254
16.4%
5 1165
15.3%
0 1090
14.3%
1 1025
13.4%
2 565
7.4%
3 504
6.6%
4 468
 
6.1%
7 440
 
5.8%
6 424
 
5.6%
8 415
 
5.4%
Hangul
ValueCountFrequency (%)
음 4
33.3%
식 4
33.3%
점 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7625
99.8%
Hangul 12
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1254
16.4%
5 1165
15.3%
0 1090
14.3%
1 1025
13.4%
2 565
7.4%
3 504
6.6%
4 468
 
6.1%
7 440
 
5.8%
6 424
 
5.6%
8 415
 
5.4%
Hangul
ValueCountFrequency (%)
음 4
33.3%
식 4
33.3%
점 4
33.3%

cn_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)1.2%
Missing4
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean603.58879
Minimum173
Maximum676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-16T13:58:06.755581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173
5-th percentile602
Q1602
median602
Q3602
95-th percentile604
Maximum676
Range503
Interquartile range (IQR)0

Descriptive statistics

Standard deviation32.337858
Coefficient of variation (CV)0.053575975
Kurtosis108.03101
Mean603.58879
Median Absolute Deviation (MAD)0
Skewness-8.394491
Sum387504
Variance1045.737
MonotonicityNot monotonic
2024-04-16T13:58:07.162454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
602 512
79.3%
603 83
 
12.8%
676 31
 
4.8%
604 12
 
1.9%
329 1
 
0.2%
343 1
 
0.2%
173 1
 
0.2%
182 1
 
0.2%
(Missing) 4
 
0.6%
ValueCountFrequency (%)
173 1
 
0.2%
182 1
 
0.2%
329 1
 
0.2%
343 1
 
0.2%
602 512
79.3%
603 83
 
12.8%
604 12
 
1.9%
676 31
 
4.8%
ValueCountFrequency (%)
676 31
 
4.8%
604 12
 
1.9%
603 83
 
12.8%
602 512
79.3%
343 1
 
0.2%
329 1
 
0.2%
182 1
 
0.2%
173 1
 
0.2%

cn
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
음식점
512 
이미용
83 
기타
 
31
목욕
 
12
<NA>
 
4
Other values (4)
 
4

Length

Max length5
Median length3
Mean length2.9458204
Min length2

Unique

Unique4 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
음식점 512
79.3%
이미용 83
 
12.8%
기타 31
 
4.8%
목욕 12
 
1.9%
<NA> 4
 
0.6%
보수동2가 1
 
0.2%
중앙동1가 1
 
0.2%
구포동 1
 
0.2%
만덕동 1
 
0.2%

Length

2024-04-16T13:58:07.277803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:58:07.390442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식점 512
79.3%
이미용 83
 
12.8%
기타 31
 
4.8%
목욕 12
 
1.9%
na 4
 
0.6%
보수동2가 1
 
0.2%
중앙동1가 1
 
0.2%
구포동 1
 
0.2%
만덕동 1
 
0.2%

locale_cd
Text

Distinct199
Distinct (%)31.0%
Missing4
Missing (%)0.6%
Memory size5.2 KiB
2024-04-16T13:58:07.696498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length3
Mean length3.1962617
Min length2

Characters and Unicode

Total characters2052
Distinct characters106
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)10.4%

Sample

1st row101
2nd row105
3rd row104
4th row109
5th row184
ValueCountFrequency (%)
59 22
 
3.1%
280 19
 
2.7%
45 16
 
2.3%
135 16
 
2.3%
271 14
 
2.0%
188 12
 
1.7%
95 12
 
1.7%
192 11
 
1.6%
216 10
 
1.4%
202 10
 
1.4%
Other values (236) 565
79.9%
2024-04-16T13:58:08.099563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 358
17.4%
1 257
12.5%
5 186
9.1%
3 183
8.9%
8 149
7.3%
0 147
7.2%
9 147
7.2%
4 131
 
6.4%
7 126
 
6.1%
6 86
 
4.2%
Other values (96) 282
13.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1770
86.3%
Other Letter 208
 
10.1%
Space Separator 66
 
3.2%
Other Punctuation 6
 
0.3%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
을 12
 
5.8%
가 10
 
4.8%
격 9
 
4.3%
정 8
 
3.8%
지 6
 
2.9%
음 6
 
2.9%
고 6
 
2.9%
있 5
 
2.4%
년 5
 
2.4%
해 5
 
2.4%
Other values (80) 136
65.4%
Decimal Number
ValueCountFrequency (%)
2 358
20.2%
1 257
14.5%
5 186
10.5%
3 183
10.3%
8 149
8.4%
0 147
8.3%
9 147
8.3%
4 131
 
7.4%
7 126
 
7.1%
6 86
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 3
50.0%
. 2
33.3%
· 1
 
16.7%
Space Separator
ValueCountFrequency (%)
66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1844
89.9%
Hangul 208
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
을 12
 
5.8%
가 10
 
4.8%
격 9
 
4.3%
정 8
 
3.8%
지 6
 
2.9%
음 6
 
2.9%
고 6
 
2.9%
있 5
 
2.4%
년 5
 
2.4%
해 5
 
2.4%
Other values (80) 136
65.4%
Common
ValueCountFrequency (%)
2 358
19.4%
1 257
13.9%
5 186
10.1%
3 183
9.9%
8 149
8.1%
0 147
8.0%
9 147
8.0%
4 131
 
7.1%
7 126
 
6.8%
6 86
 
4.7%
Other values (6) 74
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1843
89.8%
Hangul 208
 
10.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 358
19.4%
1 257
13.9%
5 186
10.1%
3 183
9.9%
8 149
8.1%
0 147
8.0%
9 147
8.0%
4 131
 
7.1%
7 126
 
6.8%
6 86
 
4.7%
Other values (5) 73
 
4.0%
Hangul
ValueCountFrequency (%)
을 12
 
5.8%
가 10
 
4.8%
격 9
 
4.3%
정 8
 
3.8%
지 6
 
2.9%
음 6
 
2.9%
고 6
 
2.9%
있 5
 
2.4%
년 5
 
2.4%
해 5
 
2.4%
Other values (80) 136
65.4%
None
ValueCountFrequency (%)
· 1
100.0%

locale
Text

Distinct197
Distinct (%)30.7%
Missing4
Missing (%)0.6%
Memory size5.2 KiB
2024-04-16T13:58:08.357069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.7274143
Min length1

Characters and Unicode

Total characters2393
Distinct characters108
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)10.0%

Sample

1st row사직2동
2nd row안락1동
3rd row수안동
4th row온천2동
5th row화명1동
ValueCountFrequency (%)
대연동 22
 
3.4%
연산동 19
 
3.0%
기장읍 16
 
2.5%
부전1동 16
 
2.5%
거제동 14
 
2.2%
감전동 12
 
1.9%
명륜동 12
 
1.9%
덕포동 11
 
1.7%
용호동 10
 
1.6%
주례동 10
 
1.6%
Other values (187) 500
77.9%
2024-04-16T13:58:08.684938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 644
26.9%
1 141
 
5.9%
2 117
 
4.9%
가 110
 
4.6%
연 64
 
2.7%
대 58
 
2.4%
3 58
 
2.4%
천 47
 
2.0%
부 46
 
1.9%
남 41
 
1.7%
Other values (98) 1067
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2034
85.0%
Decimal Number 355
 
14.8%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 644
31.7%
가 110
 
5.4%
연 64
 
3.1%
대 58
 
2.9%
천 47
 
2.3%
부 46
 
2.3%
남 41
 
2.0%
전 40
 
2.0%
산 40
 
2.0%
장 38
 
1.9%
Other values (88) 906
44.5%
Decimal Number
ValueCountFrequency (%)
1 141
39.7%
2 117
33.0%
3 58
16.3%
4 20
 
5.6%
5 13
 
3.7%
6 3
 
0.8%
9 2
 
0.6%
8 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 3
75.0%
Y 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2034
85.0%
Common 355
 
14.8%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 644
31.7%
가 110
 
5.4%
연 64
 
3.1%
대 58
 
2.9%
천 47
 
2.3%
부 46
 
2.3%
남 41
 
2.0%
전 40
 
2.0%
산 40
 
2.0%
장 38
 
1.9%
Other values (88) 906
44.5%
Common
ValueCountFrequency (%)
1 141
39.7%
2 117
33.0%
3 58
16.3%
4 20
 
5.6%
5 13
 
3.7%
6 3
 
0.8%
9 2
 
0.6%
8 1
 
0.3%
Latin
ValueCountFrequency (%)
N 3
75.0%
Y 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2034
85.0%
ASCII 359
 
15.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 644
31.7%
가 110
 
5.4%
연 64
 
3.1%
대 58
 
2.9%
천 47
 
2.3%
부 46
 
2.3%
남 41
 
2.0%
전 40
 
2.0%
산 40
 
2.0%
장 38
 
1.9%
Other values (88) 906
44.5%
ASCII
ValueCountFrequency (%)
1 141
39.3%
2 117
32.6%
3 58
16.2%
4 20
 
5.6%
5 13
 
3.6%
6 3
 
0.8%
N 3
 
0.8%
9 2
 
0.6%
Y 1
 
0.3%
8 1
 
0.3%

intrcn
Text

Distinct571
Distinct (%)88.9%
Missing4
Missing (%)0.6%
Memory size5.2 KiB
2024-04-16T13:58:08.896345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length260
Mean length86.207165
Min length7

Characters and Unicode

Total characters55345
Distinct characters688
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique562 ?
Unique (%)87.5%

Sample

1st row저렴한 가격에 맛있는 집으로 시민이 추천, 30년 전통의 집
2nd row삼대를 이어온 50여년 전통의 맛과 가격으로 승부하는 곳
3rd row전통시장 주변에 위치하여 손님 많음, 가격안정 시범거리 참여
4th row해남땅끝포크를 사용 한돈을 저렴하게 판매하여 비싸다는 한돈가격에 대한 인식변화 노력
5th row옛맛 그대로 만든 전통 추어탕맛을 고수함. 젓갈, 된장, 김치는 직접 담아 믿을 수 있음. 추어탕만 17년간 만든 주인의 노하우
ValueCountFrequency (%)
직접 117
 
1.5%
저렴한 111
 
1.4%
가격으로 65
 
0.8%
있음 54
 
0.7%
p>&nbsp;</p 49
 
0.6%
style="width 48
 
0.6%
face="굴림 43
 
0.5%
size="3 41
 
0.5%
가격을 41
 
0.5%
및 41
 
0.5%
Other values (3264) 7323
92.3%
2024-04-16T13:58:09.346421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7602
 
13.7%
p 2159
 
3.9%
< 1590
 
2.9%
> 1584
 
2.9%
s 1500
 
2.7%
t 1354
 
2.4%
n 1310
 
2.4%
" 1230
 
2.2%
e 1095
 
2.0%
b 1094
 
2.0%
Other values (678) 34827
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21021
38.0%
Lowercase Letter 15493
28.0%
Space Separator 7602
 
13.7%
Other Punctuation 4940
 
8.9%
Math Symbol 3731
 
6.7%
Decimal Number 1803
 
3.3%
Dash Punctuation 432
 
0.8%
Uppercase Letter 130
 
0.2%
Connector Punctuation 102
 
0.2%
Open Punctuation 41
 
0.1%
Other values (2) 50
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
하 699
 
3.3%
가 593
 
2.8%
이 593
 
2.8%
고 543
 
2.6%
한 486
 
2.3%
로 453
 
2.2%
을 321
 
1.5%
으 311
 
1.5%
에 293
 
1.4%
인 289
 
1.4%
Other values (595) 16440
78.2%
Lowercase Letter
ValueCountFrequency (%)
p 2159
13.9%
s 1500
 
9.7%
t 1354
 
8.7%
n 1310
 
8.5%
e 1095
 
7.1%
b 1094
 
7.1%
o 846
 
5.5%
a 774
 
5.0%
r 725
 
4.7%
l 677
 
4.4%
Other values (16) 3959
25.6%
Uppercase Letter
ValueCountFrequency (%)
E 17
13.1%
S 16
12.3%
N 13
10.0%
U 11
 
8.5%
B 10
 
7.7%
I 7
 
5.4%
P 7
 
5.4%
M 7
 
5.4%
A 7
 
5.4%
T 6
 
4.6%
Other values (9) 29
22.3%
Other Punctuation
ValueCountFrequency (%)
" 1230
24.9%
; 1076
21.8%
/ 692
14.0%
& 688
13.9%
: 477
 
9.7%
, 428
 
8.7%
. 310
 
6.3%
% 15
 
0.3%
! 10
 
0.2%
* 6
 
0.1%
Other values (2) 8
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 448
24.8%
3 254
14.1%
1 245
13.6%
5 196
10.9%
2 188
10.4%
4 109
 
6.0%
8 100
 
5.5%
7 95
 
5.3%
9 86
 
4.8%
6 82
 
4.5%
Math Symbol
ValueCountFrequency (%)
< 1590
42.6%
> 1584
42.5%
= 552
 
14.8%
~ 4
 
0.1%
+ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 27
65.9%
{ 11
26.8%
[ 3
 
7.3%
Close Punctuation
ValueCountFrequency (%)
) 27
77.1%
} 5
 
14.3%
] 3
 
8.6%
Format
ValueCountFrequency (%)
 8
53.3%
​ 7
46.7%
Space Separator
ValueCountFrequency (%)
7602
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 432
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21021
38.0%
Common 18701
33.8%
Latin 15623
28.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
하 699
 
3.3%
가 593
 
2.8%
이 593
 
2.8%
고 543
 
2.6%
한 486
 
2.3%
로 453
 
2.2%
을 321
 
1.5%
으 311
 
1.5%
에 293
 
1.4%
인 289
 
1.4%
Other values (595) 16440
78.2%
Latin
ValueCountFrequency (%)
p 2159
13.8%
s 1500
 
9.6%
t 1354
 
8.7%
n 1310
 
8.4%
e 1095
 
7.0%
b 1094
 
7.0%
o 846
 
5.4%
a 774
 
5.0%
r 725
 
4.6%
l 677
 
4.3%
Other values (35) 4089
26.2%
Common
ValueCountFrequency (%)
7602
40.7%
< 1590
 
8.5%
> 1584
 
8.5%
" 1230
 
6.6%
; 1076
 
5.8%
/ 692
 
3.7%
& 688
 
3.7%
= 552
 
3.0%
: 477
 
2.6%
0 448
 
2.4%
Other values (28) 2762
 
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34307
62.0%
Hangul 21021
38.0%
None 10
 
< 0.1%
Punctuation 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7602
22.2%
p 2159
 
6.3%
< 1590
 
4.6%
> 1584
 
4.6%
s 1500
 
4.4%
t 1354
 
3.9%
n 1310
 
3.8%
" 1230
 
3.6%
e 1095
 
3.2%
b 1094
 
3.2%
Other values (70) 13789
40.2%
Hangul
ValueCountFrequency (%)
하 699
 
3.3%
가 593
 
2.8%
이 593
 
2.8%
고 543
 
2.6%
한 486
 
2.3%
로 453
 
2.2%
을 321
 
1.5%
으 311
 
1.5%
에 293
 
1.4%
인 289
 
1.4%
Other values (595) 16440
78.2%
None
ValueCountFrequency (%)
 8
80.0%
· 2
 
20.0%
Punctuation
ValueCountFrequency (%)
​ 7
100.0%

parkng_at
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
N
432 
Y
206 
<NA>
 
4
20130221024508
 
4

Length

Max length14
Median length1
Mean length1.0990712
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowN
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 432
66.9%
Y 206
31.9%
<NA> 4
 
0.6%
20130221024508 4
 
0.6%

Length

2024-04-16T13:58:09.526627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:58:09.651903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 432
66.9%
y 206
31.9%
na 4
 
0.6%
20130221024508 4
 
0.6%

bsn_time
Text

Distinct285
Distinct (%)44.4%
Missing4
Missing (%)0.6%
Memory size5.2 KiB
2024-04-16T13:58:09.932601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length11
Mean length13.023364
Min length2

Characters and Unicode

Total characters8361
Distinct characters98
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203 ?
Unique (%)31.6%

Sample

1st row10:00~22:00
2nd row09:00~21:00
3rd row11:00~22:00
4th row11:00~21:00
5th row11:00~21:00
ValueCountFrequency (%)
67
 
6.6%
휴무 49
 
4.8%
pm 47
 
4.6%
am 43
 
4.2%
10:00~22:00 33
 
3.2%
09:00~21:00 26
 
2.5%
11:00~21:00 26
 
2.5%
10:00~20:00 26
 
2.5%
11:00~22:00 25
 
2.4%
10:00~21:00 25
 
2.4%
Other values (271) 655
64.1%
2024-04-16T13:58:10.522330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2785
33.3%
: 1225
14.7%
1 834
 
10.0%
2 669
 
8.0%
~ 526
 
6.3%
472
 
5.6%
3 236
 
2.8%
9 192
 
2.3%
m 114
 
1.4%
- 103
 
1.2%
Other values (88) 1205
14.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4935
59.0%
Other Punctuation 1303
 
15.6%
Math Symbol 542
 
6.5%
Other Letter 515
 
6.2%
Space Separator 472
 
5.6%
Lowercase Letter 346
 
4.1%
Dash Punctuation 103
 
1.2%
Uppercase Letter 68
 
0.8%
Open Punctuation 38
 
0.5%
Close Punctuation 38
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 87
16.9%
휴 60
11.7%
무 60
11.7%
요 56
10.9%
시 47
9.1%
매 34
 
6.6%
주 32
 
6.2%
째 23
 
4.5%
화 20
 
3.9%
간 15
 
2.9%
Other values (35) 81
15.7%
Lowercase Letter
ValueCountFrequency (%)
m 114
32.9%
p 67
19.4%
a 59
17.1%
e 20
 
5.8%
o 12
 
3.5%
r 9
 
2.6%
c 8
 
2.3%
g 8
 
2.3%
f 8
 
2.3%
i 8
 
2.3%
Other values (8) 33
 
9.5%
Decimal Number
ValueCountFrequency (%)
0 2785
56.4%
1 834
 
16.9%
2 669
 
13.6%
3 236
 
4.8%
9 192
 
3.9%
8 76
 
1.5%
4 54
 
1.1%
7 49
 
1.0%
5 23
 
0.5%
6 17
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
I 16
23.5%
N 12
17.6%
G 8
11.8%
M 8
11.8%
T 4
 
5.9%
D 4
 
5.9%
K 4
 
5.9%
A 4
 
5.9%
L 4
 
5.9%
U 4
 
5.9%
Other Punctuation
ValueCountFrequency (%)
: 1225
94.0%
, 38
 
2.9%
; 12
 
0.9%
& 12
 
0.9%
/ 10
 
0.8%
? 4
 
0.3%
' 1
 
0.1%
· 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 526
97.0%
= 16
 
3.0%
Space Separator
ValueCountFrequency (%)
472
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7432
88.9%
Hangul 515
 
6.2%
Latin 414
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 87
16.9%
휴 60
11.7%
무 60
11.7%
요 56
10.9%
시 47
9.1%
매 34
 
6.6%
주 32
 
6.2%
째 23
 
4.5%
화 20
 
3.9%
간 15
 
2.9%
Other values (35) 81
15.7%
Latin
ValueCountFrequency (%)
m 114
27.5%
p 67
16.2%
a 59
14.3%
e 20
 
4.8%
I 16
 
3.9%
N 12
 
2.9%
o 12
 
2.9%
r 9
 
2.2%
G 8
 
1.9%
M 8
 
1.9%
Other values (18) 89
21.5%
Common
ValueCountFrequency (%)
0 2785
37.5%
: 1225
16.5%
1 834
 
11.2%
2 669
 
9.0%
~ 526
 
7.1%
472
 
6.4%
3 236
 
3.2%
9 192
 
2.6%
- 103
 
1.4%
8 76
 
1.0%
Other values (15) 314
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7845
93.8%
Hangul 515
 
6.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2785
35.5%
: 1225
15.6%
1 834
 
10.6%
2 669
 
8.5%
~ 526
 
6.7%
472
 
6.0%
3 236
 
3.0%
9 192
 
2.4%
m 114
 
1.5%
- 103
 
1.3%
Other values (42) 689
 
8.8%
Hangul
ValueCountFrequency (%)
일 87
16.9%
휴 60
11.7%
무 60
11.7%
요 56
10.9%
시 47
9.1%
매 34
 
6.6%
주 32
 
6.2%
째 23
 
4.5%
화 20
 
3.9%
간 15
 
2.9%
Other values (35) 81
15.7%
None
ValueCountFrequency (%)
· 1
100.0%

creat_dt
Text

Distinct501
Distinct (%)78.0%
Missing4
Missing (%)0.6%
Memory size5.2 KiB
2024-04-16T13:58:10.869387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length13.990654
Min length10

Characters and Unicode

Total characters8982
Distinct characters41
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)77.9%

Sample

1st row20140427025228
2nd row20140427023912
3rd row20140427023147
4th row20140427022435
5th row20140925114144
ValueCountFrequency (%)
20130221024508 142
 
22.1%
20190422034418 1
 
0.2%
20140427025228 1
 
0.2%
20210323012642 1
 
0.2%
20210323013250 1
 
0.2%
20210323013640 1
 
0.2%
20210323013945 1
 
0.2%
20210323014311 1
 
0.2%
20210402102838 1
 
0.2%
20210402103717 1
 
0.2%
Other values (491) 491
76.5%
2024-04-16T13:58:11.351741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2444
27.2%
2 1731
19.3%
1 1436
16.0%
3 740
 
8.2%
4 684
 
7.6%
5 655
 
7.3%
8 362
 
4.0%
7 299
 
3.3%
9 293
 
3.3%
6 289
 
3.2%
Other values (31) 49
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8933
99.5%
Other Letter 30
 
0.3%
Lowercase Letter 12
 
0.1%
Other Punctuation 4
 
< 0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 2
 
6.7%
전 2
 
6.7%
국 2
 
6.7%
내 2
 
6.7%
포 1
 
3.3%
지 1
 
3.3%
돼 1
 
3.3%
통 1
 
3.3%
주 1
 
3.3%
경 1
 
3.3%
Other values (16) 16
53.3%
Decimal Number
ValueCountFrequency (%)
0 2444
27.4%
2 1731
19.4%
1 1436
16.1%
3 740
 
8.3%
4 684
 
7.7%
5 655
 
7.3%
8 362
 
4.1%
7 299
 
3.3%
9 293
 
3.3%
6 289
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
p 4
33.3%
j 4
33.3%
g 4
33.3%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8940
99.5%
Hangul 30
 
0.3%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 2
 
6.7%
전 2
 
6.7%
국 2
 
6.7%
내 2
 
6.7%
포 1
 
3.3%
지 1
 
3.3%
돼 1
 
3.3%
통 1
 
3.3%
주 1
 
3.3%
경 1
 
3.3%
Other values (16) 16
53.3%
Common
ValueCountFrequency (%)
0 2444
27.3%
2 1731
19.4%
1 1436
16.1%
3 740
 
8.3%
4 684
 
7.7%
5 655
 
7.3%
8 362
 
4.0%
7 299
 
3.3%
9 293
 
3.3%
6 289
 
3.2%
Other values (2) 7
 
0.1%
Latin
ValueCountFrequency (%)
p 4
33.3%
j 4
33.3%
g 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8952
99.7%
Hangul 30
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2444
27.3%
2 1731
19.3%
1 1436
16.0%
3 740
 
8.3%
4 684
 
7.6%
5 655
 
7.3%
8 362
 
4.0%
7 299
 
3.3%
9 293
 
3.3%
6 289
 
3.2%
Other values (5) 19
 
0.2%
Hangul
ValueCountFrequency (%)
부 2
 
6.7%
전 2
 
6.7%
국 2
 
6.7%
내 2
 
6.7%
포 1
 
3.3%
지 1
 
3.3%
돼 1
 
3.3%
통 1
 
3.3%
주 1
 
3.3%
경 1
 
3.3%
Other values (16) 16
53.3%

img_file1
Text

MISSING 

Distinct605
Distinct (%)100.0%
Missing41
Missing (%)6.3%
Memory size5.2 KiB
2024-04-16T13:58:11.672602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length76
Mean length75.704132
Min length73

Characters and Unicode

Total characters45801
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique605 ?
Unique (%)100.0%

Sample

1st row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2805&amp;fileTy=IMG&amp;fileNo=3
2nd row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2798&amp;fileTy=IMG&amp;fileNo=3
3rd row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2796&amp;fileTy=IMG&amp;fileNo=3
4th row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2790&amp;fileTy=IMG&amp;fileNo=3
5th row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2976&amp;fileTy=IMG&amp;fileNo=3
ValueCountFrequency (%)
comm/getimage?srvcid=mulgakind&amp;upperno=2237&amp;filety=img&amp;fileno=2 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4629&amp;filety=img&amp;fileno=1 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4637&amp;filety=img&amp;fileno=1 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4340&amp;filety=img&amp;fileno=1 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4339&amp;filety=img&amp;fileno=1 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4338&amp;filety=img&amp;fileno=1 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4643&amp;filety=img&amp;fileno=1 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4640&amp;filety=img&amp;fileno=1 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4639&amp;filety=img&amp;fileno=1 1
 
0.2%
comm/getimage?srvcid=mulgakind&amp;upperno=4638&amp;filety=img&amp;fileno=1 1
 
0.2%
Other values (595) 595
98.3%
2024-04-16T13:58:12.123935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 3630
 
7.9%
e 3025
 
6.6%
p 3025
 
6.6%
I 2420
 
5.3%
a 2420
 
5.3%
= 2420
 
5.3%
N 1815
 
4.0%
o 1815
 
4.0%
; 1815
 
4.0%
& 1815
 
4.0%
Other values (32) 21601
47.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24805
54.2%
Uppercase Letter 10285
22.5%
Other Punctuation 5445
 
11.9%
Decimal Number 2846
 
6.2%
Math Symbol 2420
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 3630
14.6%
e 3025
12.2%
p 3025
12.2%
a 2420
9.8%
o 1815
 
7.3%
l 1210
 
4.9%
i 1210
 
4.9%
f 1210
 
4.9%
c 1210
 
4.9%
g 1210
 
4.9%
Other values (7) 4840
19.5%
Uppercase Letter
ValueCountFrequency (%)
I 2420
23.5%
N 1815
17.6%
G 1210
11.8%
M 1210
11.8%
U 605
 
5.9%
L 605
 
5.9%
T 605
 
5.9%
D 605
 
5.9%
K 605
 
5.9%
A 605
 
5.9%
Decimal Number
ValueCountFrequency (%)
4 593
20.8%
1 518
18.2%
2 460
16.2%
3 349
12.3%
5 222
 
7.8%
6 200
 
7.0%
7 129
 
4.5%
9 127
 
4.5%
8 126
 
4.4%
0 122
 
4.3%
Other Punctuation
ValueCountFrequency (%)
; 1815
33.3%
& 1815
33.3%
/ 1210
22.2%
? 605
 
11.1%
Math Symbol
ValueCountFrequency (%)
= 2420
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35090
76.6%
Common 10711
 
23.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 3630
 
10.3%
e 3025
 
8.6%
p 3025
 
8.6%
I 2420
 
6.9%
a 2420
 
6.9%
N 1815
 
5.2%
o 1815
 
5.2%
G 1210
 
3.4%
l 1210
 
3.4%
i 1210
 
3.4%
Other values (17) 13310
37.9%
Common
ValueCountFrequency (%)
= 2420
22.6%
; 1815
16.9%
& 1815
16.9%
/ 1210
11.3%
? 605
 
5.6%
4 593
 
5.5%
1 518
 
4.8%
2 460
 
4.3%
3 349
 
3.3%
5 222
 
2.1%
Other values (5) 704
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45801
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 3630
 
7.9%
e 3025
 
6.6%
p 3025
 
6.6%
I 2420
 
5.3%
a 2420
 
5.3%
= 2420
 
5.3%
N 1815
 
4.0%
o 1815
 
4.0%
; 1815
 
4.0%
& 1815
 
4.0%
Other values (32) 21601
47.2%

img_name1
Text

MISSING 

Distinct600
Distinct (%)99.2%
Missing41
Missing (%)6.3%
Memory size5.2 KiB
2024-04-16T13:58:12.447136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length24
Mean length12.069421
Min length5

Characters and Unicode

Total characters7302
Distinct characters417
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

Unique597 ?
Unique (%)98.7%

Sample

1st row서울칼국수.jpg
2nd row밀양삼대국밥.jpg
3rd row무진장횟집.jpg
4th row맛진고기.jpg
5th row20190528_170721.jpg
ValueCountFrequency (%)
4).jpg 8
 
1.2%
3).jpg 8
 
1.2%
1).jpg 8
 
1.2%
외부.jpg 7
 
1.0%
20200228_외부사진.jpg 4
 
0.6%
2.jpg 4
 
0.6%
내부.jpg 4
 
0.6%
내부전경.jpg 3
 
0.4%
간판.jpg 3
 
0.4%
2).jpg 3
 
0.4%
Other values (632) 638
92.5%
2024-04-16T13:58:12.895715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 629
 
8.6%
p 519
 
7.1%
g 515
 
7.1%
j 477
 
6.5%
2 305
 
4.2%
1 304
 
4.2%
0 266
 
3.6%
_ 155
 
2.1%
5 127
 
1.7%
부 121
 
1.7%
Other values (407) 3884
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2827
38.7%
Lowercase Letter 1606
22.0%
Decimal Number 1477
20.2%
Other Punctuation 633
 
8.7%
Uppercase Letter 318
 
4.4%
Connector Punctuation 155
 
2.1%
Space Separator 85
 
1.2%
Close Punctuation 81
 
1.1%
Open Punctuation 81
 
1.1%
Dash Punctuation 38
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 121
 
4.3%
내 89
 
3.1%
국 69
 
2.4%
식 58
 
2.1%
수 55
 
1.9%
가 54
 
1.9%
당 49
 
1.7%
밥 44
 
1.6%
미 42
 
1.5%
어 41
 
1.5%
Other values (358) 2205
78.0%
Lowercase Letter
ValueCountFrequency (%)
p 519
32.3%
g 515
32.1%
j 477
29.7%
n 32
 
2.0%
b 15
 
0.9%
m 15
 
0.9%
i 9
 
0.6%
f 7
 
0.4%
e 5
 
0.3%
a 3
 
0.2%
Other values (7) 9
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
G 97
30.5%
J 82
25.8%
P 82
25.8%
I 15
 
4.7%
M 15
 
4.7%
C 6
 
1.9%
D 5
 
1.6%
N 5
 
1.6%
S 4
 
1.3%
B 4
 
1.3%
Other values (2) 3
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 305
20.6%
1 304
20.6%
0 266
18.0%
5 127
8.6%
4 116
 
7.9%
3 100
 
6.8%
8 80
 
5.4%
6 73
 
4.9%
7 58
 
3.9%
9 48
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 629
99.4%
% 2
 
0.3%
& 1
 
0.2%
？ 1
 
0.2%
Connector Punctuation
ValueCountFrequency (%)
_ 155
100.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Modifier Symbol
ValueCountFrequency (%)
˸ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2827
38.7%
Common 2551
34.9%
Latin 1924
26.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 121
 
4.3%
내 89
 
3.1%
국 69
 
2.4%
식 58
 
2.1%
수 55
 
1.9%
가 54
 
1.9%
당 49
 
1.7%
밥 44
 
1.6%
미 42
 
1.5%
어 41
 
1.5%
Other values (358) 2205
78.0%
Latin
ValueCountFrequency (%)
p 519
27.0%
g 515
26.8%
j 477
24.8%
G 97
 
5.0%
J 82
 
4.3%
P 82
 
4.3%
n 32
 
1.7%
I 15
 
0.8%
b 15
 
0.8%
m 15
 
0.8%
Other values (19) 75
 
3.9%
Common
ValueCountFrequency (%)
. 629
24.7%
2 305
12.0%
1 304
11.9%
0 266
10.4%
_ 155
 
6.1%
5 127
 
5.0%
4 116
 
4.5%
3 100
 
3.9%
85
 
3.3%
) 81
 
3.2%
Other values (10) 383
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4473
61.3%
Hangul 2827
38.7%
Modifier Letters 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 629
14.1%
p 519
11.6%
g 515
11.5%
j 477
10.7%
2 305
 
6.8%
1 304
 
6.8%
0 266
 
5.9%
_ 155
 
3.5%
5 127
 
2.8%
4 116
 
2.6%
Other values (37) 1060
23.7%
Hangul
ValueCountFrequency (%)
부 121
 
4.3%
내 89
 
3.1%
국 69
 
2.4%
식 58
 
2.1%
수 55
 
1.9%
가 54
 
1.9%
당 49
 
1.7%
밥 44
 
1.6%
미 42
 
1.5%
어 41
 
1.5%
Other values (358) 2205
78.0%
Modifier Letters
ValueCountFrequency (%)
˸ 1
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

img_file2
Text

MISSING 

Distinct331
Distinct (%)100.0%
Missing315
Missing (%)48.8%
Memory size5.2 KiB
2024-04-16T13:58:13.151124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length76
Mean length74.65861
Min length3

Characters and Unicode

Total characters24712
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique331 ?
Unique (%)100.0%

Sample

1st row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2976&amp;fileTy=IMG&amp;fileNo=4
2nd row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2514&amp;fileTy=IMG&amp;fileNo=2
3rd row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2497&amp;fileTy=IMG&amp;fileNo=2
4th row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2355&amp;fileTy=IMG&amp;fileNo=1
5th row/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2327&amp;fileTy=IMG&amp;fileNo=1
ValueCountFrequency (%)
comm/getimage?srvcid=mulgakind&amp;upperno=2199&amp;filety=img&amp;fileno=1 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4288&amp;filety=img&amp;fileno=2 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4290&amp;filety=img&amp;fileno=1 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4292&amp;filety=img&amp;fileno=1 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4326&amp;filety=img&amp;fileno=2 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4327&amp;filety=img&amp;fileno=2 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4320&amp;filety=img&amp;fileno=2 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4321&amp;filety=img&amp;fileno=2 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4323&amp;filety=img&amp;fileno=2 1
 
0.3%
comm/getimage?srvcid=mulgakind&amp;upperno=4324&amp;filety=img&amp;fileno=2 1
 
0.3%
Other values (321) 321
97.0%
2024-04-16T13:58:13.541226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 1962
 
7.9%
e 1635
 
6.6%
p 1635
 
6.6%
I 1308
 
5.3%
a 1308
 
5.3%
= 1308
 
5.3%
N 981
 
4.0%
o 981
 
4.0%
; 981
 
4.0%
& 981
 
4.0%
Other values (32) 11632
47.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13407
54.3%
Uppercase Letter 5559
22.5%
Other Punctuation 2943
 
11.9%
Decimal Number 1495
 
6.0%
Math Symbol 1308
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 1962
14.6%
e 1635
12.2%
p 1635
12.2%
a 1308
9.8%
o 981
 
7.3%
l 654
 
4.9%
i 654
 
4.9%
f 654
 
4.9%
c 654
 
4.9%
r 654
 
4.9%
Other values (7) 2616
19.5%
Uppercase Letter
ValueCountFrequency (%)
I 1308
23.5%
N 981
17.6%
G 654
11.8%
M 654
11.8%
A 327
 
5.9%
K 327
 
5.9%
D 327
 
5.9%
T 327
 
5.9%
L 327
 
5.9%
U 327
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 313
20.9%
2 274
18.3%
4 273
18.3%
3 162
10.8%
5 117
 
7.8%
6 89
 
6.0%
8 73
 
4.9%
0 68
 
4.5%
7 65
 
4.3%
9 61
 
4.1%
Other Punctuation
ValueCountFrequency (%)
; 981
33.3%
& 981
33.3%
/ 654
22.2%
? 327
 
11.1%
Math Symbol
ValueCountFrequency (%)
= 1308
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18966
76.7%
Common 5746
 
23.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 1962
 
10.3%
e 1635
 
8.6%
p 1635
 
8.6%
I 1308
 
6.9%
a 1308
 
6.9%
N 981
 
5.2%
o 981
 
5.2%
G 654
 
3.4%
l 654
 
3.4%
i 654
 
3.4%
Other values (17) 7194
37.9%
Common
ValueCountFrequency (%)
= 1308
22.8%
; 981
17.1%
& 981
17.1%
/ 654
11.4%
? 327
 
5.7%
1 313
 
5.4%
2 274
 
4.8%
4 273
 
4.8%
3 162
 
2.8%
5 117
 
2.0%
Other values (5) 356
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 1962
 
7.9%
e 1635
 
6.6%
p 1635
 
6.6%
I 1308
 
5.3%
a 1308
 
5.3%
= 1308
 
5.3%
N 981
 
4.0%
o 981
 
4.0%
; 981
 
4.0%
& 981
 
4.0%
Other values (32) 11632
47.1%

img_name2
Text

MISSING 

Distinct328
Distinct (%)99.1%
Missing315
Missing (%)48.8%
Memory size5.2 KiB
2024-04-16T13:58:13.725682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length13.018127
Min length6

Characters and Unicode

Total characters4309
Distinct characters343
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique327 ?
Unique (%)98.8%

Sample

1st row20190528_170557.jpg
2nd row성일손칼국수2.jpg
3rd row풍성한칼국수2.jpg
4th row하나로한우명품숯불갈비(외부).jpg
5th row선우정짜장짬뽕과닭한마리1.jpg
ValueCountFrequency (%)
내부.jpg 7
 
1.8%
메뉴.jpg 6
 
1.5%
1.jpg 5
 
1.3%
2021-05-01 4
 
1.0%
05:29:03 4
 
1.0%
외부.jpg 4
 
1.0%
외부전경.jpg 3
 
0.8%
2).jpg 3
 
0.8%
가격표.jpg 2
 
0.5%
3).jpg 2
 
0.5%
Other values (346) 348
89.7%
2024-04-16T13:58:14.028889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 353
 
8.2%
g 286
 
6.6%
p 282
 
6.5%
j 280
 
6.5%
1 233
 
5.4%
2 179
 
4.2%
0 174
 
4.0%
_ 102
 
2.4%
부 100
 
2.3%
5 89
 
2.1%
Other values (333) 2231
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1654
38.4%
Decimal Number 966
22.4%
Lowercase Letter 875
20.3%
Other Punctuation 361
 
8.4%
Uppercase Letter 173
 
4.0%
Connector Punctuation 102
 
2.4%
Space Separator 57
 
1.3%
Open Punctuation 48
 
1.1%
Close Punctuation 47
 
1.1%
Dash Punctuation 26
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 100
 
6.0%
외 79
 
4.8%
국 39
 
2.4%
식 37
 
2.2%
가 32
 
1.9%
당 30
 
1.8%
수 29
 
1.8%
미 27
 
1.6%
어 27
 
1.6%
리 25
 
1.5%
Other values (292) 1229
74.3%
Lowercase Letter
ValueCountFrequency (%)
g 286
32.7%
p 282
32.2%
j 280
32.0%
e 5
 
0.6%
f 5
 
0.6%
n 4
 
0.5%
i 3
 
0.3%
s 3
 
0.3%
a 2
 
0.2%
d 1
 
0.1%
Other values (4) 4
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 233
24.1%
2 179
18.5%
0 174
18.0%
5 89
 
9.2%
3 65
 
6.7%
4 60
 
6.2%
6 52
 
5.4%
7 39
 
4.0%
8 38
 
3.9%
9 37
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
G 53
30.6%
J 46
26.6%
P 46
26.6%
M 8
 
4.6%
I 7
 
4.0%
D 3
 
1.7%
S 3
 
1.7%
N 3
 
1.7%
C 3
 
1.7%
A 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 353
97.8%
: 8
 
2.2%
Connector Punctuation
ValueCountFrequency (%)
_ 102
100.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1654
38.4%
Common 1607
37.3%
Latin 1048
24.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 100
 
6.0%
외 79
 
4.8%
국 39
 
2.4%
식 37
 
2.2%
가 32
 
1.9%
당 30
 
1.8%
수 29
 
1.8%
미 27
 
1.6%
어 27
 
1.6%
리 25
 
1.5%
Other values (292) 1229
74.3%
Latin
ValueCountFrequency (%)
g 286
27.3%
p 282
26.9%
j 280
26.7%
G 53
 
5.1%
J 46
 
4.4%
P 46
 
4.4%
M 8
 
0.8%
I 7
 
0.7%
e 5
 
0.5%
f 5
 
0.5%
Other values (14) 30
 
2.9%
Common
ValueCountFrequency (%)
. 353
22.0%
1 233
14.5%
2 179
11.1%
0 174
10.8%
_ 102
 
6.3%
5 89
 
5.5%
3 65
 
4.0%
4 60
 
3.7%
57
 
3.5%
6 52
 
3.2%
Other values (7) 243
15.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2655
61.6%
Hangul 1654
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 353
13.3%
g 286
10.8%
p 282
10.6%
j 280
10.5%
1 233
 
8.8%
2 179
 
6.7%
0 174
 
6.6%
_ 102
 
3.8%
5 89
 
3.4%
3 65
 
2.4%
Other values (31) 612
23.1%
Hangul
ValueCountFrequency (%)
부 100
 
6.0%
외 79
 
4.8%
국 39
 
2.4%
식 37
 
2.2%
가 32
 
1.9%
당 30
 
1.8%
수 29
 
1.8%
미 27
 
1.6%
어 27
 
1.6%
리 25
 
1.5%
Other values (292) 1229
74.3%

idx
Real number (ℝ)

MISSING 

Distinct638
Distinct (%)100.0%
Missing8
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean3153.6411
Minimum5
Maximum4673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-16T13:58:14.163168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile89.85
Q11711.75
median4282.5
Q34500.75
95-th percentile4639.15
Maximum4673
Range4668
Interquartile range (IQR)2789

Descriptive statistics

Standard deviation1763.9775
Coefficient of variation (CV)0.5593463
Kurtosis-1.0234935
Mean3153.6411
Median Absolute Deviation (MAD)332
Skewness-0.84716096
Sum2012023
Variance3111616.5
MonotonicityNot monotonic
2024-04-16T13:58:14.288515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4633 1
 
0.2%
4640 1
 
0.2%
4639 1
 
0.2%
4638 1
 
0.2%
4637 1
 
0.2%
4636 1
 
0.2%
4635 1
 
0.2%
4634 1
 
0.2%
4632 1
 
0.2%
4338 1
 
0.2%
Other values (628) 628
97.2%
(Missing) 8
 
1.2%
ValueCountFrequency (%)
5 1
0.2%
6 1
0.2%
11 1
0.2%
22 1
0.2%
25 1
0.2%
29 1
0.2%
30 1
0.2%
31 1
0.2%
33 1
0.2%
35 1
0.2%
ValueCountFrequency (%)
4673 1
0.2%
4672 1
0.2%
4671 1
0.2%
4670 1
0.2%
4669 1
0.2%
4668 1
0.2%
4667 1
0.2%
4666 1
0.2%
4665 1
0.2%
4664 1
0.2%

last_load_dttm
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing8
Missing (%)1.2%
Memory size5.2 KiB
Minimum2021-05-01 05:29:03
Maximum2021-05-01 05:29:03
2024-04-16T13:58:14.379918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T13:58:14.460976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-16T13:58:03.117459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T13:58:02.934906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T13:58:03.199958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T13:58:03.021188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-16T13:58:14.521092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
cn_cdcnparkng_atidx
cn_cd1.0001.0000.6790.168
cn1.0001.0000.7940.160
parkng_at0.6790.7941.0000.068
idx0.1680.1600.0681.000
2024-04-16T13:58:14.602340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
parkng_atcn
parkng_at1.0000.713
cn0.7131.000
2024-04-16T13:58:14.677663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
cn_cdidxcnparkng_at
cn_cd1.0000.1700.9970.710
idx0.1701.0000.1020.067
cn0.9970.1021.0000.713
parkng_at0.7100.0670.7131.000

Missing values

2024-04-16T13:58:03.317757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-16T13:58:03.521402image/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.
2024-04-16T13:58:03.750350image/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

sjm_nmadrestelcn_cdcnlocale_cdlocaleintrcnparkng_atbsn_timecreat_dtimg_file1img_name1img_file2img_name2idxlast_load_dttm
0서울칼국수김경애(47864) 부산광역시 동래구 사직북로 23-3 (사직동)051-502-2093602음식점101사직2동저렴한 가격에 맛있는 집으로 시민이 추천, 30년 전통의 집Y10:00~22:0020140427025228/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2805&amp;fileTy=IMG&amp;fileNo=3서울칼국수.jpg<NA><NA>28052021-05-01 05:29:03
1밀양삼대국밥박민호(47786) 부산광역시 동래구 충렬대로359번길 23 (안락동)051-529-9825602음식점105안락1동삼대를 이어온 50여년 전통의 맛과 가격으로 승부하는 곳Y09:00~21:0020140427023912/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2798&amp;fileTy=IMG&amp;fileNo=3밀양삼대국밥.jpg<NA><NA>27982021-05-01 05:29:03
2무진장횟집옥둘선(47813) 부산광역시 동래구 명륜로98번길 41 (수안동)051-553-2078602음식점104수안동전통시장 주변에 위치하여 손님 많음, 가격안정 시범거리 참여N11:00~22:0020140427023147/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2796&amp;fileTy=IMG&amp;fileNo=3무진장횟집.jpg<NA><NA>27962021-05-01 05:29:03
3맛진고기이경희(47728) 부산광역시 동래구 중앙대로1367번길 36 (온천동)051-557-8885602음식점109온천2동해남땅끝포크를 사용 한돈을 저렴하게 판매하여 비싸다는 한돈가격에 대한 인식변화 노력Y11:00~21:0020140427022435/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2790&amp;fileTy=IMG&amp;fileNo=3맛진고기.jpg<NA><NA>27902021-05-01 05:29:03
4밀양가마솥추어탕유인숙(46506) 부산광역시 북구 효열로219번길 42 (금곡동)051-365-3434602음식점184화명1동옛맛 그대로 만든 전통 추어탕맛을 고수함. 젓갈, 된장, 김치는 직접 담아 믿을 수 있음. 추어탕만 17년간 만든 주인의 노하우Y11:00~21:0020140925114144<NA><NA><NA><NA>29802021-05-01 05:29:03
5면통장이은옥만덕2로051-342-2223602음식점182만덕동깨끗하고 위생적인 내부시설과 진한 멸치 육수가 진국임. 구매원가 절감 노력 및 좋은 식재료를 사용하여 진한 멸치국물을 매일 제조함.Y24시간20140925113855/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2976&amp;fileTy=IMG&amp;fileNo=320190528_170721.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2976&amp;fileTy=IMG&amp;fileNo=420190528_170557.jpg29762021-05-01 05:29:03
6나래투미용실이성희(47775) 부산광역시 동래구 명장로64번길 38 (명장동)051-522-4871603이미용96명장1동학교 주변에 있는 커트 전문점N09:00~21:0020140427120319/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2718&amp;fileTy=IMG&amp;fileNo=3나래투미용실.jpg<NA><NA>27182021-05-01 05:29:03
7만점갈비김만호(47814) 부산광역시 동래구 명륜로98번길 18 (수안동)051-558-2240602음식점104수안동식재료 직접 구매 박리다매 운영Y12:00~22:0020140425054734/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2680&amp;fileTy=IMG&amp;fileNo=3만점숯불갈비.JPG<NA><NA>26802021-05-01 05:29:03
8성일손칼국수김종남부산광역시 서구 해안새벽시장길8051-244-1547602음식점245충무동1가부부가 30년째 운영. 새벽시장에 위치하여 시장의 역사만큼이나 가게의 역사도 함께 묻어있는 가게이다. 손수 면을 만드는 과정을 볼 수 있고 시장 손님들의 주머니 사정을 감안하여 가격을 올리지 않고 예전과 변함없는 맛을 자랑하는 가게임.N07:00~20:0020140425112030/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2514&amp;fileTy=IMG&amp;fileNo=3착한가격업소-성일손칼국수 (4).jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2514&amp;fileTy=IMG&amp;fileNo=2성일손칼국수2.jpg25142021-05-01 05:29:03
9풍성한칼국수임소영부산광역시 서구 충무시장길59-1051-243-5508602음식점247충무동3가생면을 사용하고 있고 직접 우려낸 육수로 칼국수 국물맛이 좋음.&nbsp; 친절하고 깨끗함. 사장님 추천메뉴는 철판비빔밥이라고 하신다.N10:00~17:0020140425110156/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2497&amp;fileTy=IMG&amp;fileNo=1풍성한칼국수1.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=2497&amp;fileTy=IMG&amp;fileNo=2풍성한칼국수2.jpg24972021-05-01 05:29:03
sjm_nmadrestelcn_cdcnlocale_cdlocaleintrcnparkng_atbsn_timecreat_dtimg_file1img_name1img_file2img_name2idxlast_load_dttm
636수림헤어강난희제석로65(당리동)051-202-4715603이미용216당리동주인이 직접 운영하면서 세련된 스타일 연출로 단골 고객이 많아 착한 가격을 유지N09:00-19:0020130603053327/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1288&amp;fileTy=IMG&amp;fileNo=2수림3.JPG/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1288&amp;fileTy=IMG&amp;fileNo=1수림1.JPG12882021-05-01 05:29:03
637갯마을산낙지박정숙승학로10번길31(당리동)051-203-6900602음식점216당리동주인이 직접 충무에서 산낙지를 구매하여 맛이 신선하여 믿고 찾는 식당Y10:00-22:0020130603051426/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1278&amp;fileTy=IMG&amp;fileNo=2갯마을2.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1278&amp;fileTy=IMG&amp;fileNo=1갯마을1.jpg12782021-05-01 05:29:03
638해주냉면노승제낙동대로324번길 5 (괴정동,(희망촌1길 6))051-291-4841602음식점204감천1동냉면전문점으로 육수등 모든 조리를 직접하며 4년이상 가격유지로 고객이 믿고찾음Y11:00~19:0020130603045440/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1270&amp;fileTy=IMG&amp;fileNo=2해주3.JPG/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1270&amp;fileTy=IMG&amp;fileNo=1해주1.JPG12702021-05-01 05:29:03
639얼크니손칼국수안성모부산시 기장군 기장읍 차성로 417번길 18051-721-3487602음식점45기장읍박리다매 전략Y12:00-20:0020130221024508/comm/getImage?srvcId=MULGAKIND&amp;upperNo=448&amp;fileTy=IMG&amp;fileNo=2얼크니손칼국수_내부.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=448&amp;fileTy=IMG&amp;fileNo=1얼크니손칼국수_외부.jpg4482021-05-01 05:29:03
640가마솥 추어탕남규리(46070) 부산광역시 기장군 기장읍 대청로35번길 52051-963-8686602음식점45기장읍무조건 박리다매 전략이다. "싸야 한그릇이라도 더 판다."N10:00-21:0020130221024508/comm/getImage?srvcId=MULGAKIND&amp;upperNo=447&amp;fileTy=IMG&amp;fileNo=3가마솥 추어탕(전경).jpg<NA><NA>4472021-05-01 05:29:03
641장안사손칼국수김귀이부산시 기장군 장안읍 장안로 89051-727-6694602음식점47장안읍박리다매 전략으로 경영한다Y09:00-22:0020130221024508/comm/getImage?srvcId=MULGAKIND&amp;upperNo=446&amp;fileTy=IMG&amp;fileNo=2장안사손칼국수_내부.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=446&amp;fileTy=IMG&amp;fileNo=1장안사손칼국수_외부.jpg4462021-05-01 05:29:03
642기장손만두서병구부산시 기장군 기장읍 차성동로 67번길 2-4051-721-7367602음식점45기장읍가족경영이며, 재료준비와 만두 빚기를 직접 한다.Y09:00-20:0020130221024508/comm/getImage?srvcId=MULGAKIND&amp;upperNo=444&amp;fileTy=IMG&amp;fileNo=2기장손만두_내부.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=444&amp;fileTy=IMG&amp;fileNo=1기장손만두_외부.jpg4442021-05-01 05:29:03
643이가네돼지국밥양정인부산시 기장군 기장읍 읍내로 103-1051-722-8896602음식점45기장읍자가라서 세가 안나가고, 가족경영이라 인건비 절감Y10:00-21:0020130221024508/comm/getImage?srvcId=MULGAKIND&amp;upperNo=443&amp;fileTy=IMG&amp;fileNo=2이가네돼지국밥_내부.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=443&amp;fileTy=IMG&amp;fileNo=1이가네돼지국밥_외부.jpg4432021-05-01 05:29:03
644명품면가김정희기장읍 차성동로 126번길 22051-722-9980602음식점45기장읍면 전문점.가족경영으로 인건비 절감 및 면,양념,육수 직접 만든다.Y10:00~22:0020130605062350/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1375&amp;fileTy=IMG&amp;fileNo=2명품면가1.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1375&amp;fileTy=IMG&amp;fileNo=1명품면가.jpg13752021-05-01 05:29:03
645시골삼계탕곽한나(46023) 부산광역시 기장군 정관읍 구연1로 6051-728-7517602음식점48정관읍다양한 삼계탕전문점. 직원 안쓰고 사장이 직접 주방일 한다. 가스, 전기 아끼려 애씀Y09:00~21:0020130605061848/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1369&amp;fileTy=IMG&amp;fileNo=2시골삼계탕메뉴.jpg/comm/getImage?srvcId=MULGAKIND&amp;upperNo=1369&amp;fileTy=IMG&amp;fileNo=1시골삼계탕.jpg13692021-05-01 05:29:03