Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells1511
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory888.7 KiB
Average record size in memory91.0 B

Variable types

Numeric3
Text5
Categorical2

Dataset

Description부산광역시에 위치한 식당의 기본정보를 적어놓은 데이터 입니다. 식당명, 식당주소, 식당위경도, 식당대표전화번호, 식당소개내용 등 식당기본정보를 포함하고 있습니다.
Author부산관광공사
URLhttps://www.data.go.kr/data/15096711/fileData.do

Alerts

영업인허가명 is highly overall correlated with 영업신고증업태명High correlation
영업신고증업태명 is highly overall correlated with 영업인허가명High correlation
식당위도 is highly overall correlated with 식당경도High correlation
식당경도 is highly overall correlated with 식당위도High correlation
영업인허가명 is highly imbalanced (55.7%)Imbalance
식당대표전화번호 has 1390 (13.9%) missing valuesMissing
식당(ID) has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:55:50.645375
Analysis finished2023-12-11 23:55:54.825450
Duration4.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

식당(ID)
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean294421.85
Minimum1087
Maximum657871
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:55:54.914831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1087
5-th percentile17934.65
Q1112264.5
median290954
Q3466338.25
95-th percentile620648.55
Maximum657871
Range656784
Interquartile range (IQR)354073.75

Descriptive statistics

Standard deviation198564.13
Coefficient of variation (CV)0.67442047
Kurtosis-1.2560284
Mean294421.85
Median Absolute Deviation (MAD)176073.5
Skewness0.17286069
Sum2.9442185 × 109
Variance3.9427712 × 1010
MonotonicityNot monotonic
2023-12-12T08:55:55.099635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
546033 1
 
< 0.1%
17801 1
 
< 0.1%
209759 1
 
< 0.1%
338813 1
 
< 0.1%
169314 1
 
< 0.1%
504122 1
 
< 0.1%
291995 1
 
< 0.1%
17958 1
 
< 0.1%
314548 1
 
< 0.1%
25816 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1087 1
< 0.1%
1090 1
< 0.1%
1095 1
< 0.1%
1192 1
< 0.1%
1238 1
< 0.1%
1267 1
< 0.1%
1268 1
< 0.1%
1345 1
< 0.1%
1352 1
< 0.1%
1353 1
< 0.1%
ValueCountFrequency (%)
657871 1
< 0.1%
657856 1
< 0.1%
657827 1
< 0.1%
657774 1
< 0.1%
657732 1
< 0.1%
657724 1
< 0.1%
657585 1
< 0.1%
657584 1
< 0.1%
657535 1
< 0.1%
657460 1
< 0.1%

식당명
Text

Distinct9343
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T08:55:55.372217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length6.737
Min length1

Characters and Unicode

Total characters67370
Distinct characters1032
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8894 ?
Unique (%)88.9%

Sample

1st rowGS25(하단가락점)
2nd row산전수전
3rd row조방할매낙지
4th row아임스시
5th row테네로
ValueCountFrequency (%)
카페 32
 
0.3%
커피 15
 
0.1%
횟집 12
 
0.1%
진주식당 11
 
0.1%
옛날통닭 11
 
0.1%
밀양돼지국밥 10
 
0.1%
센텀시티점 10
 
0.1%
고봉민 10
 
0.1%
돼지국밥 9
 
0.1%
식당 9
 
0.1%
Other values (9964) 11013
98.8%
2023-12-12T08:55:55.815868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 2814
 
4.2%
) 2666
 
4.0%
( 2665
 
4.0%
이 1159
 
1.7%
1145
 
1.7%
산 1030
 
1.5%
부 962
 
1.4%
리 929
 
1.4%
스 878
 
1.3%
식 845
 
1.3%
Other values (1022) 52277
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58971
87.5%
Close Punctuation 2667
 
4.0%
Open Punctuation 2666
 
4.0%
Space Separator 1145
 
1.7%
Decimal Number 809
 
1.2%
Uppercase Letter 571
 
0.8%
Lowercase Letter 398
 
0.6%
Other Punctuation 132
 
0.2%
Dash Punctuation 6
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 2814
 
4.8%
이 1159
 
2.0%
산 1030
 
1.7%
부 962
 
1.6%
리 929
 
1.6%
스 878
 
1.5%
식 845
 
1.4%
집 768
 
1.3%
대 749
 
1.3%
당 732
 
1.2%
Other values (942) 48105
81.6%
Uppercase Letter
ValueCountFrequency (%)
C 69
12.1%
S 56
 
9.8%
P 43
 
7.5%
G 42
 
7.4%
B 39
 
6.8%
T 37
 
6.5%
E 33
 
5.8%
O 29
 
5.1%
D 27
 
4.7%
N 26
 
4.6%
Other values (16) 170
29.8%
Lowercase Letter
ValueCountFrequency (%)
e 55
13.8%
a 47
11.8%
o 31
 
7.8%
r 29
 
7.3%
n 28
 
7.0%
t 25
 
6.3%
c 21
 
5.3%
i 20
 
5.0%
s 18
 
4.5%
h 17
 
4.3%
Other values (14) 107
26.9%
Other Punctuation
ValueCountFrequency (%)
& 67
50.8%
. 21
 
15.9%
, 13
 
9.8%
! 9
 
6.8%
· 7
 
5.3%
？ 4
 
3.0%
? 4
 
3.0%
' 3
 
2.3%
: 2
 
1.5%
; 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 168
20.8%
2 144
17.8%
0 103
12.7%
9 74
9.1%
5 74
9.1%
3 72
8.9%
7 58
 
7.2%
8 49
 
6.1%
6 36
 
4.4%
4 31
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 2666
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2665
> 99.9%
[ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 2
50.0%
~ 2
50.0%
Space Separator
ValueCountFrequency (%)
1145
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58963
87.5%
Common 7429
 
11.0%
Latin 970
 
1.4%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 2814
 
4.8%
이 1159
 
2.0%
산 1030
 
1.7%
부 962
 
1.6%
리 929
 
1.6%
스 878
 
1.5%
식 845
 
1.4%
집 768
 
1.3%
대 749
 
1.3%
당 732
 
1.2%
Other values (935) 48097
81.6%
Latin
ValueCountFrequency (%)
C 69
 
7.1%
S 56
 
5.8%
e 55
 
5.7%
a 47
 
4.8%
P 43
 
4.4%
G 42
 
4.3%
B 39
 
4.0%
T 37
 
3.8%
E 33
 
3.4%
o 31
 
3.2%
Other values (41) 518
53.4%
Common
ValueCountFrequency (%)
) 2666
35.9%
( 2665
35.9%
1145
15.4%
1 168
 
2.3%
2 144
 
1.9%
0 103
 
1.4%
9 74
 
1.0%
5 74
 
1.0%
3 72
 
1.0%
& 67
 
0.9%
Other values (19) 251
 
3.4%
Han
ValueCountFrequency (%)
生 2
25.0%
心 1
12.5%
酒 1
12.5%
人 1
12.5%
香 1
12.5%
多 1
12.5%
喬 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58963
87.5%
ASCII 8387
 
12.4%
None 11
 
< 0.1%
CJK 8
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 2814
 
4.8%
이 1159
 
2.0%
산 1030
 
1.7%
부 962
 
1.6%
리 929
 
1.6%
스 878
 
1.5%
식 845
 
1.4%
집 768
 
1.3%
대 749
 
1.3%
당 732
 
1.2%
Other values (935) 48097
81.6%
ASCII
ValueCountFrequency (%)
) 2666
31.8%
( 2665
31.8%
1145
13.7%
1 168
 
2.0%
2 144
 
1.7%
0 103
 
1.2%
9 74
 
0.9%
5 74
 
0.9%
3 72
 
0.9%
C 69
 
0.8%
Other values (67) 1207
14.4%
None
ValueCountFrequency (%)
· 7
63.6%
？ 4
36.4%
CJK
ValueCountFrequency (%)
生 2
25.0%
心 1
12.5%
酒 1
12.5%
人 1
12.5%
香 1
12.5%
多 1
12.5%
喬 1
12.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

Distinct8522
Distinct (%)85.6%
Missing43
Missing (%)0.4%
Memory size156.2 KiB
2023-12-12T08:55:56.229067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length19.440695
Min length9

Characters and Unicode

Total characters193571
Distinct characters276
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

Unique7584 ?
Unique (%)76.2%

Sample

1st row부산광역시 사하구 하신번영로312번길 23
2nd row부산광역시 해운대구 반송로924번길 23
3rd row부산광역시 동래구 명륜로94번길 33
4th row부산광역시 사상구 사상로233번길 38-3
5th row부산광역시 기장군 정관읍 모전2길 19-6
ValueCountFrequency (%)
부산광역시 9957
24.7%
부산진구 1398
 
3.5%
동래구 931
 
2.3%
금정구 841
 
2.1%
사하구 772
 
1.9%
사상구 734
 
1.8%
남구 686
 
1.7%
연제구 635
 
1.6%
중구 635
 
1.6%
북구 614
 
1.5%
Other values (3923) 23110
57.3%
2023-12-12T08:55:56.833243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30356
 
15.7%
산 11699
 
6.0%
부 11580
 
6.0%
시 10300
 
5.3%
광 10275
 
5.3%
역 9959
 
5.1%
구 9701
 
5.0%
로 9520
 
4.9%
1 7620
 
3.9%
2 5063
 
2.6%
Other values (266) 77498
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125895
65.0%
Decimal Number 35461
 
18.3%
Space Separator 30356
 
15.7%
Dash Punctuation 1847
 
1.0%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 11699
 
9.3%
부 11580
 
9.2%
시 10300
 
8.2%
광 10275
 
8.2%
역 9959
 
7.9%
구 9701
 
7.7%
로 9520
 
7.6%
길 4970
 
3.9%
번 4676
 
3.7%
대 3153
 
2.5%
Other values (250) 40062
31.8%
Decimal Number
ValueCountFrequency (%)
1 7620
21.5%
2 5063
14.3%
3 4081
11.5%
4 3203
9.0%
5 3088
8.7%
6 2918
 
8.2%
7 2572
 
7.3%
9 2354
 
6.6%
8 2286
 
6.4%
0 2276
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
C 3
25.0%
P 3
25.0%
A 3
25.0%
E 3
25.0%
Space Separator
ValueCountFrequency (%)
30356
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1847
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125895
65.0%
Common 67664
35.0%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 11699
 
9.3%
부 11580
 
9.2%
시 10300
 
8.2%
광 10275
 
8.2%
역 9959
 
7.9%
구 9701
 
7.7%
로 9520
 
7.6%
길 4970
 
3.9%
번 4676
 
3.7%
대 3153
 
2.5%
Other values (250) 40062
31.8%
Common
ValueCountFrequency (%)
30356
44.9%
1 7620
 
11.3%
2 5063
 
7.5%
3 4081
 
6.0%
4 3203
 
4.7%
5 3088
 
4.6%
6 2918
 
4.3%
7 2572
 
3.8%
9 2354
 
3.5%
8 2286
 
3.4%
Other values (2) 4123
 
6.1%
Latin
ValueCountFrequency (%)
C 3
25.0%
P 3
25.0%
A 3
25.0%
E 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125895
65.0%
ASCII 67676
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30356
44.9%
1 7620
 
11.3%
2 5063
 
7.5%
3 4081
 
6.0%
4 3203
 
4.7%
5 3088
 
4.6%
6 2918
 
4.3%
7 2572
 
3.8%
9 2354
 
3.5%
8 2286
 
3.4%
Other values (6) 4135
 
6.1%
Hangul
ValueCountFrequency (%)
산 11699
 
9.3%
부 11580
 
9.2%
시 10300
 
8.2%
광 10275
 
8.2%
역 9959
 
7.9%
구 9701
 
7.7%
로 9520
 
7.6%
길 4970
 
3.9%
번 4676
 
3.7%
대 3153
 
2.5%
Other values (250) 40062
31.8%

지번주소
Text

Distinct8428
Distinct (%)84.9%
Missing78
Missing (%)0.8%
Memory size156.2 KiB
2023-12-12T08:55:57.161637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length19.574884
Min length9

Characters and Unicode

Total characters194222
Distinct characters149
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7468 ?
Unique (%)75.3%

Sample

1st row부산광역시 사하구 하단동 503-27
2nd row부산광역시 해운대구 반송동 62-309
3rd row부산광역시 동래구 명륜동 401
4th row부산광역시 사상구 괘법동 522-9
5th row부산광역시 기장군 정관읍 모전리 687-9
ValueCountFrequency (%)
부산광역시 9922
24.7%
부산진구 1394
 
3.5%
동래구 920
 
2.3%
금정구 836
 
2.1%
사하구 764
 
1.9%
사상구 733
 
1.8%
남구 691
 
1.7%
중구 640
 
1.6%
연제구 631
 
1.6%
북구 611
 
1.5%
Other values (7538) 23070
57.4%
2023-12-12T08:55:57.653855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30290
15.6%
부 12224
 
6.3%
산 11991
 
6.2%
동 11048
 
5.7%
광 10042
 
5.2%
시 9942
 
5.1%
역 9922
 
5.1%
구 9697
 
5.0%
1 9035
 
4.7%
- 8981
 
4.6%
Other values (139) 71050
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110988
57.1%
Decimal Number 43963
 
22.6%
Space Separator 30290
 
15.6%
Dash Punctuation 8981
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 12224
 
11.0%
산 11991
 
10.8%
동 11048
 
10.0%
광 10042
 
9.0%
시 9942
 
9.0%
역 9922
 
8.9%
구 9697
 
8.7%
사 1717
 
1.5%
연 1556
 
1.4%
정 1397
 
1.3%
Other values (127) 31452
28.3%
Decimal Number
ValueCountFrequency (%)
1 9035
20.6%
2 5981
13.6%
3 4893
11.1%
4 4474
10.2%
5 4273
9.7%
6 3455
 
7.9%
7 3251
 
7.4%
8 2976
 
6.8%
0 2933
 
6.7%
9 2692
 
6.1%
Space Separator
ValueCountFrequency (%)
30290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8981
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110988
57.1%
Common 83234
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 12224
 
11.0%
산 11991
 
10.8%
동 11048
 
10.0%
광 10042
 
9.0%
시 9942
 
9.0%
역 9922
 
8.9%
구 9697
 
8.7%
사 1717
 
1.5%
연 1556
 
1.4%
정 1397
 
1.3%
Other values (127) 31452
28.3%
Common
ValueCountFrequency (%)
30290
36.4%
1 9035
 
10.9%
- 8981
 
10.8%
2 5981
 
7.2%
3 4893
 
5.9%
4 4474
 
5.4%
5 4273
 
5.1%
6 3455
 
4.2%
7 3251
 
3.9%
8 2976
 
3.6%
Other values (2) 5625
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110988
57.1%
ASCII 83234
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30290
36.4%
1 9035
 
10.9%
- 8981
 
10.8%
2 5981
 
7.2%
3 4893
 
5.9%
4 4474
 
5.4%
5 4273
 
5.1%
6 3455
 
4.2%
7 3251
 
3.9%
8 2976
 
3.6%
Other values (2) 5625
 
6.8%
Hangul
ValueCountFrequency (%)
부 12224
 
11.0%
산 11991
 
10.8%
동 11048
 
10.0%
광 10042
 
9.0%
시 9942
 
9.0%
역 9922
 
8.9%
구 9697
 
8.7%
사 1717
 
1.5%
연 1556
 
1.4%
정 1397
 
1.3%
Other values (127) 31452
28.3%

식당위도
Real number (ℝ)

HIGH CORRELATION 

Distinct2046
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.847168
Minimum0
Maximum35.3823
Zeros91
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:55:58.012183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile35.0879
Q135.1187
median35.1642
Q335.2039
95-th percentile35.2563
Maximum35.3823
Range35.3823
Interquartile range (IQR)0.0852

Descriptive statistics

Standard deviation3.3400505
Coefficient of variation (CV)0.095848547
Kurtosis104.89469
Mean34.847168
Median Absolute Deviation (MAD)0.0414
Skewness-10.336539
Sum348471.68
Variance11.155937
MonotonicityNot monotonic
2023-12-12T08:55:58.173840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 91
 
0.9%
35.0983 46
 
0.5%
35.1688 36
 
0.4%
35.0968 33
 
0.3%
35.1568 26
 
0.3%
35.1875 25
 
0.2%
35.0997 22
 
0.2%
35.0984 22
 
0.2%
35.099 21
 
0.2%
35.1571 21
 
0.2%
Other values (2036) 9657
96.6%
ValueCountFrequency (%)
0.0 91
0.9%
35.0105 1
 
< 0.1%
35.0114 1
 
< 0.1%
35.0117 1
 
< 0.1%
35.0223 1
 
< 0.1%
35.0254 1
 
< 0.1%
35.0266 1
 
< 0.1%
35.0305 1
 
< 0.1%
35.0309 1
 
< 0.1%
35.0508 1
 
< 0.1%
ValueCountFrequency (%)
35.3823 1
< 0.1%
35.3775 1
< 0.1%
35.3712 1
< 0.1%
35.3709 1
< 0.1%
35.3708 2
< 0.1%
35.3704 1
< 0.1%
35.3693 1
< 0.1%
35.3662 1
< 0.1%
35.3655 1
< 0.1%
35.3591 1
< 0.1%

식당경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2332
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.88254
Minimum0
Maximum129.2904
Zeros91
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:55:58.375966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile128.9598
Q1129.0169
median129.0599
Q3129.0904
95-th percentile129.1751
Maximum129.2904
Range129.2904
Interquartile range (IQR)0.0735

Descriptive statistics

Standard deviation12.255888
Coefficient of variation (CV)0.095837074
Kurtosis104.94635
Mean127.88254
Median Absolute Deviation (MAD)0.0364
Skewness-10.340323
Sum1278825.4
Variance150.20679
MonotonicityNot monotonic
2023-12-12T08:55:58.529065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 91
 
0.9%
129.0367 38
 
0.4%
129.0855 32
 
0.3%
129.0291 31
 
0.3%
129.0586 31
 
0.3%
129.1295 29
 
0.3%
129.0604 23
 
0.2%
129.0564 22
 
0.2%
129.0612 22
 
0.2%
129.0607 22
 
0.2%
Other values (2322) 9659
96.6%
ValueCountFrequency (%)
0.0 91
0.9%
128.8124 1
 
< 0.1%
128.815 1
 
< 0.1%
128.8153 1
 
< 0.1%
128.8158 1
 
< 0.1%
128.8191 1
 
< 0.1%
128.8217 1
 
< 0.1%
128.8236 1
 
< 0.1%
128.8269 1
 
< 0.1%
128.8273 1
 
< 0.1%
ValueCountFrequency (%)
129.2904 1
< 0.1%
129.2849 1
< 0.1%
129.2843 1
< 0.1%
129.2834 1
< 0.1%
129.2833 1
< 0.1%
129.2832 1
< 0.1%
129.2831 1
< 0.1%
129.283 1
< 0.1%
129.2822 1
< 0.1%
129.2821 1
< 0.1%

식당대표전화번호
Text

MISSING 

Distinct8498
Distinct (%)98.7%
Missing1390
Missing (%)13.9%
Memory size156.2 KiB
2023-12-12T08:55:58.798835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.026249
Min length11

Characters and Unicode

Total characters103546
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8391 ?
Unique (%)97.5%

Sample

1st row051-205-4385
2nd row051-545-6522
3rd row051-553-4152
4th row051-315-0252
5th row051-728-9388
ValueCountFrequency (%)
051-253-3757 3
 
< 0.1%
051-518-2184 3
 
< 0.1%
051-266-1763 3
 
< 0.1%
051-632-2705 3
 
< 0.1%
051-633-0102 3
 
< 0.1%
051-634-1747 2
 
< 0.1%
051-867-8249 2
 
< 0.1%
051-866-6969 2
 
< 0.1%
051-832-0203 2
 
< 0.1%
051-1577-3082 2
 
< 0.1%
Other values (8488) 8585
99.7%
2023-12-12T08:55:59.230031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17220
16.6%
5 15303
14.8%
0 14792
14.3%
1 14008
13.5%
2 8064
7.8%
3 6656
 
6.4%
8 6244
 
6.0%
7 5921
 
5.7%
4 5235
 
5.1%
6 5196
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 86326
83.4%
Dash Punctuation 17220
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 15303
17.7%
0 14792
17.1%
1 14008
16.2%
2 8064
9.3%
3 6656
7.7%
8 6244
7.2%
7 5921
 
6.9%
4 5235
 
6.1%
6 5196
 
6.0%
9 4907
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 17220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 103546
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17220
16.6%
5 15303
14.8%
0 14792
14.3%
1 14008
13.5%
2 8064
7.8%
3 6656
 
6.4%
8 6244
 
6.0%
7 5921
 
5.7%
4 5235
 
5.1%
6 5196
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 103546
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17220
16.6%
5 15303
14.8%
0 14792
14.3%
1 14008
13.5%
2 8064
7.8%
3 6656
 
6.4%
8 6244
 
6.0%
7 5921
 
5.7%
4 5235
 
5.1%
6 5196
 
5.0%

영업신고증업태명
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3902 
호프/통닭
680 
분식
609 
기타
571 
커피숍
555 
Other values (30)
3683 

Length

Max length15
Median length2
Mean length3.3467
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row기타(편의점)
2nd row호프/통닭
3rd row한식
4th row일식
5th row경양식

Common Values

ValueCountFrequency (%)
한식 3902
39.0%
호프/통닭 680
 
6.8%
분식 609
 
6.1%
기타 571
 
5.7%
커피숍 555
 
5.5%
경양식 514
 
5.1%
식육(숯불구이) 493
 
4.9%
<NA> 441
 
4.4%
중국식 380
 
3.8%
회집 345
 
3.5%
Other values (25) 1510
 
15.1%

Length

2023-12-12T08:55:59.416539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3902
38.3%
기타 767
 
7.5%
호프/통닭 680
 
6.7%
분식 609
 
6.0%
커피숍 555
 
5.4%
경양식 514
 
5.0%
식육(숯불구이 493
 
4.8%
na 441
 
4.3%
중국식 380
 
3.7%
회집 345
 
3.4%
Other values (25) 1510
 
14.8%

영업인허가명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
8488 
휴게음식점
1297 
제과점영업
 
215

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row휴게음식점
2nd row일반음식점
3rd row일반음식점
4th row일반음식점
5th row일반음식점

Common Values

ValueCountFrequency (%)
일반음식점 8488
84.9%
휴게음식점 1297
 
13.0%
제과점영업 215
 
2.1%

Length

2023-12-12T08:55:59.564924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:55:59.692817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 8488
84.9%
휴게음식점 1297
 
13.0%
제과점영업 215
 
2.1%

음식점소개내용
Text

Distinct9993
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T08:56:00.017546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length417
Median length208
Mean length46.716
Min length21

Characters and Unicode

Total characters467160
Distinct characters1045
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9986 ?
Unique (%)99.9%

Sample

1st row부산광역시 사하구에서 가 볼 만한 식당을 찾으신다면? "GS25(하단가락점)"를 추천합니다!
2nd row"산전수전"은 부산광역시 해운대구에 있습니다.
3rd row부산광역시 동래구에 가신다면 "조방할매낙지"에 방문해보세요~
4th row부산광역시 사상구에서 가 볼 만한 식당을 찾으신다면? 괘법르네시떼역 근처에 있는 "아임스시"를 추천합니다!
5th row부산광역시 기장군에 가신다면 "테네로"에 방문해보세요~
ValueCountFrequency (%)
부산광역시 10000
 
12.1%
추천합니다 5203
 
6.3%
찾으신다면 3432
 
4.1%
방문해보세요 2337
 
2.8%
식당을 2221
 
2.7%
만한 2217
 
2.7%
볼 2217
 
2.7%
가 2217
 
2.7%
있습니다 1410
 
1.7%
맛집을 1211
 
1.5%
Other values (10952) 50398
60.8%
2023-12-12T08:56:00.629858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72863
 
15.6%
" 20064
 
4.3%
다 14978
 
3.2%
시 13579
 
2.9%
부 12976
 
2.8%
산 12938
 
2.8%
역 11422
 
2.4%
에 11108
 
2.4%
광 10084
 
2.2%
구 10025
 
2.1%
Other values (1035) 277123
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 345828
74.0%
Space Separator 72863
 
15.6%
Other Punctuation 37303
 
8.0%
Decimal Number 3189
 
0.7%
Close Punctuation 2630
 
0.6%
Open Punctuation 2629
 
0.6%
Uppercase Letter 1241
 
0.3%
Math Symbol 1043
 
0.2%
Lowercase Letter 427
 
0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 14978
 
4.3%
시 13579
 
3.9%
부 12976
 
3.8%
산 12938
 
3.7%
역 11422
 
3.3%
에 11108
 
3.2%
광 10084
 
2.9%
구 10025
 
2.9%
을 9782
 
2.8%
니 8212
 
2.4%
Other values (956) 230724
66.7%
Uppercase Letter
ValueCountFrequency (%)
S 258
20.8%
B 212
17.1%
K 117
9.4%
C 95
 
7.7%
T 93
 
7.5%
V 77
 
6.2%
P 43
 
3.5%
G 42
 
3.4%
M 41
 
3.3%
E 33
 
2.7%
Other values (16) 230
18.5%
Lowercase Letter
ValueCountFrequency (%)
e 58
13.6%
a 47
 
11.0%
o 34
 
8.0%
t 30
 
7.0%
r 29
 
6.8%
n 29
 
6.8%
c 21
 
4.9%
i 20
 
4.7%
s 20
 
4.7%
h 17
 
4.0%
Other values (14) 122
28.6%
Other Punctuation
ValueCountFrequency (%)
" 20064
53.8%
! 6640
 
17.8%
? 5248
 
14.1%
. 3837
 
10.3%
, 1429
 
3.8%
& 67
 
0.2%
· 7
 
< 0.1%
？ 4
 
< 0.1%
' 3
 
< 0.1%
: 2
 
< 0.1%
Other values (2) 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 686
21.5%
0 635
19.9%
1 629
19.7%
5 220
 
6.9%
3 193
 
6.1%
7 182
 
5.7%
9 180
 
5.6%
6 179
 
5.6%
4 148
 
4.6%
8 137
 
4.3%
Math Symbol
ValueCountFrequency (%)
~ 1041
99.8%
+ 2
 
0.2%
Space Separator
ValueCountFrequency (%)
72863
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2630
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2629
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 345820
74.0%
Common 119663
 
25.6%
Latin 1669
 
0.4%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 14978
 
4.3%
시 13579
 
3.9%
부 12976
 
3.8%
산 12938
 
3.7%
역 11422
 
3.3%
에 11108
 
3.2%
광 10084
 
2.9%
구 10025
 
2.9%
을 9782
 
2.8%
니 8212
 
2.4%
Other values (949) 230716
66.7%
Latin
ValueCountFrequency (%)
S 258
15.5%
B 212
 
12.7%
K 117
 
7.0%
C 95
 
5.7%
T 93
 
5.6%
V 77
 
4.6%
e 58
 
3.5%
a 47
 
2.8%
P 43
 
2.6%
G 42
 
2.5%
Other values (41) 627
37.6%
Common
ValueCountFrequency (%)
72863
60.9%
" 20064
 
16.8%
! 6640
 
5.5%
? 5248
 
4.4%
. 3837
 
3.2%
) 2630
 
2.2%
( 2629
 
2.2%
, 1429
 
1.2%
~ 1041
 
0.9%
2 686
 
0.6%
Other values (18) 2596
 
2.2%
Han
ValueCountFrequency (%)
生 2
25.0%
心 1
12.5%
香 1
12.5%
酒 1
12.5%
人 1
12.5%
多 1
12.5%
喬 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 345820
74.0%
ASCII 121320
 
26.0%
None 11
 
< 0.1%
CJK 8
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72863
60.1%
" 20064
 
16.5%
! 6640
 
5.5%
? 5248
 
4.3%
. 3837
 
3.2%
) 2630
 
2.2%
( 2629
 
2.2%
, 1429
 
1.2%
~ 1041
 
0.9%
2 686
 
0.6%
Other values (66) 4253
 
3.5%
Hangul
ValueCountFrequency (%)
다 14978
 
4.3%
시 13579
 
3.9%
부 12976
 
3.8%
산 12938
 
3.7%
역 11422
 
3.3%
에 11108
 
3.2%
광 10084
 
2.9%
구 10025
 
2.9%
을 9782
 
2.8%
니 8212
 
2.4%
Other values (949) 230716
66.7%
None
ValueCountFrequency (%)
· 7
63.6%
？ 4
36.4%
CJK
ValueCountFrequency (%)
生 2
25.0%
心 1
12.5%
香 1
12.5%
酒 1
12.5%
人 1
12.5%
多 1
12.5%
喬 1
12.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

Interactions

2023-12-12T08:55:54.012847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:55:53.293761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:55:53.624121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:55:54.118958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:55:53.403298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:55:53.742728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:55:54.231717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:55:53.511590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:55:53.881499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:56:00.771922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식당(ID)식당위도식당경도영업신고증업태명영업인허가명
식당(ID)1.0000.0000.0000.3890.327
식당위도0.0001.0001.0000.0550.000
식당경도0.0001.0001.0000.0550.000
영업신고증업태명0.3890.0550.0551.0000.998
영업인허가명0.3270.0000.0000.9981.000
2023-12-12T08:56:00.902217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업인허가명영업신고증업태명
영업인허가명1.0000.996
영업신고증업태명0.9961.000
2023-12-12T08:56:01.012412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식당(ID)식당위도식당경도영업신고증업태명영업인허가명
식당(ID)1.0000.0530.0360.1470.208
식당위도0.0531.0000.5440.0430.000
식당경도0.0360.5441.0000.0430.000
영업신고증업태명0.1470.0430.0431.0000.996
영업인허가명0.2080.0000.0000.9961.000

Missing values

2023-12-12T08:55:54.410118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:55:54.590910image/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.
2023-12-12T08:55:54.741220image/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

식당(ID)식당명도로명주소지번주소식당위도식당경도식당대표전화번호영업신고증업태명영업인허가명음식점소개내용
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식당(ID)식당명도로명주소지번주소식당위도식당경도식당대표전화번호영업신고증업태명영업인허가명음식점소개내용
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