Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells748
Missing cells (%)0.9%
Duplicate rows32
Duplicate rows (%)0.3%
Total size in memory722.7 KiB
Average record size in memory74.0 B

Variable types

DateTime2
Text3
Categorical1
Numeric2

Dataset

Description부산광역시_아동급식카드가맹점_20240320
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15102055

Alerts

데이터작성일자 has constant value ""Constant
Dataset has 32 (0.3%) duplicate rowsDuplicates
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
지번주소 has 482 (4.8%) missing valuesMissing
위도 has 133 (1.3%) missing valuesMissing
경도 has 133 (1.3%) missing valuesMissing

Reproduction

Analysis started2024-03-30 09:11:48.766384
Analysis finished2024-03-30 09:11:54.994050
Duration6.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

데이터작성일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-03-20 00:00:00
Maximum2024-03-20 00:00:00
2024-03-30T09:11:55.142705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T09:11:55.444420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

가맹점명칭
Text

Distinct9260
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-30T09:11:56.186637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length7.1908
Min length1

Characters and Unicode

Total characters71908
Distinct characters1020
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8782 ?
Unique (%)87.8%

Sample

1st row장독대
2nd row제주은희네해장국수영점
3rd row70년대 소금구이
4th row또또보리밥&매운수제비
5th row영월식당
ValueCountFrequency (%)
세븐일레븐 129
 
1.0%
gs25 116
 
0.9%
이마트24 115
 
0.9%
씨유(cu 95
 
0.7%
주식회사 70
 
0.5%
지에스(gs)25 62
 
0.5%
씨유 47
 
0.4%
파리바게뜨 42
 
0.3%
cu 38
 
0.3%
정관점 35
 
0.3%
Other values (9626) 12640
94.4%
2024-03-30T09:11:57.537004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3391
 
4.7%
점 2934
 
4.1%
이 1218
 
1.7%
시 1179
 
1.6%
산 1142
 
1.6%
부 1035
 
1.4%
광 949
 
1.3%
식 945
 
1.3%
리 926
 
1.3%
역 891
 
1.2%
Other values (1010) 57298
79.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62798
87.3%
Space Separator 3391
 
4.7%
Uppercase Letter 1785
 
2.5%
Decimal Number 1491
 
2.1%
Close Punctuation 865
 
1.2%
Open Punctuation 864
 
1.2%
Lowercase Letter 521
 
0.7%
Other Punctuation 161
 
0.2%
Dash Punctuation 23
 
< 0.1%
Modifier Symbol 4
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 2934
 
4.7%
이 1218
 
1.9%
시 1179
 
1.9%
산 1142
 
1.8%
부 1035
 
1.6%
광 949
 
1.5%
식 945
 
1.5%
리 926
 
1.5%
역 891
 
1.4%
스 834
 
1.3%
Other values (933) 50745
80.8%
Uppercase Letter
ValueCountFrequency (%)
S 295
16.5%
G 260
14.6%
C 246
13.8%
U 218
12.2%
T 74
 
4.1%
B 72
 
4.0%
A 70
 
3.9%
E 60
 
3.4%
D 54
 
3.0%
O 52
 
2.9%
Other values (16) 384
21.5%
Lowercase Letter
ValueCountFrequency (%)
o 56
 
10.7%
e 52
 
10.0%
a 45
 
8.6%
i 40
 
7.7%
s 33
 
6.3%
t 32
 
6.1%
n 32
 
6.1%
r 30
 
5.8%
c 27
 
5.2%
g 21
 
4.0%
Other values (15) 153
29.4%
Decimal Number
ValueCountFrequency (%)
2 498
33.4%
5 295
19.8%
4 158
 
10.6%
1 157
 
10.5%
0 113
 
7.6%
3 95
 
6.4%
9 64
 
4.3%
6 44
 
3.0%
7 35
 
2.3%
8 32
 
2.1%
Other Punctuation
ValueCountFrequency (%)
& 116
72.0%
. 37
 
23.0%
! 3
 
1.9%
; 2
 
1.2%
# 2
 
1.2%
% 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 863
99.8%
） 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 862
99.8%
（ 2
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
× 1
33.3%
Space Separator
ValueCountFrequency (%)
3391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62785
87.3%
Common 6804
 
9.5%
Latin 2306
 
3.2%
Han 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 2934
 
4.7%
이 1218
 
1.9%
시 1179
 
1.9%
산 1142
 
1.8%
부 1035
 
1.6%
광 949
 
1.5%
식 945
 
1.5%
리 926
 
1.5%
역 891
 
1.4%
스 834
 
1.3%
Other values (920) 50732
80.8%
Latin
ValueCountFrequency (%)
S 295
 
12.8%
G 260
 
11.3%
C 246
 
10.7%
U 218
 
9.5%
T 74
 
3.2%
B 72
 
3.1%
A 70
 
3.0%
E 60
 
2.6%
o 56
 
2.4%
D 54
 
2.3%
Other values (41) 901
39.1%
Common
ValueCountFrequency (%)
3391
49.8%
) 863
 
12.7%
( 862
 
12.7%
2 498
 
7.3%
5 295
 
4.3%
4 158
 
2.3%
1 157
 
2.3%
& 116
 
1.7%
0 113
 
1.7%
3 95
 
1.4%
Other values (16) 256
 
3.8%
Han
ValueCountFrequency (%)
家 1
 
7.7%
正 1
 
7.7%
新 1
 
7.7%
眞 1
 
7.7%
親 1
 
7.7%
心 1
 
7.7%
元 1
 
7.7%
生 1
 
7.7%
美 1
 
7.7%
每 1
 
7.7%
Other values (3) 3
23.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62785
87.3%
ASCII 9101
 
12.7%
CJK 13
 
< 0.1%
None 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3391
37.3%
) 863
 
9.5%
( 862
 
9.5%
2 498
 
5.5%
S 295
 
3.2%
5 295
 
3.2%
G 260
 
2.9%
C 246
 
2.7%
U 218
 
2.4%
4 158
 
1.7%
Other values (63) 2015
22.1%
Hangul
ValueCountFrequency (%)
점 2934
 
4.7%
이 1218
 
1.9%
시 1179
 
1.9%
산 1142
 
1.8%
부 1035
 
1.6%
광 949
 
1.5%
식 945
 
1.5%
리 926
 
1.5%
역 891
 
1.4%
스 834
 
1.3%
Other values (920) 50732
80.8%
None
ValueCountFrequency (%)
´ 4
44.4%
） 2
22.2%
（ 2
22.2%
× 1
 
11.1%
CJK
ValueCountFrequency (%)
家 1
 
7.7%
正 1
 
7.7%
新 1
 
7.7%
眞 1
 
7.7%
親 1
 
7.7%
心 1
 
7.7%
元 1
 
7.7%
生 1
 
7.7%
美 1
 
7.7%
每 1
 
7.7%
Other values (3) 3
23.1%

도로명주소
Text

Distinct9852
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-30T09:11:58.365302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length61
Mean length27.3222
Min length16

Characters and Unicode

Total characters273222
Distinct characters571
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

Unique9715 ?
Unique (%)97.2%

Sample

1st row부산광역시 남구 고동골로78번길 42 (문현동)
2nd row부산광역시 수영구 광안해변로344번길 17-5 1층 101호
3rd row부산광역시 동구 초량중로 68 1층 (초량동)
4th row부산광역시 부산진구 새싹로8번길 31 1층
5th row부산광역시 금정구 팔송로7번길 45 1층
ValueCountFrequency (%)
부산광역시 10005
 
18.0%
1층 3646
 
6.6%
부산진구 1049
 
1.9%
해운대구 873
 
1.6%
동래구 810
 
1.5%
사하구 786
 
1.4%
기장군 735
 
1.3%
금정구 668
 
1.2%
남구 654
 
1.2%
북구 651
 
1.2%
Other values (7147) 35570
64.2%
2024-03-30T09:11:59.937048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48231
 
17.7%
1 15566
 
5.7%
산 11863
 
4.3%
부 11799
 
4.3%
광 10776
 
3.9%
시 10616
 
3.9%
역 10125
 
3.7%
구 9779
 
3.6%
로 9336
 
3.4%
동 8490
 
3.1%
Other values (561) 126641
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161480
59.1%
Decimal Number 50919
 
18.6%
Space Separator 48231
 
17.7%
Open Punctuation 4830
 
1.8%
Close Punctuation 4828
 
1.8%
Dash Punctuation 2036
 
0.7%
Other Punctuation 495
 
0.2%
Uppercase Letter 354
 
0.1%
Lowercase Letter 27
 
< 0.1%
Math Symbol 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 11863
 
7.3%
부 11799
 
7.3%
광 10776
 
6.7%
시 10616
 
6.6%
역 10125
 
6.3%
구 9779
 
6.1%
로 9336
 
5.8%
동 8490
 
5.3%
층 5244
 
3.2%
길 5063
 
3.1%
Other values (510) 68389
42.4%
Uppercase Letter
ValueCountFrequency (%)
B 118
33.3%
A 89
25.1%
C 25
 
7.1%
E 18
 
5.1%
S 18
 
5.1%
K 15
 
4.2%
G 10
 
2.8%
H 8
 
2.3%
I 7
 
2.0%
D 6
 
1.7%
Other values (11) 40
 
11.3%
Lowercase Letter
ValueCountFrequency (%)
e 9
33.3%
b 4
14.8%
s 3
 
11.1%
a 3
 
11.1%
c 2
 
7.4%
k 1
 
3.7%
w 1
 
3.7%
v 1
 
3.7%
r 1
 
3.7%
i 1
 
3.7%
Decimal Number
ValueCountFrequency (%)
1 15566
30.6%
2 7138
14.0%
3 4927
 
9.7%
0 4500
 
8.8%
4 3888
 
7.6%
5 3464
 
6.8%
6 3392
 
6.7%
7 2769
 
5.4%
8 2703
 
5.3%
9 2572
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 482
97.4%
/ 11
 
2.2%
@ 2
 
0.4%
Space Separator
ValueCountFrequency (%)
48231
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4830
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4828
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2036
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161480
59.1%
Common 111360
40.8%
Latin 382
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 11863
 
7.3%
부 11799
 
7.3%
광 10776
 
6.7%
시 10616
 
6.6%
역 10125
 
6.3%
구 9779
 
6.1%
로 9336
 
5.8%
동 8490
 
5.3%
층 5244
 
3.2%
길 5063
 
3.1%
Other values (510) 68389
42.4%
Latin
ValueCountFrequency (%)
B 118
30.9%
A 89
23.3%
C 25
 
6.5%
E 18
 
4.7%
S 18
 
4.7%
K 15
 
3.9%
G 10
 
2.6%
e 9
 
2.4%
H 8
 
2.1%
I 7
 
1.8%
Other values (23) 65
17.0%
Common
ValueCountFrequency (%)
48231
43.3%
1 15566
 
14.0%
2 7138
 
6.4%
3 4927
 
4.4%
( 4830
 
4.3%
) 4828
 
4.3%
0 4500
 
4.0%
4 3888
 
3.5%
5 3464
 
3.1%
6 3392
 
3.0%
Other values (8) 10596
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161476
59.1%
ASCII 111741
40.9%
Compat Jamo 4
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48231
43.2%
1 15566
 
13.9%
2 7138
 
6.4%
3 4927
 
4.4%
( 4830
 
4.3%
) 4828
 
4.3%
0 4500
 
4.0%
4 3888
 
3.5%
5 3464
 
3.1%
6 3392
 
3.0%
Other values (40) 10977
 
9.8%
Hangul
ValueCountFrequency (%)
산 11863
 
7.3%
부 11799
 
7.3%
광 10776
 
6.7%
시 10616
 
6.6%
역 10125
 
6.3%
구 9779
 
6.1%
로 9336
 
5.8%
동 8490
 
5.3%
층 5244
 
3.2%
길 5063
 
3.1%
Other values (506) 68385
42.3%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
25.0%
ㅇ 1
25.0%
ㄷ 1
25.0%
ㅊ 1
25.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

지번주소
Text

MISSING 

Distinct8243
Distinct (%)86.6%
Missing482
Missing (%)4.8%
Memory size156.2 KiB
2024-03-30T09:12:00.821360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length19.621769
Min length15

Characters and Unicode

Total characters186760
Distinct characters153
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

Unique7335 ?
Unique (%)77.1%

Sample

1st row부산광역시 남구 문현동 119-98
2nd row부산광역시 수영구 민락동 110-42
3rd row부산광역시 동구 초량동 296-33
4th row부산광역시 부산진구 부전동 263-22
5th row부산광역시 금정구 남산동 48-7
ValueCountFrequency (%)
부산광역시 9515
24.5%
부산진구 1006
 
2.6%
해운대구 826
 
2.1%
동래구 778
 
2.0%
사하구 745
 
1.9%
기장군 697
 
1.8%
금정구 637
 
1.6%
남구 625
 
1.6%
북구 623
 
1.6%
연제구 610
 
1.6%
Other values (7528) 22737
58.6%
2024-03-30T09:12:02.277551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29281
15.7%
산 11160
 
6.0%
부 11134
 
6.0%
동 10183
 
5.5%
광 9896
 
5.3%
시 9539
 
5.1%
역 9515
 
5.1%
구 9170
 
4.9%
1 8702
 
4.7%
- 8440
 
4.5%
Other values (143) 69740
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 106698
57.1%
Decimal Number 42341
 
22.7%
Space Separator 29281
 
15.7%
Dash Punctuation 8440
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 11160
 
10.5%
부 11134
 
10.4%
동 10183
 
9.5%
광 9896
 
9.3%
시 9539
 
8.9%
역 9515
 
8.9%
구 9170
 
8.6%
대 1645
 
1.5%
사 1546
 
1.4%
연 1455
 
1.4%
Other values (131) 31455
29.5%
Decimal Number
ValueCountFrequency (%)
1 8702
20.6%
2 5845
13.8%
3 5011
11.8%
4 4250
10.0%
5 3833
9.1%
6 3208
 
7.6%
7 3131
 
7.4%
8 2917
 
6.9%
9 2748
 
6.5%
0 2696
 
6.4%
Space Separator
ValueCountFrequency (%)
29281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8440
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 106698
57.1%
Common 80062
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 11160
 
10.5%
부 11134
 
10.4%
동 10183
 
9.5%
광 9896
 
9.3%
시 9539
 
8.9%
역 9515
 
8.9%
구 9170
 
8.6%
대 1645
 
1.5%
사 1546
 
1.4%
연 1455
 
1.4%
Other values (131) 31455
29.5%
Common
ValueCountFrequency (%)
29281
36.6%
1 8702
 
10.9%
- 8440
 
10.5%
2 5845
 
7.3%
3 5011
 
6.3%
4 4250
 
5.3%
5 3833
 
4.8%
6 3208
 
4.0%
7 3131
 
3.9%
8 2917
 
3.6%
Other values (2) 5444
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 106698
57.1%
ASCII 80062
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29281
36.6%
1 8702
 
10.9%
- 8440
 
10.5%
2 5845
 
7.3%
3 5011
 
6.3%
4 4250
 
5.3%
5 3833
 
4.8%
6 3208
 
4.0%
7 3131
 
3.9%
8 2917
 
3.6%
Other values (2) 5444
 
6.8%
Hangul
ValueCountFrequency (%)
산 11160
 
10.5%
부 11134
 
10.4%
동 10183
 
9.5%
광 9896
 
9.3%
시 9539
 
8.9%
역 9515
 
8.9%
구 9170
 
8.6%
대 1645
 
1.5%
사 1546
 
1.4%
연 1455
 
1.4%
Other values (131) 31455
29.5%

업종
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
5730 
일반대중음식
1869 
편의점
842 
중식
 
483
패스트푸드
 
280
Other values (10)
796 

Length

Max length13
Median length2
Mean length2.9482
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row일반대중음식
2nd row한식
3rd row한식
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 5730
57.3%
일반대중음식 1869
 
18.7%
편의점 842
 
8.4%
중식 483
 
4.8%
패스트푸드 280
 
2.8%
양식 266
 
2.7%
제과점 266
 
2.7%
일식 249
 
2.5%
식품잡화 6
 
0.1%
할인점/슈퍼마켓 3
 
< 0.1%
Other values (5) 6
 
0.1%

Length

2024-03-30T09:12:02.873996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 5730
57.3%
일반대중음식 1869
 
18.7%
편의점 842
 
8.4%
중식 483
 
4.8%
패스트푸드 280
 
2.8%
양식 266
 
2.7%
제과점 266
 
2.7%
일식 249
 
2.5%
식품잡화 6
 
0.1%
할인점/슈퍼마켓 3
 
< 0.1%
Other values (7) 8
 
0.1%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8553
Distinct (%)86.7%
Missing133
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean35.168921
Minimum34.989747
Maximum37.662975
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-30T09:12:03.401072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.989747
5-th percentile35.083484
Q135.127071
median35.165099
Q335.202779
95-th percentile35.267067
Maximum37.662975
Range2.6732287
Interquartile range (IQR)0.07570827

Descriptive statistics

Standard deviation0.072148845
Coefficient of variation (CV)0.0020514944
Kurtosis382.58117
Mean35.168921
Median Absolute Deviation (MAD)0.03783237
Skewness11.708689
Sum347011.75
Variance0.0052054558
MonotonicityNot monotonic
2024-03-30T09:12:04.076777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.20380872 16
 
0.2%
35.09672134 12
 
0.1%
35.14649173 11
 
0.1%
35.13422946 11
 
0.1%
35.17097556 9
 
0.1%
35.1556582 8
 
0.1%
35.13266581 7
 
0.1%
35.12726691 7
 
0.1%
35.26618949 7
 
0.1%
35.06013471 7
 
0.1%
Other values (8543) 9772
97.7%
(Missing) 133
 
1.3%
ValueCountFrequency (%)
34.98974675 1
< 0.1%
35.00817871 1
< 0.1%
35.01198933 1
< 0.1%
35.01214021 1
< 0.1%
35.01258148 1
< 0.1%
35.01391787 1
< 0.1%
35.01415975 1
< 0.1%
35.01476797 1
< 0.1%
35.02301397 1
< 0.1%
35.03032699 2
< 0.1%
ValueCountFrequency (%)
37.66297547 1
< 0.1%
37.54946988 1
< 0.1%
37.54399651 1
< 0.1%
35.38287021 1
< 0.1%
35.37752494 1
< 0.1%
35.37040605 1
< 0.1%
35.37025568 1
< 0.1%
35.37023066 1
< 0.1%
35.36994466 1
< 0.1%
35.36985647 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8528
Distinct (%)86.4%
Missing133
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean129.06272
Minimum126.94748
Maximum129.28558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-30T09:12:04.664807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.94748
5-th percentile128.94832
Q1129.01571
median129.06717
Q3129.10632
95-th percentile129.19295
Maximum129.28558
Range2.3381032
Interquartile range (IQR)0.09061885

Descriptive statistics

Standard deviation0.083124848
Coefficient of variation (CV)0.00064406551
Kurtosis120.58643
Mean129.06272
Median Absolute Deviation (MAD)0.0444217
Skewness-4.82494
Sum1273461.9
Variance0.0069097403
MonotonicityNot monotonic
2024-03-30T09:12:05.130280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0859386 16
 
0.2%
129.0286701 13
 
0.1%
129.1112168 11
 
0.1%
129.0658548 11
 
0.1%
129.1776689 9
 
0.1%
129.0581408 8
 
0.1%
129.0779936 7
 
0.1%
129.1090406 7
 
0.1%
129.0805533 7
 
0.1%
129.1096681 7
 
0.1%
Other values (8518) 9771
97.7%
(Missing) 133
 
1.3%
ValueCountFrequency (%)
126.9474812 1
< 0.1%
126.9634511 1
< 0.1%
127.0123095 1
< 0.1%
128.8095893 1
< 0.1%
128.8117637 1
< 0.1%
128.8124822 1
< 0.1%
128.8145645 2
< 0.1%
128.8256978 1
< 0.1%
128.8273004 1
< 0.1%
128.8276182 1
< 0.1%
ValueCountFrequency (%)
129.2855844 1
< 0.1%
129.2854805 1
< 0.1%
129.2852835 1
< 0.1%
129.2848045 1
< 0.1%
129.2845874 1
< 0.1%
129.284549 1
< 0.1%
129.2833477 1
< 0.1%
129.2833191 1
< 0.1%
129.2832072 2
< 0.1%
129.2829303 2
< 0.1%

가맹점기준일자
Date

Distinct693
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-06-16 00:00:00
Maximum2024-03-20 00:00:00
2024-03-30T09:12:05.731859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T09:12:06.351792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-03-30T09:11:52.771397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T09:11:51.969356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T09:11:53.039518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T09:11:52.334061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T09:12:06.674654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종위도경도
업종1.0000.6810.538
위도0.6811.0000.689
경도0.5380.6891.000
2024-03-30T09:12:06.996917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종
위도1.0000.5170.409
경도0.5171.0000.335
업종0.4090.3351.000

Missing values

2024-03-30T09:11:53.526852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T09:11:54.355794image/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.
2024-03-30T09:11:54.788804image/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

데이터작성일자가맹점명칭도로명주소지번주소업종위도경도가맹점기준일자
275312024-03-20장독대부산광역시 남구 고동골로78번길 42 (문현동)부산광역시 남구 문현동 119-98일반대중음식35.14381129.0738012023-01-31
285922024-03-20제주은희네해장국수영점부산광역시 수영구 광안해변로344번길 17-5 1층 101호부산광역시 수영구 민락동 110-42한식35.15518129.1310312022-03-29
7182024-03-2070년대 소금구이부산광역시 동구 초량중로 68 1층 (초량동)부산광역시 동구 초량동 296-33한식35.117846129.038892023-04-15
94042024-03-20또또보리밥&매운수제비부산광역시 부산진구 새싹로8번길 31 1층부산광역시 부산진구 부전동 263-22한식35.159715129.0596362021-06-16
231172024-03-20영월식당부산광역시 금정구 팔송로7번길 45 1층부산광역시 금정구 남산동 48-7한식35.270181129.0918932023-07-18
224932024-03-20엄마손찌개부산광역시 북구 덕천로352번길 13 만덕부산광역시 북구 만덕동 884-8한식35.208484129.0422422023-01-03
184192024-03-20소연할매추어탕부산광역시 강서구 식만로247번길 6-3 (식만동)부산광역시 강서구 식만동 122-1한식35.215034128.913752021-06-16
84752024-03-20동두천부대찌개부산광역시 부산진구 당감로34번길 11 1층(당감동)부산광역시 부산진구 당감동 282-37한식35.164954129.0398362024-03-19
129152024-03-20밀그린치킨부산광역시 금정구 무학송로 106 1층 (부곡동)부산광역시 금정구 부곡동 59-8일반대중음식35.240552129.0936492021-06-16
277892024-03-20장터마을부산광역시 사하구 사하로186번라길 32 (괴정동)부산광역시 사하구 괴정동 436-33한식35.099669128.9950152021-06-16
데이터작성일자가맹점명칭도로명주소지번주소업종위도경도가맹점기준일자
299812024-03-20진강정(부산광역시센터점)부산광역시 기장군 정관읍 모전2길 13 1층 102호부산광역시 기장군 정관읍 모전리 685-9일반대중음식35.335443129.1693732022-06-21
110162024-03-20맛나감자탕부산광역시 연제구 중앙대로1150번길 41 (연산동)부산광역시 연제구 연산동 579-16한식35.190715129.0829412021-06-16
28972024-03-20고리식당부산광역시 기장군 장안읍 길천길 57 1층부산광역시 기장군 장안읍 길천리 188-23한식35.32665129.2852832023-11-15
352872024-03-20한마음정육식당부산광역시 기장군 정관읍 곰내길 591-15 2층부산광역시 기장군 정관읍 매학리 525-69한식35.314641129.1682062023-06-08
63882024-03-20뉴마린식당부산광역시 강서구 녹산산단381로 39 송정동부산광역시 강서구 송정동 1635-13일반대중음식35.092418128.8582472021-11-30
119082024-03-20모리부산광역시 금정구 두실로 25 (구서동)부산광역시 금정구 구서동 158-3한식35.260623129.0884552021-06-16
138062024-03-20벅스부산광역시 사하구 다대동로 23 303호 (다대동)부산광역시 사하구 다대동 798양식35.05576128.971432021-06-16
220612024-03-20양대감부산광역시 연제구 고분로 234-1 (연산동)부산광역시 연제구 연산동 480-31한식35.184361129.1077962022-06-23
30522024-03-20고성식당부산광역시 연제구 과정로265번길 6 (연산동)부산광역시 연제구 연산동 1051-3한식35.187537129.0981332021-11-02
186212024-03-20송가네부산광역시 북구 시랑로 30-1 1층부산광역시 북구 구포동 700-108한식35.202825129.0041732022-11-22

Duplicate rows

Most frequently occurring

데이터작성일자가맹점명칭도로명주소지번주소업종위도경도가맹점기준일자# duplicates
02024-03-20(주)코리아세븐 부산광역시일광바다점부산광역시 기장군 일광면 일광로 68부산광역시 기장군 일광읍 삼성리 105-1편의점35.262578129.2320322022-11-302
12024-03-20경원해물찜 부산광역시정관점부산광역시 기장군 정관읍 용수로 77 1층 일부부산광역시 기장군 정관읍 용수리 635-12한식35.328492129.1734172023-04-292
22024-03-20골목셰프부산광역시 기장군 정관읍 가동3로 20-1 101호부산광역시 기장군 정관읍 용수리 1291-4한식35.32801129.1810942022-05-282
32024-03-20꽃마름 일광삼성점부산광역시 기장군 일광읍 해빛5로 21-5 5층부산광역시 기장군 일광읍 삼성리 806한식35.260995129.2215292022-11-162
42024-03-20낙지볶음 개미집부산광역시 기장군 장안읍 해맞이로 13 .부산광역시 기장군 장안읍 좌천리 252-5한식35.313132129.245032022-01-252
52024-03-20난달부산광역시 기장군 일광면 문오성길 613 1 2층부산광역시 기장군 일광읍 문중리 33일반대중음식35.302558129.2589922021-12-242
62024-03-20다만나부산광역시 기장군 정관읍 가동길 8-21 102호부산광역시 기장군 정관읍 용수리 1294-4한식35.326442129.1802312023-03-032
72024-03-20대박통일광점부산광역시 기장군 일광면 해송1로 12 1층부산광역시 기장군 일광읍 삼성리 876-1한식35.266674129.2293422022-01-052
82024-03-20두텁삼부산광역시 기장군 정관읍 구연3로 15 .부산광역시 기장군 정관읍 매학리 751-4한식35.321089129.1815562022-08-302
92024-03-20땅스부대찌개정관점부산광역시 기장군 정관읍 정관로 545 501동104호(이진캐스빌아파트)부산광역시 기장군 정관읍 용수리 1336식품잡화35.322301129.1748442022-01-212