Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells708
Missing cells (%)0.9%
Duplicate rows35
Duplicate rows (%)0.4%
Total size in memory722.7 KiB
Average record size in memory74.0 B

Variable types

DateTime2
Text3
Categorical1
Numeric2

Dataset

Description부산광역시 아동급식카드 가맹점에 대한 데이터로 가맹점명칭, 도로명주소, 지번주소, 업종 등의 항목을 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15102055/fileData.do

Alerts

데이터작성일자 has constant value ""Constant
Dataset has 35 (0.4%) duplicate rowsDuplicates
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
지번주소 has 476 (4.8%) missing valuesMissing
위도 has 116 (1.2%) missing valuesMissing
경도 has 116 (1.2%) missing valuesMissing

Reproduction

Analysis started2024-03-23 05:34:44.251832
Analysis finished2024-03-23 05:34:48.939844
Duration4.69 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
2024-03-23T14:34:49.008775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:34:49.171956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

가맹점명칭
Text

Distinct9289
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T14:34:49.691665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length7.1992
Min length1

Characters and Unicode

Total characters71992
Distinct characters1024
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8840 ?
Unique (%)88.4%

Sample

1st row무봉리토종순대국 오시리아점
2nd row씨유서면직통로점
3rd row지에스(GS25) 구포대교점
4th row오리마루 명지본점
5th row감포식당
ValueCountFrequency (%)
gs25 147
 
1.1%
세븐일레븐 137
 
1.0%
이마트24 131
 
1.0%
씨유(cu 79
 
0.6%
주식회사 65
 
0.5%
지에스(gs)25 57
 
0.4%
씨유 50
 
0.4%
파리바게뜨 50
 
0.4%
주)코리아세븐 37
 
0.3%
정관점 36
 
0.3%
Other values (9715) 12588
94.1%
2024-03-23T14:34:50.370823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3380
 
4.7%
점 2963
 
4.1%
이 1317
 
1.8%
시 1159
 
1.6%
산 1098
 
1.5%
부 1021
 
1.4%
식 987
 
1.4%
리 952
 
1.3%
광 883
 
1.2%
역 864
 
1.2%
Other values (1014) 57368
79.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62885
87.3%
Space Separator 3380
 
4.7%
Uppercase Letter 1738
 
2.4%
Decimal Number 1577
 
2.2%
Close Punctuation 833
 
1.2%
Open Punctuation 832
 
1.2%
Lowercase Letter 578
 
0.8%
Other Punctuation 145
 
0.2%
Dash Punctuation 12
 
< 0.1%
Math Symbol 5
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 2963
 
4.7%
이 1317
 
2.1%
시 1159
 
1.8%
산 1098
 
1.7%
부 1021
 
1.6%
식 987
 
1.6%
리 952
 
1.5%
광 883
 
1.4%
역 864
 
1.4%
대 852
 
1.4%
Other values (936) 50789
80.8%
Uppercase Letter
ValueCountFrequency (%)
S 317
18.2%
G 268
15.4%
C 231
13.3%
U 192
11.0%
A 72
 
4.1%
B 70
 
4.0%
T 65
 
3.7%
H 59
 
3.4%
O 58
 
3.3%
E 53
 
3.0%
Other values (16) 353
20.3%
Lowercase Letter
ValueCountFrequency (%)
e 77
13.3%
a 52
 
9.0%
o 43
 
7.4%
r 42
 
7.3%
i 38
 
6.6%
n 34
 
5.9%
t 31
 
5.4%
s 27
 
4.7%
c 26
 
4.5%
l 24
 
4.2%
Other values (16) 184
31.8%
Decimal Number
ValueCountFrequency (%)
2 546
34.6%
5 317
20.1%
4 194
 
12.3%
1 151
 
9.6%
3 94
 
6.0%
0 89
 
5.6%
9 61
 
3.9%
7 45
 
2.9%
6 40
 
2.5%
8 40
 
2.5%
Other Punctuation
ValueCountFrequency (%)
& 98
67.6%
. 39
 
26.9%
! 4
 
2.8%
/ 2
 
1.4%
; 1
 
0.7%
@ 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 831
99.8%
） 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 830
99.8%
（ 2
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 4
80.0%
× 1
 
20.0%
Space Separator
ValueCountFrequency (%)
3380
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62875
87.3%
Common 6791
 
9.4%
Latin 2316
 
3.2%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 2963
 
4.7%
이 1317
 
2.1%
시 1159
 
1.8%
산 1098
 
1.7%
부 1021
 
1.6%
식 987
 
1.6%
리 952
 
1.5%
광 883
 
1.4%
역 864
 
1.4%
대 852
 
1.4%
Other values (927) 50779
80.8%
Latin
ValueCountFrequency (%)
S 317
 
13.7%
G 268
 
11.6%
C 231
 
10.0%
U 192
 
8.3%
e 77
 
3.3%
A 72
 
3.1%
B 70
 
3.0%
T 65
 
2.8%
H 59
 
2.5%
O 58
 
2.5%
Other values (42) 907
39.2%
Common
ValueCountFrequency (%)
3380
49.8%
) 831
 
12.2%
( 830
 
12.2%
2 546
 
8.0%
5 317
 
4.7%
4 194
 
2.9%
1 151
 
2.2%
& 98
 
1.4%
3 94
 
1.4%
0 89
 
1.3%
Other values (16) 261
 
3.8%
Han
ValueCountFrequency (%)
生 2
20.0%
杰 1
10.0%
錫 1
10.0%
人 1
10.0%
家 1
10.0%
仙 1
10.0%
酒 1
10.0%
食 1
10.0%
林 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62872
87.3%
ASCII 9099
 
12.6%
CJK 10
 
< 0.1%
None 8
 
< 0.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3380
37.1%
) 831
 
9.1%
( 830
 
9.1%
2 546
 
6.0%
S 317
 
3.5%
5 317
 
3.5%
G 268
 
2.9%
C 231
 
2.5%
4 194
 
2.1%
U 192
 
2.1%
Other values (64) 1993
21.9%
Hangul
ValueCountFrequency (%)
점 2963
 
4.7%
이 1317
 
2.1%
시 1159
 
1.8%
산 1098
 
1.7%
부 1021
 
1.6%
식 987
 
1.6%
리 952
 
1.5%
광 883
 
1.4%
역 864
 
1.4%
대 852
 
1.4%
Other values (924) 50776
80.8%
None
ValueCountFrequency (%)
´ 3
37.5%
（ 2
25.0%
） 2
25.0%
× 1
 
12.5%
CJK
ValueCountFrequency (%)
生 2
20.0%
杰 1
10.0%
錫 1
10.0%
人 1
10.0%
家 1
10.0%
仙 1
10.0%
酒 1
10.0%
食 1
10.0%
林 1
10.0%
Compat Jamo
ValueCountFrequency (%)
ㅅ 1
33.3%
ㅠ 1
33.3%
ㄴ 1
33.3%

도로명주소
Text

Distinct9850
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T14:34:51.011354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length59
Mean length27.3375
Min length16

Characters and Unicode

Total characters273375
Distinct characters576
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9704 ?
Unique (%)97.0%

Sample

1st row부산광역시 기장군 기장읍 기장해안로 172 107호
2nd row부산광역시 부산진구 신천대로162번길 91 (부전동)
3rd row부산광역시 북구 백양대로1063번길 1 1층
4th row부산광역시 강서구 명지국제6로1번가길 15 1층
5th row부산광역시 해운대구 아랫반송로23번길 37 (반송동)
ValueCountFrequency (%)
부산광역시 9999
 
18.0%
1층 3632
 
6.5%
부산진구 1094
 
2.0%
해운대구 963
 
1.7%
동래구 784
 
1.4%
사하구 777
 
1.4%
금정구 712
 
1.3%
기장군 711
 
1.3%
남구 667
 
1.2%
수영구 619
 
1.1%
Other values (7196) 35506
64.0%
2024-03-23T14:34:52.074660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48248
 
17.6%
1 15505
 
5.7%
부 11896
 
4.4%
산 11862
 
4.3%
광 10759
 
3.9%
시 10602
 
3.9%
역 10127
 
3.7%
구 9754
 
3.6%
로 9339
 
3.4%
동 8507
 
3.1%
Other values (566) 126776
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161701
59.1%
Decimal Number 50887
 
18.6%
Space Separator 48248
 
17.6%
Open Punctuation 4806
 
1.8%
Close Punctuation 4802
 
1.8%
Dash Punctuation 2035
 
0.7%
Other Punctuation 528
 
0.2%
Uppercase Letter 303
 
0.1%
Lowercase Letter 35
 
< 0.1%
Math Symbol 28
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 11896
 
7.4%
산 11862
 
7.3%
광 10759
 
6.7%
시 10602
 
6.6%
역 10127
 
6.3%
구 9754
 
6.0%
로 9339
 
5.8%
동 8507
 
5.3%
층 5243
 
3.2%
길 4982
 
3.1%
Other values (505) 68630
42.4%
Uppercase Letter
ValueCountFrequency (%)
B 109
36.0%
A 75
24.8%
C 32
 
10.6%
S 15
 
5.0%
E 11
 
3.6%
G 10
 
3.3%
K 9
 
3.0%
D 7
 
2.3%
I 4
 
1.3%
W 4
 
1.3%
Other values (12) 27
 
8.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
17.1%
a 4
11.4%
o 4
11.4%
b 3
8.6%
r 3
8.6%
c 2
 
5.7%
d 2
 
5.7%
n 2
 
5.7%
l 2
 
5.7%
k 1
 
2.9%
Other values (6) 6
17.1%
Decimal Number
ValueCountFrequency (%)
1 15505
30.5%
2 7102
14.0%
3 4961
 
9.7%
0 4580
 
9.0%
4 3883
 
7.6%
5 3510
 
6.9%
6 3297
 
6.5%
7 2857
 
5.6%
8 2726
 
5.4%
9 2466
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 506
95.8%
/ 15
 
2.8%
@ 6
 
1.1%
& 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 4803
99.9%
（ 3
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 4799
99.9%
） 3
 
0.1%
Space Separator
ValueCountFrequency (%)
48248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2035
100.0%
Math Symbol
ValueCountFrequency (%)
~ 28
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161701
59.1%
Common 111335
40.7%
Latin 339
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 11896
 
7.4%
산 11862
 
7.3%
광 10759
 
6.7%
시 10602
 
6.6%
역 10127
 
6.3%
구 9754
 
6.0%
로 9339
 
5.8%
동 8507
 
5.3%
층 5243
 
3.2%
길 4982
 
3.1%
Other values (505) 68630
42.4%
Latin
ValueCountFrequency (%)
B 109
32.2%
A 75
22.1%
C 32
 
9.4%
S 15
 
4.4%
E 11
 
3.2%
G 10
 
2.9%
K 9
 
2.7%
D 7
 
2.1%
e 6
 
1.8%
a 4
 
1.2%
Other values (29) 61
18.0%
Common
ValueCountFrequency (%)
48248
43.3%
1 15505
 
13.9%
2 7102
 
6.4%
3 4961
 
4.5%
( 4803
 
4.3%
) 4799
 
4.3%
0 4580
 
4.1%
4 3883
 
3.5%
5 3510
 
3.2%
6 3297
 
3.0%
Other values (12) 10647
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161699
59.1%
ASCII 111667
40.8%
None 6
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48248
43.2%
1 15505
 
13.9%
2 7102
 
6.4%
3 4961
 
4.4%
( 4803
 
4.3%
) 4799
 
4.3%
0 4580
 
4.1%
4 3883
 
3.5%
5 3510
 
3.1%
6 3297
 
3.0%
Other values (48) 10979
 
9.8%
Hangul
ValueCountFrequency (%)
부 11896
 
7.4%
산 11862
 
7.3%
광 10759
 
6.7%
시 10602
 
6.6%
역 10127
 
6.3%
구 9754
 
6.0%
로 9339
 
5.8%
동 8507
 
5.3%
층 5243
 
3.2%
길 4982
 
3.1%
Other values (503) 68628
42.4%
None
ValueCountFrequency (%)
） 3
50.0%
（ 3
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
50.0%
ㅎ 1
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

지번주소
Text

MISSING 

Distinct8216
Distinct (%)86.3%
Missing476
Missing (%)4.8%
Memory size156.2 KiB
2024-03-23T14:34:52.642833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length19.619698
Min length14

Characters and Unicode

Total characters186858
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

Unique7337 ?
Unique (%)77.0%

Sample

1st row부산광역시 기장군 기장읍 시랑리 717
2nd row부산광역시 부산진구 부전동 473-11
3rd row부산광역시 북구 구포동 932-34
4th row부산광역시 강서구 명지동 3578-3
5th row부산광역시 해운대구 반송동 257-306
ValueCountFrequency (%)
부산광역시 9521
24.5%
부산진구 1050
 
2.7%
해운대구 906
 
2.3%
동래구 758
 
2.0%
사하구 741
 
1.9%
금정구 693
 
1.8%
기장군 678
 
1.7%
남구 627
 
1.6%
수영구 588
 
1.5%
연제구 575
 
1.5%
Other values (7504) 22674
58.4%
2024-03-23T14:34:53.466893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29287
15.7%
부 11231
 
6.0%
산 11156
 
6.0%
동 10193
 
5.5%
광 9877
 
5.3%
시 9542
 
5.1%
역 9521
 
5.1%
구 9141
 
4.9%
1 8770
 
4.7%
- 8433
 
4.5%
Other values (143) 69707
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 106822
57.2%
Decimal Number 42316
 
22.6%
Space Separator 29287
 
15.7%
Dash Punctuation 8433
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 11231
 
10.5%
산 11156
 
10.4%
동 10193
 
9.5%
광 9877
 
9.2%
시 9542
 
8.9%
역 9521
 
8.9%
구 9141
 
8.6%
대 1704
 
1.6%
사 1505
 
1.4%
장 1405
 
1.3%
Other values (131) 31547
29.5%
Decimal Number
ValueCountFrequency (%)
1 8770
20.7%
2 5637
13.3%
3 5047
11.9%
4 4291
10.1%
5 3971
9.4%
6 3157
 
7.5%
7 3116
 
7.4%
8 2954
 
7.0%
9 2704
 
6.4%
0 2669
 
6.3%
Space Separator
ValueCountFrequency (%)
29287
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8433
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 106822
57.2%
Common 80036
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 11231
 
10.5%
산 11156
 
10.4%
동 10193
 
9.5%
광 9877
 
9.2%
시 9542
 
8.9%
역 9521
 
8.9%
구 9141
 
8.6%
대 1704
 
1.6%
사 1505
 
1.4%
장 1405
 
1.3%
Other values (131) 31547
29.5%
Common
ValueCountFrequency (%)
29287
36.6%
1 8770
 
11.0%
- 8433
 
10.5%
2 5637
 
7.0%
3 5047
 
6.3%
4 4291
 
5.4%
5 3971
 
5.0%
6 3157
 
3.9%
7 3116
 
3.9%
8 2954
 
3.7%
Other values (2) 5373
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 106822
57.2%
ASCII 80036
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29287
36.6%
1 8770
 
11.0%
- 8433
 
10.5%
2 5637
 
7.0%
3 5047
 
6.3%
4 4291
 
5.4%
5 3971
 
5.0%
6 3157
 
3.9%
7 3116
 
3.9%
8 2954
 
3.7%
Other values (2) 5373
 
6.7%
Hangul
ValueCountFrequency (%)
부 11231
 
10.5%
산 11156
 
10.4%
동 10193
 
9.5%
광 9877
 
9.2%
시 9542
 
8.9%
역 9521
 
8.9%
구 9141
 
8.6%
대 1704
 
1.6%
사 1505
 
1.4%
장 1405
 
1.3%
Other values (131) 31547
29.5%

업종
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
5632 
일반대중음식
1907 
편의점
874 
중식
 
442
제과점
 
319
Other values (7)
826 

Length

Max length8
Median length2
Mean length2.9739
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 5632
56.3%
일반대중음식 1907
 
19.1%
편의점 874
 
8.7%
중식 442
 
4.4%
제과점 319
 
3.2%
패스트푸드 285
 
2.9%
양식 278
 
2.8%
일식 246
 
2.5%
식품잡화 8
 
0.1%
할인점/슈퍼마켓 7
 
0.1%
Other values (2) 2
 
< 0.1%

Length

2024-03-23T14:34:53.771226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 5632
56.3%
일반대중음식 1907
 
19.1%
편의점 874
 
8.7%
중식 442
 
4.4%
제과점 319
 
3.2%
패스트푸드 285
 
2.8%
양식 278
 
2.8%
일식 246
 
2.5%
식품잡화 8
 
0.1%
할인점/슈퍼마켓 7
 
0.1%
Other values (3) 3
 
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8535
Distinct (%)86.4%
Missing116
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean35.168356
Minimum35.010967
Maximum37.572667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T14:34:53.983930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.010967
5-th percentile35.082782
Q135.125938
median35.163777
Q335.201902
95-th percentile35.267324
Maximum37.572667
Range2.5617005
Interquartile range (IQR)0.075963872

Descriptive statistics

Standard deviation0.072012852
Coefficient of variation (CV)0.0020476605
Kurtosis370.0258
Mean35.168356
Median Absolute Deviation (MAD)0.03805593
Skewness11.449026
Sum347604.03
Variance0.0051858508
MonotonicityNot monotonic
2024-03-23T14:34:54.400962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.09672134 12
 
0.1%
35.13422946 12
 
0.1%
35.20380872 11
 
0.1%
35.14649173 11
 
0.1%
35.16957683 11
 
0.1%
35.17097556 10
 
0.1%
35.16844803 9
 
0.1%
35.1359161 9
 
0.1%
35.09478173 9
 
0.1%
35.32239475 7
 
0.1%
Other values (8525) 9783
97.8%
(Missing) 116
 
1.2%
ValueCountFrequency (%)
35.01096703 1
< 0.1%
35.01198933 1
< 0.1%
35.01476797 2
< 0.1%
35.0154644 1
< 0.1%
35.01592407 1
< 0.1%
35.02522976 1
< 0.1%
35.02817726 1
< 0.1%
35.03043202 1
< 0.1%
35.03060049 1
< 0.1%
35.03233883 1
< 0.1%
ValueCountFrequency (%)
37.57266749 2
< 0.1%
37.54399651 1
< 0.1%
35.38287021 1
< 0.1%
35.37752494 1
< 0.1%
35.3748328 1
< 0.1%
35.37196103 1
< 0.1%
35.37106944 1
< 0.1%
35.37025568 1
< 0.1%
35.36994466 1
< 0.1%
35.36985784 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8514
Distinct (%)86.1%
Missing116
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean129.06406
Minimum126.94748
Maximum129.28541
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T14:34:54.659772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.94748
5-th percentile128.94868
Q1129.01725
median129.0685
Q3129.10832
95-th percentile129.18524
Maximum129.28541
Range2.3379276
Interquartile range (IQR)0.091067725

Descriptive statistics

Standard deviation0.082909975
Coefficient of variation (CV)0.00064239396
Kurtosis122.87547
Mean129.06406
Median Absolute Deviation (MAD)0.04404765
Skewness-4.914246
Sum1275669.2
Variance0.006874064
MonotonicityNot monotonic
2024-03-23T14:34:54.894922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0286701 13
 
0.1%
129.1112168 12
 
0.1%
129.0859386 11
 
0.1%
129.0658548 11
 
0.1%
129.1776778 11
 
0.1%
129.1776689 10
 
0.1%
129.1793931 9
 
0.1%
129.0995849 9
 
0.1%
128.9068742 9
 
0.1%
129.1759468 7
 
0.1%
Other values (8504) 9782
97.8%
(Missing) 116
 
1.2%
ValueCountFrequency (%)
126.9474812 1
< 0.1%
126.9811143 2
< 0.1%
128.8105451 1
< 0.1%
128.8117637 1
< 0.1%
128.8124822 1
< 0.1%
128.8136439 1
< 0.1%
128.8158021 1
< 0.1%
128.816317 1
< 0.1%
128.8252323 1
< 0.1%
128.8256978 1
< 0.1%
ValueCountFrequency (%)
129.2854088 2
< 0.1%
129.2845874 1
< 0.1%
129.2836646 1
< 0.1%
129.2833477 1
< 0.1%
129.2833191 1
< 0.1%
129.2832072 1
< 0.1%
129.2829303 2
< 0.1%
129.2826562 1
< 0.1%
129.2824052 1
< 0.1%
129.28222 1
< 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
2024-03-23T14:34:55.133816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:34:55.370973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-03-23T14:34:47.855274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:34:47.491870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:34:48.006135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:34:47.690512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T14:34:55.516109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종위도경도
업종1.0000.6890.630
위도0.6891.0000.686
경도0.6300.6861.000
2024-03-23T14:34:56.099898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종
위도1.0000.5290.410
경도0.5291.0000.337
업종0.4100.3371.000

Missing values

2024-03-23T14:34:48.233995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T14:34:48.571657image/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.
2024-03-23T14:34:48.828448image/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
121572024-03-20무봉리토종순대국 오시리아점부산광역시 기장군 기장읍 기장해안로 172 107호부산광역시 기장군 기장읍 시랑리 717한식35.192018129.2177682023-02-16
214002024-03-20씨유서면직통로점부산광역시 부산진구 신천대로162번길 91 (부전동)부산광역시 부산진구 부전동 473-11편의점35.154001129.054522021-06-16
297402024-03-20지에스(GS25) 구포대교점부산광역시 북구 백양대로1063번길 1 1층부산광역시 북구 구포동 932-34편의점35.200116128.9971312021-08-14
236612024-03-20오리마루 명지본점부산광역시 강서구 명지국제6로1번가길 15 1층부산광역시 강서구 명지동 3578-3한식35.095967128.9008322023-05-31
21662024-03-20감포식당부산광역시 해운대구 아랫반송로23번길 37 (반송동)부산광역시 해운대구 반송동 257-306한식35.225274129.1497632021-06-16
300152024-03-20진례추어탕부산광역시 동래구 충렬대로108번길 89 1층부산광역시 동래구 온천동 1459-3한식35.202859129.0737332021-06-16
360262024-03-20해양각부산광역시 서구 구덕로124번길 59 (토성동1가)부산광역시 서구 토성동1가 14-11중식35.099336129.0226282021-06-16
179402024-03-20세븐일레븐 부산광역시해운대주공점부산광역시 해운대구 좌3동 1282번지 주공단지분산상가 102호 103호부산광역시 해운대구 좌3동 1282편의점35.175592129.1705172021-06-16
38982024-03-20국수나라부산광역시 남구 천제등로 30 1(일부)층(대연동)부산광역시 남구 대연동 898-2한식35.132979129.0885212021-08-03
100822024-03-20류센소부산광역시 수영구 남천바다로33번길 27 1층 (광안동)부산광역시 수영구 광안동 202-7일식35.149685129.1146942021-06-16
데이터작성일자가맹점명칭도로명주소지번주소업종위도경도가맹점기준일자
221412024-03-20양정서울칼국수부산광역시 부산진구 동평로 418 (양정동)부산광역시 부산진구 양정동 370-22한식35.173087129.0703392021-06-16
51692024-03-20꼬꼬번피자치킨 주례점부산광역시 사상구 진사로 16-1 1층부산광역시 사상구 주례동 52-151일반대중음식35.149994129.0161172022-11-16
122852024-03-20문토스트 시청점부산광역시 연제구 연제로 30 201동 B105호부산광역시 연제구 연산동 2362일반대중음식35.179266129.0769592021-08-12
250292024-03-20욱이수육부산광역시 동구 진성로9번길 58 .<NA>한식<NA><NA>2023-12-22
365362024-03-20혜화동 돈까스극장부산광역시 연제구 미남로 11 1층 (거제동)부산광역시 연제구 거제동 203-15한식35.195096129.0717542021-06-16
130612024-03-20바다사랑횟집부산광역시 금정구 장전온천천로 81 (장전동)부산광역시 금정구 장전동 394-5한식35.232257129.0887372021-06-16
30132024-03-20고봉민김밥인 부산광역시용호성모점부산광역시 남구 용주로 36 301동104호부산광역시 남구 용호동 549-1한식35.112614129.113232023-01-31
3902024-03-20(주)코리아세븐부산광역시범곡점부산광역시 동구 망양로 964 (범일동)부산광역시 동구 범일동 1306-9편의점35.141775129.0546442022-11-30
245982024-03-20용소천부산광역시 남구 용호로110번길 10 용소천 (용호동)부산광역시 남구 용호동 80-33한식35.122538129.1116862021-06-16
160442024-03-20사루각20부산광역시 부산진구 서전로68번길 78 지하1층 101호부산광역시 부산진구 전포동 340-38한식35.154277129.0671172022-03-09

Duplicate rows

Most frequently occurring

데이터작성일자가맹점명칭도로명주소지번주소업종위도경도가맹점기준일자# duplicates
02024-03-20고기맛집부산광역시 기장군 일광읍 해빛6로 75-6 1층부산광역시 기장군 일광읍 삼성리 840-9한식35.264443129.2263432023-08-042
12024-03-20고봉김밥부산광역시 기장군 정관면 정관6로 3 우성스마트시티 103호부산광역시 기장군 정관읍 매학리 718-1한식35.320694129.1746392022-09-082
22024-03-20금수저부산광역시 기장군 정관읍 정관로 569 1층 107호부산광역시 기장군 정관읍 매학리 713-4한식35.321705129.1762542022-12-142
32024-03-20낙지명가 아낙촌부산광역시 기장군 정관읍 산단4로 153-40 3층부산광역시 기장군 정관읍 달산리 1222-3한식35.320668129.1903852022-08-202
42024-03-20네네치킨&봉구스밥버거부산광역시 기장군 일광읍 해빛3로 122 1층 102호(디바인스퀘어 상가)부산광역시 기장군 일광읍 삼성리 779일반대중음식35.266911129.2223012022-07-052
52024-03-20노랑통닭 정관점부산광역시 기장군 정관읍 구연3로 5 101호(신세계빌딩)부산광역시 기장군 정관읍 매학리 751-8일반대중음식35.320499129.1810352022-04-302
62024-03-20더숲부산광역시 기장군 장안읍 장안로 28 1층부산광역시 기장군 장안읍 기룡리 453-2한식35.343227129.2524122022-10-292
72024-03-20두텁삼부산광역시 기장군 정관읍 구연3로 15 .부산광역시 기장군 정관읍 매학리 751-4한식35.321089129.1815562022-08-302
82024-03-20롯데지알에스(주)부산광역시 강서구 공항진입로 108 (대저2동)<NA>양식<NA><NA>2023-08-262
92024-03-20마카오미 마라탕부산광역시 기장군 정관읍 정관6로 3 1층 107호부산광역시 기장군 정관읍 매학리 718-1중식35.320694129.1746392022-09-152