Overview

Dataset statistics

Number of variables7
Number of observations766
Missing cells44
Missing cells (%)0.8%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory43.5 KiB
Average record size in memory58.2 B

Variable types

Text3
Categorical2
Numeric2

Dataset

Description경상남도 김해시 관내 아동급식지원 가맹점 현황에 대한 자료로 가맹점명, 가맹점구분, 지번주소, 도로명주소, 위도, 경도 데이터로 구성되어 있습니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033422/fileData.do

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
비고 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
가맹점구분 is highly overall correlated with 비고High correlation
위도 is highly overall correlated with 비고High correlation
경도 is highly overall correlated with 비고High correlation
비고 is highly imbalanced (68.8%)Imbalance
지번주소 has 43 (5.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 22:44:17.527240
Analysis finished2023-12-12 22:44:19.071711
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가맹점명
Text

Distinct752
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2023-12-13T07:44:19.281567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length9.6605744
Min length2

Characters and Unicode

Total characters7400
Distinct characters434
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

Unique739 ?
Unique (%)96.5%

Sample

1st row코끼리가 반한 핫도그&와플
2nd row짜장119
3rd row아이러브피자앤치킨 동김해점
4th row김밥일번지(삼정점)
5th row롯데지알에스(주)_롯데리아 김해장유점
ValueCountFrequency (%)
cu 107
 
10.7%
미니스톱 26
 
2.6%
하나로마트 10
 
1.0%
파리바게뜨 9
 
0.9%
김밥천국 5
 
0.5%
뚜레쥬르 5
 
0.5%
장유점 5
 
0.5%
맘스터치 4
 
0.4%
김해진영점 4
 
0.4%
59쌀피자 3
 
0.3%
Other values (792) 822
82.2%
2023-12-13T07:44:19.775614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 573
 
7.7%
김 330
 
4.5%
해 301
 
4.1%
( 299
 
4.0%
) 298
 
4.0%
236
 
3.2%
븐 208
 
2.8%
C 183
 
2.5%
U 180
 
2.4%
2 174
 
2.4%
Other values (424) 4618
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5447
73.6%
Uppercase Letter 718
 
9.7%
Decimal Number 373
 
5.0%
Open Punctuation 299
 
4.0%
Close Punctuation 298
 
4.0%
Space Separator 236
 
3.2%
Lowercase Letter 14
 
0.2%
Other Punctuation 12
 
0.2%
Connector Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 573
 
10.5%
김 330
 
6.1%
해 301
 
5.5%
븐 208
 
3.8%
장 126
 
2.3%
일 124
 
2.3%
레 117
 
2.1%
유 113
 
2.1%
동 113
 
2.1%
세 107
 
2.0%
Other values (380) 3335
61.2%
Uppercase Letter
ValueCountFrequency (%)
C 183
25.5%
U 180
25.1%
S 167
23.3%
G 165
23.0%
R 5
 
0.7%
K 4
 
0.6%
D 2
 
0.3%
I 2
 
0.3%
B 2
 
0.3%
E 1
 
0.1%
Other values (7) 7
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
21.4%
r 2
14.3%
a 2
14.3%
t 1
 
7.1%
s 1
 
7.1%
c 1
 
7.1%
d 1
 
7.1%
o 1
 
7.1%
h 1
 
7.1%
y 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 174
46.6%
5 172
46.1%
1 9
 
2.4%
9 8
 
2.1%
4 4
 
1.1%
3 3
 
0.8%
0 1
 
0.3%
7 1
 
0.3%
6 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
& 9
75.0%
' 2
 
16.7%
. 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 299
100.0%
Close Punctuation
ValueCountFrequency (%)
) 298
100.0%
Space Separator
ValueCountFrequency (%)
236
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5447
73.6%
Common 1221
 
16.5%
Latin 732
 
9.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 573
 
10.5%
김 330
 
6.1%
해 301
 
5.5%
븐 208
 
3.8%
장 126
 
2.3%
일 124
 
2.3%
레 117
 
2.1%
유 113
 
2.1%
동 113
 
2.1%
세 107
 
2.0%
Other values (380) 3335
61.2%
Latin
ValueCountFrequency (%)
C 183
25.0%
U 180
24.6%
S 167
22.8%
G 165
22.5%
R 5
 
0.7%
K 4
 
0.5%
e 3
 
0.4%
D 2
 
0.3%
I 2
 
0.3%
r 2
 
0.3%
Other values (17) 19
 
2.6%
Common
ValueCountFrequency (%)
( 299
24.5%
) 298
24.4%
236
19.3%
2 174
14.3%
5 172
14.1%
1 9
 
0.7%
& 9
 
0.7%
9 8
 
0.7%
4 4
 
0.3%
3 3
 
0.2%
Other values (7) 9
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5447
73.6%
ASCII 1953
 
26.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 573
 
10.5%
김 330
 
6.1%
해 301
 
5.5%
븐 208
 
3.8%
장 126
 
2.3%
일 124
 
2.3%
레 117
 
2.1%
유 113
 
2.1%
동 113
 
2.1%
세 107
 
2.0%
Other values (380) 3335
61.2%
ASCII
ValueCountFrequency (%)
( 299
15.3%
) 298
15.3%
236
12.1%
C 183
9.4%
U 180
9.2%
2 174
8.9%
5 172
8.8%
S 167
8.6%
G 165
8.4%
1 9
 
0.5%
Other values (34) 70
 
3.6%

가맹점구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
식당
259 
BGF리테일(CU)
181 
GS리테일
164 
세븐일레븐
104 
미니스톱
26 
Other values (3)
32 

Length

Max length10
Median length5
Mean length5.0822454
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식당 259
33.8%
BGF리테일(CU) 181
23.6%
GS리테일 164
21.4%
세븐일레븐 104
13.6%
미니스톱 26
 
3.4%
하나로마트 16
 
2.1%
슈퍼 13
 
1.7%
일반편의점 3
 
0.4%

Length

2023-12-13T07:44:19.973244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:44:20.127404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식당 259
33.8%
bgf리테일(cu 181
23.6%
gs리테일 164
21.4%
세븐일레븐 104
13.6%
미니스톱 26
 
3.4%
하나로마트 16
 
2.1%
슈퍼 13
 
1.7%
일반편의점 3
 
0.4%

지번주소
Text

MISSING 

Distinct674
Distinct (%)93.2%
Missing43
Missing (%)5.6%
Memory size6.1 KiB
2023-12-13T07:44:20.402737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length36
Mean length20.820194
Min length15

Characters and Unicode

Total characters15053
Distinct characters240
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique634 ?
Unique (%)87.7%

Sample

1st row경상남도 김해시 삼정동 197-15
2nd row경상남도 김해시 대청동 285-8
3rd row경상남도 김해시 삼방동 199-5
4th row경상남도 김해시 삼정동 196-14
5th row경상남도 김해시 부곡동 1161-12
ValueCountFrequency (%)
경상남도 723
22.2%
김해시 722
22.2%
진영읍 82
 
2.5%
외동 57
 
1.7%
삼계동 56
 
1.7%
삼방동 52
 
1.6%
진영리 51
 
1.6%
내동 43
 
1.3%
삼정동 38
 
1.2%
율하동 33
 
1.0%
Other values (869) 1402
43.0%
2023-12-13T07:44:20.886905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2536
16.8%
1 877
 
5.8%
상 791
 
5.3%
해 733
 
4.9%
김 732
 
4.9%
시 731
 
4.9%
남 725
 
4.8%
경 724
 
4.8%
도 724
 
4.8%
동 652
 
4.3%
Other values (230) 5828
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8672
57.6%
Decimal Number 3221
 
21.4%
Space Separator 2536
 
16.8%
Dash Punctuation 612
 
4.1%
Uppercase Letter 6
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Letter Number 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 791
 
9.1%
해 733
 
8.5%
김 732
 
8.4%
시 731
 
8.4%
남 725
 
8.4%
경 724
 
8.3%
도 724
 
8.3%
동 652
 
7.5%
삼 175
 
2.0%
리 163
 
1.9%
Other values (208) 2522
29.1%
Decimal Number
ValueCountFrequency (%)
1 877
27.2%
2 311
 
9.7%
3 303
 
9.4%
6 294
 
9.1%
4 285
 
8.8%
5 279
 
8.7%
0 250
 
7.8%
7 214
 
6.6%
8 208
 
6.5%
9 200
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
33.3%
I 1
16.7%
T 1
16.7%
Q 1
16.7%
D 1
16.7%
Space Separator
ValueCountFrequency (%)
2536
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 612
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8672
57.6%
Common 6372
42.3%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 791
 
9.1%
해 733
 
8.5%
김 732
 
8.4%
시 731
 
8.4%
남 725
 
8.4%
경 724
 
8.3%
도 724
 
8.3%
동 652
 
7.5%
삼 175
 
2.0%
리 163
 
1.9%
Other values (208) 2522
29.1%
Common
ValueCountFrequency (%)
2536
39.8%
1 877
 
13.8%
- 612
 
9.6%
2 311
 
4.9%
3 303
 
4.8%
6 294
 
4.6%
4 285
 
4.5%
5 279
 
4.4%
0 250
 
3.9%
7 214
 
3.4%
Other values (5) 411
 
6.5%
Latin
ValueCountFrequency (%)
e 2
22.2%
S 2
22.2%
Ⅰ 1
11.1%
I 1
11.1%
T 1
11.1%
Q 1
11.1%
D 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8672
57.6%
ASCII 6380
42.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2536
39.7%
1 877
 
13.7%
- 612
 
9.6%
2 311
 
4.9%
3 303
 
4.7%
6 294
 
4.6%
4 285
 
4.5%
5 279
 
4.4%
0 250
 
3.9%
7 214
 
3.4%
Other values (11) 419
 
6.6%
Hangul
ValueCountFrequency (%)
상 791
 
9.1%
해 733
 
8.5%
김 732
 
8.4%
시 731
 
8.4%
남 725
 
8.4%
경 724
 
8.3%
도 724
 
8.3%
동 652
 
7.5%
삼 175
 
2.0%
리 163
 
1.9%
Other values (208) 2522
29.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명주소
Text

Distinct712
Distinct (%)93.1%
Missing1
Missing (%)0.1%
Memory size6.1 KiB
2023-12-13T07:44:21.285831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length26.464052
Min length8

Characters and Unicode

Total characters20245
Distinct characters278
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

Unique703 ?
Unique (%)91.9%

Sample

1st row경상남도 김해시 활천로36번길 33 (삼정동)1층
2nd row경상남도 김해시 계동로 157 (대청동)
3rd row경상남도 김해시 삼안로 169-1 (삼방동)
4th row경상남도 김해시 활천로36번길 27-9 (삼정동)103호
5th row경상남도 김해시 능동로167번길 1 (부곡동)
ValueCountFrequency (%)
경상남도 765
 
19.4%
김해시 764
 
19.3%
진영읍 70
 
1.8%
삼계동 28
 
0.7%
김해대로 25
 
0.6%
삼방동 24
 
0.6%
2 22
 
0.6%
외동 22
 
0.6%
1층 21
 
0.5%
진영리 21
 
0.5%
Other values (1080) 2190
55.4%
2023-12-13T07:44:21.767503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3205
 
15.8%
1 1009
 
5.0%
해 870
 
4.3%
상 861
 
4.3%
김 847
 
4.2%
남 773
 
3.8%
시 772
 
3.8%
경 770
 
3.8%
도 767
 
3.8%
로 715
 
3.5%
Other values (268) 9656
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12099
59.8%
Decimal Number 3610
 
17.8%
Space Separator 3205
 
15.8%
Open Punctuation 521
 
2.6%
Close Punctuation 521
 
2.6%
Dash Punctuation 147
 
0.7%
Other Punctuation 120
 
0.6%
Uppercase Letter 18
 
0.1%
Lowercase Letter 2
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 870
 
7.2%
상 861
 
7.1%
김 847
 
7.0%
남 773
 
6.4%
시 772
 
6.4%
경 770
 
6.4%
도 767
 
6.3%
로 715
 
5.9%
동 597
 
4.9%
번 396
 
3.3%
Other values (240) 4731
39.1%
Decimal Number
ValueCountFrequency (%)
1 1009
28.0%
2 529
14.7%
3 364
 
10.1%
0 320
 
8.9%
4 307
 
8.5%
5 254
 
7.0%
9 230
 
6.4%
6 219
 
6.1%
7 213
 
5.9%
8 165
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 5
27.8%
S 3
16.7%
I 3
16.7%
D 2
 
11.1%
C 1
 
5.6%
P 1
 
5.6%
Q 1
 
5.6%
T 1
 
5.6%
K 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 118
98.3%
/ 2
 
1.7%
Space Separator
ValueCountFrequency (%)
3205
100.0%
Open Punctuation
ValueCountFrequency (%)
( 521
100.0%
Close Punctuation
ValueCountFrequency (%)
) 521
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12099
59.8%
Common 8125
40.1%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 870
 
7.2%
상 861
 
7.1%
김 847
 
7.0%
남 773
 
6.4%
시 772
 
6.4%
경 770
 
6.4%
도 767
 
6.3%
로 715
 
5.9%
동 597
 
4.9%
번 396
 
3.3%
Other values (240) 4731
39.1%
Common
ValueCountFrequency (%)
3205
39.4%
1 1009
 
12.4%
2 529
 
6.5%
( 521
 
6.4%
) 521
 
6.4%
3 364
 
4.5%
0 320
 
3.9%
4 307
 
3.8%
5 254
 
3.1%
9 230
 
2.8%
Other values (7) 865
 
10.6%
Latin
ValueCountFrequency (%)
B 5
23.8%
S 3
14.3%
I 3
14.3%
e 2
 
9.5%
D 2
 
9.5%
Ⅰ 1
 
4.8%
C 1
 
4.8%
P 1
 
4.8%
Q 1
 
4.8%
T 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12099
59.8%
ASCII 8145
40.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3205
39.3%
1 1009
 
12.4%
2 529
 
6.5%
( 521
 
6.4%
) 521
 
6.4%
3 364
 
4.5%
0 320
 
3.9%
4 307
 
3.8%
5 254
 
3.1%
9 230
 
2.8%
Other values (17) 885
 
10.9%
Hangul
ValueCountFrequency (%)
해 870
 
7.2%
상 861
 
7.1%
김 847
 
7.0%
남 773
 
6.4%
시 772
 
6.4%
경 770
 
6.4%
도 767
 
6.3%
로 715
 
5.9%
동 597
 
4.9%
번 396
 
3.3%
Other values (240) 4731
39.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct667
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.240204
Minimum35.156332
Maximum35.48747
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2023-12-13T07:44:21.928156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.156332
5-th percentile35.172887
Q135.222473
median35.236731
Q335.262367
95-th percentile35.308614
Maximum35.48747
Range0.33113841
Interquartile range (IQR)0.039893883

Descriptive statistics

Standard deviation0.039755098
Coefficient of variation (CV)0.0011281177
Kurtosis1.4195583
Mean35.240204
Median Absolute Deviation (MAD)0.02437211
Skewness0.4389959
Sum26993.996
Variance0.0015804678
MonotonicityNot monotonic
2023-12-13T07:44:22.070806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.2730789 43
 
5.6%
35.1563315808 6
 
0.8%
35.23718005 3
 
0.4%
35.30660759 3
 
0.4%
35.23667014 3
 
0.4%
35.30805685 3
 
0.4%
35.23489095 2
 
0.3%
35.16955596 2
 
0.3%
35.23425349 2
 
0.3%
35.19185733 2
 
0.3%
Other values (657) 697
91.0%
ValueCountFrequency (%)
35.1563315808 6
0.8%
35.16441439 1
 
0.1%
35.16747137 1
 
0.1%
35.16755385 1
 
0.1%
35.16767772 1
 
0.1%
35.16812085 1
 
0.1%
35.16884603 1
 
0.1%
35.16903231 1
 
0.1%
35.16904289 1
 
0.1%
35.16939315 1
 
0.1%
ValueCountFrequency (%)
35.48746999 1
0.1%
35.37366261 1
0.1%
35.32704945 1
0.1%
35.3265703 1
0.1%
35.32414464 1
0.1%
35.32396628 1
0.1%
35.32134624 1
0.1%
35.32019286 1
0.1%
35.31930923 1
0.1%
35.31910676 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct667
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.84393
Minimum128.70796
Maximum128.99815
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2023-12-13T07:44:22.222793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70796
5-th percentile128.73359
Q1128.80685
median128.86139
Q3128.8811
95-th percentile128.91227
Maximum128.99815
Range0.2901959
Interquartile range (IQR)0.074244834

Descriptive statistics

Standard deviation0.055208876
Coefficient of variation (CV)0.0004284942
Kurtosis-0.22300467
Mean128.84393
Median Absolute Deviation (MAD)0.04013685
Skewness-0.52616497
Sum98694.448
Variance0.00304802
MonotonicityNot monotonic
2023-12-13T07:44:22.381883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8613894 43
 
5.6%
128.8722452618 6
 
0.8%
128.8597911 3
 
0.4%
128.7252002 3
 
0.4%
128.8678351 3
 
0.4%
128.7345095 3
 
0.4%
128.8521594 2
 
0.3%
128.814232 2
 
0.3%
128.8673674 2
 
0.3%
128.8040813 2
 
0.3%
Other values (657) 697
91.0%
ValueCountFrequency (%)
128.7079577 1
 
0.1%
128.7186226 1
 
0.1%
128.718831 1
 
0.1%
128.7192045 1
 
0.1%
128.7200694 1
 
0.1%
128.7201775 1
 
0.1%
128.7214842 1
 
0.1%
128.7236815 1
 
0.1%
128.7238298 1
 
0.1%
128.7252002 3
0.4%
ValueCountFrequency (%)
128.9981536 1
0.1%
128.9934031 1
0.1%
128.9859937 1
0.1%
128.9852366 1
0.1%
128.9799823 1
0.1%
128.9677497 1
0.1%
128.9675689 1
0.1%
128.9629322 1
0.1%
128.9493551 1
0.1%
128.9479032 1
0.1%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
<NA>
723 
인근좌표
 
43

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 723
94.4%
인근좌표 43
 
5.6%

Length

2023-12-13T07:44:22.499291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:44:22.609476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 723
94.4%
인근좌표 43
 
5.6%

Interactions

2023-12-13T07:44:18.446486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:44:18.212222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:44:18.572784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:44:18.331358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:44:22.679187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점구분위도경도
가맹점구분1.0000.3010.275
위도0.3011.0000.752
경도0.2750.7521.000
2023-12-13T07:44:22.755002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고가맹점구분
비고1.0001.000
가맹점구분1.0001.000
2023-12-13T07:44:22.847639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도가맹점구분비고
위도1.0000.0030.1041.000
경도0.0031.0000.1351.000
가맹점구분0.1040.1351.0001.000
비고1.0001.0001.0001.000

Missing values

2023-12-13T07:44:18.725851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:44:18.877535image/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.
2023-12-13T07:44:19.007692image/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

가맹점명가맹점구분지번주소도로명주소위도경도비고
0코끼리가 반한 핫도그&와플식당경상남도 김해시 삼정동 197-15경상남도 김해시 활천로36번길 33 (삼정동)1층35.23258128.896464<NA>
1짜장119식당경상남도 김해시 대청동 285-8경상남도 김해시 계동로 157 (대청동)35.188596128.795744<NA>
2아이러브피자앤치킨 동김해점식당경상남도 김해시 삼방동 199-5경상남도 김해시 삼안로 169-1 (삼방동)35.243411128.912731<NA>
3김밥일번지(삼정점)식당경상남도 김해시 삼정동 196-14경상남도 김해시 활천로36번길 27-9 (삼정동)103호35.232185128.895608<NA>
4롯데지알에스(주)_롯데리아 김해장유점식당경상남도 김해시 부곡동 1161-12경상남도 김해시 능동로167번길 1 (부곡동)35.203192128.808971<NA>
5맛있는분식식당경상남도 김해시 대청동 332-2 대청프라자경상남도 김해시 대청로 121 (대청동, 대청프라자)B동 213호35.185768128.797912<NA>
6임창정의 대단한갈비 김해진영점식당경상남도 김해시 진영읍 진영리 1630-2경상남도 김해시 진영읍 장등로 34 (진영리)1층35.30934128.735482<NA>
7맘스터치 김해주촌점식당경상남도 김해시 주촌면 천곡리 1524-7경상남도 김해시 주촌면 천곡로 14 (천곡리)104호35.233963128.838207<NA>
8동대문떡볶이 동떡 내외동점식당경상남도 김해시 내동 161-11경상남도 김해시 금관대로1297번길 2 (내동)35.240209128.861482<NA>
9중화분식식당경상남도 김해시 진영읍 진영리 326-90경상남도 김해시 진영읍 진영로109번길 6 (진영리)35.304348128.725499<NA>
가맹점명가맹점구분지번주소도로명주소위도경도비고
756봉구스밥버거진영점식당경상남도 김해시 진영읍 진영리 1605-5 103호경상남도 김해시 진영읍 김해대로361번길 3 103호35.307133128.729205<NA>
757통큰할매돼지국밥식당경상남도 김해시 삼정동 595-1경상남도 김해시 활천로36번길 22-46(삼정동)35.231656128.897819<NA>
758삼방가야밀면식당경상남도 김해시 삼방동 186-2경상남도 김해시 활천로267번길 38 (삼방동)35.246358128.908456<NA>
759세븐일레븐(김해활천점)세븐일레븐경상남도 김해시 어방동 1093-1 1층경상남도 김해시 분성로517번길 6-435.235931128.902711<NA>
760GS25진영래온빌점GS리테일경상남도 김해시 진영읍 진영리 1555 1층경상남도 김해시 진영읍 김해대로332번길 37-435.305536128.72383<NA>
761상동농협 매리지점 하나로마트하나로마트경상남도 김해시 상동면 매리 93-3경상남도 김해시 동북로 48535.315943128.96775<NA>
762CU(삼방해피점)BGF리테일(CU)경상남도 김해시 삼방동 579-1경상남도 김해시 삼안로255번길 3135.250128128.906466<NA>
763GS25김해인덕점GS리테일경상남도 김해시 삼방동 160-7경상남도 김해시 인제로200(삼방동 160-7)35.246541128.904081<NA>
764CU(김해부원점)BGF리테일(CU)경상남도 김해시 부원동 610-7경상남도 김해시 김해대로2355번길 3735.229904128.883362<NA>
765CU(더큰외동점)BGF리테일(CU)경상남도 김해시 외동 1263-5경상남도 김해시 분성로 20835.230198128.869625<NA>

Duplicate rows

Most frequently occurring

가맹점명가맹점구분지번주소도로명주소위도경도비고# duplicates
0GS25(진영터미널점)GS리테일경상남도 김해시 진영읍 여래리 711-1경상남도 김해시 진영읍 진영로 215 (여래리)35.302759128.736483<NA>2