Overview

Dataset statistics

Number of variables9
Number of observations399
Missing cells137
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.6 KiB
Average record size in memory73.3 B

Variable types

Numeric1
Categorical4
Text4

Dataset

Description안양시 만안구 종량제물품 판매소 목록(업체명, 주소 등)
Author안양시시설관리공단
URLhttps://www.data.go.kr/data/15056045/fileData.do

Alerts

관리지역 has constant value ""Constant
번호 is highly overall correlated with 행정동 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
법정동 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
분류 is highly imbalanced (92.3%)Imbalance
지정번호 has 133 (33.3%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:13:30.415942
Analysis finished2023-12-11 23:13:31.520979
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct399
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200
Minimum1
Maximum399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-12T08:13:31.609391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.9
Q1100.5
median200
Q3299.5
95-th percentile379.1
Maximum399
Range398
Interquartile range (IQR)199

Descriptive statistics

Standard deviation115.32563
Coefficient of variation (CV)0.57662813
Kurtosis-1.2
Mean200
Median Absolute Deviation (MAD)100
Skewness0
Sum79800
Variance13300
MonotonicityStrictly increasing
2023-12-12T08:13:31.788835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
264 1
 
0.3%
274 1
 
0.3%
273 1
 
0.3%
272 1
 
0.3%
271 1
 
0.3%
270 1
 
0.3%
269 1
 
0.3%
268 1
 
0.3%
267 1
 
0.3%
Other values (389) 389
97.5%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
399 1
0.3%
398 1
0.3%
397 1
0.3%
396 1
0.3%
395 1
0.3%
394 1
0.3%
393 1
0.3%
392 1
0.3%
391 1
0.3%
390 1
0.3%

분류
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
판매처
393 
구입처
 
5
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0025063
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
판매처 393
98.5%
구입처 5
 
1.3%
<NA> 1
 
0.3%

Length

2023-12-12T08:13:31.982121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:13:32.095635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
판매처 393
98.5%
구입처 5
 
1.3%
na 1
 
0.3%

거래처명
Text

Distinct393
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T08:13:32.327378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.0576441
Min length3

Characters and Unicode

Total characters2816
Distinct characters305
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique388 ?
Unique (%)97.2%

Sample

1st row365플러스안양박달점
2nd row강남마트
3rd row건국슈퍼
4th row디마트
5th row땡백화점
ValueCountFrequency (%)
세븐일레븐 5
 
1.2%
지에스25 4
 
0.9%
우리마트 3
 
0.7%
이마트24 3
 
0.7%
영광슈퍼 2
 
0.5%
행운마트 2
 
0.5%
하나로할인마트 2
 
0.5%
안양일번가점 2
 
0.5%
한라마트 2
 
0.5%
미니스톱 2
 
0.5%
Other values (397) 397
93.6%
2023-12-12T08:13:32.807280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 180
 
6.4%
안 156
 
5.5%
양 142
 
5.0%
마 125
 
4.4%
트 121
 
4.3%
스 91
 
3.2%
2 76
 
2.7%
지 70
 
2.5%
에 67
 
2.4%
5 63
 
2.2%
Other values (295) 1725
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2598
92.3%
Decimal Number 174
 
6.2%
Space Separator 26
 
0.9%
Uppercase Letter 7
 
0.2%
Close Punctuation 6
 
0.2%
Open Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 180
 
6.9%
안 156
 
6.0%
양 142
 
5.5%
마 125
 
4.8%
트 121
 
4.7%
스 91
 
3.5%
지 70
 
2.7%
에 67
 
2.6%
퍼 61
 
2.3%
슈 58
 
2.2%
Other values (280) 1527
58.8%
Decimal Number
ValueCountFrequency (%)
2 76
43.7%
5 63
36.2%
4 16
 
9.2%
6 7
 
4.0%
3 6
 
3.4%
8 3
 
1.7%
9 2
 
1.1%
1 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
G 2
28.6%
C 2
28.6%
D 2
28.6%
L 1
14.3%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2598
92.3%
Common 211
 
7.5%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 180
 
6.9%
안 156
 
6.0%
양 142
 
5.5%
마 125
 
4.8%
트 121
 
4.7%
스 91
 
3.5%
지 70
 
2.7%
에 67
 
2.6%
퍼 61
 
2.3%
슈 58
 
2.2%
Other values (280) 1527
58.8%
Common
ValueCountFrequency (%)
2 76
36.0%
5 63
29.9%
26
 
12.3%
4 16
 
7.6%
6 7
 
3.3%
3 6
 
2.8%
) 6
 
2.8%
( 5
 
2.4%
8 3
 
1.4%
9 2
 
0.9%
Latin
ValueCountFrequency (%)
G 2
28.6%
C 2
28.6%
D 2
28.6%
L 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2598
92.3%
ASCII 218
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 180
 
6.9%
안 156
 
6.0%
양 142
 
5.5%
마 125
 
4.8%
트 121
 
4.7%
스 91
 
3.5%
지 70
 
2.7%
에 67
 
2.6%
퍼 61
 
2.3%
슈 58
 
2.2%
Other values (280) 1527
58.8%
ASCII
ValueCountFrequency (%)
2 76
34.9%
5 63
28.9%
26
 
11.9%
4 16
 
7.3%
6 7
 
3.2%
3 6
 
2.8%
) 6
 
2.8%
( 5
 
2.3%
8 3
 
1.4%
G 2
 
0.9%
Other values (5) 8
 
3.7%

행정동
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
안양2동
49 
안양6동
42 
석수2동
36 
안양1동
33 
안양4동
29 
Other values (9)
210 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row박달1동
2nd row박달1동
3rd row박달1동
4th row박달1동
5th row박달1동

Common Values

ValueCountFrequency (%)
안양2동 49
12.3%
안양6동 42
10.5%
석수2동 36
9.0%
안양1동 33
8.3%
안양4동 29
 
7.3%
안양5동 29
 
7.3%
박달1동 28
 
7.0%
석수1동 28
 
7.0%
안양3동 24
 
6.0%
안양7동 23
 
5.8%
Other values (4) 78
19.5%

Length

2023-12-12T08:13:32.948924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안양2동 49
12.3%
안양6동 42
10.5%
석수2동 36
9.0%
안양1동 33
8.3%
안양4동 29
 
7.3%
안양5동 29
 
7.3%
박달1동 28
 
7.0%
석수1동 28
 
7.0%
안양3동 24
 
6.0%
안양7동 23
 
5.8%
Other values (4) 78
19.5%

법정동
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
안양동
270 
석수동
78 
박달동
50 
귀인동
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
안양동 270
67.7%
석수동 78
 
19.5%
박달동 50
 
12.5%
귀인동 1
 
0.3%

Length

2023-12-12T08:13:33.086696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:13:33.211222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안양동 270
67.7%
석수동 78
 
19.5%
박달동 50
 
12.5%
귀인동 1
 
0.3%

관리지역
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
만안구
399 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
만안구 399
100.0%

Length

2023-12-12T08:13:33.322493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:13:33.414932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
만안구 399
100.0%

대표
Text

Distinct378
Distinct (%)95.2%
Missing2
Missing (%)0.5%
Memory size3.2 KiB
2023-12-12T08:13:33.748197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.0806045
Min length2

Characters and Unicode

Total characters1223
Distinct characters166
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique362 ?
Unique (%)91.2%

Sample

1st row김인종
2nd row박용규
3rd row김은옥
4th row하현희
5th row손미영외 1명
ValueCountFrequency (%)
정승인 5
 
1.2%
조지현 2
 
0.5%
김선호 2
 
0.5%
1명 2
 
0.5%
확인 2
 
0.5%
신준민 2
 
0.5%
이정금 2
 
0.5%
이미숙 2
 
0.5%
정명순 2
 
0.5%
박영순 2
 
0.5%
Other values (371) 379
94.3%
2023-12-12T08:13:34.276903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 86
 
7.0%
이 68
 
5.6%
정 53
 
4.3%
영 37
 
3.0%
순 37
 
3.0%
희 26
 
2.1%
성 25
 
2.0%
숙 25
 
2.0%
최 24
 
2.0%
진 21
 
1.7%
Other values (156) 821
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1209
98.9%
Space Separator 7
 
0.6%
Decimal Number 4
 
0.3%
Other Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 86
 
7.1%
이 68
 
5.6%
정 53
 
4.4%
영 37
 
3.1%
순 37
 
3.1%
희 26
 
2.2%
성 25
 
2.1%
숙 25
 
2.1%
최 24
 
2.0%
진 21
 
1.7%
Other values (151) 807
66.7%
Space Separator
ValueCountFrequency (%)
7
100.0%
Decimal Number
ValueCountFrequency (%)
1 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1209
98.9%
Common 14
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 86
 
7.1%
이 68
 
5.6%
정 53
 
4.4%
영 37
 
3.1%
순 37
 
3.1%
희 26
 
2.2%
성 25
 
2.1%
숙 25
 
2.1%
최 24
 
2.0%
진 21
 
1.7%
Other values (151) 807
66.7%
Common
ValueCountFrequency (%)
7
50.0%
1 4
28.6%
, 1
 
7.1%
) 1
 
7.1%
( 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1209
98.9%
ASCII 14
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 86
 
7.1%
이 68
 
5.6%
정 53
 
4.4%
영 37
 
3.1%
순 37
 
3.1%
희 26
 
2.2%
성 25
 
2.1%
숙 25
 
2.1%
최 24
 
2.0%
진 21
 
1.7%
Other values (151) 807
66.7%
ASCII
ValueCountFrequency (%)
7
50.0%
1 4
28.6%
, 1
 
7.1%
) 1
 
7.1%
( 1
 
7.1%

지정번호
Text

MISSING 

Distinct235
Distinct (%)88.3%
Missing133
Missing (%)33.3%
Memory size3.2 KiB
2023-12-12T08:13:34.500607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.7556391
Min length4

Characters and Unicode

Total characters2329
Distinct characters32
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

Unique212 ?
Unique (%)79.7%

Sample

1st row2016-2
2nd row2013-6
3rd row제2019-1호
4th row제2018-2호
5th row2016-5
ValueCountFrequency (%)
박달2동 5
 
1.8%
2016-1 4
 
1.4%
안양4동 4
 
1.4%
2019-2 4
 
1.4%
2019-3 3
 
1.1%
2016-2 3
 
1.1%
2019-01 3
 
1.1%
2015-04 3
 
1.1%
2014-1 3
 
1.1%
2015-2 3
 
1.1%
Other values (227) 244
87.5%
2023-12-12T08:13:34.900410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 431
18.5%
- 399
17.1%
1 390
16.7%
2 385
16.5%
6 78
 
3.3%
3 70
 
3.0%
안 70
 
3.0%
7 67
 
2.9%
4 67
 
2.9%
9 62
 
2.7%
Other values (22) 310
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1665
71.5%
Dash Punctuation 399
 
17.1%
Other Letter 240
 
10.3%
Space Separator 13
 
0.6%
Lowercase Letter 6
 
0.3%
Other Punctuation 4
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 70
29.2%
동 32
13.3%
석 28
 
11.7%
수 26
 
10.8%
양 22
 
9.2%
호 14
 
5.8%
박 10
 
4.2%
달 10
 
4.2%
오 9
 
3.8%
제 7
 
2.9%
Other values (2) 12
 
5.0%
Decimal Number
ValueCountFrequency (%)
0 431
25.9%
1 390
23.4%
2 385
23.1%
6 78
 
4.7%
3 70
 
4.2%
7 67
 
4.0%
4 67
 
4.0%
9 62
 
3.7%
5 59
 
3.5%
8 56
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
d 2
33.3%
k 1
16.7%
s 1
16.7%
l 1
16.7%
f 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 399
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2083
89.4%
Hangul 240
 
10.3%
Latin 6
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 431
20.7%
- 399
19.2%
1 390
18.7%
2 385
18.5%
6 78
 
3.7%
3 70
 
3.4%
7 67
 
3.2%
4 67
 
3.2%
9 62
 
3.0%
5 59
 
2.8%
Other values (5) 75
 
3.6%
Hangul
ValueCountFrequency (%)
안 70
29.2%
동 32
13.3%
석 28
 
11.7%
수 26
 
10.8%
양 22
 
9.2%
호 14
 
5.8%
박 10
 
4.2%
달 10
 
4.2%
오 9
 
3.8%
제 7
 
2.9%
Other values (2) 12
 
5.0%
Latin
ValueCountFrequency (%)
d 2
33.3%
k 1
16.7%
s 1
16.7%
l 1
16.7%
f 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2089
89.7%
Hangul 240
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 431
20.6%
- 399
19.1%
1 390
18.7%
2 385
18.4%
6 78
 
3.7%
3 70
 
3.4%
7 67
 
3.2%
4 67
 
3.2%
9 62
 
3.0%
5 59
 
2.8%
Other values (10) 81
 
3.9%
Hangul
ValueCountFrequency (%)
안 70
29.2%
동 32
13.3%
석 28
 
11.7%
수 26
 
10.8%
양 22
 
9.2%
호 14
 
5.8%
박 10
 
4.2%
달 10
 
4.2%
오 9
 
3.8%
제 7
 
2.9%
Other values (2) 12
 
5.0%

도로명주소
Text

Distinct388
Distinct (%)97.7%
Missing2
Missing (%)0.5%
Memory size3.2 KiB
2023-12-12T08:13:35.152423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length20.186398
Min length13

Characters and Unicode

Total characters8014
Distinct characters82
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

Unique380 ?
Unique (%)95.7%

Sample

1st row경기 안양시 만안구 양화로 101-4
2nd row경기 안양시 만안구 박달우회로138번길 37
3rd row경기 안양시 만안구 박달로525번길 21
4th row경기 안양시 만안구 양화로136번길 28
5th row경기도 안양시 만안구 양화로136번길 15
ValueCountFrequency (%)
만안구 395
19.9%
안양시 394
19.9%
경기 280
14.1%
경기도 115
 
5.8%
안양로 27
 
1.4%
만안로 22
 
1.1%
냉천로 15
 
0.8%
병목안로 15
 
0.8%
박달로 14
 
0.7%
양화로 11
 
0.6%
Other values (358) 696
35.1%
2023-12-12T08:13:35.480407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1587
19.8%
안 932
11.6%
양 509
 
6.4%
만 424
 
5.3%
경 418
 
5.2%
구 396
 
4.9%
시 395
 
4.9%
기 395
 
4.9%
로 392
 
4.9%
1 308
 
3.8%
Other values (72) 2258
28.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4961
61.9%
Space Separator 1587
 
19.8%
Decimal Number 1436
 
17.9%
Dash Punctuation 30
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 932
18.8%
양 509
10.3%
만 424
8.5%
경 418
8.4%
구 396
8.0%
시 395
8.0%
기 395
8.0%
로 392
7.9%
길 183
 
3.7%
번 182
 
3.7%
Other values (60) 735
14.8%
Decimal Number
ValueCountFrequency (%)
1 308
21.4%
2 210
14.6%
3 162
11.3%
4 155
10.8%
5 133
9.3%
0 107
 
7.5%
7 104
 
7.2%
6 92
 
6.4%
9 87
 
6.1%
8 78
 
5.4%
Space Separator
ValueCountFrequency (%)
1587
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4961
61.9%
Common 3053
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 932
18.8%
양 509
10.3%
만 424
8.5%
경 418
8.4%
구 396
8.0%
시 395
8.0%
기 395
8.0%
로 392
7.9%
길 183
 
3.7%
번 182
 
3.7%
Other values (60) 735
14.8%
Common
ValueCountFrequency (%)
1587
52.0%
1 308
 
10.1%
2 210
 
6.9%
3 162
 
5.3%
4 155
 
5.1%
5 133
 
4.4%
0 107
 
3.5%
7 104
 
3.4%
6 92
 
3.0%
9 87
 
2.8%
Other values (2) 108
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4961
61.9%
ASCII 3053
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1587
52.0%
1 308
 
10.1%
2 210
 
6.9%
3 162
 
5.3%
4 155
 
5.1%
5 133
 
4.4%
0 107
 
3.5%
7 104
 
3.4%
6 92
 
3.0%
9 87
 
2.8%
Other values (2) 108
 
3.5%
Hangul
ValueCountFrequency (%)
안 932
18.8%
양 509
10.3%
만 424
8.5%
경 418
8.4%
구 396
8.0%
시 395
8.0%
기 395
8.0%
로 392
7.9%
길 183
 
3.7%
번 182
 
3.7%
Other values (60) 735
14.8%

Interactions

2023-12-12T08:13:30.935182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:13:35.562202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호분류행정동법정동
번호1.0000.2300.9700.869
분류0.2301.0000.1420.000
행정동0.9700.1421.0000.923
법정동0.8690.0000.9231.000
2023-12-12T08:13:35.650393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동분류행정동
법정동1.0000.0000.794
분류0.0001.0000.109
행정동0.7940.1091.000
2023-12-12T08:13:35.757306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호분류행정동법정동
번호1.0000.1750.8650.723
분류0.1751.0000.1090.000
행정동0.8650.1091.0000.794
법정동0.7230.0000.7941.000

Missing values

2023-12-12T08:13:31.091571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:13:31.262232image/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.
2023-12-12T08:13:31.416315image/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

번호분류거래처명행정동법정동관리지역대표지정번호도로명주소
01판매처365플러스안양박달점박달1동박달동만안구김인종2016-2경기 안양시 만안구 양화로 101-4
12판매처강남마트박달1동박달동만안구박용규2013-6경기 안양시 만안구 박달우회로138번길 37
23판매처건국슈퍼박달1동박달동만안구김은옥<NA>경기 안양시 만안구 박달로525번길 21
34판매처디마트박달1동박달동만안구하현희<NA>경기 안양시 만안구 양화로136번길 28
45판매처땡백화점박달1동박달동만안구손미영외 1명제2019-1호경기도 안양시 만안구 양화로136번길 15
56판매처박달할인마트박달1동박달동만안구이종애제2018-2호경기도 안양시 만안구 박달로545번길 19
67판매처서해수산박달1동박달동만안구이호근2016-5만안구 박달로525번길 46
78판매처성진슈퍼박달1동박달동만안구이복임2016-1경기 안양시 만안구 양화로 121
89판매처세븐일레븐박달희망점박달1동박달동만안구이건숙2012-04-19경기 안양시 만안구 박달로539번길 32
910판매처소망슈퍼박달1동박달동만안구송유옥<NA>경기 안양시 만안구 양화로148번길 59
번호분류거래처명행정동법정동관리지역대표지정번호도로명주소
389390판매처에스마트안양9동안양동만안구김순자<NA>경기 안양시 만안구 병목안로130번길 11
390391판매처에코미스트존안양9동안양동만안구홍순덕2019-01경기도 안양시 만안구 병목안로156번길 24-11
391392판매처우리유통안양9동안양동만안구임서택<NA>경기 안양시 만안구 병목안로 103
392393판매처위드미안양수리산점안양9동안양동만안구임완수2016-02경기 안양시 만안구 창박로 30
393394판매처이마트24안양9동점안양9동안양동만안구최인미2020-01경기도 안양시 만안구 병목안로130번길 120
394395판매처지에스25안양9동점안양9동안양동만안구이혜영2013-02경기 안양시 만안구 병목안로 174
395396판매처지에스25안양나래점안양9동안양동만안구이미숙2016-01경기 안양시 만안구 장내로 40
396397판매처지에스25안양수리산점안양9동안양동만안구김애경2017-03경기 안양시 만안구 창박로 38
397398판매처하이슈퍼안양9동안양동만안구이기두2014-02경기 안양시 만안구 병목안로 158
398399판매처홈마트안양9동안양동만안구최병곤2019-02경기도 안양시 만안구 창박로 41