Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells4731
Missing cells (%)7.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory556.6 KiB
Average record size in memory57.0 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description전라북도 군산시 소재한 군산사랑상품권 가맹점현황에 대한 데이터로 업종,상호,주소,행정동,유선전화번호 등이 포함되어 있습니다.
Author전라북도 군산시
URLhttps://www.data.go.kr/data/15077590/fileData.do

Alerts

전화번호 has 4731 (47.3%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:21:29.121535
Analysis finished2023-12-12 10:21:31.276414
Duration2.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5750.0821
Minimum1
Maximum11466
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:21:31.429449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile569.95
Q12857.75
median5769.5
Q38630.25
95-th percentile10892.05
Maximum11466
Range11465
Interquartile range (IQR)5772.5

Descriptive statistics

Standard deviation3319.954
Coefficient of variation (CV)0.57737506
Kurtosis-1.2087143
Mean5750.0821
Median Absolute Deviation (MAD)2886
Skewness-0.011499059
Sum57500821
Variance11022095
MonotonicityNot monotonic
2023-12-12T19:21:31.740888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10601 1
 
< 0.1%
9291 1
 
< 0.1%
7397 1
 
< 0.1%
910 1
 
< 0.1%
7199 1
 
< 0.1%
8400 1
 
< 0.1%
11074 1
 
< 0.1%
6402 1
 
< 0.1%
10985 1
 
< 0.1%
7817 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
11466 1
< 0.1%
11465 1
< 0.1%
11464 1
< 0.1%
11462 1
< 0.1%
11461 1
< 0.1%
11460 1
< 0.1%
11459 1
< 0.1%
11458 1
< 0.1%
11457 1
< 0.1%
11456 1
< 0.1%

업종
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
소매업
4078 
음식점업
3094 
개인서비스업
1673 
교육서비스업
 
372
제조업
 
325
Other values (4)
458 

Length

Max length11
Median length6
Mean length3.9344
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인서비스업
2nd row소매업
3rd row소매업
4th row개인서비스업
5th row개인서비스업

Common Values

ValueCountFrequency (%)
소매업 4078
40.8%
음식점업 3094
30.9%
개인서비스업 1673
16.7%
교육서비스업 372
 
3.7%
제조업 325
 
3.2%
보건업 247
 
2.5%
기타 125
 
1.2%
숙박업 56
 
0.6%
스포츠여가관련서비스업 30
 
0.3%

Length

2023-12-12T19:21:32.184508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:21:32.386758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소매업 4078
40.8%
음식점업 3094
30.9%
개인서비스업 1673
16.7%
교육서비스업 372
 
3.7%
제조업 325
 
3.2%
보건업 247
 
2.5%
기타 125
 
1.2%
숙박업 56
 
0.6%
스포츠여가관련서비스업 30
 
0.3%

상호
Text

Distinct9602
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:21:32.864749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length6.3374
Min length1

Characters and Unicode

Total characters63374
Distinct characters1042
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

Unique9372 ?
Unique (%)93.7%

Sample

1st row더샤인
2nd row씨엠씨
3rd row옥구농협 옥서지점
4th row화려한외출미용실
5th row아이리스헤어
ValueCountFrequency (%)
노점 88
 
0.7%
유한회사 75
 
0.6%
군산점 52
 
0.4%
주식회사 46
 
0.4%
나운점 45
 
0.4%
수송점 39
 
0.3%
군산수송점 38
 
0.3%
gs25 37
 
0.3%
아모레카운셀러 36
 
0.3%
세븐일레븐 28
 
0.2%
Other values (10141) 11262
95.9%
2023-12-12T19:21:33.571979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1755
 
2.8%
산 1671
 
2.6%
점 1492
 
2.4%
이 1181
 
1.9%
군 1104
 
1.7%
스 1048
 
1.7%
원 953
 
1.5%
수 920
 
1.5%
리 870
 
1.4%
사 778
 
1.2%
Other values (1032) 51602
81.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57756
91.1%
Space Separator 1755
 
2.8%
Uppercase Letter 1157
 
1.8%
Decimal Number 669
 
1.1%
Close Punctuation 600
 
0.9%
Lowercase Letter 600
 
0.9%
Open Punctuation 592
 
0.9%
Other Punctuation 176
 
0.3%
Other Symbol 49
 
0.1%
Dash Punctuation 14
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 1671
 
2.9%
점 1492
 
2.6%
이 1181
 
2.0%
군 1104
 
1.9%
스 1048
 
1.8%
원 953
 
1.7%
수 920
 
1.6%
리 870
 
1.5%
사 778
 
1.3%
어 742
 
1.3%
Other values (952) 46997
81.4%
Uppercase Letter
ValueCountFrequency (%)
S 133
 
11.5%
G 100
 
8.6%
E 85
 
7.3%
A 74
 
6.4%
O 73
 
6.3%
C 70
 
6.1%
T 59
 
5.1%
B 59
 
5.1%
M 52
 
4.5%
N 50
 
4.3%
Other values (15) 402
34.7%
Lowercase Letter
ValueCountFrequency (%)
a 67
 
11.2%
e 66
 
11.0%
o 55
 
9.2%
i 44
 
7.3%
n 39
 
6.5%
t 33
 
5.5%
m 33
 
5.5%
r 32
 
5.3%
l 30
 
5.0%
s 27
 
4.5%
Other values (15) 174
29.0%
Other Punctuation
ValueCountFrequency (%)
& 49
27.8%
. 41
23.3%
, 36
20.5%
; 18
 
10.2%
' 9
 
5.1%
? 7
 
4.0%
# 6
 
3.4%
/ 3
 
1.7%
! 3
 
1.7%
· 2
 
1.1%
Decimal Number
ValueCountFrequency (%)
2 189
28.3%
5 124
18.5%
1 79
11.8%
4 59
 
8.8%
3 50
 
7.5%
0 46
 
6.9%
9 45
 
6.7%
7 28
 
4.2%
8 25
 
3.7%
6 24
 
3.6%
Close Punctuation
ValueCountFrequency (%)
) 599
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 591
99.8%
[ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1755
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57791
91.2%
Common 3812
 
6.0%
Latin 1757
 
2.8%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 1671
 
2.9%
점 1492
 
2.6%
이 1181
 
2.0%
군 1104
 
1.9%
스 1048
 
1.8%
원 953
 
1.6%
수 920
 
1.6%
리 870
 
1.5%
사 778
 
1.3%
어 742
 
1.3%
Other values (947) 47032
81.4%
Latin
ValueCountFrequency (%)
S 133
 
7.6%
G 100
 
5.7%
E 85
 
4.8%
A 74
 
4.2%
O 73
 
4.2%
C 70
 
4.0%
a 67
 
3.8%
e 66
 
3.8%
T 59
 
3.4%
B 59
 
3.4%
Other values (40) 971
55.3%
Common
ValueCountFrequency (%)
1755
46.0%
) 599
 
15.7%
( 591
 
15.5%
2 189
 
5.0%
5 124
 
3.3%
1 79
 
2.1%
4 59
 
1.5%
3 50
 
1.3%
& 49
 
1.3%
0 46
 
1.2%
Other values (19) 271
 
7.1%
Han
ValueCountFrequency (%)
生 9
64.3%
秀 1
 
7.1%
李 1
 
7.1%
作 1
 
7.1%
家 1
 
7.1%
月 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57742
91.1%
ASCII 5567
 
8.8%
None 51
 
0.1%
CJK 14
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1755
31.5%
) 599
 
10.8%
( 591
 
10.6%
2 189
 
3.4%
S 133
 
2.4%
5 124
 
2.2%
G 100
 
1.8%
E 85
 
1.5%
1 79
 
1.4%
A 74
 
1.3%
Other values (68) 1838
33.0%
Hangul
ValueCountFrequency (%)
산 1671
 
2.9%
점 1492
 
2.6%
이 1181
 
2.0%
군 1104
 
1.9%
스 1048
 
1.8%
원 953
 
1.7%
수 920
 
1.6%
리 870
 
1.5%
사 778
 
1.3%
어 742
 
1.3%
Other values (946) 46983
81.4%
None
ValueCountFrequency (%)
㈜ 49
96.1%
· 2
 
3.9%
CJK
ValueCountFrequency (%)
生 9
64.3%
秀 1
 
7.1%
李 1
 
7.1%
作 1
 
7.1%
家 1
 
7.1%
月 1
 
7.1%

주소
Text

Distinct8353
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:21:34.009344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length54
Mean length22.1086
Min length8

Characters and Unicode

Total characters221086
Distinct characters390
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

Unique7523 ?
Unique (%)75.2%

Sample

1st row전라북도 군산시 문화로 147(수송동)
2nd row전라북도 군산시 해망로 362-4(해망동)
3rd row전라북도 군산시 옥서면 옥구저수지로 213
4th row전라북도 군산시 설림3길 23
5th row전라북도 군산시 미장남로 10(미장동, 군산미장아이파크), 1층101호 군산아이파크
ValueCountFrequency (%)
전라북도 9999
22.0%
군산시 9993
22.0%
1층 811
 
1.8%
월명로 343
 
0.8%
대학로 340
 
0.7%
수송로 297
 
0.7%
대야면 248
 
0.5%
나운동 231
 
0.5%
공단대로 224
 
0.5%
신금길 213
 
0.5%
Other values (5785) 22797
50.1%
2023-12-12T19:21:34.692385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35537
 
16.1%
산 10990
 
5.0%
북 10512
 
4.8%
도 10361
 
4.7%
시 10319
 
4.7%
군 10127
 
4.6%
전 10081
 
4.6%
라 10029
 
4.5%
1 9097
 
4.1%
동 8206
 
3.7%
Other values (380) 95827
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133195
60.2%
Space Separator 35537
 
16.1%
Decimal Number 34469
 
15.6%
Close Punctuation 6412
 
2.9%
Open Punctuation 6412
 
2.9%
Other Punctuation 2935
 
1.3%
Dash Punctuation 2016
 
0.9%
Uppercase Letter 67
 
< 0.1%
Math Symbol 22
 
< 0.1%
Lowercase Letter 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 10990
 
8.3%
북 10512
 
7.9%
도 10361
 
7.8%
시 10319
 
7.7%
군 10127
 
7.6%
전 10081
 
7.6%
라 10029
 
7.5%
동 8206
 
6.2%
로 5347
 
4.0%
길 4204
 
3.2%
Other values (337) 43019
32.3%
Uppercase Letter
ValueCountFrequency (%)
A 19
28.4%
B 17
25.4%
C 10
14.9%
D 4
 
6.0%
G 4
 
6.0%
S 2
 
3.0%
E 2
 
3.0%
K 2
 
3.0%
U 1
 
1.5%
M 1
 
1.5%
Other values (5) 5
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 9097
26.4%
2 5247
15.2%
3 4039
11.7%
4 2975
 
8.6%
0 2939
 
8.5%
5 2413
 
7.0%
6 2216
 
6.4%
7 1954
 
5.7%
8 1909
 
5.5%
9 1680
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 10
50.0%
g 3
 
15.0%
i 2
 
10.0%
n 1
 
5.0%
d 1
 
5.0%
l 1
 
5.0%
v 1
 
5.0%
c 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 2596
88.4%
. 326
 
11.1%
? 12
 
0.4%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
35537
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6412
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6412
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2016
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133196
60.2%
Common 87803
39.7%
Latin 87
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 10990
 
8.3%
북 10512
 
7.9%
도 10361
 
7.8%
시 10319
 
7.7%
군 10127
 
7.6%
전 10081
 
7.6%
라 10029
 
7.5%
동 8206
 
6.2%
로 5347
 
4.0%
길 4204
 
3.2%
Other values (338) 43020
32.3%
Latin
ValueCountFrequency (%)
A 19
21.8%
B 17
19.5%
C 10
11.5%
e 10
11.5%
D 4
 
4.6%
G 4
 
4.6%
g 3
 
3.4%
S 2
 
2.3%
E 2
 
2.3%
i 2
 
2.3%
Other values (13) 14
16.1%
Common
ValueCountFrequency (%)
35537
40.5%
1 9097
 
10.4%
) 6412
 
7.3%
( 6412
 
7.3%
2 5247
 
6.0%
3 4039
 
4.6%
4 2975
 
3.4%
0 2939
 
3.3%
, 2596
 
3.0%
5 2413
 
2.7%
Other values (9) 10136
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133195
60.2%
ASCII 87890
39.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35537
40.4%
1 9097
 
10.4%
) 6412
 
7.3%
( 6412
 
7.3%
2 5247
 
6.0%
3 4039
 
4.6%
4 2975
 
3.4%
0 2939
 
3.3%
, 2596
 
3.0%
5 2413
 
2.7%
Other values (32) 10223
 
11.6%
Hangul
ValueCountFrequency (%)
산 10990
 
8.3%
북 10512
 
7.9%
도 10361
 
7.8%
시 10319
 
7.7%
군 10127
 
7.6%
전 10081
 
7.6%
라 10029
 
7.5%
동 8206
 
6.2%
로 5347
 
4.0%
길 4204
 
3.2%
Other values (337) 43019
32.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

전화번호
Text

MISSING 

Distinct5041
Distinct (%)95.7%
Missing4731
Missing (%)47.3%
Memory size156.2 KiB
2023-12-12T19:21:35.100335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters63228
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

Unique4863 ?
Unique (%)92.3%

Sample

1st row063-468-7376
2nd row063-446-0269
3rd row063-451-6888
4th row063-465-0561
5th row063-445-3582
ValueCountFrequency (%)
063-462-3690 36
 
0.7%
063-461-5850 5
 
0.1%
063-462-2131 4
 
0.1%
063-452-1543 3
 
0.1%
063-453-8883 3
 
0.1%
063-471-9919 3
 
0.1%
063-467-1273 3
 
0.1%
063-471-4383 3
 
0.1%
063-466-0467 3
 
0.1%
063-464-6670 3
 
0.1%
Other values (5031) 5203
98.7%
2023-12-12T19:21:35.693501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 10538
16.7%
6 10524
16.6%
4 8462
13.4%
0 8266
13.1%
3 7914
12.5%
5 3814
 
6.0%
2 3228
 
5.1%
1 3071
 
4.9%
7 2822
 
4.5%
8 2516
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52690
83.3%
Dash Punctuation 10538
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 10524
20.0%
4 8462
16.1%
0 8266
15.7%
3 7914
15.0%
5 3814
 
7.2%
2 3228
 
6.1%
1 3071
 
5.8%
7 2822
 
5.4%
8 2516
 
4.8%
9 2073
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 10538
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 10538
16.7%
6 10524
16.6%
4 8462
13.4%
0 8266
13.1%
3 7914
12.5%
5 3814
 
6.0%
2 3228
 
5.1%
1 3071
 
4.9%
7 2822
 
4.5%
8 2516
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 10538
16.7%
6 10524
16.6%
4 8462
13.4%
0 8266
13.1%
3 7914
12.5%
5 3814
 
6.0%
2 3228
 
5.1%
1 3071
 
4.9%
7 2822
 
4.5%
8 2516
 
4.0%

행정동
Text

Distinct84
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:21:35.987360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.8892
Min length1

Characters and Unicode

Total characters28892
Distinct characters87
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)0.2%

Sample

1st row수송동
2nd row해신동
3rd row옥서면
4th row소룡동
5th row수송동
ValueCountFrequency (%)
수송동 1604
16.0%
1379
13.8%
조촌동 626
 
6.3%
소룡동 577
 
5.8%
나운3동 576
 
5.8%
월명동 539
 
5.4%
중앙동 536
 
5.4%
나운2동 508
 
5.1%
나운1동 499
 
5.0%
흥남동 438
 
4.4%
Other values (75) 2719
27.2%
2023-12-12T19:21:36.504416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 7826
27.1%
나 1827
 
6.3%
운 1802
 
6.2%
수 1656
 
5.7%
송 1610
 
5.6%
- 1379
 
4.8%
면 710
 
2.5%
조 626
 
2.2%
촌 626
 
2.2%
룡 622
 
2.2%
Other values (77) 10208
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25904
89.7%
Decimal Number 1607
 
5.6%
Dash Punctuation 1379
 
4.8%
Space Separator 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7826
30.2%
나 1827
 
7.1%
운 1802
 
7.0%
수 1656
 
6.4%
송 1610
 
6.2%
면 710
 
2.7%
조 626
 
2.4%
촌 626
 
2.4%
룡 622
 
2.4%
소 578
 
2.2%
Other values (71) 8021
31.0%
Decimal Number
ValueCountFrequency (%)
3 585
36.4%
2 512
31.9%
1 510
31.7%
Dash Punctuation
ValueCountFrequency (%)
- 1379
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25904
89.7%
Common 2988
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7826
30.2%
나 1827
 
7.1%
운 1802
 
7.0%
수 1656
 
6.4%
송 1610
 
6.2%
면 710
 
2.7%
조 626
 
2.4%
촌 626
 
2.4%
룡 622
 
2.4%
소 578
 
2.2%
Other values (71) 8021
31.0%
Common
ValueCountFrequency (%)
- 1379
46.2%
3 585
19.6%
2 512
 
17.1%
1 510
 
17.1%
1
 
< 0.1%
? 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25904
89.7%
ASCII 2988
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 7826
30.2%
나 1827
 
7.1%
운 1802
 
7.0%
수 1656
 
6.4%
송 1610
 
6.2%
면 710
 
2.7%
조 626
 
2.4%
촌 626
 
2.4%
룡 622
 
2.4%
소 578
 
2.2%
Other values (71) 8021
31.0%
ASCII
ValueCountFrequency (%)
- 1379
46.2%
3 585
19.6%
2 512
 
17.1%
1 510
 
17.1%
1
 
< 0.1%
? 1
 
< 0.1%

Interactions

2023-12-12T19:21:30.606847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:21:36.628289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종행정동
번호1.0000.1400.516
업종0.1401.0000.378
행정동0.5160.3781.000
2023-12-12T19:21:36.755029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종
번호1.0000.064
업종0.0641.000

Missing values

2023-12-12T19:21:30.809532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:21:31.143940image/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.

Sample

번호업종상호주소전화번호행정동
1060010601개인서비스업더샤인전라북도 군산시 문화로 147(수송동)063-468-7376수송동
74467447소매업씨엠씨전라북도 군산시 해망로 362-4(해망동)<NA>해신동
20492050소매업옥구농협 옥서지점전라북도 군산시 옥서면 옥구저수지로 213<NA>옥서면
51525153개인서비스업화려한외출미용실전라북도 군산시 설림3길 23063-446-0269소룡동
44814482개인서비스업아이리스헤어전라북도 군산시 미장남로 10(미장동, 군산미장아이파크), 1층101호 군산아이파크063-451-6888수송동
91889189개인서비스업휴앤미전라북도 군산시 수송안9길 17(수송동.코갭3)063-465-0561수송동
28192820소매업캠핑고래 군산점전라북도 군산시 내항1길 23(장미동), 1층<NA>장미동
28782879소매업삼보컴퓨터중앙점전라북도 군산시 중앙로 92 (중앙로2가)063-445-3582중앙동
60026003개인서비스업윤미용실전라북도 군산시 옥서면 산동길 27-17063-465-3040옥서면
53755376음식점업시골부뚜막전라북도 군산시 성산면 십자들로 167063-445-7072성산면
번호업종상호주소전화번호행정동
1018110182개인서비스업황금이용원전라북도 군산시 소룡안1길 47<NA>미성동
1102511026개인서비스업샤네일전라북도 군산시 문화2길 47(문화동)<NA>신풍동
84578458음식점업리에또쿠치나전라북도 군산시 부골2길 39(조촌동)063-451-8817조촌동
40224023개인서비스업비앤에이치(B&H)클린119전라북도 군산시 번영로 14(경장동)<NA>경장동
1022810229교육서비스업라시움어학원전라북도 군산시 나운동 340-17063-467-1605나운2동
1071010711소매업아모레카운셀러전라북도 군산시 나운로 4063-462-3690신풍동
66616662소매업윤여사반찬전라북도 군산시 서수송2길 36063-466-8837나운2동
95359536음식점업등촌칼국수 군산점전라북도 군산시 나운4길 7-5063-471-4471나운2동
41504151개인서비스업이룩스터디카페전라북도 군산시 황룡로 27(미룡동), 3동 2층 201호<NA>-
16381639소매업쉬끄 랑데부전라북도 군산시 신지길 51(지곡동), 1층<NA>지곡동