Overview

Dataset statistics

Number of variables9
Number of observations1495
Missing cells105
Missing cells (%)0.8%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory111.1 KiB
Average record size in memory76.1 B

Variable types

Categorical2
Text3
Numeric4

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
소재지우편번호 is highly overall correlated with 시군명High correlation
WGS84위도 is highly overall correlated with 시군명High correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
소재지도로명주소 has 85 (5.7%) missing valuesMissing

Reproduction

Analysis started2023-12-10 20:59:11.765776
Analysis finished2023-12-10 20:59:17.905621
Duration6.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
안산시
175 
성남시
165 
부천시
156 
수원시
142 
고양시
132 
Other values (23)
725 

Length

Max length4
Median length3
Mean length3.0829431
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안산시 175
11.7%
성남시 165
11.0%
부천시 156
 
10.4%
수원시 142
 
9.5%
고양시 132
 
8.8%
안양시 72
 
4.8%
구리시 65
 
4.3%
의정부시 61
 
4.1%
남양주시 60
 
4.0%
시흥시 57
 
3.8%
Other values (18) 410
27.4%

Length

2023-12-11T05:59:17.999436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안산시 175
11.7%
성남시 165
11.0%
부천시 156
 
10.4%
수원시 142
 
9.5%
고양시 132
 
8.8%
안양시 72
 
4.8%
구리시 65
 
4.3%
의정부시 61
 
4.1%
남양주시 60
 
4.0%
시흥시 57
 
3.8%
Other values (18) 410
27.4%

사업장명
Text

Distinct1106
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T05:59:18.297682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length6.8167224
Min length2

Characters and Unicode

Total characters10191
Distinct characters441
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique904 ?
Unique (%)60.5%

Sample

1st row지엠트랜스
2nd row꽃미남이사
3rd row남북한,일산종합사다리차
4th row(주)스마트무빙
5th rowKT트랜스
ValueCountFrequency (%)
업체명 49
 
3.1%
통인익스프레스 17
 
1.1%
익스프레스 16
 
1.0%
삼성익스프레스 11
 
0.7%
현대익스프레스 10
 
0.6%
주식회사 8
 
0.5%
국제익스프레스 7
 
0.4%
하나익스프레스 7
 
0.4%
쌍용익스프레스 7
 
0.4%
행운익스프레스 6
 
0.4%
Other values (1120) 1434
91.2%
2023-12-11T05:59:18.815541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 1736
 
17.0%
프 785
 
7.7%
레 783
 
7.7%
익 781
 
7.7%
이 355
 
3.5%
사 319
 
3.1%
물 153
 
1.5%
화 123
 
1.2%
주 122
 
1.2%
한 119
 
1.2%
Other values (431) 4915
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9472
92.9%
Uppercase Letter 198
 
1.9%
Decimal Number 147
 
1.4%
Close Punctuation 113
 
1.1%
Open Punctuation 113
 
1.1%
Space Separator 77
 
0.8%
Lowercase Letter 38
 
0.4%
Other Punctuation 23
 
0.2%
Other Symbol 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1736
18.3%
프 785
 
8.3%
레 783
 
8.3%
익 781
 
8.2%
이 355
 
3.7%
사 319
 
3.4%
물 153
 
1.6%
화 123
 
1.3%
주 122
 
1.3%
한 119
 
1.3%
Other values (383) 4196
44.3%
Uppercase Letter
ValueCountFrequency (%)
K 58
29.3%
G 34
17.2%
O 22
 
11.1%
B 21
 
10.6%
S 19
 
9.6%
J 9
 
4.5%
C 8
 
4.0%
T 8
 
4.0%
L 5
 
2.5%
E 4
 
2.0%
Other values (6) 10
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
e 8
21.1%
o 4
10.5%
n 4
10.5%
s 3
 
7.9%
j 3
 
7.9%
c 3
 
7.9%
g 3
 
7.9%
k 2
 
5.3%
y 2
 
5.3%
i 2
 
5.3%
Other values (4) 4
10.5%
Decimal Number
ValueCountFrequency (%)
2 61
41.5%
4 50
34.0%
1 14
 
9.5%
9 5
 
3.4%
5 5
 
3.4%
3 4
 
2.7%
6 3
 
2.0%
8 3
 
2.0%
7 1
 
0.7%
0 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 13
56.5%
& 5
 
21.7%
, 3
 
13.0%
" 2
 
8.7%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%
Space Separator
ValueCountFrequency (%)
77
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9482
93.0%
Common 473
 
4.6%
Latin 236
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1736
18.3%
프 785
 
8.3%
레 783
 
8.3%
익 781
 
8.2%
이 355
 
3.7%
사 319
 
3.4%
물 153
 
1.6%
화 123
 
1.3%
주 122
 
1.3%
한 119
 
1.3%
Other values (384) 4206
44.4%
Latin
ValueCountFrequency (%)
K 58
24.6%
G 34
14.4%
O 22
 
9.3%
B 21
 
8.9%
S 19
 
8.1%
J 9
 
3.8%
C 8
 
3.4%
T 8
 
3.4%
e 8
 
3.4%
L 5
 
2.1%
Other values (20) 44
18.6%
Common
ValueCountFrequency (%)
) 113
23.9%
( 113
23.9%
77
16.3%
2 61
12.9%
4 50
10.6%
1 14
 
3.0%
. 13
 
2.7%
9 5
 
1.1%
& 5
 
1.1%
5 5
 
1.1%
Other values (7) 17
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9472
92.9%
ASCII 709
 
7.0%
None 10
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 1736
18.3%
프 785
 
8.3%
레 783
 
8.3%
익 781
 
8.2%
이 355
 
3.7%
사 319
 
3.4%
물 153
 
1.6%
화 123
 
1.3%
주 122
 
1.3%
한 119
 
1.3%
Other values (383) 4196
44.3%
ASCII
ValueCountFrequency (%)
) 113
15.9%
( 113
15.9%
77
10.9%
2 61
8.6%
K 58
8.2%
4 50
 
7.1%
G 34
 
4.8%
O 22
 
3.1%
B 21
 
3.0%
S 19
 
2.7%
Other values (37) 141
19.9%
None
ValueCountFrequency (%)
㈜ 10
100.0%

인허가일자
Real number (ℝ)

Distinct1008
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20006759
Minimum19840628
Maximum20180807
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T05:59:19.012171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19840628
5-th percentile19930117
Q119971014
median20010616
Q320030918
95-th percentile20090772
Maximum20180807
Range340179
Interquartile range (IQR)59903.5

Descriptive statistics

Standard deviation51994.182
Coefficient of variation (CV)0.0025988308
Kurtosis0.84528844
Mean20006759
Median Absolute Deviation (MAD)29511
Skewness0.21751713
Sum2.9910105 × 1010
Variance2.703395 × 109
MonotonicityNot monotonic
2023-12-11T05:59:19.231046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050413 6
 
0.4%
20020828 6
 
0.4%
20030918 5
 
0.3%
19931130 5
 
0.3%
20040421 5
 
0.3%
20030314 5
 
0.3%
19930925 5
 
0.3%
19921231 5
 
0.3%
20030819 5
 
0.3%
20000530 5
 
0.3%
Other values (998) 1443
96.5%
ValueCountFrequency (%)
19840628 3
0.2%
19841117 1
 
0.1%
19850426 2
0.1%
19850725 2
0.1%
19851206 1
 
0.1%
19880203 1
 
0.1%
19880314 3
0.2%
19880428 1
 
0.1%
19880826 1
 
0.1%
19880912 1
 
0.1%
ValueCountFrequency (%)
20180807 1
0.1%
20180620 1
0.1%
20180531 1
0.1%
20180528 1
0.1%
20180105 1
0.1%
20171206 1
0.1%
20171024 1
0.1%
20170922 1
0.1%
20170920 1
0.1%
20170818 1
0.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
운영중
1161 
폐업 등
334 

Length

Max length4
Median length3
Mean length3.2234114
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 1161
77.7%
폐업 등 334
 
22.3%

Length

2023-12-11T05:59:19.412730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:59:19.554388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 1161
63.5%
폐업 334
 
18.3%
등 334
 
18.3%

소재지도로명주소
Text

MISSING 

Distinct1312
Distinct (%)93.0%
Missing85
Missing (%)5.7%
Memory size11.8 KiB
2023-12-11T05:59:19.987443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length45
Mean length26.260284
Min length13

Characters and Unicode

Total characters37027
Distinct characters389
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

Unique1226 ?
Unique (%)87.0%

Sample

1st row경기도 고양시 일산서구 탄중로 136 (덕이동)
2nd row경기도 고양시 덕양구 화신로 273, 702호 (화정동, 명지프라자)
3rd row경기도 고양시 일산서구 덕이로 30-17 (덕이동)
4th row경기도 고양시 덕양구 동산1로1길 13-16 (동산동, 1층상가)
5th row경기도 고양시 일산동구 은행마을로6번길 86-1 (식사동)
ValueCountFrequency (%)
경기도 1410
 
17.7%
안산시 170
 
2.1%
성남시 158
 
2.0%
부천시 141
 
1.8%
수원시 132
 
1.7%
고양시 128
 
1.6%
상록구 102
 
1.3%
안양시 68
 
0.9%
단원구 68
 
0.9%
1층 64
 
0.8%
Other values (2171) 5520
69.3%
2023-12-11T05:59:20.679071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6554
 
17.7%
시 1493
 
4.0%
경 1465
 
4.0%
도 1462
 
3.9%
기 1441
 
3.9%
1 1421
 
3.8%
로 1273
 
3.4%
동 1186
 
3.2%
( 942
 
2.5%
) 942
 
2.5%
Other values (379) 18848
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21506
58.1%
Space Separator 6554
 
17.7%
Decimal Number 6202
 
16.7%
Open Punctuation 942
 
2.5%
Close Punctuation 942
 
2.5%
Other Punctuation 488
 
1.3%
Dash Punctuation 352
 
1.0%
Uppercase Letter 36
 
0.1%
Lowercase Letter 3
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1493
 
6.9%
경 1465
 
6.8%
도 1462
 
6.8%
기 1441
 
6.7%
로 1273
 
5.9%
동 1186
 
5.5%
길 845
 
3.9%
구 789
 
3.7%
번 658
 
3.1%
안 426
 
2.0%
Other values (347) 10468
48.7%
Uppercase Letter
ValueCountFrequency (%)
A 10
27.8%
B 8
22.2%
I 5
13.9%
L 3
 
8.3%
E 3
 
8.3%
T 2
 
5.6%
F 1
 
2.8%
M 1
 
2.8%
D 1
 
2.8%
N 1
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 1421
22.9%
2 939
15.1%
3 777
12.5%
4 591
9.5%
0 560
 
9.0%
5 476
 
7.7%
6 413
 
6.7%
8 367
 
5.9%
7 349
 
5.6%
9 309
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
r 1
33.3%
a 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 485
99.4%
. 3
 
0.6%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
6554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 942
100.0%
Close Punctuation
ValueCountFrequency (%)
) 942
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 352
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21506
58.1%
Common 15480
41.8%
Latin 41
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1493
 
6.9%
경 1465
 
6.8%
도 1462
 
6.8%
기 1441
 
6.7%
로 1273
 
5.9%
동 1186
 
5.5%
길 845
 
3.9%
구 789
 
3.7%
번 658
 
3.1%
안 426
 
2.0%
Other values (347) 10468
48.7%
Common
ValueCountFrequency (%)
6554
42.3%
1 1421
 
9.2%
( 942
 
6.1%
) 942
 
6.1%
2 939
 
6.1%
3 777
 
5.0%
4 591
 
3.8%
0 560
 
3.6%
, 485
 
3.1%
5 476
 
3.1%
Other values (6) 1793
 
11.6%
Latin
ValueCountFrequency (%)
A 10
24.4%
B 8
19.5%
I 5
12.2%
L 3
 
7.3%
E 3
 
7.3%
T 2
 
4.9%
Ⅲ 1
 
2.4%
e 1
 
2.4%
Ⅱ 1
 
2.4%
F 1
 
2.4%
Other values (6) 6
14.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21506
58.1%
ASCII 15519
41.9%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6554
42.2%
1 1421
 
9.2%
( 942
 
6.1%
) 942
 
6.1%
2 939
 
6.1%
3 777
 
5.0%
4 591
 
3.8%
0 560
 
3.6%
, 485
 
3.1%
5 476
 
3.1%
Other values (20) 1832
 
11.8%
Hangul
ValueCountFrequency (%)
시 1493
 
6.9%
경 1465
 
6.8%
도 1462
 
6.8%
기 1441
 
6.7%
로 1273
 
5.9%
동 1186
 
5.5%
길 845
 
3.9%
구 789
 
3.7%
번 658
 
3.1%
안 426
 
2.0%
Other values (347) 10468
48.7%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
50.0%
Ⅱ 1
50.0%

소재지지번주소
Text

Distinct1367
Distinct (%)92.0%
Missing9
Missing (%)0.6%
Memory size11.8 KiB
2023-12-11T05:59:21.108220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length41
Mean length23.654778
Min length11

Characters and Unicode

Total characters35151
Distinct characters346
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

Unique1258 ?
Unique (%)84.7%

Sample

1st row경기도 고양시 일산서구 덕이동 245-20번지 1층
2nd row경기도 고양시 덕양구 화정동 1002-1번지 명지프라자 702호
3rd row경기도 고양시 일산서구 덕이동 452-3번지
4th row경기도 고양시 덕양구 동산동 356-10번지 1층상가
5th row경기도 고양시 일산동구 식사동 561-3번지
ValueCountFrequency (%)
경기도 1486
 
19.7%
안산시 175
 
2.3%
성남시 165
 
2.2%
부천시 154
 
2.0%
수원시 140
 
1.9%
고양시 131
 
1.7%
상록구 105
 
1.4%
안양시 72
 
1.0%
단원구 70
 
0.9%
구리시 64
 
0.8%
Other values (2090) 4988
66.1%
2023-12-11T05:59:21.646824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6147
 
17.5%
시 1551
 
4.4%
도 1527
 
4.3%
동 1527
 
4.3%
기 1504
 
4.3%
경 1493
 
4.2%
1 1453
 
4.1%
지 1369
 
3.9%
번 1269
 
3.6%
- 1203
 
3.4%
Other values (336) 16108
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20525
58.4%
Decimal Number 7102
 
20.2%
Space Separator 6147
 
17.5%
Dash Punctuation 1203
 
3.4%
Uppercase Letter 49
 
0.1%
Close Punctuation 46
 
0.1%
Open Punctuation 46
 
0.1%
Lowercase Letter 24
 
0.1%
Other Punctuation 7
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1551
 
7.6%
도 1527
 
7.4%
동 1527
 
7.4%
기 1504
 
7.3%
경 1493
 
7.3%
지 1369
 
6.7%
번 1269
 
6.2%
구 804
 
3.9%
안 395
 
1.9%
양 384
 
1.9%
Other values (298) 8702
42.4%
Uppercase Letter
ValueCountFrequency (%)
A 12
24.5%
B 11
22.4%
F 5
10.2%
I 4
 
8.2%
J 4
 
8.2%
M 2
 
4.1%
E 2
 
4.1%
L 2
 
4.1%
T 2
 
4.1%
D 2
 
4.1%
Other values (3) 3
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 1453
20.5%
2 899
12.7%
3 761
10.7%
4 742
10.4%
5 655
9.2%
0 613
8.6%
6 549
 
7.7%
7 549
 
7.7%
8 465
 
6.5%
9 416
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
b 5
20.8%
e 5
20.8%
n 4
16.7%
a 4
16.7%
u 3
12.5%
r 2
 
8.3%
g 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%
Space Separator
ValueCountFrequency (%)
6147
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1203
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20525
58.4%
Common 14551
41.4%
Latin 75
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1551
 
7.6%
도 1527
 
7.4%
동 1527
 
7.4%
기 1504
 
7.3%
경 1493
 
7.3%
지 1369
 
6.7%
번 1269
 
6.2%
구 804
 
3.9%
안 395
 
1.9%
양 384
 
1.9%
Other values (298) 8702
42.4%
Latin
ValueCountFrequency (%)
A 12
16.0%
B 11
14.7%
b 5
 
6.7%
e 5
 
6.7%
F 5
 
6.7%
n 4
 
5.3%
I 4
 
5.3%
J 4
 
5.3%
a 4
 
5.3%
u 3
 
4.0%
Other values (12) 18
24.0%
Common
ValueCountFrequency (%)
6147
42.2%
1 1453
 
10.0%
- 1203
 
8.3%
2 899
 
6.2%
3 761
 
5.2%
4 742
 
5.1%
5 655
 
4.5%
0 613
 
4.2%
6 549
 
3.8%
7 549
 
3.8%
Other values (6) 980
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20525
58.4%
ASCII 14624
41.6%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6147
42.0%
1 1453
 
9.9%
- 1203
 
8.2%
2 899
 
6.1%
3 761
 
5.2%
4 742
 
5.1%
5 655
 
4.5%
0 613
 
4.2%
6 549
 
3.8%
7 549
 
3.8%
Other values (26) 1053
 
7.2%
Hangul
ValueCountFrequency (%)
시 1551
 
7.6%
도 1527
 
7.4%
동 1527
 
7.4%
기 1504
 
7.3%
경 1493
 
7.3%
지 1369
 
6.7%
번 1269
 
6.2%
구 804
 
3.9%
안 395
 
1.9%
양 384
 
1.9%
Other values (298) 8702
42.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct980
Distinct (%)65.9%
Missing9
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean255920.48
Minimum10012
Maximum487882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T05:59:22.091634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10012
5-th percentile10848.25
Q114465
median413808
Q3440210
95-th percentile471038
Maximum487882
Range477870
Interquartile range (IQR)425745

Descriptive statistics

Standard deviation211095.34
Coefficient of variation (CV)0.8248474
Kurtosis-1.9091713
Mean255920.48
Median Absolute Deviation (MAD)54058
Skewness-0.26438111
Sum3.8029783 × 108
Variance4.4561243 × 1010
MonotonicityNot monotonic
2023-12-11T05:59:22.324677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13504 12
 
0.8%
411450 10
 
0.7%
471032 10
 
0.7%
412210 9
 
0.6%
471021 8
 
0.5%
16653 7
 
0.5%
423010 7
 
0.5%
10092 7
 
0.5%
467010 7
 
0.5%
426817 6
 
0.4%
Other values (970) 1403
93.8%
(Missing) 9
 
0.6%
ValueCountFrequency (%)
10012 3
0.2%
10013 1
 
0.1%
10017 1
 
0.1%
10025 1
 
0.1%
10028 1
 
0.1%
10030 1
 
0.1%
10039 1
 
0.1%
10043 1
 
0.1%
10046 2
0.1%
10053 1
 
0.1%
ValueCountFrequency (%)
487882 1
0.1%
487822 1
0.1%
483120 1
0.1%
482862 1
0.1%
480864 1
0.1%
480852 1
0.1%
480844 1
0.1%
480840 1
0.1%
480838 2
0.1%
480835 1
0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1299
Distinct (%)86.9%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean37.447399
Minimum36.944305
Maximum38.017231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T05:59:22.507078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.944305
5-th percentile37.195815
Q137.313839
median37.434379
Q337.598621
95-th percentile37.736874
Maximum38.017231
Range1.0729261
Interquartile range (IQR)0.28478239

Descriptive statistics

Standard deviation0.1794127
Coefficient of variation (CV)0.0047910591
Kurtosis-0.28809722
Mean37.447399
Median Absolute Deviation (MAD)0.13358811
Skewness0.026328211
Sum55946.415
Variance0.032188918
MonotonicityNot monotonic
2023-12-11T05:59:22.730156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2522952839 7
 
0.5%
37.2578874314 5
 
0.3%
37.6452914111 5
 
0.3%
37.3425326328 4
 
0.3%
37.5869833547 4
 
0.3%
37.5027310631 4
 
0.3%
37.324028361 4
 
0.3%
37.3308825205 3
 
0.2%
37.4343793534 3
 
0.2%
37.4277492669 3
 
0.2%
Other values (1289) 1452
97.1%
ValueCountFrequency (%)
36.9443047488 1
0.1%
36.9448573727 1
0.1%
36.9627970114 1
0.1%
36.9628025986 1
0.1%
36.9665291317 1
0.1%
36.9708036988 2
0.1%
36.9859934449 2
0.1%
36.9886932149 1
0.1%
36.9908263015 1
0.1%
36.9909394162 1
0.1%
ValueCountFrequency (%)
38.017230896 1
0.1%
37.9785385091 1
0.1%
37.9366615417 1
0.1%
37.9100443899 1
0.1%
37.9082724014 1
0.1%
37.8822156725 1
0.1%
37.8810510259 1
0.1%
37.8703074506 1
0.1%
37.8602136328 1
0.1%
37.8558629402 1
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1299
Distinct (%)86.9%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean126.97124
Minimum126.55956
Maximum127.62892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T05:59:22.906760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55956
5-th percentile126.73148
Q1126.81046
median126.95981
Q3127.12853
95-th percentile127.27811
Maximum127.62892
Range1.0693649
Interquartile range (IQR)0.31806696

Descriptive statistics

Standard deviation0.18707073
Coefficient of variation (CV)0.0014733316
Kurtosis-0.023701166
Mean126.97124
Median Absolute Deviation (MAD)0.15565925
Skewness0.54527114
Sum189695.03
Variance0.034995458
MonotonicityNot monotonic
2023-12-11T05:59:23.055747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0056998943 7
 
0.5%
127.4859637404 5
 
0.3%
126.706638768 5
 
0.3%
126.8014647829 4
 
0.3%
127.1483122963 4
 
0.3%
126.7673564651 4
 
0.3%
126.7876030313 4
 
0.3%
126.9372012778 3
 
0.2%
126.8783452766 3
 
0.2%
127.149845314 3
 
0.2%
Other values (1289) 1452
97.1%
ValueCountFrequency (%)
126.5595586725 1
0.1%
126.5713961628 1
0.1%
126.5761210321 1
0.1%
126.5780362573 1
0.1%
126.5784491863 2
0.1%
126.579757207 1
0.1%
126.5802824817 2
0.1%
126.5893646226 2
0.1%
126.5971759468 1
0.1%
126.606788106 1
0.1%
ValueCountFrequency (%)
127.628923575 1
0.1%
127.6281161499 1
0.1%
127.5433209437 1
0.1%
127.5428674332 1
0.1%
127.5356135556 1
0.1%
127.535116114 1
0.1%
127.5244008233 1
0.1%
127.5191539178 1
0.1%
127.5077153171 1
0.1%
127.4938241047 1
0.1%

Interactions

2023-12-11T05:59:16.891874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.387906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.909002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.425325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:17.050541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.560416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.049011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.562105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:17.189125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.662840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.190022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.671001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:17.313384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:15.781720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.310451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:16.781419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T05:59:23.159590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가일자영업상태명소재지우편번호WGS84위도WGS84경도
시군명1.0000.3530.2110.8000.9490.948
인허가일자0.3531.0000.0000.1140.2120.208
영업상태명0.2110.0001.0000.3670.0590.126
소재지우편번호0.8000.1140.3671.0000.3650.624
WGS84위도0.9490.2120.0590.3651.0000.718
WGS84경도0.9480.2080.1260.6240.7181.000
2023-12-11T05:59:23.264050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명
영업상태명1.0000.166
시군명0.1661.000
2023-12-11T05:59:23.343162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자소재지우편번호WGS84위도WGS84경도시군명영업상태명
인허가일자1.000-0.0250.027-0.0910.1390.000
소재지우편번호-0.0251.000-0.3490.2600.5070.244
WGS84위도0.027-0.3491.000-0.2120.7370.045
WGS84경도-0.0910.260-0.2121.0000.7350.096
시군명0.1390.5070.7370.7351.0000.166
영업상태명0.0000.2440.0450.0960.1661.000

Missing values

2023-12-11T05:59:17.475494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T05:59:17.649594image/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.
2023-12-11T05:59:17.815020image/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

시군명사업장명인허가일자영업상태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0고양시지엠트랜스20030916운영중경기도 고양시 일산서구 탄중로 136 (덕이동)경기도 고양시 일산서구 덕이동 245-20번지 1층41145037.691985126.760376
1고양시꽃미남이사20110112운영중경기도 고양시 덕양구 화신로 273, 702호 (화정동, 명지프라자)경기도 고양시 덕양구 화정동 1002-1번지 명지프라자 702호41227237.630528126.830767
2고양시남북한,일산종합사다리차20110729운영중경기도 고양시 일산서구 덕이로 30-17 (덕이동)경기도 고양시 일산서구 덕이동 452-3번지41145037.690263126.755438
3고양시(주)스마트무빙20020830운영중경기도 고양시 덕양구 동산1로1길 13-16 (동산동, 1층상가)경기도 고양시 덕양구 동산동 356-10번지 1층상가41209037.643686126.885565
4고양시KT트랜스20020328운영중경기도 고양시 일산동구 은행마을로6번길 86-1 (식사동)경기도 고양시 일산동구 식사동 561-3번지41005037.666162126.808233
5고양시이사데이20031028운영중경기도 고양시 덕양구 행신로 320, 2층 (행신동)경기도 고양시 덕양구 행신동 248-9번지 2층41222237.623216126.846756
6고양시나래익스프레스20030102운영중경기도 고양시 덕양구 지도로103번길 96-12경기도 고양시 덕양구 토당동 288-3번지41281737.62577126.818238
7고양시한울익스프레스20030228운영중경기도 고양시 덕양구 지도로54번길 7, 1층 (토당동)경기도 고양시 덕양구 토당동 373-66번지 1층41221037.622077126.824953
8고양시동진익스프레스20030610운영중경기도 고양시 일산동구 백석로85번길 5-6 (백석동)경기도 고양시 일산동구 백석동 1213-6번지41036237.647879126.78649
9고양시파란이사몰20031011운영중경기도 고양시 덕양구 지도로92번길 35-9 (토당동)경기도 고양시 덕양구 토당동 847-4번지41221037.626024126.825816
시군명사업장명인허가일자영업상태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
1485화성시현대퀵특송19991110운영중경기도 화성시 남양읍 역골로 23-9경기도 화성시 남양읍 남양리 2075-8번지1827137.201464126.827139
1486화성시대성통운익스프레스19980422운영중경기도 화성시 송산면 당성로364번길 12-5경기도 화성시 송산면 칠곡리 447-5번지1855237.199045126.703616
1487화성시에스제이로지스19980216운영중경기도 화성시 효행로 1062, 센타 프라자 505호 (병점동)경기도 화성시 병점동 844-4번지 센타 프라자 505호1840537.214436127.043417
1488화성시KPS익스프레스19960514운영중경기도 화성시 병점중앙로155번길 28 (진안동)경기도 화성시 진안동 512-25번지1840137.210717127.035473
1489화성시대신익스프레스19950731운영중경기도 화성시 우정읍 남양만로 704경기도 화성시 우정읍 이화리 489-1번지44595437.045369126.795564
1490화성시웅진익스프레스19970308운영중경기도 화성시 우정읍 원안길 146-4경기도 화성시 우정읍 원안리 248-6번지44595337.099951126.78339
1491화성시화성물류20010216운영중경기도 화성시 팔탄면 푸른들판로 956-4경기도 화성시 팔탄면 창곡리 264-4번지 2층44594937.191298126.883239
1492화성시우리동네익스프레스20020404운영중경기도 화성시 효행로 988-12 (진안동)경기도 화성시 진안동 516-9번지44539037.210356127.03625
1493화성시2424몰20021213운영중경기도 화성시 장지남길 5경기도 화성시 동탄면 장지리 512번지44581237.154144127.117693
1494화성시참조은이사19981023폐업 등경기도 화성시 10용사로 225경기도 화성시 능동 710-2번지 성호(아)단지내상가 102호44532037.199695127.042835

Duplicate rows

Most frequently occurring

시군명사업장명인허가일자영업상태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도# duplicates
0이천시KT익스프레스20000530폐업 등경기도 이천시 부발읍 신아로 38-9경기도 이천시 부발읍 아미리 745번지46786637.257887127.4859643