Overview

Dataset statistics

Number of variables10
Number of observations108
Missing cells93
Missing cells (%)8.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory86.2 B

Variable types

Categorical2
Text3
Numeric5

Dataset

Description일반이사화물업체 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=15O8A8T95HB97KQ3YWP81074336&infSeq=2

Alerts

폐업일자 is highly overall correlated with 영업상태명High correlation
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
영업상태명 is highly overall correlated with 폐업일자High correlation
폐업일자 has 88 (81.5%) missing valuesMissing
소재지도로명주소 has 5 (4.6%) missing valuesMissing

Reproduction

Analysis started2023-12-10 21:33:18.063418
Analysis finished2023-12-10 21:33:21.721591
Duration3.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Memory size996.0 B
성남시
11 
남양주시
9 
파주시
9 
고양시
8 
하남시
8 
Other values (17)
63 

Length

Max length4
Median length3
Mean length3.1111111
Min length3

Unique

Unique2 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 11
 
10.2%
남양주시 9
 
8.3%
파주시 9
 
8.3%
고양시 8
 
7.4%
하남시 8
 
7.4%
부천시 7
 
6.5%
수원시 7
 
6.5%
군포시 6
 
5.6%
김포시 5
 
4.6%
시흥시 5
 
4.6%
Other values (12) 33
30.6%

Length

2023-12-11T06:33:21.782420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 11
 
10.2%
파주시 9
 
8.3%
남양주시 9
 
8.3%
고양시 8
 
7.4%
하남시 8
 
7.4%
부천시 7
 
6.5%
수원시 7
 
6.5%
군포시 6
 
5.6%
김포시 5
 
4.6%
시흥시 5
 
4.6%
Other values (12) 33
30.6%

사업장명
Text

Distinct101
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T06:33:22.019572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.9074074
Min length3

Characters and Unicode

Total characters746
Distinct characters166
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)87.0%

Sample

1st row24플러스화물
2nd row(주)산채원
3rd row신도화물
4th row일오화물물류
5th row대림제일사다리익스프레스
ValueCountFrequency (%)
24플러스화물 2
 
1.8%
원토탈퀵서비스 2
 
1.8%
스마일익스프레스 2
 
1.8%
휴먼로지스(주 2
 
1.8%
우리홈솔퀵화물 2
 
1.8%
솔퀵화물 2
 
1.8%
주)올예스무빙 2
 
1.8%
고려종합물류(주 1
 
0.9%
익스프레스 1
 
0.9%
평화고속화물 1
 
0.9%
Other values (97) 97
85.1%
2023-12-11T06:33:22.484240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 60
 
8.0%
물 57
 
7.6%
화 41
 
5.5%
주 36
 
4.8%
( 34
 
4.6%
) 34
 
4.6%
류 18
 
2.4%
레 16
 
2.1%
프 16
 
2.1%
익 15
 
2.0%
Other values (156) 419
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 647
86.7%
Open Punctuation 34
 
4.6%
Close Punctuation 34
 
4.6%
Decimal Number 18
 
2.4%
Space Separator 7
 
0.9%
Uppercase Letter 5
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 60
 
9.3%
물 57
 
8.8%
화 41
 
6.3%
주 36
 
5.6%
류 18
 
2.8%
레 16
 
2.5%
프 16
 
2.5%
익 15
 
2.3%
퀵 13
 
2.0%
로 12
 
1.9%
Other values (142) 363
56.1%
Decimal Number
ValueCountFrequency (%)
2 6
33.3%
4 4
22.2%
5 3
16.7%
8 2
 
11.1%
7 2
 
11.1%
1 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
K 2
40.0%
T 1
20.0%
B 1
20.0%
G 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 647
86.7%
Common 94
 
12.6%
Latin 5
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 60
 
9.3%
물 57
 
8.8%
화 41
 
6.3%
주 36
 
5.6%
류 18
 
2.8%
레 16
 
2.5%
프 16
 
2.5%
익 15
 
2.3%
퀵 13
 
2.0%
로 12
 
1.9%
Other values (142) 363
56.1%
Common
ValueCountFrequency (%)
( 34
36.2%
) 34
36.2%
7
 
7.4%
2 6
 
6.4%
4 4
 
4.3%
5 3
 
3.2%
8 2
 
2.1%
7 2
 
2.1%
1 1
 
1.1%
, 1
 
1.1%
Latin
ValueCountFrequency (%)
K 2
40.0%
T 1
20.0%
B 1
20.0%
G 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 647
86.7%
ASCII 99
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 60
 
9.3%
물 57
 
8.8%
화 41
 
6.3%
주 36
 
5.6%
류 18
 
2.8%
레 16
 
2.5%
프 16
 
2.5%
익 15
 
2.3%
퀵 13
 
2.0%
로 12
 
1.9%
Other values (142) 363
56.1%
ASCII
ValueCountFrequency (%)
( 34
34.3%
) 34
34.3%
7
 
7.1%
2 6
 
6.1%
4 4
 
4.0%
5 3
 
3.0%
K 2
 
2.0%
8 2
 
2.0%
7 2
 
2.0%
T 1
 
1.0%
Other values (4) 4
 
4.0%

인허가일자
Real number (ℝ)

Distinct85
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20003855
Minimum19810128
Maximum20170731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T06:33:22.638384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19810128
5-th percentile19924342
Q119971017
median20000767
Q320033449
95-th percentile20097391
Maximum20170731
Range360603
Interquartile range (IQR)62432

Descriptive statistics

Standard deviation56448.61
Coefficient of variation (CV)0.0028218866
Kurtosis1.2780923
Mean20003855
Median Absolute Deviation (MAD)30455.5
Skewness0.1155402
Sum2.1604164 × 109
Variance3.1864456 × 109
MonotonicityNot monotonic
2023-12-11T06:33:22.812253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19980106 4
 
3.7%
19971017 3
 
2.8%
19981118 3
 
2.8%
19990611 2
 
1.9%
19940816 2
 
1.9%
20010529 2
 
1.9%
19960805 2
 
1.9%
20050316 2
 
1.9%
20101208 2
 
1.9%
20011108 2
 
1.9%
Other values (75) 84
77.8%
ValueCountFrequency (%)
19810128 1
0.9%
19890503 1
0.9%
19890711 1
0.9%
19910802 1
0.9%
19921221 1
0.9%
19921231 1
0.9%
19930119 1
0.9%
19930125 1
0.9%
19930413 1
0.9%
19930930 1
0.9%
ValueCountFrequency (%)
20170731 1
0.9%
20170728 1
0.9%
20111205 1
0.9%
20110506 1
0.9%
20101208 2
1.9%
20090302 1
0.9%
20081209 1
0.9%
20081208 1
0.9%
20081028 1
0.9%
20071101 1
0.9%

영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
운영중
88 
폐업 등
20 

Length

Max length4
Median length3
Mean length3.1851852
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 88
81.5%
폐업 등 20
 
18.5%

Length

2023-12-11T06:33:22.949587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:23.103286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 88
68.8%
폐업 20
 
15.6%
등 20
 
15.6%

폐업일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)100.0%
Missing88
Missing (%)81.5%
Infinite0
Infinite (%)0.0%
Mean20123661
Minimum20100319
Maximum20180712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T06:33:23.204668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100319
5-th percentile20100614
Q120107882
median20110968
Q320140612
95-th percentile20152689
Maximum20180712
Range80393
Interquartile range (IQR)32729.5

Descriptive statistics

Standard deviation22958.699
Coefficient of variation (CV)0.0011408809
Kurtosis0.10124781
Mean20123661
Median Absolute Deviation (MAD)10251.5
Skewness0.90408137
Sum4.0247322 × 108
Variance5.2710188 × 108
MonotonicityNot monotonic
2023-12-11T06:33:23.353116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20110103 1
 
0.9%
20141226 1
 
0.9%
20120412 1
 
0.9%
20150310 1
 
0.9%
20100319 1
 
0.9%
20140407 1
 
0.9%
20110526 1
 
0.9%
20110307 1
 
0.9%
20111111 1
 
0.9%
20140110 1
 
0.9%
Other values (10) 10
 
9.3%
(Missing) 88
81.5%
ValueCountFrequency (%)
20100319 1
0.9%
20100629 1
0.9%
20100803 1
0.9%
20101111 1
0.9%
20101220 1
0.9%
20110103 1
0.9%
20110307 1
0.9%
20110520 1
0.9%
20110526 1
0.9%
20110824 1
0.9%
ValueCountFrequency (%)
20180712 1
0.9%
20151214 1
0.9%
20150728 1
0.9%
20150310 1
0.9%
20141226 1
0.9%
20140407 1
0.9%
20140110 1
0.9%
20130626 1
0.9%
20120412 1
0.9%
20111111 1
0.9%

소재지도로명주소
Text

MISSING 

Distinct98
Distinct (%)95.1%
Missing5
Missing (%)4.6%
Memory size996.0 B
2023-12-11T06:33:23.617159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length38
Mean length28.76699
Min length18

Characters and Unicode

Total characters2963
Distinct characters216
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

Unique94 ?
Unique (%)91.3%

Sample

1st row경기도 고양시 일산서구 덕이로 191 (덕이동)
2nd row경기도 고양시 덕양구 통일로1170번길 30 (내유동)
3rd row경기도 고양시 덕양구 흥도로 53 (화전동)
4th row경기도 고양시 일산동구 장항로 122-8 (백석동)
5th row경기도 고양시 일산동구 장항로 249 (장항동)
ValueCountFrequency (%)
경기도 103
 
16.2%
성남시 11
 
1.7%
파주시 9
 
1.4%
중원구 8
 
1.3%
고양시 8
 
1.3%
남양주시 7
 
1.1%
수원시 7
 
1.1%
2층 7
 
1.1%
1층 6
 
0.9%
부천시 6
 
0.9%
Other values (336) 463
72.9%
2023-12-11T06:33:24.106740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
532
 
18.0%
1 116
 
3.9%
시 109
 
3.7%
도 108
 
3.6%
경 107
 
3.6%
기 106
 
3.6%
로 100
 
3.4%
동 90
 
3.0%
( 85
 
2.9%
) 85
 
2.9%
Other values (206) 1525
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1691
57.1%
Space Separator 532
 
18.0%
Decimal Number 491
 
16.6%
Open Punctuation 85
 
2.9%
Close Punctuation 85
 
2.9%
Other Punctuation 59
 
2.0%
Dash Punctuation 18
 
0.6%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 109
 
6.4%
도 108
 
6.4%
경 107
 
6.3%
기 106
 
6.3%
로 100
 
5.9%
동 90
 
5.3%
구 36
 
2.1%
호 36
 
2.1%
남 33
 
2.0%
길 33
 
2.0%
Other values (189) 933
55.2%
Decimal Number
ValueCountFrequency (%)
1 116
23.6%
2 79
16.1%
0 54
11.0%
3 54
11.0%
5 43
 
8.8%
4 39
 
7.9%
9 28
 
5.7%
7 27
 
5.5%
6 26
 
5.3%
8 25
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
532
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Other Punctuation
ValueCountFrequency (%)
, 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1691
57.1%
Common 1270
42.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 109
 
6.4%
도 108
 
6.4%
경 107
 
6.3%
기 106
 
6.3%
로 100
 
5.9%
동 90
 
5.3%
구 36
 
2.1%
호 36
 
2.1%
남 33
 
2.0%
길 33
 
2.0%
Other values (189) 933
55.2%
Common
ValueCountFrequency (%)
532
41.9%
1 116
 
9.1%
( 85
 
6.7%
) 85
 
6.7%
2 79
 
6.2%
, 59
 
4.6%
0 54
 
4.3%
3 54
 
4.3%
5 43
 
3.4%
4 39
 
3.1%
Other values (5) 124
 
9.8%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1691
57.1%
ASCII 1272
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
532
41.8%
1 116
 
9.1%
( 85
 
6.7%
) 85
 
6.7%
2 79
 
6.2%
, 59
 
4.6%
0 54
 
4.2%
3 54
 
4.2%
5 43
 
3.4%
4 39
 
3.1%
Other values (7) 126
 
9.9%
Hangul
ValueCountFrequency (%)
시 109
 
6.4%
도 108
 
6.4%
경 107
 
6.3%
기 106
 
6.3%
로 100
 
5.9%
동 90
 
5.3%
구 36
 
2.1%
호 36
 
2.1%
남 33
 
2.0%
길 33
 
2.0%
Other values (189) 933
55.2%

소재지지번주소
Text

Distinct102
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T06:33:24.436438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length25.101852
Min length15

Characters and Unicode

Total characters2711
Distinct characters182
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)90.7%

Sample

1st row경기도 고양시 일산서구 덕이동 994-5번지
2nd row경기도 고양시 덕양구 내유동 447-7번지
3rd row경기도 고양시 덕양구 화전동 455-12번지
4th row경기도 고양시 일산동구 백석동 1104-10번지
5th row경기도 고양시 일산동구 장항동 578-20번지
ValueCountFrequency (%)
경기도 108
 
18.6%
성남시 11
 
1.9%
남양주시 9
 
1.5%
파주시 9
 
1.5%
하남시 8
 
1.4%
중원구 8
 
1.4%
고양시 8
 
1.4%
부천시 7
 
1.2%
수원시 7
 
1.2%
군포시 6
 
1.0%
Other values (296) 400
68.8%
2023-12-11T06:33:24.912879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
473
 
17.4%
지 117
 
4.3%
시 113
 
4.2%
도 113
 
4.2%
1 111
 
4.1%
기 111
 
4.1%
경 109
 
4.0%
번 105
 
3.9%
동 87
 
3.2%
2 82
 
3.0%
Other values (172) 1290
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1616
59.6%
Decimal Number 534
 
19.7%
Space Separator 473
 
17.4%
Dash Punctuation 80
 
3.0%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 117
 
7.2%
시 113
 
7.0%
도 113
 
7.0%
기 111
 
6.9%
경 109
 
6.7%
번 105
 
6.5%
동 87
 
5.4%
리 46
 
2.8%
구 38
 
2.4%
원 31
 
1.9%
Other values (156) 746
46.2%
Decimal Number
ValueCountFrequency (%)
1 111
20.8%
2 82
15.4%
3 52
9.7%
4 51
9.6%
5 50
9.4%
0 48
9.0%
6 44
 
8.2%
7 40
 
7.5%
9 29
 
5.4%
8 27
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
473
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1616
59.6%
Common 1093
40.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 117
 
7.2%
시 113
 
7.0%
도 113
 
7.0%
기 111
 
6.9%
경 109
 
6.7%
번 105
 
6.5%
동 87
 
5.4%
리 46
 
2.8%
구 38
 
2.4%
원 31
 
1.9%
Other values (156) 746
46.2%
Common
ValueCountFrequency (%)
473
43.3%
1 111
 
10.2%
2 82
 
7.5%
- 80
 
7.3%
3 52
 
4.8%
4 51
 
4.7%
5 50
 
4.6%
0 48
 
4.4%
6 44
 
4.0%
7 40
 
3.7%
Other values (4) 62
 
5.7%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1616
59.6%
ASCII 1095
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
473
43.2%
1 111
 
10.1%
2 82
 
7.5%
- 80
 
7.3%
3 52
 
4.7%
4 51
 
4.7%
5 50
 
4.6%
0 48
 
4.4%
6 44
 
4.0%
7 40
 
3.7%
Other values (6) 64
 
5.8%
Hangul
ValueCountFrequency (%)
지 117
 
7.2%
시 113
 
7.0%
도 113
 
7.0%
기 111
 
6.9%
경 109
 
6.7%
번 105
 
6.5%
동 87
 
5.4%
리 46
 
2.8%
구 38
 
2.4%
원 31
 
1.9%
Other values (156) 746
46.2%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263717.5
Minimum10264
Maximum487822
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T06:33:25.073754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10264
5-th percentile12075.95
Q114946.5
median413828
Q3443039.75
95-th percentile479364.75
Maximum487822
Range477558
Interquartile range (IQR)428093.25

Descriptive statistics

Standard deviation212551.59
Coefficient of variation (CV)0.80598214
Kurtosis-1.8985598
Mean263717.5
Median Absolute Deviation (MAD)58988
Skewness-0.3163489
Sum28481490
Variance4.517818 × 1010
MonotonicityNot monotonic
2023-12-11T06:33:25.227940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
413843 3
 
2.8%
465736 3
 
2.8%
413825 2
 
1.9%
410381 2
 
1.9%
482863 2
 
1.9%
465819 2
 
1.9%
435871 2
 
1.9%
415851 2
 
1.9%
411809 1
 
0.9%
425809 1
 
0.9%
Other values (88) 88
81.5%
ValueCountFrequency (%)
10264 1
0.9%
10434 1
0.9%
11189 1
0.9%
11192 1
0.9%
11623 1
0.9%
12021 1
0.9%
12178 1
0.9%
12196 1
0.9%
12234 1
0.9%
12814 1
0.9%
ValueCountFrequency (%)
487822 1
0.9%
487817 1
0.9%
483800 1
0.9%
483757 1
0.9%
482863 2
1.9%
472868 1
0.9%
472848 1
0.9%
472821 1
0.9%
472811 1
0.9%
472140 1
0.9%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct100
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.491305
Minimum36.98341
Maximum37.911746
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T06:33:25.384654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.98341
5-th percentile37.144003
Q137.332965
median37.49229
Q337.651734
95-th percentile37.821419
Maximum37.911746
Range0.9283358
Interquartile range (IQR)0.31876907

Descriptive statistics

Standard deviation0.21744679
Coefficient of variation (CV)0.0057999258
Kurtosis-0.69902936
Mean37.491305
Median Absolute Deviation (MAD)0.1597633
Skewness-0.15236826
Sum4049.0609
Variance0.047283106
MonotonicityNot monotonic
2023-12-11T06:33:25.529068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5536078 4
 
3.7%
37.3555634 2
 
1.9%
37.7291776 2
 
1.9%
37.8002756 2
 
1.9%
37.6689036 2
 
1.9%
37.3436744 2
 
1.9%
37.6947876 1
 
0.9%
37.7399266 1
 
0.9%
37.2620133 1
 
0.9%
37.233356 1
 
0.9%
Other values (90) 90
83.3%
ValueCountFrequency (%)
36.9834105 1
0.9%
37.0076625 1
0.9%
37.0266271 1
0.9%
37.0498546 1
0.9%
37.1244796 1
0.9%
37.1350027 1
0.9%
37.1607182 1
0.9%
37.1617677 1
0.9%
37.1906574 1
0.9%
37.2116615 1
0.9%
ValueCountFrequency (%)
37.9117463 1
0.9%
37.8898803 1
0.9%
37.8495051 1
0.9%
37.8494427 1
0.9%
37.8301939 1
0.9%
37.8243992 1
0.9%
37.8158837 1
0.9%
37.8143674 1
0.9%
37.8002756 2
1.9%
37.7860128 1
0.9%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct100
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99671
Minimum126.59698
Maximum127.43666
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T06:33:25.710789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.59698
5-th percentile126.70724
Q1126.79618
median127.02459
Q3127.16957
95-th percentile127.28423
Maximum127.43666
Range0.8396835
Interquartile range (IQR)0.3733956

Descriptive statistics

Standard deviation0.20356008
Coefficient of variation (CV)0.0016028768
Kurtosis-1.152533
Mean126.99671
Median Absolute Deviation (MAD)0.18177325
Skewness-0.094410793
Sum13715.645
Variance0.041436707
MonotonicityNot monotonic
2023-12-11T06:33:25.884363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1946579 4
 
3.7%
126.9410399 2
 
1.9%
126.839478 2
 
1.9%
126.7541862 2
 
1.9%
126.596976 2
 
1.9%
126.9501795 2
 
1.9%
126.7396858 1
 
0.9%
127.0355674 1
 
0.9%
127.1003606 1
 
0.9%
127.291229 1
 
0.9%
Other values (90) 90
83.3%
ValueCountFrequency (%)
126.596976 2
1.9%
126.6069464 1
0.9%
126.6311751 1
0.9%
126.6949389 1
0.9%
126.6982471 1
0.9%
126.7239447 1
0.9%
126.7306327 1
0.9%
126.7367633 1
0.9%
126.7378201 1
0.9%
126.7388033 1
0.9%
ValueCountFrequency (%)
127.4366595 1
0.9%
127.362782 1
0.9%
127.3346901 1
0.9%
127.310102 1
0.9%
127.3093762 1
0.9%
127.291229 1
0.9%
127.2712214 1
0.9%
127.2675665 1
0.9%
127.2411425 1
0.9%
127.2249656 1
0.9%

Interactions

2023-12-11T06:33:20.931593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:18.627589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.150023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.734156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:20.231310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:21.017825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:18.723270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.269852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.834905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:20.330592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:21.119156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:18.839665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.376442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.936641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:20.659558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:21.215605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:18.937573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.493534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:20.026019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:20.739654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:21.323678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.050516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:19.614076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:20.143789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:20.856239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:33:26.024610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가일자영업상태명폐업일자소재지도로명주소소재지우편번호WGS84위도WGS84경도
시군명1.0000.4920.3110.6781.0000.8790.9420.943
인허가일자0.4921.0000.0000.0001.0000.1550.3630.438
영업상태명0.3110.0001.000NaN0.0000.2350.1760.327
폐업일자0.6780.000NaN1.0000.6080.3780.0000.809
소재지도로명주소1.0001.0000.0000.6081.0001.0001.0001.000
소재지우편번호0.8790.1550.2350.3781.0001.0000.5620.686
WGS84위도0.9420.3630.1760.0001.0000.5621.0000.765
WGS84경도0.9430.4380.3270.8091.0000.6860.7651.000
2023-12-11T06:33:26.139686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명
영업상태명1.0000.218
시군명0.2181.000
2023-12-11T06:33:26.221420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자폐업일자소재지우편번호WGS84위도WGS84경도시군명영업상태명
인허가일자1.000-0.327-0.1420.238-0.0910.2100.000
폐업일자-0.3271.000-0.140-0.291-0.0180.2961.000
소재지우편번호-0.142-0.1401.0000.0920.0020.6500.384
WGS84위도0.238-0.2910.0921.000-0.1330.6870.127
WGS84경도-0.091-0.0180.002-0.1331.0000.6910.240
시군명0.2100.2960.6500.6870.6911.0000.218
영업상태명0.0001.0000.3840.1270.2400.2181.000

Missing values

2023-12-11T06:33:21.452642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:33:21.578969image/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.
2023-12-11T06:33:21.678077image/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

시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0고양시24플러스화물19980623운영중<NA>경기도 고양시 일산서구 덕이로 191 (덕이동)경기도 고양시 일산서구 덕이동 994-5번지41180937.694788126.739686
1고양시(주)산채원19960805운영중<NA>경기도 고양시 덕양구 통일로1170번길 30 (내유동)경기도 고양시 덕양구 내유동 447-7번지1026437.719317126.850036
2고양시신도화물20010425운영중<NA>경기도 고양시 덕양구 흥도로 53 (화전동)경기도 고양시 덕양구 화전동 455-12번지41216037.613781126.866868
3고양시일오화물물류20070523운영중<NA>경기도 고양시 일산동구 장항로 122-8 (백석동)경기도 고양시 일산동구 백석동 1104-10번지1043437.634629126.783379
4고양시대림제일사다리익스프레스19960719운영중<NA>경기도 고양시 일산동구 장항로 249 (장항동)경기도 고양시 일산동구 장항동 578-20번지41038137.641635126.771938
5고양시드림월드익스프레스퀵특송20020214운영중<NA>경기도 고양시 일산동구 장항로 59, 2층 (백석동)경기도 고양시 일산동구 백석동 1122-17번지 외2필지 2층호41036237.630466126.787798
6고양시신성화물19960805폐업 등20140110경기도 고양시 일산동구 장항로225번길 89 (장항동)경기도 고양시 일산동구 장항동 579-33번지41038137.641297126.769571
7고양시24플러스화물19980623폐업 등20150728경기도 고양시 일산서구 덕산로266번길 59 (덕이동)경기도 고양시 일산서구 덕이동 1287-1번지41145037.693073126.730633
8광주시KT이삿짐센타19981208운영중<NA>경기도 광주시 오포읍 오포로 218 (능평리)경기도 광주시 오포읍 능평리 26-10번지46489237.349977127.186295
9광주시1577포장이사(주)20170728운영중<NA>경기도 광주시 도척면 도척로330번길 57경기도 광주시 도척면 진우리 111-2번지1281437.327768127.33469
시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
98하남시승리화물20030121운영중<NA>경기도 하남시신평로101번길 9(덕풍동)경기도 하남시 덕풍동 317-49번지46501137.542542127.20642
99하남시태상로지스틱스(주)19990218운영중<NA>경기도 하남시 대청로 33, 현대베스코아빌딩 4층 428호 (신장동)경기도 하남시 신장동 523-1번지 현대베스코아빌딩1294737.541012127.215954
100하남시우리홈솔퀵화물19980106운영중<NA>경기도 하남시 조정대로 150, 1층 125호 (덕풍동)경기도 하남시 덕풍동 762번지46573637.553608127.194658
101하남시우리홈솔퀵화물19980106폐업 등20150310경기도 하남시 조정대로 150, 1층 125호 (덕풍동)경기도 하남시 덕풍동 762번지46573637.553608127.194658
102하남시솔퀵화물19980106폐업 등20120412경기도 하남시 조정대로 150 (덕풍동)경기도 하남시 덕풍동 762번지46583437.553608127.194658
103하남시솔퀵화물19980106폐업 등20141226경기도 하남시 조정대로 150, 1층 125호 (덕풍동)경기도 하남시 덕풍동 762번지46573637.553608127.194658
104화성시원토탈퀵서비스20010529운영중<NA>경기도 화성시 병점동로 84-1, 골든뷰 401호 (진안동)경기도 화성시 진안동 886-12번지 골든뷰 401호1840437.211661127.040971
105화성시조은물류,이사19890503운영중<NA>경기도 화성시 팔탄면 푸른들판로 949경기도 화성시 팔탄면 창곡리 264-9번지 205호44594937.190657126.882632
106화성시투세븐특송화물19980708운영중<NA>경기도 화성시 팔탄면 서해로1121번길 18-1, 203동 101호 (발안현대공구타운)경기도 화성시 팔탄면 율암리 580-8번지 발안현대공구타운 203동 101호1852937.161768126.889399
107화성시(주)오케이종합특송19951225운영중<NA>경기도 화성시 봉담읍 마당바위로 174, 3,4층경기도 화성시 봉담읍 덕우리 195-1번지1833637.160718126.916431