Overview

Dataset statistics

Number of variables10
Number of observations2873
Missing cells2410
Missing cells (%)8.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory238.6 KiB
Average record size in memory85.0 B

Variable types

Categorical2
Text3
Numeric5

Alerts

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
폐업일자 has 2293 (79.8%) missing valuesMissing
소재지도로명주소 has 100 (3.5%) missing valuesMissing

Reproduction

Analysis started2023-12-10 21:31:59.046987
Analysis finished2023-12-10 21:32:03.708141
Duration4.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
시흥시
314 
화성시
276 
안산시
221 
용인시
192 
평택시
186 
Other values (26)
1684 

Length

Max length4
Median length3
Mean length3.035851
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
시흥시 314
 
10.9%
화성시 276
 
9.6%
안산시 221
 
7.7%
용인시 192
 
6.7%
평택시 186
 
6.5%
광주시 166
 
5.8%
고양시 133
 
4.6%
이천시 128
 
4.5%
파주시 116
 
4.0%
김포시 116
 
4.0%
Other values (21) 1025
35.7%

Length

2023-12-11T06:32:03.792607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시흥시 314
 
10.9%
화성시 276
 
9.6%
안산시 221
 
7.7%
용인시 192
 
6.7%
평택시 186
 
6.5%
광주시 166
 
5.8%
고양시 133
 
4.6%
이천시 128
 
4.5%
파주시 116
 
4.0%
김포시 116
 
4.0%
Other values (21) 1025
35.7%

사업장명
Text

Distinct2551
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
2023-12-11T06:32:04.044102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length20
Mean length6.4075879
Min length1

Characters and Unicode

Total characters18409
Distinct characters484
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

Unique2307 ?
Unique (%)80.3%

Sample

1st row(주)태영지엘에스
2nd row성실트렌스
3rd row주식회사 로지위드
4th row코리아전국물류
5th row전국백마화물퀵㈜
ValueCountFrequency (%)
주식회사 30
 
1.0%
업체명 14
 
0.5%
전국화물 6
 
0.2%
미래물류 6
 
0.2%
대성화물 5
 
0.2%
전국특송 5
 
0.2%
제일화물 5
 
0.2%
한국화물 4
 
0.1%
다모아물류(주 4
 
0.1%
ok특송화물 4
 
0.1%
Other values (2569) 2869
97.2%
2023-12-11T06:32:04.457462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
물 1566
 
8.5%
주 1121
 
6.1%
) 1079
 
5.9%
( 1079
 
5.9%
류 849
 
4.6%
스 807
 
4.4%
화 781
 
4.2%
지 492
 
2.7%
로 486
 
2.6%
합 306
 
1.7%
Other values (474) 9843
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15739
85.5%
Close Punctuation 1079
 
5.9%
Open Punctuation 1079
 
5.9%
Uppercase Letter 150
 
0.8%
Other Symbol 118
 
0.6%
Decimal Number 81
 
0.4%
Space Separator 79
 
0.4%
Lowercase Letter 43
 
0.2%
Other Punctuation 39
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
물 1566
 
9.9%
주 1121
 
7.1%
류 849
 
5.4%
스 807
 
5.1%
화 781
 
5.0%
지 492
 
3.1%
로 486
 
3.1%
합 306
 
1.9%
퀵 298
 
1.9%
이 283
 
1.8%
Other values (419) 8750
55.6%
Uppercase Letter
ValueCountFrequency (%)
K 20
13.3%
S 19
12.7%
O 18
12.0%
L 12
 
8.0%
M 8
 
5.3%
J 8
 
5.3%
C 7
 
4.7%
N 7
 
4.7%
D 7
 
4.7%
G 6
 
4.0%
Other values (13) 38
25.3%
Lowercase Letter
ValueCountFrequency (%)
s 11
25.6%
p 5
11.6%
o 4
 
9.3%
a 4
 
9.3%
t 3
 
7.0%
e 3
 
7.0%
i 3
 
7.0%
c 3
 
7.0%
d 2
 
4.7%
g 2
 
4.7%
Other values (3) 3
 
7.0%
Decimal Number
ValueCountFrequency (%)
1 15
18.5%
2 15
18.5%
0 11
13.6%
8 10
12.3%
3 8
9.9%
4 7
8.6%
5 6
 
7.4%
6 5
 
6.2%
7 3
 
3.7%
9 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 26
66.7%
& 8
 
20.5%
, 3
 
7.7%
· 2
 
5.1%
Close Punctuation
ValueCountFrequency (%)
) 1079
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1079
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 118
100.0%
Space Separator
ValueCountFrequency (%)
79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15857
86.1%
Common 2359
 
12.8%
Latin 193
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
물 1566
 
9.9%
주 1121
 
7.1%
류 849
 
5.4%
스 807
 
5.1%
화 781
 
4.9%
지 492
 
3.1%
로 486
 
3.1%
합 306
 
1.9%
퀵 298
 
1.9%
이 283
 
1.8%
Other values (420) 8868
55.9%
Latin
ValueCountFrequency (%)
K 20
 
10.4%
S 19
 
9.8%
O 18
 
9.3%
L 12
 
6.2%
s 11
 
5.7%
M 8
 
4.1%
J 8
 
4.1%
C 7
 
3.6%
N 7
 
3.6%
D 7
 
3.6%
Other values (26) 76
39.4%
Common
ValueCountFrequency (%)
) 1079
45.7%
( 1079
45.7%
79
 
3.3%
. 26
 
1.1%
1 15
 
0.6%
2 15
 
0.6%
0 11
 
0.5%
8 10
 
0.4%
& 8
 
0.3%
3 8
 
0.3%
Other values (8) 29
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15739
85.5%
ASCII 2550
 
13.9%
None 120
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
물 1566
 
9.9%
주 1121
 
7.1%
류 849
 
5.4%
스 807
 
5.1%
화 781
 
5.0%
지 492
 
3.1%
로 486
 
3.1%
합 306
 
1.9%
퀵 298
 
1.9%
이 283
 
1.8%
Other values (419) 8750
55.6%
ASCII
ValueCountFrequency (%)
) 1079
42.3%
( 1079
42.3%
79
 
3.1%
. 26
 
1.0%
K 20
 
0.8%
S 19
 
0.7%
O 18
 
0.7%
1 15
 
0.6%
2 15
 
0.6%
L 12
 
0.5%
Other values (43) 188
 
7.4%
None
ValueCountFrequency (%)
㈜ 118
98.3%
· 2
 
1.7%

인허가일자
Real number (ℝ)

Distinct1743
Distinct (%)60.7%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean20015706
Minimum19620621
Maximum20180731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.4 KiB
2023-12-11T06:32:04.639183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19620621
5-th percentile19920470
Q119980608
median20020328
Q320050620
95-th percentile20130521
Maximum20180731
Range560110
Interquartile range (IQR)70011.25

Descriptive statistics

Standard deviation62059.407
Coefficient of variation (CV)0.0031005355
Kurtosis1.2567619
Mean20015706
Median Absolute Deviation (MAD)39299
Skewness-0.18511698
Sum5.7485106 × 1010
Variance3.8513699 × 109
MonotonicityNot monotonic
2023-12-11T06:32:04.807106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040421 12
 
0.4%
20070723 9
 
0.3%
19991110 8
 
0.3%
20040119 8
 
0.3%
20070720 8
 
0.3%
20070713 8
 
0.3%
20040130 8
 
0.3%
20070213 7
 
0.2%
20070430 7
 
0.2%
20150909 7
 
0.2%
Other values (1733) 2790
97.1%
ValueCountFrequency (%)
19620621 1
< 0.1%
19681116 1
< 0.1%
19710611 1
< 0.1%
19790607 1
< 0.1%
19800814 2
0.1%
19801115 1
< 0.1%
19810904 1
< 0.1%
19820315 1
< 0.1%
19830308 1
< 0.1%
19830425 1
< 0.1%
ValueCountFrequency (%)
20180731 1
 
< 0.1%
20180717 1
 
< 0.1%
20171226 1
 
< 0.1%
20171127 1
 
< 0.1%
20171031 1
 
< 0.1%
20171030 3
0.1%
20170904 1
 
< 0.1%
20170711 1
 
< 0.1%
20170705 1
 
< 0.1%
20170203 1
 
< 0.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
운영중
2295 
폐업 등
578 

Length

Max length4
Median length3
Mean length3.2011834
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 2295
79.9%
폐업 등 578
 
20.1%

Length

2023-12-11T06:32:04.962414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:32:05.287038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 2295
66.5%
폐업 578
 
16.7%
등 578
 
16.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct512
Distinct (%)88.3%
Missing2293
Missing (%)79.8%
Infinite0
Infinite (%)0.0%
Mean20139267
Minimum20090309
Maximum20180821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.4 KiB
2023-12-11T06:32:05.450996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090309
5-th percentile20100598
Q120120128
median20140514
Q320160830
95-th percentile20180516
Maximum20180821
Range90512
Interquartile range (IQR)40702

Descriptive statistics

Standard deviation26213.57
Coefficient of variation (CV)0.0013016149
Kurtosis-1.2149144
Mean20139267
Median Absolute Deviation (MAD)20316.5
Skewness-0.03195914
Sum1.1680775 × 1010
Variance6.8715128 × 108
MonotonicityNot monotonic
2023-12-11T06:32:05.588586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180816 3
 
0.1%
20170808 3
 
0.1%
20140319 3
 
0.1%
20141229 3
 
0.1%
20170714 3
 
0.1%
20121204 3
 
0.1%
20150709 3
 
0.1%
20131106 3
 
0.1%
20180730 3
 
0.1%
20110114 2
 
0.1%
Other values (502) 551
 
19.2%
(Missing) 2293
79.8%
ValueCountFrequency (%)
20090309 1
< 0.1%
20090512 1
< 0.1%
20090813 1
< 0.1%
20090824 1
< 0.1%
20091021 1
< 0.1%
20091022 1
< 0.1%
20091120 1
< 0.1%
20091124 1
< 0.1%
20091125 1
< 0.1%
20091127 1
< 0.1%
ValueCountFrequency (%)
20180821 1
 
< 0.1%
20180820 2
0.1%
20180816 3
0.1%
20180809 2
0.1%
20180801 1
 
< 0.1%
20180731 1
 
< 0.1%
20180730 3
0.1%
20180727 1
 
< 0.1%
20180720 1
 
< 0.1%
20180718 1
 
< 0.1%

소재지도로명주소
Text

MISSING 

Distinct2376
Distinct (%)85.7%
Missing100
Missing (%)3.5%
Memory size22.6 KiB
2023-12-11T06:32:05.877927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length46
Mean length27.067436
Min length13

Characters and Unicode

Total characters75058
Distinct characters500
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

Unique2116 ?
Unique (%)76.3%

Sample

1st row경기도 가평군 하면 조종희망로 5, 3층 (태영빌딩)
2nd row경기도 고양시 덕양구 행당로 880-13 (행신동, 운진주택)
3rd row경기도 고양시 덕양구 동헌로 337, LG전자고양물류센타 (대자동)
4th row경기도 고양시 일산동구 장대길 128-47 (장항동)
5th row경기도 고양시 일산동구 백석로71번길 33 (백석동)
ValueCountFrequency (%)
경기도 2773
 
16.9%
시흥시 309
 
1.9%
화성시 270
 
1.6%
안산시 217
 
1.3%
용인시 185
 
1.1%
평택시 179
 
1.1%
단원구 173
 
1.1%
광주시 159
 
1.0%
정왕동 156
 
1.0%
고양시 128
 
0.8%
Other values (3698) 11815
72.2%
2023-12-11T06:32:06.433901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13601
 
18.1%
시 3196
 
4.3%
도 2958
 
3.9%
기 2940
 
3.9%
경 2886
 
3.8%
1 2630
 
3.5%
로 2495
 
3.3%
동 2035
 
2.7%
2 2010
 
2.7%
, 1585
 
2.1%
Other values (490) 38722
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43351
57.8%
Space Separator 13601
 
18.1%
Decimal Number 12792
 
17.0%
Other Punctuation 1600
 
2.1%
Open Punctuation 1471
 
2.0%
Close Punctuation 1471
 
2.0%
Dash Punctuation 541
 
0.7%
Uppercase Letter 222
 
0.3%
Lowercase Letter 5
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3196
 
7.4%
도 2958
 
6.8%
기 2940
 
6.8%
경 2886
 
6.7%
로 2495
 
5.8%
동 2035
 
4.7%
구 944
 
2.2%
길 931
 
2.1%
호 899
 
2.1%
대 716
 
1.7%
Other values (446) 23351
53.9%
Uppercase Letter
ValueCountFrequency (%)
C 30
13.5%
I 29
13.1%
B 28
12.6%
D 27
12.2%
A 26
11.7%
L 16
7.2%
T 12
 
5.4%
S 10
 
4.5%
G 9
 
4.1%
E 7
 
3.2%
Other values (10) 28
12.6%
Decimal Number
ValueCountFrequency (%)
1 2630
20.6%
2 2010
15.7%
3 1517
11.9%
0 1312
10.3%
4 1197
9.4%
5 904
 
7.1%
7 857
 
6.7%
6 828
 
6.5%
8 783
 
6.1%
9 754
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1585
99.1%
. 10
 
0.6%
& 3
 
0.2%
/ 1
 
0.1%
@ 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
b 2
40.0%
s 2
40.0%
k 1
20.0%
Space Separator
ValueCountFrequency (%)
13601
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1471
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1471
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 541
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43351
57.8%
Common 31477
41.9%
Latin 230
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3196
 
7.4%
도 2958
 
6.8%
기 2940
 
6.8%
경 2886
 
6.7%
로 2495
 
5.8%
동 2035
 
4.7%
구 944
 
2.2%
길 931
 
2.1%
호 899
 
2.1%
대 716
 
1.7%
Other values (446) 23351
53.9%
Latin
ValueCountFrequency (%)
C 30
13.0%
I 29
12.6%
B 28
12.2%
D 27
11.7%
A 26
11.3%
L 16
7.0%
T 12
 
5.2%
S 10
 
4.3%
G 9
 
3.9%
E 7
 
3.0%
Other values (14) 36
15.7%
Common
ValueCountFrequency (%)
13601
43.2%
1 2630
 
8.4%
2 2010
 
6.4%
, 1585
 
5.0%
3 1517
 
4.8%
( 1471
 
4.7%
) 1471
 
4.7%
0 1312
 
4.2%
4 1197
 
3.8%
5 904
 
2.9%
Other values (10) 3779
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43351
57.8%
ASCII 31704
42.2%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13601
42.9%
1 2630
 
8.3%
2 2010
 
6.3%
, 1585
 
5.0%
3 1517
 
4.8%
( 1471
 
4.6%
) 1471
 
4.6%
0 1312
 
4.1%
4 1197
 
3.8%
5 904
 
2.9%
Other values (33) 4006
 
12.6%
Hangul
ValueCountFrequency (%)
시 3196
 
7.4%
도 2958
 
6.8%
기 2940
 
6.8%
경 2886
 
6.7%
로 2495
 
5.8%
동 2035
 
4.7%
구 944
 
2.2%
길 931
 
2.1%
호 899
 
2.1%
대 716
 
1.7%
Other values (446) 23351
53.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

소재지지번주소
Text

Distinct2469
Distinct (%)86.2%
Missing8
Missing (%)0.3%
Memory size22.6 KiB
2023-12-11T06:32:06.818420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length25.685166
Min length10

Characters and Unicode

Total characters73588
Distinct characters458
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2168 ?
Unique (%)75.7%

Sample

1st row경기도 가평군 조종면 현리 412-7번지 태영빌딩 3층
2nd row경기도 고양시 덕양구 대자동 596-1번지 LG전자고양물류센타
3rd row경기도 고양시 일산동구 장항동 548-25번지
4th row경기도 고양시 일산동구 백석동 1199-2번지
5th row경기도 고양시 덕양구 덕은동 7-12번지
ValueCountFrequency (%)
경기도 2865
 
18.2%
시흥시 313
 
2.0%
화성시 276
 
1.8%
정왕동 242
 
1.5%
안산시 221
 
1.4%
용인시 192
 
1.2%
평택시 186
 
1.2%
단원구 175
 
1.1%
광주시 166
 
1.1%
고양시 132
 
0.8%
Other values (3759) 10954
69.7%
2023-12-11T06:32:07.403129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12889
 
17.5%
시 3254
 
4.4%
도 3016
 
4.1%
1 3013
 
4.1%
기 2975
 
4.0%
지 2961
 
4.0%
경 2885
 
3.9%
번 2716
 
3.7%
동 2403
 
3.3%
- 2165
 
2.9%
Other values (448) 35311
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43472
59.1%
Decimal Number 14762
 
20.1%
Space Separator 12889
 
17.5%
Dash Punctuation 2165
 
2.9%
Uppercase Letter 184
 
0.3%
Other Punctuation 42
 
0.1%
Close Punctuation 31
 
< 0.1%
Open Punctuation 31
 
< 0.1%
Lowercase Letter 8
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3254
 
7.5%
도 3016
 
6.9%
기 2975
 
6.8%
지 2961
 
6.8%
경 2885
 
6.6%
번 2716
 
6.2%
동 2403
 
5.5%
리 1216
 
2.8%
구 1005
 
2.3%
호 880
 
2.0%
Other values (402) 20161
46.4%
Uppercase Letter
ValueCountFrequency (%)
B 36
19.6%
A 32
17.4%
C 17
9.2%
D 17
9.2%
L 16
8.7%
S 11
 
6.0%
I 11
 
6.0%
T 9
 
4.9%
N 8
 
4.3%
E 6
 
3.3%
Other values (9) 21
11.4%
Decimal Number
ValueCountFrequency (%)
1 3013
20.4%
2 2061
14.0%
3 1695
11.5%
4 1515
10.3%
0 1353
9.2%
5 1229
8.3%
6 1196
 
8.1%
7 1026
 
7.0%
9 907
 
6.1%
8 767
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
b 2
25.0%
s 2
25.0%
c 1
12.5%
n 1
12.5%
v 1
12.5%
o 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 34
81.0%
. 3
 
7.1%
& 2
 
4.8%
@ 2
 
4.8%
/ 1
 
2.4%
Space Separator
ValueCountFrequency (%)
12889
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2165
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43472
59.1%
Common 29921
40.7%
Latin 195
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3254
 
7.5%
도 3016
 
6.9%
기 2975
 
6.8%
지 2961
 
6.8%
경 2885
 
6.6%
번 2716
 
6.2%
동 2403
 
5.5%
리 1216
 
2.8%
구 1005
 
2.3%
호 880
 
2.0%
Other values (402) 20161
46.4%
Latin
ValueCountFrequency (%)
B 36
18.5%
A 32
16.4%
C 17
8.7%
D 17
8.7%
L 16
8.2%
S 11
 
5.6%
I 11
 
5.6%
T 9
 
4.6%
N 8
 
4.1%
E 6
 
3.1%
Other values (16) 32
16.4%
Common
ValueCountFrequency (%)
12889
43.1%
1 3013
 
10.1%
- 2165
 
7.2%
2 2061
 
6.9%
3 1695
 
5.7%
4 1515
 
5.1%
0 1353
 
4.5%
5 1229
 
4.1%
6 1196
 
4.0%
7 1026
 
3.4%
Other values (10) 1779
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43471
59.1%
ASCII 30113
40.9%
Number Forms 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12889
42.8%
1 3013
 
10.0%
- 2165
 
7.2%
2 2061
 
6.8%
3 1695
 
5.6%
4 1515
 
5.0%
0 1353
 
4.5%
5 1229
 
4.1%
6 1196
 
4.0%
7 1026
 
3.4%
Other values (35) 1971
 
6.5%
Hangul
ValueCountFrequency (%)
시 3254
 
7.5%
도 3016
 
6.9%
기 2975
 
6.8%
지 2961
 
6.8%
경 2885
 
6.6%
번 2716
 
6.2%
동 2403
 
5.5%
리 1216
 
2.8%
구 1005
 
2.3%
호 880
 
2.0%
Other values (401) 20160
46.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1456
Distinct (%)50.8%
Missing8
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean253964.13
Minimum10011
Maximum487921
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.4 KiB
2023-12-11T06:32:07.562050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile11157
Q115489
median415090
Q3445923
95-th percentile469665.8
Maximum487921
Range477910
Interquartile range (IQR)430434

Descriptive statistics

Standard deviation213039.18
Coefficient of variation (CV)0.8388554
Kurtosis-1.9319248
Mean253964.13
Median Absolute Deviation (MAD)52773
Skewness-0.22054541
Sum7.2760724 × 108
Variance4.5385694 × 1010
MonotonicityNot monotonic
2023-12-11T06:32:07.726574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
429879 34
 
1.2%
429451 33
 
1.1%
425780 31
 
1.1%
15103 27
 
0.9%
429853 26
 
0.9%
15431 24
 
0.8%
451821 17
 
0.6%
464070 17
 
0.6%
425850 16
 
0.6%
15014 15
 
0.5%
Other values (1446) 2625
91.4%
ValueCountFrequency (%)
10011 1
 
< 0.1%
10013 3
0.1%
10014 1
 
< 0.1%
10016 1
 
< 0.1%
10020 1
 
< 0.1%
10024 1
 
< 0.1%
10029 1
 
< 0.1%
10030 2
0.1%
10032 2
0.1%
10035 1
 
< 0.1%
ValueCountFrequency (%)
487921 1
< 0.1%
487914 1
< 0.1%
487883 1
< 0.1%
487874 1
< 0.1%
487832 1
< 0.1%
487831 1
< 0.1%
487826 1
< 0.1%
487825 1
< 0.1%
487823 1
< 0.1%
487821 1
< 0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct2125
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.376255
Minimum36.938997
Maximum38.104082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.4 KiB
2023-12-11T06:32:07.894586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.938997
5-th percentile37.015327
Q137.243361
median37.337501
Q337.507236
95-th percentile37.800143
Maximum38.104082
Range1.165085
Interquartile range (IQR)0.2638747

Descriptive statistics

Standard deviation0.22401413
Coefficient of variation (CV)0.0059934879
Kurtosis-0.24317105
Mean37.376255
Median Absolute Deviation (MAD)0.11461026
Skewness0.44288192
Sum107381.98
Variance0.050182332
MonotonicityNot monotonic
2023-12-11T06:32:08.043144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.324028361 37
 
1.3%
37.3308825205 22
 
0.8%
37.3485657281 18
 
0.6%
37.3361982548 15
 
0.5%
37.3380955118 13
 
0.5%
37.3444699035 13
 
0.5%
37.3715256588 13
 
0.5%
37.3303699437 13
 
0.5%
37.323170299 10
 
0.3%
37.3368989782 8
 
0.3%
Other values (2115) 2711
94.4%
ValueCountFrequency (%)
36.9389968935 1
 
< 0.1%
36.9412449654 1
 
< 0.1%
36.9438089704 2
0.1%
36.9442208048 1
 
< 0.1%
36.9448573727 4
0.1%
36.9456935806 1
 
< 0.1%
36.9476936869 1
 
< 0.1%
36.9490236937 1
 
< 0.1%
36.9501044563 2
0.1%
36.9501088257 1
 
< 0.1%
ValueCountFrequency (%)
38.1040818837 1
< 0.1%
38.0965248165 2
0.1%
38.0927499872 1
< 0.1%
38.0247828907 1
< 0.1%
38.0189523743 1
< 0.1%
38.0055175511 1
< 0.1%
38.0048146782 2
0.1%
37.9769029687 2
0.1%
37.9748800828 1
< 0.1%
37.9694647371 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2125
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98399
Minimum126.53032
Maximum127.72669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.4 KiB
2023-12-11T06:32:08.191436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53032
5-th percentile126.70004
Q1126.7876
median126.95375
Q3127.14468
95-th percentile127.4043
Maximum127.72669
Range1.1963684
Interquartile range (IQR)0.3570786

Descriptive statistics

Standard deviation0.23036219
Coefficient of variation (CV)0.0018141042
Kurtosis-0.32385345
Mean126.98399
Median Absolute Deviation (MAD)0.17113566
Skewness0.57087029
Sum364825.01
Variance0.05306674
MonotonicityNot monotonic
2023-12-11T06:32:08.342347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7876030313 37
 
1.3%
126.9372012778 22
 
0.8%
126.7203585982 18
 
0.6%
126.9554770489 15
 
0.5%
126.7239749889 13
 
0.5%
126.7000376581 13
 
0.5%
126.9520679799 13
 
0.5%
126.9587867261 13
 
0.5%
126.7337554258 10
 
0.3%
126.7247467432 8
 
0.3%
Other values (2115) 2711
94.4%
ValueCountFrequency (%)
126.5303195597 2
0.1%
126.5367295826 1
< 0.1%
126.5514507822 1
< 0.1%
126.5573960263 2
0.1%
126.5583146408 1
< 0.1%
126.5588119011 1
< 0.1%
126.5632892855 1
< 0.1%
126.5729823981 2
0.1%
126.574011144 1
< 0.1%
126.5743769315 1
< 0.1%
ValueCountFrequency (%)
127.7266879295 2
0.1%
127.7168299209 1
< 0.1%
127.6868260846 2
0.1%
127.6707735865 1
< 0.1%
127.6686303637 1
< 0.1%
127.6621604944 1
< 0.1%
127.6605012997 1
< 0.1%
127.6576615634 1
< 0.1%
127.6524968914 1
< 0.1%
127.6505008582 1
< 0.1%

Interactions

2023-12-11T06:32:02.637862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:00.303430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:00.914563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.474473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:02.020135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:02.789602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:00.411534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.036629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.594855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:02.145208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:02.907800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:00.536683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.132791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.702041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:02.255029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:03.020556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:00.655312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.219024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.802095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:02.375095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:03.134607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:00.789233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.328073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:01.893173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:32:02.499145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:32:08.437821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가일자영업상태명폐업일자소재지우편번호WGS84위도WGS84경도
시군명1.0000.2980.1460.2460.7780.9530.940
인허가일자0.2981.0000.0580.1040.2640.1510.139
영업상태명0.1460.0581.0000.0000.1510.1090.082
폐업일자0.2460.1040.0001.0000.4800.0000.000
소재지우편번호0.7780.2640.1510.4801.0000.4980.585
WGS84위도0.9530.1510.1090.0000.4981.0000.643
WGS84경도0.9400.1390.0820.0000.5850.6431.000
2023-12-11T06:32:08.573816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명
시군명1.0000.123
영업상태명0.1231.000
2023-12-11T06:32:08.662803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자폐업일자소재지우편번호WGS84위도WGS84경도시군명영업상태명
인허가일자1.0000.006-0.1150.069-0.1460.1090.040
폐업일자0.0061.000-0.3190.0420.0320.0900.000
소재지우편번호-0.115-0.3191.000-0.2260.2980.5620.250
WGS84위도0.0690.042-0.2261.000-0.2230.7420.083
WGS84경도-0.1460.0320.298-0.2231.0000.6990.063
시군명0.1090.0900.5620.7420.6991.0000.123
영업상태명0.0400.0000.2500.0830.0630.1231.000

Missing values

2023-12-11T06:32:03.279694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:32:03.437372image/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.
2023-12-11T06:32:03.615612image/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
0가평군(주)태영지엘에스20140808운영중<NA>경기도 가평군 하면 조종희망로 5, 3층 (태영빌딩)경기도 가평군 조종면 현리 412-7번지 태영빌딩 3층1243737.818229127.349037
1고양시성실트렌스20150825운영중<NA>경기도 고양시 덕양구 행당로 880-13 (행신동, 운진주택)<NA><NA>37.615755126.833225
2고양시주식회사 로지위드20020725운영중<NA>경기도 고양시 덕양구 동헌로 337, LG전자고양물류센타 (대자동)경기도 고양시 덕양구 대자동 596-1번지 LG전자고양물류센타1027937.709678126.891336
3고양시코리아전국물류19990105운영중<NA>경기도 고양시 일산동구 장대길 128-47 (장항동)경기도 고양시 일산동구 장항동 548-25번지1042837.641909126.764629
4고양시전국백마화물퀵㈜20030611운영중<NA>경기도 고양시 일산동구 백석로71번길 33 (백석동)경기도 고양시 일산동구 백석동 1199-2번지1042037.647831126.784462
5고양시(주)범일특송20171031운영중<NA>경기도 고양시 덕양구 중앙로64번길 28-72, 103호 (덕은동)경기도 고양시 덕양구 덕은동 7-12번지1053937.59811126.880507
6고양시주식회사 씨엠20111111운영중<NA>경기도 고양시 일산서구 송산로 498-11 (덕이동)경기도 고양시 일산서구 덕이동 937-23번지1022437.688902126.734514
7고양시동해공동화물20000214운영중<NA>경기도 고양시 덕양구 삼송로 293, 2층 (지축동)경기도 고양시 덕양구 지축동 724-1번지 2층호41212037.652913126.90664
8고양시한양물류(주)20000523운영중<NA>경기도 고양시 일산동구 호수로 688, A동 1507호 (장항동, 코오롱레이크폴리스2)경기도 고양시 일산동구 장항동 749번지 코오롱레이크폴리스2 A동 1507호41038137.662774126.763814
9고양시비전종합물류20020305운영중<NA>경기도 고양시 일산서구 멱절길124번길 20-8, 105호 (대화동)경기도 고양시 일산서구 대화동 1926-33번지 105호41141037.6576126.733516
시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
2863화성시한빛특송퀵화물19980527폐업 등20130326경기도 화성시 향남읍 토성로 423경기도 화성시 향남읍 요리 190-1번지 32통44592437.111591126.964652
2864화성시무지개퀵화물20020424폐업 등20140120경기도 화성시 팔탄면 하저자안로 59-16경기도 화성시 팔탄면 하저리 596-4번지44595837.185777126.869137
2865화성시혜성로지스19920131폐업 등20121101경기도 화성시 팔탄면 서해로 1278경기도 화성시 팔탄면 창곡리 1013-3번지44594937.175191126.887465
2866화성시대박물류19930129폐업 등20131105경기도 화성시 팔탄면 온천로 318경기도 화성시 팔탄면 덕천리 117-1번지44591937.147126.872323
2867화성시마도퀵특송19940827폐업 등20110711경기도 화성시 마도면 화성로 790경기도 화성시 마도면 두곡리 347번지44586237.206682126.775253
2868화성시팔탄화물19940112폐업 등20131029경기도 화성시 팔탄면 서해로987번길 15, 5동 108호경기도 화성시 팔탄면 지월리 499-3번지 5동 108호44591737.150253126.890294
2869화성시비전화물19991210폐업 등20130529경기도 화성시 정남면 정남동로 134경기도 화성시 정남면 덕절리 287번지44596437.141087127.024841
2870화성시아줌마물류20030115폐업 등20160111경기도 화성시 마도면 마도공단로1길 8, 다동 303호 (마도유통공구상가)경기도 화성시 마도면 쌍송리 662번지 마도유통공구상가 가동 319호44586137.18605126.790417
2871화성시공단화물20030806폐업 등20110525경기도 화성시 정남면 시청로 1604경기도 화성시 정남면 백리 76번지 207호44596237.170245126.951291
2872화성시세광종합화물20020830폐업 등20110112경기도 화성시 남양읍 화성로 1280경기도 화성시 남양읍 송림리 220-3번지44505037.217018126.822856