Overview

Dataset statistics

Number of variables10
Number of observations294
Missing cells240
Missing cells (%)8.2%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory24.5 KiB
Average record size in memory85.4 B

Variable types

Categorical2
Text3
Numeric5

Dataset

Description특수여객업체 현황_인허가
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=OSU9J5N9K0OWJ3265NNR1307389&infSeq=1

Alerts

Dataset has 1 (0.3%) duplicate rowsDuplicates
인허가일자 is highly overall correlated with 폐업일자 and 1 other fieldsHigh correlation
폐업일자 is highly overall correlated with 인허가일자 and 1 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with 인허가일자 and 1 other fieldsHigh 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 217 (73.8%) missing valuesMissing
소재지도로명주소 has 20 (6.8%) missing valuesMissing

Reproduction

Analysis started2023-12-10 21:19:00.598512
Analysis finished2023-12-10 21:19:03.634320
Duration3.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
고양시
38 
평택시
23 
파주시
18 
부천시
18 
수원시
18 
Other values (25)
179 

Length

Max length4
Median length3
Mean length3.0646259
Min length3

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
고양시 38
 
12.9%
평택시 23
 
7.8%
파주시 18
 
6.1%
부천시 18
 
6.1%
수원시 18
 
6.1%
안성시 16
 
5.4%
화성시 13
 
4.4%
포천시 13
 
4.4%
남양주시 13
 
4.4%
성남시 13
 
4.4%
Other values (20) 111
37.8%

Length

2023-12-11T06:19:03.702440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 38
 
12.9%
평택시 23
 
7.8%
파주시 18
 
6.1%
부천시 18
 
6.1%
수원시 18
 
6.1%
안성시 16
 
5.4%
화성시 13
 
4.4%
포천시 13
 
4.4%
남양주시 13
 
4.4%
성남시 13
 
4.4%
Other values (20) 111
37.8%

사업장명
Text

Distinct274
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T06:19:03.927159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length6.9693878
Min length2

Characters and Unicode

Total characters2049
Distinct characters240
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

Unique255 ?
Unique (%)86.7%

Sample

1st row연새장례식장
2nd row가평군농업협동조합 장례문화센터
3rd row연새장례예식장
4th row연세장례예식장
5th row(주)다운
ValueCountFrequency (%)
주식회사 5
 
1.6%
장례식장 5
 
1.6%
하늘 3
 
1.0%
금강특수 2
 
0.6%
주)천지인장묘개발 2
 
0.6%
예지장례예식장 2
 
0.6%
특수여객 2
 
0.6%
전국연합장의사 2
 
0.6%
주)대주리무진 2
 
0.6%
선진특수 2
 
0.6%
Other values (276) 288
91.4%
2023-12-11T06:19:04.291329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 168
 
8.2%
수 96
 
4.7%
특 85
 
4.1%
주 81
 
4.0%
) 78
 
3.8%
( 78
 
3.8%
례 62
 
3.0%
여 57
 
2.8%
객 55
 
2.7%
의 53
 
2.6%
Other values (230) 1236
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1855
90.5%
Close Punctuation 78
 
3.8%
Open Punctuation 78
 
3.8%
Space Separator 21
 
1.0%
Decimal Number 10
 
0.5%
Uppercase Letter 4
 
0.2%
Dash Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 168
 
9.1%
수 96
 
5.2%
특 85
 
4.6%
주 81
 
4.4%
례 62
 
3.3%
여 57
 
3.1%
객 55
 
3.0%
의 53
 
2.9%
식 52
 
2.8%
사 46
 
2.5%
Other values (217) 1100
59.3%
Decimal Number
ValueCountFrequency (%)
8 3
30.0%
1 2
20.0%
6 2
20.0%
3 1
 
10.0%
4 1
 
10.0%
2 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
M 2
50.0%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1855
90.5%
Common 190
 
9.3%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 168
 
9.1%
수 96
 
5.2%
특 85
 
4.6%
주 81
 
4.4%
례 62
 
3.3%
여 57
 
3.1%
객 55
 
3.0%
의 53
 
2.9%
식 52
 
2.8%
사 46
 
2.5%
Other values (217) 1100
59.3%
Common
ValueCountFrequency (%)
) 78
41.1%
( 78
41.1%
21
 
11.1%
8 3
 
1.6%
- 2
 
1.1%
1 2
 
1.1%
6 2
 
1.1%
, 1
 
0.5%
3 1
 
0.5%
4 1
 
0.5%
Latin
ValueCountFrequency (%)
K 2
50.0%
M 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1855
90.5%
ASCII 194
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 168
 
9.1%
수 96
 
5.2%
특 85
 
4.6%
주 81
 
4.4%
례 62
 
3.3%
여 57
 
3.1%
객 55
 
3.0%
의 53
 
2.9%
식 52
 
2.8%
사 46
 
2.5%
Other values (217) 1100
59.3%
ASCII
ValueCountFrequency (%)
) 78
40.2%
( 78
40.2%
21
 
10.8%
8 3
 
1.5%
- 2
 
1.0%
1 2
 
1.0%
6 2
 
1.0%
K 2
 
1.0%
M 2
 
1.0%
, 1
 
0.5%
Other values (3) 3
 
1.5%

인허가일자
Real number (ℝ)

HIGH CORRELATION 

Distinct273
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20088635
Minimum19840514
Maximum20180828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:19:04.414086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19840514
5-th percentile19960250
Q120040528
median20101221
Q320140891
95-th percentile20180121
Maximum20180828
Range340314
Interquartile range (IQR)100363

Descriptive statistics

Standard deviation70062.649
Coefficient of variation (CV)0.003487676
Kurtosis-0.0031129764
Mean20088635
Median Absolute Deviation (MAD)49492.5
Skewness-0.81167927
Sum5.9060585 × 109
Variance4.9087748 × 109
MonotonicityNot monotonic
2023-12-11T06:19:04.749560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030408 2
 
0.7%
20110826 2
 
0.7%
20140528 2
 
0.7%
20180803 2
 
0.7%
20170712 2
 
0.7%
20080425 2
 
0.7%
20160502 2
 
0.7%
20091027 2
 
0.7%
20130722 2
 
0.7%
19990202 2
 
0.7%
Other values (263) 274
93.2%
ValueCountFrequency (%)
19840514 1
0.3%
19890627 1
0.3%
19900101 1
0.3%
19910626 1
0.3%
19910730 1
0.3%
19930318 1
0.3%
19930409 1
0.3%
19931011 1
0.3%
19931206 1
0.3%
19940208 1
0.3%
ValueCountFrequency (%)
20180828 1
0.3%
20180803 2
0.7%
20180725 1
0.3%
20180718 1
0.3%
20180703 1
0.3%
20180618 1
0.3%
20180615 1
0.3%
20180611 1
0.3%
20180523 1
0.3%
20180323 1
0.3%

영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
운영중
217 
폐업 등
77 

Length

Max length4
Median length3
Mean length3.2619048
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 217
73.8%
폐업 등 77
 
26.2%

Length

2023-12-11T06:19:04.878400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:19:04.964805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 217
58.5%
폐업 77
 
20.8%
등 77
 
20.8%

폐업일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct74
Distinct (%)96.1%
Missing217
Missing (%)73.8%
Infinite0
Infinite (%)0.0%
Mean20126044
Minimum20050530
Maximum20180611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:19:05.063578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050530
5-th percentile20078947
Q120101102
median20130516
Q320150828
95-th percentile20173024
Maximum20180611
Range130081
Interquartile range (IQR)49726

Descriptive statistics

Standard deviation29875.508
Coefficient of variation (CV)0.0014844203
Kurtosis-0.22395374
Mean20126044
Median Absolute Deviation (MAD)20505
Skewness-0.28341905
Sum1.5497054 × 109
Variance8.9254598 × 108
MonotonicityNot monotonic
2023-12-11T06:19:05.196572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20101029 2
 
0.7%
20180207 2
 
0.7%
20131213 2
 
0.7%
20130516 1
 
0.3%
20130408 1
 
0.3%
20160909 1
 
0.3%
20121106 1
 
0.3%
20090327 1
 
0.3%
20120628 1
 
0.3%
20140730 1
 
0.3%
Other values (64) 64
 
21.8%
(Missing) 217
73.8%
ValueCountFrequency (%)
20050530 1
0.3%
20051101 1
0.3%
20070507 1
0.3%
20070613 1
0.3%
20081031 1
0.3%
20081216 1
0.3%
20090116 1
0.3%
20090219 1
0.3%
20090327 1
0.3%
20090402 1
0.3%
ValueCountFrequency (%)
20180611 1
0.3%
20180523 1
0.3%
20180207 2
0.7%
20171228 1
0.3%
20161103 1
0.3%
20160909 1
0.3%
20160530 1
0.3%
20160510 1
0.3%
20160503 1
0.3%
20160502 1
0.3%

소재지도로명주소
Text

MISSING 

Distinct241
Distinct (%)88.0%
Missing20
Missing (%)6.8%
Memory size2.4 KiB
2023-12-11T06:19:05.428437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length42
Mean length24.532847
Min length14

Characters and Unicode

Total characters6722
Distinct characters280
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

Unique214 ?
Unique (%)78.1%

Sample

1st row경기도 가평군 청평면 경춘로 1219
2nd row경기도 가평군 가평읍 경춘로 1775 (가평군농업협동조합장례문화센터)
3rd row경기도 가평군 청평면 경춘로 1219
4th row경기도 가평군 청평면 경춘로 1219
5th row경기도 고양시 일산동구 지영로 81 (지영동)
ValueCountFrequency (%)
경기도 274
 
18.3%
고양시 35
 
2.3%
일산동구 20
 
1.3%
파주시 18
 
1.2%
부천시 18
 
1.2%
안성시 16
 
1.1%
평택시 16
 
1.1%
수원시 15
 
1.0%
덕양구 14
 
0.9%
화성시 13
 
0.9%
Other values (625) 1056
70.6%
2023-12-11T06:19:05.781125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1221
 
18.2%
경 291
 
4.3%
도 289
 
4.3%
기 286
 
4.3%
시 273
 
4.1%
1 246
 
3.7%
로 241
 
3.6%
동 191
 
2.8%
2 153
 
2.3%
) 142
 
2.1%
Other values (270) 3389
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4001
59.5%
Space Separator 1221
 
18.2%
Decimal Number 1084
 
16.1%
Close Punctuation 142
 
2.1%
Open Punctuation 142
 
2.1%
Other Punctuation 67
 
1.0%
Dash Punctuation 51
 
0.8%
Uppercase Letter 14
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 291
 
7.3%
도 289
 
7.2%
기 286
 
7.1%
시 273
 
6.8%
로 241
 
6.0%
동 191
 
4.8%
양 101
 
2.5%
길 100
 
2.5%
구 100
 
2.5%
안 70
 
1.7%
Other values (248) 2059
51.5%
Decimal Number
ValueCountFrequency (%)
1 246
22.7%
2 153
14.1%
3 137
12.6%
5 102
9.4%
4 98
 
9.0%
0 81
 
7.5%
8 72
 
6.6%
9 68
 
6.3%
7 66
 
6.1%
6 61
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
I 7
50.0%
B 2
 
14.3%
C 1
 
7.1%
E 1
 
7.1%
T 1
 
7.1%
H 1
 
7.1%
L 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1221
100.0%
Close Punctuation
ValueCountFrequency (%)
) 142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 142
100.0%
Other Punctuation
ValueCountFrequency (%)
, 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4001
59.5%
Common 2707
40.3%
Latin 14
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 291
 
7.3%
도 289
 
7.2%
기 286
 
7.1%
시 273
 
6.8%
로 241
 
6.0%
동 191
 
4.8%
양 101
 
2.5%
길 100
 
2.5%
구 100
 
2.5%
안 70
 
1.7%
Other values (248) 2059
51.5%
Common
ValueCountFrequency (%)
1221
45.1%
1 246
 
9.1%
2 153
 
5.7%
) 142
 
5.2%
( 142
 
5.2%
3 137
 
5.1%
5 102
 
3.8%
4 98
 
3.6%
0 81
 
3.0%
8 72
 
2.7%
Other values (5) 313
 
11.6%
Latin
ValueCountFrequency (%)
I 7
50.0%
B 2
 
14.3%
C 1
 
7.1%
E 1
 
7.1%
T 1
 
7.1%
H 1
 
7.1%
L 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4001
59.5%
ASCII 2721
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1221
44.9%
1 246
 
9.0%
2 153
 
5.6%
) 142
 
5.2%
( 142
 
5.2%
3 137
 
5.0%
5 102
 
3.7%
4 98
 
3.6%
0 81
 
3.0%
8 72
 
2.6%
Other values (12) 327
 
12.0%
Hangul
ValueCountFrequency (%)
경 291
 
7.3%
도 289
 
7.2%
기 286
 
7.1%
시 273
 
6.8%
로 241
 
6.0%
동 191
 
4.8%
양 101
 
2.5%
길 100
 
2.5%
구 100
 
2.5%
안 70
 
1.7%
Other values (248) 2059
51.5%

소재지지번주소
Text

Distinct251
Distinct (%)86.0%
Missing2
Missing (%)0.7%
Memory size2.4 KiB
2023-12-11T06:19:06.037420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length39
Mean length23.842466
Min length11

Characters and Unicode

Total characters6962
Distinct characters251
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

Unique217 ?
Unique (%)74.3%

Sample

1st row경기도 가평군 청평면 상천리 1148-3번지
2nd row경기도 가평군 가평읍 상색리 269-1번지 가평군농업협동조합장례문화센터
3rd row경기도 가평군 청평면 상천리 1148-3번지
4th row경기도 가평군 청평면 상천리 1148-3번지
5th row경기도 고양시 일산동구 지영동 382-16번지 1층 일부
ValueCountFrequency (%)
경기도 292
 
19.6%
고양시 38
 
2.5%
평택시 23
 
1.5%
일산동구 20
 
1.3%
파주시 18
 
1.2%
부천시 18
 
1.2%
수원시 18
 
1.2%
덕양구 17
 
1.1%
안성시 16
 
1.1%
안산시 13
 
0.9%
Other values (610) 1020
68.3%
2023-12-11T06:19:06.408023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1201
 
17.3%
도 308
 
4.4%
기 302
 
4.3%
지 302
 
4.3%
경 293
 
4.2%
번 286
 
4.1%
시 280
 
4.0%
동 244
 
3.5%
1 243
 
3.5%
- 223
 
3.2%
Other values (241) 3280
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4234
60.8%
Decimal Number 1280
 
18.4%
Space Separator 1201
 
17.3%
Dash Punctuation 223
 
3.2%
Uppercase Letter 16
 
0.2%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 308
 
7.3%
기 302
 
7.1%
지 302
 
7.1%
경 293
 
6.9%
번 286
 
6.8%
시 280
 
6.6%
동 244
 
5.8%
양 112
 
2.6%
리 109
 
2.6%
구 105
 
2.5%
Other values (218) 1893
44.7%
Decimal Number
ValueCountFrequency (%)
1 243
19.0%
2 166
13.0%
3 151
11.8%
4 144
11.2%
5 111
8.7%
0 101
7.9%
9 99
7.7%
6 96
 
7.5%
7 95
 
7.4%
8 74
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
I 7
43.8%
B 3
18.8%
C 1
 
6.2%
E 1
 
6.2%
A 1
 
6.2%
T 1
 
6.2%
H 1
 
6.2%
L 1
 
6.2%
Space Separator
ValueCountFrequency (%)
1201
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4234
60.8%
Common 2712
39.0%
Latin 16
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 308
 
7.3%
기 302
 
7.1%
지 302
 
7.1%
경 293
 
6.9%
번 286
 
6.8%
시 280
 
6.6%
동 244
 
5.8%
양 112
 
2.6%
리 109
 
2.6%
구 105
 
2.5%
Other values (218) 1893
44.7%
Common
ValueCountFrequency (%)
1201
44.3%
1 243
 
9.0%
- 223
 
8.2%
2 166
 
6.1%
3 151
 
5.6%
4 144
 
5.3%
5 111
 
4.1%
0 101
 
3.7%
9 99
 
3.7%
6 96
 
3.5%
Other values (5) 177
 
6.5%
Latin
ValueCountFrequency (%)
I 7
43.8%
B 3
18.8%
C 1
 
6.2%
E 1
 
6.2%
A 1
 
6.2%
T 1
 
6.2%
H 1
 
6.2%
L 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4234
60.8%
ASCII 2728
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1201
44.0%
1 243
 
8.9%
- 223
 
8.2%
2 166
 
6.1%
3 151
 
5.5%
4 144
 
5.3%
5 111
 
4.1%
0 101
 
3.7%
9 99
 
3.6%
6 96
 
3.5%
Other values (13) 193
 
7.1%
Hangul
ValueCountFrequency (%)
도 308
 
7.3%
기 302
 
7.1%
지 302
 
7.1%
경 293
 
6.9%
번 286
 
6.8%
시 280
 
6.6%
동 244
 
5.8%
양 112
 
2.6%
리 109
 
2.6%
구 105
 
2.5%
Other values (218) 1893
44.7%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct238
Distinct (%)81.2%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean268327.72
Minimum10108
Maximum487922
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:19:06.532494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10108
5-th percentile10414
Q114556
median415030
Q3451884
95-th percentile480823.6
Maximum487922
Range477814
Interquartile range (IQR)437328

Descriptive statistics

Standard deviation214670.26
Coefficient of variation (CV)0.80003012
Kurtosis-1.8705798
Mean268327.72
Median Absolute Deviation (MAD)61774
Skewness-0.33185967
Sum78620022
Variance4.6083319 × 1010
MonotonicityNot monotonic
2023-12-11T06:19:06.648728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10414 7
 
2.4%
425021 5
 
1.7%
472847 5
 
1.7%
476841 4
 
1.4%
451881 3
 
1.0%
476804 3
 
1.0%
426860 3
 
1.0%
477814 3
 
1.0%
10267 3
 
1.0%
17595 2
 
0.7%
Other values (228) 255
86.7%
ValueCountFrequency (%)
10108 1
 
0.3%
10135 1
 
0.3%
10254 1
 
0.3%
10267 3
1.0%
10278 1
 
0.3%
10312 2
 
0.7%
10364 1
 
0.3%
10401 2
 
0.7%
10407 1
 
0.3%
10414 7
2.4%
ValueCountFrequency (%)
487922 1
0.3%
487915 2
0.7%
487911 1
0.3%
487862 1
0.3%
487831 1
0.3%
487825 1
0.3%
487824 1
0.3%
487805 1
0.3%
487712 1
0.3%
486903 2
0.7%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct241
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.451121
Minimum36.954451
Maximum38.049201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:19:06.773865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.954451
5-th percentile37.003945
Q137.272019
median37.464938
Q337.657401
95-th percentile37.847097
Maximum38.049201
Range1.0947504
Interquartile range (IQR)0.38538277

Descriptive statistics

Standard deviation0.26292195
Coefficient of variation (CV)0.0070204027
Kurtosis-0.84076154
Mean37.451121
Median Absolute Deviation (MAD)0.1931993
Skewness-0.063751648
Sum11010.63
Variance0.069127953
MonotonicityNot monotonic
2023-12-11T06:19:06.909104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6534042834 8
 
2.7%
37.6236426937 4
 
1.4%
37.7660460901 3
 
1.0%
37.317285459 3
 
1.0%
37.3030626189 3
 
1.0%
37.7562640104 3
 
1.0%
37.278574467 2
 
0.7%
37.3082817156 2
 
0.7%
37.3368079341 2
 
0.7%
37.3527743918 2
 
0.7%
Other values (231) 262
89.1%
ValueCountFrequency (%)
36.9544505732 1
0.3%
36.9721392604 2
0.7%
36.9809342926 2
0.7%
36.9814067112 1
0.3%
36.9817204649 1
0.3%
36.9817741712 1
0.3%
36.9927446012 1
0.3%
36.9931579592 1
0.3%
36.9960189752 1
0.3%
36.9963332657 2
0.7%
ValueCountFrequency (%)
38.0492009659 1
0.3%
38.0370955955 1
0.3%
38.0174005605 2
0.7%
37.9516278768 1
0.3%
37.934746289 2
0.7%
37.9040569381 1
0.3%
37.8970810772 1
0.3%
37.8884116656 1
0.3%
37.8713320767 1
0.3%
37.8526729854 2
0.7%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct241
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03687
Minimum126.5404
Maximum127.64731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:19:07.038379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5404
5-th percentile126.7451
Q1126.83075
median127.02215
Q3127.18712
95-th percentile127.50804
Maximum127.64731
Range1.106907
Interquartile range (IQR)0.35636816

Descriptive statistics

Standard deviation0.2394773
Coefficient of variation (CV)0.0018851008
Kurtosis-0.27966341
Mean127.03687
Median Absolute Deviation (MAD)0.18640206
Skewness0.61105246
Sum37348.839
Variance0.057349378
MonotonicityNot monotonic
2023-12-11T06:19:07.161258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7778507772 8
 
2.7%
127.2875191388 4
 
1.4%
127.4458963115 3
 
1.0%
126.842269145 3
 
1.0%
126.8754039565 3
 
1.0%
127.0215148306 3
 
1.0%
127.0331682113 2
 
0.7%
126.8277709217 2
 
0.7%
126.7282000609 2
 
0.7%
126.7245527449 2
 
0.7%
Other values (231) 262
89.1%
ValueCountFrequency (%)
126.5403987483 2
0.7%
126.6965851612 1
0.3%
126.7040838835 1
0.3%
126.7069814413 1
0.3%
126.7150553782 1
0.3%
126.7157496052 1
0.3%
126.7245527449 2
0.7%
126.725341158 1
0.3%
126.7282000609 2
0.7%
126.7300039897 1
0.3%
ValueCountFrequency (%)
127.6473057841 1
0.3%
127.6454641724 1
0.3%
127.6424377689 1
0.3%
127.6318630637 1
0.3%
127.6251908362 2
0.7%
127.5951674256 1
0.3%
127.593023065 1
0.3%
127.5888376352 1
0.3%
127.5835621795 1
0.3%
127.551171944 1
0.3%

Interactions

2023-12-11T06:19:02.752980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.112294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.525863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.931779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.365914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.876938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.191644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.605538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.017354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.444102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:03.004738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.275761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.682903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.119076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.524877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:03.130863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.354938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.758635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.217003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.600457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:03.232383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.436207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:01.851172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.295985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:19:02.675310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:19:07.242957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가일자영업상태명폐업일자소재지우편번호WGS84위도WGS84경도
시군명1.0000.3960.2030.4570.8280.9730.958
인허가일자0.3961.0000.1640.5380.7690.0000.098
영업상태명0.2030.1641.000NaN0.1380.0000.135
폐업일자0.4570.538NaN1.0000.4620.0000.000
소재지우편번호0.8280.7690.1380.4621.0000.3990.631
WGS84위도0.9730.0000.0000.0000.3991.0000.656
WGS84경도0.9580.0980.1350.0000.6310.6561.000
2023-12-11T06:19:07.339364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명
시군명1.0000.152
영업상태명0.1521.000
2023-12-11T06:19:07.415252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자폐업일자소재지우편번호WGS84위도WGS84경도시군명영업상태명
인허가일자1.0000.535-0.5160.005-0.0790.1710.155
폐업일자0.5351.000-0.431-0.126-0.0480.2101.000
소재지우편번호-0.516-0.4311.000-0.1440.4300.5470.229
WGS84위도0.005-0.126-0.1441.000-0.2260.7210.000
WGS84경도-0.079-0.0480.430-0.2261.0000.6670.102
시군명0.1710.2100.5470.7210.6671.0000.152
영업상태명0.1551.0000.2290.0000.1020.1521.000

Missing values

2023-12-11T06:19:03.338422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:19:03.472541image/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.
2023-12-11T06:19:03.584335image/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
0가평군연새장례식장20151201운영중<NA>경기도 가평군 청평면 경춘로 1219경기도 가평군 청평면 상천리 1148-3번지47781437.766046127.445896
1가평군가평군농업협동조합 장례문화센터19960425운영중<NA>경기도 가평군 가평읍 경춘로 1775 (가평군농업협동조합장례문화센터)경기도 가평군 가평읍 상색리 269-1번지 가평군농업협동조합장례문화센터1242637.798044127.481307
2가평군연새장례예식장20140912폐업 등20151201경기도 가평군 청평면 경춘로 1219경기도 가평군 청평면 상천리 1148-3번지47781437.766046127.445896
3가평군연세장례예식장20041118폐업 등20140903경기도 가평군 청평면 경춘로 1219경기도 가평군 청평면 상천리 1148-3번지47781437.766046127.445896
4고양시(주)다운20130708운영중<NA>경기도 고양시 일산동구 지영로 81 (지영동)경기도 고양시 일산동구 지영동 382-16번지 1층 일부1025437.708151126.822037
5고양시금강특수20130726운영중<NA>경기도 고양시 일산동구 일산로 78, 7층 707호 (백석동, 백석위브센티움)경기도 고양시 일산동구 백석동 1241-2번지1045037.644463126.790409
6고양시(주)나래장의개발20140314운영중<NA>경기도 고양시 일산동구 강석로 145 (마두동)경기도 고양시 일산동구 마두동 799-4번지1041437.653404126.777851
7고양시진명특수여객20141126운영중<NA>경기도 고양시 일산동구 강석로 145, 고양축협 마두지점 2층 3호 (마두동)경기도 고양시 일산동구 마두동 799-4번지 고양축협 마두지점1041437.653404126.777851
8고양시그린장묘20161220운영중<NA>경기도 고양시 일산동구 강석로 145, 203호 (마두동, 고양축협 마두지점)경기도 고양시 일산동구 마두동 799-4번지 축협빌딩 203호1041437.653404126.777851
9고양시제이씨아이(주)20180119운영중<NA>경기도 고양시 덕양구 보광로 184 (벽제동)경기도 고양시 덕양구 벽제동 564-1번지1026737.730651126.910668
시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
284화성시(주)효원장례문화센타20011211운영중<NA>경기도 화성시 정조로 107 (반정동)경기도 화성시 반정동 508-3번지1839037.220658127.026452
285화성시(주)봉담장례문화원20090720운영중<NA>경기도 화성시 봉담읍 서봉산길 40경기도 화성시 봉담읍 유리 150번지1833537.175887126.936818
286화성시효원특수여객20170220운영중<NA>경기도 화성시 향남읍 발안로 322경기도 화성시 향남읍 관리 295-14번지1858937.132667126.94201
287화성시화성중앙병원장례식장20160530운영중<NA>경기도 화성시 향남읍 발안로 5경기도 화성시 향남읍 평리 74-1번지1859237.131277126.910827
288화성시(주)함께향남실버케어센터20110217폐업 등20150828경기도 화성시 향남읍 제암길56번길 75경기도 화성시 향남읍 제암리 340-4번지44594637.13003126.896097
289화성시화성중앙병원장례식장식당20130531폐업 등20160530경기도 화성시 향남읍 발안로 5경기도 화성시 향남읍 평리 74-1번지1859237.131277126.910827
290화성시승전자동차(주)20091009폐업 등20140501경기도 화성시 효행로 211경기도 화성시 기안동 333-1번지44531037.22863126.97123
291화성시(주)세운20110214폐업 등20130801경기도 화성시 남양읍 남양성지로 254-3경기도 화성시 남양읍 남양리 1417-2번지44501037.213406126.829444
292화성시건국리무진20120816폐업 등20130830경기도 화성시 효행로 211 (기안동)경기도 화성시 기안동 333-1번지1833737.22863126.97123
293화성시(주)드림20121113폐업 등20160502경기도 화성시 송산면 화성로 284경기도 화성시 송산면 육일리 412-2번지44587337.202738126.725341

Duplicate rows

Most frequently occurring

시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도# duplicates
0파주시(주)삼육리무진20151210폐업 등20180207경기도 파주시 광탄면 혜음로454번길 18-12 (자동화산업)경기도 파주시 광탄면 용미리 260-1번지 (자동화산업)1095537.734819126.8859442