Overview

Dataset statistics

Number of variables11
Number of observations91
Missing cells88
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory94.5 B

Variable types

Categorical3
Text3
Numeric5

Alerts

업체유형명 has constant value ""Constant
인허가일자 is highly overall correlated with 소재지우편번호High correlation
폐업일자 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with 인허가일자 and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 폐업일자 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 폐업일자 and 3 other fieldsHigh correlation
영업상태명 is highly overall correlated with 폐업일자High correlation
폐업일자 has 76 (83.5%) missing valuesMissing
소재지도로명주소 has 12 (13.2%) missing valuesMissing

Reproduction

Analysis started2023-12-10 20:59:52.423105
Analysis finished2023-12-10 20:59:56.636920
Duration4.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size860.0 B
파주시
13 
수원시
9 
고양시
8 
부천시
6 
화성시
 
5
Other values (23)
50 

Length

Max length4
Median length3
Mean length3.0659341
Min length3

Unique

Unique6 ?
Unique (%)6.6%

Sample

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

Common Values

ValueCountFrequency (%)
파주시 13
14.3%
수원시 9
 
9.9%
고양시 8
 
8.8%
부천시 6
 
6.6%
화성시 5
 
5.5%
시흥시 5
 
5.5%
포천시 4
 
4.4%
평택시 4
 
4.4%
광명시 3
 
3.3%
김포시 3
 
3.3%
Other values (18) 31
34.1%

Length

2023-12-11T05:59:56.707226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
파주시 13
14.3%
수원시 9
 
9.9%
고양시 8
 
8.8%
부천시 6
 
6.6%
화성시 5
 
5.5%
시흥시 5
 
5.5%
포천시 4
 
4.4%
평택시 4
 
4.4%
광명시 3
 
3.3%
김포시 3
 
3.3%
Other values (18) 31
34.1%

사업장명
Text

Distinct77
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-11T05:59:56.941746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.2527473
Min length4

Characters and Unicode

Total characters660
Distinct characters109
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)75.8%

Sample

1st row(주)진흥고속
2nd row남정여객
3rd row고양교통(주)
4th row(주)뉴그랜드관광
5th row명성운수(주)
ValueCountFrequency (%)
신성여객(주 5
 
5.2%
주식회사 5
 
5.2%
주)시흥교통 5
 
5.2%
합)신일여객 3
 
3.1%
주)화성운수 2
 
2.1%
선진버스 2
 
2.1%
파주선진(주 2
 
2.1%
합자)경남여객 2
 
2.1%
대양운수 2
 
2.1%
경진여객운수㈜ 2
 
2.1%
Other values (67) 67
69.1%
2023-12-11T05:59:57.344522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 70
 
10.6%
( 61
 
9.2%
) 60
 
9.1%
여 28
 
4.2%
객 27
 
4.1%
운 24
 
3.6%
수 22
 
3.3%
사 15
 
2.3%
성 14
 
2.1%
식 13
 
2.0%
Other values (99) 326
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 519
78.6%
Open Punctuation 62
 
9.4%
Close Punctuation 61
 
9.2%
Other Symbol 12
 
1.8%
Space Separator 6
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 70
 
13.5%
여 28
 
5.4%
객 27
 
5.2%
운 24
 
4.6%
수 22
 
4.2%
사 15
 
2.9%
성 14
 
2.7%
식 13
 
2.5%
스 13
 
2.5%
신 13
 
2.5%
Other values (93) 280
53.9%
Open Punctuation
ValueCountFrequency (%)
( 61
98.4%
[ 1
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 60
98.4%
] 1
 
1.6%
Other Symbol
ValueCountFrequency (%)
㈜ 12
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 531
80.5%
Common 129
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 70
 
13.2%
여 28
 
5.3%
객 27
 
5.1%
운 24
 
4.5%
수 22
 
4.1%
사 15
 
2.8%
성 14
 
2.6%
식 13
 
2.4%
스 13
 
2.4%
신 13
 
2.4%
Other values (94) 292
55.0%
Common
ValueCountFrequency (%)
( 61
47.3%
) 60
46.5%
6
 
4.7%
] 1
 
0.8%
[ 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 519
78.6%
ASCII 129
 
19.5%
None 12
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 70
 
13.5%
여 28
 
5.4%
객 27
 
5.2%
운 24
 
4.6%
수 22
 
4.2%
사 15
 
2.9%
성 14
 
2.7%
식 13
 
2.5%
스 13
 
2.5%
신 13
 
2.5%
Other values (93) 280
53.9%
ASCII
ValueCountFrequency (%)
( 61
47.3%
) 60
46.5%
6
 
4.7%
] 1
 
0.8%
[ 1
 
0.8%
None
ValueCountFrequency (%)
㈜ 12
100.0%

인허가일자
Real number (ℝ)

HIGH CORRELATION 

Distinct83
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20034714
Minimum19490107
Maximum20180731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-11T05:59:57.500358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19490107
5-th percentile19691016
Q119980621
median20090720
Q320160664
95-th percentile20180366
Maximum20180731
Range690624
Interquartile range (IQR)180042.5

Descriptive statistics

Standard deviation162634.32
Coefficient of variation (CV)0.0081176266
Kurtosis1.0632428
Mean20034714
Median Absolute Deviation (MAD)79607
Skewness-1.3462708
Sum1.8231589 × 109
Variance2.6449923 × 1010
MonotonicityNot monotonic
2023-12-11T05:59:57.632237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160421 2
 
2.2%
20130625 2
 
2.2%
20170327 2
 
2.2%
20150803 2
 
2.2%
19760331 2
 
2.2%
20170901 2
 
2.2%
20121221 2
 
2.2%
20160422 2
 
2.2%
20040108 1
 
1.1%
20040915 1
 
1.1%
Other values (73) 73
80.2%
ValueCountFrequency (%)
19490107 1
1.1%
19620710 1
1.1%
19620807 1
1.1%
19681007 1
1.1%
19681220 1
1.1%
19700813 1
1.1%
19730201 1
1.1%
19760331 2
2.2%
19760612 1
1.1%
19770610 1
1.1%
ValueCountFrequency (%)
20180731 1
1.1%
20180713 1
1.1%
20180712 1
1.1%
20180518 1
1.1%
20180504 1
1.1%
20180228 1
1.1%
20180213 1
1.1%
20171228 1
1.1%
20171113 1
1.1%
20170901 2
2.2%

영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
운영중
76 
폐업 등
15 

Length

Max length4
Median length3
Mean length3.1648352
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 76
83.5%
폐업 등 15
 
16.5%

Length

2023-12-11T05:59:57.765675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:59:57.889417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 76
71.7%
폐업 15
 
14.2%
등 15
 
14.2%

폐업일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)80.0%
Missing76
Missing (%)83.5%
Infinite0
Infinite (%)0.0%
Mean20163413
Minimum20070402
Maximum20180814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-11T05:59:58.032193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070402
5-th percentile20126976
Q120160765
median20170601
Q320180562
95-th percentile20180814
Maximum20180814
Range110412
Interquartile range (IQR)19796.5

Descriptive statistics

Standard deviation27437.744
Coefficient of variation (CV)0.0013607688
Kurtosis10.835512
Mean20163413
Median Absolute Deviation (MAD)9973
Skewness-3.1084346
Sum3.024512 × 108
Variance7.528298 × 108
MonotonicityNot monotonic
2023-12-11T05:59:58.172312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20180814 4
 
4.4%
20160628 1
 
1.1%
20070402 1
 
1.1%
20170901 1
 
1.1%
20151222 1
 
1.1%
20160902 1
 
1.1%
20161116 1
 
1.1%
20160422 1
 
1.1%
20170209 1
 
1.1%
20170601 1
 
1.1%
Other values (2) 2
 
2.2%
(Missing) 76
83.5%
ValueCountFrequency (%)
20070402 1
1.1%
20151222 1
1.1%
20160422 1
1.1%
20160628 1
1.1%
20160902 1
1.1%
20161116 1
1.1%
20170209 1
1.1%
20170601 1
1.1%
20170901 1
1.1%
20171229 1
1.1%
ValueCountFrequency (%)
20180814 4
4.4%
20180309 1
 
1.1%
20171229 1
 
1.1%
20170901 1
 
1.1%
20170601 1
 
1.1%
20170209 1
 
1.1%
20161116 1
 
1.1%
20160902 1
 
1.1%
20160628 1
 
1.1%
20160422 1
 
1.1%

업체유형명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
시내버스
91 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시내버스 91
100.0%

Length

2023-12-11T05:59:58.314513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:59:58.649059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시내버스 91
100.0%

소재지도로명주소
Text

MISSING 

Distinct67
Distinct (%)84.8%
Missing12
Missing (%)13.2%
Memory size860.0 B
2023-12-11T05:59:58.984313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length24.822785
Min length15

Characters and Unicode

Total characters1961
Distinct characters175
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)73.4%

Sample

1st row경기도 가평군 가평읍 가화로 51
2nd row경기도 고양시 일산동구 성현로431번길 40 (문봉동)
3rd row경기도 고양시 일산동구무궁화로 385-11(식사동)
4th row경기도 고양시 일산동구 중앙로 1233, 현대타운빌 433호 (장항동)
5th row경기도 고양시 일산서구대화로 97(대화동)
ValueCountFrequency (%)
경기도 79
 
18.8%
파주시 11
 
2.6%
고양시 8
 
1.9%
교하로 6
 
1.4%
1358 6
 
1.4%
교하동 6
 
1.4%
수원시 6
 
1.4%
부천시 6
 
1.4%
신현로 5
 
1.2%
181 5
 
1.2%
Other values (205) 283
67.2%
2023-12-11T05:59:59.520610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
342
 
17.4%
시 84
 
4.3%
경 82
 
4.2%
도 81
 
4.1%
기 81
 
4.1%
로 75
 
3.8%
1 71
 
3.6%
동 71
 
3.6%
( 58
 
3.0%
) 58
 
3.0%
Other values (165) 958
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1193
60.8%
Space Separator 342
 
17.4%
Decimal Number 277
 
14.1%
Open Punctuation 58
 
3.0%
Close Punctuation 58
 
3.0%
Other Punctuation 21
 
1.1%
Dash Punctuation 12
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 84
 
7.0%
경 82
 
6.9%
도 81
 
6.8%
기 81
 
6.8%
로 75
 
6.3%
동 71
 
6.0%
고 25
 
2.1%
구 23
 
1.9%
하 22
 
1.8%
주 21
 
1.8%
Other values (150) 628
52.6%
Decimal Number
ValueCountFrequency (%)
1 71
25.6%
3 34
12.3%
2 32
11.6%
8 28
 
10.1%
5 23
 
8.3%
7 20
 
7.2%
4 18
 
6.5%
6 18
 
6.5%
9 18
 
6.5%
0 15
 
5.4%
Space Separator
ValueCountFrequency (%)
342
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1193
60.8%
Common 768
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 84
 
7.0%
경 82
 
6.9%
도 81
 
6.8%
기 81
 
6.8%
로 75
 
6.3%
동 71
 
6.0%
고 25
 
2.1%
구 23
 
1.9%
하 22
 
1.8%
주 21
 
1.8%
Other values (150) 628
52.6%
Common
ValueCountFrequency (%)
342
44.5%
1 71
 
9.2%
( 58
 
7.6%
) 58
 
7.6%
3 34
 
4.4%
2 32
 
4.2%
8 28
 
3.6%
5 23
 
3.0%
, 21
 
2.7%
7 20
 
2.6%
Other values (5) 81
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1193
60.8%
ASCII 768
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
342
44.5%
1 71
 
9.2%
( 58
 
7.6%
) 58
 
7.6%
3 34
 
4.4%
2 32
 
4.2%
8 28
 
3.6%
5 23
 
3.0%
, 21
 
2.7%
7 20
 
2.6%
Other values (5) 81
 
10.5%
Hangul
ValueCountFrequency (%)
시 84
 
7.0%
경 82
 
6.9%
도 81
 
6.8%
기 81
 
6.8%
로 75
 
6.3%
동 71
 
6.0%
고 25
 
2.1%
구 23
 
1.9%
하 22
 
1.8%
주 21
 
1.8%
Other values (150) 628
52.6%

소재지지번주소
Text

Distinct78
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-11T05:59:59.851713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length30
Mean length22.252747
Min length16

Characters and Unicode

Total characters2025
Distinct characters149
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)75.8%

Sample

1st row경기도 가평군 가평읍 대곡리 168-9번지
2nd row경기도 고양시 일산동구 문봉동 82-2번지
3rd row경기도 고양시 일산동구 식사동 825-12번지
4th row경기도 고양시 일산동구 장항동 848-1번지 현대타운빌
5th row경기도 고양시 일산서구 대화동 1478번지
ValueCountFrequency (%)
경기도 91
 
20.6%
파주시 13
 
2.9%
수원시 9
 
2.0%
권선구 8
 
1.8%
고양시 8
 
1.8%
부천시 6
 
1.4%
교하동 6
 
1.4%
548번지 6
 
1.4%
포동 5
 
1.1%
67-296번지 5
 
1.1%
Other values (199) 284
64.4%
2023-12-11T06:00:00.300300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
350
 
17.3%
지 100
 
4.9%
시 96
 
4.7%
도 93
 
4.6%
경 91
 
4.5%
기 91
 
4.5%
번 88
 
4.3%
동 82
 
4.0%
- 65
 
3.2%
1 57
 
2.8%
Other values (139) 912
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1264
62.4%
Space Separator 350
 
17.3%
Decimal Number 346
 
17.1%
Dash Punctuation 65
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 100
 
7.9%
시 96
 
7.6%
도 93
 
7.4%
경 91
 
7.2%
기 91
 
7.2%
번 88
 
7.0%
동 82
 
6.5%
구 29
 
2.3%
고 23
 
1.8%
리 22
 
1.7%
Other values (127) 549
43.4%
Decimal Number
ValueCountFrequency (%)
1 57
16.5%
2 46
13.3%
8 38
11.0%
5 38
11.0%
3 34
9.8%
4 34
9.8%
7 33
9.5%
6 33
9.5%
9 18
 
5.2%
0 15
 
4.3%
Space Separator
ValueCountFrequency (%)
350
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1264
62.4%
Common 761
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 100
 
7.9%
시 96
 
7.6%
도 93
 
7.4%
경 91
 
7.2%
기 91
 
7.2%
번 88
 
7.0%
동 82
 
6.5%
구 29
 
2.3%
고 23
 
1.8%
리 22
 
1.7%
Other values (127) 549
43.4%
Common
ValueCountFrequency (%)
350
46.0%
- 65
 
8.5%
1 57
 
7.5%
2 46
 
6.0%
8 38
 
5.0%
5 38
 
5.0%
3 34
 
4.5%
4 34
 
4.5%
7 33
 
4.3%
6 33
 
4.3%
Other values (2) 33
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1264
62.4%
ASCII 761
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
350
46.0%
- 65
 
8.5%
1 57
 
7.5%
2 46
 
6.0%
8 38
 
5.0%
5 38
 
5.0%
3 34
 
4.5%
4 34
 
4.5%
7 33
 
4.3%
6 33
 
4.3%
Other values (2) 33
 
4.3%
Hangul
ValueCountFrequency (%)
지 100
 
7.9%
시 96
 
7.6%
도 93
 
7.4%
경 91
 
7.2%
기 91
 
7.2%
번 88
 
7.0%
동 82
 
6.5%
구 29
 
2.3%
고 23
 
1.8%
리 22
 
1.7%
Other values (127) 549
43.4%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228864.76
Minimum10023
Maximum487914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-11T06:00:00.480985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10023
5-th percentile10293.5
Q112052.5
median18364
Q3446547.5
95-th percentile481070
Maximum487914
Range477891
Interquartile range (IQR)434495

Descriptive statistics

Standard deviation220143.94
Coefficient of variation (CV)0.96189533
Kurtosis-2.0217161
Mean228864.76
Median Absolute Deviation (MAD)8341
Skewness0.038199946
Sum20826693
Variance4.8463355 × 1010
MonotonicityNot monotonic
2023-12-11T06:00:00.662430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10867 6
 
6.6%
14961 5
 
5.5%
441360 3
 
3.3%
420823 2
 
2.2%
10807 2
 
2.2%
445925 2
 
2.2%
14404 2
 
2.2%
465260 2
 
2.2%
11366 2
 
2.2%
472861 2
 
2.2%
Other values (60) 63
69.2%
ValueCountFrequency (%)
10023 2
 
2.2%
10225 1
 
1.1%
10258 1
 
1.1%
10267 1
 
1.1%
10320 1
 
1.1%
10390 1
 
1.1%
10403 1
 
1.1%
10807 2
 
2.2%
10824 1
 
1.1%
10867 6
6.6%
ValueCountFrequency (%)
487914 1
1.1%
487862 1
1.1%
487030 1
1.1%
482150 1
1.1%
482060 1
1.1%
480080 1
1.1%
476801 1
1.1%
472861 2
2.2%
471033 1
1.1%
471010 1
1.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.509798
Minimum36.993519
Maximum38.057149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-11T06:00:00.802116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.993519
5-th percentile37.105634
Q137.296658
median37.485177
Q337.745357
95-th percentile37.870507
Maximum38.057149
Range1.0636302
Interquartile range (IQR)0.44869935

Descriptive statistics

Standard deviation0.25716246
Coefficient of variation (CV)0.0068558743
Kurtosis-0.96307561
Mean37.509798
Median Absolute Deviation (MAD)0.22415931
Skewness-0.095089149
Sum3413.3916
Variance0.066132529
MonotonicityNot monotonic
2023-12-11T06:00:00.966705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7525633947 6
 
6.6%
37.4019077284 5
 
5.5%
37.705956869 2
 
2.2%
37.2519884305 2
 
2.2%
37.2536041158 2
 
2.2%
37.8503619024 2
 
2.2%
37.4851765568 2
 
2.2%
37.5375091491 2
 
2.2%
37.882798194 2
 
2.2%
37.7526210329 2
 
2.2%
Other values (62) 64
70.3%
ValueCountFrequency (%)
36.993518957 1
1.1%
36.9973130579 1
1.1%
37.0038518308 1
1.1%
37.0269120822 1
1.1%
37.0764325856 1
1.1%
37.1348356794 1
1.1%
37.1396942904 1
1.1%
37.140532408 1
1.1%
37.172940262 1
1.1%
37.1987736102 1
1.1%
ValueCountFrequency (%)
38.0571491701 1
1.1%
37.9427111276 1
1.1%
37.903690838 1
1.1%
37.882798194 2
2.2%
37.8582156649 1
1.1%
37.852415817 1
1.1%
37.8503619024 2
2.2%
37.8473034775 1
1.1%
37.8447539212 1
1.1%
37.8336416588 1
1.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.96902
Minimum126.5634
Maximum127.6362
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-11T06:00:01.149019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5634
5-th percentile126.73635
Q1126.78415
median126.92657
Q3127.10725
95-th percentile127.32576
Maximum127.6362
Range1.0727973
Interquartile range (IQR)0.32309887

Descriptive statistics

Standard deviation0.22202652
Coefficient of variation (CV)0.0017486668
Kurtosis0.66771182
Mean126.96902
Median Absolute Deviation (MAD)0.1521064
Skewness0.84656243
Sum11554.181
Variance0.049295774
MonotonicityNot monotonic
2023-12-11T06:00:01.324139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7425676998 6
 
6.6%
126.7711057595 5
 
5.5%
126.5634006056 2
 
2.2%
126.9916216187 2
 
2.2%
126.9630359183 2
 
2.2%
126.9016910791 2
 
2.2%
126.784461849 2
 
2.2%
126.8179358284 2
 
2.2%
127.060069678 2
 
2.2%
126.7794342597 2
 
2.2%
Other values (62) 64
70.3%
ValueCountFrequency (%)
126.5634006056 2
 
2.2%
126.6599292183 1
 
1.1%
126.7212423267 1
 
1.1%
126.7308558651 1
 
1.1%
126.7418539878 1
 
1.1%
126.7425676998 6
6.6%
126.7528659622 1
 
1.1%
126.758155186 1
 
1.1%
126.7711057595 5
5.5%
126.7744646435 1
 
1.1%
ValueCountFrequency (%)
127.6361979459 1
1.1%
127.6352220696 1
1.1%
127.5152687261 1
1.1%
127.5016755201 1
1.1%
127.3852179996 1
1.1%
127.2662959652 1
1.1%
127.2579774714 1
1.1%
127.2573923852 1
1.1%
127.2345276334 2
2.2%
127.2209085791 1
1.1%

Interactions

2023-12-11T05:59:55.835865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:53.797594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.294158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.780644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:55.284372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:55.938696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:53.897171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.395134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.894493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:55.392571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:56.023458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:53.991509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.493300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.987974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:55.508700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:56.101450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.103145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.579868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:55.084105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:55.625093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:56.181038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.193481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:54.669205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:55.188047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:59:55.724684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:00:01.449194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.8200.5431.0001.0001.0000.8500.9640.945
사업장명1.0001.0000.9830.0001.0000.9910.9920.9350.9920.993
인허가일자0.8200.9831.0000.2250.9230.9800.9640.8020.3450.276
영업상태명0.5430.0000.2251.000NaN0.0000.0000.1430.2280.463
폐업일자1.0001.0000.923NaN1.0001.0001.0000.3950.8870.107
소재지도로명주소1.0000.9910.9800.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0000.9920.9640.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.8500.9350.8020.1430.3951.0001.0001.0000.3410.613
WGS84위도0.9640.9920.3450.2280.8871.0001.0000.3411.0000.827
WGS84경도0.9450.9930.2760.4630.1071.0001.0000.6130.8271.000
2023-12-11T06:00:01.583029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명
영업상태명1.0000.361
시군명0.3611.000
2023-12-11T06:00:01.674519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자폐업일자소재지우편번호WGS84위도WGS84경도시군명영업상태명
인허가일자1.0000.126-0.5900.236-0.3700.4260.193
폐업일자0.1261.000-0.4030.719-0.2260.9051.000
소재지우편번호-0.590-0.4031.000-0.3100.5620.5390.245
WGS84위도0.2360.719-0.3101.000-0.1280.7020.163
WGS84경도-0.370-0.2260.562-0.1281.0000.6400.338
시군명0.4260.9050.5390.7020.6401.0000.361
영업상태명0.1931.0000.2450.1630.3380.3611.000

Missing values

2023-12-11T05:59:56.295456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T05:59:56.442988image/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.
2023-12-11T05:59:56.574243image/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

시군명사업장명인허가일자영업상태명폐업일자업체유형명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군(주)진흥고속20131129운영중<NA>시내버스경기도 가평군 가평읍 가화로 51경기도 가평군 가평읍 대곡리 168-9번지1242037.824569127.515269
1고양시남정여객20180518운영중<NA>시내버스경기도 고양시 일산동구 성현로431번길 40 (문봉동)경기도 고양시 일산동구 문봉동 82-2번지1025837.698625126.83256
2고양시고양교통(주)20041230운영중<NA>시내버스경기도 고양시 일산동구무궁화로 385-11(식사동)경기도 고양시 일산동구 식사동 825-12번지41005037.679097126.801295
3고양시(주)뉴그랜드관광20180504운영중<NA>시내버스경기도 고양시 일산동구 중앙로 1233, 현대타운빌 433호 (장항동)경기도 고양시 일산동구 장항동 848-1번지 현대타운빌1040337.656407126.774465
4고양시명성운수(주)19770610운영중<NA>시내버스경기도 고양시 일산서구대화로 97(대화동)경기도 고양시 일산서구 대화동 1478번지41180237.669243126.730856
5고양시(주)가온누리엠20090720운영중<NA>시내버스경기도 고양시 일산서구 킨텍스로 217-59 (대화동, 제2킨텍스)경기도 고양시 일산서구 대화동 2700번지1039037.664935126.741854
6고양시일산엠버스20120516운영중<NA>시내버스경기도 고양시 일산동구 동국로 169 (식사동)경기도 고양시 일산동구 식사동 733-4번지1032037.685406126.807706
7고양시서현운수(주)20130625운영중<NA>시내버스경기도 고양시 덕양구 보광로 192-16 (벽제동)경기도 고양시 덕양구 벽제동 575-9번지 외 3필지1026737.731481126.911972
8고양시신성운수(주)20130625폐업 등20160628시내버스경기도 고양시 일산서구 경의로789번길 3 (대화동, 신성교통)경기도 고양시 일산서구 대화동 24-1번지1022537.688097126.758155
9과천시주식회사 과천여객20160202운영중<NA>시내버스경기도 과천시 문원로 110 (문원동)경기도 과천시 문원동 142번지1382737.424471127.007717
시군명사업장명인허가일자영업상태명폐업일자업체유형명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
81포천시선진고속(주)20100201운영중<NA>시내버스경기도 포천시호국로883번길 9(설운동)경기도 포천시 설운동 70-3번지48703037.844754127.157645
82포천시선진시내버스(주)20050627운영중<NA>시내버스경기도 포천시 이동면 화동로 2411경기도 포천시 이동면 도평리 166-5번지48786238.057149127.385218
83포천시(주)포천교통19980518운영중<NA>시내버스경기도 포천시 신북면 신평로 192경기도 포천시 신북면 신평리 319번지48791437.942711127.220909
84하남시하남시내버스(주)20040915운영중<NA>시내버스<NA>경기도 하남시 상산곡동 46번지 공영차고지 1단지46526037.498828127.234528
85하남시(주)경기상운20040108운영중<NA>시내버스경기도 하남시 하남대로284번길 59 (상산곡동)경기도 하남시 상산곡동 46번지46526037.498828127.234528
86화성시경진여객운수㈜19980724운영중<NA>시내버스경기도 화성시 안녕길 58 (안녕동)경기도 화성시 안녕동 188-355번지1832637.20244126.991449
87화성시(주)화성운수20130412운영중<NA>시내버스경기도 화성시 향남읍 푸른들판로 324-4경기도 화성시 향남읍 장짐리 85-28번지44592537.139694126.901768
88화성시(주)화성여객20150130운영중<NA>시내버스경기도 화성시 안녕남로 111 (안녕동)경기도 화성시 안녕동 157-1번지1836437.198774126.995842
89화성시(주)화성운수20080822운영중<NA>시내버스경기도 화성시 향남읍 푸른들판로 324-10경기도 화성시 향남읍 장짐리 85-28번지 화성운수 차고지 및 사무실44592537.140532126.901935
90화성시제부여객㈜19960409운영중<NA>시내버스경기도 화성시 서신면 해양공단로 17경기도 화성시 서신면 송교리 372-2번지44588337.17294126.659929