Overview

Dataset statistics

Number of variables10
Number of observations177
Missing cells9
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.3 KiB
Average record size in memory82.7 B

Variable types

Categorical2
DateTime2
Text4
Numeric2

Dataset

Description부천시 숙박업에 대한 업소명, 신고일자, 소새지 주소(지번,도로명), 영업장 면적, 소재지전화번호 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15076966/fileData.do

Alerts

우편번호(도로명) is highly overall correlated with 책임읍면동명High correlation
책임읍면동명 is highly overall correlated with 우편번호(도로명)High correlation
업종명 is highly imbalanced (73.4%)Imbalance
영업장면적 has 9 (5.1%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique
영업소 주소(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:55:30.556405
Analysis finished2023-12-12 03:55:32.503983
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
숙박업(일반)
169 
숙박업(생활)
 
8

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
숙박업(일반) 169
95.5%
숙박업(생활) 8
 
4.5%

Length

2023-12-12T12:55:32.607206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:55:32.790130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 169
95.5%
숙박업(생활 8
 
4.5%

신고일자
Date

Distinct156
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1971-08-12 00:00:00
Maximum2023-01-31 00:00:00
2023-12-12T12:55:32.997043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:55:33.243344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

Distinct174
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T12:55:33.716116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.9830508
Min length1

Characters and Unicode

Total characters882
Distinct characters209
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)96.6%

Sample

1st row신신모텔
2nd row동성여인숙
3rd row38리빙텔
4th row안성여인숙
5th row경인장여관
ValueCountFrequency (%)
돈키호텔 2
 
1.1%
썸모텔 2
 
1.1%
리베라여관 2
 
1.1%
365st 1
 
0.5%
어반후스 1
 
0.5%
마시모 1
 
0.5%
모텔 1
 
0.5%
노블레스 1
 
0.5%
나인9 1
 
0.5%
신신모텔 1
 
0.5%
Other values (171) 171
92.9%
2023-12-12T12:55:34.331826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 94
 
10.7%
모 57
 
6.5%
여 55
 
6.2%
호 41
 
4.6%
관 32
 
3.6%
인 29
 
3.3%
스 27
 
3.1%
숙 26
 
2.9%
장 20
 
2.3%
이 17
 
1.9%
Other values (199) 484
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 777
88.1%
Uppercase Letter 41
 
4.6%
Decimal Number 17
 
1.9%
Open Punctuation 15
 
1.7%
Close Punctuation 15
 
1.7%
Space Separator 7
 
0.8%
Lowercase Letter 6
 
0.7%
Other Punctuation 3
 
0.3%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 94
 
12.1%
모 57
 
7.3%
여 55
 
7.1%
호 41
 
5.3%
관 32
 
4.1%
인 29
 
3.7%
스 27
 
3.5%
숙 26
 
3.3%
장 20
 
2.6%
이 17
 
2.2%
Other values (164) 379
48.8%
Uppercase Letter
ValueCountFrequency (%)
L 5
12.2%
E 5
12.2%
O 5
12.2%
T 5
12.2%
H 5
12.2%
A 4
9.8%
Z 2
 
4.9%
C 2
 
4.9%
R 2
 
4.9%
S 2
 
4.9%
Other values (4) 4
9.8%
Decimal Number
ValueCountFrequency (%)
3 5
29.4%
2 4
23.5%
9 1
 
5.9%
0 1
 
5.9%
1 1
 
5.9%
5 1
 
5.9%
6 1
 
5.9%
7 1
 
5.9%
4 1
 
5.9%
8 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
t 2
33.3%
l 1
16.7%
e 1
16.7%
o 1
16.7%
s 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
& 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 777
88.1%
Common 58
 
6.6%
Latin 47
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 94
 
12.1%
모 57
 
7.3%
여 55
 
7.1%
호 41
 
5.3%
관 32
 
4.1%
인 29
 
3.7%
스 27
 
3.5%
숙 26
 
3.3%
장 20
 
2.6%
이 17
 
2.2%
Other values (164) 379
48.8%
Latin
ValueCountFrequency (%)
L 5
10.6%
E 5
10.6%
O 5
10.6%
T 5
10.6%
H 5
10.6%
A 4
 
8.5%
Z 2
 
4.3%
C 2
 
4.3%
t 2
 
4.3%
R 2
 
4.3%
Other values (9) 10
21.3%
Common
ValueCountFrequency (%)
( 15
25.9%
) 15
25.9%
7
12.1%
3 5
 
8.6%
2 4
 
6.9%
. 2
 
3.4%
9 1
 
1.7%
0 1
 
1.7%
1 1
 
1.7%
5 1
 
1.7%
Other values (6) 6
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 777
88.1%
ASCII 105
 
11.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 94
 
12.1%
모 57
 
7.3%
여 55
 
7.1%
호 41
 
5.3%
관 32
 
4.1%
인 29
 
3.7%
스 27
 
3.5%
숙 26
 
3.3%
장 20
 
2.6%
이 17
 
2.2%
Other values (164) 379
48.8%
ASCII
ValueCountFrequency (%)
( 15
14.3%
) 15
14.3%
7
 
6.7%
L 5
 
4.8%
E 5
 
4.8%
O 5
 
4.8%
T 5
 
4.8%
H 5
 
4.8%
3 5
 
4.8%
A 4
 
3.8%
Other values (25) 34
32.4%

영업소 주소(도로명)
Text

UNIQUE 

Distinct177
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T12:55:34.799129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length25.220339
Min length19

Characters and Unicode

Total characters4464
Distinct characters81
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)100.0%

Sample

1st row경기도 부천시 경인로234번길 19 (심곡본동)
2nd row경기도 부천시 경인옛로22번길 4 (소사본동)
3rd row경기도 부천시 부일로496번길 18 (심곡동)
4th row경기도 부천시 부일로 440-11 (심곡동)
5th row경기도 부천시 경인로194번길 17 (심곡본동)
ValueCountFrequency (%)
경기도 177
19.2%
부천시 177
19.2%
심곡동 81
 
8.8%
상동 19
 
2.1%
원종동 17
 
1.8%
부천로6번길 15
 
1.6%
심곡본동 15
 
1.6%
부일로 14
 
1.5%
소사본동 13
 
1.4%
역곡동 10
 
1.1%
Other values (204) 384
41.6%
2023-12-12T12:55:35.499527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
745
 
16.7%
부 254
 
5.7%
천 220
 
4.9%
경 192
 
4.3%
도 180
 
4.0%
동 178
 
4.0%
( 177
 
4.0%
) 177
 
4.0%
기 177
 
4.0%
로 177
 
4.0%
Other values (71) 1987
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2479
55.5%
Decimal Number 790
 
17.7%
Space Separator 745
 
16.7%
Open Punctuation 177
 
4.0%
Close Punctuation 177
 
4.0%
Other Punctuation 54
 
1.2%
Dash Punctuation 36
 
0.8%
Math Symbol 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 254
10.2%
천 220
 
8.9%
경 192
 
7.7%
도 180
 
7.3%
동 178
 
7.2%
기 177
 
7.1%
로 177
 
7.1%
시 177
 
7.1%
길 161
 
6.5%
번 150
 
6.1%
Other values (54) 613
24.7%
Decimal Number
ValueCountFrequency (%)
1 139
17.6%
2 132
16.7%
4 98
12.4%
3 90
11.4%
7 78
9.9%
6 78
9.9%
5 50
 
6.3%
9 50
 
6.3%
0 40
 
5.1%
8 35
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 53
98.1%
. 1
 
1.9%
Space Separator
ValueCountFrequency (%)
745
100.0%
Open Punctuation
ValueCountFrequency (%)
( 177
100.0%
Close Punctuation
ValueCountFrequency (%)
) 177
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2479
55.5%
Common 1985
44.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 254
10.2%
천 220
 
8.9%
경 192
 
7.7%
도 180
 
7.3%
동 178
 
7.2%
기 177
 
7.1%
로 177
 
7.1%
시 177
 
7.1%
길 161
 
6.5%
번 150
 
6.1%
Other values (54) 613
24.7%
Common
ValueCountFrequency (%)
745
37.5%
( 177
 
8.9%
) 177
 
8.9%
1 139
 
7.0%
2 132
 
6.6%
4 98
 
4.9%
3 90
 
4.5%
7 78
 
3.9%
6 78
 
3.9%
, 53
 
2.7%
Other values (7) 218
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2479
55.5%
ASCII 1985
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
745
37.5%
( 177
 
8.9%
) 177
 
8.9%
1 139
 
7.0%
2 132
 
6.6%
4 98
 
4.9%
3 90
 
4.5%
7 78
 
3.9%
6 78
 
3.9%
, 53
 
2.7%
Other values (7) 218
 
11.0%
Hangul
ValueCountFrequency (%)
부 254
10.2%
천 220
 
8.9%
경 192
 
7.7%
도 180
 
7.3%
동 178
 
7.2%
기 177
 
7.1%
로 177
 
7.1%
시 177
 
7.1%
길 161
 
6.5%
번 150
 
6.1%
Other values (54) 613
24.7%

우편번호(도로명)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14618.701
Minimum14400
Maximum14755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:55:35.722901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14400
5-th percentile14420
Q114598
median14641
Q314644
95-th percentile14730
Maximum14755
Range355
Interquartile range (IQR)46

Descriptive statistics

Standard deviation86.386458
Coefficient of variation (CV)0.0059093117
Kurtosis0.77687793
Mean14618.701
Median Absolute Deviation (MAD)18
Skewness-1.1142657
Sum2587510
Variance7462.6201
MonotonicityNot monotonic
2023-12-12T12:55:35.943722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
14643 25
 
14.1%
14636 20
 
11.3%
14644 18
 
10.2%
14420 15
 
8.5%
14637 8
 
4.5%
14543 7
 
4.0%
14674 6
 
3.4%
14754 5
 
2.8%
14704 5
 
2.8%
14676 5
 
2.8%
Other values (31) 63
35.6%
ValueCountFrequency (%)
14400 1
 
0.6%
14420 15
8.5%
14424 3
 
1.7%
14437 1
 
0.6%
14517 1
 
0.6%
14525 1
 
0.6%
14542 3
 
1.7%
14543 7
4.0%
14544 2
 
1.1%
14547 4
 
2.3%
ValueCountFrequency (%)
14755 1
 
0.6%
14754 5
2.8%
14752 2
 
1.1%
14750 1
 
0.6%
14725 2
 
1.1%
14717 1
 
0.6%
14713 1
 
0.6%
14712 2
 
1.1%
14711 3
1.7%
14710 3
1.7%

영업소 주소(지번)
Text

UNIQUE 

Distinct177
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T12:55:36.632566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length19.519774
Min length15

Characters and Unicode

Total characters3455
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)100.0%

Sample

1st row경기도 부천시 심곡본동 677-5
2nd row경기도 부천시 소사본동 76
3rd row경기도 부천시 심곡동 171-29
4th row경기도 부천시 심곡동 396-15
5th row경기도 부천시 심곡본동 591 ,591-10,11, 592-14,15
ValueCountFrequency (%)
경기도 177
23.4%
부천시 177
23.4%
심곡동 85
 
11.2%
상동 19
 
2.5%
원종동 18
 
2.4%
심곡본동 15
 
2.0%
소사본동 13
 
1.7%
역곡동 10
 
1.3%
중동 6
 
0.8%
괴안동 5
 
0.7%
Other values (218) 232
30.6%
2023-12-12T12:55:37.520975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
757
21.9%
1 218
 
6.3%
- 183
 
5.3%
도 179
 
5.2%
부 178
 
5.2%
동 178
 
5.2%
경 177
 
5.1%
천 177
 
5.1%
시 177
 
5.1%
기 177
 
5.1%
Other values (42) 1054
30.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1643
47.6%
Decimal Number 840
24.3%
Space Separator 757
21.9%
Dash Punctuation 183
 
5.3%
Other Punctuation 25
 
0.7%
Math Symbol 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 179
10.9%
부 178
10.8%
동 178
10.8%
경 177
10.8%
천 177
10.8%
시 177
10.8%
기 177
10.8%
곡 110
6.7%
심 100
6.1%
본 28
 
1.7%
Other values (27) 162
9.9%
Decimal Number
ValueCountFrequency (%)
1 218
26.0%
2 107
12.7%
3 102
12.1%
7 77
 
9.2%
5 71
 
8.5%
4 66
 
7.9%
8 56
 
6.7%
6 50
 
6.0%
9 49
 
5.8%
0 44
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 24
96.0%
. 1
 
4.0%
Space Separator
ValueCountFrequency (%)
757
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1812
52.4%
Hangul 1643
47.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 179
10.9%
부 178
10.8%
동 178
10.8%
경 177
10.8%
천 177
10.8%
시 177
10.8%
기 177
10.8%
곡 110
6.7%
심 100
6.1%
본 28
 
1.7%
Other values (27) 162
9.9%
Common
ValueCountFrequency (%)
757
41.8%
1 218
 
12.0%
- 183
 
10.1%
2 107
 
5.9%
3 102
 
5.6%
7 77
 
4.2%
5 71
 
3.9%
4 66
 
3.6%
8 56
 
3.1%
6 50
 
2.8%
Other values (5) 125
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1812
52.4%
Hangul 1643
47.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
757
41.8%
1 218
 
12.0%
- 183
 
10.1%
2 107
 
5.9%
3 102
 
5.6%
7 77
 
4.2%
5 71
 
3.9%
4 66
 
3.6%
8 56
 
3.1%
6 50
 
2.8%
Other values (5) 125
 
6.9%
Hangul
ValueCountFrequency (%)
도 179
10.9%
부 178
10.8%
동 178
10.8%
경 177
10.8%
천 177
10.8%
시 177
10.8%
기 177
10.8%
곡 110
6.7%
심 100
6.1%
본 28
 
1.7%
Other values (27) 162
9.9%

영업장면적
Real number (ℝ)

MISSING 

Distinct166
Distinct (%)98.8%
Missing9
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean862.11881
Minimum40.8
Maximum5613.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:55:37.758539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40.8
5-th percentile203.906
Q1358.9275
median550.705
Q3921.64
95-th percentile2334.3795
Maximum5613.66
Range5572.86
Interquartile range (IQR)562.7125

Descriptive statistics

Standard deviation922.95173
Coefficient of variation (CV)1.0705621
Kurtosis10.259093
Mean862.11881
Median Absolute Deviation (MAD)243.84
Skewness2.955346
Sum144835.96
Variance851839.9
MonotonicityNot monotonic
2023-12-12T12:55:37.997768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
481.06 2
 
1.1%
330.0 2
 
1.1%
482.95 1
 
0.6%
104.9 1
 
0.6%
852.24 1
 
0.6%
305.44 1
 
0.6%
1298.29 1
 
0.6%
396.0 1
 
0.6%
264.0 1
 
0.6%
221.1 1
 
0.6%
Other values (156) 156
88.1%
(Missing) 9
 
5.1%
ValueCountFrequency (%)
40.8 1
0.6%
66.4 1
0.6%
104.9 1
0.6%
120.96 1
0.6%
132.0 1
0.6%
149.3 1
0.6%
170.3 1
0.6%
184.73 1
0.6%
198.6 1
0.6%
213.76 1
0.6%
ValueCountFrequency (%)
5613.66 1
0.6%
5374.97 1
0.6%
5087.26 1
0.6%
4081.8 1
0.6%
3810.24 1
0.6%
3489.68 1
0.6%
3233.17 1
0.6%
2672.94 1
0.6%
2374.43 1
0.6%
2260.0 1
0.6%

소재지전화
Text

Distinct172
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T12:55:38.411369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.011299
Min length12

Characters and Unicode

Total characters2126
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)96.6%

Sample

1st row032-651-6342
2nd row032-346-9955
3rd row032-613-2266
4th row032-668-4420
5th row032-000-0000
ValueCountFrequency (%)
032-000-0000 6
 
3.4%
032-652-9750 1
 
0.6%
032-329-3333 1
 
0.6%
032-651-4764 1
 
0.6%
032-665-0353 1
 
0.6%
032-671-8833 1
 
0.6%
032-348-0710 1
 
0.6%
032-653-2261 1
 
0.6%
032-657-2130 1
 
0.6%
032-326-2255 1
 
0.6%
Other values (162) 162
91.5%
2023-12-12T12:55:39.059310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 354
16.7%
3 340
16.0%
0 313
14.7%
2 277
13.0%
6 229
10.8%
5 142
6.7%
4 117
 
5.5%
1 108
 
5.1%
7 100
 
4.7%
8 81
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1772
83.3%
Dash Punctuation 354
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 340
19.2%
0 313
17.7%
2 277
15.6%
6 229
12.9%
5 142
8.0%
4 117
 
6.6%
1 108
 
6.1%
7 100
 
5.6%
8 81
 
4.6%
9 65
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 354
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2126
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 354
16.7%
3 340
16.0%
0 313
14.7%
2 277
13.0%
6 229
10.8%
5 142
6.7%
4 117
 
5.5%
1 108
 
5.1%
7 100
 
4.7%
8 81
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 354
16.7%
3 340
16.0%
0 313
14.7%
2 277
13.0%
6 229
10.8%
5 142
6.7%
4 117
 
5.5%
1 108
 
5.1%
7 100
 
4.7%
8 81
 
3.8%

영업자시작일
Date

Distinct173
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1984-10-24 00:00:00
Maximum2023-05-17 00:00:00
2023-12-12T12:55:39.280672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:55:39.519592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

책임읍면동명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
심곡동
86 
오정동
20 
대산동
15 
상동
15 
소사본동
13 
Other values (4)
28 

Length

Max length4
Median length3
Mean length2.9661017
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대산동
2nd row소사본동
3rd row심곡동
4th row심곡동
5th row대산동

Common Values

ValueCountFrequency (%)
심곡동 86
48.6%
오정동 20
 
11.3%
대산동 15
 
8.5%
상동 15
 
8.5%
소사본동 13
 
7.3%
부천동 12
 
6.8%
신중동 7
 
4.0%
범안동 5
 
2.8%
중동 4
 
2.3%

Length

2023-12-12T12:55:39.753437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:55:39.924819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
심곡동 86
48.6%
오정동 20
 
11.3%
대산동 15
 
8.5%
상동 15
 
8.5%
소사본동 13
 
7.3%
부천동 12
 
6.8%
신중동 7
 
4.0%
범안동 5
 
2.8%
중동 4
 
2.3%

Interactions

2023-12-12T12:55:31.391000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:55:31.092844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:55:31.534974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:55:31.239241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:55:40.076905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명우편번호(도로명)영업장면적책임읍면동명
업종명1.0000.0000.0000.000
우편번호(도로명)0.0001.0000.4770.961
영업장면적0.0000.4771.0000.639
책임읍면동명0.0000.9610.6391.000
2023-12-12T12:55:40.226757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
책임읍면동명업종명
책임읍면동명1.0000.000
업종명0.0001.000
2023-12-12T12:55:40.363784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호(도로명)영업장면적업종명책임읍면동명
우편번호(도로명)1.000-0.2360.0000.672
영업장면적-0.2361.0000.0000.251
업종명0.0000.0001.0000.000
책임읍면동명0.6720.2510.0001.000

Missing values

2023-12-12T12:55:31.739306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:55:32.399481image/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.

Sample

업종명신고일자업소명영업소 주소(도로명)우편번호(도로명)영업소 주소(지번)영업장면적소재지전화영업자시작일책임읍면동명
0숙박업(일반)1971-08-12신신모텔경기도 부천시 경인로234번길 19 (심곡본동)14713경기도 부천시 심곡본동 677-5318.74032-651-63422019-11-06대산동
1숙박업(일반)1980-06-05동성여인숙경기도 부천시 경인옛로22번길 4 (소사본동)14704경기도 부천시 소사본동 76353.42032-346-99552012-05-14소사본동
2숙박업(일반)1980-09-1738리빙텔경기도 부천시 부일로496번길 18 (심곡동)14644경기도 부천시 심곡동 171-29314.6032-613-22662016-12-16심곡동
3숙박업(일반)1980-05-27안성여인숙경기도 부천시 부일로 440-11 (심곡동)14636경기도 부천시 심곡동 396-1540.8032-668-44201984-10-24심곡동
4숙박업(일반)1981-10-22경인장여관경기도 부천시 경인로194번길 17 (심곡본동)14712경기도 부천시 심곡본동 591 ,591-10,11, 592-14,15548.36032-000-00001999-03-22대산동
5숙박업(일반)1981-06-26썸모텔경기도 부천시 부일로 465-2 (심곡동)14634경기도 부천시 심곡동 176-6612.0032-652-64012017-05-12심곡동
6숙박업(일반)1981-12-22반도장여관경기도 부천시 조마루로386번길 24 (원미동)14566경기도 부천시 원미동 73-7492.11032-667-28112007-07-02부천동
7숙박업(일반)1982-11-17광명여관경기도 부천시 경인로194번길 22 (심곡본동)14712경기도 부천시 심곡본동 593-15120.96032-655-54312006-11-08대산동
8숙박업(일반)1982-11-17약대모텔경기도 부천시 수도로74번길 7, 가동 2-3층 (도당동)14517경기도 부천시 도당동 214-3 2-3층 가동400.0032-675-98652022-09-02신중동
9숙박업(일반)1982-12-13보림장여관경기도 부천시 부천로90번길 50 (원미동)14572경기도 부천시 원미동 147-13252.0032-652-88052014-06-24심곡동
업종명신고일자업소명영업소 주소(도로명)우편번호(도로명)영업소 주소(지번)영업장면적소재지전화영업자시작일책임읍면동명
167숙박업(일반)2022-10-07명성여인숙경기도 부천시 부일로 444-14 (심곡동)14636경기도 부천시 심곡동 396-7243.7032-653-39692022-10-07심곡동
168숙박업(일반)2023-01-31애플경기도 부천시 신흥로22번길 54, 1층일부, 2층, 3층 (심곡동)14636경기도 부천시 심곡동 388-12 1층일부, 2층, 3층348.79032-000-00002023-01-31심곡동
169숙박업(생활)1984-05-24소사빌경기도 부천시 호현로 475 (소사본동)14755경기도 부천시 소사본동 131-2486.18032-343-77482007-07-27소사본동
170숙박업(생활)1988-07-04창성여인숙경기도 부천시 호현로474번길 14, 1~2층 (소사본동)14705경기도 부천시 소사본동 77-3 ,1~2층490.32032-349-61102005-06-13소사본동
171숙박업(생활)1990-01-22어반후스경기도 부천시 부천로6번길 56 (심곡동,, 142-6)14643경기도 부천시 심곡동 143-3 , 142-61143.19032-667-58142016-03-28심곡동
172숙박업(생활)2001-03-13365st경기도 부천시 부흥로374번길 25-6 (심곡동)14630경기도 부천시 심곡동 365-5519.67032-611-88302005-05-30심곡동
173숙박업(생활)2002-10-29카프리경기도 부천시 성무로 7 (심곡본동)14752경기도 부천시 심곡본동 746-2945.0032-679-00632017-03-30대산동
174숙박업(생활)2012-11-27시티텔지엠경기도 부천시 부천로1번길 38, 1-6층 (심곡동)14637경기도 부천시 심곡동 386-8 1-6층920.72070-7361-91782012-11-27심곡동
175숙박업(생활)2013-09-06드림하우스경기도 부천시 원종로65번길 14-23 (원종동, 2,3,4층)14420경기도 부천시 원종동 275-9 2,3,4층460.08032-673-68982018-04-12오정동
176숙박업(생활)2013-02-01스타빌경기도 부천시 원미로17번길 10, 1-5층 (심곡동)14643경기도 부천시 심곡동 129-13 1-5층764.36070-7320-10002013-02-01심곡동